Code.ipynb

{
  "cells": [
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "ccfa5f74",
      "metadata": {
        "id": "ccfa5f74"
      },
      "outputs": [],
      "source": [
        "import pandas as pd\n",
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "6d6a707d",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "6d6a707d",
        "outputId": "49920112-4da9-43f0-de52-5649e1e03a71"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                  Date   Sample_ID    MG unprocessed    MG retained pairs   \\\n",
              "0   2010-10-04 00:00:00        A01           17531630             16368148   \n",
              "1   2011-01-25 00:00:00        A02           14699402             13108258   \n",
              "2   2011-03-21 00:00:00        D37           35999747             32911158   \n",
              "3   2011-03-29 00:00:00        D02           34135175             27721744   \n",
              "4   2011-04-05 00:00:00        D39           28908243             26605828   \n",
              "5   2011-04-14 00:00:00        D24           29187268             27401321   \n",
              "6   2011-04-21 00:00:00        D25           25320222             20487745   \n",
              "7   2011-04-29 00:00:00        D35           30371838             27587583   \n",
              "8   2011-05-06 00:00:00        D46           28122705             25044633   \n",
              "9   2011-05-13 00:00:00        D13           31173943             29336922   \n",
              "10  2011-05-20 00:00:00        D40           25651909             24085668   \n",
              "11  2011-05-27 00:00:00        D33           30235782             28307886   \n",
              "12  2011-06-03 00:00:00        D06           30216637             26954409   \n",
              "13  2011-06-09 00:00:00        D27           27497422             25777061   \n",
              "14  2011-06-17 00:00:00        D42           27303250             25503950   \n",
              "15  2011-06-24 00:00:00        D03           32347395             29220419   \n",
              "16  2011-07-01 00:00:00        D47           30109054             27730630   \n",
              "17  2011-07-08 00:00:00        D18           23391679             22164878   \n",
              "18  2011-08-05 00:00:00        D45           29930665             27829830   \n",
              "19  2011-08-11 00:00:00        D51           29852842             26901508   \n",
              "20  2011-08-19 00:00:00        D43           26075473             24281057   \n",
              "21  2011-08-29 00:00:00        D34           30403109             28058664   \n",
              "22  2011-09-05 00:00:00        D30           30532662             28718715   \n",
              "23  2011-09-12 00:00:00        D04           29014224             25778552   \n",
              "24  2011-09-19 00:00:00        D31           25456037             23744583   \n",
              "25  2011-09-28 00:00:00        D29           29839175             27199081   \n",
              "26  2011-10-05 00:00:00        D49           29042305             26641829   \n",
              "27  2011-10-12 00:00:00        D32           28460125             26905139   \n",
              "28  2011-11-02 00:00:00        D23           23448618             18851501   \n",
              "29  2011-11-07 00:00:00        D44           27963482             24897807   \n",
              "30  2011-11-16 00:00:00        D20           32139021             30421843   \n",
              "31  2011-11-23 00:00:00        D15           26973299             24536053   \n",
              "32  2011-11-29 00:00:00        D05           25621580             22949103   \n",
              "33  2011-12-21 00:00:00        D28           29329592             27574163   \n",
              "34  2011-12-28 00:00:00        D09           31138147             25898148   \n",
              "35  2012-01-03 00:00:00        D38           24493806             22681193   \n",
              "36  2012-01-11 00:00:00        D36           34928806             32014419   \n",
              "37  2012-01-19 00:00:00        D12           26256782             24765672   \n",
              "38  2012-01-25 00:00:00        D10           32576299             28822117   \n",
              "39  2012-02-01 00:00:00        D14           26995145             22067691   \n",
              "40  2012-02-08 00:00:00        D08           33462713             29590993   \n",
              "41  2012-02-14 00:00:00        D26           29242844             27118676   \n",
              "42  2012-02-23 00:00:00        D21           24350474             22754752   \n",
              "43  2012-02-29 00:00:00        D19           32574065             28288700   \n",
              "44  2012-03-08 00:00:00        D17           23876138             22226625   \n",
              "45  2012-03-14 00:00:00        D41           30626165             28490276   \n",
              "46  2012-03-22 00:00:00        D11           29495784             27691057   \n",
              "47  2012-03-28 00:00:00        D16           28186198             26162520   \n",
              "48  2012-04-04 00:00:00        D07           21699617             15940878   \n",
              "49  2012-04-10 00:00:00        D22           33671265             30670757   \n",
              "50  2012-04-17 00:00:00        D01           32692858             27975133   \n",
              "51  2012-04-25 00:00:00        D50           24359112             22277277   \n",
              "52  2012-05-03 00:00:00        D48           27267336             25359794   \n",
              "53               Total          NaN        1504179064           1362404347   \n",
              "54              Average         NaN          28380737             25705742   \n",
              "55   Standard deviation         NaN           4025168              3847016   \n",
              "\n",
              "     MG retained singles   MG retained combined reads   MT unprocessed  \\\n",
              "0                 1078317                3.381461e+07         56764165   \n",
              "1                 1199766                2.741628e+07         16493393   \n",
              "2                 2199347                6.802166e+07         35975301   \n",
              "3                 2837683                5.828117e+07         33912215   \n",
              "4                 1673538                5.488519e+07         38592454   \n",
              "5                 1354513                5.615716e+07         36395674   \n",
              "6                 4083256                4.505875e+07         33954127   \n",
              "7                 1797893                5.697306e+07         29681622   \n",
              "8                 2528946                5.261821e+07         34116436   \n",
              "9                 1467456                6.014130e+07         35894482   \n",
              "10                1018577                4.918991e+07         27707752   \n",
              "11                1506824                5.812260e+07         27369514   \n",
              "12                1576187                5.548500e+07         32430876   \n",
              "13                1306125                5.286025e+07         30331588   \n",
              "14                1313167                5.232107e+07         34544359   \n",
              "15                1797971                6.023881e+07         32699565   \n",
              "16                1936737                5.739800e+07         36766788   \n",
              "17                1066058                4.539581e+07         31924022   \n",
              "18                1644918                5.730458e+07         35378306   \n",
              "19                2115968                5.591898e+07         44174409   \n",
              "20                1444335                5.000645e+07         27171859   \n",
              "21                2030863                5.814819e+07         28421236   \n",
              "22                1490886                5.892832e+07         29515165   \n",
              "23                1730152                5.328726e+07         35007981   \n",
              "24                1302766                4.879193e+07         30499924   \n",
              "25                2226114                5.662428e+07         33708983   \n",
              "26                1400099                5.468376e+07         29639609   \n",
              "27                1280844                5.509112e+07         31894222   \n",
              "28                3923449                4.162645e+07         32127592   \n",
              "29                2376671                5.217228e+07         23803138   \n",
              "30                1283367                6.212705e+07         33469570   \n",
              "31                1365590                5.043770e+07         35418302   \n",
              "32                 773926                4.667213e+07         32499996   \n",
              "33                1289080                5.643741e+07         34336596   \n",
              "34                3088153                5.488445e+07         33883001   \n",
              "35                 991272                4.635366e+07         23571029   \n",
              "36                2069892                6.609873e+07         37853692   \n",
              "37                1183841                5.071518e+07         32078032   \n",
              "38                2112865                5.975710e+07         35356100   \n",
              "39                2719767                4.685515e+07         33583347   \n",
              "40                2191955                6.137394e+07         32414295   \n",
              "41                1565421                5.580277e+07         31735326   \n",
              "42                1033309                4.654281e+07         34301246   \n",
              "43                3165796                5.974320e+07         36394504   \n",
              "44                1033784                4.548703e+07         30362735   \n",
              "45                1515664                5.849622e+07         27396429   \n",
              "46                1348071                5.673018e+07         35677196   \n",
              "47                1081186                5.340623e+07         36820589   \n",
              "48                3465313                3.534707e+07         34514784   \n",
              "49                2094658                6.343617e+07         34097677   \n",
              "50                2329138                5.827940e+07         33418152   \n",
              "51                1450478                4.600503e+07         32882193   \n",
              "52                1619284                5.233887e+07         32450531   \n",
              "53               95481236                2.820290e+09       1751412079   \n",
              "54                1801533                5.321302e+07         33045511   \n",
              "55                 745508                7.687894e+06          5388215   \n",
              "\n",
              "     MT retained pairs    MT retained singles   MT retained combined reads  \\\n",
              "0              46430755                1833300                9.469481e+07   \n",
              "1               9119940                1951440                2.019132e+07   \n",
              "2              13400496                2315369                2.911636e+07   \n",
              "3              13612603                1826984                2.905219e+07   \n",
              "4              17367979                2504144                3.724010e+07   \n",
              "5              18174395                2162663                3.851145e+07   \n",
              "6              13847740                1736581                2.943206e+07   \n",
              "7              12018746                1441649                2.547914e+07   \n",
              "8              13596582                2102990                2.929615e+07   \n",
              "9              12307140                1424327                2.603861e+07   \n",
              "10              9331432                1515442                2.017831e+07   \n",
              "11             10155882                1139082                2.145085e+07   \n",
              "12             12235924                1998252                2.647010e+07   \n",
              "13             11628944                1328863                2.458675e+07   \n",
              "14             14363643                1328939                3.005622e+07   \n",
              "15             18755346                2503880                4.001457e+07   \n",
              "16             19790420                2959780                4.254062e+07   \n",
              "17             13802753                1538828                2.914433e+07   \n",
              "18             15997138                2372196                3.436647e+07   \n",
              "19             18564123                2671740                3.979999e+07   \n",
              "20             14640598                1251988                3.053318e+07   \n",
              "21             14285422                1622021                3.019286e+07   \n",
              "22             15646084                2024810                3.331698e+07   \n",
              "23             19311266                2775618                4.139815e+07   \n",
              "24             18342790                1783389                3.846897e+07   \n",
              "25             17931937                2782354                3.864623e+07   \n",
              "26             14248134                1675031                3.017130e+07   \n",
              "27             17448520                1520300                3.641734e+07   \n",
              "28             18036232                2631682                3.870415e+07   \n",
              "29             16386146                1843356                3.461565e+07   \n",
              "30             28141065                1936802                5.821893e+07   \n",
              "31             26585849                4005009                5.717671e+07   \n",
              "32             25199023                3264871                5.366292e+07   \n",
              "33             20937720                2097177                4.397262e+07   \n",
              "34             17654965                2767161                3.807709e+07   \n",
              "35             12051161                1421055                2.552338e+07   \n",
              "36             16360403                3039172                3.575998e+07   \n",
              "37             11415158                1142644                2.397296e+07   \n",
              "38             12792706                2064782                2.765019e+07   \n",
              "39             12404420                1860511                2.666935e+07   \n",
              "40             11974617                1443747                2.539298e+07   \n",
              "41              9954805                1106915                2.101652e+07   \n",
              "42             11506763                1627570                2.464110e+07   \n",
              "43             12496491                1734078                2.672706e+07   \n",
              "44             10236878                1340616                2.181437e+07   \n",
              "45              8434111                1040702                1.790892e+07   \n",
              "46              8436575                1195654                1.806880e+07   \n",
              "47             10406024                1424590                2.223664e+07   \n",
              "48             13143860                1791203                2.807892e+07   \n",
              "49             17817055                3145665                3.877978e+07   \n",
              "50             15582015                2155159                3.331919e+07   \n",
              "51             16384859                1888715                3.465843e+07   \n",
              "52             15443434                2107587                3.299446e+07   \n",
              "53            826139067              104168383                1.756447e+09   \n",
              "54             15587530                1965441                3.314050e+07   \n",
              "55              6065706                 637401                1.246086e+07   \n",
              "\n",
              "     MT rRNA pairs    MT rRNA singles    MT contigs    Co-assembly contigs   \n",
              "0           8162922             211837         57491                 126390  \n",
              "1           4110417             775696         47726                 208345  \n",
              "2          17642665            2323133         61242                 431078  \n",
              "3          16504703            1719392         81321                 443307  \n",
              "4          16717068            1685117        118913                 479608  \n",
              "5          14460847            1445338        130962                 517506  \n",
              "6          16687126            1534912         91152                 331870  \n",
              "7          14775098            1342298         73557                 377432  \n",
              "8          15704281            1559060         86116                 389063  \n",
              "9          20133094            1889977         70840                 478799  \n",
              "10         14726480            1669177         44671                 326463  \n",
              "11         14561598            1374840         72686                 401437  \n",
              "12         16026593            1959118         89444                 396383  \n",
              "13         15895274            1332740         94475                 413711  \n",
              "14         17320121            1449468        117872                 468428  \n",
              "15          9988214             944102        145997                 553152  \n",
              "16         12327661            1279728        132644                 494971  \n",
              "17         15093605            1388116        107211                 404870  \n",
              "18         14915695            1347833        103844                 517913  \n",
              "19         20249314            2173170        108969                 490163  \n",
              "20         10516375             682408        119962                 438208  \n",
              "21         11327996            1029180        115348                 425668  \n",
              "22         10561939            1116334        128807                 482611  \n",
              "23         11158731            1232688        154729                 500533  \n",
              "24          9426018             755439        144450                 448666  \n",
              "25         10936159            1380297        133424                 504283  \n",
              "26         12356024            1169930        104818                 443476  \n",
              "27         11887316             902949        149581                 538414  \n",
              "28          9851426            1340869        134971                 353499  \n",
              "29          4949382             514343        113204                 415829  \n",
              "30          3111109             208282        137445                 466269  \n",
              "31          4108201             572155        114025                 338261  \n",
              "32          3342329             446283        117807                 334496  \n",
              "33         10285053             900638        111373                 442661  \n",
              "34         11810528            1504504        112721                 399510  \n",
              "35          9055794             858754         84128                 339691  \n",
              "36         15527661            2517756        114618                 482520  \n",
              "37         17950311            1459721         87563                 417909  \n",
              "38         18080293            2224365         98151                 403369  \n",
              "39         17209617            1986249         91357                 354881  \n",
              "40         17301018            1546768         94461                 501333  \n",
              "41         19045314            1542360         57897                 423528  \n",
              "42         19117272            1858032         86515                 375114  \n",
              "43         19915026            2069786         97348                 449815  \n",
              "44         17044898            1653723         79024                 333653  \n",
              "45         16251236            1553860         61024                 395166  \n",
              "46         23290747            2631821         50236                 401414  \n",
              "47         22364722            2538008         69141                 370833  \n",
              "48         17520794            1800547         93079                 264999  \n",
              "49         11029695            1793094        116509                 432627  \n",
              "50         13975373            1477695        113332                 465002  \n",
              "51         12992641            1329066        108632                 380672  \n",
              "52         13248562            1405761        106065                 412436  \n",
              "53        732552336           75408717       5338878               21988235  \n",
              "54         13821742            1422806        100734                 414872  \n",
              "55          4743139             560733         27534                  79092  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-28416b14-8535-4ab3-9a6e-de9ffd47fa02\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Date</th>\n",
              "      <th>Sample_ID</th>\n",
              "      <th>MG unprocessed</th>\n",
              "      <th>MG retained pairs</th>\n",
              "      <th>MG retained singles</th>\n",
              "      <th>MG retained combined reads</th>\n",
              "      <th>MT unprocessed</th>\n",
              "      <th>MT retained pairs</th>\n",
              "      <th>MT retained singles</th>\n",
              "      <th>MT retained combined reads</th>\n",
              "      <th>MT rRNA pairs</th>\n",
              "      <th>MT rRNA singles</th>\n",
              "      <th>MT contigs</th>\n",
              "      <th>Co-assembly contigs</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2010-10-04 00:00:00</td>\n",
              "      <td>A01</td>\n",
              "      <td>17531630</td>\n",
              "      <td>16368148</td>\n",
              "      <td>1078317</td>\n",
              "      <td>3.381461e+07</td>\n",
              "      <td>56764165</td>\n",
              "      <td>46430755</td>\n",
              "      <td>1833300</td>\n",
              "      <td>9.469481e+07</td>\n",
              "      <td>8162922</td>\n",
              "      <td>211837</td>\n",
              "      <td>57491</td>\n",
              "      <td>126390</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2011-01-25 00:00:00</td>\n",
              "      <td>A02</td>\n",
              "      <td>14699402</td>\n",
              "      <td>13108258</td>\n",
              "      <td>1199766</td>\n",
              "      <td>2.741628e+07</td>\n",
              "      <td>16493393</td>\n",
              "      <td>9119940</td>\n",
              "      <td>1951440</td>\n",
              "      <td>2.019132e+07</td>\n",
              "      <td>4110417</td>\n",
              "      <td>775696</td>\n",
              "      <td>47726</td>\n",
              "      <td>208345</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2011-03-21 00:00:00</td>\n",
              "      <td>D37</td>\n",
              "      <td>35999747</td>\n",
              "      <td>32911158</td>\n",
              "      <td>2199347</td>\n",
              "      <td>6.802166e+07</td>\n",
              "      <td>35975301</td>\n",
              "      <td>13400496</td>\n",
              "      <td>2315369</td>\n",
              "      <td>2.911636e+07</td>\n",
              "      <td>17642665</td>\n",
              "      <td>2323133</td>\n",
              "      <td>61242</td>\n",
              "      <td>431078</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2011-03-29 00:00:00</td>\n",
              "      <td>D02</td>\n",
              "      <td>34135175</td>\n",
              "      <td>27721744</td>\n",
              "      <td>2837683</td>\n",
              "      <td>5.828117e+07</td>\n",
              "      <td>33912215</td>\n",
              "      <td>13612603</td>\n",
              "      <td>1826984</td>\n",
              "      <td>2.905219e+07</td>\n",
              "      <td>16504703</td>\n",
              "      <td>1719392</td>\n",
              "      <td>81321</td>\n",
              "      <td>443307</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2011-04-05 00:00:00</td>\n",
              "      <td>D39</td>\n",
              "      <td>28908243</td>\n",
              "      <td>26605828</td>\n",
              "      <td>1673538</td>\n",
              "      <td>5.488519e+07</td>\n",
              "      <td>38592454</td>\n",
              "      <td>17367979</td>\n",
              "      <td>2504144</td>\n",
              "      <td>3.724010e+07</td>\n",
              "      <td>16717068</td>\n",
              "      <td>1685117</td>\n",
              "      <td>118913</td>\n",
              "      <td>479608</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>2011-04-14 00:00:00</td>\n",
              "      <td>D24</td>\n",
              "      <td>29187268</td>\n",
              "      <td>27401321</td>\n",
              "      <td>1354513</td>\n",
              "      <td>5.615716e+07</td>\n",
              "      <td>36395674</td>\n",
              "      <td>18174395</td>\n",
              "      <td>2162663</td>\n",
              "      <td>3.851145e+07</td>\n",
              "      <td>14460847</td>\n",
              "      <td>1445338</td>\n",
              "      <td>130962</td>\n",
              "      <td>517506</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>2011-04-21 00:00:00</td>\n",
              "      <td>D25</td>\n",
              "      <td>25320222</td>\n",
              "      <td>20487745</td>\n",
              "      <td>4083256</td>\n",
              "      <td>4.505875e+07</td>\n",
              "      <td>33954127</td>\n",
              "      <td>13847740</td>\n",
              "      <td>1736581</td>\n",
              "      <td>2.943206e+07</td>\n",
              "      <td>16687126</td>\n",
              "      <td>1534912</td>\n",
              "      <td>91152</td>\n",
              "      <td>331870</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>2011-04-29 00:00:00</td>\n",
              "      <td>D35</td>\n",
              "      <td>30371838</td>\n",
              "      <td>27587583</td>\n",
              "      <td>1797893</td>\n",
              "      <td>5.697306e+07</td>\n",
              "      <td>29681622</td>\n",
              "      <td>12018746</td>\n",
              "      <td>1441649</td>\n",
              "      <td>2.547914e+07</td>\n",
              "      <td>14775098</td>\n",
              "      <td>1342298</td>\n",
              "      <td>73557</td>\n",
              "      <td>377432</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>2011-05-06 00:00:00</td>\n",
              "      <td>D46</td>\n",
              "      <td>28122705</td>\n",
              "      <td>25044633</td>\n",
              "      <td>2528946</td>\n",
              "      <td>5.261821e+07</td>\n",
              "      <td>34116436</td>\n",
              "      <td>13596582</td>\n",
              "      <td>2102990</td>\n",
              "      <td>2.929615e+07</td>\n",
              "      <td>15704281</td>\n",
              "      <td>1559060</td>\n",
              "      <td>86116</td>\n",
              "      <td>389063</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>2011-05-13 00:00:00</td>\n",
              "      <td>D13</td>\n",
              "      <td>31173943</td>\n",
              "      <td>29336922</td>\n",
              "      <td>1467456</td>\n",
              "      <td>6.014130e+07</td>\n",
              "      <td>35894482</td>\n",
              "      <td>12307140</td>\n",
              "      <td>1424327</td>\n",
              "      <td>2.603861e+07</td>\n",
              "      <td>20133094</td>\n",
              "      <td>1889977</td>\n",
              "      <td>70840</td>\n",
              "      <td>478799</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>2011-05-20 00:00:00</td>\n",
              "      <td>D40</td>\n",
              "      <td>25651909</td>\n",
              "      <td>24085668</td>\n",
              "      <td>1018577</td>\n",
              "      <td>4.918991e+07</td>\n",
              "      <td>27707752</td>\n",
              "      <td>9331432</td>\n",
              "      <td>1515442</td>\n",
              "      <td>2.017831e+07</td>\n",
              "      <td>14726480</td>\n",
              "      <td>1669177</td>\n",
              "      <td>44671</td>\n",
              "      <td>326463</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>2011-05-27 00:00:00</td>\n",
              "      <td>D33</td>\n",
              "      <td>30235782</td>\n",
              "      <td>28307886</td>\n",
              "      <td>1506824</td>\n",
              "      <td>5.812260e+07</td>\n",
              "      <td>27369514</td>\n",
              "      <td>10155882</td>\n",
              "      <td>1139082</td>\n",
              "      <td>2.145085e+07</td>\n",
              "      <td>14561598</td>\n",
              "      <td>1374840</td>\n",
              "      <td>72686</td>\n",
              "      <td>401437</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>2011-06-03 00:00:00</td>\n",
              "      <td>D06</td>\n",
              "      <td>30216637</td>\n",
              "      <td>26954409</td>\n",
              "      <td>1576187</td>\n",
              "      <td>5.548500e+07</td>\n",
              "      <td>32430876</td>\n",
              "      <td>12235924</td>\n",
              "      <td>1998252</td>\n",
              "      <td>2.647010e+07</td>\n",
              "      <td>16026593</td>\n",
              "      <td>1959118</td>\n",
              "      <td>89444</td>\n",
              "      <td>396383</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>2011-06-09 00:00:00</td>\n",
              "      <td>D27</td>\n",
              "      <td>27497422</td>\n",
              "      <td>25777061</td>\n",
              "      <td>1306125</td>\n",
              "      <td>5.286025e+07</td>\n",
              "      <td>30331588</td>\n",
              "      <td>11628944</td>\n",
              "      <td>1328863</td>\n",
              "      <td>2.458675e+07</td>\n",
              "      <td>15895274</td>\n",
              "      <td>1332740</td>\n",
              "      <td>94475</td>\n",
              "      <td>413711</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>2011-06-17 00:00:00</td>\n",
              "      <td>D42</td>\n",
              "      <td>27303250</td>\n",
              "      <td>25503950</td>\n",
              "      <td>1313167</td>\n",
              "      <td>5.232107e+07</td>\n",
              "      <td>34544359</td>\n",
              "      <td>14363643</td>\n",
              "      <td>1328939</td>\n",
              "      <td>3.005622e+07</td>\n",
              "      <td>17320121</td>\n",
              "      <td>1449468</td>\n",
              "      <td>117872</td>\n",
              "      <td>468428</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>2011-06-24 00:00:00</td>\n",
              "      <td>D03</td>\n",
              "      <td>32347395</td>\n",
              "      <td>29220419</td>\n",
              "      <td>1797971</td>\n",
              "      <td>6.023881e+07</td>\n",
              "      <td>32699565</td>\n",
              "      <td>18755346</td>\n",
              "      <td>2503880</td>\n",
              "      <td>4.001457e+07</td>\n",
              "      <td>9988214</td>\n",
              "      <td>944102</td>\n",
              "      <td>145997</td>\n",
              "      <td>553152</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>2011-07-01 00:00:00</td>\n",
              "      <td>D47</td>\n",
              "      <td>30109054</td>\n",
              "      <td>27730630</td>\n",
              "      <td>1936737</td>\n",
              "      <td>5.739800e+07</td>\n",
              "      <td>36766788</td>\n",
              "      <td>19790420</td>\n",
              "      <td>2959780</td>\n",
              "      <td>4.254062e+07</td>\n",
