bigdata.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import zipfile\n",
    "import gzip\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "path = \"D:\\Python Projects\\Panama Papers\\\\bigdata\\companies.csv.gz\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "ename": "BadZipFile",
     "evalue": "File is not a zip file",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mBadZipFile\u001b[0m                                Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-7-8e10ccbec0c3>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mzf\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mzipfile\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mZipFile\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mpath\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      2\u001b[0m \u001b[1;31m# if you want to see all files inside zip folder\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      3\u001b[0m \u001b[0mzf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mnamelist\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      4\u001b[0m \u001b[1;31m# now read your csv file\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[0mdf\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mread_csv\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mzf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mopen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'companies.csv'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\anaconda3\\lib\\zipfile.py\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, file, mode, compression, allowZip64, compresslevel, strict_timestamps)\u001b[0m\n\u001b[0;32m   1266\u001b[0m         \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1267\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mmode\u001b[0m \u001b[1;33m==\u001b[0m \u001b[1;34m'r'\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1268\u001b[1;33m                 \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_RealGetContents\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1269\u001b[0m             \u001b[1;32melif\u001b[0m \u001b[0mmode\u001b[0m \u001b[1;32min\u001b[0m \u001b[1;33m(\u001b[0m\u001b[1;34m'w'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'x'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1270\u001b[0m                 \u001b[1;31m# set the modified flag so central directory gets written\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\anaconda3\\lib\\zipfile.py\u001b[0m in \u001b[0;36m_RealGetContents\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m   1333\u001b[0m             \u001b[1;32mraise\u001b[0m \u001b[0mBadZipFile\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"File is not a zip file\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1334\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mendrec\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1335\u001b[1;33m             \u001b[1;32mraise\u001b[0m \u001b[0mBadZipFile\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"File is not a zip file\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1336\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdebug\u001b[0m \u001b[1;33m>\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1337\u001b[0m             \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mendrec\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mBadZipFile\u001b[0m: File is not a zip file"
     ]
    }
   ],
   "source": [
    "zf = zipfile.ZipFile(path) \n",
    "# if you want to see all files inside zip folder\n",
    "zf.namelist() \n",
    "# now read your csv file \n",
    "df = pd.read_csv(zf.open('companies.csv'))\n",
    "df.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "openCorporate\\companiesOC1.csv\n",
      "openCorporate\\companiesOC2.csv\n",
      "openCorporate\\companiesOC3.csv\n",
      "openCorporate\\companiesOC4.csv\n",
      "openCorporate\\companiesOC5.csv\n",
      "openCorporate\\companiesOC6.csv\n",
      "openCorporate\\companiesOC7.csv\n",
      "openCorporate\\companiesOC8.csv\n",
      "openCorporate\\companiesOC9.csv\n",
      "openCorporate\\companiesOC10.csv\n",
      "openCorporate\\companiesOC11.csv\n",
      "openCorporate\\companiesOC12.csv\n",
      "openCorporate\\companiesOC13.csv\n",
      "openCorporate\\companiesOC14.csv\n",
      "openCorporate\\companiesOC15.csv\n",
      "openCorporate\\companiesOC16.csv\n",
      "openCorporate\\companiesOC17.csv\n",
      "openCorporate\\companiesOC18.csv\n",
      "openCorporate\\companiesOC19.csv\n",
      "openCorporate\\companiesOC20.csv\n",
      "openCorporate\\companiesOC21.csv\n",
      "openCorporate\\companiesOC22.csv\n",
      "openCorporate\\companiesOC23.csv\n",
      "openCorporate\\companiesOC24.csv\n",
      "openCorporate\\companiesOC25.csv\n",
      "openCorporate\\companiesOC26.csv\n",
      "openCorporate\\companiesOC27.csv\n",
      "openCorporate\\companiesOC28.csv\n",
      "openCorporate\\companiesOC29.csv\n",
      "openCorporate\\companiesOC30.csv\n",
      "openCorporate\\companiesOC31.csv\n",
      "openCorporate\\companiesOC32.csv\n",
      "openCorporate\\companiesOC33.csv\n",
      "openCorporate\\companiesOC34.csv\n",
      "openCorporate\\companiesOC35.csv\n",
      "openCorporate\\companiesOC36.csv\n",
      "openCorporate\\companiesOC37.csv\n",
      "openCorporate\\companiesOC38.csv\n",
      "openCorporate\\companiesOC39.csv\n",
      "openCorporate\\companiesOC40.csv\n",
      "openCorporate\\companiesOC41.csv\n",
      "openCorporate\\companiesOC42.csv\n",
      "openCorporate\\companiesOC43.csv\n",
      "openCorporate\\companiesOC44.csv\n",
      "openCorporate\\companiesOC45.csv\n",
