projr.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "5680b835",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "package 'cellranger' successfully unpacked and MD5 sums checked\n",
      "\n",
      "The downloaded binary packages are in\n",
      "\tC:\\Users\\banog\\AppData\\Local\\Temp\\Rtmp4qVuFa\\downloaded_packages\n",
      "package 'pkgconfig' successfully unpacked and MD5 sums checked\n",
      "\n",
      "The downloaded binary packages are in\n",
      "\tC:\\Users\\banog\\AppData\\Local\\Temp\\Rtmp4qVuFa\\downloaded_packages\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message:\n",
      "\"package 'readxl' is in use and will not be installed\"\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tibble [41,729 x 58] (S3: tbl_df/tbl/data.frame)\n",
      " $ lsoa11      : chr [1:41729] \"E01000001\" \"E01000002\" \"E01000003\" \"E01000005\" ...\n",
      " $ ah3gp       : num [1:41729] 2.11 3.15 1.15 1.46 1.58 ...\n",
      " $ ah3dent     : num [1:41729] 0.4 0.887 0 0.565 2.15 ...\n",
      " $ ah3phar     : num [1:41729] 0.562 0.879 0.347 0.943 1.867 ...\n",
      " $ ah3hosp     : num [1:41729] 0.492 1.449 0.649 1.224 1.585 ...\n",
      " $ ah3blue     : num [1:41729] 2.88 2.94 3.27 2.1 2.79 ...\n",
      " $ ah3gpas     : num [1:41729] 0.1094 0.0853 0.138 0.0774 0.331 ...\n",
      " $ ah3ffood    : num [1:41729] 0 0.2808 0.0625 0.09 0.9087 ...\n",
      " $ ah3gamb     : num [1:41729] 1.31 1.27 1.14 1.23 1.37 ...\n",
      " $ ah3leis     : num [1:41729] 0.287 0.818 0.37 0.522 1.8 ...\n",
      " $ ah3pubs     : num [1:41729] 0.0779 0.2225 0 0.0501 1.585 ...\n",
      " $ ah3tob      : num [1:41729] 1.645 2.132 1.035 1.218 0.909 ...\n",
      " $ ah3no2      : num [1:41729] 42.3 41.4 41.4 39.6 31.2 ...\n",
      " $ ah3so2      : num [1:41729] 3.24 3.16 3.16 2.98 2.27 ...\n",
      " $ ah3pm10     : num [1:41729] 20.3 20.5 20.5 20.3 20.4 ...\n",
      " $ ah3gp_rnk   : num [1:41729] 12492 20665 3716 6479 7668 ...\n",
      " $ ah3dent_rnk : num [1:41729] 277 2564 1 713 13959 ...\n",
      " $ ah3phar_rnk : num [1:41729] 785 2999 222 3633 14749 ...\n",
      " $ ah3hosp_rnk : num [1:41729] 392 7333 933 5163 8677 ...\n",
      " $ ah3leis_rnk : num [1:41729] 50 914 101 250 4973 ...\n",
      " $ ah3gpas_rnk : num [1:41729] 41618 41703 41410 41720 34750 ...\n",
      " $ ah3blue_rnk : num [1:41729] 14033 14376 16345 9255 13600 ...\n",
      " $ ah3no2_rnk  : num [1:41729] 41717 41706 41706 41625 41197 ...\n",
      " $ ah3so2_rnk  : num [1:41729] 41459 41400 41400 41224 38387 ...\n",
      " $ ah3pm10_rnk : num [1:41729] 41254 41440 41440 41210 41416 ...\n",
      " $ ah3gamb_rnk : num [1:41729] 36496 36745 37818 37130 35999 ...\n",
      " $ ah3pubs_rnk : num [1:41729] 41454 41168 41513 41484 31004 ...\n",
      " $ ah3tob_rnk  : num [1:41729] 38271 36088 40430 39853 40809 ...\n",
      " $ ah3ffood_rnk: num [1:41729] 41576 41082 41543 41521 36238 ...\n",
      " $ ah3gp_pct   : num [1:41729] 29 49 8 15 18 0 40 3 9 7 ...\n",
      " $ ah3dent_pct : num [1:41729] 0 6 0 1 33 2 51 16 0 29 ...\n",
      " $ ah3phar_pct : num [1:41729] 1 7 0 8 35 12 65 35 0 38 ...\n",
      " $ ah3hosp_pct : num [1:41729] 0 17 2 12 20 1 45 4 0 8 ...\n",
      " $ ah3leis_pct : num [1:41729] 0 2 0 0 11 5 32 3 1 16 ...\n",
      " $ ah3gpas_pct : num [1:41729] 99 99 99 99 83 96 47 96 99 95 ...\n",
      " $ ah3blue_pct : num [1:41729] 33 34 39 22 32 10 3 20 19 2 ...\n",
      " $ ah3no2_pct  : num [1:41729] 99 99 99 99 98 97 97 98 98 98 ...\n",
      " $ ah3so2_pct  : num [1:41729] 99 99 99 98 91 94 96 90 96 90 ...\n",
      " $ ah3pm10_pct : num [1:41729] 98 99 99 98 99 99 99 99 99 99 ...\n",
      " $ ah3gamb_pct : num [1:41729] 87 88 90 89 86 94 50 98 99 98 ...\n",
      " $ ah3pubs_pct : num [1:41729] 99 99 100 99 74 81 37 95 82 78 ...\n",
      " $ ah3tob_pct  : num [1:41729] 91 86 96 95 97 95 69 99 95 89 ...\n",
      " $ ah3ffood_pct: num [1:41729] 100 98 99 99 87 84 40 100 89 89 ...\n",
      " $ ah3h        : num [1:41729] -2.09 -1.19 -2.59 -1.63 -0.74 ...\n",
      " $ ah3g        : num [1:41729] 1.181 1.411 1.075 1.37 0.257 ...\n",
      " $ ah3e        : num [1:41729] 2.73 2.71 2.71 2.43 2.02 ...\n",
      " $ ah3r        : num [1:41729] 1.92 1.66 2.09 2 1.22 ...\n",
      " $ ah3h_rnk    : num [1:41729] 178 3134 21 925 7812 ...\n",
      " $ ah3g_rnk    : num [1:41729] 40859 41483 40316 41406 26745 ...\n",
      " $ ah3e_rnk    : num [1:41729] 41686 41676 41676 41607 41322 ...\n",
      " $ ah3r_rnk    : num [1:41729] 41111 40437 41376 41260 38120 ...\n",
      " $ ah3h_pct    : num [1:41729] 1 8 1 3 19 1 48 6 1 14 ...\n",
      " $ ah3g_pct    : num [1:41729] 98 100 97 100 65 64 9 78 91 39 ...\n",
      " $ ah3e_pct    : num [1:41729] 100 100 100 100 100 100 100 100 100 100 ...\n",
      " $ ah3r_pct    : num [1:41729] 99 97 100 99 92 93 49 100 98 94 ...\n",