              "      <td>12327661</td>\n",
              "      <td>1279728</td>\n",
              "      <td>132644</td>\n",
              "      <td>494971</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>2011-07-08 00:00:00</td>\n",
              "      <td>D18</td>\n",
              "      <td>23391679</td>\n",
              "      <td>22164878</td>\n",
              "      <td>1066058</td>\n",
              "      <td>4.539581e+07</td>\n",
              "      <td>31924022</td>\n",
              "      <td>13802753</td>\n",
              "      <td>1538828</td>\n",
              "      <td>2.914433e+07</td>\n",
              "      <td>15093605</td>\n",
              "      <td>1388116</td>\n",
              "      <td>107211</td>\n",
              "      <td>404870</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>2011-08-05 00:00:00</td>\n",
              "      <td>D45</td>\n",
              "      <td>29930665</td>\n",
              "      <td>27829830</td>\n",
              "      <td>1644918</td>\n",
              "      <td>5.730458e+07</td>\n",
              "      <td>35378306</td>\n",
              "      <td>15997138</td>\n",
              "      <td>2372196</td>\n",
              "      <td>3.436647e+07</td>\n",
              "      <td>14915695</td>\n",
              "      <td>1347833</td>\n",
              "      <td>103844</td>\n",
              "      <td>517913</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>2011-08-11 00:00:00</td>\n",
              "      <td>D51</td>\n",
              "      <td>29852842</td>\n",
              "      <td>26901508</td>\n",
              "      <td>2115968</td>\n",
              "      <td>5.591898e+07</td>\n",
              "      <td>44174409</td>\n",
              "      <td>18564123</td>\n",
              "      <td>2671740</td>\n",
              "      <td>3.979999e+07</td>\n",
              "      <td>20249314</td>\n",
              "      <td>2173170</td>\n",
              "      <td>108969</td>\n",
              "      <td>490163</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>2011-08-19 00:00:00</td>\n",
              "      <td>D43</td>\n",
              "      <td>26075473</td>\n",
              "      <td>24281057</td>\n",
              "      <td>1444335</td>\n",
              "      <td>5.000645e+07</td>\n",
              "      <td>27171859</td>\n",
              "      <td>14640598</td>\n",
              "      <td>1251988</td>\n",
              "      <td>3.053318e+07</td>\n",
              "      <td>10516375</td>\n",
              "      <td>682408</td>\n",
              "      <td>119962</td>\n",
              "      <td>438208</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>2011-08-29 00:00:00</td>\n",
              "      <td>D34</td>\n",
              "      <td>30403109</td>\n",
              "      <td>28058664</td>\n",
              "      <td>2030863</td>\n",
              "      <td>5.814819e+07</td>\n",
              "      <td>28421236</td>\n",
              "      <td>14285422</td>\n",
              "      <td>1622021</td>\n",
              "      <td>3.019286e+07</td>\n",
              "      <td>11327996</td>\n",
              "      <td>1029180</td>\n",
              "      <td>115348</td>\n",
              "      <td>425668</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>2011-09-05 00:00:00</td>\n",
              "      <td>D30</td>\n",
              "      <td>30532662</td>\n",
              "      <td>28718715</td>\n",
              "      <td>1490886</td>\n",
              "      <td>5.892832e+07</td>\n",
              "      <td>29515165</td>\n",
              "      <td>15646084</td>\n",
              "      <td>2024810</td>\n",
              "      <td>3.331698e+07</td>\n",
              "      <td>10561939</td>\n",
              "      <td>1116334</td>\n",
              "      <td>128807</td>\n",
              "      <td>482611</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>2011-09-12 00:00:00</td>\n",
              "      <td>D04</td>\n",
              "      <td>29014224</td>\n",
              "      <td>25778552</td>\n",
              "      <td>1730152</td>\n",
              "      <td>5.328726e+07</td>\n",
              "      <td>35007981</td>\n",
              "      <td>19311266</td>\n",
              "      <td>2775618</td>\n",
              "      <td>4.139815e+07</td>\n",
              "      <td>11158731</td>\n",
              "      <td>1232688</td>\n",
              "      <td>154729</td>\n",
              "      <td>500533</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>2011-09-19 00:00:00</td>\n",
              "      <td>D31</td>\n",
              "      <td>25456037</td>\n",
              "      <td>23744583</td>\n",
              "      <td>1302766</td>\n",
              "      <td>4.879193e+07</td>\n",
              "      <td>30499924</td>\n",
              "      <td>18342790</td>\n",
              "      <td>1783389</td>\n",
              "      <td>3.846897e+07</td>\n",
              "      <td>9426018</td>\n",
              "      <td>755439</td>\n",
              "      <td>144450</td>\n",
              "      <td>448666</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>2011-09-28 00:00:00</td>\n",
              "      <td>D29</td>\n",
              "      <td>29839175</td>\n",
              "      <td>27199081</td>\n",
              "      <td>2226114</td>\n",
              "      <td>5.662428e+07</td>\n",
              "      <td>33708983</td>\n",
              "      <td>17931937</td>\n",
              "      <td>2782354</td>\n",
              "      <td>3.864623e+07</td>\n",
              "      <td>10936159</td>\n",
              "      <td>1380297</td>\n",
              "      <td>133424</td>\n",
              "      <td>504283</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>2011-10-05 00:00:00</td>\n",
              "      <td>D49</td>\n",
              "      <td>29042305</td>\n",
              "      <td>26641829</td>\n",
              "      <td>1400099</td>\n",
              "      <td>5.468376e+07</td>\n",
              "      <td>29639609</td>\n",
              "      <td>14248134</td>\n",
              "      <td>1675031</td>\n",
              "      <td>3.017130e+07</td>\n",
              "      <td>12356024</td>\n",
              "      <td>1169930</td>\n",
              "      <td>104818</td>\n",
              "      <td>443476</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>2011-10-12 00:00:00</td>\n",
              "      <td>D32</td>\n",
              "      <td>28460125</td>\n",
              "      <td>26905139</td>\n",
              "      <td>1280844</td>\n",
              "      <td>5.509112e+07</td>\n",
              "      <td>31894222</td>\n",
              "      <td>17448520</td>\n",
              "      <td>1520300</td>\n",
              "      <td>3.641734e+07</td>\n",
              "      <td>11887316</td>\n",
              "      <td>902949</td>\n",
              "      <td>149581</td>\n",
              "      <td>538414</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>2011-11-02 00:00:00</td>\n",
              "      <td>D23</td>\n",
              "      <td>23448618</td>\n",
              "      <td>18851501</td>\n",
              "      <td>3923449</td>\n",
              "      <td>4.162645e+07</td>\n",
              "      <td>32127592</td>\n",
              "      <td>18036232</td>\n",
              "      <td>2631682</td>\n",
              "      <td>3.870415e+07</td>\n",
              "      <td>9851426</td>\n",
              "      <td>1340869</td>\n",
              "      <td>134971</td>\n",
              "      <td>353499</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>2011-11-07 00:00:00</td>\n",
              "      <td>D44</td>\n",
              "      <td>27963482</td>\n",
              "      <td>24897807</td>\n",
              "      <td>2376671</td>\n",
              "      <td>5.217228e+07</td>\n",
              "      <td>23803138</td>\n",
              "      <td>16386146</td>\n",
              "      <td>1843356</td>\n",
              "      <td>3.461565e+07</td>\n",
              "      <td>4949382</td>\n",
              "      <td>514343</td>\n",
              "      <td>113204</td>\n",
              "      <td>415829</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30</th>\n",
              "      <td>2011-11-16 00:00:00</td>\n",
              "      <td>D20</td>\n",
              "      <td>32139021</td>\n",
              "      <td>30421843</td>\n",
              "      <td>1283367</td>\n",
              "      <td>6.212705e+07</td>\n",
              "      <td>33469570</td>\n",
              "      <td>28141065</td>\n",
              "      <td>1936802</td>\n",
              "      <td>5.821893e+07</td>\n",
              "      <td>3111109</td>\n",
              "      <td>208282</td>\n",
              "      <td>137445</td>\n",
              "      <td>466269</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31</th>\n",
              "      <td>2011-11-23 00:00:00</td>\n",
              "      <td>D15</td>\n",
              "      <td>26973299</td>\n",
              "      <td>24536053</td>\n",
              "      <td>1365590</td>\n",
              "      <td>5.043770e+07</td>\n",
              "      <td>35418302</td>\n",
              "      <td>26585849</td>\n",
              "      <td>4005009</td>\n",
              "      <td>5.717671e+07</td>\n",
              "      <td>4108201</td>\n",
              "      <td>572155</td>\n",
              "      <td>114025</td>\n",
              "      <td>338261</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32</th>\n",
              "      <td>2011-11-29 00:00:00</td>\n",
              "      <td>D05</td>\n",
              "      <td>25621580</td>\n",
              "      <td>22949103</td>\n",
              "      <td>773926</td>\n",
              "      <td>4.667213e+07</td>\n",
              "      <td>32499996</td>\n",
              "      <td>25199023</td>\n",
              "      <td>3264871</td>\n",
              "      <td>5.366292e+07</td>\n",
              "      <td>3342329</td>\n",
              "      <td>446283</td>\n",
              "      <td>117807</td>\n",
              "      <td>334496</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>33</th>\n",
              "      <td>2011-12-21 00:00:00</td>\n",
              "      <td>D28</td>\n",
              "      <td>29329592</td>\n",
              "      <td>27574163</td>\n",
              "      <td>1289080</td>\n",
              "      <td>5.643741e+07</td>\n",
              "      <td>34336596</td>\n",
              "      <td>20937720</td>\n",
              "      <td>2097177</td>\n",
              "      <td>4.397262e+07</td>\n",
              "      <td>10285053</td>\n",
              "      <td>900638</td>\n",
              "      <td>111373</td>\n",
              "      <td>442661</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>34</th>\n",
              "      <td>2011-12-28 00:00:00</td>\n",
              "      <td>D09</td>\n",
              "      <td>31138147</td>\n",
              "      <td>25898148</td>\n",
              "      <td>3088153</td>\n",
              "      <td>5.488445e+07</td>\n",
              "      <td>33883001</td>\n",
              "      <td>17654965</td>\n",
              "      <td>2767161</td>\n",
              "      <td>3.807709e+07</td>\n",
              "      <td>11810528</td>\n",
              "      <td>1504504</td>\n",
              "      <td>112721</td>\n",
              "      <td>399510</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35</th>\n",
              "      <td>2012-01-03 00:00:00</td>\n",
              "      <td>D38</td>\n",
              "      <td>24493806</td>\n",
              "      <td>22681193</td>\n",
              "      <td>991272</td>\n",
              "      <td>4.635366e+07</td>\n",
              "      <td>23571029</td>\n",
              "      <td>12051161</td>\n",
              "      <td>1421055</td>\n",
              "      <td>2.552338e+07</td>\n",
              "      <td>9055794</td>\n",
              "      <td>858754</td>\n",
              "      <td>84128</td>\n",
              "      <td>339691</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>36</th>\n",
              "      <td>2012-01-11 00:00:00</td>\n",
              "      <td>D36</td>\n",
              "      <td>34928806</td>\n",
              "      <td>32014419</td>\n",
              "      <td>2069892</td>\n",
              "      <td>6.609873e+07</td>\n",
              "      <td>37853692</td>\n",
              "      <td>16360403</td>\n",
              "      <td>3039172</td>\n",
              "      <td>3.575998e+07</td>\n",
              "      <td>15527661</td>\n",
              "      <td>2517756</td>\n",
              "      <td>114618</td>\n",
              "      <td>482520</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>37</th>\n",
              "      <td>2012-01-19 00:00:00</td>\n",
              "      <td>D12</td>\n",
              "      <td>26256782</td>\n",
              "      <td>24765672</td>\n",
              "      <td>1183841</td>\n",
              "      <td>5.071518e+07</td>\n",
              "      <td>32078032</td>\n",
              "      <td>11415158</td>\n",
              "      <td>1142644</td>\n",
              "      <td>2.397296e+07</td>\n",
              "      <td>17950311</td>\n",
              "      <td>1459721</td>\n",
              "      <td>87563</td>\n",
              "      <td>417909</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38</th>\n",
              "      <td>2012-01-25 00:00:00</td>\n",
              "      <td>D10</td>\n",
              "      <td>32576299</td>\n",
              "      <td>28822117</td>\n",
              "      <td>2112865</td>\n",
              "      <td>5.975710e+07</td>\n",
              "      <td>35356100</td>\n",
              "      <td>12792706</td>\n",
              "      <td>2064782</td>\n",
              "      <td>2.765019e+07</td>\n",
              "      <td>18080293</td>\n",
              "      <td>2224365</td>\n",
              "      <td>98151</td>\n",
              "      <td>403369</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39</th>\n",
              "      <td>2012-02-01 00:00:00</td>\n",
              "      <td>D14</td>\n",
              "      <td>26995145</td>\n",
              "      <td>22067691</td>\n",
              "      <td>2719767</td>\n",
              "      <td>4.685515e+07</td>\n",
              "      <td>33583347</td>\n",
              "      <td>12404420</td>\n",
              "      <td>1860511</td>\n",
              "      <td>2.666935e+07</td>\n",
              "      <td>17209617</td>\n",
              "      <td>1986249</td>\n",
              "      <td>91357</td>\n",
              "      <td>354881</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>40</th>\n",
              "      <td>2012-02-08 00:00:00</td>\n",
              "      <td>D08</td>\n",
              "      <td>33462713</td>\n",
              "      <td>29590993</td>\n",
              "      <td>2191955</td>\n",
              "      <td>6.137394e+07</td>\n",
              "      <td>32414295</td>\n",
              "      <td>11974617</td>\n",
              "      <td>1443747</td>\n",
              "      <td>2.539298e+07</td>\n",
              "      <td>17301018</td>\n",
              "      <td>1546768</td>\n",
              "      <td>94461</td>\n",
              "      <td>501333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>41</th>\n",
              "      <td>2012-02-14 00:00:00</td>\n",
              "      <td>D26</td>\n",
              "      <td>29242844</td>\n",
              "      <td>27118676</td>\n",
              "      <td>1565421</td>\n",
              "      <td>5.580277e+07</td>\n",
              "      <td>31735326</td>\n",
              "      <td>9954805</td>\n",
              "      <td>1106915</td>\n",
              "      <td>2.101652e+07</td>\n",
              "      <td>19045314</td>\n",
              "      <td>1542360</td>\n",
              "      <td>57897</td>\n",
              "      <td>423528</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>42</th>\n",
              "      <td>2012-02-23 00:00:00</td>\n",
              "      <td>D21</td>\n",
              "      <td>24350474</td>\n",
              "      <td>22754752</td>\n",
              "      <td>1033309</td>\n",
              "      <td>4.654281e+07</td>\n",
              "      <td>34301246</td>\n",
              "      <td>11506763</td>\n",
              "      <td>1627570</td>\n",
              "      <td>2.464110e+07</td>\n",
              "      <td>19117272</td>\n",
              "      <td>1858032</td>\n",
              "      <td>86515</td>\n",
              "      <td>375114</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>43</th>\n",
              "      <td>2012-02-29 00:00:00</td>\n",
              "      <td>D19</td>\n",
              "      <td>32574065</td>\n",
              "      <td>28288700</td>\n",
              "      <td>3165796</td>\n",
              "      <td>5.974320e+07</td>\n",
              "      <td>36394504</td>\n",
              "      <td>12496491</td>\n",
              "      <td>1734078</td>\n",
              "      <td>2.672706e+07</td>\n",
              "      <td>19915026</td>\n",
              "      <td>2069786</td>\n",
              "      <td>97348</td>\n",
              "      <td>449815</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>44</th>\n",
              "      <td>2012-03-08 00:00:00</td>\n",
              "      <td>D17</td>\n",
              "      <td>23876138</td>\n",
              "      <td>22226625</td>\n",
              "      <td>1033784</td>\n",
              "      <td>4.548703e+07</td>\n",
              "      <td>30362735</td>\n",
              "      <td>10236878</td>\n",
              "      <td>1340616</td>\n",
              "      <td>2.181437e+07</td>\n",
              "      <td>17044898</td>\n",
              "      <td>1653723</td>\n",
              "      <td>79024</td>\n",
              "      <td>333653</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45</th>\n",
              "      <td>2012-03-14 00:00:00</td>\n",
              "      <td>D41</td>\n",
              "      <td>30626165</td>\n",
              "      <td>28490276</td>\n",
              "      <td>1515664</td>\n",
              "      <td>5.849622e+07</td>\n",
              "      <td>27396429</td>\n",
              "      <td>8434111</td>\n",
              "      <td>1040702</td>\n",
              "      <td>1.790892e+07</td>\n",
              "      <td>16251236</td>\n",
              "      <td>1553860</td>\n",
              "      <td>61024</td>\n",
              "      <td>395166</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>46</th>\n",
              "      <td>2012-03-22 00:00:00</td>\n",
              "      <td>D11</td>\n",
              "      <td>29495784</td>\n",
              "      <td>27691057</td>\n",
              "      <td>1348071</td>\n",
              "      <td>5.673018e+07</td>\n",
              "      <td>35677196</td>\n",
              "      <td>8436575</td>\n",
              "      <td>1195654</td>\n",
              "      <td>1.806880e+07</td>\n",
              "      <td>23290747</td>\n",
              "      <td>2631821</td>\n",
              "      <td>50236</td>\n",
              "      <td>401414</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>47</th>\n",
              "      <td>2012-03-28 00:00:00</td>\n",
              "      <td>D16</td>\n",
              "      <td>28186198</td>\n",
              "      <td>26162520</td>\n",
              "      <td>1081186</td>\n",
              "      <td>5.340623e+07</td>\n",
              "      <td>36820589</td>\n",
              "      <td>10406024</td>\n",
              "      <td>1424590</td>\n",
              "      <td>2.223664e+07</td>\n",
              "      <td>22364722</td>\n",
              "      <td>2538008</td>\n",
              "      <td>69141</td>\n",
              "      <td>370833</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>2012-04-04 00:00:00</td>\n",
              "      <td>D07</td>\n",
              "      <td>21699617</td>\n",
              "      <td>15940878</td>\n",
              "      <td>3465313</td>\n",
              "      <td>3.534707e+07</td>\n",
              "      <td>34514784</td>\n",
              "      <td>13143860</td>\n",
              "      <td>1791203</td>\n",
              "      <td>2.807892e+07</td>\n",
              "      <td>17520794</td>\n",
              "      <td>1800547</td>\n",
              "      <td>93079</td>\n",
              "      <td>264999</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>49</th>\n",
              "      <td>2012-04-10 00:00:00</td>\n",
              "      <td>D22</td>\n",
              "      <td>33671265</td>\n",
              "      <td>30670757</td>\n",
              "      <td>2094658</td>\n",
              "      <td>6.343617e+07</td>\n",
              "      <td>34097677</td>\n",
              "      <td>17817055</td>\n",
              "      <td>3145665</td>\n",
              "      <td>3.877978e+07</td>\n",
              "      <td>11029695</td>\n",
              "      <td>1793094</td>\n",
              "      <td>116509</td>\n",
              "      <td>432627</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50</th>\n",
              "      <td>2012-04-17 00:00:00</td>\n",
              "      <td>D01</td>\n",
              "      <td>32692858</td>\n",
              "      <td>27975133</td>\n",
              "      <td>2329138</td>\n",
              "      <td>5.827940e+07</td>\n",
              "      <td>33418152</td>\n",
              "      <td>15582015</td>\n",
              "      <td>2155159</td>\n",
              "      <td>3.331919e+07</td>\n",
              "      <td>13975373</td>\n",
              "      <td>1477695</td>\n",
              "      <td>113332</td>\n",
              "      <td>465002</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>51</th>\n",
              "      <td>2012-04-25 00:00:00</td>\n",
              "      <td>D50</td>\n",
              "      <td>24359112</td>\n",
              "      <td>22277277</td>\n",
              "      <td>1450478</td>\n",
              "      <td>4.600503e+07</td>\n",
              "      <td>32882193</td>\n",
              "      <td>16384859</td>\n",
              "      <td>1888715</td>\n",
              "      <td>3.465843e+07</td>\n",
              "      <td>12992641</td>\n",
              "      <td>1329066</td>\n",
              "      <td>108632</td>\n",
              "      <td>380672</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>52</th>\n",
              "      <td>2012-05-03 00:00:00</td>\n",
              "      <td>D48</td>\n",
              "      <td>27267336</td>\n",
              "      <td>25359794</td>\n",
              "      <td>1619284</td>\n",
              "      <td>5.233887e+07</td>\n",
              "      <td>32450531</td>\n",
              "      <td>15443434</td>\n",
              "      <td>2107587</td>\n",
              "      <td>3.299446e+07</td>\n",
              "      <td>13248562</td>\n",
              "      <td>1405761</td>\n",
              "      <td>106065</td>\n",
              "      <td>412436</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>53</th>\n",
              "      <td>Total</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1504179064</td>\n",
              "      <td>1362404347</td>\n",
              "      <td>95481236</td>\n",
              "      <td>2.820290e+09</td>\n",
              "      <td>1751412079</td>\n",
              "      <td>826139067</td>\n",
              "      <td>104168383</td>\n",
              "      <td>1.756447e+09</td>\n",
              "      <td>732552336</td>\n",
              "      <td>75408717</td>\n",
              "      <td>5338878</td>\n",
              "      <td>21988235</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>54</th>\n",
              "      <td>Average</td>\n",
              "      <td>NaN</td>\n",
              "      <td>28380737</td>\n",
              "      <td>25705742</td>\n",
              "      <td>1801533</td>\n",
              "      <td>5.321302e+07</td>\n",
              "      <td>33045511</td>\n",
              "      <td>15587530</td>\n",
              "      <td>1965441</td>\n",
              "      <td>3.314050e+07</td>\n",
              "      <td>13821742</td>\n",
              "      <td>1422806</td>\n",
              "      <td>100734</td>\n",
              "      <td>414872</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>55</th>\n",
              "      <td>Standard deviation</td>\n",
              "      <td>NaN</td>\n",
              "      <td>4025168</td>\n",
              "      <td>3847016</td>\n",
              "      <td>745508</td>\n",
              "      <td>7.687894e+06</td>\n",
              "      <td>5388215</td>\n",
              "      <td>6065706</td>\n",
              "      <td>637401</td>\n",
              "      <td>1.246086e+07</td>\n",
              "      <td>4743139</td>\n",
              "      <td>560733</td>\n",
              "      <td>27534</td>\n",
              "      <td>79092</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-28416b14-8535-4ab3-9a6e-de9ffd47fa02')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
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              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-28416b14-8535-4ab3-9a6e-de9ffd47fa02 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-28416b14-8535-4ab3-9a6e-de9ffd47fa02');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 70
        }
      ],
      "source": [
        "df=pd.read_excel(\"/content/Supplementary Data 1.xlsx\", skiprows=1)\n",
        "df"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "ca622c40",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "ca622c40",
        "outputId": "203393b5-e3b5-466d-dcaa-d547c575037a"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                  Date   Sample_ID    MG unprocessed    MG retained pairs   \\\n",
              "0   2010-10-04 00:00:00        A01           17531630             16368148   \n",
              "1   2011-01-25 00:00:00        A02           14699402             13108258   \n",
              "2   2011-03-21 00:00:00        D37           35999747             32911158   \n",
              "3   2011-03-29 00:00:00        D02           34135175             27721744   \n",
              "4   2011-04-05 00:00:00        D39           28908243             26605828   \n",
              "5   2011-04-14 00:00:00        D24           29187268             27401321   \n",
              "6   2011-04-21 00:00:00        D25           25320222             20487745   \n",
              "7   2011-04-29 00:00:00        D35           30371838             27587583   \n",
              "8   2011-05-06 00:00:00        D46           28122705             25044633   \n",
              "9   2011-05-13 00:00:00        D13           31173943             29336922   \n",
              "10  2011-05-20 00:00:00        D40           25651909             24085668   \n",
              "11  2011-05-27 00:00:00        D33           30235782             28307886   \n",
              "12  2011-06-03 00:00:00        D06           30216637             26954409   \n",
              "13  2011-06-09 00:00:00        D27           27497422             25777061   \n",
              "14  2011-06-17 00:00:00        D42           27303250             25503950   \n",
              "15  2011-06-24 00:00:00        D03           32347395             29220419   \n",
              "16  2011-07-01 00:00:00        D47           30109054             27730630   \n",
              "17  2011-07-08 00:00:00        D18           23391679             22164878   \n",
              "18  2011-08-05 00:00:00        D45           29930665             27829830   \n",
              "19  2011-08-11 00:00:00        D51           29852842             26901508   \n",
              "20  2011-08-19 00:00:00        D43           26075473             24281057   \n",
              "21  2011-08-29 00:00:00        D34           30403109             28058664   \n",
              "22  2011-09-05 00:00:00        D30           30532662             28718715   \n",
              "23  2011-09-12 00:00:00        D04           29014224             25778552   \n",
              "24  2011-09-19 00:00:00        D31           25456037             23744583   \n",
              "25  2011-09-28 00:00:00        D29           29839175             27199081   \n",
              "26  2011-10-05 00:00:00        D49           29042305             26641829   \n",
              "27  2011-10-12 00:00:00        D32           28460125             26905139   \n",
              "28  2011-11-02 00:00:00        D23           23448618             18851501   \n",
              "29  2011-11-07 00:00:00        D44           27963482             24897807   \n",
              "30  2011-11-16 00:00:00        D20           32139021             30421843   \n",
              "31  2011-11-23 00:00:00        D15           26973299             24536053   \n",
              "32  2011-11-29 00:00:00        D05           25621580             22949103   \n",
              "33  2011-12-21 00:00:00        D28           29329592             27574163   \n",
              "34  2011-12-28 00:00:00        D09           31138147             25898148   \n",
              "35  2012-01-03 00:00:00        D38           24493806             22681193   \n",
              "36  2012-01-11 00:00:00        D36           34928806             32014419   \n",
              "37  2012-01-19 00:00:00        D12           26256782             24765672   \n",
              "38  2012-01-25 00:00:00        D10           32576299             28822117   \n",
              "39  2012-02-01 00:00:00        D14           26995145             22067691   \n",
              "40  2012-02-08 00:00:00        D08           33462713             29590993   \n",
              "41  2012-02-14 00:00:00        D26           29242844             27118676   \n",
              "42  2012-02-23 00:00:00        D21           24350474             22754752   \n",
              "43  2012-02-29 00:00:00        D19           32574065             28288700   \n",
              "44  2012-03-08 00:00:00        D17           23876138             22226625   \n",
              "45  2012-03-14 00:00:00        D41           30626165             28490276   \n",
              "46  2012-03-22 00:00:00        D11           29495784             27691057   \n",
              "47  2012-03-28 00:00:00        D16           28186198             26162520   \n",
              "48  2012-04-04 00:00:00        D07           21699617             15940878   \n",
              "49  2012-04-10 00:00:00        D22           33671265             30670757   \n",
              "50  2012-04-17 00:00:00        D01           32692858             27975133   \n",
              "51  2012-04-25 00:00:00        D50           24359112             22277277   \n",
              "52  2012-05-03 00:00:00        D48           27267336             25359794   \n",
              "\n",
              "     MG retained singles   MG retained combined reads   MT unprocessed  \\\n",
              "0                 1078317                  33814613.0         56764165   \n",
              "1                 1199766                  27416282.0         16493393   \n",
              "2                 2199347                  68021663.0         35975301   \n",
              "3                 2837683                  58281171.0         33912215   \n",
              "4                 1673538                  54885194.0         38592454   \n",
              "5                 1354513                  56157155.0         36395674   \n",
              "6                 4083256                  45058746.0         33954127   \n",
              "7                 1797893                  56973059.0         29681622   \n",
              "8                 2528946                  52618212.0         34116436   \n",
              "9                 1467456                  60141300.0         35894482   \n",
              "10                1018577                  49189913.0         27707752   \n",
              "11                1506824                  58122596.0         27369514   \n",
              "12                1576187                  55485005.0         32430876   \n",
              "13                1306125                  52860247.0         30331588   \n",
              "14                1313167                  52321067.0         34544359   \n",
              "15                1797971                  60238809.0         32699565   \n",
              "16                1936737                  57397997.0         36766788   \n",
              "17                1066058                  45395814.0         31924022   \n",
              "18                1644918                  57304578.0         35378306   \n",
              "19                2115968                  55918984.0         44174409   \n",
              "20                1444335                  50006449.0         27171859   \n",
