MNC_Day4.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "kernelspec": {
      "display_name": "Python 3",
      "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": "3.7.7"
    },
    "colab": {
      "name": "MNC_Day4.ipynb",
      "provenance": [],
      "collapsed_sections": [
        "CzLdzppGkUaA",
        "eggWlLu0mhv-"
      ],
      "toc_visible": true
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "haXfnvS8tcui",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "PROVIDE_OWN_INPUT = False"
      ],
      "execution_count": 24,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JqYQq3SVPojs",
        "colab_type": "code",
        "colab": {
          "resources": {
            "http://localhost:8080/nbextensions/google.colab/files.js": {
              "data": 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              "ok": true,
              "headers": [
                [
                  "content-type",
                  "application/javascript"
                ]
              ],
              "status": 200,
              "status_text": ""
            }
          },
          "base_uri": "https://localhost:8080/",
          "height": 111
        },
        "outputId": "59ab6f4e-ecf0-4b41-840a-fe2276677ccf"
      },
      "source": [
        "from google.colab import files\n",
        "files.upload()"
      ],
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "     <input type=\"file\" id=\"files-8b5ee413-6fdc-4423-a58b-87a8a2d0d083\" name=\"files[]\" multiple disabled\n",
              "        style=\"border:none\" />\n",
              "     <output id=\"result-8b5ee413-6fdc-4423-a58b-87a8a2d0d083\">\n",
              "      Upload widget is only available when the cell has been executed in the\n",
              "      current browser session. Please rerun this cell to enable.\n",
              "      </output>\n",
              "      <script src=\"/nbextensions/google.colab/files.js\"></script> "
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Saving dataset4.csv to dataset4 (1).csv\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'dataset4.csv': b'Company Name,Net Sales,Cons PAT,Cons OCF,OCF/PAT,PBIDTM (%),PATM (%),ROE (%),ROCE (%),Asset Turnover(x),Total Debt/Equity(x),FR_Dividend Pay Out Ratio(%),Free Float,Ev/EBITDA,M/Sales\\r\\n3I Infotech Ltd.,1311.36,-504.97,49.48,-0.1,11.81,-36.9,-61.72,-4.81,0.34,2.6,0,40.37,19.55,0.27\\r\\n3M India Ltd.,1574.13,52.27,63.78,1.22,7.37,3.16,8.29,11.31,1.68,0.26,0,12.59,37.04,2.98\\r\\nAavas Financiers Ltd.,17.39,1.89,-172.5,-91.5,57.3,10.84,6.69,9.57,0.16,5.17,0,0,0,0\\r\\nABB India Ltd.,7610.48,140.94,-44.2,-0.31,4.76,1.85,5.49,9.82,1.19,0.13,45.1,13.15,39.42,2.05\\r\\nAbbott India Ltd.,1652.69,144.7,101.35,0.7,13.38,8.64,24.3,36.11,1.74,0,24.96,20.12,13.82,2.03\\r\\nAccelya Solutions India Ltd.,303.84,84.38,114.18,1.35,44.48,27.77,70.46,102.99,1.4,0,123.83,20.48,3.75,1.47\\r\\nAegis Logistics Ltd.,3981.64,33.6,1774.26,52.81,3.31,0.88,11.69,7.42,2.01,1.07,39.76,24.26,4.98,0.1\\r\\nAGC Networks Ltd.,1050.1,-21.9,-60.8,2.78,4.04,-2.08,-6.97,4.89,1,1.04,0,20.66,4.12,0.43\\r\\nAgro Tech Foods Ltd.,788.92,41.9,17.83,0.43,8.57,5.3,18.45,26.86,2.63,0,11.63,24.26,19.23,1.6\\r\\nAkzo Nobel India Ltd.,2232,218.8,208,0.95,13.21,8.85,17.28,22.65,1.1,0,170.75,10.65,20.53,4.66\\r\\nAllsec Technologies Ltd.,320.07,1.95,27.22,13.96,12.68,2.76,8.81,24.89,2.14,0.05,0,20.51,2.53,0.24\\r\\nAmbuja Cements Ltd.,9750.45,1293.21,1859.95,1.44,25.51,11.68,15.37,23.24,0.92,0.01,42.93,33.2,11.14,3.23\\r\\nAndhra Paper Ltd.,1230.5,-23.7,174.1,-7.35,10.69,-1.83,-5.06,3.72,1.05,0.98,0,19.81,15.06,1.2\\r\\nAsahi India Glass Ltd.,1929.1,-97.5,111.44,-1.14,8.15,-4.55,-110.66,1.36,0.97,38.63,0,30.57,15.17,0.54\\r\\nAsian Hotels (East) Ltd.,151.11,10.7,31.83,2.98,37.92,0.57,0.11,3.97,0.14,0.44,48.13,40.93,4.67,3.1\\r\\nAsian Hotels (North) Ltd.,320.84,59.75,76.95,1.29,32.62,-114.74,-60.45,-17.04,0.14,1.22,3.26,13.94,9.69,1.01\\r\\nAsian Hotels (West) Ltd.,135.47,-2.66,118.1,-44.45,23.5,-5.32,-2.33,2.34,0.13,2.03,-86.25,23.7,13.06,1.08\\r\\nAsian Oilfield Services Ltd.,55.38,-10.29,-9.43,0.92,5.42,-18.59,-13.32,-7.13,0.47,0.38,0,38.79,0,0.86\\r\\nAstrazeneca Pharma India Ltd.,390.42,-89.53,-6.04,0.07,-14.56,-22.47,-61.95,-48.62,1.26,0,0,10,33.85,8.58\\r\\nBanco Products (India) Ltd.,1024.14,61.3,97.49,1.59,11.62,5.71,13.7,15.27,1.36,0.45,21,24.65,4.03,0.42\\r\\nBASF India Ltd.,3940.63,114.08,233.22,2.04,6.02,2.69,10.72,13.82,1.7,0.34,15.18,17.89,12.11,0.73\\r\\nBata India Ltd.,1842.45,172.08,184.46,1.07,16.88,9.19,28.37,43.63,1.9,0,22.41,36.06,14.17,3.43\\r\\nBayer CropScience Ltd.,2725.3,1161.7,138.3,0.12,15.1,40.92,85.29,115.04,0.91,0,1.7,21.35,9.83,1.67\\r\\nBilcare Ltd.,3546.75,39.59,227.37,5.74,11.05,1.61,4.38,7.96,0.87,1.59,0,25.01,3.3,0.11\\r\\nBlack Rose Industries  Ltd.,122,1.66,6.72,4.06,4.69,1.36,12.81,13.16,2.15,1.62,0,19.16,12.61,0.24\\r\\nBlue Dart Express Ltd.,2171.71,193.28,182.51,0.94,14.22,8.78,28.82,41.42,1.89,0,87.17,11.64,23.15,3.15\\r\\nBosch Ltd.,8659.1,958.3,871.2,0.91,18.33,10.22,18.6,24.94,1.16,0.04,19.66,17.24,14.72,3.3\\r\\nCairn India Ltd. (Amalgamated),17524.15,12056.39,11055.63,0.92,81.07,68.8,25.13,25.42,0.33,0,18.22,21.62,4.63,4.37\\r\\nCapital First Ltd. - (Amalgamated),800.29,66.38,-1223.5,-18.43,68.45,8.72,8.08,9.12,0.12,6.83,17.35,1.91,8.59,1.35\\r\\nCastrol India Ltd.,3120.86,447.39,467.16,1.04,18.59,11.97,71.39,106.66,2.72,0,116.07,20.98,19.79,4.64\\r\\nClariant Chemicals (India) Ltd.,1096.28,101.3,76.58,0.76,13.33,8.65,20.53,29.13,1.45,0,72.38,31.11,9.18,1.69\\r\\nCMI FPE Ltd.,532.9,-0.99,-49.61,49.93,1.04,-0.18,-0.66,0.65,1.17,0.45,0,19.77,20.31,0.84\\r\\nColgate-Palmolive (India) Ltd.,3163.81,496.75,614.9,1.24,21.26,14.94,107.41,143.35,1.82,0,76.65,35.45,24.98,6.09\\r\\nCreditAccess Grameen Ltd.,86.7,8.46,-104.35,-12.34,57.29,9.76,10.36,23.52,0.2,1.31,0,29.45,0,0\\r\\nCRISIL Ltd.,977.72,220.4,223.26,1.01,35.59,22.54,46.55,66.26,1.18,0,50.99,17.61,19.87,7.66\\r\\nCSB Bank Ltd.,1320.86,32.67,60.41,1.85,7.72,2.47,5.64,6.99,0,0.32,19.22,100,0,0\\r\\nCummins India Ltd.,4589.38,764.11,528.61,0.69,21.26,15.59,34.5,47.67,1.45,0,47.16,29.03,20.17,3.7\\r\\nDabur India Ltd.,6169.1,763.42,869.54,1.14,17.62,12.31,42.75,32.85,1.28,0.62,34.25,22.45,22.06,3.76\\r\\nDCB Bank Ltd.,916.1,102.06,55.27,0.54,13.77,11.14,11.67,8.82,0,1.61,0,42.32,23.21,1.36\\r\\nDe Nora India Ltd.,64.25,13.31,17.36,1.3,29.65,19.62,44.57,65.33,1.46,0,27.93,37.79,6.15,1.67\\r\\nDenso India Ltd.,1218.6,12.8,-28.2,-2.2,-1.3,0.94,8.92,8.51,2.15,1.42,0,19.95,0,0.12\\r\\nDIC India Ltd.,715.99,21.5,3.05,0.14,5.9,2.7,7.83,12.18,1.81,0.12,17.08,23.26,4.67,0.31\\r\\nDisa India Ltd.,152.46,18.84,18.32,0.97,18.34,11.26,35.99,52.27,1.29,0,2,13.44,10.48,2.8\\r\\nDixon Technologies (India) Ltd.,724.87,3.22,43.11,13.38,2.38,0.44,4.43,7.67,2.82,1.17,9.63,95.97,0,0\\r\\nD-Link (India) Ltd.,353.7,12.33,-2.31,-0.19,5.67,3.48,14.86,22.18,2.55,0,12.17,36.66,5.05,0.3\\r\\nElantas Beck India Ltd.,274.46,27.58,25.6,0.93,13.67,9,17.6,23.69,1.28,0,264.48,13.36,26.86,4.12\\r\\nEndurance Technologies Ltd.,3810.24,170.42,345.29,2.03,6.15,4.47,25.52,14.3,1.63,1.3,2.07,0,0,0\\r\\nEnkei Wheels (India) Ltd.,286.96,4.35,26.07,5.99,5.89,1.35,0,8.69,0.97,-19.46,0,18.16,9.08,0.22\\r\\nEros International Media Ltd.,1067.95,154.53,647.92,4.19,22.84,14.59,17.17,17.77,0.61,0.41,8.92,17.15,7.43,1.6\\r\\nEsab India Ltd.,503.52,37.77,46.12,1.22,12.06,6.83,16.88,24.53,1.78,0,30.56,17.5,9.82,1.35\\r\\nEssar Shipping Ltd.,3209.19,35.8,1205.14,33.66,26.96,1.12,0.59,3.85,0.25,0.79,0,8.71,6.46,0.18\\r\\nEster Industries Ltd.,886.02,-5.28,22.69,-4.3,4.93,-0.55,-2.07,3.51,1.5,1.15,0,27.9,8.17,0.15\\r\\nExpleo Solutions Ltd.,161.44,19.44,18.41,0.95,20.2,12.04,23.75,31.43,1.41,0.16,31.24,46.18,1.24,0.55\\r\\nFederal-Mogul Goetze (India) Ltd.,1199.13,-6.72,79.29,-11.8,8.53,0.15,0.46,7.3,1.47,0.42,-95.4,9.87,9.61,1.03\\r\\nFinolex Industries Ltd.,2144.82,136.14,274.39,2.02,16.11,5.59,19.68,14.8,1.19,1.16,50.13,38.01,6,0.39\\r\\nFoseco India Ltd.,246.75,21.82,20.03,0.92,13.69,7.96,26.04,35.2,2.01,0.11,40.99,13.52,8.93,1.56\\r\\nGE Power India Ltd.,2785.84,183.59,31.9,0.17,11.84,6.4,24.76,38.34,0.9,0,36.62,20.83,7.68,1.05\\r\\nGillette India Ltd.,1437.72,87.16,29.4,0.34,11.62,5.97,13.74,21.8,1.14,0,56.09,10.2,52.45,5.97\\r\\nGlaxosmithkline Consumer Healthcare Ltd.,3187.49,436.76,554.33,1.27,20.41,12.97,34.87,51.98,1.23,0,43.33,22.53,18.43,4.52\\r\\nGlaxosmithkline Pharmaceuticals Ltd.,2692.06,561.88,313.59,0.56,36.22,20.34,28.5,42.24,0.93,0,75.37,30.11,16.19,6.99\\r\\nGMM Pfaudler Ltd.,212.89,9.69,24.47,2.53,9.39,4.25,8.29,12.11,1.2,0,42.25,22.89,5.54,0.54\\r\\nGokaldas Exports Ltd.,981,-109.44,-66.15,0.6,-3.65,-10.96,-62.34,-15.22,1.59,2.56,0,6.38,0,0.22\\r\\nGoodricke Group Ltd.,539.53,20,16.57,0.83,8.28,3.7,11.38,15.64,1.31,0.23,43.2,21.58,7.11,0.62\\r\\nGoodyear India Ltd.,1481.29,56.32,25.66,0.46,6.98,3.49,16.95,26.62,1.75,0,28.67,18.17,4.31,0.5\\r\\nGP