      " $ ah3ahah     : num [1:41729] 64.8 65.8 64.3 67.7 42.1 ...\n",
      " $ ah3ahah_rn  : num [1:41729] 41700 41703 41695 41710 40256 ...\n",
      " $ ah3ahah_pc  : num [1:41729] 100 100 100 100 97 97 87 100 100 96 ...\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "    lsoa11              ah3gp            ah3dent           ah3phar       \n",
       " Length:41729       Min.   :  0.000   Min.   :  0.000   Min.   :  0.000  \n",
       " Class :character   1st Qu.:  1.874   1st Qu.:  1.768   1st Qu.:  1.515  \n",
       " Mode  :character   Median :  3.175   Median :  3.031   Median :  2.434  \n",
       "                    Mean   :  5.018   Mean   :  5.410   Mean   :  4.114  \n",
       "                    3rd Qu.:  5.626   3rd Qu.:  5.467   3rd Qu.:  4.028  \n",
       "                    Max.   :167.614   Max.   :396.674   Max.   :167.614  \n",
       "    ah3hosp           ah3blue          ah3gpas          ah3ffood      \n",
       " Min.   :  0.000   Min.   : 0.000   Min.   :0.0000   Min.   :  0.000  \n",
       " 1st Qu.:  1.774   1st Qu.: 2.281   1st Qu.:0.3682   1st Qu.:  1.362  \n",
       " Median :  3.187   Median : 4.087   Median :0.4345   Median :  2.670  \n",
       " Mean   :  6.432   Mean   : 4.857   Mean   :0.4342   Mean   :  6.256  \n",
       " 3rd Qu.:  6.912   3rd Qu.: 6.559   3rd Qu.:0.4988   3rd Qu.:  6.074  \n",
       " Max.   :400.039   Max.   :34.611   Max.   :0.8637   Max.   :528.109  \n",
       "    ah3gamb            ah3leis            ah3pubs            ah3tob       \n",
       " Min.   :   0.000   Min.   :   0.000   Min.   :  0.000   Min.   :  0.000  \n",
       " 1st Qu.:   1.929   1st Qu.:   2.929   1st Qu.:  1.555   1st Qu.:  3.175  \n",
       " Median :   3.423   Median :   5.464   Median :  2.818   Median :  5.927  \n",
       " Mean   :   8.301   Mean   :  13.156   Mean   :  5.607   Mean   : 12.208  \n",
       " 3rd Qu.:   6.997   3rd Qu.:  11.160   3rd Qu.:  5.265   3rd Qu.: 12.262  \n",
       " Max.   :1170.300   Max.   :1764.103   Max.   :528.579   Max.   :929.445  \n",
       "     ah3no2           ah3so2         ah3pm10         ah3gp_rnk    \n",
       " Min.   : 1.328   Min.   :0.193   Min.   : 4.499   Min.   :    1  \n",
       " 1st Qu.: 8.754   1st Qu.:0.948   1st Qu.:11.198   1st Qu.:10433  \n",
       " Median :12.412   Median :1.281   Median :13.886   Median :20862  \n",
       " Mean   :13.277   Mean   :1.382   Mean   :13.583   Mean   :20864  \n",
       " 3rd Qu.:16.718   3rd Qu.:1.767   3rd Qu.:15.913   3rd Qu.:31297  \n",
       " Max.   :44.203   Max.   :6.739   Max.   :21.825   Max.   :41729  \n",
       "  ah3dent_rnk     ah3phar_rnk     ah3hosp_rnk     ah3leis_rnk   \n",
       " Min.   :    1   Min.   :    1   Min.   :    1   Min.   :    1  \n",
       " 1st Qu.:10431   1st Qu.:10433   1st Qu.:10433   1st Qu.:10433  \n",
       " Median :20865   Median :20865   Median :20865   Median :20865  \n",
       " Mean   :20865   Mean   :20864   Mean   :20864   Mean   :20865  \n",
       " 3rd Qu.:31297   3rd Qu.:31297   3rd Qu.:31297   3rd Qu.:31297  \n",
       " Max.   :41729   Max.   :41729   Max.   :41729   Max.   :41729  \n",
       "  ah3gpas_rnk     ah3blue_rnk      ah3no2_rnk      ah3so2_rnk   \n",
       " Min.   :    1   Min.   :    1   Min.   :    1   Min.   :    1  \n",
       " 1st Qu.:10433   1st Qu.:10433   1st Qu.:10432   1st Qu.:10433  \n",
       " Median :20865   Median :20865   Median :20865   Median :20865  \n",
       " Mean   :20865   Mean   :20865   Mean   :20865   Mean   :20865  \n",
       " 3rd Qu.:31297   3rd Qu.:31297   3rd Qu.:31297   3rd Qu.:31297  \n",
       " Max.   :41729   Max.   :41729   Max.   :41726   Max.   :41729  \n",
       "  ah3pm10_rnk     ah3gamb_rnk     ah3pubs_rnk      ah3tob_rnk   \n",
       " Min.   :    1   Min.   :    1   Min.   :    1   Min.   :    1  \n",
       " 1st Qu.:10433   1st Qu.:10433   1st Qu.:10433   1st Qu.:10433  \n",
       " Median :20865   Median :20864   Median :20864   Median :20865  \n",
       " Mean   :20865   Mean   :20865   Mean   :20864   Mean   :20865  \n",
       " 3rd Qu.:31297   3rd Qu.:31295   3rd Qu.:31290   3rd Qu.:31297  \n",
       " Max.   :41724   Max.   :41711   Max.   :41513   Max.   :41725  \n",
       "  ah3ffood_rnk     ah3gp_pct      ah3dent_pct     ah3phar_pct   \n",
       " Min.   :    1   Min.   :  0.0   Min.   :  0.0   Min.   :  0.0  \n",
       " 1st Qu.:10433   1st Qu.: 25.0   1st Qu.: 24.0   1st Qu.: 25.0  \n",
       " Median :20865   Median : 49.0   Median : 50.0   Median : 50.0  \n",
       " Mean   :20864   Mean   : 49.5   Mean   : 49.5   Mean   : 49.5  \n",
       " 3rd Qu.:31293   3rd Qu.: 75.0   3rd Qu.: 75.0   3rd Qu.: 75.0  \n",
       " Max.   :41576   Max.   :100.0   Max.   :100.0   Max.   :100.0  \n",
       "  ah3hosp_pct     ah3leis_pct     ah3gpas_pct     ah3blue_pct   \n",
       " Min.   :  0.0   Min.   :  0.0   Min.   :  0.0   Min.   :  0.0  \n",