              "21                2030863                  58148191.0         28421236   \n",
              "22                1490886                  58928316.0         29515165   \n",
              "23                1730152                  53287256.0         35007981   \n",
              "24                1302766                  48791932.0         30499924   \n",
              "25                2226114                  56624276.0         33708983   \n",
              "26                1400099                  54683757.0         29639609   \n",
              "27                1280844                  55091122.0         31894222   \n",
              "28                3923449                  41626451.0         32127592   \n",
              "29                2376671                  52172285.0         23803138   \n",
              "30                1283367                  62127053.0         33469570   \n",
              "31                1365590                  50437696.0         35418302   \n",
              "32                 773926                  46672132.0         32499996   \n",
              "33                1289080                  56437406.0         34336596   \n",
              "34                3088153                  54884449.0         33883001   \n",
              "35                 991272                  46353658.0         23571029   \n",
              "36                2069892                  66098730.0         37853692   \n",
              "37                1183841                  50715185.0         32078032   \n",
              "38                2112865                  59757099.0         35356100   \n",
              "39                2719767                  46855149.0         33583347   \n",
              "40                2191955                  61373941.0         32414295   \n",
              "41                1565421                  55802773.0         31735326   \n",
              "42                1033309                  46542813.0         34301246   \n",
              "43                3165796                  59743196.0         36394504   \n",
              "44                1033784                  45487034.0         30362735   \n",
              "45                1515664                  58496216.0         27396429   \n",
              "46                1348071                  56730185.0         35677196   \n",
              "47                1081186                  53406226.0         36820589   \n",
              "48                3465313                  35347069.0         34514784   \n",
              "49                2094658                  63436172.0         34097677   \n",
              "50                2329138                  58279404.0         33418152   \n",
              "51                1450478                  46005032.0         32882193   \n",
              "52                1619284                  52338872.0         32450531   \n",
              "\n",
              "     MT retained pairs    MT retained singles   MT retained combined reads  \\\n",
              "0              46430755                1833300                  94694810.0   \n",
              "1               9119940                1951440                  20191320.0   \n",
              "2              13400496                2315369                  29116361.0   \n",
              "3              13612603                1826984                  29052190.0   \n",
              "4              17367979                2504144                  37240102.0   \n",
              "5              18174395                2162663                  38511453.0   \n",
              "6              13847740                1736581                  29432061.0   \n",
              "7              12018746                1441649                  25479141.0   \n",
              "8              13596582                2102990                  29296154.0   \n",
              "9              12307140                1424327                  26038607.0   \n",
              "10              9331432                1515442                  20178306.0   \n",
              "11             10155882                1139082                  21450846.0   \n",
              "12             12235924                1998252                  26470100.0   \n",
              "13             11628944                1328863                  24586751.0   \n",
              "14             14363643                1328939                  30056225.0   \n",
              "15             18755346                2503880                  40014572.0   \n",
              "16             19790420                2959780                  42540620.0   \n",
              "17             13802753                1538828                  29144334.0   \n",
              "18             15997138                2372196                  34366472.0   \n",
              "19             18564123                2671740                  39799986.0   \n",
              "20             14640598                1251988                  30533184.0   \n",
              "21             14285422                1622021                  30192865.0   \n",
              "22             15646084                2024810                  33316978.0   \n",
              "23             19311266                2775618                  41398150.0   \n",
              "24             18342790                1783389                  38468969.0   \n",
              "25             17931937                2782354                  38646228.0   \n",
              "26             14248134                1675031                  30171299.0   \n",
              "27             17448520                1520300                  36417340.0   \n",
              "28             18036232                2631682                  38704146.0   \n",
              "29             16386146                1843356                  34615648.0   \n",
              "30             28141065                1936802                  58218932.0   \n",
              "31             26585849                4005009                  57176707.0   \n",
              "32             25199023                3264871                  53662917.0   \n",
              "33             20937720                2097177                  43972617.0   \n",
              "34             17654965                2767161                  38077091.0   \n",
              "35             12051161                1421055                  25523377.0   \n",
              "36             16360403                3039172                  35759978.0   \n",
              "37             11415158                1142644                  23972960.0   \n",
              "38             12792706                2064782                  27650194.0   \n",
              "39             12404420                1860511                  26669351.0   \n",
              "40             11974617                1443747                  25392981.0   \n",
              "41              9954805                1106915                  21016525.0   \n",
              "42             11506763                1627570                  24641096.0   \n",
              "43             12496491                1734078                  26727060.0   \n",
              "44             10236878                1340616                  21814372.0   \n",
              "45              8434111                1040702                  17908924.0   \n",
              "46              8436575                1195654                  18068804.0   \n",
              "47             10406024                1424590                  22236638.0   \n",
              "48             13143860                1791203                  28078923.0   \n",
              "49             17817055                3145665                  38779775.0   \n",
              "50             15582015                2155159                  33319189.0   \n",
              "51             16384859                1888715                  34658433.0   \n",
              "52             15443434                2107587                  32994455.0   \n",
              "\n",
              "     MT rRNA pairs    MT rRNA singles    MT contigs    Co-assembly contigs   \n",
              "0           8162922             211837         57491                 126390  \n",
              "1           4110417             775696         47726                 208345  \n",
              "2          17642665            2323133         61242                 431078  \n",
              "3          16504703            1719392         81321                 443307  \n",
              "4          16717068            1685117        118913                 479608  \n",
              "5          14460847            1445338        130962                 517506  \n",
              "6          16687126            1534912         91152                 331870  \n",
              "7          14775098            1342298         73557                 377432  \n",
              "8          15704281            1559060         86116                 389063  \n",
              "9          20133094            1889977         70840                 478799  \n",
              "10         14726480            1669177         44671                 326463  \n",
              "11         14561598            1374840         72686                 401437  \n",
              "12         16026593            1959118         89444                 396383  \n",
              "13         15895274            1332740         94475                 413711  \n",
              "14         17320121            1449468        117872                 468428  \n",
              "15          9988214             944102        145997                 553152  \n",
              "16         12327661            1279728        132644                 494971  \n",
              "17         15093605            1388116        107211                 404870  \n",
              "18         14915695            1347833        103844                 517913  \n",
              "19         20249314            2173170        108969                 490163  \n",
              "20         10516375             682408        119962                 438208  \n",
              "21         11327996            1029180        115348                 425668  \n",
              "22         10561939            1116334        128807                 482611  \n",
              "23         11158731            1232688        154729                 500533  \n",
              "24          9426018             755439        144450                 448666  \n",
              "25         10936159            1380297        133424                 504283  \n",
              "26         12356024            1169930        104818                 443476  \n",
              "27         11887316             902949        149581                 538414  \n",
              "28          9851426            1340869        134971                 353499  \n",
              "29          4949382             514343        113204                 415829  \n",
              "30          3111109             208282        137445                 466269  \n",
              "31          4108201             572155        114025                 338261  \n",
              "32          3342329             446283        117807                 334496  \n",
              "33         10285053             900638        111373                 442661  \n",
              "34         11810528            1504504        112721                 399510  \n",
              "35          9055794             858754         84128                 339691  \n",
              "36         15527661            2517756        114618                 482520  \n",
              "37         17950311            1459721         87563                 417909  \n",
              "38         18080293            2224365         98151                 403369  \n",
              "39         17209617            1986249         91357                 354881  \n",
              "40         17301018            1546768         94461                 501333  \n",
              "41         19045314            1542360         57897                 423528  \n",
              "42         19117272            1858032         86515                 375114  \n",
              "43         19915026            2069786         97348                 449815  \n",
              "44         17044898            1653723         79024                 333653  \n",
              "45         16251236            1553860         61024                 395166  \n",
              "46         23290747            2631821         50236                 401414  \n",
              "47         22364722            2538008         69141                 370833  \n",
              "48         17520794            1800547         93079                 264999  \n",
              "49         11029695            1793094        116509                 432627  \n",
              "50         13975373            1477695        113332                 465002  \n",
              "51         12992641            1329066        108632                 380672  \n",
              "52         13248562            1405761        106065                 412436  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-97bbd235-ed16-42be-94c5-922d211e884c\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Date</th>\n",
              "      <th>Sample_ID</th>\n",
              "      <th>MG unprocessed</th>\n",
              "      <th>MG retained pairs</th>\n",
              "      <th>MG retained singles</th>\n",
              "      <th>MG retained combined reads</th>\n",
              "      <th>MT unprocessed</th>\n",
              "      <th>MT retained pairs</th>\n",
              "      <th>MT retained singles</th>\n",
              "      <th>MT retained combined reads</th>\n",
              "      <th>MT rRNA pairs</th>\n",
              "      <th>MT rRNA singles</th>\n",
              "      <th>MT contigs</th>\n",
              "      <th>Co-assembly contigs</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2010-10-04 00:00:00</td>\n",
              "      <td>A01</td>\n",
              "      <td>17531630</td>\n",
              "      <td>16368148</td>\n",
              "      <td>1078317</td>\n",
              "      <td>33814613.0</td>\n",
              "      <td>56764165</td>\n",
              "      <td>46430755</td>\n",
              "      <td>1833300</td>\n",
              "      <td>94694810.0</td>\n",
              "      <td>8162922</td>\n",
              "      <td>211837</td>\n",
              "      <td>57491</td>\n",
              "      <td>126390</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2011-01-25 00:00:00</td>\n",
              "      <td>A02</td>\n",
              "      <td>14699402</td>\n",
              "      <td>13108258</td>\n",
              "      <td>1199766</td>\n",
              "      <td>27416282.0</td>\n",
              "      <td>16493393</td>\n",
              "      <td>9119940</td>\n",
              "      <td>1951440</td>\n",
              "      <td>20191320.0</td>\n",
              "      <td>4110417</td>\n",
              "      <td>775696</td>\n",
              "      <td>47726</td>\n",
              "      <td>208345</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2011-03-21 00:00:00</td>\n",
              "      <td>D37</td>\n",
              "      <td>35999747</td>\n",
              "      <td>32911158</td>\n",
              "      <td>2199347</td>\n",
              "      <td>68021663.0</td>\n",
              "      <td>35975301</td>\n",
              "      <td>13400496</td>\n",
              "      <td>2315369</td>\n",
              "      <td>29116361.0</td>\n",
              "      <td>17642665</td>\n",
              "      <td>2323133</td>\n",
              "      <td>61242</td>\n",
              "      <td>431078</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2011-03-29 00:00:00</td>\n",
              "      <td>D02</td>\n",
              "      <td>34135175</td>\n",
              "      <td>27721744</td>\n",
              "      <td>2837683</td>\n",
              "      <td>58281171.0</td>\n",
              "      <td>33912215</td>\n",
              "      <td>13612603</td>\n",
              "      <td>1826984</td>\n",
              "      <td>29052190.0</td>\n",
              "      <td>16504703</td>\n",
              "      <td>1719392</td>\n",
              "      <td>81321</td>\n",
              "      <td>443307</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2011-04-05 00:00:00</td>\n",
              "      <td>D39</td>\n",
              "      <td>28908243</td>\n",
              "      <td>26605828</td>\n",
              "      <td>1673538</td>\n",
              "      <td>54885194.0</td>\n",
              "      <td>38592454</td>\n",
              "      <td>17367979</td>\n",
              "      <td>2504144</td>\n",
              "      <td>37240102.0</td>\n",
              "      <td>16717068</td>\n",
              "      <td>1685117</td>\n",
              "      <td>118913</td>\n",
              "      <td>479608</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>2011-04-14 00:00:00</td>\n",
              "      <td>D24</td>\n",
              "      <td>29187268</td>\n",
              "      <td>27401321</td>\n",
              "      <td>1354513</td>\n",
              "      <td>56157155.0</td>\n",
              "      <td>36395674</td>\n",
              "      <td>18174395</td>\n",
              "      <td>2162663</td>\n",
              "      <td>38511453.0</td>\n",
              "      <td>14460847</td>\n",
              "      <td>1445338</td>\n",
              "      <td>130962</td>\n",
              "      <td>517506</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>2011-04-21 00:00:00</td>\n",
              "      <td>D25</td>\n",
              "      <td>25320222</td>\n",
              "      <td>20487745</td>\n",
              "      <td>4083256</td>\n",
              "      <td>45058746.0</td>\n",
              "      <td>33954127</td>\n",
              "      <td>13847740</td>\n",
              "      <td>1736581</td>\n",
              "      <td>29432061.0</td>\n",
              "      <td>16687126</td>\n",
              "      <td>1534912</td>\n",
              "      <td>91152</td>\n",
              "      <td>331870</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>2011-04-29 00:00:00</td>\n",
              "      <td>D35</td>\n",
              "      <td>30371838</td>\n",
              "      <td>27587583</td>\n",
              "      <td>1797893</td>\n",
              "      <td>56973059.0</td>\n",
              "      <td>29681622</td>\n",
              "      <td>12018746</td>\n",
              "      <td>1441649</td>\n",
              "      <td>25479141.0</td>\n",
              "      <td>14775098</td>\n",
              "      <td>1342298</td>\n",
              "      <td>73557</td>\n",
              "      <td>377432</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>2011-05-06 00:00:00</td>\n",
              "      <td>D46</td>\n",
              "      <td>28122705</td>\n",
              "      <td>25044633</td>\n",
              "      <td>2528946</td>\n",
              "      <td>52618212.0</td>\n",
              "      <td>34116436</td>\n",
              "      <td>13596582</td>\n",
              "      <td>2102990</td>\n",
              "      <td>29296154.0</td>\n",
              "      <td>15704281</td>\n",
              "      <td>1559060</td>\n",
              "      <td>86116</td>\n",
              "      <td>389063</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>2011-05-13 00:00:00</td>\n",
              "      <td>D13</td>\n",
              "      <td>31173943</td>\n",
              "      <td>29336922</td>\n",
              "      <td>1467456</td>\n",
              "      <td>60141300.0</td>\n",
              "      <td>35894482</td>\n",
              "      <td>12307140</td>\n",
              "      <td>1424327</td>\n",
              "      <td>26038607.0</td>\n",
              "      <td>20133094</td>\n",
              "      <td>1889977</td>\n",
              "      <td>70840</td>\n",
              "      <td>478799</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>2011-05-20 00:00:00</td>\n",
              "      <td>D40</td>\n",
              "      <td>25651909</td>\n",
              "      <td>24085668</td>\n",
              "      <td>1018577</td>\n",
              "      <td>49189913.0</td>\n",
              "      <td>27707752</td>\n",
              "      <td>9331432</td>\n",
              "      <td>1515442</td>\n",
              "      <td>20178306.0</td>\n",
              "      <td>14726480</td>\n",
              "      <td>1669177</td>\n",
              "      <td>44671</td>\n",
              "      <td>326463</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>2011-05-27 00:00:00</td>\n",
              "      <td>D33</td>\n",
              "      <td>30235782</td>\n",
              "      <td>28307886</td>\n",
              "      <td>1506824</td>\n",
              "      <td>58122596.0</td>\n",
              "      <td>27369514</td>\n",
              "      <td>10155882</td>\n",
              "      <td>1139082</td>\n",
              "      <td>21450846.0</td>\n",
              "      <td>14561598</td>\n",
              "      <td>1374840</td>\n",
              "      <td>72686</td>\n",
              "      <td>401437</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>2011-06-03 00:00:00</td>\n",
              "      <td>D06</td>\n",
              "      <td>30216637</td>\n",
              "      <td>26954409</td>\n",
              "      <td>1576187</td>\n",
              "      <td>55485005.0</td>\n",
              "      <td>32430876</td>\n",
              "      <td>12235924</td>\n",
              "      <td>1998252</td>\n",
              "      <td>26470100.0</td>\n",
              "      <td>16026593</td>\n",
              "      <td>1959118</td>\n",
              "      <td>89444</td>\n",
              "      <td>396383</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>2011-06-09 00:00:00</td>\n",
              "      <td>D27</td>\n",
              "      <td>27497422</td>\n",
              "      <td>25777061</td>\n",
              "      <td>1306125</td>\n",
              "      <td>52860247.0</td>\n",
              "      <td>30331588</td>\n",
              "      <td>11628944</td>\n",
              "      <td>1328863</td>\n",
              "      <td>24586751.0</td>\n",
              "      <td>15895274</td>\n",
              "      <td>1332740</td>\n",
              "      <td>94475</td>\n",
              "      <td>413711</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>2011-06-17 00:00:00</td>\n",
              "      <td>D42</td>\n",
              "      <td>27303250</td>\n",
              "      <td>25503950</td>\n",
              "      <td>1313167</td>\n",
              "      <td>52321067.0</td>\n",
              "      <td>34544359</td>\n",
              "      <td>14363643</td>\n",
              "      <td>1328939</td>\n",
              "      <td>30056225.0</td>\n",
              "      <td>17320121</td>\n",
              "      <td>1449468</td>\n",
              "      <td>117872</td>\n",
              "      <td>468428</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>2011-06-24 00:00:00</td>\n",
              "      <td>D03</td>\n",
              "      <td>32347395</td>\n",
              "      <td>29220419</td>\n",
              "      <td>1797971</td>\n",
              "      <td>60238809.0</td>\n",
              "      <td>32699565</td>\n",
              "      <td>18755346</td>\n",
              "      <td>2503880</td>\n",
              "      <td>40014572.0</td>\n",
              "      <td>9988214</td>\n",
              "      <td>944102</td>\n",
              "      <td>145997</td>\n",
              "      <td>553152</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>2011-07-01 00:00:00</td>\n",
              "      <td>D47</td>\n",
              "      <td>30109054</td>\n",
              "      <td>27730630</td>\n",
              "      <td>1936737</td>\n",
              "      <td>57397997.0</td>\n",
              "      <td>36766788</td>\n",
              "      <td>19790420</td>\n",
              "      <td>2959780</td>\n",
              "      <td>42540620.0</td>\n",
              "      <td>12327661</td>\n",
              "      <td>1279728</td>\n",
              "      <td>132644</td>\n",
              "      <td>494971</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>2011-07-08 00:00:00</td>\n",
              "      <td>D18</td>\n",
              "      <td>23391679</td>\n",
              "      <td>22164878</td>\n",
              "      <td>1066058</td>\n",
              "      <td>45395814.0</td>\n",
              "      <td>31924022</td>\n",
              "      <td>13802753</td>\n",
              "      <td>1538828</td>\n",
              "      <td>29144334.0</td>\n",
              "      <td>15093605</td>\n",
              "      <td>1388116</td>\n",
              "      <td>107211</td>\n",
              "      <td>404870</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>2011-08-05 00:00:00</td>\n",
              "      <td>D45</td>\n",
              "      <td>29930665</td>\n",
              "      <td>27829830</td>\n",
              "      <td>1644918</td>\n",
              "      <td>57304578.0</td>\n",
              "      <td>35378306</td>\n",
              "      <td>15997138</td>\n",
              "      <td>2372196</td>\n",
              "      <td>34366472.0</td>\n",
              "      <td>14915695</td>\n",
              "      <td>1347833</td>\n",
              "      <td>103844</td>\n",
              "      <td>517913</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>2011-08-11 00:00:00</td>\n",
              "      <td>D51</td>\n",
              "      <td>29852842</td>\n",
              "      <td>26901508</td>\n",
              "      <td>2115968</td>\n",
              "      <td>55918984.0</td>\n",
              "      <td>44174409</td>\n",
              "      <td>18564123</td>\n",
              "      <td>2671740</td>\n",
              "      <td>39799986.0</td>\n",
              "      <td>20249314</td>\n",
              "      <td>2173170</td>\n",
              "      <td>108969</td>\n",
              "      <td>490163</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>2011-08-19 00:00:00</td>\n",
              "      <td>D43</td>\n",
              "      <td>26075473</td>\n",
              "      <td>24281057</td>\n",
              "      <td>1444335</td>\n",
              "      <td>50006449.0</td>\n",
              "      <td>27171859</td>\n",
              "      <td>14640598</td>\n",
              "      <td>1251988</td>\n",
              "      <td>30533184.0</td>\n",
              "      <td>10516375</td>\n",
              "      <td>682408</td>\n",
              "      <td>119962</td>\n",
              "      <td>438208</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>2011-08-29 00:00:00</td>\n",
              "      <td>D34</td>\n",
              "      <td>30403109</td>\n",
              "      <td>28058664</td>\n",
              "      <td>2030863</td>\n",
              "      <td>58148191.0</td>\n",
              "      <td>28421236</td>\n",
              "      <td>14285422</td>\n",
              "      <td>1622021</td>\n",
              "      <td>30192865.0</td>\n",
              "      <td>11327996</td>\n",
              "      <td>1029180</td>\n",
              "      <td>115348</td>\n",
              "      <td>425668</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>2011-09-05 00:00:00</td>\n",
              "      <td>D30</td>\n",
              "      <td>30532662</td>\n",
              "      <td>28718715</td>\n",
              "      <td>1490886</td>\n",
              "      <td>58928316.0</td>\n",
              "      <td>29515165</td>\n",
              "      <td>15646084</td>\n",
              "      <td>2024810</td>\n",
              "      <td>33316978.0</td>\n",
              "      <td>10561939</td>\n",
              "      <td>1116334</td>\n",
              "      <td>128807</td>\n",
              "      <td>482611</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>2011-09-12 00:00:00</td>\n",
              "      <td>D04</td>\n",
              "      <td>29014224</td>\n",
              "      <td>25778552</td>\n",
              "      <td>1730152</td>\n",
              "      <td>53287256.0</td>\n",
              "      <td>35007981</td>\n",
              "      <td>19311266</td>\n",
              "      <td>2775618</td>\n",
              "      <td>41398150.0</td>\n",
              "      <td>11158731</td>\n",
              "      <td>1232688</td>\n",
              "      <td>154729</td>\n",
              "      <td>500533</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>2011-09-19 00:00:00</td>\n",
              "      <td>D31</td>\n",
              "      <td>25456037</td>\n",
              "      <td>23744583</td>\n",
              "      <td>1302766</td>\n",
              "      <td>48791932.0</td>\n",
              "      <td>30499924</td>\n",
              "      <td>18342790</td>\n",
              "      <td>1783389</td>\n",
              "      <td>38468969.0</td>\n",
              "      <td>9426018</td>\n",
              "      <td>755439</td>\n",
              "      <td>144450</td>\n",
              "      <td>448666</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>2011-09-28 00:00:00</td>\n",
              "      <td>D29</td>\n",
              "      <td>29839175</td>\n",
              "      <td>27199081</td>\n",
              "      <td>2226114</td>\n",
              "      <td>56624276.0</td>\n",
              "      <td>33708983</td>\n",
              "      <td>17931937</td>\n",
              "      <td>2782354</td>\n",
              "      <td>38646228.0</td>\n",
              "      <td>10936159</td>\n",
              "      <td>1380297</td>\n",
              "      <td>133424</td>\n",
              "      <td>504283</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>2011-10-05 00:00:00</td>\n",
              "      <td>D49</td>\n",
              "      <td>29042305</td>\n",
              "      <td>26641829</td>\n",
              "      <td>1400099</td>\n",
              "      <td>54683757.0</td>\n",
              "      <td>29639609</td>\n",
              "      <td>14248134</td>\n",
              "      <td>1675031</td>\n",
              "      <td>30171299.0</td>\n",
              "      <td>12356024</td>\n",
              "      <td>1169930</td>\n",
              "      <td>104818</td>\n",
              "      <td>443476</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>2011-10-12 00:00:00</td>\n",
              "      <td>D32</td>\n",
              "      <td>28460125</td>\n",
              "      <td>26905139</td>\n",
              "      <td>1280844</td>\n",
              "      <td>55091122.0</td>\n",
              "      <td>31894222</td>\n",
              "      <td>17448520</td>\n",
              "      <td>1520300</td>\n",
              "      <td>36417340.0</td>\n",
              "      <td>11887316</td>\n",
              "      <td>902949</td>\n",
              "      <td>149581</td>\n",
              "      <td>538414</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>2011-11-02 00:00:00</td>\n",
              "      <td>D23</td>\n",
              "      <td>23448618</td>\n",
              "      <td>18851501</td>\n",
              "      <td>3923449</td>\n",
              "      <td>41626451.0</td>\n",
              "      <td>32127592</td>\n",
              "      <td>18036232</td>\n",
              "      <td>2631682</td>\n",
              "      <td>38704146.0</td>\n",
              "      <td>9851426</td>\n",
              "      <td>1340869</td>\n",
              "      <td>134971</td>\n",
              "      <td>353499</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>2011-11-07 00:00:00</td>\n",
              "      <td>D44</td>\n",
              "      <td>27963482</td>\n",
              "      <td>24897807</td>\n",
              "      <td>2376671</td>\n",
              "      <td>52172285.0</td>\n",
              "      <td>23803138</td>\n",
              "      <td>16386146</td>\n",
              "      <td>1843356</td>\n",
              "      <td>34615648.0</td>\n",
              "      <td>4949382</td>\n",
              "      <td>514343</td>\n",
              "      <td>113204</td>\n",
              "      <td>415829</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30</th>\n",
              "      <td>2011-11-16 00:00:00</td>\n",
              "      <td>D20</td>\n",
              "      <td>32139021</td>\n",
              "      <td>30421843</td>\n",
              "      <td>1283367</td>\n",
              "      <td>62127053.0</td>\n",
              "      <td>33469570</td>\n",
              "      <td>28141065</td>\n",
              "      <td>1936802</td>\n",
              "      <td>58218932.0</td>\n",
              "      <td>3111109</td>\n",
              "      <td>208282</td>\n",
              "      <td>137445</td>\n",
              "      <td>466269</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31</th>\n",