      "openCorporate\\companiesOC46.csv\n",
      "openCorporate\\companiesOC47.csv\n",
      "openCorporate\\companiesOC48.csv\n",
      "openCorporate\\companiesOC49.csv\n",
      "openCorporate\\companiesOC50.csv\n",
      "openCorporate\\companiesOC51.csv\n",
      "openCorporate\\companiesOC52.csv\n",
      "openCorporate\\companiesOC53.csv\n",
      "openCorporate\\companiesOC54.csv\n",
      "openCorporate\\companiesOC55.csv\n",
      "openCorporate\\companiesOC56.csv\n",
      "openCorporate\\companiesOC57.csv\n",
      "openCorporate\\companiesOC58.csv\n",
      "openCorporate\\companiesOC59.csv\n",
      "openCorporate\\companiesOC60.csv\n",
      "openCorporate\\companiesOC61.csv\n",
      "openCorporate\\companiesOC62.csv\n",
      "openCorporate\\companiesOC63.csv\n",
      "openCorporate\\companiesOC64.csv\n",
      "openCorporate\\companiesOC65.csv\n",
      "openCorporate\\companiesOC66.csv\n",
      "openCorporate\\companiesOC67.csv\n",
      "openCorporate\\companiesOC68.csv\n",
      "openCorporate\\companiesOC69.csv\n",
      "openCorporate\\companiesOC70.csv\n",
      "openCorporate\\companiesOC71.csv\n",
      "openCorporate\\companiesOC72.csv\n",
      "openCorporate\\companiesOC73.csv\n",
      "openCorporate\\companiesOC74.csv\n",
      "openCorporate\\companiesOC75.csv\n",
      "openCorporate\\companiesOC76.csv\n",
      "openCorporate\\companiesOC77.csv\n",
      "openCorporate\\companiesOC78.csv\n",
      "openCorporate\\companiesOC79.csv\n",
      "openCorporate\\companiesOC80.csv\n",
      "openCorporate\\companiesOC81.csv\n",
      "openCorporate\\companiesOC82.csv\n",
      "openCorporate\\companiesOC83.csv\n",
      "openCorporate\\companiesOC84.csv\n",
      "openCorporate\\companiesOC85.csv\n",
      "openCorporate\\companiesOC86.csv\n",
      "openCorporate\\companiesOC87.csv\n",
      "openCorporate\\companiesOC88.csv\n",
      "openCorporate\\companiesOC89.csv\n",
      "openCorporate\\companiesOC90.csv\n",
      "openCorporate\\companiesOC91.csv\n",
      "openCorporate\\companiesOC92.csv\n",
      "openCorporate\\companiesOC93.csv\n",
      "openCorporate\\companiesOC94.csv\n",
      "openCorporate\\companiesOC95.csv\n",
      "openCorporate\\companiesOC96.csv\n",
      "openCorporate\\companiesOC97.csv\n",
      "openCorporate\\companiesOC98.csv\n",
      "openCorporate\\companiesOC99.csv\n",
      "openCorporate\\companiesOC100.csv\n",
      "openCorporate\\companiesOC101.csv\n",
      "openCorporate\\companiesOC102.csv\n",
      "openCorporate\\companiesOC103.csv\n",
      "openCorporate\\companiesOC104.csv\n",
      "openCorporate\\companiesOC105.csv\n",
      "openCorporate\\companiesOC106.csv\n",
      "openCorporate\\companiesOC107.csv\n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-37-86a658cd2cf9>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[0mcount\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[1;32mfor\u001b[0m \u001b[0mchunk\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mpd\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mread_csv\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mpath\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcompression\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'gzip'\u001b[0m\u001b[1;33m,\u001b[0m  \u001b[0mchunksize\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m200000\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mlow_memory\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mFalse\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      3\u001b[0m     \u001b[0mtemp\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mchunk\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      4\u001b[0m     \u001b[0mp\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;34m\"openCorporate\\\\companiesOC\"\u001b[0m \u001b[1;33m+\u001b[0m \u001b[0mstr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcount\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m+\u001b[0m\u001b[1;34m\".csv\"\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m     \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mp\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\pandas\\io\\parsers.py\u001b[0m in \u001b[0;36m__next__\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m   1105\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m__next__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1106\u001b[0m         \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1107\u001b[1;33m             \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_chunk\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1108\u001b[0m         \u001b[1;32mexcept\u001b[0m \u001b[0mStopIteration\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1109\u001b[0m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mclose\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\pandas\\io\\parsers.py\u001b[0m in \u001b[0;36mget_chunk\u001b[1;34m(self, size)\u001b[0m\n\u001b[0;32m   1165\u001b[0m                 \u001b[1;32mraise\u001b[0m \u001b[0mStopIteration\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1166\u001b[0m             \u001b[0msize\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mmin\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msize\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mnrows\u001b[0m \u001b[1;33m-\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_currow\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1167\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mread\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mnrows\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0msize\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1168\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1169\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\pandas\\io\\parsers.py\u001b[0m