Petroleums Ltd.,417.37,-1.26,-14.92,11.81,3.85,-0.27,-1.03,13.13,1.46,0,-3.48,10.75,2.8,0.25\\r\\nGrindwell Norton Ltd.,946.99,97.31,104.27,1.07,15.91,9.49,20.03,27.4,1.34,0.04,36.98,25.2,7.95,1.58\\r\\nGujarat Gas Company Ltd. - (Amalgamation),3096.05,286.62,306.94,1.07,15.09,9.16,33.05,46.32,1.32,0,31.35,14.37,9.18,1.38\\r\\nGulf Oil Lubricants India Ltd.,0,0,0,2.48,0,0,3.37,3.37,0,0,0,100,0,0\\r\\nHeidelberg Cement India Ltd.,869.81,30.84,50.09,1.62,7.63,2.96,3.78,3.25,0.45,1.24,0,23,20.99,0.97\\r\\nHella India Lighting Ltd.,68.04,-3.55,3,-0.84,-3.13,-4.6,-22.37,-12.89,1.63,0,0,18.15,0,0.71\\r\\nHexaware Technologies Ltd.,1948.18,327.65,219.9,0.67,22.46,16.82,29.53,36.49,1.3,0,48.87,38.26,6.92,1.85\\r\\nHinduja Foundries Ltd. - (Amalgamated),306.72,-103.78,-69.26,0.67,-10.87,-30.21,0,-8.5,0.31,5.04,0,9.24,3.59,0.23\\r\\nHindustan Unilever Ltd.,27003.99,3828.98,3604.76,0.94,16.63,13.48,118.67,155.02,2.47,0.01,104.48,41.1,27.43,4.46\\r\\nHindustan Zinc Ltd.,12699.84,6899.48,4785.01,0.69,62.32,50.52,23.33,26.53,0.42,0,18.98,5.54,6.21,4.69\\r\\nHonda Siel Power Products Ltd.,515.55,20.6,-30.39,-1.48,8.13,3.69,7.57,11.65,1.11,0,19.69,27.11,6.75,1.05\\r\\nHoneywell Automation India Ltd.,1660.73,85.17,-17.32,-0.2,7.89,5.03,12.76,17.92,1.24,0,10.38,17.92,16.14,1.36\\r\\nHuhtamaki PPL Ltd.,900.59,45.08,62.53,1.39,10.26,4.69,12.81,15.6,1.59,0.15,36.16,28.13,4.7,0.47\\r\\nIndian Hume Pipe Company Ltd.,684.31,22.85,4.17,0.18,9.52,3.29,9.99,15.02,0.91,0.74,23.33,25.36,7.61,0.46\\r\\nIndostar Capital Finance Ltd.,241.38,90.09,-520.37,-5.78,85.48,37.32,9.2,13,0.15,1.08,0,12.39,0,0\\r\\nINEOS Styrolution India Ltd.,989.33,63.13,-23.77,-0.38,9.96,5.7,15.49,19.08,1.52,0.15,11.14,12.67,14,1.31\\r\\nInfinite Computer Solutions (India) Ltd.,1390.61,130.74,106.72,0.82,15.09,9.4,23.66,26.63,1.27,0.14,29.3,17.34,1.97,0.42\\r\\nIngersoll-Rand (India) Ltd.,585.58,77.94,50.28,0.65,18.64,12.37,9.26,13.33,0.43,0,24.3,21.15,7.64,2.47\\r\\nITC Ltd.,29901.27,7418.39,6709.89,0.9,27.52,17.62,35.67,51.64,1.31,0,55.92,37.59,20.9,8\\r\\nITD Cementation India Ltd.,1539.27,21.98,15.05,0.68,13.07,1.43,5.62,13.59,0.88,1.96,10.48,26.49,4.55,0.15\\r\\nJagatjit Industries Ltd.,993.4,4.95,-24.44,-4.94,2.39,0.36,2.11,6.92,1.74,0.86,0,7.59,4.59,0.25\\r\\nJagran Prakashan Ltd.,1521.8,255.08,201.85,0.79,27.03,16.74,30.24,20.16,0.69,0.52,24.8,22.63,10.51,2.25\\r\\nJash Engineering Ltd.,81.96,1.49,-6.45,-4.33,13.3,1.69,2.54,8.57,0.69,0.63,51.4,62.93,0,0\\r\\nJayant Agro-Organics Ltd.,1624.95,36.22,30.14,0.83,6.08,2.23,22.65,19.46,2.91,1.77,9.32,29.92,4.37,0.11\\r\\nJet Airways (India) Ltd.,19409.87,-779.8,1880.18,-2.41,6.43,-4.02,0,4.05,1,-4.63,0,17.27,48.69,0.22\\r\\nJohnson Controls - Hitachi Air Conditioning India Ltd.,929.99,15.3,67.74,4.43,4.71,1.5,8.67,8.29,1.43,0.91,22.5,25.67,11.34,0.36\\r\\nKansai Nerolac Paints Ltd.,2867.04,293.14,220.03,0.75,10.45,8.67,30.12,39.72,2.14,0.07,20.22,13.87,30.04,3.81\\r\\nKennametal India Ltd.,489.77,14.85,32.79,2.21,8.78,2.82,4.81,6.34,1.03,0,0,12.81,17.27,3.45\\r\\nKingfa Science & Technology (India) Ltd.,156.58,-5.05,8.83,-1.75,1.52,-2.86,-22.55,-0.22,2.04,1.73,0,28.98,8.87,0.06\\r\\nKokuyo Camlin Ltd.,438.37,-15.11,-3.79,0.25,-1.09,-3.3,-12.31,-7.42,1.75,0.57,0,30.16,19.92,0.7\\r\\nLemon Tree Hotels Ltd.,214.81,-20.45,153.4,-7.5,22.66,-9.11,-2.3,1.88,0.13,0.54,0,100,0,0\\r\\nLinde India Ltd.,1324.44,89.48,96.25,1.08,14.64,6.34,6.9,7.33,0.44,0.82,14.3,10.52,18.27,2.66\\r\\nMac Charles (India) Ltd.,46.91,16.08,13.17,0.82,62.41,34.28,7.13,9.93,0.18,0.01,48.88,22.23,8.64,2.94\\r\\nMahanagar Gas Ltd.,1514.38,298.51,438.89,1.47,31.17,18.08,26.54,39.07,0.99,0.01,52.38,50.25,0,0\\r\\nMahindra CIE Automotive Ltd.,2216.4,-113.94,101.83,-0.89,2.06,-5.02,-14.12,-4.44,1.18,0.91,0,9.81,5.09,0.2\\r\\nMaruti Suzuki India Ltd.,44304.4,2469.2,4058.9,1.64,10.34,4.91,14.11,17.34,1.97,0.08,9.78,31.02,11.13,1.07\\r\\nMonsanto India Ltd. - (Amalgamated),442.42,67.34,89.39,1.33,18.81,14.63,17.01,19.11,0.82,0,56.39,17.54,14.5,2.85\\r\\nMorganite Crucible (India) Ltd.,100.03,9.62,14.52,1.51,21.59,10.22,23.48,37.52,1.12,0,2.91,20,4.12,1.01\\r\\nMoschip Technologies Ltd.,9.79,-14.39,-1.43,0.1,-68.61,-146.9,-233.05,-111.46,0.67,4.03,0,70.15,0,2.95\\r\\nMphasis Ltd.,5490.68,792.32,965.77,1.22,22.16,14.43,19.13,23.38,0.97,0.07,45.08,14.37,6.75,1.51\\r\\nMPS Ltd.,164,31.89,31.56,0.99,29.21,19.45,41.7,49.8,1.5,0.06,52.75,25,12.88,0.91\\r\\nMultibase India Ltd.,45.15,4.49,-0.38,-0.08,14.32,9.02,16.81,24.83,1.43,0,0,21.63,8.2,1.13\\r\\nMusic Broadcast Ltd.,138.06,11.62,34.26,2.95,26.3,8.42,0,11.68,0.79,-10.84,0,7.18,0,0\\r\\nNestle India Ltd.,8334.53,1067.93,1693.38,1.59,21.63,12.4,69.52,62.01,1.8,0.58,43.79,29.03,26.39,5.58\\r\\nNewgen Software Technologies Ltd.,188.77,31.92,24.76,0.78,23.98,16.91,32.93,40.2,1.37,0,14.08,100,0,0\\r\\nNIIT Ltd.,960.8,26.26,47.16,1.8,5.58,-2.57,-3.71,-6.31,0.74,0.23,100.6,37.27,3.74,0.45\\r\\nNirlon Ltd.,159.66,12.03,139.92,11.63,74.66,7.54,11.19,11.94,0.07,6.07,0,32.56,9.55,2.6\\r\\nNovartis India Ltd.,903.36,119.73,7.43,0.06,19.11,13.21,13.94,19.74,0.48,0,26.69,21.21,10.17,2.57\\r\\nOracle Financial Services Software Ltd.,3474,1075.14,1134.35,1.06,48.33,30.95,15.67,23.51,0.39,0,0,16.84,12.91,7.54\\r\\nOrient Green Power Company Ltd.,435.45,-69.89,-45.62,0.65,48.56,-18.76,-7.21,4.03,0.12,1.8,0,18.65,12.8,1.78\\r\\nOrient Refractories Ltd.,360.58,41.39,37.54,0.91,17.57,10.64,46.65,63.29,2.21,0.05,29.03,34.5,7.33,1.29\\r\\nPage Industries Ltd.,876.31,112.53,87.14,0.77,20.34,12.11,59.34,63.96,2.2,0.47,49.56,17.1,22.27,4.74\\r\\nPanasonic Appliances India Company Ltd.,147.55,-11.41,-0.24,0.02,-2.61,-6.83,-158.92,-18.87,2.05,4.02,0,16.3,0,0.47\\r\\nPanasonic Carbon India Company Ltd.,35.16,6.54,2.6,0.4,27.35,17.53,11.35,17.02,0.46,0,51.41,22.44,1.97,2.51\\r\\nPfizer Ltd.,1048.84,503.2,-16.01,-0.03,26.41,45.91,33.56,46.38,0.61,0,19.27,29.25,9.36,3.52\\r\\nPhoenix Lamps Ltd. - (Amalgamated),482.81,-24.07,33.73,-1.4,2.79,-4.85,-22.82,-0.72,1.28,1.55,0,24.29,5.97,0.3\\r\\nPolycab India Ltd.,3719.47,76.89,503.51,6.55,7.59,2.07,6.55,12.23,1.38,0.42,9.18,85,0,0\\r\\nProcter & Gamble Health Ltd.,687.28,78.4,54.26,0.69,17.7,11.04,17.54,26.14,0.74,0,5.29,27.58,8.93,1.66\\r\\nProcter & Gamble Hygiene & Health Care Ltd.,1686.78,203.22,104.2,0.51,18.69,11.96,27.05,38.1,1.25,0,39.93,21.97,29.25,5.77\\r\\nPuravankara Ltd.,1245.89,243.44,39.91,0.16,47.19,18.32,12.73,17.29,0.33,0.94,30.69,4.07,6.45,1.81\\r\\nQuess Corp Ltd.,1001.15,11.24,-16.12,-1.43,4.56,1.62,40.59,31.15,3.51,1.38,0,100,0,0\\r\\nR Systems International Ltd.,465.01,18.36,34.52,1.88,8.52,3.95,9.34,14.97,1.46,0,160.24,15.91,3.55,0.5\\r\\nRanbaxy Laboratories Ltd.- (Amalgamation),12459.73,922.76,1582.1,1.71,16.78,7.62,27.53,18.96,0.78,1.21,0,27.09,9.63,1.68\\r\\nRhodia Specialty Chemicals India Ltd.,284.42,36.86,-6.97,-0.19,5.59,11.98,64.79,44.84,1.81,0.37,1.83,15.29,18.96,0.52\\r\\nRicoh India Ltd.,633.12,-1.32,-96.67,73.23,3.55,-0.21,-1.07,4.67,1.13,2.08,0,24.84,5.02,0.44\\r\\nSaint-Gobain Sekurit India Ltd.,108.56,0.65,11.69,18.07,9.22,0.53,0.89,3.19,1.21,0.08,0,14.23,23.43,3.47\\r\\nSanofi India Ltd.,1573.04,176.66,289.78,1.64,21.89,10.95,15.38,22.9,1.03,0,43.02,10.41,14.89,3.68\\r\\nSaurashtra Cement Ltd.,540.33,183.72,126.65,0.69,20.42,30.64,395.73,121.11,1.4,1.22,0,15.07,5.06,0.25\\r\\nSchaeffler India Ltd.,1446.65,159.18,137.06,0.86,17.01,10.2,19.83,29.31,1.46,0,5.22,18.75,8.52,1.87\\r\\nSeamec Ltd.,337.33,40.4,56.2,1.39,29.69,11.98,8.91,11.62,0.67,0,0,18.93,8.34,1.51\\r\\nShreyas Shipping & Logistics Ltd.,388.89,16.38,14.87,0.91,11.25,3.96,10.56,10.73,1.26,0.9,8.54,26.71,4.09,0.23\\r\\nSiemens Ltd.,12919.9,343.2,43.3,0.13,6.7,2.58,8.83,14.67,1.31,0,59.53,19.69,14.99,1.92\\r\\nSinger India Ltd.,#N/A,#N/A,-0.73,#N/A,5.19,7.78,72.2,45.42,3.91,0,10.52,19.53,42.54,1.12\\r\\nSKF India Ltd.,196.92,15.32,199.04,12.99,13.63,7.93,17.55,26.14,1.54,0,20.81,25.91,8.73,1.42\\r\\nSobha Ltd.,1864.54,217.18,254.15,1.17,29.58,11.6,10.5,14.64,0.41,0.65,31.61,25.18,8.77,2.18\\r\\nSterlite Industries (India) Ltd.