              "      <td>2011-11-23 00:00:00</td>\n",
              "      <td>D15</td>\n",
              "      <td>26973299</td>\n",
              "      <td>24536053</td>\n",
              "      <td>1365590</td>\n",
              "      <td>50437696.0</td>\n",
              "      <td>35418302</td>\n",
              "      <td>26585849</td>\n",
              "      <td>4005009</td>\n",
              "      <td>57176707.0</td>\n",
              "      <td>4108201</td>\n",
              "      <td>572155</td>\n",
              "      <td>114025</td>\n",
              "      <td>338261</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32</th>\n",
              "      <td>2011-11-29 00:00:00</td>\n",
              "      <td>D05</td>\n",
              "      <td>25621580</td>\n",
              "      <td>22949103</td>\n",
              "      <td>773926</td>\n",
              "      <td>46672132.0</td>\n",
              "      <td>32499996</td>\n",
              "      <td>25199023</td>\n",
              "      <td>3264871</td>\n",
              "      <td>53662917.0</td>\n",
              "      <td>3342329</td>\n",
              "      <td>446283</td>\n",
              "      <td>117807</td>\n",
              "      <td>334496</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>33</th>\n",
              "      <td>2011-12-21 00:00:00</td>\n",
              "      <td>D28</td>\n",
              "      <td>29329592</td>\n",
              "      <td>27574163</td>\n",
              "      <td>1289080</td>\n",
              "      <td>56437406.0</td>\n",
              "      <td>34336596</td>\n",
              "      <td>20937720</td>\n",
              "      <td>2097177</td>\n",
              "      <td>43972617.0</td>\n",
              "      <td>10285053</td>\n",
              "      <td>900638</td>\n",
              "      <td>111373</td>\n",
              "      <td>442661</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>34</th>\n",
              "      <td>2011-12-28 00:00:00</td>\n",
              "      <td>D09</td>\n",
              "      <td>31138147</td>\n",
              "      <td>25898148</td>\n",
              "      <td>3088153</td>\n",
              "      <td>54884449.0</td>\n",
              "      <td>33883001</td>\n",
              "      <td>17654965</td>\n",
              "      <td>2767161</td>\n",
              "      <td>38077091.0</td>\n",
              "      <td>11810528</td>\n",
              "      <td>1504504</td>\n",
              "      <td>112721</td>\n",
              "      <td>399510</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35</th>\n",
              "      <td>2012-01-03 00:00:00</td>\n",
              "      <td>D38</td>\n",
              "      <td>24493806</td>\n",
              "      <td>22681193</td>\n",
              "      <td>991272</td>\n",
              "      <td>46353658.0</td>\n",
              "      <td>23571029</td>\n",
              "      <td>12051161</td>\n",
              "      <td>1421055</td>\n",
              "      <td>25523377.0</td>\n",
              "      <td>9055794</td>\n",
              "      <td>858754</td>\n",
              "      <td>84128</td>\n",
              "      <td>339691</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>36</th>\n",
              "      <td>2012-01-11 00:00:00</td>\n",
              "      <td>D36</td>\n",
              "      <td>34928806</td>\n",
              "      <td>32014419</td>\n",
              "      <td>2069892</td>\n",
              "      <td>66098730.0</td>\n",
              "      <td>37853692</td>\n",
              "      <td>16360403</td>\n",
              "      <td>3039172</td>\n",
              "      <td>35759978.0</td>\n",
              "      <td>15527661</td>\n",
              "      <td>2517756</td>\n",
              "      <td>114618</td>\n",
              "      <td>482520</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>37</th>\n",
              "      <td>2012-01-19 00:00:00</td>\n",
              "      <td>D12</td>\n",
              "      <td>26256782</td>\n",
              "      <td>24765672</td>\n",
              "      <td>1183841</td>\n",
              "      <td>50715185.0</td>\n",
              "      <td>32078032</td>\n",
              "      <td>11415158</td>\n",
              "      <td>1142644</td>\n",
              "      <td>23972960.0</td>\n",
              "      <td>17950311</td>\n",
              "      <td>1459721</td>\n",
              "      <td>87563</td>\n",
              "      <td>417909</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38</th>\n",
              "      <td>2012-01-25 00:00:00</td>\n",
              "      <td>D10</td>\n",
              "      <td>32576299</td>\n",
              "      <td>28822117</td>\n",
              "      <td>2112865</td>\n",
              "      <td>59757099.0</td>\n",
              "      <td>35356100</td>\n",
              "      <td>12792706</td>\n",
              "      <td>2064782</td>\n",
              "      <td>27650194.0</td>\n",
              "      <td>18080293</td>\n",
              "      <td>2224365</td>\n",
              "      <td>98151</td>\n",
              "      <td>403369</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39</th>\n",
              "      <td>2012-02-01 00:00:00</td>\n",
              "      <td>D14</td>\n",
              "      <td>26995145</td>\n",
              "      <td>22067691</td>\n",
              "      <td>2719767</td>\n",
              "      <td>46855149.0</td>\n",
              "      <td>33583347</td>\n",
              "      <td>12404420</td>\n",
              "      <td>1860511</td>\n",
              "      <td>26669351.0</td>\n",
              "      <td>17209617</td>\n",
              "      <td>1986249</td>\n",
              "      <td>91357</td>\n",
              "      <td>354881</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>40</th>\n",
              "      <td>2012-02-08 00:00:00</td>\n",
              "      <td>D08</td>\n",
              "      <td>33462713</td>\n",
              "      <td>29590993</td>\n",
              "      <td>2191955</td>\n",
              "      <td>61373941.0</td>\n",
              "      <td>32414295</td>\n",
              "      <td>11974617</td>\n",
              "      <td>1443747</td>\n",
              "      <td>25392981.0</td>\n",
              "      <td>17301018</td>\n",
              "      <td>1546768</td>\n",
              "      <td>94461</td>\n",
              "      <td>501333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>41</th>\n",
              "      <td>2012-02-14 00:00:00</td>\n",
              "      <td>D26</td>\n",
              "      <td>29242844</td>\n",
              "      <td>27118676</td>\n",
              "      <td>1565421</td>\n",
              "      <td>55802773.0</td>\n",
              "      <td>31735326</td>\n",
              "      <td>9954805</td>\n",
              "      <td>1106915</td>\n",
              "      <td>21016525.0</td>\n",
              "      <td>19045314</td>\n",
              "      <td>1542360</td>\n",
              "      <td>57897</td>\n",
              "      <td>423528</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>42</th>\n",
              "      <td>2012-02-23 00:00:00</td>\n",
              "      <td>D21</td>\n",
              "      <td>24350474</td>\n",
              "      <td>22754752</td>\n",
              "      <td>1033309</td>\n",
              "      <td>46542813.0</td>\n",
              "      <td>34301246</td>\n",
              "      <td>11506763</td>\n",
              "      <td>1627570</td>\n",
              "      <td>24641096.0</td>\n",
              "      <td>19117272</td>\n",
              "      <td>1858032</td>\n",
              "      <td>86515</td>\n",
              "      <td>375114</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>43</th>\n",
              "      <td>2012-02-29 00:00:00</td>\n",
              "      <td>D19</td>\n",
              "      <td>32574065</td>\n",
              "      <td>28288700</td>\n",
              "      <td>3165796</td>\n",
              "      <td>59743196.0</td>\n",
              "      <td>36394504</td>\n",
              "      <td>12496491</td>\n",
              "      <td>1734078</td>\n",
              "      <td>26727060.0</td>\n",
              "      <td>19915026</td>\n",
              "      <td>2069786</td>\n",
              "      <td>97348</td>\n",
              "      <td>449815</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>44</th>\n",
              "      <td>2012-03-08 00:00:00</td>\n",
              "      <td>D17</td>\n",
              "      <td>23876138</td>\n",
              "      <td>22226625</td>\n",
              "      <td>1033784</td>\n",
              "      <td>45487034.0</td>\n",
              "      <td>30362735</td>\n",
              "      <td>10236878</td>\n",
              "      <td>1340616</td>\n",
              "      <td>21814372.0</td>\n",
              "      <td>17044898</td>\n",
              "      <td>1653723</td>\n",
              "      <td>79024</td>\n",
              "      <td>333653</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45</th>\n",
              "      <td>2012-03-14 00:00:00</td>\n",
              "      <td>D41</td>\n",
              "      <td>30626165</td>\n",
              "      <td>28490276</td>\n",
              "      <td>1515664</td>\n",
              "      <td>58496216.0</td>\n",
              "      <td>27396429</td>\n",
              "      <td>8434111</td>\n",
              "      <td>1040702</td>\n",
              "      <td>17908924.0</td>\n",
              "      <td>16251236</td>\n",
              "      <td>1553860</td>\n",
              "      <td>61024</td>\n",
              "      <td>395166</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>46</th>\n",
              "      <td>2012-03-22 00:00:00</td>\n",
              "      <td>D11</td>\n",
              "      <td>29495784</td>\n",
              "      <td>27691057</td>\n",
              "      <td>1348071</td>\n",
              "      <td>56730185.0</td>\n",
              "      <td>35677196</td>\n",
              "      <td>8436575</td>\n",
              "      <td>1195654</td>\n",
              "      <td>18068804.0</td>\n",
              "      <td>23290747</td>\n",
              "      <td>2631821</td>\n",
              "      <td>50236</td>\n",
              "      <td>401414</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>47</th>\n",
              "      <td>2012-03-28 00:00:00</td>\n",
              "      <td>D16</td>\n",
              "      <td>28186198</td>\n",
              "      <td>26162520</td>\n",
              "      <td>1081186</td>\n",
              "      <td>53406226.0</td>\n",
              "      <td>36820589</td>\n",
              "      <td>10406024</td>\n",
              "      <td>1424590</td>\n",
              "      <td>22236638.0</td>\n",
              "      <td>22364722</td>\n",
              "      <td>2538008</td>\n",
              "      <td>69141</td>\n",
              "      <td>370833</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>2012-04-04 00:00:00</td>\n",
              "      <td>D07</td>\n",
              "      <td>21699617</td>\n",
              "      <td>15940878</td>\n",
              "      <td>3465313</td>\n",
              "      <td>35347069.0</td>\n",
              "      <td>34514784</td>\n",
              "      <td>13143860</td>\n",
              "      <td>1791203</td>\n",
              "      <td>28078923.0</td>\n",
              "      <td>17520794</td>\n",
              "      <td>1800547</td>\n",
              "      <td>93079</td>\n",
              "      <td>264999</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>49</th>\n",
              "      <td>2012-04-10 00:00:00</td>\n",
              "      <td>D22</td>\n",
              "      <td>33671265</td>\n",
              "      <td>30670757</td>\n",
              "      <td>2094658</td>\n",
              "      <td>63436172.0</td>\n",
              "      <td>34097677</td>\n",
              "      <td>17817055</td>\n",
              "      <td>3145665</td>\n",
              "      <td>38779775.0</td>\n",
              "      <td>11029695</td>\n",
              "      <td>1793094</td>\n",
              "      <td>116509</td>\n",
              "      <td>432627</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50</th>\n",
              "      <td>2012-04-17 00:00:00</td>\n",
              "      <td>D01</td>\n",
              "      <td>32692858</td>\n",
              "      <td>27975133</td>\n",
              "      <td>2329138</td>\n",
              "      <td>58279404.0</td>\n",
              "      <td>33418152</td>\n",
              "      <td>15582015</td>\n",
              "      <td>2155159</td>\n",
              "      <td>33319189.0</td>\n",
              "      <td>13975373</td>\n",
              "      <td>1477695</td>\n",
              "      <td>113332</td>\n",
              "      <td>465002</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>51</th>\n",
              "      <td>2012-04-25 00:00:00</td>\n",
              "      <td>D50</td>\n",
              "      <td>24359112</td>\n",
              "      <td>22277277</td>\n",
              "      <td>1450478</td>\n",
              "      <td>46005032.0</td>\n",
              "      <td>32882193</td>\n",
              "      <td>16384859</td>\n",
              "      <td>1888715</td>\n",
              "      <td>34658433.0</td>\n",
              "      <td>12992641</td>\n",
              "      <td>1329066</td>\n",
              "      <td>108632</td>\n",
              "      <td>380672</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>52</th>\n",
              "      <td>2012-05-03 00:00:00</td>\n",
              "      <td>D48</td>\n",
              "      <td>27267336</td>\n",
              "      <td>25359794</td>\n",
              "      <td>1619284</td>\n",
              "      <td>52338872.0</td>\n",
              "      <td>32450531</td>\n",
              "      <td>15443434</td>\n",
              "      <td>2107587</td>\n",
              "      <td>32994455.0</td>\n",
              "      <td>13248562</td>\n",
              "      <td>1405761</td>\n",
              "      <td>106065</td>\n",
              "      <td>412436</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-97bbd235-ed16-42be-94c5-922d211e884c')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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            ]
          },
          "metadata": {},
          "execution_count": 71
        }
      ],
      "source": [
        "df.head(-3)"
      ]
    },
    {
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      "execution_count": null,
      "id": "2d11b827",
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        "colab": {
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      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(56, 14)"
            ]
          },
          "metadata": {},
          "execution_count": 72
        }
      ],
      "source": [
        "df.shape"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "6db5c33d",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 399
        },
        "id": "6db5c33d",
        "outputId": "fa206de6-3c04-46d0-fd0a-1d02e5bf991f"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        MG unprocessed    MG retained pairs    MG retained singles   \\\n",
              "count      5.600000e+01         5.600000e+01           5.600000e+01   \n",
              "mean       5.429936e+07         4.918503e+07           3.455527e+06   \n",
              "std        1.973367e+08         1.787400e+08           1.254280e+07   \n",
              "min        4.025168e+06         3.847016e+06           7.455080e+05   \n",
              "25%        2.596958e+07         2.400040e+07           1.299344e+06   \n",
              "50%        2.902826e+07         2.662383e+07           1.570804e+06   \n",
              "75%        3.055604e+07         2.799602e+07           2.134965e+06   \n",
              "max        1.504179e+09         1.362404e+09           9.548124e+07   \n",
              "\n",
              "       MG retained combined reads   MT unprocessed   MT retained pairs   \\\n",
              "count                5.600000e+01     5.600000e+01         5.600000e+01   \n",
              "mean                 1.018122e+08     6.323675e+07         2.989163e+07   \n",
              "std                  3.700023e+08     2.297830e+08         1.085055e+08   \n",
              "min                  7.687894e+06     5.388215e+06         6.065706e+06   \n",
              "25%                  4.909042e+07     3.046563e+07         1.204306e+07   \n",
              "50%                  5.488482e+07     3.344386e+07         1.432453e+07   \n",
              "75%                  5.818099e+07     3.536165e+07         1.784578e+07   \n",
              "max                  2.820290e+09     1.751412e+09         8.261391e+08   \n",
              "\n",
              "        MT retained singles   MT retained combined reads   MT rRNA pairs   \\\n",
              "count           5.600000e+01                5.600000e+01     5.600000e+01   \n",
              "mean            3.766779e+06                6.354454e+07     2.649410e+07   \n",
              "std             1.367587e+07                2.306717e+08     9.618476e+07   \n",
              "min             6.374010e+05                1.246086e+07     3.111109e+06   \n",
              "25%             1.443222e+06                2.551232e+07     1.084260e+07   \n",
              "50%             1.851934e+06                3.018208e+07     1.464404e+07   \n",
              "75%             2.329576e+06                3.847959e+07     1.723247e+07   \n",
              "max             1.041684e+08                1.756447e+09     7.325523e+08   \n",
              "\n",
              "        MT rRNA singles    MT contigs    Co-assembly contigs   \n",
              "count       5.600000e+01  5.600000e+01           5.600000e+01  \n",
              "mean        2.728589e+06  1.929647e+05           7.941149e+05  \n",
              "std         9.904567e+06  7.007343e+05           2.885052e+06  \n",
              "min         2.082820e+05  2.753400e+04           7.909200e+04  \n",
              "25%         1.094546e+06  8.342625e+04           3.768525e+05  \n",
              "50%         1.434072e+06  1.043310e+05           4.168690e+05  \n",
              "75%         1.737818e+06  1.178232e+05           4.710208e+05  \n",
              "max         7.540872e+07  5.338878e+06           2.198824e+07  "
            ],
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              "\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>MG unprocessed</th>\n",
              "      <th>MG retained pairs</th>\n",
              "      <th>MG retained singles</th>\n",
              "      <th>MG retained combined reads</th>\n",
              "      <th>MT unprocessed</th>\n",
              "      <th>MT retained pairs</th>\n",
              "      <th>MT retained singles</th>\n",
              "      <th>MT retained combined reads</th>\n",
              "      <th>MT rRNA pairs</th>\n",
              "      <th>MT rRNA singles</th>\n",
              "      <th>MT contigs</th>\n",
              "      <th>Co-assembly contigs</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>5.600000e+01</td>\n",
              "      <td>5.600000e+01</td>\n",
              "      <td>5.600000e+01</td>\n",
              "      <td>5.600000e+01</td>\n",
              "      <td>5.600000e+01</td>\n",
              "      <td>5.600000e+01</td>\n",
              "      <td>5.600000e+01</td>\n",
              "      <td>5.600000e+01</td>\n",
              "      <td>5.600000e+01</td>\n",
              "      <td>5.600000e+01</td>\n",
              "      <td>5.600000e+01</td>\n",
              "      <td>5.600000e+01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>5.429936e+07</td>\n",
              "      <td>4.918503e+07</td>\n",
              "      <td>3.455527e+06</td>\n",
              "      <td>1.018122e+08</td>\n",
              "      <td>6.323675e+07</td>\n",
              "      <td>2.989163e+07</td>\n",
              "      <td>3.766779e+06</td>\n",
              "      <td>6.354454e+07</td>\n",
              "      <td>2.649410e+07</td>\n",
              "      <td>2.728589e+06</td>\n",
              "      <td>1.929647e+05</td>\n",
              "      <td>7.941149e+05</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>1.973367e+08</td>\n",
              "      <td>1.787400e+08</td>\n",
              "      <td>1.254280e+07</td>\n",
              "      <td>3.700023e+08</td>\n",
              "      <td>2.297830e+08</td>\n",
              "      <td>1.085055e+08</td>\n",
              "      <td>1.367587e+07</td>\n",
              "      <td>2.306717e+08</td>\n",
              "      <td>9.618476e+07</td>\n",
              "      <td>9.904567e+06</td>\n",
              "      <td>7.007343e+05</td>\n",
              "      <td>2.885052e+06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>4.025168e+06</td>\n",
              "      <td>3.847016e+06</td>\n",
              "      <td>7.455080e+05</td>\n",
              "      <td>7.687894e+06</td>\n",
              "      <td>5.388215e+06</td>\n",
              "      <td>6.065706e+06</td>\n",
              "      <td>6.374010e+05</td>\n",
              "      <td>1.246086e+07</td>\n",
              "      <td>3.111109e+06</td>\n",
              "      <td>2.082820e+05</td>\n",
              "      <td>2.753400e+04</td>\n",
              "      <td>7.909200e+04</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>2.596958e+07</td>\n",
              "      <td>2.400040e+07</td>\n",
              "      <td>1.299344e+06</td>\n",
              "      <td>4.909042e+07</td>\n",
              "      <td>3.046563e+07</td>\n",
              "      <td>1.204306e+07</td>\n",
              "      <td>1.443222e+06</td>\n",
              "      <td>2.551232e+07</td>\n",
              "      <td>1.084260e+07</td>\n",
              "      <td>1.094546e+06</td>\n",
              "      <td>8.342625e+04</td>\n",
              "      <td>3.768525e+05</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>2.902826e+07</td>\n",
              "      <td>2.662383e+07</td>\n",
              "      <td>1.570804e+06</td>\n",
              "      <td>5.488482e+07</td>\n",
              "      <td>3.344386e+07</td>\n",
              "      <td>1.432453e+07</td>\n",
              "      <td>1.851934e+06</td>\n",
              "      <td>3.018208e+07</td>\n",
              "      <td>1.464404e+07</td>\n",
              "      <td>1.434072e+06</td>\n",
              "      <td>1.043310e+05</td>\n",
              "      <td>4.168690e+05</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>3.055604e+07</td>\n",
              "      <td>2.799602e+07</td>\n",
              "      <td>2.134965e+06</td>\n",
              "      <td>5.818099e+07</td>\n",
              "      <td>3.536165e+07</td>\n",
              "      <td>1.784578e+07</td>\n",
              "      <td>2.329576e+06</td>\n",
              "      <td>3.847959e+07</td>\n",
              "      <td>1.723247e+07</td>\n",
              "      <td>1.737818e+06</td>\n",
              "      <td>1.178232e+05</td>\n",
              "      <td>4.710208e+05</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>1.504179e+09</td>\n",
              "      <td>1.362404e+09</td>\n",
              "      <td>9.548124e+07</td>\n",
              "      <td>2.820290e+09</td>\n",
              "      <td>1.751412e+09</td>\n",
              "      <td>8.261391e+08</td>\n",
              "      <td>1.041684e+08</td>\n",
              "      <td>1.756447e+09</td>\n",
              "      <td>7.325523e+08</td>\n",
              "      <td>7.540872e+07</td>\n",
              "      <td>5.338878e+06</td>\n",
              "      <td>2.198824e+07</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-f8e5a67f-082f-4ce3-b434-dc0e73608a07')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
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              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-f8e5a67f-082f-4ce3-b434-dc0e73608a07 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-f8e5a67f-082f-4ce3-b434-dc0e73608a07');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "          element.appendChild(docLink);\n",
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              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 73
        }
      ],
      "source": [
        "df.describe()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "0c23bfce",
      "metadata": {
        "id": "0c23bfce"
      },
      "outputs": [],
      "source": [
        "df.dropna(inplace=True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "2f813d55",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2f813d55",
        "outputId": "9912d62b-23d1-4d01-b4ed-4e66734a3d34"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              " Date                         0\n",
              " Sample_ID                    0\n",
              " MG unprocessed               0\n",
              " MG retained pairs            0\n",
              " MG retained singles          0\n",
              "MG retained combined reads    0\n",
              " MT unprocessed               0\n",
              " MT retained pairs            0\n",
              " MT retained singles          0\n",
              "MT retained combined reads    0\n",
              " MT rRNA pairs                0\n",
              " MT rRNA singles              0\n",
              " MT contigs                   0\n",
              " Co-assembly contigs          0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 75
        }
      ],
      "source": [
        "df.isnull().sum()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "3bf1042e",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3bf1042e",
        "outputId": "2f171f8c-12d3-4824-d4f7-c7771ae40ee1"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Int64Index: 53 entries, 0 to 52\n",
            "Data columns (total 14 columns):\n",
            " #   Column                      Non-Null Count  Dtype  \n",
            "---  ------                      --------------  -----  \n",
            " 0    Date                       53 non-null     object \n",
            " 1    Sample_ID                  53 non-null     object \n",
            " 2    MG unprocessed             53 non-null     int64  \n",
            " 3    MG retained pairs          53 non-null     int64  \n",
            " 4    MG retained singles        53 non-null     int64  \n",
            " 5   MG retained combined reads  53 non-null     float64\n",
            " 6    MT unprocessed             53 non-null     int64  \n",
            " 7    MT retained pairs          53 non-null     int64  \n",
            " 8    MT retained singles        53 non-null     int64  \n",
            " 9   MT retained combined reads  53 non-null     float64\n",
            " 10   MT rRNA pairs              53 non-null     int64  \n",
            " 11   MT rRNA singles            53 non-null     int64  \n",
            " 12   MT contigs                 53 non-null     int64  \n",
            " 13   Co-assembly contigs        53 non-null     int64  \n",
            "dtypes: float64(2), int64(10), object(2)\n",
            "memory usage: 6.2+ KB\n"
          ]
        }
      ],
      "source": [
        "df.info()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "62684fd8",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 621
        },
        "id": "62684fd8",
        "outputId": "b0679b93-4d35-4942-d89d-9f6141ad60f6"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1080x576 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "source": [
        "plt.figure(figsize = (15,8))\n",
        "sns.heatmap(df.corr(),annot=True,cmap='Blues')\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "8fc39e3f",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8fc39e3f",
        "outputId": "16bb3b72-bc16-4a3a-834a-3acd5b1f1a0c"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index([' Date ', ' Sample_ID ', ' MG unprocessed ', ' MG retained pairs ',\n",
              "       ' MG retained singles ', 'MG retained combined reads',\n",
              "       ' MT unprocessed', ' MT retained pairs ', ' MT retained singles ',\n",
              "       'MT retained combined reads', ' MT rRNA pairs ', ' MT rRNA singles ',\n",
              "       ' MT contigs ', ' Co-assembly contigs '],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 78
        }
      ],
      "source": [
        "df.columns"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "3e23b28b",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "3e23b28b",
        "outputId": "96fe91f9-08bb-4dc2-8e8c-67ed6f9cb403"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     MG unprocessed    MT retained pairs    MT retained singles   \\\n",
              "0           17531630             46430755                1833300   \n",
              "1           14699402              9119940                1951440   \n",
              "2           35999747             13400496                2315369   \n",
              "3           34135175             13612603                1826984   \n",
              "4           28908243             17367979                2504144   \n",
              "5           29187268             18174395                2162663   \n",
              "6           25320222             13847740                1736581   \n",
              "7           30371838             12018746                1441649   \n",
              "8           28122705             13596582                2102990   \n",
              "9           31173943             12307140                1424327   \n",
              "10          25651909              9331432                1515442   \n",
              "11          30235782             10155882                1139082   \n",
              "12          30216637             12235924                1998252   \n",
              "13          27497422             11628944                1328863   \n",
              "14          27303250             14363643                1328939   \n",
              "15          32347395             18755346                2503880   \n",
              "16          30109054             19790420                2959780   \n",
              "17          23391679             13802753                1538828   \n",
              "18          29930665             15997138                2372196   \n",
              "19          29852842             18564123                2671740   \n",
              "20          26075473             14640598                1251988   \n",
              "21          30403109             14285422                1622021   \n",
              "22          30532662             15646084                2024810   \n",
              "23          29014224             19311266                2775618   \n",
              "24          25456037             18342790                1783389   \n",
              "25          29839175             17931937                2782354   \n",
              "26          29042305             14248134                1675031   \n",
              "27          28460125             17448520                1520300   \n",
              "28          23448618             18036232                2631682   \n",
              "29          27963482             16386146                1843356   \n",
              "30          32139021             28141065                1936802   \n",
              "31          26973299             26585849                4005009   \n",
              "32          25621580             25199023                3264871   \n",
              "33          29329592             20937720                2097177   \n",
              "34          31138147             17654965                2767161   \n",
              "35          24493806             12051161                1421055   \n",
              "36          34928806             16360403                3039172   \n",
              "37          26256782             11415158                1142644   \n",
              "38          32576299             12792706                2064782   \n",
              "39          26995145             12404420                1860511   \n",
              "40          33462713             11974617                1443747   \n",
              "41          29242844              9954805                1106915   \n",
              "42          24350474             11506763                1627570   \n",
              "43          32574065             12496491                1734078   \n",
              "44          23876138             10236878                1340616   \n",
              "45          30626165              8434111                1040702   \n",
              "46          29495784              8436575                1195654   \n",
              "47          28186198             10406024                1424590   \n",
              "48          21699617             13143860                1791203   \n",