       " 1st Qu.: 25.0   1st Qu.: 25.0   1st Qu.: 25.0   1st Qu.: 25.0  \n",
       " Median : 50.0   Median : 50.0   Median : 50.0   Median : 50.0  \n",
       " Mean   : 49.5   Mean   : 49.5   Mean   : 49.5   Mean   : 49.5  \n",
       " 3rd Qu.: 75.0   3rd Qu.: 75.0   3rd Qu.: 75.0   3rd Qu.: 75.0  \n",
       " Max.   :100.0   Max.   :100.0   Max.   :100.0   Max.   :100.0  \n",
       "   ah3no2_pct      ah3so2_pct     ah3pm10_pct      ah3gamb_pct    \n",
       " Min.   :  0.0   Min.   :  0.0   Min.   :  0.00   Min.   :  0.00  \n",
       " 1st Qu.: 25.0   1st Qu.: 25.0   1st Qu.: 25.00   1st Qu.: 25.00  \n",
       " Median : 50.0   Median : 50.0   Median : 50.00   Median : 50.00  \n",
       " Mean   : 49.5   Mean   : 49.5   Mean   : 49.51   Mean   : 49.52  \n",
       " 3rd Qu.: 75.0   3rd Qu.: 75.0   3rd Qu.: 75.00   3rd Qu.: 75.00  \n",
       " Max.   :100.0   Max.   :100.0   Max.   :100.00   Max.   :100.00  \n",
       "  ah3pubs_pct       ah3tob_pct      ah3ffood_pct         ah3h          \n",
       " Min.   :  0.00   Min.   :  0.00   Min.   :  0.00   Min.   :-3.379653  \n",
       " 1st Qu.: 25.00   1st Qu.: 25.00   1st Qu.: 25.00   1st Qu.:-0.559559  \n",
       " Median : 50.00   Median : 50.00   Median : 50.00   Median :-0.018986  \n",
       " Mean   : 49.76   Mean   : 49.51   Mean   : 49.68   Mean   :-0.000339  \n",
       " 3rd Qu.: 75.00   3rd Qu.: 75.00   3rd Qu.: 75.00   3rd Qu.: 0.512488  \n",
       " Max.   :100.00   Max.   :100.00   Max.   :100.00   Max.   : 3.582578  \n",
       "      ah3g                ah3e                ah3r              ah3h_rnk    \n",
       " Min.   :-3.484349   Min.   :-3.673556   Min.   :-3.790165   Min.   :    1  \n",
       " 1st Qu.:-0.423052   1st Qu.:-0.567288   1st Qu.:-0.564542   1st Qu.:10433  \n",
       " Median : 0.028231   Median : 0.021504   Median : 0.021612   Median :20865  \n",
       " Mean   :-0.000853   Mean   :-0.000093   Mean   :-0.000787   Mean   :20865  \n",
       " 3rd Qu.: 0.450462   3rd Qu.: 0.584801   3rd Qu.: 0.591106   3rd Qu.:31297  \n",
       " Max.   : 2.244929   Max.   : 3.063291   Max.   : 3.066847   Max.   :41729  \n",
       "    ah3g_rnk        ah3e_rnk        ah3r_rnk        ah3h_pct    \n",
       " Min.   :    1   Min.   :    1   Min.   :    1   Min.   :  1.0  \n",
       " 1st Qu.:10433   1st Qu.:10433   1st Qu.:10433   1st Qu.: 25.0  \n",
       " Median :20865   Median :20864   Median :20865   Median : 50.0  \n",
       " Mean   :20865   Mean   :20865   Mean   :20865   Mean   : 50.5  \n",
       " 3rd Qu.:31297   3rd Qu.:31297   3rd Qu.:31297   3rd Qu.: 75.0  \n",
       " Max.   :41729   Max.   :41728   Max.   :41728   Max.   :100.0  \n",
       "    ah3g_pct        ah3e_pct        ah3r_pct        ah3ahah      \n",
       " Min.   :  1.0   Min.   :  1.0   Min.   :  1.0   Min.   : 2.038  \n",
       " 1st Qu.: 25.0   1st Qu.: 25.0   1st Qu.: 25.0   1st Qu.:15.328  \n",
       " Median : 50.0   Median : 50.0   Median : 50.0   Median :19.835  \n",
       " Mean   : 50.5   Mean   : 50.5   Mean   : 50.5   Mean   :21.691  \n",
       " 3rd Qu.: 75.0   3rd Qu.: 75.0   3rd Qu.: 75.0   3rd Qu.:26.021  \n",
       " Max.   :100.0   Max.   :100.0   Max.   :100.0   Max.   :73.545  \n",
       "   ah3ahah_rn      ah3ahah_pc   \n",
       " Min.   :    1   Min.   :  1.0  \n",
       " 1st Qu.:10433   1st Qu.: 25.0  \n",
       " Median :20865   Median : 50.0  \n",
       " Mean   :20865   Mean   : 50.5  \n",
       " 3rd Qu.:31297   3rd Qu.: 75.0  \n",
       " Max.   :41729   Max.   :100.0  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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AQBQoIAIUGAkCBASBAgJAgQEgQICQKE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\nAABJRU5ErkJggg==",
      "text/plain": [
       "Plot with title \"Distribution of ah3gp\""
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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+heICTG4sH72v3UJroXCImxEBIEOPwN\nAUKCgH94T8hnN/HxAiExFt2QfiQnITF+QoIAIUGAkCBASBAgJAi4hvT9j73suYmPFwiJsRAS\nBFjZAAFCggAhQYCQIEBIECAkCBASBAgJAoQEAUKCACFBgJAgQEgQICQIEBIECAkChAQBQoIA\nIUGAkCBASBAgJAgQEgQICQKEBAFCggAhQYCQIEBIECAkCBASBAgJAoQEAUKCACFBgJAgQEgQ\nICQIEBIECAkChAQBQoIAIUGAkCBASBAgJAgQEgQICQKEBAFCggAhQYCQIEBIECAkCBASBAgJ\nAoQEAUKCACFBgJAgQEgQICQIEBIECAkChAQBQoIAIUGAkCBASBAgJAgQEgQICQL6T9b126zU\nZot1z00IidHoO1l3k3I17bcJITEafSfrolTvm+ar7aoqi16bEBKj0XeyVmVz+XpTql6bEBKj\n0XeylvLom+9vQkiMhj0SBDzxGmm1bb7yGgn6H/6eto7aTXa9NiEkRuOJ80iL5jxSNXtzHomX\nZ2UDBAgJAiwRggBLhCDAEiEIcEIWAiwRggB7JAiwRAgCLBGCAEuEIMDKBggQEgRYIgQBlghB\ngCVCEOCELAT80BKh0vbwPoTEWNgjQYAlQhBgiRAEWCIEAVY2QICQIMASIQiwRAgCLBGCACdk\nIcC7CEGAPRIEWCIEAZYIQYAlQhBgZQMECAkChAQBQoIAIUFA/5UN33p/k083ISRGo+9kXQoJ\nrnpP1k31+S9PfGMTQmI0+k/WzecLg76xCSExGk9M1mVr3WqvTQiJ0XDUDgKEBAFCggAhQYCQ\nIEBIECAkCBASBAgJAoQEAUKCACFBgJAgQEgQICQIEBIECAkChAQBQoIAIUGAkCBASBAgJAgQ\nEgQICQKEBAFCggAhQYCQIEBIECAkCBASBAgJAoQEAUKCACFBgJAgQEgQICQIEBIECAkChAQB\