(Merged),45162.29,6060.32,6824.37,1.13,29.23,19.4,19.1,17.89,0.52,0.38,12.76,13.53,3.23,0.83\\r\\nSterlite Technologies Ltd.,3092.34,25.19,282.97,11.23,7.49,0.77,2.13,4.84,0.73,2.44,46.86,27.83,9.56,0.47\\r\\nStovec Industries Ltd.,73.09,7.4,10.25,1.39,15.54,9.31,18,26.28,1.32,0,30.19,27.68,5.07,0.98\\r\\nSumitomo Chemical India Ltd.,494.58,12.78,-16.02,-1.25,4.18,2.58,8.14,8.83,1.36,0.01,0,6.2,0,0\\r\\nTake Solutions Ltd.,831.97,79.47,116.63,1.47,20.2,10.71,23.38,21.14,1.05,0.47,15.1,20.85,3.04,0.5\\r\\nTCNS Clothing Co Ltd.,128.38,4.76,5.18,1.09,11.94,3.57,6.62,12.63,1.02,0.41,0,93.13,0,0\\r\\nThomas Cook (India) Ltd.,430.19,50.44,114.51,2.27,28.42,11.72,12.2,17.38,0.46,0.43,15.85,12.9,10.16,3.14\\r\\nThyrocare Technologies Ltd.,134.26,56.82,45.92,0.81,60.54,42.32,43.28,49.89,0.81,0.16,0,29.55,0,0\\r\\nTimex Group India Ltd.,121.44,-41.96,7.29,-0.17,-31.25,-33.92,-405.41,-67.13,0.78,0.34,0,25.07,70.83,1.23\\r\\nTimken India Ltd.,688.52,44.24,13.14,0.3,10.68,5.99,13.52,19.43,1.33,0,28.81,19.98,15.49,1.88\\r\\nUnited Spirits Ltd.,10498.62,-101.21,1968.84,-19.45,5.76,-0.48,-2.33,8.32,1.34,1.79,-32.31,44.14,17.69,1.78\\r\\nVardhman Acrylics Ltd.,436.49,24.4,23.73,0.97,10.58,5.15,9.57,14.86,1.28,0.02,0,31.76,0,0\\r\\nVedanta Ltd.,2748.94,2280.25,22.21,0.01,18.22,-4.6,-0.8,1.46,0.13,0.28,0.38,31.4,7.23,2.23\\r\\nVesuvius India Ltd.,563.79,55.76,50.16,0.9,16.24,9.09,17.39,25.97,0.99,0,16.38,20.77,6.98,1.3\\r\\nVoith Paper Fabrics India Ltd.,57.74,13.02,9.1,0.7,33.28,20.34,11.68,16.71,0.51,0,10.12,24.79,3.26,2.18\\r\\nVST Industries Ltd.,668.68,126.25,118.35,0.94,12.7,7.76,43.03,62.73,2.27,0,76.45,25.97,11.92,3.94\\r\\nWabco India Ltd.,965.92,130.79,90.21,0.69,19.41,12.28,22.21,31.41,1.45,0,7.25,20.29,12.49,2.95\\r\\nWhirlpool Of India Ltd.,2772.73,127.75,143.97,1.13,7.07,3.72,23.65,33.72,2.67,0,0,18.61,11.51,1.12\\r\\nWintac Ltd.,20.88,-17.2,-3.01,0.17,-11.89,-75.82,-55.5,-33.55,0.42,0.09,0,17.86,0,2.25\\r\\nWyeth Ltd.- (Amalgamated),678.34,130.06,92.32,0.71,28.08,18.54,24.8,36.88,0.99,0,29.7,28.03,8.03,3.33\\r\\nXchanging Solutions Ltd.,208.83,12.25,14.25,1.16,15.05,5.87,5.03,8.56,0.62,0.01,0,6.71,4.46,0.45\\r\\nZim Laboratories Ltd.,185,9.52,15.49,1.63,14.51,5.03,12.26,17.47,1.01,0.56,8.4,55.91,0,0\\r\\n'}"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qeLkeLYRPW7N",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "%matplotlib inline"
      ],
      "execution_count": 26,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fYHGizAaPW7U",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "data = pd.read_csv('dataset4.csv')"
      ],
      "execution_count": 27,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uVj7NWT2PW7Y",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "d727e924-13c8-47ac-af78-74dc4e97ec86"
      },
      "source": [
        "data.head(20)"
      ],
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<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>Company Name</th>\n",
              "      <th>Net Sales</th>\n",
              "      <th>Cons PAT</th>\n",
              "      <th>Cons OCF</th>\n",
              "      <th>OCF/PAT</th>\n",
              "      <th>PBIDTM (%)</th>\n",
              "      <th>PATM (%)</th>\n",
              "      <th>ROE (%)</th>\n",
              "      <th>ROCE (%)</th>\n",
              "      <th>Asset Turnover(x)</th>\n",
              "      <th>Total Debt/Equity(x)</th>\n",
              "      <th>Free Float</th>\n",
              "      <th>FR_Dividend Pay Out Ratio(%)</th>\n",
              "      <th>Ev/EBITDA</th>\n",
              "      <th>M/Sales</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>3I Infotech Ltd.</td>\n",
              "      <td>1311.36</td>\n",
              "      <td>-504.97</td>\n",
              "      <td>49.48</td>\n",
              "      <td>-0.10</td>\n",
              "      <td>11.81</td>\n",
              "      <td>-36.90</td>\n",
              "      <td>-61.72</td>\n",
              "      <td>-4.81</td>\n",
              "      <td>0.34</td>\n",
              "      <td>2.60</td>\n",
              "      <td>40.37</td>\n",
              "      <td>0.00</td>\n",
              "      <td>19.55</td>\n",
              "      <td>0.27</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>3M India Ltd.</td>\n",
              "      <td>1574.13</td>\n",
              "      <td>52.27</td>\n",
              "      <td>63.78</td>\n",
              "      <td>1.22</td>\n",
              "      <td>7.37</td>\n",
              "      <td>3.16</td>\n",
              "      <td>8.29</td>\n",
              "      <td>11.31</td>\n",
              "      <td>1.68</td>\n",
              "      <td>0.26</td>\n",
              "      <td>12.59</td>\n",
              "      <td>0.00</td>\n",
              "      <td>37.04</td>\n",
              "      <td>2.98</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Aavas Financiers Ltd.</td>\n",
              "      <td>17.39</td>\n",
              "      <td>1.89</td>\n",
              "      <td>-172.50</td>\n",
              "      <td>-91.50</td>\n",
              "      <td>57.30</td>\n",
              "      <td>10.84</td>\n",
              "      <td>6.69</td>\n",
              "      <td>9.57</td>\n",
              "      <td>0.16</td>\n",
              "      <td>5.17</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>ABB India Ltd.</td>\n",
              "      <td>7610.48</td>\n",
              "      <td>140.94</td>\n",
              "      <td>-44.20</td>\n",
              "      <td>-0.31</td>\n",
              "      <td>4.76</td>\n",
              "      <td>1.85</td>\n",
              "      <td>5.49</td>\n",
              "      <td>9.82</td>\n",
              "      <td>1.19</td>\n",
              "      <td>0.13</td>\n",
              "      <td>13.15</td>\n",
              "      <td>45.10</td>\n",
              "      <td>39.42</td>\n",
              "      <td>2.05</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Abbott India Ltd.</td>\n",
              "      <td>1652.69</td>\n",
              "      <td>144.70</td>\n",
              "      <td>101.35</td>\n",
              "      <td>0.70</td>\n",
              "      <td>13.38</td>\n",
              "      <td>8.64</td>\n",
              "      <td>24.30</td>\n",
              "      <td>36.11</td>\n",
              "      <td>1.74</td>\n",
              "      <td>0.00</td>\n",
              "      <td>20.12</td>\n",
              "      <td>24.96</td>\n",
              "      <td>13.82</td>\n",
              "      <td>2.03</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Accelya Solutions India Ltd.</td>\n",
              "      <td>303.84</td>\n",
              "      <td>84.38</td>\n",
              "      <td>114.18</td>\n",
              "      <td>1.35</td>\n",
              "      <td>44.48</td>\n",
              "      <td>27.77</td>\n",
              "      <td>70.46</td>\n",
              "      <td>102.99</td>\n",
              "      <td>1.40</td>\n",
              "      <td>0.00</td>\n",
              "      <td>20.48</td>\n",
              "      <td>123.83</td>\n",
              "      <td>3.75</td>\n",
              "      <td>1.47</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Aegis Logistics Ltd.</td>\n",
              "      <td>3981.64</td>\n",
              "      <td>33.60</td>\n",
              "      <td>1774.26</td>\n",
              "      <td>52.81</td>\n",
              "      <td>3.31</td>\n",
              "      <td>0.88</td>\n",
              "      <td>11.69</td>\n",
              "      <td>7.42</td>\n",
              "      <td>2.01</td>\n",
              "      <td>1.07</td>\n",
              "      <td>24.26</td>\n",
              "      <td>39.76</td>\n",
              "      <td>4.98</td>\n",
              "      <td>0.10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>AGC Networks Ltd.</td>\n",
              "      <td>1050.10</td>\n",
              "      <td>-21.90</td>\n",
              "      <td>-60.80</td>\n",
              "      <td>2.78</td>\n",
              "      <td>4.04</td>\n",
              "      <td>-2.08</td>\n",
              "      <td>-6.97</td>\n",
              "      <td>4.89</td>\n",
              "      <td>1.00</td>\n",
              "      <td>1.04</td>\n",
              "      <td>20.66</td>\n",
              "      <td>0.00</td>\n",
              "      <td>4.12</td>\n",
              "      <td>0.43</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>Agro Tech Foods Ltd.</td>\n",
              "      <td>788.92</td>\n",
              "      <td>41.90</td>\n",
              "      <td>17.83</td>\n",
              "      <td>0.43</td>\n",
              "      <td>8.57</td>\n",
              "      <td>5.30</td>\n",
              "      <td>18.45</td>\n",
              "      <td>26.86</td>\n",
              "      <td>2.63</td>\n",
              "      <td>0.00</td>\n",
              "      <td>24.26</td>\n",
              "      <td>11.63</td>\n",
              "      <td>19.23</td>\n",
              "      <td>1.60</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>Akzo Nobel India Ltd.</td>\n",
              "      <td>2232.00</td>\n",
              "      <td>218.80</td>\n",
              "      <td>208.00</td>\n",
              "      <td>0.95</td>\n",
              "      <td>13.21</td>\n",
              "      <td>8.85</td>\n",
              "      <td>17.28</td>\n",
              "      <td>22.65</td>\n",
              "      <td>1.10</td>\n",
              "      <td>0.00</td>\n",
              "      <td>10.65</td>\n",
              "      <td>170.75</td>\n",
              "      <td>20.53</td>\n",
              "      <td>4.66</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>Allsec Technologies Ltd.</td>\n",