              "49          33671265             17817055                3145665   \n",
              "50          32692858             15582015                2155159   \n",
              "51          24359112             16384859                1888715   \n",
              "52          27267336             15443434                2107587   \n",
              "\n",
              "    MT retained combined reads  \n",
              "0                   94694810.0  \n",
              "1                   20191320.0  \n",
              "2                   29116361.0  \n",
              "3                   29052190.0  \n",
              "4                   37240102.0  \n",
              "5                   38511453.0  \n",
              "6                   29432061.0  \n",
              "7                   25479141.0  \n",
              "8                   29296154.0  \n",
              "9                   26038607.0  \n",
              "10                  20178306.0  \n",
              "11                  21450846.0  \n",
              "12                  26470100.0  \n",
              "13                  24586751.0  \n",
              "14                  30056225.0  \n",
              "15                  40014572.0  \n",
              "16                  42540620.0  \n",
              "17                  29144334.0  \n",
              "18                  34366472.0  \n",
              "19                  39799986.0  \n",
              "20                  30533184.0  \n",
              "21                  30192865.0  \n",
              "22                  33316978.0  \n",
              "23                  41398150.0  \n",
              "24                  38468969.0  \n",
              "25                  38646228.0  \n",
              "26                  30171299.0  \n",
              "27                  36417340.0  \n",
              "28                  38704146.0  \n",
              "29                  34615648.0  \n",
              "30                  58218932.0  \n",
              "31                  57176707.0  \n",
              "32                  53662917.0  \n",
              "33                  43972617.0  \n",
              "34                  38077091.0  \n",
              "35                  25523377.0  \n",
              "36                  35759978.0  \n",
              "37                  23972960.0  \n",
              "38                  27650194.0  \n",
              "39                  26669351.0  \n",
              "40                  25392981.0  \n",
              "41                  21016525.0  \n",
              "42                  24641096.0  \n",
              "43                  26727060.0  \n",
              "44                  21814372.0  \n",
              "45                  17908924.0  \n",
              "46                  18068804.0  \n",
              "47                  22236638.0  \n",
              "48                  28078923.0  \n",
              "49                  38779775.0  \n",
              "50                  33319189.0  \n",
              "51                  34658433.0  \n",
              "52                  32994455.0  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-583a538c-b5c9-402a-90d3-659be2a637db\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>MG unprocessed</th>\n",
              "      <th>MT retained pairs</th>\n",
              "      <th>MT retained singles</th>\n",
              "      <th>MT retained combined reads</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>17531630</td>\n",
              "      <td>46430755</td>\n",
              "      <td>1833300</td>\n",
              "      <td>94694810.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>14699402</td>\n",
              "      <td>9119940</td>\n",
              "      <td>1951440</td>\n",
              "      <td>20191320.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>35999747</td>\n",
              "      <td>13400496</td>\n",
              "      <td>2315369</td>\n",
              "      <td>29116361.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>34135175</td>\n",
              "      <td>13612603</td>\n",
              "      <td>1826984</td>\n",
              "      <td>29052190.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>28908243</td>\n",
              "      <td>17367979</td>\n",
              "      <td>2504144</td>\n",
              "      <td>37240102.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>29187268</td>\n",
              "      <td>18174395</td>\n",
              "      <td>2162663</td>\n",
              "      <td>38511453.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>25320222</td>\n",
              "      <td>13847740</td>\n",
              "      <td>1736581</td>\n",
              "      <td>29432061.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>30371838</td>\n",
              "      <td>12018746</td>\n",
              "      <td>1441649</td>\n",
              "      <td>25479141.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>28122705</td>\n",
              "      <td>13596582</td>\n",
              "      <td>2102990</td>\n",
              "      <td>29296154.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>31173943</td>\n",
              "      <td>12307140</td>\n",
              "      <td>1424327</td>\n",
              "      <td>26038607.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>25651909</td>\n",
              "      <td>9331432</td>\n",
              "      <td>1515442</td>\n",
              "      <td>20178306.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>30235782</td>\n",
              "      <td>10155882</td>\n",
              "      <td>1139082</td>\n",
              "      <td>21450846.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>30216637</td>\n",
              "      <td>12235924</td>\n",
              "      <td>1998252</td>\n",
              "      <td>26470100.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>27497422</td>\n",
              "      <td>11628944</td>\n",
              "      <td>1328863</td>\n",
              "      <td>24586751.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>27303250</td>\n",
              "      <td>14363643</td>\n",
              "      <td>1328939</td>\n",
              "      <td>30056225.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>32347395</td>\n",
              "      <td>18755346</td>\n",
              "      <td>2503880</td>\n",
              "      <td>40014572.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>30109054</td>\n",
              "      <td>19790420</td>\n",
              "      <td>2959780</td>\n",
              "      <td>42540620.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>23391679</td>\n",
              "      <td>13802753</td>\n",
              "      <td>1538828</td>\n",
              "      <td>29144334.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>29930665</td>\n",
              "      <td>15997138</td>\n",
              "      <td>2372196</td>\n",
              "      <td>34366472.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>29852842</td>\n",
              "      <td>18564123</td>\n",
              "      <td>2671740</td>\n",
              "      <td>39799986.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>26075473</td>\n",
              "      <td>14640598</td>\n",
              "      <td>1251988</td>\n",
              "      <td>30533184.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>30403109</td>\n",
              "      <td>14285422</td>\n",
              "      <td>1622021</td>\n",
              "      <td>30192865.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>30532662</td>\n",
              "      <td>15646084</td>\n",
              "      <td>2024810</td>\n",
              "      <td>33316978.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>29014224</td>\n",
              "      <td>19311266</td>\n",
              "      <td>2775618</td>\n",
              "      <td>41398150.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>25456037</td>\n",
              "      <td>18342790</td>\n",
              "      <td>1783389</td>\n",
              "      <td>38468969.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>29839175</td>\n",
              "      <td>17931937</td>\n",
              "      <td>2782354</td>\n",
              "      <td>38646228.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>29042305</td>\n",
              "      <td>14248134</td>\n",
              "      <td>1675031</td>\n",
              "      <td>30171299.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>28460125</td>\n",
              "      <td>17448520</td>\n",
              "      <td>1520300</td>\n",
              "      <td>36417340.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>23448618</td>\n",
              "      <td>18036232</td>\n",
              "      <td>2631682</td>\n",
              "      <td>38704146.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>27963482</td>\n",
              "      <td>16386146</td>\n",
              "      <td>1843356</td>\n",
              "      <td>34615648.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30</th>\n",
              "      <td>32139021</td>\n",
              "      <td>28141065</td>\n",
              "      <td>1936802</td>\n",
              "      <td>58218932.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31</th>\n",
              "      <td>26973299</td>\n",
              "      <td>26585849</td>\n",
              "      <td>4005009</td>\n",
              "      <td>57176707.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32</th>\n",
              "      <td>25621580</td>\n",
              "      <td>25199023</td>\n",
              "      <td>3264871</td>\n",
              "      <td>53662917.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>33</th>\n",
              "      <td>29329592</td>\n",
              "      <td>20937720</td>\n",
              "      <td>2097177</td>\n",
              "      <td>43972617.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>34</th>\n",
              "      <td>31138147</td>\n",
              "      <td>17654965</td>\n",
              "      <td>2767161</td>\n",
              "      <td>38077091.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35</th>\n",
              "      <td>24493806</td>\n",
              "      <td>12051161</td>\n",
              "      <td>1421055</td>\n",
              "      <td>25523377.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>36</th>\n",
              "      <td>34928806</td>\n",
              "      <td>16360403</td>\n",
              "      <td>3039172</td>\n",
              "      <td>35759978.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>37</th>\n",
              "      <td>26256782</td>\n",
              "      <td>11415158</td>\n",
              "      <td>1142644</td>\n",
              "      <td>23972960.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38</th>\n",
              "      <td>32576299</td>\n",
              "      <td>12792706</td>\n",
              "      <td>2064782</td>\n",
              "      <td>27650194.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39</th>\n",
              "      <td>26995145</td>\n",
              "      <td>12404420</td>\n",
              "      <td>1860511</td>\n",
              "      <td>26669351.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>40</th>\n",
              "      <td>33462713</td>\n",
              "      <td>11974617</td>\n",
              "      <td>1443747</td>\n",
              "      <td>25392981.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>41</th>\n",
              "      <td>29242844</td>\n",
              "      <td>9954805</td>\n",
              "      <td>1106915</td>\n",
              "      <td>21016525.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>42</th>\n",
              "      <td>24350474</td>\n",
              "      <td>11506763</td>\n",
              "      <td>1627570</td>\n",
              "      <td>24641096.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>43</th>\n",
              "      <td>32574065</td>\n",
              "      <td>12496491</td>\n",
              "      <td>1734078</td>\n",
              "      <td>26727060.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>44</th>\n",
              "      <td>23876138</td>\n",
              "      <td>10236878</td>\n",
              "      <td>1340616</td>\n",
              "      <td>21814372.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45</th>\n",
              "      <td>30626165</td>\n",
              "      <td>8434111</td>\n",
              "      <td>1040702</td>\n",
              "      <td>17908924.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>46</th>\n",
              "      <td>29495784</td>\n",
              "      <td>8436575</td>\n",
              "      <td>1195654</td>\n",
              "      <td>18068804.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>47</th>\n",
              "      <td>28186198</td>\n",
              "      <td>10406024</td>\n",
              "      <td>1424590</td>\n",
              "      <td>22236638.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>21699617</td>\n",
              "      <td>13143860</td>\n",
              "      <td>1791203</td>\n",
              "      <td>28078923.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>49</th>\n",
              "      <td>33671265</td>\n",
              "      <td>17817055</td>\n",
              "      <td>3145665</td>\n",
              "      <td>38779775.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50</th>\n",
              "      <td>32692858</td>\n",
              "      <td>15582015</td>\n",
              "      <td>2155159</td>\n",
              "      <td>33319189.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>51</th>\n",
              "      <td>24359112</td>\n",
              "      <td>16384859</td>\n",
              "      <td>1888715</td>\n",
              "      <td>34658433.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>52</th>\n",
              "      <td>27267336</td>\n",
              "      <td>15443434</td>\n",
              "      <td>2107587</td>\n",
              "      <td>32994455.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-583a538c-b5c9-402a-90d3-659be2a637db')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-583a538c-b5c9-402a-90d3-659be2a637db button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-583a538c-b5c9-402a-90d3-659be2a637db');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 79
        }
      ],
      "source": [
        "numrilcal_df=df[[' MG unprocessed ',' MT retained pairs ',' MT retained singles ','MT retained combined reads']]\n",
        "numrilcal_df"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from scipy.stats import ttest_ind, ttest_ind_from_stats"
      ],
      "metadata": {
        "id": "KhcH4G3p_IDq"
      },
      "id": "KhcH4G3p_IDq",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(15,8))\n",
        "sns.boxplot(data=numrilcal_df)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 494
        },
        "id": "6hJgyYXxdIaL",
        "outputId": "c7014153-e04f-4d06-d78d-443c34d0b2b5"
      },
      "id": "6hJgyYXxdIaL",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1080x576 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.columns"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VGb5oyTyDhCO",
        "outputId": "59409c46-c449-4d33-b583-846cf29f02fb"
      },
      "id": "VGb5oyTyDhCO",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index([' Date ', ' Sample_ID ', ' MG unprocessed ', ' MG retained pairs ',\n",
              "       ' MG retained singles ', 'MG retained combined reads',\n",
              "       ' MT unprocessed', ' MT retained pairs ', ' MT retained singles ',\n",
              "       'MT retained combined reads', ' MT rRNA pairs ', ' MT rRNA singles ',\n",
              "       ' MT contigs ', ' Co-assembly contigs '],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 82
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.loc[df['MG retained combined reads']==df['MG retained combined reads'].max()]\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 214
        },
        "id": "CZjLrWL19dGH",
        "outputId": "77cc5755-d0cf-452d-e24b-e879d07dc348"
      },
      "id": "CZjLrWL19dGH",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                 Date   Sample_ID    MG unprocessed    MG retained pairs   \\\n",
              "2  2011-03-21 00:00:00        D37           35999747             32911158   \n",
              "\n",
              "    MG retained singles   MG retained combined reads   MT unprocessed  \\\n",
              "2                2199347                  68021663.0         35975301   \n",
              "\n",
              "    MT retained pairs    MT retained singles   MT retained combined reads  \\\n",
              "2             13400496                2315369                  29116361.0   \n",
              "\n",
              "    MT rRNA pairs    MT rRNA singles    MT contigs    Co-assembly contigs   \n",
              "2         17642665            2323133         61242                 431078  "
            ],
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              "      <th>Date</th>\n",
              "      <th>Sample_ID</th>\n",
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              "      <th>MG retained singles</th>\n",
              "      <th>MG retained combined reads</th>\n",
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              "      <th>MT retained pairs</th>\n",
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              "      <th>2</th>\n",
              "      <td>2011-03-21 00:00:00</td>\n",
              "      <td>D37</td>\n",
              "      <td>35999747</td>\n",
              "      <td>32911158</td>\n",
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              "      <td>17642665</td>\n",
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              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-7c2abccc-7c0f-4212-a2a3-7e2485b9d8f2 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-7c2abccc-7c0f-4212-a2a3-7e2485b9d8f2');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 83
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "\n",
        "df[' MT contigs '].hist(figsize = (5, 5))\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 320
        },
        "id": "619vuARfZ0nc",
        "outputId": "207256d5-bf4a-4a54-f4b5-0d04a6ae53a7"
      },
      "id": "619vuARfZ0nc",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "4bb3746e",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 320
        },
        "id": "4bb3746e",
        "outputId": "4c46db39-acce-4abc-a09d-59dfecbf116c"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ],
            "image/png": 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y8/Fm1XeBTrO80kfaTjX+2DLjnGKONdU8fbsXeAI4QO9s5MnMPLFMjc/01aw/DjyfZ/99eP4p5lhL7wXeCfy4uX+qOjZ6rwAJfCEiDkXvE0dQ+LF8OgO9haSaiBgDPg38fmb+sLnUAEBmZkSs6UvRw5hj0Vz/C7w0Is4FPgP8wjDmHbaIuAp4IjMPRcTkqOsZktdk5tGI+DngQEQ8uHhltcfy6Xgm14iI59ALuI9n5m3N8LGI2N6s307vrAdW/kjbqcZ3LjN+qjmGIjOfBO6m93Tq3Ig4+R/f4hqf6atZvw34Ps/++/D9U8yxVl4N/FpEHKH3m3JeC7zvFHVs5F4ByMyjzdcn6P0H9go2wWN5JYYcvVeYgA8DhzPzPYtW3Q6cfFXpBnrX6k6Ov7l5ZepS4Hhzmn4n8IaIOK95ZekN9K7DPA78MCIubeZ685JjLTfHmomIFzRncETEVnrXHw/TC7url6llcY1XA1/M3oWX24FrmlckLwReTO+i9LIf+Wv2WWmONZGZezNzZ2aON3V8MTOvO0UdG7ZXgIg4OyLOOblM7zF4H0Ufy6sy6ouC6+EGvIbedYxvAPc2tyvoXVe5C3gY+Cfg/Gb7oPcLQx8F5oHuomO9FXikub1l0XiX3oPtUeAD/OSN2MvOscb9vgT4WtPvfcCfNOMvovcP9xHgU8DzmvEzm/uPNOtftOhY72p6eojmVbZm/Ap6r1I/Crxr0fiycwzp5zzJT15dLdlrM+fXm9v9J+up+lhezc1PPEgqzaerkkoz5CSVZshJKs2Qk1SaISepNENOUmmGnKTSDDlJpf0fsL7zMoxgVaIAAAAASUVORK5CYII=\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "source": [
        "import matplotlib.pyplot as plt\n",
        "\n",
        "df[' Co-assembly contigs '].hist(figsize = (5, 5))\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import seaborn as sns\n",
        "sns.distplot(df[' Co-assembly contigs '])\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 346
        },
        "id": "6tna5CwObgBZ",
        "outputId": "93a21cbb-7749-449a-c05b-d31e14e44df3"
      },
      "id": "6tna5CwObgBZ",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.8/dist-packages/seaborn/distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
            "  warnings.warn(msg, FutureWarning)\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#dentify the contigs that are outside the Interquartile range (IQR) \n",
        "contigs_size = df[' Co-assembly contigs ']\n",
        "contigs_size_outliers = contigs_size[(contigs_size > contigs_size.quantile(0.75)) | (contigs_size < contigs_size.quantile(0.25))]\n",
        "print(contigs_size_outliers)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "QsxQ4g01bwCE",
        "outputId": "152e0cf9-1a1c-4f89-89b4-d7fd8baf8587"
      },
      "id": "QsxQ4g01bwCE",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0     126390\n",
            "1     208345\n",
            "4     479608\n",
            "5     517506\n",
            "6     331870\n",
            "9     478799\n",
            "10    326463\n",
            "15    553152\n",
            "16    494971\n",
            "18    517913\n",
            "19    490163\n",
            "22    482611\n",
            "23    500533\n",
            "25    504283\n",
            "27    538414\n",
            "28    353499\n",
            "31    338261\n",
            "32    334496\n",
            "35    339691\n",
            "36    482520\n",
            "39    354881\n",
            "40    501333\n",
            "42    375114\n",
            "44    333653\n",
            "47    370833\n",
            "48    264999\n",
            "Name:  Co-assembly contigs , dtype: int64\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_filtered = df[(df[' Co-assembly contigs '] > contigs_size.quantile(0.25)) & (df[' Co-assembly contigs '] < contigs_size.quantile(0.75))]\n",
        "print(df_filtered)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "RHdUHYWOcaR2",
        "outputId": "0cd075ba-0a1d-451d-c8c5-9df445ea2e54"
      },
      "id": "RHdUHYWOcaR2",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "                  Date   Sample_ID    MG unprocessed    MG retained pairs   \\\n",
            "2   2011-03-21 00:00:00        D37           35999747             32911158   \n",
            "3   2011-03-29 00:00:00        D02           34135175             27721744   \n",
            "8   2011-05-06 00:00:00        D46           28122705             25044633   \n",
            "11  2011-05-27 00:00:00        D33           30235782             28307886   \n",
            "12  2011-06-03 00:00:00        D06           30216637             26954409   \n",
            "13  2011-06-09 00:00:00        D27           27497422             25777061   \n",
            "17  2011-07-08 00:00:00        D18           23391679             22164878   \n",
            "20  2011-08-19 00:00:00        D43           26075473             24281057   \n",
            "21  2011-08-29 00:00:00        D34           30403109             28058664   \n",
            "24  2011-09-19 00:00:00        D31           25456037             23744583   \n",
            "26  2011-10-05 00:00:00        D49           29042305             26641829   \n",
            "29  2011-11-07 00:00:00        D44           27963482             24897807   \n",
            "30  2011-11-16 00:00:00        D20           32139021             30421843   \n",
            "33  2011-12-21 00:00:00        D28           29329592             27574163   \n",
            "34  2011-12-28 00:00:00        D09           31138147             25898148   \n",
            "37  2012-01-19 00:00:00        D12           26256782             24765672   \n",
            "38  2012-01-25 00:00:00        D10           32576299             28822117   \n",
            "41  2012-02-14 00:00:00        D26           29242844             27118676   \n",
            "43  2012-02-29 00:00:00        D19           32574065             28288700   \n",
            "45  2012-03-14 00:00:00        D41           30626165             28490276   \n",
            "46  2012-03-22 00:00:00        D11           29495784             27691057   \n",
            "49  2012-04-10 00:00:00        D22           33671265             30670757   \n",
            "50  2012-04-17 00:00:00        D01           32692858             27975133   \n",
            "51  2012-04-25 00:00:00        D50           24359112             22277277   \n",
            "52  2012-05-03 00:00:00        D48           27267336             25359794   \n",
            "\n",
            "     MG retained singles   MG retained combined reads   MT unprocessed  \\\n",
            "2                 2199347                  68021663.0         35975301   \n",
            "3                 2837683                  58281171.0         33912215   \n",
            "8                 2528946                  52618212.0         34116436   \n",
            "11                1506824                  58122596.0         27369514   \n",
            "12                1576187                  55485005.0         32430876   \n",
            "13                1306125                  52860247.0         30331588   \n",
            "17                1066058                  45395814.0         31924022   \n",
            "20                1444335                  50006449.0         27171859   \n",
            "21                2030863                  58148191.0         28421236   \n",
            "24                1302766                  48791932.0         30499924   \n",
            "26                1400099                  54683757.0         29639609   \n",
            "29                2376671                  52172285.0         23803138   \n",
            "30                1283367                  62127053.0         33469570   \n",
            "33                1289080                  56437406.0         34336596   \n",
            "34                3088153                  54884449.0         33883001   \n",
            "37                1183841                  50715185.0         32078032   \n",
            "38                2112865                  59757099.0         35356100   \n",
            "41                1565421                  55802773.0         31735326   \n",
            "43                3165796                  59743196.0         36394504   \n",
            "45                1515664                  58496216.0         27396429   \n",
            "46                1348071                  56730185.0         35677196   \n",
            "49                2094658                  63436172.0         34097677   \n",
            "50                2329138                  58279404.0         33418152   \n",
            "51                1450478                  46005032.0         32882193   \n",
            "52                1619284                  52338872.0         32450531   \n",
            "\n",
            "     MT retained pairs    MT retained singles   MT retained combined reads  \\\n",
            "2              13400496                2315369                  29116361.0   \n",
            "3              13612603                1826984                  29052190.0   \n",
            "8              13596582                2102990                  29296154.0   \n",
            "11             10155882                1139082                  21450846.0   \n",
            "12             12235924                1998252                  26470100.0   \n",
            "13             11628944                1328863                  24586751.0   \n",
            "17             13802753                1538828                  29144334.0   \n",
            "20             14640598                1251988                  30533184.0   \n",
            "21             14285422                1622021                  30192865.0   \n",
            "24             18342790                1783389                  38468969.0   \n",
            "26             14248134                1675031                  30171299.0   \n",
            "29             16386146                1843356                  34615648.0   \n",
            "30             28141065                1936802                  58218932.0   \n",
            "33             20937720                2097177                  43972617.0   \n",
            "34             17654965                2767161                  38077091.0   \n",
            "37             11415158                1142644                  23972960.0   \n",
            "38             12792706                2064782                  27650194.0   \n",
            "41              9954805                1106915                  21016525.0   \n",
            "43             12496491                1734078                  26727060.0   \n",
            "45              8434111                1040702                  17908924.0   \n",
            "46              8436575                1195654                  18068804.0   \n",
            "49             17817055                3145665                  38779775.0   \n",
            "50             15582015                2155159                  33319189.0   \n",
            "51             16384859                1888715                  34658433.0   \n",
            "52             15443434                2107587                  32994455.0   \n",
            "\n",
            "     MT rRNA pairs    MT rRNA singles    MT contigs    Co-assembly contigs   \n",
            "2          17642665            2323133         61242                 431078  \n",
            "3          16504703            1719392         81321                 443307  \n",
            "8          15704281            1559060         86116                 389063  \n",
            "11         14561598            1374840         72686                 401437  \n",
            "12         16026593            1959118         89444                 396383  \n",
            "13         15895274            1332740         94475                 413711  \n",
            "17         15093605            1388116        107211                 404870  \n",
            "20         10516375             682408        119962                 438208  \n",
            "21         11327996            1029180        115348                 425668  \n",
            "24          9426018             755439        144450                 448666  \n",
            "26         12356024            1169930        104818                 443476  \n",
            "29          4949382             514343        113204                 415829  \n",
            "30          3111109             208282        137445                 466269  \n",
            "33         10285053             900638        111373                 442661  \n",
            "34         11810528            1504504        112721                 399510  \n",
            "37         17950311            1459721         87563                 417909  \n",
            "38         18080293            2224365         98151                 403369  \n",
            "41         19045314            1542360         57897                 423528  \n",
            "43         19915026            2069786         97348                 449815  \n",
            "45         16251236            1553860         61024                 395166  \n",
            "46         23290747            2631821         50236                 401414  \n",
            "49         11029695            1793094        116509                 432627  \n",
            "50         13975373            1477695        113332                 465002  \n",
            "51         12992641            1329066        108632                 380672  \n",
            "52         13248562            1405761        106065                 412436  \n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.plot.scatter(x=' Co-assembly contigs ', y=' Date ')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 279
        },
        "id": "q-HtkBhXcwCv",
        "outputId": "0505547b-37f1-4876-d85e-57cf24f2021f"
      },
      "id": "q-HtkBhXcwCv",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize = (15,8))\n",
        "sns.relplot(data=df, x=' Co-assembly contigs ', y=' Date ', palette='Set2', hue=' Sample_ID ')\n",
        "plt.show"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 881
        },
        "id": "Yy1DX6QbeWOL",
        "outputId": "6d62c125-6ebc-41ac-dba6-190f3d535c12"
      },
      "id": "Yy1DX6QbeWOL",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<function matplotlib.pyplot.show(*args, **kw)>"
            ]
          },
          "metadata": {},
          "execution_count": 91
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1080x576 with 0 Axes>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 427.125x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "49f6a02c",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 768
        },
        "id": "49f6a02c",
        "outputId": "db7d266a-01f5-4745-a857-e470c0dd26e8"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                             MG unprocessed    MG retained pairs   \\\n",