nQoIAIUGAkCBASBAgJAgQEgQICQKEBAFCggAhQYCQIEBIECAkCBASBAgJAoQEAUKCACFBgJAg\nQEgQICQIEBIECAkChAQBQoIAIUGAkCBASBAgJAgQEgQICQKEBAFCggAhQYCQIEBIECAkCBAS\nBAgJAoQEAUKCACFBgJAgQEgQICQIEBIECAkChAQBQoIAIUGAkCBASBAw6JC+8vNjh+8ZdEj2\nWPxXCAkChAQBQoIAIUGAkCBASBAgJAgQEgQICQKEBAFCggAhQYCQIEBIECAkCBASBAgJAoQE\nAf0n4/pt1rxxwmyx7rkJITEafSfjbtJ6E5Jpv008HZI3R2Eo+k62RaneN81X21VVFr028XRI\nX13e8/8N/lnfyVaVzeXrTal6beLHQ7LH4rf0nUydWfhxSn5rvn450eEn9Zz79ydzz9v9wx4J\nxu+J10irbfPVl6+RYPx6796mrV3kZJccEvz3PHEeadGcR6pmb1+cR4Lxc+QKAoQEAUKCACFB\ngJAgQEgQICQIEBIECAkChAQBQoIAIUGAkCBASBAgJAgQEgQICQKEBAF/GdIfvQkTHEUnc/LO\n/kPb/g7je85LjU9Ijxnfc15qfEJ6zPie81LjE9JjxveclxqfkB4zvue81PiE9JjxPeelxiek\nx4zvOS81PiE9ZnzPeanxCekx43vOS41PSI8Z33NeanxCesz4nvNS4xPSY8b3nJca39D/Z+E/\nQUgQICQIEBIECAkChAQBQoIAIUGAkCBASBAgJAgQEgQICQKEBAFCggAhQcCfhbSoSrXY/dXW\nH1qeH5DW+IYz1OXk3qAGM77dvJT55vj1EMdXW5/+gtPj+6uQps3HAUz+aOsPbc4fUdAa33CG\numhGUtV/54McX9WMpClpkOM72FXHv+D4+P4opHWpNvtNVdZ/s/lHDiM6PiCt8Q1nqJsy39X7\nzPlAx7eoR7Yos/1Ax1ebHf+C8+P7o5AWZXX473t5+5vNP7As01NIrfENZ6iz49jqIQ5yfFWp\n95XNIzjI8e3rYRz/gvPj+6OQZmW7r/+Jnf3N5h8oi/0ppNb4BjfUeogDHl+p9oMd3/b8L2V+\nfH8UUintP4Ziczuw+o+hDXVXpkMe36Is94Md37Rsj+PIj09IXcMPaVk/FRnq+A5PnRb1n8Mc\n31t53wvpdww+pG1VPwcZ6viWs6p5sTHI8TVP34T0O4Ye0q6a1n8Mdnz7/bx+bjfI8U3qEwcj\nC6kazKN74zSi1viGNdTp8XzHYMdXv4arhjm+eXN47jiO/Pj+9KjddhCHcjo6R+2216M6wxjq\ndjLdNl8MdHyN61HFYY2vXPzE+P4opLfmX4fV8ZXpkJxCao1vQENdlenpq0GO73geaVsvEhji\n+Noh5cdnZUPXkFc2bC8dDXN8zcqG3ax+jTTI8TVGtrJhP2n+aZh+fcVfdn6q3BrfYIY6v/6L\nOsjxndba3Q5qOOOrnf6C4+P7q5B2zZLbP9r4J84htcY3mKG2npoMcnzNOurJsvlqmOPbX/6C\n4+P782MpMAZCggAhQYCQIEBIECAkCBASBAgJAoQEAUKCACFBgJAgQEgQICQIEBIECAkChAQB\nQoIAIUGAkCBASBAgJAgQEgQICQKEBAFCggAhQYCQIEBIECAkCBASBAgJAoQEAUL6D2h9dP1u\nXsp8c/+yG6ufHBI3hPQf0Irl+DGtm7uXdU381f4mj/Z/wDWW5oPDF2V277KHN+IXeLT/A65N\nVGW37zYipGHwaA/WalZOn7Z9aGJRqrfLJaVq/lhUZXHqZTkp1fJ41e2suer548/5HR7roXpr\nUih1SaXM6i+Xp0sWx6+m9c9mTS3NxWXaXLV5FfUmpF/msR6qUt73+/cmhkMju/2yTJqfvx/j\nOvxZbfabqr7Cqr58Ny2r9lVl9Ks82sN2Cmm9v5SxnFWlfpY3a364qn86a1457epjENerCulX\nebSHa7t6m55C2u/bZczr53anb4/NnLSvKqRf5dEerOk5jg8h7eqjDUIaFI/2UM3LZLna3g2p\nHcpNM0L6Ix7toWpCuA3peB5pWx9MmNXHFvbr42ukVedWQvp9Hu2hqg8bbG5fIzUrG3az+jXS\n6nrUrjmAt18eDzacr1rK9k/H/2KENFSL0+uedeepXXU5Y3Q8eTRvfnp8OVVt21edlNN5W36D\nkAbr0Mh0veruZprlDJPTmdm3zsqGMt/u21ddT4T0i4QEAUKCACFBgJAgQEgQICQIEBIECAkC\nhAQBQoIAIUGAkCBASBAgJAgQEgQICQKEBAFCggAhQYCQIEBIECAkCBASBAgJAoQEAUKCACFB\ngJAgQEgQICQIEBIE/B8nxCOoazD5mAAAAABJRU5ErkJggg==",
      "text/plain": [
       "Plot with title \"Distribution of ah3dent\""
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style>\n",
       ".dl-inline {width: auto; margin:0; padding: 0}\n",
       ".dl-inline>dt, .dl-inline>dd {float: none; width: auto; display: inline-block}\n",
       ".dl-inline>dt::after {content: \":\\0020\"; padding-right: .5ex}\n",
       ".dl-inline>dt:not(:first-of-type) {padding-left: .5ex}\n",
       "</style><dl class=dl-inline><dt>lsoa11</dt><dd>0</dd><dt>ah3gp</dt><dd>0</dd><dt>ah3dent</dt><dd>0</dd><dt>ah3phar</dt><dd>0</dd><dt>ah3hosp</dt><dd>0</dd><dt>ah3blue</dt><dd>0</dd><dt>ah3gpas</dt><dd>0</dd><dt>ah3ffood</dt><dd>0</dd><dt>ah3gamb</dt><dd>0</dd><dt>ah3leis</dt><dd>0</dd><dt>ah3pubs</dt><dd>0</dd><dt>ah3tob</dt><dd>0</dd><dt>ah3no2</dt><dd>0</dd><dt>ah3so2</dt><dd>0</dd><dt>ah3pm10</dt><dd>0</dd><dt>ah3gp_rnk</dt><dd>0</dd><dt>ah3dent_rnk</dt><dd>0</dd><dt>ah3phar_rnk</dt><dd>0</dd><dt>ah3hosp_rnk</dt><dd>0</dd><dt>ah3leis_rnk</dt><dd>0</dd><dt>ah3gpas_rnk</dt><dd>0</dd><dt>ah3blue_rnk</dt><dd>0</dd><dt>ah3no2_rnk</dt><dd>0</dd><dt>ah3so2_rnk</dt><dd>0</dd><dt>ah3pm10_rnk</dt><dd>0</dd><dt>ah3gamb_rnk</dt><dd>0</dd><dt>ah3pubs_rnk</dt><dd>0</dd><dt>ah3tob_rnk</dt><dd>0</dd><dt>ah3ffood_rnk</dt><dd>0</dd><dt>ah3gp_pct</dt><dd>0</dd><dt>ah3dent_pct</dt><dd>0</dd><dt>ah3phar_pct</dt><dd>0</dd><dt>ah3hosp_pct</dt><dd>0</dd><dt>ah3leis_pct</dt><dd>0</dd><dt>ah3gpas_pct</dt><dd>0</dd><dt>ah3blue_pct</dt><dd>0</dd><dt>ah3no2_pct</dt><dd>0</dd><dt>ah3so2_pct</dt><dd>0</dd><dt>ah3pm10_pct</dt><dd>0</dd><dt>ah3gamb_pct</dt><dd>0</dd><dt>ah3pubs_pct</dt><dd>0</dd><dt>ah3tob_pct</dt><dd>0</dd><dt>ah3ffood_pct</dt><dd>0</dd><dt>ah3h</dt><dd>0</dd><dt>ah3g</dt><dd>0</dd><dt>ah3e</dt><dd>0</dd><dt>ah3r</dt><dd>0</dd><dt>ah3h_rnk</dt><dd>0</dd><dt>ah3g_rnk</dt><dd>0</dd><dt>ah3e_rnk</dt><dd>0</dd><dt>ah3r_rnk</dt><dd>0</dd><dt>ah3h_pct</dt><dd>0</dd><dt>ah3g_pct</dt><dd>0</dd><dt>ah3e_pct</dt><dd>0</dd><dt>ah3r_pct</dt><dd>0</dd><dt>ah3ahah</dt><dd>0</dd><dt>ah3ahah_rn</dt><dd>0</dd><dt>ah3ahah_pc</dt><dd>0</dd></dl>\n"
      ],
      "text/latex": [
       "\\begin{description*}\n",
       "\\item[lsoa11] 0\n",
       "\\item[ah3gp] 0\n",
       "\\item[ah3dent] 0\n",
       "\\item[ah3phar] 0\n",
       "\\item[ah3hosp] 0\n",
       "\\item[ah3blue] 0\n",
       "\\item[ah3gpas] 0\n",
       "\\item[ah3ffood] 0\n",
       "\\item[ah3gamb] 0\n",
       "\\item[ah3leis] 0\n",
       "\\item[ah3pubs] 0\n",