              "      <td>320.07</td>\n",
              "      <td>1.95</td>\n",
              "      <td>27.22</td>\n",
              "      <td>13.96</td>\n",
              "      <td>12.68</td>\n",
              "      <td>2.76</td>\n",
              "      <td>8.81</td>\n",
              "      <td>24.89</td>\n",
              "      <td>2.14</td>\n",
              "      <td>0.05</td>\n",
              "      <td>20.51</td>\n",
              "      <td>0.00</td>\n",
              "      <td>2.53</td>\n",
              "      <td>0.24</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>Ambuja Cements Ltd.</td>\n",
              "      <td>9750.45</td>\n",
              "      <td>1293.21</td>\n",
              "      <td>1859.95</td>\n",
              "      <td>1.44</td>\n",
              "      <td>25.51</td>\n",
              "      <td>11.68</td>\n",
              "      <td>15.37</td>\n",
              "      <td>23.24</td>\n",
              "      <td>0.92</td>\n",
              "      <td>0.01</td>\n",
              "      <td>33.20</td>\n",
              "      <td>42.93</td>\n",
              "      <td>11.14</td>\n",
              "      <td>3.23</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>Andhra Paper Ltd.</td>\n",
              "      <td>1230.50</td>\n",
              "      <td>-23.70</td>\n",
              "      <td>174.10</td>\n",
              "      <td>-7.35</td>\n",
              "      <td>10.69</td>\n",
              "      <td>-1.83</td>\n",
              "      <td>-5.06</td>\n",
              "      <td>3.72</td>\n",
              "      <td>1.05</td>\n",
              "      <td>0.98</td>\n",
              "      <td>19.81</td>\n",
              "      <td>0.00</td>\n",
              "      <td>15.06</td>\n",
              "      <td>1.20</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>Asahi India Glass Ltd.</td>\n",
              "      <td>1929.10</td>\n",
              "      <td>-97.50</td>\n",
              "      <td>111.44</td>\n",
              "      <td>-1.14</td>\n",
              "      <td>8.15</td>\n",
              "      <td>-4.55</td>\n",
              "      <td>-110.66</td>\n",
              "      <td>1.36</td>\n",
              "      <td>0.97</td>\n",
              "      <td>38.63</td>\n",
              "      <td>30.57</td>\n",
              "      <td>0.00</td>\n",
              "      <td>15.17</td>\n",
              "      <td>0.54</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>Asian Hotels (East) Ltd.</td>\n",
              "      <td>151.11</td>\n",
              "      <td>10.70</td>\n",
              "      <td>31.83</td>\n",
              "      <td>2.98</td>\n",
              "      <td>37.92</td>\n",
              "      <td>0.57</td>\n",
              "      <td>0.11</td>\n",
              "      <td>3.97</td>\n",
              "      <td>0.14</td>\n",
              "      <td>0.44</td>\n",
              "      <td>40.93</td>\n",
              "      <td>48.13</td>\n",
              "      <td>4.67</td>\n",
              "      <td>3.10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>Asian Hotels (North) Ltd.</td>\n",
              "      <td>320.84</td>\n",
              "      <td>59.75</td>\n",
              "      <td>76.95</td>\n",
              "      <td>1.29</td>\n",
              "      <td>32.62</td>\n",
              "      <td>-114.74</td>\n",
              "      <td>-60.45</td>\n",
              "      <td>-17.04</td>\n",
              "      <td>0.14</td>\n",
              "      <td>1.22</td>\n",
              "      <td>13.94</td>\n",
              "      <td>3.26</td>\n",
              "      <td>9.69</td>\n",
              "      <td>1.01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>Asian Hotels (West) Ltd.</td>\n",
              "      <td>135.47</td>\n",
              "      <td>-2.66</td>\n",
              "      <td>118.10</td>\n",
              "      <td>-44.45</td>\n",
              "      <td>23.50</td>\n",
              "      <td>-5.32</td>\n",
              "      <td>-2.33</td>\n",
              "      <td>2.34</td>\n",
              "      <td>0.13</td>\n",
              "      <td>2.03</td>\n",
              "      <td>23.70</td>\n",
              "      <td>-86.25</td>\n",
              "      <td>13.06</td>\n",
              "      <td>1.08</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>Asian Oilfield Services Ltd.</td>\n",
              "      <td>55.38</td>\n",
              "      <td>-10.29</td>\n",
              "      <td>-9.43</td>\n",
              "      <td>0.92</td>\n",
              "      <td>5.42</td>\n",
              "      <td>-18.59</td>\n",
              "      <td>-13.32</td>\n",
              "      <td>-7.13</td>\n",
              "      <td>0.47</td>\n",
              "      <td>0.38</td>\n",
              "      <td>38.79</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.86</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>Astrazeneca Pharma India Ltd.</td>\n",
              "      <td>390.42</td>\n",
              "      <td>-89.53</td>\n",
              "      <td>-6.04</td>\n",
              "      <td>0.07</td>\n",
              "      <td>-14.56</td>\n",
              "      <td>-22.47</td>\n",
              "      <td>-61.95</td>\n",
              "      <td>-48.62</td>\n",
              "      <td>1.26</td>\n",
              "      <td>0.00</td>\n",
              "      <td>10.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>33.85</td>\n",
              "      <td>8.58</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>Banco Products (India) Ltd.</td>\n",
              "      <td>1024.14</td>\n",
              "      <td>61.30</td>\n",
              "      <td>97.49</td>\n",
              "      <td>1.59</td>\n",
              "      <td>11.62</td>\n",
              "      <td>5.71</td>\n",
              "      <td>13.70</td>\n",
              "      <td>15.27</td>\n",
              "      <td>1.36</td>\n",
              "      <td>0.45</td>\n",
              "      <td>24.65</td>\n",
              "      <td>21.00</td>\n",
              "      <td>4.03</td>\n",
              "      <td>0.42</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                     Company Name  Net Sales  ...  Ev/EBITDA  M/Sales\n",
              "0                3I Infotech Ltd.    1311.36  ...      19.55     0.27\n",
              "1                   3M India Ltd.    1574.13  ...      37.04     2.98\n",
              "2           Aavas Financiers Ltd.      17.39  ...       0.00     0.00\n",
              "3                  ABB India Ltd.    7610.48  ...      39.42     2.05\n",
              "4               Abbott India Ltd.    1652.69  ...      13.82     2.03\n",
              "5    Accelya Solutions India Ltd.     303.84  ...       3.75     1.47\n",
              "6            Aegis Logistics Ltd.    3981.64  ...       4.98     0.10\n",
              "7               AGC Networks Ltd.    1050.10  ...       4.12     0.43\n",
              "8            Agro Tech Foods Ltd.     788.92  ...      19.23     1.60\n",
              "9           Akzo Nobel India Ltd.    2232.00  ...      20.53     4.66\n",
              "10       Allsec Technologies Ltd.     320.07  ...       2.53     0.24\n",
              "11            Ambuja Cements Ltd.    9750.45  ...      11.14     3.23\n",
              "12              Andhra Paper Ltd.    1230.50  ...      15.06     1.20\n",
              "13         Asahi India Glass Ltd.    1929.10  ...      15.17     0.54\n",
              "14       Asian Hotels (East) Ltd.     151.11  ...       4.67     3.10\n",
              "15      Asian Hotels (North) Ltd.     320.84  ...       9.69     1.01\n",
              "16       Asian Hotels (West) Ltd.     135.47  ...      13.06     1.08\n",
              "17   Asian Oilfield Services Ltd.      55.38  ...       0.00     0.86\n",
              "18  Astrazeneca Pharma India Ltd.     390.42  ...      33.85     8.58\n",
              "19    Banco Products (India) Ltd.    1024.14  ...       4.03     0.42\n",
              "\n",
              "[20 rows x 15 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9Qh4N7djPW7d",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "test = data.iloc[:,:]"
      ],
      "execution_count": 29,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bKApmFNkPW7h",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "data = data.replace( ' -   ', np.nan)"
      ],
      "execution_count": 30,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kHoY6-0T2Z9T",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 308
        },
        "outputId": "4f3dda33-8ef7-4366-882b-389cf02182e3"
      },
      "source": [
        "data.dtypes"
      ],
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Company Name                     object\n",
              "Net Sales                       float64\n",