              " MG unprocessed                     1.000000             0.952400   \n",
              " MG retained pairs                  0.952400             1.000000   \n",
              " MG retained singles                0.208983            -0.056677   \n",
              "MG retained combined reads          0.973426             0.995302   \n",
              " MT unprocessed                     0.119196             0.097039   \n",
              " MT retained pairs                 -0.169508            -0.145806   \n",
              " MT retained singles                0.173503             0.098607   \n",
              "MT retained combined reads         -0.156151            -0.136907   \n",
              " MT rRNA pairs                      0.281115             0.246053   \n",
              " MT rRNA singles                    0.395628             0.318440   \n",
              " MT contigs                         0.210807             0.194090   \n",
              " Co-assembly contigs                0.735662             0.771168   \n",
              "\n",
              "                             MG retained singles   MG retained combined reads  \\\n",
              " MG unprocessed                          0.208983                    0.973426   \n",
              " MG retained pairs                      -0.056677                    0.995302   \n",
              " MG retained singles                     1.000000                    0.040249   \n",
              "MG retained combined reads               0.040249                    1.000000   \n",
              " MT unprocessed                          0.100225                    0.106835   \n",
              " MT retained pairs                      -0.089192                   -0.154572   \n",
              " MT retained singles                     0.212918                    0.119332   \n",
              "MT retained combined reads              -0.075942                   -0.144381   \n",
              " MT rRNA pairs                           0.159559                    0.261722   \n",
              " MT rRNA singles                         0.277068                    0.345562   \n",
              " MT contigs                              0.126198                    0.206483   \n",
              " Co-assembly contigs                     0.009540                    0.772709   \n",
              "\n",
              "                             MT unprocessed   MT retained pairs   \\\n",
              " MG unprocessed                    0.119196            -0.169508   \n",
              " MG retained pairs                 0.097039            -0.145806   \n",
              " MG retained singles               0.100225            -0.089192   \n",
              "MG retained combined reads         0.106835            -0.154572   \n",
              " MT unprocessed                    1.000000             0.621936   \n",
              " MT retained pairs                 0.621936             1.000000   \n",
              " MT retained singles               0.296561             0.497610   \n",
              "MT retained combined reads         0.620663             0.999015   \n",
              " MT rRNA pairs                     0.273452            -0.571400   \n",
              " MT rRNA singles                   0.210843            -0.577521   \n",
              " MT contigs                        0.062241             0.367836   \n",
              " Co-assembly contigs              -0.004626            -0.167888   \n",
              "\n",
              "                             MT retained singles   MT retained combined reads  \\\n",
              " MG unprocessed                          0.173503                   -0.156151   \n",
              " MG retained pairs                       0.098607                   -0.136907   \n",
              " MG retained singles                     0.212918                   -0.075942   \n",
              "MG retained combined reads               0.119332                   -0.144381   \n",
              " MT unprocessed                          0.296561                    0.620663   \n",
              " MT retained pairs                       0.497610                    0.999015   \n",
              " MT retained singles                     1.000000                    0.535606   \n",
              "MT retained combined reads               0.535606                    1.000000   \n",
              " MT rRNA pairs                          -0.439196                   -0.578758   \n",
              " MT rRNA singles                        -0.105733                   -0.567660   \n",
              " MT contigs                              0.499802                    0.383676   \n",
              " Co-assembly contigs                     0.131441                   -0.156725   \n",
              "\n",
              "                             MT rRNA pairs    MT rRNA singles    MT contigs   \\\n",
              " MG unprocessed                    0.281115           0.395628      0.210807   \n",
              " MG retained pairs                 0.246053           0.318440      0.194090   \n",
              " MG retained singles               0.159559           0.277068      0.126198   \n",
              "MG retained combined reads         0.261722           0.345562      0.206483   \n",
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              " MT rRNA pairs                     1.000000           0.870482     -0.428398   \n",
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              " MT contigs                       -0.428398          -0.361737      1.000000   \n",
              " Co-assembly contigs               0.167374           0.156281      0.590033   \n",
              "\n",
              "                             Co-assembly contigs   \n",
              " MG unprocessed                          0.735662  \n",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ],
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "\n",
        "df2 = pd.DataFrame(df)\n",
        "corr = df2.corr(method ='pearson')\n",
        "corr"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df3=df2.iloc[0:4,:]"
      ],
      "metadata": {
        "id": "ouyiQycCQLZk"
      },
      "id": "ouyiQycCQLZk",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df3"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 360
        },
        "id": "0bFSjD2Kq5jq",
        "outputId": "4504f666-e4f0-4ccc-dd27-ba127876430e"
      },
      "id": "0bFSjD2Kq5jq",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "                 Date   Sample_ID    MG unprocessed    MG retained pairs   \\\n",
              "0  2010-10-04 00:00:00        A01           17531630             16368148   \n",
              "1  2011-01-25 00:00:00        A02           14699402             13108258   \n",
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              "\n",
              "    MG retained singles   MG retained combined reads   MT unprocessed  \\\n",
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              "\n",
              "    MT retained pairs    MT retained singles   MT retained combined reads  \\\n",
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              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-d7adb691-5c23-4af0-8f85-6a20dfea86f7')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-d7adb691-5c23-4af0-8f85-6a20dfea86f7 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-d7adb691-5c23-4af0-8f85-6a20dfea86f7');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sns.relplot(data=df2, x=' MG unprocessed ', y=' Date ')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 387
        },
        "id": "ibWV8WhuhXIl",
        "outputId": "2ca7599f-a08b-4652-b412-32442d20f405"
      },
      "id": "ibWV8WhuhXIl",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.FacetGrid at 0x7f7bb58d14f0>"
            ]
          },
          "metadata": {},
          "execution_count": 21
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "plt.figure(figsize = (30,8))\n",
        "sns.lineplot(data=df, x=' Sample_ID ', y=' Date ')\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 293
        },
        "id": "R48sKtFNpukT",
        "outputId": "b2b84e8a-976b-4c79-a2d8-43e52f984c1f"
      },
      "id": "R48sKtFNpukT",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f7bb3714880>"
            ]
          },
          "metadata": {},
          "execution_count": 22
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 2160x576 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sns.relplot(data=df, x=' MG unprocessed ', y=' Date ', kind=\"line\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 387
        },
        "id": "JrYhRrkHiY8-",
        "outputId": "0809cf1a-6681-43d7-bb7f-fa755912a4e6"
      },
      "id": "JrYhRrkHiY8-",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.FacetGrid at 0x7f7bb36b5d90>"
            ]
          },
          "metadata": {},
          "execution_count": 23
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#*Encoding data*\n"
      ],
      "metadata": {
        "id": "vMZA9oZFu01O"
      },
      "id": "vMZA9oZFu01O"
    },
    {
      "cell_type": "code",
      "source": [
        "data_modeling=df.copy()"
      ],
      "metadata": {
        "id": "DqN3xGRWtykW"
      },
      "id": "DqN3xGRWtykW",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.preprocessing import OneHotEncoder\n",
        "import pandas as pd\n",
        "\n",
        "# Initialize the OneHotEncoder\n",
        "encoder = OneHotEncoder()\n",
        "\n",
        "# Create a copy of the dataframe\n",
        "data_modeling_encoded = data_modeling.copy()\n",
        "\n",
        "# Specify the columns to be one-hot encoded\n",
        "columns_to_encode = [\" MG unprocessed \", \" MG retained pairs \", \" MG retained singles \", \" MT contigs \", \" MT retained pairs \", \" MT retained singles \"]\n",
        "\n",
        "# Fit and transform the specified columns\n",
        "for column in columns_to_encode:\n",
        "    data_temp = data_modeling[[column]]\n",
        "    encoder.fit(data_temp)\n",
        "    temp = encoder.transform(data_temp).toarray()\n",
        "    temp = pd.DataFrame(temp, columns=[(column + \"_\" + str(i)) for i in encoder.categories_[0]])\n",
        "    data_modeling_encoded = data_modeling_encoded.drop(column, axis=1)\n",
        "    data_modeling_encoded = data_modeling_encoded.join(temp)"
      ],
      "metadata": {
        "id": "tbxEKo9Wfomh"
      },
      "id": "tbxEKo9Wfomh",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "'''from sklearn import preprocessing\n",
        "encoding=preprocessing.LabelEncoder()\n",
        "data_modeling[\" MG unprocessed \"]=encoding.fit_transform(data_modeling[\" MG unprocessed \"])\n",
        "data_modeling[\" MG retained pairs \"]=encoding.fit_transform(data_modeling[\" MG retained pairs \"])\n",
        "data_modeling[\" MG retained singles \"]=encoding.fit_transform(data_modeling[\" MG retained singles \"])\n",
        "data_modeling[\" MT contigs \"]=encoding.fit_transform(data_modeling[\" MT contigs \"])\n",
        "data_modeling[\" MT retained pairs \"]=encoding.fit_transform(data_modeling[\" MT retained pairs \"])\n",
        "data_modeling[\" MT retained singles \"]=encoding.fit_transform(data_modeling[\" MT retained singles \"])'''"
      ],
      "metadata": {
        "id": "QBdOypQdzLmd"
      },
      "id": "QBdOypQdzLmd",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "data_modeling"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "9SVkiqLO0cW3",
        "outputId": "4806fc20-c02d-4862-b066-668afd9a4cc3"
      },
      "id": "9SVkiqLO0cW3",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                  Date   Sample_ID    MG unprocessed    MG retained pairs   \\\n",
              "0   2010-10-04 00:00:00        A01                  1                    2   \n",
              "1   2011-01-25 00:00:00        A02                  0                    0   \n",
              "2   2011-03-21 00:00:00        D37                 52                   52   \n",
              "3   2011-03-29 00:00:00        D02                 50                   36   \n",
              "4   2011-04-05 00:00:00        D39                 24                   25   \n",
              "5   2011-04-14 00:00:00        D24                 27                   32   \n",
              "6   2011-04-21 00:00:00        D25                  9                    4   \n",
              "7   2011-04-29 00:00:00        D35                 37                   34   \n",
              "8   2011-05-06 00:00:00        D46                 21                   18   \n",
              "9   2011-05-13 00:00:00        D13                 42                   47   \n",
              "10  2011-05-20 00:00:00        D40                 12                   13   \n",
              "11  2011-05-27 00:00:00        D33                 36                   42   \n",
              "12  2011-06-03 00:00:00        D06                 35                   29   \n",
              "13  2011-06-09 00:00:00        D27                 19                   21   \n",
              "14  2011-06-17 00:00:00        D42                 18                   20   \n",
              "15  2011-06-24 00:00:00        D03                 44                   46   \n",
              "16  2011-07-01 00:00:00        D47                 34                   37   \n",
              "17  2011-07-08 00:00:00        D18                  3                    6   \n",
              "18  2011-08-05 00:00:00        D45                 33                   38   \n",
              "19  2011-08-11 00:00:00        D51                 32                   27   \n",
              "20  2011-08-19 00:00:00        D43                 13                   14   \n",
              "21  2011-08-29 00:00:00        D34                 38                   40   \n",
              "22  2011-09-05 00:00:00        D30                 39                   44   \n",
              "23  2011-09-12 00:00:00        D04                 25                   22   \n",
              "24  2011-09-19 00:00:00        D31                 10                   12   \n",
              "25  2011-09-28 00:00:00        D29                 31                   31   \n",
              "26  2011-10-05 00:00:00        D49                 26                   26   \n",
              "27  2011-10-12 00:00:00        D32                 23                   28   \n",
              "28  2011-11-02 00:00:00        D23                  4                    3   \n",
              "29  2011-11-07 00:00:00        D44                 20                   17   \n",
              "30  2011-11-16 00:00:00        D20                 43                   49   \n",
              "31  2011-11-23 00:00:00        D15                 15                   15   \n",
              "32  2011-11-29 00:00:00        D05                 11                   11   \n",
              "33  2011-12-21 00:00:00        D28                 29                   33   \n",
              "34  2011-12-28 00:00:00        D09                 41                   23   \n",
              "35  2012-01-03 00:00:00        D38                  8                    9   \n",
              "36  2012-01-11 00:00:00        D36                 51                   51   \n",
              "37  2012-01-19 00:00:00        D12                 14                   16   \n",
              "38  2012-01-25 00:00:00        D10                 46                   45   \n",
              "39  2012-02-01 00:00:00        D14                 16                    5   \n",
              "40  2012-02-08 00:00:00        D08                 48                   48   \n",
              "41  2012-02-14 00:00:00        D26                 28                   30   \n",
              "42  2012-02-23 00:00:00        D21                  6                   10   \n",
              "43  2012-02-29 00:00:00        D19                 45                   41   \n",
              "44  2012-03-08 00:00:00        D17                  5                    7   \n",
              "45  2012-03-14 00:00:00        D41                 40                   43   \n",
              "46  2012-03-22 00:00:00        D11                 30                   35   \n",
              "47  2012-03-28 00:00:00        D16                 22                   24   \n",
              "48  2012-04-04 00:00:00        D07                  2                    1   \n",
              "49  2012-04-10 00:00:00        D22                 49                   50   \n",
              "50  2012-04-17 00:00:00        D01                 47                   39   \n",
              "51  2012-04-25 00:00:00        D50                  7                    8   \n",
              "52  2012-05-03 00:00:00        D48                 17                   19   \n",
              "\n",
              "     MG retained singles   MG retained combined reads   MT unprocessed  \\\n",
              "0                       6                  33814613.0         56764165   \n",
              "1                       9                  27416282.0         16493393   \n",
              "2                      41                  68021663.0         35975301   \n",
              "3                      47                  58281171.0         33912215   \n",
              "4                      30                  54885194.0         38592454   \n",
              "5                      17                  56157155.0         36395674   \n",
              "6                      52                  45058746.0         33954127   \n",
              "7                      32                  56973059.0         29681622   \n",
              "8                      45                  52618212.0         34116436   \n",
              "9                      22                  60141300.0         35894482   \n",
              "10                      2                  49189913.0         27707752   \n",
              "11                     24                  58122596.0         27369514   \n",
              "12                     27                  55485005.0         32430876   \n",
              "13                     14                  52860247.0         30331588   \n",
              "14                     15                  52321067.0         34544359   \n",
              "15                     33                  60238809.0         32699565   \n",
              "16                     34                  57397997.0         36766788   \n",
              "17                      5                  45395814.0         31924022   \n",
              "18                     29                  57304578.0         35378306   \n",
              "19                     39                  55918984.0         44174409   \n",
              "20                     20                  50006449.0         27171859   \n",
              "21                     35                  58148191.0         28421236   \n",
              "22                     23                  58928316.0         29515165   \n",
              "23                     31                  53287256.0         35007981   \n",
              "24                     13                  48791932.0         30499924   \n",
              "25                     42                  56624276.0         33708983   \n",
              "26                     19                  54683757.0         29639609   \n",
              "27                     10                  55091122.0         31894222   \n",
              "28                     51                  41626451.0         32127592   \n",
              "29                     44                  52172285.0         23803138   \n",
              "30                     11                  62127053.0         33469570   \n",
              "31                     18                  50437696.0         35418302   \n",
              "32                      0                  46672132.0         32499996   \n",
              "33                     12                  56437406.0         34336596   \n",
              "34                     48                  54884449.0         33883001   \n",
              "35                      1                  46353658.0         23571029   \n",
              "36                     36                  66098730.0         37853692   \n",
              "37                      8                  50715185.0         32078032   \n",
              "38                     38                  59757099.0         35356100   \n",
              "39                     46                  46855149.0         33583347   \n",
              "40                     40                  61373941.0         32414295   \n",
              "41                     26                  55802773.0         31735326   \n",
              "42                      3                  46542813.0         34301246   \n",
              "43                     49                  59743196.0         36394504   \n",
              "44                      4                  45487034.0         30362735   \n",
              "45                     25                  58496216.0         27396429   \n",
              "46                     16                  56730185.0         35677196   \n",
              "47                      7                  53406226.0         36820589   \n",
              "48                     50                  35347069.0         34514784   \n",
              "49                     37                  63436172.0         34097677   \n",
              "50                     43                  58279404.0         33418152   \n",
              "51                     21                  46005032.0         32882193   \n",
              "52                     28                  52338872.0         32450531   \n",
              "\n",
              "     MT retained pairs    MT retained singles   MT retained combined reads  \\\n",
              "0                    52                     25                  94694810.0   \n",
              "1                     2                     30                  20191320.0   \n",
              "2                    20                     39                  29116361.0   \n",
              "3                    22                     24                  29052190.0   \n",
              "4                    36                     42                  37240102.0   \n",
              "5                    42                     38                  38511453.0   \n",
              "6                    24                     21                  29432061.0   \n",
              "7                    12                     12                  25479141.0   \n",
              "8                    21                     35                  29296154.0   \n",
              "9                    15                     10                  26038607.0   \n",
              "10                    3                     14                  20178306.0   \n",
              "11                    5                      2                  21450846.0   \n",
              "12                   14                     31                  26470100.0   \n",
              "13                   10                      6                  24586751.0   \n",
              "14                   27                      7                  30056225.0   \n",
              "15                   45                     41                  40014572.0   \n",
              "16                   47                     48                  42540620.0   \n",
              "17                   23                     16                  29144334.0   \n",
              "18                   32                     40                  34366472.0   \n",
              "19                   44                     44                  39799986.0   \n",
              "20                   28                      5                  30533184.0   \n",
              "21                   26                     17                  30192865.0   \n",
              "22                   31                     32                  33316978.0   \n",
              "23                   46                     46                  41398150.0   \n",
              "24                   43                     22                  38468969.0   \n",
              "25                   40                     47                  38646228.0   \n",
              "26                   25                     19                  30171299.0   \n",
              "27                   37                     15                  36417340.0   \n",
              "28                   41                     43                  38704146.0   \n",
              "29                   35                     26                  34615648.0   \n",
              "30                   51                     29                  58218932.0   \n",
              "31                   50                     52                  57176707.0   \n",
              "32                   49                     51                  53662917.0   \n",
              "33                   48                     34                  43972617.0   \n",
              "34                   38                     45                  38077091.0   \n",
              "35                   13                      9                  25523377.0   \n",
              "36                   33                     49                  35759978.0   \n",
              "37                    8                      3                  23972960.0   \n",
              "38                   18                     33                  27650194.0   \n",
              "39                   16                     27                  26669351.0   \n",
              "40                   11                     13                  25392981.0   \n",
              "41                    4                      1                  21016525.0   \n",
              "42                    9                     18                  24641096.0   \n",
              "43                   17                     20                  26727060.0   \n",
              "44                    6                      8                  21814372.0   \n",
              "45                    0                      0                  17908924.0   \n",
              "46                    1                      4                  18068804.0   \n",
              "47                    7                     11                  22236638.0   \n",
              "48                   19                     23                  28078923.0   \n",
              "49                   39                     50                  38779775.0   \n",
              "50                   30                     37                  33319189.0   \n",
              "51                   34                     28                  34658433.0   \n",
              "52                   29                     36                  32994455.0   \n",
              "\n",
              "     MT rRNA pairs    MT rRNA singles    MT contigs    Co-assembly contigs   \n",
              "0           8162922             211837             3                 126390  \n",
              "1           4110417             775696             1                 208345  \n",
              "2          17642665            2323133             6                 431078  \n",
              "3          16504703            1719392            12                 443307  \n",
              "4          16717068            1685117            41                 479608  \n",
              "5          14460847            1445338            44                 517506  \n",
              "6          16687126            1534912            18                 331870  \n",
              "7          14775098            1342298            10                 377432  \n",
              "8          15704281            1559060            14                 389063  \n",
              "9          20133094            1889977             8                 478799  \n",
              "10         14726480            1669177             0                 326463  \n",
              "11         14561598            1374840             9                 401437  \n",
              "12         16026593            1959118            17                 396383  \n",
              "13         15895274            1332740            22                 413711  \n",
              "14         17320121            1449468            40                 468428  \n",
              "15          9988214             944102            50                 553152  \n",
              "16         12327661            1279728            45                 494971  \n",
              "17         15093605            1388116            28                 404870  \n",
              "18         14915695            1347833            25                 517913  \n",
              "19         20249314            2173170            30                 490163  \n",
              "20         10516375             682408            42                 438208  \n",
              "21         11327996            1029180            37                 425668  \n",
              "22         10561939            1116334            43                 482611  \n",
              "23         11158731            1232688            52                 500533  \n",
              "24          9426018             755439            49                 448666  \n",
              "25         10936159            1380297            46                 504283  \n",
              "26         12356024            1169930            26                 443476  \n",
              "27         11887316             902949            51                 538414  \n",
              "28          9851426            1340869            47                 353499  \n",
              "29          4949382             514343            33                 415829  \n",
              "30          3111109             208282            48                 466269  \n",
              "31          4108201             572155            35                 338261  \n",
              "32          3342329             446283            39                 334496  \n",
              "33         10285053             900638            31                 442661  \n",
              "34         11810528            1504504            32                 399510  \n",
              "35          9055794             858754            13                 339691  \n",
              "36         15527661            2517756            36                 482520  \n",
              "37         17950311            1459721            16                 417909  \n",
              "38         18080293            2224365            24                 403369  \n",
              "39         17209617            1986249            19                 354881  \n",
              "40         17301018            1546768            21                 501333  \n",
              "41         19045314            1542360             4                 423528  \n",
              "42         19117272            1858032            15                 375114  \n",
              "43         19915026            2069786            23                 449815  \n",
              "44         17044898            1653723            11                 333653  \n",
              "45         16251236            1553860             5                 395166  \n",
              "46         23290747            2631821             2                 401414  \n",
              "47         22364722            2538008             7                 370833  \n",
              "48         17520794            1800547            20                 264999  \n",
              "49         11029695            1793094            38                 432627  \n",
              "50         13975373            1477695            34                 465002  \n",
              "51         12992641            1329066            29                 380672  \n",
              "52         13248562            1405761            27                 412436  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-ffe94f49-c981-422d-9b78-105832d0e241\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Date</th>\n",
              "      <th>Sample_ID</th>\n",
              "      <th>MG unprocessed</th>\n",
              "      <th>MG retained pairs</th>\n",
              "      <th>MG retained singles</th>\n",
              "      <th>MG retained combined reads</th>\n",
              "      <th>MT unprocessed</th>\n",
              "      <th>MT retained pairs</th>\n",
              "      <th>MT retained singles</th>\n",
              "      <th>MT retained combined reads</th>\n",
              "      <th>MT rRNA pairs</th>\n",
              "      <th>MT rRNA singles</th>\n",
              "      <th>MT contigs</th>\n",
              "      <th>Co-assembly contigs</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2010-10-04 00:00:00</td>\n",
              "      <td>A01</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>6</td>\n",
              "      <td>33814613.0</td>\n",
              "      <td>56764165</td>\n",