in \u001b[0;36mread\u001b[1;34m(self, nrows)\u001b[0m\n\u001b[0;32m   1131\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mread\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mnrows\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1132\u001b[0m         \u001b[0mnrows\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0m_validate_integer\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"nrows\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mnrows\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1133\u001b[1;33m         \u001b[0mret\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mread\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mnrows\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1134\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1135\u001b[0m         \u001b[1;31m# May alter columns / col_dict\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\pandas\\io\\parsers.py\u001b[0m in \u001b[0;36mread\u001b[1;34m(self, nrows)\u001b[0m\n\u001b[0;32m   2035\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mread\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mnrows\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2036\u001b[0m         \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 2037\u001b[1;33m             \u001b[0mdata\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_reader\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mread\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mnrows\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   2038\u001b[0m         \u001b[1;32mexcept\u001b[0m \u001b[0mStopIteration\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2039\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_first_chunk\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mpandas\\_libs\\parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader.read\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;32mpandas\\_libs\\parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader._read_rows\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;32mpandas\\_libs\\parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader._convert_column_data\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;32mpandas\\_libs\\parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader._convert_tokens\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;32mpandas\\_libs\\parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader._convert_with_dtype\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\pandas\\core\\dtypes\\common.py\u001b[0m in \u001b[0;36mis_categorical_dtype\u001b[1;34m(arr_or_dtype)\u001b[0m\n\u001b[0;32m    540\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    541\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 542\u001b[1;33m \u001b[1;32mdef\u001b[0m \u001b[0mis_categorical_dtype\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0marr_or_dtype\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m->\u001b[0m \u001b[0mbool\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    543\u001b[0m     \"\"\"\n\u001b[0;32m    544\u001b[0m     \u001b[0mCheck\u001b[0m \u001b[0mwhether\u001b[0m \u001b[0man\u001b[0m \u001b[0marray\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0mlike\u001b[0m \u001b[1;32mor\u001b[0m \u001b[0mdtype\u001b[0m \u001b[1;32mis\u001b[0m \u001b[0mof\u001b[0m \u001b[0mthe\u001b[0m \u001b[0mCategorical\u001b[0m \u001b[0mdtype\u001b[0m\u001b[1;33m.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "count = 1\n",
    "for chunk in pd.read_csv(path, compression='gzip',  chunksize=200000,low_memory=False):\n",
    "    temp = chunk\n",
    "    p = \"openCorporate\\\\companiesOC\" + str(count) +\".csv\"\n",
    "    print(p)\n",
    "    temp.to_csv(p)\n",
    "    count += 1\n",
    "    #break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "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_number</th>\n",
       "      <th>jurisdiction_code</th>\n",
       "      <th>name</th>\n",
       "      <th>normalised_name</th>\n",
       "      <th>company_type</th>\n",
       "      <th>nonprofit</th>\n",
       "      <th>current_status</th>\n",
       "      <th>incorporation_date</th>\n",
       "      <th>dissolution_date</th>\n",
       "      <th>branch</th>\n",
       "      <th>...</th>\n",
       "      <th>registered_address.postal_code</th>\n",
       "      <th>registered_address.country</th>\n",
       "      <th>registered_address.in_full</th>\n",
       "      <th>home_jurisdiction_code</th>\n",
       "      <th>home_jurisdiction_company_number</th>\n",
       "      <th>industry_code_uids</th>\n",
       "      <th>latest_accounts_date</th>\n",
       "      <th>latest_accounts_cash</th>\n",
       "      <th>latest_accounts_assets</th>\n",
       "      <th>latest_accounts_liabilities</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>,,</td>\n",
       "      <td>us_mo</td>\n",
       "      <td>Lewis Structures, Inc.</td>\n",
       "      <td>lewis structures incorporated</td>\n",
       "      <td>Gen. Business - For Profit</td>\n",
       "      <td>False</td>\n",
       "      <td>Non Qualified</td>\n",
       "      <td>2016-01-14</td>\n",
       "      <td>NaN</td>\n",
       "      <td>F</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>United States</td>\n",
       "      <td>13500 N. Rancho Vistoso Blvd. Apt# 356\\nTucson...</td>\n",
       "      <td>us_az</td>\n",
       "      <td>20540849</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>,-</td>\n",
       "      <td>us_mo</td>\n",