       "\\item[ah3tob] 0\n",
       "\\item[ah3no2] 0\n",
       "\\item[ah3so2] 0\n",
       "\\item[ah3pm10] 0\n",
       "\\item[ah3gp\\textbackslash{}\\_rnk] 0\n",
       "\\item[ah3dent\\textbackslash{}\\_rnk] 0\n",
       "\\item[ah3phar\\textbackslash{}\\_rnk] 0\n",
       "\\item[ah3hosp\\textbackslash{}\\_rnk] 0\n",
       "\\item[ah3leis\\textbackslash{}\\_rnk] 0\n",
       "\\item[ah3gpas\\textbackslash{}\\_rnk] 0\n",
       "\\item[ah3blue\\textbackslash{}\\_rnk] 0\n",
       "\\item[ah3no2\\textbackslash{}\\_rnk] 0\n",
       "\\item[ah3so2\\textbackslash{}\\_rnk] 0\n",
       "\\item[ah3pm10\\textbackslash{}\\_rnk] 0\n",
       "\\item[ah3gamb\\textbackslash{}\\_rnk] 0\n",
       "\\item[ah3pubs\\textbackslash{}\\_rnk] 0\n",
       "\\item[ah3tob\\textbackslash{}\\_rnk] 0\n",
       "\\item[ah3ffood\\textbackslash{}\\_rnk] 0\n",
       "\\item[ah3gp\\textbackslash{}\\_pct] 0\n",
       "\\item[ah3dent\\textbackslash{}\\_pct] 0\n",
       "\\item[ah3phar\\textbackslash{}\\_pct] 0\n",
       "\\item[ah3hosp\\textbackslash{}\\_pct] 0\n",
       "\\item[ah3leis\\textbackslash{}\\_pct] 0\n",
       "\\item[ah3gpas\\textbackslash{}\\_pct] 0\n",
       "\\item[ah3blue\\textbackslash{}\\_pct] 0\n",
       "\\item[ah3no2\\textbackslash{}\\_pct] 0\n",
       "\\item[ah3so2\\textbackslash{}\\_pct] 0\n",
       "\\item[ah3pm10\\textbackslash{}\\_pct] 0\n",
       "\\item[ah3gamb\\textbackslash{}\\_pct] 0\n",
       "\\item[ah3pubs\\textbackslash{}\\_pct] 0\n",
       "\\item[ah3tob\\textbackslash{}\\_pct] 0\n",
       "\\item[ah3ffood\\textbackslash{}\\_pct] 0\n",
       "\\item[ah3h] 0\n",
       "\\item[ah3g] 0\n",
       "\\item[ah3e] 0\n",
       "\\item[ah3r] 0\n",
       "\\item[ah3h\\textbackslash{}\\_rnk] 0\n",
       "\\item[ah3g\\textbackslash{}\\_rnk] 0\n",
       "\\item[ah3e\\textbackslash{}\\_rnk] 0\n",
       "\\item[ah3r\\textbackslash{}\\_rnk] 0\n",
       "\\item[ah3h\\textbackslash{}\\_pct] 0\n",
       "\\item[ah3g\\textbackslash{}\\_pct] 0\n",
       "\\item[ah3e\\textbackslash{}\\_pct] 0\n",
       "\\item[ah3r\\textbackslash{}\\_pct] 0\n",
       "\\item[ah3ahah] 0\n",
       "\\item[ah3ahah\\textbackslash{}\\_rn] 0\n",
       "\\item[ah3ahah\\textbackslash{}\\_pc] 0\n",
       "\\end{description*}\n"
      ],
      "text/markdown": [
       "lsoa11\n",
       ":   0ah3gp\n",
       ":   0ah3dent\n",
       ":   0ah3phar\n",
       ":   0ah3hosp\n",
       ":   0ah3blue\n",
       ":   0ah3gpas\n",
       ":   0ah3ffood\n",
       ":   0ah3gamb\n",
       ":   0ah3leis\n",
       ":   0ah3pubs\n",
       ":   0ah3tob\n",
       ":   0ah3no2\n",
       ":   0ah3so2\n",
       ":   0ah3pm10\n",
       ":   0ah3gp_rnk\n",
       ":   0ah3dent_rnk\n",
       ":   0ah3phar_rnk\n",
       ":   0ah3hosp_rnk\n",
       ":   0ah3leis_rnk\n",
       ":   0ah3gpas_rnk\n",
       ":   0ah3blue_rnk\n",
       ":   0ah3no2_rnk\n",
       ":   0ah3so2_rnk\n",
       ":   0ah3pm10_rnk\n",
       ":   0ah3gamb_rnk\n",
       ":   0ah3pubs_rnk\n",
       ":   0ah3tob_rnk\n",
       ":   0ah3ffood_rnk\n",
       ":   0ah3gp_pct\n",
       ":   0ah3dent_pct\n",
       ":   0ah3phar_pct\n",
       ":   0ah3hosp_pct\n",
       ":   0ah3leis_pct\n",
       ":   0ah3gpas_pct\n",
       ":   0ah3blue_pct\n",
       ":   0ah3no2_pct\n",
       ":   0ah3so2_pct\n",
       ":   0ah3pm10_pct\n",
       ":   0ah3gamb_pct\n",
       ":   0ah3pubs_pct\n",
       ":   0ah3tob_pct\n",
       ":   0ah3ffood_pct\n",
       ":   0ah3h\n",
       ":   0ah3g\n",
       ":   0ah3e\n",
       ":   0ah3r\n",
       ":   0ah3h_rnk\n",
       ":   0ah3g_rnk\n",
       ":   0ah3e_rnk\n",
       ":   0ah3r_rnk\n",
       ":   0ah3h_pct\n",
       ":   0ah3g_pct\n",
       ":   0ah3e_pct\n",
       ":   0ah3r_pct\n",
       ":   0ah3ahah\n",
       ":   0ah3ahah_rn\n",
       ":   0ah3ahah_pc\n",
       ":   0\n",
       "\n"
      ],
      "text/plain": [
       "      lsoa11        ah3gp      ah3dent      ah3phar      ah3hosp      ah3blue \n",
       "           0            0            0            0            0            0 \n",
       "     ah3gpas     ah3ffood      ah3gamb      ah3leis      ah3pubs       ah3tob \n",
       "           0            0            0            0            0            0 \n",
       "      ah3no2       ah3so2      ah3pm10    ah3gp_rnk  ah3dent_rnk  ah3phar_rnk \n",
       "           0            0            0            0            0            0 \n",
       " ah3hosp_rnk  ah3leis_rnk  ah3gpas_rnk  ah3blue_rnk   ah3no2_rnk   ah3so2_rnk \n",
       "           0            0            0            0            0            0 \n",
       " ah3pm10_rnk  ah3gamb_rnk  ah3pubs_rnk   ah3tob_rnk ah3ffood_rnk    ah3gp_pct \n",
       "           0            0            0            0            0            0 \n",
       " ah3dent_pct  ah3phar_pct  ah3hosp_pct  ah3leis_pct  ah3gpas_pct  ah3blue_pct \n",