              "      <td>52</td>\n",
              "      <td>25</td>\n",
              "      <td>94694810.0</td>\n",
              "      <td>8162922</td>\n",
              "      <td>211837</td>\n",
              "      <td>3</td>\n",
              "      <td>126390</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2011-01-25 00:00:00</td>\n",
              "      <td>A02</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>9</td>\n",
              "      <td>27416282.0</td>\n",
              "      <td>16493393</td>\n",
              "      <td>2</td>\n",
              "      <td>30</td>\n",
              "      <td>20191320.0</td>\n",
              "      <td>4110417</td>\n",
              "      <td>775696</td>\n",
              "      <td>1</td>\n",
              "      <td>208345</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2011-03-21 00:00:00</td>\n",
              "      <td>D37</td>\n",
              "      <td>52</td>\n",
              "      <td>52</td>\n",
              "      <td>41</td>\n",
              "      <td>68021663.0</td>\n",
              "      <td>35975301</td>\n",
              "      <td>20</td>\n",
              "      <td>39</td>\n",
              "      <td>29116361.0</td>\n",
              "      <td>17642665</td>\n",
              "      <td>2323133</td>\n",
              "      <td>6</td>\n",
              "      <td>431078</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2011-03-29 00:00:00</td>\n",
              "      <td>D02</td>\n",
              "      <td>50</td>\n",
              "      <td>36</td>\n",
              "      <td>47</td>\n",
              "      <td>58281171.0</td>\n",
              "      <td>33912215</td>\n",
              "      <td>22</td>\n",
              "      <td>24</td>\n",
              "      <td>29052190.0</td>\n",
              "      <td>16504703</td>\n",
              "      <td>1719392</td>\n",
              "      <td>12</td>\n",
              "      <td>443307</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2011-04-05 00:00:00</td>\n",
              "      <td>D39</td>\n",
              "      <td>24</td>\n",
              "      <td>25</td>\n",
              "      <td>30</td>\n",
              "      <td>54885194.0</td>\n",
              "      <td>38592454</td>\n",
              "      <td>36</td>\n",
              "      <td>42</td>\n",
              "      <td>37240102.0</td>\n",
              "      <td>16717068</td>\n",
              "      <td>1685117</td>\n",
              "      <td>41</td>\n",
              "      <td>479608</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>2011-04-14 00:00:00</td>\n",
              "      <td>D24</td>\n",
              "      <td>27</td>\n",
              "      <td>32</td>\n",
              "      <td>17</td>\n",
              "      <td>56157155.0</td>\n",
              "      <td>36395674</td>\n",
              "      <td>42</td>\n",
              "      <td>38</td>\n",
              "      <td>38511453.0</td>\n",
              "      <td>14460847</td>\n",
              "      <td>1445338</td>\n",
              "      <td>44</td>\n",
              "      <td>517506</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>2011-04-21 00:00:00</td>\n",
              "      <td>D25</td>\n",
              "      <td>9</td>\n",
              "      <td>4</td>\n",
              "      <td>52</td>\n",
              "      <td>45058746.0</td>\n",
              "      <td>33954127</td>\n",
              "      <td>24</td>\n",
              "      <td>21</td>\n",
              "      <td>29432061.0</td>\n",
              "      <td>16687126</td>\n",
              "      <td>1534912</td>\n",
              "      <td>18</td>\n",
              "      <td>331870</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>2011-04-29 00:00:00</td>\n",
              "      <td>D35</td>\n",
              "      <td>37</td>\n",
              "      <td>34</td>\n",
              "      <td>32</td>\n",
              "      <td>56973059.0</td>\n",
              "      <td>29681622</td>\n",
              "      <td>12</td>\n",
              "      <td>12</td>\n",
              "      <td>25479141.0</td>\n",
              "      <td>14775098</td>\n",
              "      <td>1342298</td>\n",
              "      <td>10</td>\n",
              "      <td>377432</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>2011-05-06 00:00:00</td>\n",
              "      <td>D46</td>\n",
              "      <td>21</td>\n",
              "      <td>18</td>\n",
              "      <td>45</td>\n",
              "      <td>52618212.0</td>\n",
              "      <td>34116436</td>\n",
              "      <td>21</td>\n",
              "      <td>35</td>\n",
              "      <td>29296154.0</td>\n",
              "      <td>15704281</td>\n",
              "      <td>1559060</td>\n",
              "      <td>14</td>\n",
              "      <td>389063</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>2011-05-13 00:00:00</td>\n",
              "      <td>D13</td>\n",
              "      <td>42</td>\n",
              "      <td>47</td>\n",
              "      <td>22</td>\n",
              "      <td>60141300.0</td>\n",
              "      <td>35894482</td>\n",
              "      <td>15</td>\n",
              "      <td>10</td>\n",
              "      <td>26038607.0</td>\n",
              "      <td>20133094</td>\n",
              "      <td>1889977</td>\n",
              "      <td>8</td>\n",
              "      <td>478799</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>2011-05-20 00:00:00</td>\n",
              "      <td>D40</td>\n",
              "      <td>12</td>\n",
              "      <td>13</td>\n",
              "      <td>2</td>\n",
              "      <td>49189913.0</td>\n",
              "      <td>27707752</td>\n",
              "      <td>3</td>\n",
              "      <td>14</td>\n",
              "      <td>20178306.0</td>\n",
              "      <td>14726480</td>\n",
              "      <td>1669177</td>\n",
              "      <td>0</td>\n",
              "      <td>326463</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>2011-05-27 00:00:00</td>\n",
              "      <td>D33</td>\n",
              "      <td>36</td>\n",
              "      <td>42</td>\n",
              "      <td>24</td>\n",
              "      <td>58122596.0</td>\n",
              "      <td>27369514</td>\n",
              "      <td>5</td>\n",
              "      <td>2</td>\n",
              "      <td>21450846.0</td>\n",
              "      <td>14561598</td>\n",
              "      <td>1374840</td>\n",
              "      <td>9</td>\n",
              "      <td>401437</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>2011-06-03 00:00:00</td>\n",
              "      <td>D06</td>\n",
              "      <td>35</td>\n",
              "      <td>29</td>\n",
              "      <td>27</td>\n",
              "      <td>55485005.0</td>\n",
              "      <td>32430876</td>\n",
              "      <td>14</td>\n",
              "      <td>31</td>\n",
              "      <td>26470100.0</td>\n",
              "      <td>16026593</td>\n",
              "      <td>1959118</td>\n",
              "      <td>17</td>\n",
              "      <td>396383</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>2011-06-09 00:00:00</td>\n",
              "      <td>D27</td>\n",
              "      <td>19</td>\n",
              "      <td>21</td>\n",
              "      <td>14</td>\n",
              "      <td>52860247.0</td>\n",
              "      <td>30331588</td>\n",
              "      <td>10</td>\n",
              "      <td>6</td>\n",
              "      <td>24586751.0</td>\n",
              "      <td>15895274</td>\n",
              "      <td>1332740</td>\n",
              "      <td>22</td>\n",
              "      <td>413711</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>2011-06-17 00:00:00</td>\n",
              "      <td>D42</td>\n",
              "      <td>18</td>\n",
              "      <td>20</td>\n",
              "      <td>15</td>\n",
              "      <td>52321067.0</td>\n",
              "      <td>34544359</td>\n",
              "      <td>27</td>\n",
              "      <td>7</td>\n",
              "      <td>30056225.0</td>\n",
              "      <td>17320121</td>\n",
              "      <td>1449468</td>\n",
              "      <td>40</td>\n",
              "      <td>468428</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>2011-06-24 00:00:00</td>\n",
              "      <td>D03</td>\n",
              "      <td>44</td>\n",
              "      <td>46</td>\n",
              "      <td>33</td>\n",
              "      <td>60238809.0</td>\n",
              "      <td>32699565</td>\n",
              "      <td>45</td>\n",
              "      <td>41</td>\n",
              "      <td>40014572.0</td>\n",
              "      <td>9988214</td>\n",
              "      <td>944102</td>\n",
              "      <td>50</td>\n",
              "      <td>553152</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>2011-07-01 00:00:00</td>\n",
              "      <td>D47</td>\n",
              "      <td>34</td>\n",
              "      <td>37</td>\n",
              "      <td>34</td>\n",
              "      <td>57397997.0</td>\n",
              "      <td>36766788</td>\n",
              "      <td>47</td>\n",
              "      <td>48</td>\n",
              "      <td>42540620.0</td>\n",
              "      <td>12327661</td>\n",
              "      <td>1279728</td>\n",
              "      <td>45</td>\n",
              "      <td>494971</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>2011-07-08 00:00:00</td>\n",
              "      <td>D18</td>\n",
              "      <td>3</td>\n",
              "      <td>6</td>\n",
              "      <td>5</td>\n",
              "      <td>45395814.0</td>\n",
              "      <td>31924022</td>\n",
              "      <td>23</td>\n",
              "      <td>16</td>\n",
              "      <td>29144334.0</td>\n",
              "      <td>15093605</td>\n",
              "      <td>1388116</td>\n",
              "      <td>28</td>\n",
              "      <td>404870</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>2011-08-05 00:00:00</td>\n",
              "      <td>D45</td>\n",
              "      <td>33</td>\n",
              "      <td>38</td>\n",
              "      <td>29</td>\n",
              "      <td>57304578.0</td>\n",
              "      <td>35378306</td>\n",
              "      <td>32</td>\n",
              "      <td>40</td>\n",
              "      <td>34366472.0</td>\n",
              "      <td>14915695</td>\n",
              "      <td>1347833</td>\n",
              "      <td>25</td>\n",
              "      <td>517913</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>2011-08-11 00:00:00</td>\n",
              "      <td>D51</td>\n",
              "      <td>32</td>\n",
              "      <td>27</td>\n",
              "      <td>39</td>\n",
              "      <td>55918984.0</td>\n",
              "      <td>44174409</td>\n",
              "      <td>44</td>\n",
              "      <td>44</td>\n",
              "      <td>39799986.0</td>\n",
              "      <td>20249314</td>\n",
              "      <td>2173170</td>\n",
              "      <td>30</td>\n",
              "      <td>490163</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>2011-08-19 00:00:00</td>\n",
              "      <td>D43</td>\n",
              "      <td>13</td>\n",
              "      <td>14</td>\n",
              "      <td>20</td>\n",
              "      <td>50006449.0</td>\n",
              "      <td>27171859</td>\n",
              "      <td>28</td>\n",
              "      <td>5</td>\n",
              "      <td>30533184.0</td>\n",
              "      <td>10516375</td>\n",
              "      <td>682408</td>\n",
              "      <td>42</td>\n",
              "      <td>438208</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>2011-08-29 00:00:00</td>\n",
              "      <td>D34</td>\n",
              "      <td>38</td>\n",
              "      <td>40</td>\n",
              "      <td>35</td>\n",
              "      <td>58148191.0</td>\n",
              "      <td>28421236</td>\n",
              "      <td>26</td>\n",
              "      <td>17</td>\n",
              "      <td>30192865.0</td>\n",
              "      <td>11327996</td>\n",
              "      <td>1029180</td>\n",
              "      <td>37</td>\n",
              "      <td>425668</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>2011-09-05 00:00:00</td>\n",
              "      <td>D30</td>\n",
              "      <td>39</td>\n",
              "      <td>44</td>\n",
              "      <td>23</td>\n",
              "      <td>58928316.0</td>\n",
              "      <td>29515165</td>\n",
              "      <td>31</td>\n",
              "      <td>32</td>\n",
              "      <td>33316978.0</td>\n",
              "      <td>10561939</td>\n",
              "      <td>1116334</td>\n",
              "      <td>43</td>\n",
              "      <td>482611</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>2011-09-12 00:00:00</td>\n",
              "      <td>D04</td>\n",
              "      <td>25</td>\n",
              "      <td>22</td>\n",
              "      <td>31</td>\n",
              "      <td>53287256.0</td>\n",
              "      <td>35007981</td>\n",
              "      <td>46</td>\n",
              "      <td>46</td>\n",
              "      <td>41398150.0</td>\n",
              "      <td>11158731</td>\n",
              "      <td>1232688</td>\n",
              "      <td>52</td>\n",
              "      <td>500533</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>2011-09-19 00:00:00</td>\n",
              "      <td>D31</td>\n",
              "      <td>10</td>\n",
              "      <td>12</td>\n",
              "      <td>13</td>\n",
              "      <td>48791932.0</td>\n",
              "      <td>30499924</td>\n",
              "      <td>43</td>\n",
              "      <td>22</td>\n",
              "      <td>38468969.0</td>\n",
              "      <td>9426018</td>\n",
              "      <td>755439</td>\n",
              "      <td>49</td>\n",
              "      <td>448666</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>2011-09-28 00:00:00</td>\n",
              "      <td>D29</td>\n",
              "      <td>31</td>\n",
              "      <td>31</td>\n",
              "      <td>42</td>\n",
              "      <td>56624276.0</td>\n",
              "      <td>33708983</td>\n",
              "      <td>40</td>\n",
              "      <td>47</td>\n",
              "      <td>38646228.0</td>\n",
              "      <td>10936159</td>\n",
              "      <td>1380297</td>\n",
              "      <td>46</td>\n",
              "      <td>504283</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>2011-10-05 00:00:00</td>\n",
              "      <td>D49</td>\n",
              "      <td>26</td>\n",
              "      <td>26</td>\n",
              "      <td>19</td>\n",
              "      <td>54683757.0</td>\n",
              "      <td>29639609</td>\n",
              "      <td>25</td>\n",
              "      <td>19</td>\n",
              "      <td>30171299.0</td>\n",
              "      <td>12356024</td>\n",
              "      <td>1169930</td>\n",
              "      <td>26</td>\n",
              "      <td>443476</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>2011-10-12 00:00:00</td>\n",
              "      <td>D32</td>\n",
              "      <td>23</td>\n",
              "      <td>28</td>\n",
              "      <td>10</td>\n",
              "      <td>55091122.0</td>\n",
              "      <td>31894222</td>\n",
              "      <td>37</td>\n",
              "      <td>15</td>\n",
              "      <td>36417340.0</td>\n",
              "      <td>11887316</td>\n",
              "      <td>902949</td>\n",
              "      <td>51</td>\n",
              "      <td>538414</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>2011-11-02 00:00:00</td>\n",
              "      <td>D23</td>\n",
              "      <td>4</td>\n",
              "      <td>3</td>\n",
              "      <td>51</td>\n",
              "      <td>41626451.0</td>\n",
              "      <td>32127592</td>\n",
              "      <td>41</td>\n",
              "      <td>43</td>\n",
              "      <td>38704146.0</td>\n",
              "      <td>9851426</td>\n",
              "      <td>1340869</td>\n",
              "      <td>47</td>\n",
              "      <td>353499</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>2011-11-07 00:00:00</td>\n",
              "      <td>D44</td>\n",
              "      <td>20</td>\n",
              "      <td>17</td>\n",
              "      <td>44</td>\n",
              "      <td>52172285.0</td>\n",
              "      <td>23803138</td>\n",
              "      <td>35</td>\n",
              "      <td>26</td>\n",
              "      <td>34615648.0</td>\n",
              "      <td>4949382</td>\n",
              "      <td>514343</td>\n",
              "      <td>33</td>\n",
              "      <td>415829</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30</th>\n",
              "      <td>2011-11-16 00:00:00</td>\n",
              "      <td>D20</td>\n",
              "      <td>43</td>\n",
              "      <td>49</td>\n",
              "      <td>11</td>\n",
              "      <td>62127053.0</td>\n",
              "      <td>33469570</td>\n",
              "      <td>51</td>\n",
              "      <td>29</td>\n",
              "      <td>58218932.0</td>\n",
              "      <td>3111109</td>\n",
              "      <td>208282</td>\n",
              "      <td>48</td>\n",
              "      <td>466269</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31</th>\n",
              "      <td>2011-11-23 00:00:00</td>\n",
              "      <td>D15</td>\n",
              "      <td>15</td>\n",
              "      <td>15</td>\n",
              "      <td>18</td>\n",
              "      <td>50437696.0</td>\n",
              "      <td>35418302</td>\n",
              "      <td>50</td>\n",
              "      <td>52</td>\n",
              "      <td>57176707.0</td>\n",
              "      <td>4108201</td>\n",
              "      <td>572155</td>\n",
              "      <td>35</td>\n",
              "      <td>338261</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32</th>\n",
              "      <td>2011-11-29 00:00:00</td>\n",
              "      <td>D05</td>\n",
              "      <td>11</td>\n",
              "      <td>11</td>\n",
              "      <td>0</td>\n",
              "      <td>46672132.0</td>\n",
              "      <td>32499996</td>\n",
              "      <td>49</td>\n",
              "      <td>51</td>\n",
              "      <td>53662917.0</td>\n",
              "      <td>3342329</td>\n",
              "      <td>446283</td>\n",
              "      <td>39</td>\n",
              "      <td>334496</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>33</th>\n",
              "      <td>2011-12-21 00:00:00</td>\n",
              "      <td>D28</td>\n",
              "      <td>29</td>\n",
              "      <td>33</td>\n",
              "      <td>12</td>\n",
              "      <td>56437406.0</td>\n",
              "      <td>34336596</td>\n",
              "      <td>48</td>\n",
              "      <td>34</td>\n",
              "      <td>43972617.0</td>\n",
              "      <td>10285053</td>\n",
              "      <td>900638</td>\n",
              "      <td>31</td>\n",
              "      <td>442661</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>34</th>\n",
              "      <td>2011-12-28 00:00:00</td>\n",
              "      <td>D09</td>\n",
              "      <td>41</td>\n",
              "      <td>23</td>\n",
              "      <td>48</td>\n",
              "      <td>54884449.0</td>\n",
              "      <td>33883001</td>\n",
              "      <td>38</td>\n",
              "      <td>45</td>\n",
              "      <td>38077091.0</td>\n",
              "      <td>11810528</td>\n",
              "      <td>1504504</td>\n",
              "      <td>32</td>\n",
              "      <td>399510</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35</th>\n",
              "      <td>2012-01-03 00:00:00</td>\n",
              "      <td>D38</td>\n",
              "      <td>8</td>\n",
              "      <td>9</td>\n",
              "      <td>1</td>\n",
              "      <td>46353658.0</td>\n",
              "      <td>23571029</td>\n",
              "      <td>13</td>\n",
              "      <td>9</td>\n",
              "      <td>25523377.0</td>\n",
              "      <td>9055794</td>\n",
              "      <td>858754</td>\n",
              "      <td>13</td>\n",
              "      <td>339691</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>36</th>\n",
              "      <td>2012-01-11 00:00:00</td>\n",
              "      <td>D36</td>\n",
              "      <td>51</td>\n",
              "      <td>51</td>\n",
              "      <td>36</td>\n",
              "      <td>66098730.0</td>\n",
              "      <td>37853692</td>\n",
              "      <td>33</td>\n",
              "      <td>49</td>\n",
              "      <td>35759978.0</td>\n",
              "      <td>15527661</td>\n",
              "      <td>2517756</td>\n",
              "      <td>36</td>\n",
              "      <td>482520</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>37</th>\n",
              "      <td>2012-01-19 00:00:00</td>\n",
              "      <td>D12</td>\n",
              "      <td>14</td>\n",
              "      <td>16</td>\n",
              "      <td>8</td>\n",
              "      <td>50715185.0</td>\n",
              "      <td>32078032</td>\n",
              "      <td>8</td>\n",
              "      <td>3</td>\n",
              "      <td>23972960.0</td>\n",
              "      <td>17950311</td>\n",
              "      <td>1459721</td>\n",
              "      <td>16</td>\n",
              "      <td>417909</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38</th>\n",
              "      <td>2012-01-25 00:00:00</td>\n",
              "      <td>D10</td>\n",
              "      <td>46</td>\n",
              "      <td>45</td>\n",
              "      <td>38</td>\n",
              "      <td>59757099.0</td>\n",
              "      <td>35356100</td>\n",
              "      <td>18</td>\n",
              "      <td>33</td>\n",
              "      <td>27650194.0</td>\n",
              "      <td>18080293</td>\n",
              "      <td>2224365</td>\n",
              "      <td>24</td>\n",
              "      <td>403369</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39</th>\n",
              "      <td>2012-02-01 00:00:00</td>\n",
              "      <td>D14</td>\n",
              "      <td>16</td>\n",
              "      <td>5</td>\n",
              "      <td>46</td>\n",
              "      <td>46855149.0</td>\n",
              "      <td>33583347</td>\n",
              "      <td>16</td>\n",
              "      <td>27</td>\n",
              "      <td>26669351.0</td>\n",
              "      <td>17209617</td>\n",
              "      <td>1986249</td>\n",
              "      <td>19</td>\n",
              "      <td>354881</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>40</th>\n",
              "      <td>2012-02-08 00:00:00</td>\n",
              "      <td>D08</td>\n",
              "      <td>48</td>\n",
              "      <td>48</td>\n",
              "      <td>40</td>\n",
              "      <td>61373941.0</td>\n",
              "      <td>32414295</td>\n",
              "      <td>11</td>\n",
              "      <td>13</td>\n",
              "      <td>25392981.0</td>\n",
              "      <td>17301018</td>\n",
              "      <td>1546768</td>\n",
              "      <td>21</td>\n",
              "      <td>501333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>41</th>\n",
              "      <td>2012-02-14 00:00:00</td>\n",
              "      <td>D26</td>\n",
              "      <td>28</td>\n",
              "      <td>30</td>\n",
              "      <td>26</td>\n",
              "      <td>55802773.0</td>\n",
              "      <td>31735326</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>21016525.0</td>\n",
              "      <td>19045314</td>\n",
              "      <td>1542360</td>\n",
              "      <td>4</td>\n",
              "      <td>423528</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>42</th>\n",
              "      <td>2012-02-23 00:00:00</td>\n",
              "      <td>D21</td>\n",
              "      <td>6</td>\n",
              "      <td>10</td>\n",
              "      <td>3</td>\n",
              "      <td>46542813.0</td>\n",
              "      <td>34301246</td>\n",
              "      <td>9</td>\n",
              "      <td>18</td>\n",
              "      <td>24641096.0</td>\n",
              "      <td>19117272</td>\n",
              "      <td>1858032</td>\n",
              "      <td>15</td>\n",
              "      <td>375114</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>43</th>\n",
              "      <td>2012-02-29 00:00:00</td>\n",
              "      <td>D19</td>\n",
              "      <td>45</td>\n",
              "      <td>41</td>\n",
              "      <td>49</td>\n",
              "      <td>59743196.0</td>\n",
              "      <td>36394504</td>\n",
              "      <td>17</td>\n",
              "      <td>20</td>\n",
              "      <td>26727060.0</td>\n",
              "      <td>19915026</td>\n",
              "      <td>2069786</td>\n",
              "      <td>23</td>\n",
              "      <td>449815</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>44</th>\n",
              "      <td>2012-03-08 00:00:00</td>\n",
              "      <td>D17</td>\n",
              "      <td>5</td>\n",
              "      <td>7</td>\n",
              "      <td>4</td>\n",
              "      <td>45487034.0</td>\n",
              "      <td>30362735</td>\n",
              "      <td>6</td>\n",
              "      <td>8</td>\n",
              "      <td>21814372.0</td>\n",
              "      <td>17044898</td>\n",
              "      <td>1653723</td>\n",
              "      <td>11</td>\n",
              "      <td>333653</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45</th>\n",
              "      <td>2012-03-14 00:00:00</td>\n",
              "      <td>D41</td>\n",
              "      <td>40</td>\n",
              "      <td>43</td>\n",
              "      <td>25</td>\n",
              "      <td>58496216.0</td>\n",
              "      <td>27396429</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>17908924.0</td>\n",
              "      <td>16251236</td>\n",
              "      <td>1553860</td>\n",
              "      <td>5</td>\n",
              "      <td>395166</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>46</th>\n",
              "      <td>2012-03-22 00:00:00</td>\n",
              "      <td>D11</td>\n",
              "      <td>30</td>\n",
              "      <td>35</td>\n",
              "      <td>16</td>\n",
              "      <td>56730185.0</td>\n",
              "      <td>35677196</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>18068804.0</td>\n",
              "      <td>23290747</td>\n",
              "      <td>2631821</td>\n",
              "      <td>2</td>\n",
              "      <td>401414</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>47</th>\n",
              "      <td>2012-03-28 00:00:00</td>\n",
              "      <td>D16</td>\n",
              "      <td>22</td>\n",
              "      <td>24</td>\n",
              "      <td>7</td>\n",
              "      <td>53406226.0</td>\n",
              "      <td>36820589</td>\n",
              "      <td>7</td>\n",
              "      <td>11</td>\n",
              "      <td>22236638.0</td>\n",
              "      <td>22364722</td>\n",
              "      <td>2538008</td>\n",
              "      <td>7</td>\n",
              "      <td>370833</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>2012-04-04 00:00:00</td>\n",
              "      <td>D07</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>50</td>\n",
              "      <td>35347069.0</td>\n",
              "      <td>34514784</td>\n",
              "      <td>19</td>\n",
              "      <td>23</td>\n",
              "      <td>28078923.0</td>\n",
              "      <td>17520794</td>\n",
              "      <td>1800547</td>\n",
              "      <td>20</td>\n",
              "      <td>264999</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>49</th>\n",
              "      <td>2012-04-10 00:00:00</td>\n",
              "      <td>D22</td>\n",
              "      <td>49</td>\n",
              "      <td>50</td>\n",
              "      <td>37</td>\n",
              "      <td>63436172.0</td>\n",
              "      <td>34097677</td>\n",
              "      <td>39</td>\n",
              "      <td>50</td>\n",
              "      <td>38779775.0</td>\n",
              "      <td>11029695</td>\n",
              "      <td>1793094</td>\n",
              "      <td>38</td>\n",
              "      <td>432627</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50</th>\n",
              "      <td>2012-04-17 00:00:00</td>\n",
              "      <td>D01</td>\n",
              "      <td>47</td>\n",
              "      <td>39</td>\n",
              "      <td>43</td>\n",
              "      <td>58279404.0</td>\n",
              "      <td>33418152</td>\n",
              "      <td>30</td>\n",
              "      <td>37</td>\n",
              "      <td>33319189.0</td>\n",
              "      <td>13975373</td>\n",
              "      <td>1477695</td>\n",
              "      <td>34</td>\n",
              "      <td>465002</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>51</th>\n",
              "      <td>2012-04-25 00:00:00</td>\n",
              "      <td>D50</td>\n",
              "      <td>7</td>\n",
              "      <td>8</td>\n",
              "      <td>21</td>\n",
              "      <td>46005032.0</td>\n",
              "      <td>32882193</td>\n",
              "      <td>34</td>\n",
              "      <td>28</td>\n",
              "      <td>34658433.0</td>\n",
              "      <td>12992641</td>\n",
              "      <td>1329066</td>\n",
              "      <td>29</td>\n",
              "      <td>380672</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>52</th>\n",
              "      <td>2012-05-03 00:00:00</td>\n",
              "      <td>D48</td>\n",
              "      <td>17</td>\n",
              "      <td>19</td>\n",
              "      <td>28</td>\n",
              "      <td>52338872.0</td>\n",
              "      <td>32450531</td>\n",
              "      <td>29</td>\n",
              "      <td>36</td>\n",
              "      <td>32994455.0</td>\n",
              "      <td>13248562</td>\n",
              "      <td>1405761</td>\n",
              "      <td>27</td>\n",
              "      <td>412436</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-ffe94f49-c981-422d-9b78-105832d0e241')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
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              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-ffe94f49-c981-422d-9b78-105832d0e241 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-ffe94f49-c981-422d-9b78-105832d0e241');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 100
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(15,8))\n",
        "sns.heatmap(data_modeling.corr(), annot=True)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 621
        },
        "id": "-6xN_TgN2vqD",
        "outputId": "777cb31e-06a2-4d29-ccff-2c5ade771cd1"
      },
      "id": "-6xN_TgN2vqD",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1080x576 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data_modeling.columns"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Pto4pffk2veP",
        "outputId": "c16df779-539d-4e94-d585-caf74353367e"
      },
      "id": "Pto4pffk2veP",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index([' Date ', ' Sample_ID ', ' MG unprocessed ', ' MG retained pairs ',\n",
              "       ' MG retained singles ', 'MG retained combined reads',\n",
              "       ' MT unprocessed', ' MT retained pairs ', ' MT retained singles ',\n",
              "       'MT retained combined reads', ' MT rRNA pairs ', ' MT rRNA singles ',\n",
              "       ' MT contigs ', ' Co-assembly contigs '],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 102
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "mod_data=data_modeling[[\" MG unprocessed \",\" MG retained pairs \",\" MT retained pairs \",\" MT contigs \",\" Co-assembly contigs \"]]"
      ],
      "metadata": {
        "id": "nfk7ZA_v2vRK"
      },
      "id": "nfk7ZA_v2vRK",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "mod_data"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "Peik546437L8",
        "outputId": "d1319912-998b-4f17-892f-cd52c381658a"
      },