       "      <td>Site 10.01, Inc.</td>\n",
       "      <td>site 10 01 incorporated</td>\n",
       "      <td>Gen. Business - For Profit</td>\n",
       "      <td>False</td>\n",
       "      <td>Non Qualified</td>\n",
       "      <td>2016-07-25</td>\n",
       "      <td>NaN</td>\n",
       "      <td>F</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>United States</td>\n",
       "      <td>120 South Central Ave\\nClayton, MO 63105, Unit...</td>\n",
       "      <td>us_de</td>\n",
       "      <td>6106874</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>,</td>\n",
       "      <td>us_mo</td>\n",
       "      <td>BHM Healthcare Solutions, Inc.</td>\n",
       "      <td>bhm healthcare solutions incorporated</td>\n",
       "      <td>Gen. Business - For Profit</td>\n",
       "      <td>False</td>\n",
       "      <td>Non Qualified</td>\n",
       "      <td>2015-12-31</td>\n",
       "      <td>NaN</td>\n",
       "      <td>F</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>United States</td>\n",
       "      <td>1980 Concourse Drive\\nSt. Louis, MO 63146, Uni...</td>\n",
       "      <td>us_fl</td>\n",
       "      <td>P15000098295</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0000000000000</td>\n",
       "      <td>th</td>\n",
       "      <td>กกก</td>\n",
       "      <td>กกก</td>\n",
       "      <td>Trade Association (สมาคมการค้า)</td>\n",
       "      <td>False</td>\n",
       "      <td>Process (ยังดำเนินกิจการอยู่)</td>\n",
       "      <td>2016-11-08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Thailand</td>\n",
       "      <td>เลขที่ 111, Thailand</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>00000000000191</td>\n",
       "      <td>br</td>\n",
       "      <td>BANCO DO BRASIL SA</td>\n",
       "      <td>banco do brasil sa</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 42 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   company_number jurisdiction_code                            name  \\\n",
       "0              ,,             us_mo          Lewis Structures, Inc.   \n",
       "1              ,-             us_mo                Site 10.01, Inc.   \n",
       "2               ,             us_mo  BHM Healthcare Solutions, Inc.   \n",
       "3   0000000000000                th                             กกก   \n",
       "4  00000000000191                br              BANCO DO BRASIL SA   \n",
       "\n",
       "                         normalised_name                     company_type  \\\n",
       "0          lewis structures incorporated       Gen. Business - For Profit   \n",
       "1                site 10 01 incorporated       Gen. Business - For Profit   \n",
       "2  bhm healthcare solutions incorporated       Gen. Business - For Profit   \n",
       "3                                    กกก  Trade Association (สมาคมการค้า)   \n",
       "4                     banco do brasil sa                              NaN   \n",
       "\n",
       "   nonprofit                 current_status incorporation_date  \\\n",
       "0      False                  Non Qualified         2016-01-14   \n",
       "1      False                  Non Qualified         2016-07-25   \n",
       "2      False                  Non Qualified         2015-12-31   \n",
       "3      False  Process (ยังดำเนินกิจการอยู่)         2016-11-08   \n",
       "4      False                            NaN                NaN   \n",
       "\n",
       "  dissolution_date branch  ...  registered_address.postal_code  \\\n",
       "0              NaN      F  ...                             NaN   \n",
       "1              NaN      F  ...                             NaN   \n",
       "2              NaN      F  ...                             NaN   \n",
       "3              NaN    NaN  ...                             NaN   \n",
       "4              NaN    NaN  ...                             NaN   \n",
       "\n",
       "  registered_address.country  \\\n",
       "0              United States   \n",
       "1              United States   \n",
       "2              United States   \n",
       "3                   Thailand   \n",
       "4                        NaN   \n",
       "\n",
       "                          registered_address.in_full home_jurisdiction_code  \\\n",
       "0  13500 N. Rancho Vistoso Blvd. Apt# 356\\nTucson...                  us_az   \n",
       "1  120 South Central Ave\\nClayton, MO 63105, Unit...                  us_de   \n",
       "2  1980 Concourse Drive\\nSt. Louis, MO 63146, Uni...                  us_fl   \n",
       "3                               เลขที่ 111, Thailand                    NaN   \n",
       "4                                                NaN                    NaN   \n",
       "\n",
       "   home_jurisdiction_company_number industry_code_uids latest_accounts_date  \\\n",
       "0                          20540849                NaN                  NaN   \n",
       "1                           6106874                NaN                  NaN   \n",
       "2                      P15000098295                NaN                  NaN   \n",
       "3                               NaN                NaN                  NaN   \n",
       "4                               NaN                NaN                  NaN   \n",
       "\n",
       "  latest_accounts_cash latest_accounts_assets latest_accounts_liabilities  \n",
       "0                  NaN                    NaN                         NaN  \n",
       "1                  NaN                    NaN                         NaN  \n",
       "2                  NaN                    NaN                         NaN  \n",