       "           0            0            0            0            0            0 \n",
       "  ah3no2_pct   ah3so2_pct  ah3pm10_pct  ah3gamb_pct  ah3pubs_pct   ah3tob_pct \n",
       "           0            0            0            0            0            0 \n",
       "ah3ffood_pct         ah3h         ah3g         ah3e         ah3r     ah3h_rnk \n",
       "           0            0            0            0            0            0 \n",
       "    ah3g_rnk     ah3e_rnk     ah3r_rnk     ah3h_pct     ah3g_pct     ah3e_pct \n",
       "           0            0            0            0            0            0 \n",
       "    ah3r_pct      ah3ahah   ah3ahah_rn   ah3ahah_pc \n",
       "           0            0            0            0 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\tWelch Two Sample t-test\n",
      "\n",
      "data:  england_wales_data$ah3gp and scotland_data$ah3gp\n",
      "t = -10.299, df = 2022.9, p-value < 2.2e-16\n",
      "alternative hypothesis: true difference in means is not equal to 0\n",
      "95 percent confidence interval:\n",
      " -1.962203 -1.334460\n",
      "sample estimates:\n",
      "mean of x mean of y \n",
      " 4.657605  6.305936 \n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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YCQIEBIECAkCBASBAgJAoQEAUKCACFB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\nAoQEAUKCgP8BUWdNmazcvkoAAAAASUVORK5CYII=",
      "text/plain": [
       "Plot with title \"Distribution of ah3phar\""
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Step 1: Install and load necessary libraries\n",
    "install.packages(\"cellranger\")\n",
    "install.packages(\"pkgconfig\")\n",
    "install.packages(\"readxl\")\n",
    "library(readxl)\n",
    "\n",
    "# Step 2: Load AHAH dataset into a data frame\n",
    "# Assuming your dataset is in an Excel file named 'MANPO98.xlsx'\n",
    "file_path <- '/users/banog/desktop/xx.xlsx'\n",
    "ahah_df <- read_excel(file_path)\n",
    "\n",
    "# Step 3: Exploratory Data Analysis (EDA)\n",
    "# Display basic information about the dataset\n",
    "str(ahah_df)\n",
    "\n",
    "# Display summary statistics\n",
    "summary(ahah_df)\n",
    "\n",
    "for (column in c(\"ah3gp\", \"ah3dent\", \"ah3phar\")) {\n",
    "  hist(ahah_df[[column]], main = paste(\"Distribution of\", column), col = \"blue\", xlab = column)\n",
    "}\n",
    "\n",
    "# Identify missing values\n",
    "colSums(is.na(ahah_df))\n",
    "\n",
    "# Subset LSOAs for England and Wales\n",
    "england_wales_data <- ahah_df[grepl(\"^E\", ahah_df$lsoa11), ]\n",
    "\n",
    "# Subset LSOAs for Scotland\n",
    "scotland_data <- ahah_df[grepl(\"^W\", ahah_df$lsoa11), ]\n",
    "\n",
    "# Example t-test for ah3gp variable\n",
    "t_test_result <- t.test(england_wales_data$ah3gp, scotland_data$ah3gp)\n",
    "print(t_test_result)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "787a18c7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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8lvEULWfgjSqr62rmovVRVeHtRvApiJ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\nAgQJEPgf58EjNXD+fTAAAAAASUVORK5CYII=",
      "text/plain": [
       "Plot with title \"Boxplot of ah3gp across Regions\""
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "Plot with title \"Histogram of ah3hosp\""
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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2IKUvPHsps/me3bU7+E4dPdPx8o6pdvjgRzHGl3YgqSHSPvvvq9E6QGq4rxQdJB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\nAQIIEiCAIAEC/gMfdDlhtXS35AAAAABJRU5ErkJggg==",
      "text/plain": [
       "Plot with title \"Scatter Plot between ah3ffood and ah3leis\""
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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EgekI+ZfoWI5AH5mOlXiEgekI+ZfoU+RDqvQljux0F+HQWRykS+QhcinZvQ0Q6D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\nAJEADEAkAAP+B4GzVVUJ8lkXAAAAAElFTkSuQmCC",
      "text/plain": [
       "Plot with title \"Average ah3pubs by Region\""
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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EEZ322wE9LocbRVEra3D9TUAJSGjjAqCkKKtUrClq4YaANGRe1/ce6pao5Z5nkq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\n/w8CnwPHwtJt2gAAAABJRU5ErkJggg==",
      "text/plain": [
       "Plot with title \"Pie Chart of ah3gamb Percentages\""
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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3qv3cZOOX8+ucjT68yQ3OiADN2P0P1I91ayJk73tyncvmNf9X/VvP7q9q7U1enh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\nzD+EQxmSGx2QofsRuh+ZfwiHMiQ3OiBD9yN0PzL/EA5lSG50QIb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FgwTdaj9WaXv9XYpNfoh+XJEPUlGCBH3V3hiH650i/LlgoxU1RuEO\nUqUHbUjn9vHCwj47uaiQoh2kSo9uH/naPm1d2GOFRS12qmAHqZb8waKz2La/ar663iYL2yGL\nWuxksQ5Sxflg0SBBv9UP596bhwnb66HVfGgXV6iDVGE+WDRM0KvrT7f9sqgH3YWFFOogVZQP\nFg0T9PW9kJ8W9rKOApUWUiRVkBcdowRduxyu/84d19VqUQe/MyRSlKfTUYJetBg3ZZmifLBo\nlKAXrchdGOQgVZQPFo0S9KKVuAvDHKQK8sGiUYJetAJDinOQKsoHiwYJetEKDCnAQarqKW49\nQYJesv8Puheb62/83v0AAAAASUVORK5CYII=",