              "Cons PAT                        float64\n",
              "Cons OCF                        float64\n",
              "OCF/PAT                         float64\n",
              "PBIDTM (%)                      float64\n",
              "PATM (%)                        float64\n",
              "ROE (%)                         float64\n",
              "ROCE (%)                        float64\n",
              "Asset Turnover(x)               float64\n",
              "Total Debt/Equity(x)            float64\n",
              "Free Float                      float64\n",
              "FR_Dividend Pay Out Ratio(%)    float64\n",
              "Ev/EBITDA                       float64\n",
              "M/Sales                         float64\n",
              "dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9YSg1kfBPW7k",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#data.drop(labels='Company Name', axis=1, inplace=True)"
      ],
      "execution_count": 32,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qLPgieKYPW7o",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "data.iloc[:,1:] = data.iloc[:,1:].astype('float64')"
      ],
      "execution_count": 33,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6baN_MMKPW7s",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "data.fillna(data.mean(), inplace=True)"
      ],
      "execution_count": 34,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "W_fAZTkN_hb1",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "outputId": "86138d3b-5039-497e-9337-cd402f43a996"
      },
      "source": [
        "len(data.columns)"
      ],
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "15"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vJfzFUelXRIQ",
        "colab_type": "text"
      },
      "source": [
        "# **Ev/EBITDA Prediction**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bBWjhlu7PW70",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "data1 = data.iloc[:,:-1 ]"
      ],
      "execution_count": 36,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WQ6KM6YFPW73",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 339
        },
        "outputId": "fc5df293-fc0c-4e68-cd2c-cbbc9acfbca8"
      },
      "source": [
        "data1.tail()\n"
      ],
      "execution_count": 37,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<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>Company Name</th>\n",
              "      <th>Net Sales</th>\n",
              "      <th>Cons PAT</th>\n",
              "      <th>Cons OCF</th>\n",
              "      <th>OCF/PAT</th>\n",
              "      <th>PBIDTM (%)</th>\n",
              "      <th>PATM (%)</th>\n",
              "      <th>ROE (%)</th>\n",
              "      <th>ROCE (%)</th>\n",
              "      <th>Asset Turnover(x)</th>\n",
              "      <th>Total Debt/Equity(x)</th>\n",
              "      <th>Free Float</th>\n",
              "      <th>FR_Dividend Pay Out Ratio(%)</th>\n",
              "      <th>Ev/EBITDA</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>156</th>\n",
              "      <td>Whirlpool Of India Ltd.</td>\n",
              "      <td>2772.73</td>\n",
              "      <td>127.75</td>\n",
              "      <td>143.97</td>\n",
              "      <td>1.13</td>\n",
              "      <td>7.07</td>\n",
              "      <td>3.72</td>\n",
              "      <td>23.65</td>\n",
              "      <td>33.72</td>\n",
              "      <td>2.67</td>\n",
              "      <td>0.00</td>\n",
              "      <td>18.61</td>\n",
              "      <td>0.0</td>\n",
              "      <td>11.51</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>157</th>\n",
              "      <td>Wintac Ltd.</td>\n",
              "      <td>20.88</td>\n",
              "      <td>-17.20</td>\n",
              "      <td>-3.01</td>\n",
              "      <td>0.17</td>\n",
              "      <td>-11.89</td>\n",
              "      <td>-75.82</td>\n",
              "      <td>-55.50</td>\n",
              "      <td>-33.55</td>\n",
              "      <td>0.42</td>\n",
              "      <td>0.09</td>\n",
              "      <td>17.86</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>158</th>\n",
              "      <td>Wyeth Ltd.- (Amalgamated)</td>\n",
              "      <td>678.34</td>\n",
              "      <td>130.06</td>\n",
              "      <td>92.32</td>\n",
              "      <td>0.71</td>\n",
              "      <td>28.08</td>\n",
              "      <td>18.54</td>\n",
              "      <td>24.80</td>\n",
              "      <td>36.88</td>\n",
              "      <td>0.99</td>\n",
              "      <td>0.00</td>\n",
              "      <td>28.03</td>\n",
              "      <td>29.7</td>\n",
              "      <td>8.03</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>159</th>\n",
              "      <td>Xchanging Solutions Ltd.</td>\n",
              "      <td>208.83</td>\n",
              "      <td>12.25</td>\n",
              "      <td>14.25</td>\n",
              "      <td>1.16</td>\n",
              "      <td>15.05</td>\n",
              "      <td>5.87</td>\n",
              "      <td>5.03</td>\n",
              "      <td>8.56</td>\n",
              "      <td>0.62</td>\n",
              "      <td>0.01</td>\n",
              "      <td>6.71</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4.46</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>160</th>\n",
              "      <td>Zim Laboratories Ltd.</td>\n",
              "      <td>185.00</td>\n",
              "      <td>9.52</td>\n",
              "      <td>15.49</td>\n",
              "      <td>1.63</td>\n",
              "      <td>14.51</td>\n",
              "      <td>5.03</td>\n",
              "      <td>12.26</td>\n",
              "      <td>17.47</td>\n",
              "      <td>1.01</td>\n",
              "      <td>0.56</td>\n",
              "      <td>55.91</td>\n",
              "      <td>8.4</td>\n",
              "      <td>0.00</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                  Company Name  ...  Ev/EBITDA\n",
              "156    Whirlpool Of India Ltd.  ...      11.51\n",
              "157                Wintac Ltd.  ...       0.00\n",
              "158  Wyeth Ltd.- (Amalgamated)  ...       8.03\n",
              "159   Xchanging Solutions Ltd.  ...       4.46\n",
              "160      Zim Laboratories Ltd.  ...       0.00\n",
              "\n",
              "[5 rows x 14 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 37
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-5qEKJb_PW7_",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 868
        },
        "outputId": "1235d0f4-d0fb-4c45-f57f-e333d4b62083"
      },
      "source": [
        "plt.figure(figsize=(16,16))\n",
        "cor = data1.corr()\n",
        "sns.heatmap(cor, annot=True, cmap='Greens')\n",
        "plt.show()"
      ],
      "execution_count": 38,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1152x1152 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "VJtw-Zstb-bm",
        "colab_type": "text"
      },
      "source": [
        "## Selecting most important features:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NwpHXXlkPW8F",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 72
        },
        "outputId": "4f0662e0-5ca1-49c2-9449-2e2eed324842"
      },
      "source": [
        "cor_target = abs(cor[\"Ev/EBITDA\"])\n",
        "relevant_features = cor_target[cor_target>0.15]\n",
        "relevant_features.index"
      ],
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['Net Sales', 'PBIDTM (%)', 'ROE (%)', 'Asset Turnover(x)', 'Free Float',\n",
              "       'FR_Dividend Pay Out Ratio(%)', 'Ev/EBITDA'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 41
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "T66rR4ayPW8I",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "X,y = data1[['Net Sales', 'PBIDTM (%)', 'ROE (%)', 'Asset Turnover(x)', 'Free Float',\n",
        "       'FR_Dividend Pay Out Ratio(%)']], data1['Ev/EBITDA']"
      ],
      "execution_count": 42,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WvL1kqO-PW8W",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from sklearn.model_selection import train_test_split\n",
        "if PROVIDE_OWN_INPUT:\n",
        "    X_test =  pd.read_csv('test_data.csv')\n",
        "    X_train,y_train = X,y\n",
        "else:\n",
        "    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.2,random_state = 42)"
      ],
      "execution_count": 43,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dNS2oDutBoIr",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from sklearn.linear_model import LassoCV\n",
        "import xgboost as xgb\n",
        "from sklearn.linear_model import RidgeCV\n",