      "id": "Peik546437L8",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     MG unprocessed    MG retained pairs    MT retained pairs    MT contigs   \\\n",
              "0                  1                    2                   52             3   \n",
              "1                  0                    0                    2             1   \n",
              "2                 52                   52                   20             6   \n",
              "3                 50                   36                   22            12   \n",
              "4                 24                   25                   36            41   \n",
              "5                 27                   32                   42            44   \n",
              "6                  9                    4                   24            18   \n",
              "7                 37                   34                   12            10   \n",
              "8                 21                   18                   21            14   \n",
              "9                 42                   47                   15             8   \n",
              "10                12                   13                    3             0   \n",
              "11                36                   42                    5             9   \n",
              "12                35                   29                   14            17   \n",
              "13                19                   21                   10            22   \n",
              "14                18                   20                   27            40   \n",
              "15                44                   46                   45            50   \n",
              "16                34                   37                   47            45   \n",
              "17                 3                    6                   23            28   \n",
              "18                33                   38                   32            25   \n",
              "19                32                   27                   44            30   \n",
              "20                13                   14                   28            42   \n",
              "21                38                   40                   26            37   \n",
              "22                39                   44                   31            43   \n",
              "23                25                   22                   46            52   \n",
              "24                10                   12                   43            49   \n",
              "25                31                   31                   40            46   \n",
              "26                26                   26                   25            26   \n",
              "27                23                   28                   37            51   \n",
              "28                 4                    3                   41            47   \n",
              "29                20                   17                   35            33   \n",
              "30                43                   49                   51            48   \n",
              "31                15                   15                   50            35   \n",
              "32                11                   11                   49            39   \n",
              "33                29                   33                   48            31   \n",
              "34                41                   23                   38            32   \n",
              "35                 8                    9                   13            13   \n",
              "36                51                   51                   33            36   \n",
              "37                14                   16                    8            16   \n",
              "38                46                   45                   18            24   \n",
              "39                16                    5                   16            19   \n",
              "40                48                   48                   11            21   \n",
              "41                28                   30                    4             4   \n",
              "42                 6                   10                    9            15   \n",
              "43                45                   41                   17            23   \n",
              "44                 5                    7                    6            11   \n",
              "45                40                   43                    0             5   \n",
              "46                30                   35                    1             2   \n",
              "47                22                   24                    7             7   \n",
              "48                 2                    1                   19            20   \n",
              "49                49                   50                   39            38   \n",
              "50                47                   39                   30            34   \n",
              "51                 7                    8                   34            29   \n",
              "52                17                   19                   29            27   \n",
              "\n",
              "     Co-assembly contigs   \n",
              "0                  126390  \n",
              "1                  208345  \n",
              "2                  431078  \n",
              "3                  443307  \n",
              "4                  479608  \n",
              "5                  517506  \n",
              "6                  331870  \n",
              "7                  377432  \n",
              "8                  389063  \n",
              "9                  478799  \n",
              "10                 326463  \n",
              "11                 401437  \n",
              "12                 396383  \n",
              "13                 413711  \n",
              "14                 468428  \n",
              "15                 553152  \n",
              "16                 494971  \n",
              "17                 404870  \n",
              "18                 517913  \n",
              "19                 490163  \n",
              "20                 438208  \n",
              "21                 425668  \n",
              "22                 482611  \n",
              "23                 500533  \n",
              "24                 448666  \n",
              "25                 504283  \n",
              "26                 443476  \n",
              "27                 538414  \n",
              "28                 353499  \n",
              "29                 415829  \n",
              "30                 466269  \n",
              "31                 338261  \n",
              "32                 334496  \n",
              "33                 442661  \n",
              "34                 399510  \n",
              "35                 339691  \n",
              "36                 482520  \n",
              "37                 417909  \n",
              "38                 403369  \n",
              "39                 354881  \n",
              "40                 501333  \n",
              "41                 423528  \n",
              "42                 375114  \n",
              "43                 449815  \n",
              "44                 333653  \n",
              "45                 395166  \n",
              "46                 401414  \n",
              "47                 370833  \n",
              "48                 264999  \n",
              "49                 432627  \n",
              "50                 465002  \n",
              "51                 380672  \n",
              "52                 412436  "
            ],
            "text/html": [
              "\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>MG unprocessed</th>\n",
              "      <th>MG retained pairs</th>\n",
              "      <th>MT retained pairs</th>\n",
              "      <th>MT contigs</th>\n",
              "      <th>Co-assembly contigs</th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
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              "      <td>52</td>\n",
              "      <td>3</td>\n",
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              "      <th>1</th>\n",
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              "      <td>0</td>\n",
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              "      <td>1</td>\n",
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              "      <th>2</th>\n",
              "      <td>52</td>\n",
              "      <td>52</td>\n",
              "      <td>20</td>\n",
              "      <td>6</td>\n",
              "      <td>431078</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>50</td>\n",
              "      <td>36</td>\n",
              "      <td>22</td>\n",
              "      <td>12</td>\n",
              "      <td>443307</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>24</td>\n",
              "      <td>25</td>\n",
              "      <td>36</td>\n",
              "      <td>41</td>\n",
              "      <td>479608</td>\n",
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              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>27</td>\n",
              "      <td>32</td>\n",
              "      <td>42</td>\n",
              "      <td>44</td>\n",
              "      <td>517506</td>\n",
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              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>9</td>\n",
              "      <td>4</td>\n",
              "      <td>24</td>\n",
              "      <td>18</td>\n",
              "      <td>331870</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>37</td>\n",
              "      <td>34</td>\n",
              "      <td>12</td>\n",
              "      <td>10</td>\n",
              "      <td>377432</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>21</td>\n",
              "      <td>18</td>\n",
              "      <td>21</td>\n",
              "      <td>14</td>\n",
              "      <td>389063</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>42</td>\n",
              "      <td>47</td>\n",
              "      <td>15</td>\n",
              "      <td>8</td>\n",
              "      <td>478799</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>12</td>\n",
              "      <td>13</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>326463</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>36</td>\n",
              "      <td>42</td>\n",
              "      <td>5</td>\n",
              "      <td>9</td>\n",
              "      <td>401437</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>35</td>\n",
              "      <td>29</td>\n",
              "      <td>14</td>\n",
              "      <td>17</td>\n",
              "      <td>396383</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>19</td>\n",
              "      <td>21</td>\n",
              "      <td>10</td>\n",
              "      <td>22</td>\n",
              "      <td>413711</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>18</td>\n",
              "      <td>20</td>\n",
              "      <td>27</td>\n",
              "      <td>40</td>\n",
              "      <td>468428</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>44</td>\n",
              "      <td>46</td>\n",
              "      <td>45</td>\n",
              "      <td>50</td>\n",
              "      <td>553152</td>\n",
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              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>34</td>\n",
              "      <td>37</td>\n",
              "      <td>47</td>\n",
              "      <td>45</td>\n",
              "      <td>494971</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>3</td>\n",
              "      <td>6</td>\n",
              "      <td>23</td>\n",
              "      <td>28</td>\n",
              "      <td>404870</td>\n",
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              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>33</td>\n",
              "      <td>38</td>\n",
              "      <td>32</td>\n",
              "      <td>25</td>\n",
              "      <td>517913</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>32</td>\n",
              "      <td>27</td>\n",
              "      <td>44</td>\n",
              "      <td>30</td>\n",
              "      <td>490163</td>\n",
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              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>13</td>\n",
              "      <td>14</td>\n",
              "      <td>28</td>\n",
              "      <td>42</td>\n",
              "      <td>438208</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>38</td>\n",
              "      <td>40</td>\n",
              "      <td>26</td>\n",
              "      <td>37</td>\n",
              "      <td>425668</td>\n",
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              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>39</td>\n",
              "      <td>44</td>\n",
              "      <td>31</td>\n",
              "      <td>43</td>\n",
              "      <td>482611</td>\n",
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              "      <th>23</th>\n",
              "      <td>25</td>\n",
              "      <td>22</td>\n",
              "      <td>46</td>\n",
              "      <td>52</td>\n",
              "      <td>500533</td>\n",
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              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>10</td>\n",
              "      <td>12</td>\n",
              "      <td>43</td>\n",
              "      <td>49</td>\n",
              "      <td>448666</td>\n",
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              "      <th>25</th>\n",
              "      <td>31</td>\n",
              "      <td>31</td>\n",
              "      <td>40</td>\n",
              "      <td>46</td>\n",
              "      <td>504283</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>26</td>\n",
              "      <td>26</td>\n",
              "      <td>25</td>\n",
              "      <td>26</td>\n",
              "      <td>443476</td>\n",
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              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>23</td>\n",
              "      <td>28</td>\n",
              "      <td>37</td>\n",
              "      <td>51</td>\n",
              "      <td>538414</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>4</td>\n",
              "      <td>3</td>\n",
              "      <td>41</td>\n",
              "      <td>47</td>\n",
              "      <td>353499</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>20</td>\n",
              "      <td>17</td>\n",
              "      <td>35</td>\n",
              "      <td>33</td>\n",
              "      <td>415829</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30</th>\n",
              "      <td>43</td>\n",
              "      <td>49</td>\n",
              "      <td>51</td>\n",
              "      <td>48</td>\n",
              "      <td>466269</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31</th>\n",
              "      <td>15</td>\n",
              "      <td>15</td>\n",
              "      <td>50</td>\n",
              "      <td>35</td>\n",
              "      <td>338261</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32</th>\n",
              "      <td>11</td>\n",
              "      <td>11</td>\n",
              "      <td>49</td>\n",
              "      <td>39</td>\n",
              "      <td>334496</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>33</th>\n",
              "      <td>29</td>\n",
              "      <td>33</td>\n",
              "      <td>48</td>\n",
              "      <td>31</td>\n",
              "      <td>442661</td>\n",
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              "    <tr>\n",
              "      <th>34</th>\n",
              "      <td>41</td>\n",
              "      <td>23</td>\n",
              "      <td>38</td>\n",
              "      <td>32</td>\n",
              "      <td>399510</td>\n",
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              "    <tr>\n",
              "      <th>35</th>\n",
              "      <td>8</td>\n",
              "      <td>9</td>\n",
              "      <td>13</td>\n",
              "      <td>13</td>\n",
              "      <td>339691</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>36</th>\n",
              "      <td>51</td>\n",
              "      <td>51</td>\n",
              "      <td>33</td>\n",
              "      <td>36</td>\n",
              "      <td>482520</td>\n",
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              "    <tr>\n",
              "      <th>37</th>\n",
              "      <td>14</td>\n",
              "      <td>16</td>\n",
              "      <td>8</td>\n",
              "      <td>16</td>\n",
              "      <td>417909</td>\n",
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              "    <tr>\n",
              "      <th>38</th>\n",
              "      <td>46</td>\n",
              "      <td>45</td>\n",
              "      <td>18</td>\n",
              "      <td>24</td>\n",
              "      <td>403369</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39</th>\n",
              "      <td>16</td>\n",
              "      <td>5</td>\n",
              "      <td>16</td>\n",
              "      <td>19</td>\n",
              "      <td>354881</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>40</th>\n",
              "      <td>48</td>\n",
              "      <td>48</td>\n",
              "      <td>11</td>\n",
              "      <td>21</td>\n",
              "      <td>501333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>41</th>\n",
              "      <td>28</td>\n",
              "      <td>30</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>423528</td>\n",
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              "    <tr>\n",
              "      <th>42</th>\n",
              "      <td>6</td>\n",
              "      <td>10</td>\n",
              "      <td>9</td>\n",
              "      <td>15</td>\n",
              "      <td>375114</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>43</th>\n",
              "      <td>45</td>\n",
              "      <td>41</td>\n",
              "      <td>17</td>\n",
              "      <td>23</td>\n",
              "      <td>449815</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>44</th>\n",
              "      <td>5</td>\n",
              "      <td>7</td>\n",
              "      <td>6</td>\n",
              "      <td>11</td>\n",
              "      <td>333653</td>\n",
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              "    <tr>\n",
              "      <th>45</th>\n",
              "      <td>40</td>\n",
              "      <td>43</td>\n",
              "      <td>0</td>\n",
              "      <td>5</td>\n",
              "      <td>395166</td>\n",
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              "      <th>46</th>\n",
              "      <td>30</td>\n",
              "      <td>35</td>\n",
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              "      <td>2</td>\n",
              "      <td>401414</td>\n",
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              "    <tr>\n",
              "      <th>47</th>\n",
              "      <td>22</td>\n",
              "      <td>24</td>\n",
              "      <td>7</td>\n",
              "      <td>7</td>\n",
              "      <td>370833</td>\n",
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              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>19</td>\n",
              "      <td>20</td>\n",
              "      <td>264999</td>\n",
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              "    <tr>\n",
              "      <th>49</th>\n",
              "      <td>49</td>\n",
              "      <td>50</td>\n",
              "      <td>39</td>\n",
              "      <td>38</td>\n",
              "      <td>432627</td>\n",
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              "    <tr>\n",
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              "      <td>47</td>\n",
              "      <td>39</td>\n",
              "      <td>30</td>\n",
              "      <td>34</td>\n",
              "      <td>465002</td>\n",
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              "    <tr>\n",
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              "      <td>7</td>\n",
              "      <td>8</td>\n",
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              "      <td>29</td>\n",
              "      <td>380672</td>\n",
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              "      <td>17</td>\n",
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              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-75c09440-4421-405e-866e-69dc972f8056 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-75c09440-4421-405e-866e-69dc972f8056');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 104
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "mod_data.dtypes"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "D9vWVTL237Il",
        "outputId": "7f22696b-ad5c-43dc-c85a-847f703f57c1"
      },
      "id": "D9vWVTL237Il",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              " MG unprocessed          int64\n",
              " MG retained pairs       int64\n",
              " MT retained pairs       int64\n",
              " MT contigs              int64\n",
              " Co-assembly contigs     int64\n",
              "dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 105
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "X = mod_data.iloc[:, :-1].values\n",
        "y = mod_data.iloc[:, -1].values"
      ],
      "metadata": {
        "id": "4_UOPdp-36_h"
      },
      "id": "4_UOPdp-36_h",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "target = data_modeling.iloc[:,-1]"
      ],
      "metadata": {
        "id": "LEruTmyNlYS2"
      },
      "id": "LEruTmyNlYS2",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.metrics import accuracy_score,confusion_matrix"
      ],
      "metadata": {
        "id": "CSWurwde4UEU"
      },
      "id": "CSWurwde4UEU",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)"
      ],
      "metadata": {
        "id": "qI8AKDQ836xX"
      },
      "id": "qI8AKDQ836xX",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "X_train.shape,X_test.shape,y_train.shape,y_test.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BzTEiei54e1-",
        "outputId": "7ed1a9ff-deaa-4f40-d20b-d23ebb0183a4"
      },
      "id": "BzTEiei54e1-",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "((42, 4), (11, 4), (42,), (11,))"
            ]
          },
          "metadata": {},
          "execution_count": 109
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.svm import SVC\n",
        "model = SVC(kernel='linear', random_state=27)\n",
        "model.fit(X_train, y_train)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "V_6dj8GG4lgN",
        "outputId": "f4ce3ff8-f476-43b3-c37e-b37b36a3bf37"
      },
      "id": "V_6dj8GG4lgN",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "SVC(kernel='linear', random_state=27)"
            ]
          },
          "metadata": {},
          "execution_count": 110
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y_pred = model.predict(X_test)"
      ],
      "metadata": {
        "id": "LaRMNycQ5zSP"
      },
      "id": "LaRMNycQ5zSP",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "y_test"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BI-FgkHt5zOz",
        "outputId": "34989a8c-8bfc-47af-ed99-b332b3c5eb87"
      },
      "id": "BI-FgkHt5zOz",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([490163, 423528, 370833, 396383, 449815, 517506, 404870, 465002,\n",
              "       443307, 334496, 413711])"
            ]
          },
          "metadata": {},
          "execution_count": 112
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y_pred"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "56jJlVL45zMK",
        "outputId": "57a91642-9ae4-40ab-a754-c29fc89b0d6c"
      },
      "id": "56jJlVL45zMK",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([442661, 401414, 417909, 377432, 403369, 504283, 264999, 425668,\n",
              "       478799, 338261, 417909])"
            ]
          },
          "metadata": {},
          "execution_count": 113
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "c_matrix=confusion_matrix(y_pred,y_test)"
      ],
      "metadata": {
        "id": "RFHlCw7j5y8g"
      },
      "id": "RFHlCw7j5y8g",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "sns.heatmap(c_matrix, annot=True)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 269
        },
        "id": "uzVtURat5y3L",
        "outputId": "eaa43cba-147c-4c30-b345-1e2e91e1e592"
      },
      "id": "uzVtURat5y3L",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.cluster import KMeans"
      ],
      "metadata": {
        "id": "NHiWtYF060lo"
      },
      "id": "NHiWtYF060lo",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "X"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jc0YDt-B64Rr",
        "outputId": "8fac15f9-78b1-4507-d9d0-db90829314f6"
      },
      "id": "jc0YDt-B64Rr",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[ 1,  2, 52,  3],\n",
              "       [ 0,  0,  2,  1],\n",
              "       [52, 52, 20,  6],\n",
              "       [50, 36, 22, 12],\n",
              "       [24, 25, 36, 41],\n",
              "       [27, 32, 42, 44],\n",
              "       [ 9,  4, 24, 18],\n",
              "       [37, 34, 12, 10],\n",
              "       [21, 18, 21, 14],\n",
              "       [42, 47, 15,  8],\n",
              "       [12, 13,  3,  0],\n",
              "       [36, 42,  5,  9],\n",
              "       [35, 29, 14, 17],\n",
              "       [19, 21, 10, 22],\n",
              "       [18, 20, 27, 40],\n",
              "       [44, 46, 45, 50],\n",
              "       [34, 37, 47, 45],\n",
              "       [ 3,  6, 23, 28],\n",
              "       [33, 38, 32, 25],\n",
              "       [32, 27, 44, 30],\n",
              "       [13, 14, 28, 42],\n",
              "       [38, 40, 26, 37],\n",
              "       [39, 44, 31, 43],\n",
              "       [25, 22, 46, 52],\n",
              "       [10, 12, 43, 49],\n",
              "       [31, 31, 40, 46],\n",
              "       [26, 26, 25, 26],\n",
              "       [23, 28, 37, 51],\n",
              "       [ 4,  3, 41, 47],\n",
              "       [20, 17, 35, 33],\n",
              "       [43, 49, 51, 48],\n",
              "       [15, 15, 50, 35],\n",
              "       [11, 11, 49, 39],\n",
              "       [29, 33, 48, 31],\n",
              "       [41, 23, 38, 32],\n",
              "       [ 8,  9, 13, 13],\n",
              "       [51, 51, 33, 36],\n",
              "       [14, 16,  8, 16],\n",
              "       [46, 45, 18, 24],\n",
              "       [16,  5, 16, 19],\n",
              "       [48, 48, 11, 21],\n",
              "       [28, 30,  4,  4],\n",
              "       [ 6, 10,  9, 15],\n",
              "       [45, 41, 17, 23],\n",
              "       [ 5,  7,  6, 11],\n",
              "       [40, 43,  0,  5],\n",
              "       [30, 35,  1,  2],\n",
              "       [22, 24,  7,  7],\n",
              "       [ 2,  1, 19, 20],\n",
              "       [49, 50, 39, 38],\n",
              "       [47, 39, 30, 34],\n",
              "       [ 7,  8, 34, 29],\n",
              "       [17, 19, 29, 27]])"
            ]
          },
          "metadata": {},
          "execution_count": 117
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "kmeans = KMeans(n_clusters=4, random_state=2).fit(X)\n",
        "b=kmeans.labels_"
      ],
      "metadata": {
        "id": "HDklm5LX67mg"
      },
      "id": "HDklm5LX67mg",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "centers=kmeans.cluster_centers_"
      ],
      "metadata": {
        "id": "7rxZ_t5H67el"
      },
      "id": "7rxZ_t5H67el",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.decomposition import PCA\n",
        "from sklearn.cluster import KMeans\n",
        "import numpy as np\n",
        "pca = PCA(2)\n",
        "df = pca.fit_transform(mod_data)\n",
        "df.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "poxD-CuzAusL",
        "outputId": "355cbabe-401f-4481-ea52-88e53738a291"
      },
      "id": "poxD-CuzAusL",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(53, 2)"
            ]
          },
          "metadata": {},
          "execution_count": 120
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Print the explained variance ratio of the first two components\n",
        "print(\"Explained variance ratio:\", pca.explained_variance_ratio_)\n",
        "\n",
        "# Create a new dataframe from the PCA transformed data\n",
        "data_modeling_pca = pd.DataFrame(df, columns=['PC1', 'PC2'])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rE_iAR9QnuJ2",
        "outputId": "89e872dd-d759-4185-c169-8eafdc9775dc"
      },
      "id": "rE_iAR9QnuJ2",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Explained variance ratio: [9.99999894e-01 6.47618947e-08]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.cluster import KMeans\n",
        "\n",
        "# Initialize the KMeans model with 4 clusters\n",
        "kmeans = KMeans(n_clusters=4)\n",
        "\n",
        "# Fit the model to the PCA transformed data\n",
        "kmeans.fit(df)\n",
        "\n",
        "# Get the cluster assignments for each sample\n",
        "clusters = kmeans.predict(df)\n",
        "\n",
        "# Add the cluster assignment as a new column to the original dataframe\n",
        "data_modeling_pca['cluster'] = clusters\n",
        "\n",
        "# Plot the data points for each cluster\n",
        "import matplotlib.pyplot as plt\n",
        "for i in range(4):\n",
        "    cluster = data_modeling_pca[data_modeling_pca['cluster'] == i]\n",
        "    plt.scatter(cluster['PC1'], cluster['PC2'])\n",
        "\n",
        "# Add axis labels and show the plot\n",
        "plt.xlabel('First Principal Component')\n",
        "plt.ylabel('Second Principal Component')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 279
        },
        "id": "lwXrDl6pniuj",
        "outputId": "6fe73cbc-ec7e-48f1-cb79-7816cf14202a"
      },
      "id": "lwXrDl6pniuj",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import seaborn as sns\n",
        "\n",
        "# Plot the violin plots\n",
        "sns.violinplot(data=data_modeling_pca, x='cluster', y='PC1', inner='stick')\n",
        "sns.violinplot(data=data_modeling_pca, x='cluster', y='PC2', inner='stick')\n",
        "\n",
        "# Add axis labels and show the plot\n",
        "plt.xlabel('Cluster')\n",
        "plt.ylabel('PCA Transformed Data')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 279
        },
        "id": "gcjVrjXJoGIK",
        "outputId": "f6302120-f0c6-416c-bd00-4eb08cdb684b"
      },
      "id": "gcjVrjXJoGIK",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.cluster import KMeans\n",
        "#Initialize the class object\n",
        "kmeans = KMeans(n_clusters= 4)\n",
        "#predict the labels of clusters.\n",
        "label = kmeans.fit_predict(mod_data)\n",
        "print(label)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "oRop12TNBBDn",
        "outputId": "86b93d17-e816-439e-cd09-bb0ce93354ac"
      },
      "id": "oRop12TNBBDn",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[0 0 3 3 1 1 2 2 3 1 2 3 3 3 1 1 1 3 1 1 3 3 1 1 3 1 3 1 2 3 1 2 2 3 3 2 1\n",
            " 3 3 2 1 3 2 3 2 3 3 2 0 3 1 2 3]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "unique, counts = np.unique(label, return_counts=True)\n",
        "plt.bar(unique, counts)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 265
        },
        "id": "Pengmfg6Os11",
        "outputId": "d66d43c1-abd2-4635-ff1e-bfb79b99ce09"
      },
      "id": "Pengmfg6Os11",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "for i in range(4):\n",
        "    # Extract data for each cluster\n",
        "    cluster_data = mod_data[label == i]\n",
        "    # create violin plot\n",
        "    sns.violinplot(x=' Co-assembly contigs ', data=cluster_data)\n",
        "    plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "sVBaAQ4aCNxH",
        "outputId": "da2d3a5f-675b-40a6-ca4a-4b1abf7bb9be"
      },
      "id": "sVBaAQ4aCNxH",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    }
  ],
  "metadata": {
    "kernelspec": {
      "display_name": "Python 3 (ipykernel)",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.10.4"
    },
    "colab": {
      "provenance": []
    }
  },
  "nbformat": 4,
  "nbformat_minor": 5
}