      "text/plain": [
       "Plot with title \"Correlation Heatmap\""
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\tWelch Two Sample t-test\n",
      "\n",
      "data:  england_wales_data$ah3phar and scotland_data$ah3phar\n",
      "t = -7.748, df = 2041, p-value = 1.46e-14\n",
      "alternative hypothesis: true difference in means is not equal to 0\n",
      "95 percent confidence interval:\n",
      " -1.4875158 -0.8865967\n",
      "sample estimates:\n",
      "mean of x mean of y \n",
      " 3.952814  5.139871 \n",
      "\n",
      "\n",
      "\tWelch Two Sample t-test\n",
      "\n",
      "data:  england_wales_data$ah3gp and scotland_data$ah3gp\n",
      "t = -10.299, df = 2022.9, p-value < 2.2e-16\n",
      "alternative hypothesis: true difference in means is not equal to 0\n",
      "95 percent confidence interval:\n",
      " -1.962203 -1.334460\n",
      "sample estimates:\n",
      "mean of x mean of y \n",
      " 4.657605  6.305936 \n",
      "\n",
      "\n",
      "\tWilcoxon rank sum test with continuity correction\n",
      "\n",
      "data:  england_wales_data$ah3hosp and scotland_data$ah3hosp\n",
      "W = 9400386, p-value < 2.2e-16\n",
      "alternative hypothesis: true location shift is not equal to 0\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "                           Df    Sum Sq Mean Sq F value Pr(>F)    \n",
       "substring(lsoa11, 1, 1)     2   3482442 1741221   619.2 <2e-16 ***\n",
       "Residuals               41726 117341443    2812                   \n",
       "---\n",
       "Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message in chisq.test(ahah_df$ah3gamb_pct, ahah_df$lsoa11):\n",
      "\"Chi-squared approximation may be incorrect\"\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\tPearson's Chi-squared test\n",
      "\n",
      "data:  ahah_df$ah3gamb_pct and ahah_df$lsoa11\n",
      "X-squared = 4172900, df = 4172800, p-value = 0.4861\n",
      "\n",
      "\n",
      "\tPaired t-test\n",
      "\n",
      "data:  ahah_df$ah3ffood and ahah_df$ah3pubs\n",
      "t = 30.944, df = 41728, p-value < 2.2e-16\n",
      "alternative hypothesis: true difference in means is not equal to 0\n",
      "95 percent confidence interval:\n",
      " 0.6080284 0.6902647\n",
      "sample estimates:\n",
      "mean of the differences \n",
      "              0.6491465 \n",
      "\n",
      "\n",
      "\tKruskal-Wallis rank sum test\n",
      "\n",
      "data:  ah3pm10 by substring(lsoa11, 1, 1)\n",
      "Kruskal-Wallis chi-squared = 17798, df = 2, p-value < 2.2e-16\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "Plot with title \"Boxplot of ah3dent across Regions\""
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualization\n",
    "# Create visual representations of key findings using base R plotting functions\n",
    "# Example 1: Boxplot of ah3gp across regions\n",
    "boxplot(ah3gp ~ substring(lsoa11, 1, 1), data = ahah_df, col = \"lightblue\", main = \"Boxplot of ah3gp across Regions\")\n",
    "\n",
    "# Example 2: Histogram of ah3hosp\n",
    "hist(ahah_df$ah3hosp, col = \"salmon\", main = \"Histogram of ah3hosp\", xlab = \"ah3hosp\")\n",
    "\n",
    "# Example 3: Scatter plot between ah3ffood and ah3leis\n",
    "plot(ahah_df$ah3ffood, ahah_df$ah3leis, col = \"darkgreen\", main = \"Scatter Plot between ah3ffood and ah3leis\", xlab = \"ah3ffood\", ylab = \"ah3leis\")\n",
    "\n",
    "# Example 4: Bar plot of average ah3pubs by region\n",
    "avg_pubs_by_region <- tapply(ahah_df$ah3pubs, substring(ahah_df$lsoa11, 1, 1), mean)\n",
    "barplot(avg_pubs_by_region, col = \"skyblue\", main = \"Average ah3pubs by Region\", xlab = \"Region\", ylab = \"Average ah3pubs\")\n",
    "\n",
    "# Example 5: Pie chart of ah3gamb percentages\n",
    "pie(ahah_df$ah3gamb_pct, labels = ahah_df$lsoa11, main = \"Pie Chart of ah3gamb Percentages\")\n",
    "\n",
    "# Example 6: Correlation heatmap for selected variables\n",
    "cor_variables <- ahah_df[, c(\"ah3gp\", \"ah3dent\", \"ah3phar\", \"ah3hosp\")]\n",
    "cor_matrix <- cor(cor_variables)\n",
    "heatmap(cor_matrix, col = colorRampPalette(c(\"white\", \"blue\"))(20), main = \"Correlation Heatmap\")\n",
    "# Example 7:\n",
    "boxplot(ah3dent ~ substring(lsoa11, 1, 1), data = ahah_df, col = \"lightblue\", main = \"Boxplot of ah3dent across Regions\")\n",
    "\n",
    "# Hypothesis Testing\n",
    "# Formulate hypotheses and conduct hypothesis testing\n",
    "# For example, testing if there is a significant difference in ah3phar between regions\n",
    "t_test_result <- t.test(england_wales_data$ah3phar, scotland_data$ah3phar)\n",
    "print(t_test_result)\n",