        "from sklearn.linear_model import BayesianRidge\n",
        "from sklearn.linear_model import ARDRegression\n",
        "from sklearn.linear_model import ElasticNetCV\n",
        "from sklearn.linear_model import LassoLarsCV\n",
        "from sklearn.svm import SVR\n",
        "l=[LassoCV(cv=5, random_state=0),\n",
        "    xgb.XGBRegressor(objective ='reg:squarederror', colsample_bytree = 0.3, learning_rate = 0.1, alpha = 10, n_estimators = 500),\n",
        "    RidgeCV(alphas=[1e-3, 1e-2, 1e-1, 1]),\n",
        "    BayesianRidge(compute_score=True),\n",
        "    ARDRegression(),\n",
        "    ElasticNetCV(cv=10, random_state=42),\n",
        "    LassoLarsCV(cv=5),\n",
        "    SVR(kernel='rbf', C=100, gamma=0.1, epsilon=.1)\n",
        "]\n",
        "reg_name = ['LassoCV', 'XGBRegressor', 'RidgeCV', 'BayesianRidge', 'ARDRegression',\n",
        "            'ElasticNetCV', 'LassoLarsCV', 'SVR']\n",
        "pred_list = []\n",
        "for i in l:\n",
        "    i.fit(X_train,y_train)\n",
        "    #print(i)\n",
        "    pred_list.append(i.predict(X_test))"
      ],
      "execution_count": 44,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CzLdzppGkUaA",
        "colab_type": "text"
      },
      "source": [
        "### Mean Squared Error\n",
        "> Lower the value of error, better the performance"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nfLjLXQ6CmL6",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 163
        },
        "outputId": "08c06bab-68fd-4a9f-e9fb-183ecb20462d"
      },
      "source": [
        "from sklearn.metrics import mean_squared_error\n",
        "for i,r,p in zip(range(len(reg_name)),reg_name,pred_list):\n",
        "    #print(r,'\\t',mean_squared_error(y_test.values, p))\n",
        "    \n",
        "    print('{:2d} {:20s}    {:.10f}'.format(i,r, mean_squared_error(y_test.values, p),))"
      ],
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            " 0 LassoCV                 55.7717035578\n",
            " 1 XGBRegressor            86.7092449883\n",
            " 2 RidgeCV                 40.7696272487\n",
            " 3 BayesianRidge           39.0607305046\n",
            " 4 ARDRegression           43.1705325437\n",
            " 5 ElasticNetCV            54.5307845649\n",
            " 6 LassoLarsCV             55.7717035578\n",
            " 7 SVR                     55.8664468033\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "SPKbBcSQkkIb",
        "colab_type": "text"
      },
      "source": [
        "### R2 Score\n",
        "> Higher the score, better the model. A perfect model willl have the highest value(i.e 1)."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XT0PwTMVMJFl",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 163
        },
        "outputId": "5c9d9c77-5fb2-4318-960f-261b1a812cb5"
      },
      "source": [
        "from sklearn.metrics import r2_score\n",
        "for i,r,p in zip(range(len(reg_name)),reg_name,pred_list):\n",
        "    #print(r,'\\t',mean_squared_error(y_test.values, p))\n",
        "    \n",
        "    print('{:2d} {:20s}    {:.5f}'.format(i,r, r2_score(y_test.values, p)))"
      ],
      "execution_count": 46,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            " 0 LassoCV                 -0.04979\n",
            " 1 XGBRegressor            -0.63213\n",
            " 2 RidgeCV                 0.23259\n",
            " 3 BayesianRidge           0.26476\n",
            " 4 ARDRegression           0.18740\n",
            " 5 ElasticNetCV            -0.02644\n",
            " 6 LassoLarsCV             -0.04979\n",
            " 7 SVR                     -0.05158\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HveRXF9Apinu",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 285
        },
        "outputId": "94afdffc-a419-4791-f490-cc508c2d21a3"
      },
      "source": [
        "if PROVIDE_OWN_INPUT:\n",
        "    plt.plot(range(y_train.shape[0]),y_train,'.r')\n",
        "else:\n",
        "    plt.plot(range(y_test.shape[0]),y_test,'.r')\n",
        "plt.plot([i for i in range(len(pred_list[3]))], pred_list[3])"
      ],
      "execution_count": 50,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7fc34e904080>]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 50
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JQFUM9oXV7hO",
        "colab_type": "text"
      },
      "source": [
        "# **M/Sales Prediction**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LhHK5BKsXNWA",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "data2 = data.iloc[:,: ].drop('Ev/EBITDA', axis=1)"
      ],
      "execution_count": 51,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0WqC2pY0ZuEh",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 374
        },
        "outputId": "ef7f454e-b29b-47f3-e2d9-c9e3960d4187"
      },
      "source": [
        "data2.head()"
      ],
      "execution_count": 52,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<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>Company Name</th>\n",
              "      <th>Net Sales</th>\n",
              "      <th>Cons PAT</th>\n",
              "      <th>Cons OCF</th>\n",
              "      <th>OCF/PAT</th>\n",
              "      <th>PBIDTM (%)</th>\n",
              "      <th>PATM (%)</th>\n",
              "      <th>ROE (%)</th>\n",
              "      <th>ROCE (%)</th>\n",
              "      <th>Asset Turnover(x)</th>\n",
              "      <th>Total Debt/Equity(x)</th>\n",
              "      <th>Free Float</th>\n",
              "      <th>FR_Dividend Pay Out Ratio(%)</th>\n",
              "      <th>M/Sales</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>3I Infotech Ltd.</td>\n",
              "      <td>1311.36</td>\n",
              "      <td>-504.97</td>\n",
              "      <td>49.48</td>\n",
              "      <td>-0.10</td>\n",
              "      <td>11.81</td>\n",
              "      <td>-36.90</td>\n",
              "      <td>-61.72</td>\n",
              "      <td>-4.81</td>\n",
              "      <td>0.34</td>\n",
              "      <td>2.60</td>\n",
              "      <td>40.37</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.27</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>3M India Ltd.</td>\n",
              "      <td>1574.13</td>\n",
              "      <td>52.27</td>\n",
              "      <td>63.78</td>\n",
              "      <td>1.22</td>\n",
              "      <td>7.37</td>\n",
              "      <td>3.16</td>\n",
              "      <td>8.29</td>\n",
              "      <td>11.31</td>\n",
              "      <td>1.68</td>\n",
              "      <td>0.26</td>\n",
              "      <td>12.59</td>\n",
              "      <td>0.00</td>\n",
              "      <td>2.98</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Aavas Financiers Ltd.</td>\n",
              "      <td>17.39</td>\n",
              "      <td>1.89</td>\n",
              "      <td>-172.50</td>\n",
              "      <td>-91.50</td>\n",
              "      <td>57.30</td>\n",
              "      <td>10.84</td>\n",
              "      <td>6.69</td>\n",
              "      <td>9.57</td>\n",
              "      <td>0.16</td>\n",
              "      <td>5.17</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>ABB India Ltd.</td>\n",
              "      <td>7610.48</td>\n",
              "      <td>140.94</td>\n",
              "      <td>-44.20</td>\n",
              "      <td>-0.31</td>\n",
              "      <td>4.76</td>\n",
              "      <td>1.85</td>\n",
              "      <td>5.49</td>\n",
              "      <td>9.82</td>\n",
              "      <td>1.19</td>\n",
              "      <td>0.13</td>\n",
              "      <td>13.15</td>\n",
              "      <td>45.10</td>\n",
              "      <td>2.05</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Abbott India Ltd.</td>\n",
              "      <td>1652.69</td>\n",
              "      <td>144.70</td>\n",
              "      <td>101.35</td>\n",
              "      <td>0.70</td>\n",
              "      <td>13.38</td>\n",
              "      <td>8.64</td>\n",
              "      <td>24.30</td>\n",
              "      <td>36.11</td>\n",
              "      <td>1.74</td>\n",
              "      <td>0.00</td>\n",
              "      <td>20.12</td>\n",
              "      <td>24.96</td>\n",
              "      <td>2.03</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "            Company Name  Net Sales  ...  FR_Dividend Pay Out Ratio(%)  M/Sales\n",
              "0       3I Infotech Ltd.    1311.36  ...                          0.00     0.27\n",
              "1          3M India Ltd.    1574.13  ...                          0.00     2.98\n",