       "3                  NaN                    NaN                         NaN  \n",
       "4                  NaN                    NaN                         NaN  \n",
       "\n",
       "[5 rows x 42 columns]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "temp.to_csv('temp.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "ename": "ParserError",
     "evalue": "Error tokenizing data. C error: Calling read(nbytes) on source failed. Try engine='python'.",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mParserError\u001b[0m                               Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-18-e94d42cb5fc7>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mpd\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mread_csv\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mpath\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcompression\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'gzip'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\pandas\\io\\parsers.py\u001b[0m in \u001b[0;36mparser_f\u001b[1;34m(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, squeeze, prefix, mangle_dupe_cols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, skipfooter, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, dayfirst, cache_dates, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, doublequote, escapechar, comment, encoding, dialect, error_bad_lines, warn_bad_lines, delim_whitespace, low_memory, memory_map, float_precision)\u001b[0m\n\u001b[0;32m    674\u001b[0m         )\n\u001b[0;32m    675\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 676\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0m_read\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkwds\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    677\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    678\u001b[0m     \u001b[0mparser_f\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__name__\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mname\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\pandas\\io\\parsers.py\u001b[0m in \u001b[0;36m_read\u001b[1;34m(filepath_or_buffer, kwds)\u001b[0m\n\u001b[0;32m    452\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    453\u001b[0m     \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 454\u001b[1;33m         \u001b[0mdata\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mparser\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mread\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mnrows\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    455\u001b[0m     \u001b[1;32mfinally\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    456\u001b[0m         \u001b[0mparser\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mclose\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\pandas\\io\\parsers.py\u001b[0m in \u001b[0;36mread\u001b[1;34m(self, nrows)\u001b[0m\n\u001b[0;32m   1131\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mread\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mnrows\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1132\u001b[0m         \u001b[0mnrows\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0m_validate_integer\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"nrows\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mnrows\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1133\u001b[1;33m         \u001b[0mret\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mread\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mnrows\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1134\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1135\u001b[0m         \u001b[1;31m# May alter columns / col_dict\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\pandas\\io\\parsers.py\u001b[0m in \u001b[0;36mread\u001b[1;34m(self, nrows)\u001b[0m\n\u001b[0;32m   2035\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mread\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mnrows\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2036\u001b[0m         \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 2037\u001b[1;33m             \u001b[0mdata\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_reader\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mread\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mnrows\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   2038\u001b[0m         \u001b[1;32mexcept\u001b[0m \u001b[0mStopIteration\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2039\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_first_chunk\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mpandas\\_libs\\parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader.read\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;32mpandas\\_libs\\parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader._read_low_memory\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;32mpandas\\_libs\\parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader._read_rows\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;32mpandas\\_libs\\parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader._tokenize_rows\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;32mpandas\\_libs\\parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.raise_parser_error\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;31mParserError\u001b[0m: Error tokenizing data. C error: Calling read(nbytes) on source failed. Try engine='python'."
     ]
    }
   ],
   "source": [
    "pd.read_csv(path, compression='gzip')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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