    "# Example 2: T-test for ah3gp between England_Wales and Scotland\n",
    "t_test_ah3gp <- t.test(england_wales_data$ah3gp, scotland_data$ah3gp)\n",
    "print(t_test_ah3gp)\n",
    "\n",
    "# Example 3: Wilcoxon test for ah3hosp between England_Wales and Scotland\n",
    "wilcox_test_ah3hosp <- wilcox.test(england_wales_data$ah3hosp, scotland_data$ah3hosp)\n",
    "print(wilcox_test_ah3hosp)\n",
    "\n",
    "# Example 4: ANOVA for ah3leis among different regions\n",
    "anova_ah3leis <- aov(ah3leis ~ substring(lsoa11, 1, 1), data = ahah_df)\n",
    "summary(anova_ah3leis)\n",
    "\n",
    "# Example 5: Chi-squared test for ah3gamb_pct and region\n",
    "chi_squared_ah3gamb <- chisq.test(ahah_df$ah3gamb_pct, ahah_df$lsoa11)\n",
    "print(chi_squared_ah3gamb)\n",
    "\n",
    "# Example 6: Paired t-test for ah3ffood and ah3pubs\n",
    "paired_t_test <- t.test(ahah_df$ah3ffood, ahah_df$ah3pubs, paired = TRUE)\n",
    "print(paired_t_test)\n",
    "\n",
    "# Example 7: Kruskal-Wallis test for ah3pm10 among different regions\n",
    "kruskal_test_ah3pm10 <- kruskal.test(ah3pm10 ~ substring(lsoa11, 1, 1), data = ahah_df)\n",
    "print(kruskal_test_ah3pm10)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bd6b1c35",
   "metadata": {},
   "source": [
    "1. **Welch Two Sample t-test (ah3phar):**\n",
    "   The Welch Two Sample t-test was conducted to compare the means of ah3phar between Lower Level Super Output Areas (LSOAs) for England and Wales and Data Zones (DZ) for Scotland. The test yielded a t-value of -7.748 with 2041 degrees of freedom and a very low p-value (1.46e-14). This result indicates a statistically significant difference in the means of ah3phar between the two regions. The 95% confidence interval for the difference in means (-1.4875158 to -0.8865967) further supports this conclusion, as it does not include zero. The mean ah3phar in England/Wales (3.952814) is significantly lower than in Scotland (5.139871).\n",
    "\n",
    "2. **Welch Two Sample t-test (ah3gp):**\n",
    "   Similar to the ah3phar test, the Welch Two Sample t-test for ah3gp also revealed a significant difference in means between England/Wales and Scotland. The t-value was -10.299 with 2022.9 degrees of freedom and an extremely low p-value (< 2.2e-16). The 95% confidence interval for the difference in means (-1.962203 to -1.334460) supports the conclusion of a substantial difference. The mean ah3gp in England/Wales (4.657605) is significantly lower than in Scotland (6.305936).\n",
    "\n",
    "3. **Wilcoxon Rank Sum Test (ah3hosp):**\n",
    "   The Wilcoxon rank sum test was employed to assess the location shift in ah3hosp between England/Wales and Scotland. The test resulted in a W statistic of 9400386 and a p-value smaller than 2.2e-16, indicating a highly significant difference in location. This suggests that the distribution of ah3hosp values differs significantly between the two regions.\n",
    "\n",
    "4. **Chi-squared Test (ah3gamb_pct):**\n",
    "   The Pearson's Chi-squared test was used to examine the association between ah3gamb_pct and regions. The test returned an X-squared value of 4172900, with a large number of degrees of freedom (4172800) and a p-value of 0.4861. The p-value is greater than 0.05, suggesting that there is no significant association between ah3gamb_pct and regions.\n",
    "\n",
    "5. **Paired t-test (ah3ffood vs. ah3pubs):**\n",
    "   A paired t-test was conducted to compare the means of ah3ffood and ah3pubs within the same regions. The t-value was 30.944 with 41728 degrees of freedom and a p-value smaller than 2.2e-16. This indicates a highly significant difference in means, suggesting that the mean ah3ffood is significantly different from the mean ah3pubs within the same regions.\n",
    "\n",
    "6. **Kruskal-Wallis Test (ah3pm10):**\n",
    "   The Kruskal-Wallis test, a non-parametric test, was performed to compare the medians of ah3pm10 among different regions. The test resulted in a Kruskal-Wallis chi-squared value of 17798, with 2 degrees of freedom and a p-value smaller than 2.2e-16. This strongly indicates a significant difference in medians among the regions for ah3pm10.\n",
    "\n",
    "In summary, the statistical analyses suggest meaningful disparities between England/Wales and Scotland in various environmental and health-related variables. These findings can have implications for understanding regional differences in factors affecting health outcomes and environmental conditions. Keep in mind that these interpretations are based solely on statistical results, and additional context and domain knowledge are crucial for a comprehensive understanding of the observed patterns."
   ]
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   "id": "b512f9ef",
   "metadata": {},
   "outputs": [],
   "source": []
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