              "2  Aavas Financiers Ltd.      17.39  ...                          0.00     0.00\n",
              "3         ABB India Ltd.    7610.48  ...                         45.10     2.05\n",
              "4      Abbott India Ltd.    1652.69  ...                         24.96     2.03\n",
              "\n",
              "[5 rows x 14 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 52
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QIlTiSHvi6Ew",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 868
        },
        "outputId": "3a01b9dc-029a-4a99-fc61-f722e27dc9b5"
      },
      "source": [
        "plt.figure(figsize=(16,16))\n",
        "cor = data2.corr()\n",
        "sns.heatmap(cor, annot=True, cmap='YlGnBu')\n",
        "plt.show()"
      ],
      "execution_count": 53,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1152x1152 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yp2ozzLRjVV_",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 72
        },
        "outputId": "9764e95a-603f-4cf1-cdc0-c2f21f7d4c32"
      },
      "source": [
        "cor_target = abs(cor[\"M/Sales\"])\n",
        "relevant_features = cor_target[cor_target>=0.2]\n",
        "relevant_features.index"
      ],
      "execution_count": 55,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['Cons PAT', 'Cons OCF', 'PBIDTM (%)', 'ROCE (%)',\n",
              "       'FR_Dividend Pay Out Ratio(%)', 'M/Sales'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 55
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2mnSuhtOkWX5",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "X,y = data2[['Cons PAT', 'Cons OCF', 'PBIDTM (%)', 'ROCE (%)',\n",
        "       'FR_Dividend Pay Out Ratio(%)']], data2['M/Sales']"
      ],
      "execution_count": 56,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "eE1B8yP7mOQK",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from sklearn.model_selection import train_test_split\n",
        "if PROVIDE_OWN_INPUT:\n",
        "    X_test =  pd.read_csv('test_data.csv')\n",
        "    X_train,y_train = X,y\n",
        "else:\n",
        "    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.2,random_state = 42)"
      ],
      "execution_count": 57,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WIzQNsgynCjy",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from sklearn.linear_model import LassoCV\n",
        "import xgboost as xgb\n",
        "from sklearn.linear_model import RidgeCV\n",
        "from sklearn.linear_model import BayesianRidge\n",
        "from sklearn.linear_model import ARDRegression\n",
        "from sklearn.linear_model import ElasticNetCV\n",
        "from sklearn.linear_model import LassoLarsCV\n",
        "from sklearn.svm import SVR\n",
        "l=[LassoCV(cv=5, random_state=0),\n",
        "    xgb.XGBRegressor(objective ='reg:squarederror', colsample_bytree = 0.3, learning_rate = 0.1, alpha = 10, n_estimators = 500),\n",
        "    RidgeCV(alphas=[1e-3, 1e-2, 1e-1, 1],cv=5),\n",
        "    BayesianRidge(compute_score=True),\n",
        "    ARDRegression(),\n",
        "    ElasticNetCV(cv=10, random_state=42),\n",
        "    LassoLarsCV(cv=10),\n",
        "    SVR(kernel='rbf', C=100, gamma=0.1, epsilon=.1)\n",
        "]\n",
        "reg_name = ['LassoCV', 'XGBRegressor', 'RidgeCV', 'BayesianRidge', 'ARDRegression',\n",
        "            'ElasticNetCV', 'LassoLarsCV', 'SVR',]\n",
        "pred_list = []\n",
        "for i in l:\n",
        "    i.fit(X_train,y_train)\n",
        "    #print(i)\n",
        "    pred_list.append(i.predict(X_test))"
      ],
      "execution_count": 58,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "eggWlLu0mhv-",
        "colab_type": "text"
      },
      "source": [
        "### Mean Squared Error\n",
        "> Lower the value of error, better the performance"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hrZW8zxVnHVw",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 163
        },
        "outputId": "0ed76923-56bc-4444-91f6-c647ef7d907b"
      },
      "source": [
        "from sklearn.metrics import mean_squared_error\n",
        "for i,r,p in zip(range(len(reg_name)),reg_name,pred_list):\n",
        "    #print(r,'\\t',mean_squared_error(y_test.values, p))\n",
        "    \n",
        "    print('{:2d} {:20s}    {:.5f}'.format(i,r, round(mean_squared_error(y_test.values, p)**0.5,5),))"
      ],
      "execution_count": 59,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            " 0 LassoCV                 1.68439\n",
            " 1 XGBRegressor            1.93293\n",
            " 2 RidgeCV                 1.74922\n",
            " 3 BayesianRidge           1.70968\n",
            " 4 ARDRegression           1.75174\n",
            " 5 ElasticNetCV            1.68418\n",
            " 6 LassoLarsCV             1.73946\n",
            " 7 SVR                     1.76843\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rEo4-Hdbmm6Q",
        "colab_type": "text"
      },
      "source": [
        "### R2 Score\n",
        "> Higher the score, better the model. A perfect model willl have the highest value(i.e 1)."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5zUzKsp3LFiV",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 153
        },
        "outputId": "adbbf2cf-ef4f-4123-8db9-778d8c48697e"
      },
      "source": [
        "from sklearn.metrics import r2_score\n",
        "for i,r,p in zip(range(len(reg_name)),reg_name,pred_list):\n",
        "    #print(r,'\\t',mean_squared_error(y_test.values, p))\n",
        "    \n",
        "    print('{:2d} {:20s}    {:.5f}'.format(i,r, r2_score(y_test.values, p)))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            " 0 LassoCV                 0.03001\n",
            " 1 XGBRegressor            -0.41364\n",
            " 2 RidgeCV                 0.00609\n",
            " 3 BayesianRidge           0.06581\n",
            " 4 ARDRegression           0.03058\n",
            " 5 ElasticNetCV            0.03034\n",
            " 6 LassoLarsCV             0.05452\n",
            " 7 SVR                     -0.02523\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YQCC_uwFnMcP",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 283
        },
        "outputId": "6e0bcd7c-60bb-4673-8cf9-53d9584eedec"
      },
      "source": [
        "if PROVIDE_OWN_INPUT:\n",
        "    plt.plot(range(y_train.shape[0]),y_train,'.r')\n",
        "else:\n",
        "    plt.plot(range(y_test.shape[0]),y_test,'.r')\n",
        "plt.plot([i for i in range(len(pred_list[3]))], pred_list[5])"
      ],
      "execution_count": 60,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7fc35e927b00>]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 60
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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VmJn+yiqufWut+84i4yallTUs2XiYAD8fPlhzkAOtOLnqnvwSftlzlOsn9MXPun9FVNdOnDekF4vTsmRSEThZZWJvQWmL9Wkb2/1ccbKLzLwSnvwqnXMG9+SuSQObvW9wgB8Xj4zizRvG8uqsMWzOKuTejzc5VQqpMZl57Itt9OgSyEMXDql32+jYbtx2zgA+XHuI1XuOtur38TSnatRKqX7AaGCtndvuUEqlKaXSCgoKXBOdG5nMmj98splXftrDfzcddvhxmXklLS4dtychOsylS8k/WneIPfmlpO47xu0L06iodn4E4in/3XSY0soaXps1mgA/H55ftsvp53g/9SABvj5cPa5PvetnjY8lv6SSn3Z6d03SFXbmFmPWTa9IbMhWx25rz//JKhN3L9pISJA/L848Ax8f1fKDrC6M781fLh7ODzvyeOrrdIePGBekHmT74WKe/M0IQu2cGu+BqXH079mZR5ZspcwLd7N0OFErpboAnwP3a60bfeVqredrrRO11onh4eGujNEtFqdlse1wEaFBfry2Yo9Ds881JjP7jpY5VZ+2GRkTxuHCkxxvQ/3Npryqhld/2sOZ/bvz4sxRrN57jDvf30BljfGTtdaWCcD46FCmDo/g9nMG8M3WI2w6dMLh5yipqOazDdlcPDKSnl0C692WPCSc3qFBfNTaScXUVJg713Lp5Zrag7op4SGBRIQGtrlF7+n/pbOnoJR/XT2K8JDAlh/QwM1n9ef2c/qzMPUg83/e1/gODf5GOYUneXHZLs4bEs70hN52nzPI31ICyT5xkueXOj8w8DSHErVSyh9Lkl6ktV7i3pDcr7C8in98v5Px/bvzz6tGcfBYOV84MKqu3ePDifq0jSt30ntv9QGOllby8IVDuGJMDHMvT2BlZgF3L9pk+EP+tIMn2Jlbwg0T+qKU4vZJA+jZJZC53+10ePT0xabDlFWZuHFiv0a3+fn6MHNcH1ZmtmJSMTUVJk+GP//ZcunlyTo9p5iwTv7EdOvk8GPio9q2N83XW3L4aF0Wvzt3IOcMbv2A7dGLhjFjZCRzv9vJV1tyTt1g52/05FfpmLTm6Uvj650PsqFx/bozO6kfC1IPsP7A8VbH5gmOdH0o4D9Ahtb6RfeH5H7/XLaL4ooanrpkBFOHRzAiKtShUXVmnqXjw5keapvaRJ3dtgnFovJq3kzZy+ShvWonaK4ZH8vTl47gx4w87vt4k1t6U11lYepBQoL8uGSUZZqjS6Af908ZzLr9xx3qgdZas2D1AUbFhHFGn65273P1OMuk4uI0JycVU1KgqgpMJstlSopzjzeYHTlFjU5m25IR0WHsLSht1bzHoWPlPLpkG2Niu/KHqXFOP74uHx/FC1eNYny/7vxx8RbW7DtmuaHB32jpDxtZtiOP+6fE0ad7cIvP+9C0IUR37cQjn231qnKhIyPqs4AbgPOVUput/013c1xNqjaZOdyGPR22Hy5i0dpD3DChr3XXMMX9U+IcGlU7s8dHQ6FB/gzo2bnNder5q/ZSXFHDgxfUnzC5Makfj88Yxrfbcnnw0y0u6Ul1tfySCr7ffoSrxvahU4Bv7fVXj+vDgPDOzP0uo8UvmV/3HGNvQRmz7YymbaK7diJ5SC8+WZ/l3JdWcjIEBICvr+UyOdnxxxpMjcnMztwSh8seNvFRoZg1ZBwpcepxVTVmfv/RRnwUvDJrtN0TFDgryN+X+TeOpU/3TtyxMM2yGVqdv1Fp51CeNA9gaO8Qbj27v0PP2TnQj7//diT7jpbxrx8y2xyjjdaaLzcf5qmv0132nHU50vXxi9Zaaa1Haq3PsP73rVuiaUHW8XJ+O2815/z9J5am5zr9eLNZ85cvt9Ojc0C9b/wpw3o5NKrenV9KTDfnOj7qSogJa1PpI7+kgnd+OcAlo6IanU0a4LZzBvDwhUP4cnMOj3y+FbPBkvXi9VlUmzTXTYitd72/rw+PXDiUvQVlLE7LbvY5FqQeoEfnAKYnRJ660k5duVWTiklJlC/9kf/++VUql/3o1Wd333e0jMoac+3ScEfZjvzSneynfn7pTrZmF/GPK0cS063lka2jugYH8N7N4wn09+Wmd9aRN2I0LF8OzzzDi88vJrfSzF8vT3Dqi+GsQT2ZNT6Wt1btY3NW21tm9xWUcv1/1nLfx5vZePCEW7qwvGZl4tL0XKa/sor9R8sY3CuEez/a5HSdacmmw2w8VMgjFw4lrNOpmWFHR9WZeSWtqk/bJESHcaSogvySilY9/o0Ve6kymZs9rJyTPIj7pwzmsw3ZPP7ldsP0WdeYzHy49hBnD+rJwPDGr+EFwyNI7NuNf/2Y2eSsfNbxcpZn5HHN+D4E+VtH5E3Ulc8bEk5EaKBTk4pVNWbu2u3H/Sdjeb28h/O/pIHYEu3wSMc6Pmxsi2OcqVOv2JnPW6v2c2NSXy6Mj2z5AU7q0z2Yd28aR+HJam56dz0loxPZdsMc3ttfyXVnxjK2bzenn/PR6UOJCA3i4c+2tHoSvqLaxIvLdnHhS6vYml3EM5eOYMmcswgOaN1ArjmGT9RVNWae+d8O7nx/A/16dOabe87hozsmEN21E7e+t55duY4dohVXVPO37zIYHduV346JaXR7S6PqGpOZfQVlrapP2yS04UwaWcfLWbT2IDMT+9C/Z+dm73vf5MHMSR7Ih2sP8dTXOwyRrH/amU9OUQU3JPW1e7tSikenD6OgpJK3V+23e59Fay1J97oz6zxHE3VlP18frk7sQ0pmgUOlMrNZ89BnW/g5s4ChvUOYt3Ive/KdO/w3kvTDxQT6+TAwvPn3SkNKKUZEhTp8sttDx8p58NMtDIsM5bHpw1oTqkPio8N447oxZOaVMGfRxlM909OGtur5QoP8ee7yBDLzSnn66x0cKXKunLoys4BpL/3MKz/t4aKE3ix/8FxuSOqHrxOtiM5wfep3oewT5fz+w01szipkdlJfHpsxjEA/y0hqwS3j+e281cx+Zx2fz5lIdNfmZ7Zf+mE3x8qqePem8af6OlNTLR/s5GRUUhL3T4nj9oVpfLHpMFcl1u/PPXi8nCqTY2d1acqI6DCUgrQDJzh/aIRTj315+W6UUtw7eVCL91VK8dC0IVTVmHn7l/3UmM1MHNiz3n3s5e4xfbsSGeZ4h4Az3l9jWUU4eWivJu8ztm83Lorvzb9/3su1Z8bWa+2qqDbxyfpDXDC8N1F1/9a2mmVVVaO68sxxfXh1xR4+WXeIBxrU9OvSWvPMNzv4cnMOD00bwtXj+jD5hZU89sV2PrljglOTcUaRnlPM0N4htYuBnDEiKoz//LKPyhpT7efNnpzCk8x6aw1mrXnt2tGnjnLcJHlIL+ZensDDn28F4LVrR9c7MnbWeUN7MWt8LIvWHmLR2kMM7R3CuXHhnBsXTmK/7gT4NX7t8oorePp/O/hm6xEG9OzMotvO5KxBPe08u2sZNlEvz8jjgcWWSbHXrx3DjJH1D6n6dA9mwS3jmflmKrPfWcdndyXRNdj+fgY7c4tZkHqAWeNjSYixHgraDpltH/Dly5kyYULtqPry0dH13uS7azs+Wl/66BLoxzmDw3lz5V769gjm6nGxLT8Iyyq8JRuzufXs/g4nUqUUf5oxjGqTmQWpB/lgTcslgJBAP/5+5cj69V8X2H+0jFW7j/Lg1LgWE8dD04bww448Xl6eybOXJdRe//WWHE6UV3PjxAYj8qQkS83S+oVbt64c0y2Yc+PC+SQti3snD27yZ7+Rspd3fz3ALWf1Z07yQJRSPDZ9KI98vo1PN2Qzs8GXtqsdKTqJWdPiYMNRlpPZFjFjZFSrHh8fHUq1SbM7r7S2Zt1QfkkF1729luKT1Xx4+wS75Sx3mDmuD+VVNWSdOMkMF7xPn7s8ntkT+7JyVwErMwt459f9/PvnfQQH+DJxYE/OHRJOclw4kWFBLEw9yIs/ZFJlMvPA1DjuPHdAs19krmS4RF1tMvP80l3M/3kfwyNDeeO6MfRr4lB/WGQo829MZPY767jlvfUsum1CvW4CsLxpn/gynZAgPx6qO6qyc8jc3Kja1vHR1jfkvOvG8LtFG3nk820UlFRy93mDWhyxvbAsk+AAP36X3PJoui6lFE9eMoKbzupPVU3jck7dH1tWWcNTX+9gzqKN3JjUlz/VOXppqw/WHMTPR3H1+JYT3oDwLlx7pmWUc/NZ/RkY3sXSkpd6gMG9upA0wE7tOCmpyYm/a8fHcsf7G1ixq4CpwxsfxXy87hDPL93FZWdE8fiMYbV/i6vG9uGzDdk8920Gk4f2okcX5xduOOquDzZyvKySFQ8mt2oE3FD2iZMUV9Q43fFhE19nhaK9RH28rIob3l5HXnEF7986/tTgp53cdJZjHR6OUEoxtHcoQ3uHcue5AymtrCF17zFWZuaTsquAHzPyAAjr5E/RyWomxYXz9CUjmsxJ7mKoGnVO4Umumb+G+T/v4/oJsSyZM7HFFyRpYA9euuYMNmUV8vsPNzaqL3+99Qhr9x/noWlD6FZ3B7EmWrGaqlVntrHjw6ZzoB//mZ3I5aOj+eeyTJ74Kr3ZVrqt2YV8tz2X287p79AOaA0ppejfszNDeoc0+i8u4tR/o2O7sfjOJG4727Ii7LfzVnPwmPN7cDR0ssrEp2lZXBjfm14hQQ495t7Jgwny8+Ef31s20dl4qJDth4u5cWI/p8sQ5w/tRa8Q+5OKS9NzeeyLbZwbF84/rhxVb6mzj4/iucsTKKus4blv3beZT/aJcrZkFZJ1/CRfb81p+QEOcHZFYkOx3YMJCfSzu5Ne0clqbnxnLQeOlfH2jYmNNlvyOg06hroE+jF1eATPXpbAqofP46cHz+UvFw9nUlw4r187hgU3j2v3JA0GStSF5VVc/Oov7DxSzCuzRvPsZQkO17ymJ0Ty9CUjWL4zn8e+2FY7eVZaWcNfv9lBfHQo1zQsM9gOmZ95xnJpHZHV7QD57+ZTH5zdeSVtmkisy9/XhxeuGsUdkwawMPUg93y0scmZ5+eX7qJbsL/DfaJtEeDnw+MXD+etGxPJOn6Si1/5hW+3HWnTc369JYfiihpumNCgZNHMUu2eXQK569yBLE3PI+3AcRamHiAk0I8rRju/F5ifdT+QlF359SYV1+w7xj0fbWJkTFfmXT/Gbj1ycEQId0wawOcbs1m91z2b+Xy/3dJmGhUWxBsr9rqkpXLHkWJ8FAzt3bpE7eOjGG5nQrGssoab313HrtwS3rxhLBPboTbrVi2sRFVKMSC8C7ec3Z9XZ41mxshIj81XGCZRdw0O4N7zB/HVPWdzySjna2s3JPXjnvMHsTgtmxeWWRrZX/1pN3nFlTx9abz92dikJHj00UaHzbZR9as/7abGZK7t+HD09FuO8PFRPDZ9GH+ablmkctM76xttL5m69xirdh/l7vMGEWJnoxl3mTo8gm/uPZuBvbowZ9FG/vLl9la1MGmtWbjmAHERXRjfv87Iy4Gl2ree059eIYH8+ct0vt12hCsTY1p9NDMzsQ8aSx83WHaHu31BGrHWtq/m2qnuOX8wsd2DefyL1r0GLVmansvQUF8eqcpkd34pP1gPtdtiR04RA8O7NCoDOiM+OoyMI8W1R5UV1SZuW5DGluwiXp01mvOGND0p7DW8aCWqYRI1WGpPbakBPzA1jmvG9eG1FXt47tsM3vllP1eNjandm9ZRSinumzy4dlRd2/HRyzUj6rpunzSAf109ivUHjnP1v9eQX2zpsdZa8/zSnfQODeL6hqPRdhDTLZjFdybVbo7TmlLIluwith8urt3Xo5YDH5DgAD8emBpHxpFiqk268YjcCX26BzNpcDifrM9iX0EpN76zji5Bfiy8ZXz9cpgdQf6+PHtZPPuOljEvZW+rY7Anv6SCtAMnuHDZh8x49j76Fubyxteb29xOmZ5TbHdBlDPio0OprDGzt6CMyhoTd32wgTX7j/HCVaMa90p760ZWXrQS1VCJuq2UUjx7WTxThkUw/+d9BPn78shFreuznDo8guGRllF1hvW8c23p+GjO5aNj+M9N4zh4rIwr5q1m/9EyftqZz8ZDhdw3ZbDb256aEuDnw59m1C+FfLP1iMOJ5P3Ug3QO8OWyhiULBz8gV46NYXhkKKQtfSEAAA3cSURBVFOGRTCgjZO4s8bHkltcwaWv/0qN2cz7t46v3+bXjElx4VwyKoo3Vuxlb0Fpm+Koa1l6Hhq4aOcv+NVUc+e6z9lSaGL13mOtfs7jZVUcKapodX3axrbl6ZasQu77aDMpuwp47vKExn9Lb97IqonypxF1qEQNlprkq7NGc8WYaP52xchG22A6ylKrtoyqX/7RchaS1uzx4ahz48L56PYJlFeZuHLeap79JoN+PYK5cmzjxTntrW4p5O4PN3LFvNV8vz232XrqibIqvt6awxVjYhqXbRz8gPj5+rBkzkTeuG5Mm3+HycN6ER4SSI1J8+5N4xjk5NHR4xcPI9Dfh8e/cN1qz++359K/sw9xxbng68tvd/9Cr0DF6yv2tPo5039cA8CIQsf3WLdnQM/OBPn78Mz/dvB9ei5/uXg4s8bbaSf1ovKBXU2UP42mwyVqgE4Bvrw484xGvdfOso2qd+eX0qd7J7csDa1rVJ+ufHZXEp0CfNl/tIwHLhjiks1tXMFWCnnm0hEcLa3krg82MOXFlXy87pDd2u2nGyxnB2+ybOPgByTI39fuRJ+z/H19eO/mcSyZM5HRTpbCAHqFBPF/Fw0ldd8xlmxsWxIEy+R56r5jTEvsj7J+aQUuW8odU4ayeu8xNjqxP3et1FTSn38DgBGzr2zT6NbP14dhkaGUVNbw0LQh3NLUZLYXlQ+8mTGygI3Bal22UTVAnBvq0/YMCO/CkjkTeenqM7jYxQtP2irAz4cbkvqx4sFkXp01mk4Bvvzfkm2c/fcVzEvZWzsZajZrPlhziPH9uzOkd/u8bo4YERXGMAfPH2jPrHGxjIntyl+/zWjTCVgBfszIx2TWXBTfu96X1qzxsXQN9ueNFc7Xw/WKFFKjhxNdlE/XkuNtHt3eN3kwz14Wz93nNdO/70XlA29mnAUvdlYKGuGPPnV4BJeeEdWus9y9QoIa1wINxM/Xh9+MiuLikZH8uucYb67cy9+/38nrK/Zw3ZmxDAzvwqHj5Tw0rell297Ix0fx3BUJXPzKL8z9LoN/XDmq5QfV2aag7vv5++1HiAoLYmSDxSKdA/24aWI/XvpxN7tyS5z6ovtPnzNZWXySP676wCWj22RH3/PNLDgSrmGcEbVBa11KKV6+ZrShE6enKKU4e3BPPrjtTP53z9kkDwnnrVX7ePjzrfTsEsi0EfZPi+TNhvYO5bZzBrA4LZu1+1qY9Gtioq20soafdx9lWnxvu325N03sR3CAL/NSHK9Vr9iVz3M7TnJRpD9zZow0zEDHaQY7qjYK4yTq06XW1UHfiPHRYbx27RhS/ngetw0M4mlzJgHrG50DuUO4b/JgYrp14omv0ptfoNLE4GPFznyqasxc2MQXWdfgAK6f0JevtuRw6FjLpxPbk1/KvR9uYmjvUF743fn4PGb8yTG7vLmDxM2Mk6hPh1rXafBGjM3cwuP3/YbpT9/bYX/HTgG+PDRtCDtzS/imuZWbTQw+vk/PpWeXABL7Nb38+taz++Pn48ObPzdfqy4qr+b2hWkE+vvw1uxEt094u5VBj6qNwDiJGrymVabVToc34unwOwK/GRnFkIgQ/vVjZtNnBbIz+KioNrFiZz5Th/dudu/iiNAgrkyM4bO07NpFUA3VmCynv8o+Uc6b14912e57HuPqo+oOdPRqrETd0Z0O5Z3T4XfEMrH4h6lx7Csoq7cnTCMNBh+rdh+lvMpk6fZowV2TBlJjtuwpbs9fv81g1e6j/PWyhGZH517DlUfVHezo1YuPk7xQM3sndxinw+9oNW1EBPHRoby8PJNLRkU51O/93fYjhAb5McHedq0NxPYI5pJRUXyw5iBzkgfW22/9k/WHavfQnjnOTftlN9Gx4lau6iCxd2Tnxe9FGVG3t45e3oHT43fE0vXy4AVDyDp+kk83ZLV4/2qTmR935DFleITDi3h+lzyI8ioT760+UHvd+gPHefy/25kUF85j01u3RUKLvH1E2sGO7CRRC9EGyXHhjO3bjVeX76Giuvnd9dbsO0ZxRU2T3R72DOkdwpRhEby3+gBllTVknyjnrvc30KdbMK/OGu2SEw3Y5e1zDR2sOUEStRBtoJTijxcMIbe4ovbku035bnsuwQG+TIoLd+pnzDlvIIXl1by9aj+3L9xAlcnMW7MT23S+wBZ1hBFpBzqykxq1EG2UNLAHZw3qwbyUPVwzro/dfbNNZs2y9DzOG9LL6d0Qx8R2Y+LAHvzrx0x8FLx783j3n6PwNJpr8AYyohbCBR6YOoSjpVUsSD1g9/YNB09wtLSSCx3o9rDnnvMH4+uj+NOM4Zzr5Ii81TrQiNTbSaIWwgXG9u3G+UN78e+V+xqdqQcsW5oG+Plw3tDW7RmTNLAHm/4ytV1OySZayY1925KoO7oO1PRvdA9MjaPopKWWXJfWmqXpuUwa3JMubTg5cmg7no5NOMnNXTKSqDsyb2+x8jLx0WFMT+jNO7/s53idbVC3HS7icOHJDrlJlbByc5eMJOqOzJk3z+kw8m6H3/EPU+Ioq6rh33X26Phuey6+PoqpwyPc9nOFh7m5S0a6Pjoy25vHtsd3U28eg+4F7lLt9DsOjgjhsjOiWbD6ALee3Z/wLoF8vz2XpAE96q0sFB2Mm7tkZETdkTna9O/tixsc0Y6/432TB1Nt0ryxYi+780vZf7SMaa3s9hBexI1dMjKi7ugc2TvB0ZG3N2vH37Ffz87MTIzhw7WHqKg2oRRMk7KHaANJ1MLxwzZPbNLjqp/Zzgs4fn/+YD7fcJiP12eR2LcbvUKD3PrzRMcmiVpYtDTy9kQd29U/05Xn9mvhCyS6ayeuPTOW91YfaPUiFyFsJFEbkSdGri3xxLaRRt2q0sEvkHvOH0RljYkrxsR4IEjRkUiiNhqjdmB4oo5t1Nq5g18gPboEMveKke0enuh4JFEbjVFHkZ7YpMeoGwMZ9QtEdFgOJWql1IXAy4Av8LbW+m9ujep0ZuQk4Moar5F/ZkuM+gUiOqwWE7VSyhd4HZgKZAPrlVJfaa13uDs4uxyt37qyztueNWNJAt7BiF8gRmbEeRdneDh+R0bU44E9Wut9AEqpj4FLgfZP1I7Wb11Z5/VEzViSgOhIjDrv4igDxO/IysRooO4J4bKt19WjlLpDKZWmlEorKChwVXz1Obq6zJWr0E6HVXtCuJO3f4YMEL/LlpBrredrrRO11onh4W7a2NzRjU9cuUFKRzglkRCe5O2fIQPE70jp4zBQ93z0Mdbr2p+j9VtX1nmlZixE23j7Z8gA8SutdfN3UMoPyAQmY0nQ64FrtdbpTT0mMTFRp6WluTJOIYTo0JRSG7TWifZua3FErbWuUUr9HliKpT3vneaStBBCCNdyqI9aa/0t8K2bYxFCCGGH7EcthBAGJ4laCCEMThK1EEIYnCRqIYQwuBbb81r1pEoVAAdb+fCewFEXhtOevDl28O74vTl2kPg9ySix99Va210t6JZE3RZKqbSmegmNzptjB++O35tjB4nfk7whdil9CCGEwUmiFkIIgzNiop7v6QDawJtjB++O35tjB4nfkwwfu+Fq1EIIIeoz4ohaCCFEHZKohRDC4AyTqJVSFyqldiml9iil/s/T8ThLKXVAKbVNKbVZKWX4PV6VUu8opfKVUtvrXNddKfWDUmq39bKbJ2NsShOxP6mUOmx9/TcrpaZ7MsamKKX6KKVWKKV2KKXSlVL3Wa/3lte+qfi95fUPUkqtU0ptscb/lPX6/kqptdb884lSKsDTsdZliBq19QS6mdQ5gS4wy2Mn0G0FpdQBIFFrbYTG+RYppSYBpcBCrXW89bp/AMe11n+zfll201o/4sk47Wki9ieBUq31Pz0ZW0uUUpFApNZ6o1IqBNgAXAbchHe89k3FPxPveP0V0FlrXaqU8gd+Ae4DHgCWaK0/Vkq9CWzRWs/zZKx1GWVEXXsCXa11FWA7ga5wE631z8DxBldfCiyw/nsBlg+g4TQRu1fQWh/RWm+0/rsEyMByDlJvee2bit8raItS6//6W//TwPnAZ9brDff6GyVRO3QCXYPTwDKl1Aal1B2eDqaVIrTWR6z/zgUiPBlMK/xeKbXVWhoxZOmgLqVUP2A0sBYvfO0bxA9e8vorpXyVUpuBfOAHYC9QqLWusd7FcPnHKIm6Izhbaz0GuAi423p47rW0pSbm+bqY4+YBA4EzgCPAC54Np3lKqS7A58D9Wuviurd5w2tvJ36vef211iat9RlYzv86Hhjq4ZBaZJREbZwT6LaS1vqw9TIf+ALLG8Db5FlrkLZaZL6H43GY1jrP+gE0A29h4NffWhv9HFiktV5ivdprXnt78XvT62+jtS4EVgBJQFfr+WHBgPnHKIl6PTDYOvMaAFwDfOXhmBymlOpsnVhBKdUZuADY3vyjDOkrYLb137OBLz0Yi1NsSc7qcgz6+lsns/4DZGitX6xzk1e89k3F70Wvf7hSqqv1352wNDBkYEnYV1rvZrjX3xBdHwDWdp6XOHUC3b96OCSHKaUGYBlFg+U8lB8aPX6l1EdAMpYtHvOAJ4D/AouBWCzb1M7UWhtu0q6J2JOxHHZr4ABwZ52ar2Eopc4GVgHbALP16sew1Hm94bVvKv5ZeMfrPxLLZKEvloHqYq3109bP8MdAd2ATcL3WutJzkdZnmEQthBDCPqOUPoQQQjRBErUQQhicJGohhDA4SdRCCGFwkqiFEMLgJFELIYTBSaIWQgiD+3/6p2RyI6esUAAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rxHmctBJmrUe",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}