Pandas/Read, Write Files.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Read, Write Files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df = pd.DataFrame(data=[[2,3],\n",
    "                        [\"Hello\", \"World\"],\n",
    "                        [34, True]],\n",
    "                 index = ['R1', 'R2', 'R3'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## .csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df.to_csv('samplecsv.csv') #Write to .csv file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df1 = pd.read_csv('samplecsv.csv') #Read .csv file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>R1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>R2</td>\n",
       "      <td>Hello</td>\n",
       "      <td>World</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>R3</td>\n",
       "      <td>34</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Unnamed: 0      0      1\n",
       "0         R1      2      3\n",
       "1         R2  Hello  World\n",
       "2         R3     34   True"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df1 = pd.read_csv('samplecsv.csv', index_col=0)\n",
    "#0th column is not a particular column, but index column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>R1</th>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R2</th>\n",
       "      <td>Hello</td>\n",
       "      <td>World</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R3</th>\n",
       "      <td>34</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        0      1\n",
       "R1      2      3\n",
       "R2  Hello  World\n",
       "R3     34   True"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## .html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# https://en.wikipedia.org/wiki/The_World%27s_Billionaires"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "list_of_tables = pd.read_html('https://en.wikipedia.org/wiki/The_World%27s_Billionaires')\n",
    "#returns list and not DataFrame\n",
    "#Returns tables of that page"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "list"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(list_of_tables)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "26"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(list_of_tables)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>No.</td>\n",
       "      <td>Name</td>\n",
       "      <td>Net worth (USD)</td>\n",
       "      <td>Age</td>\n",
       "      <td>Nationality</td>\n",
       "      <td>Source(s) of wealth</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7000100000000000000♠1</td>\n",
       "      <td>Gates, BillBill Gates</td>\n",
       "      <td>$86.0 billion</td>\n",
       "      <td>61</td>\n",
       "      <td>United States</td>\n",
       "      <td>Microsoft</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>7000200000000000000♠2</td>\n",
       "      <td>Buffett, WarrenWarren Buffett</td>\n",
       "      <td>$75.6 billion</td>\n",
       "      <td>86</td>\n",
       "      <td>United States</td>\n",
       "      <td>Berkshire Hathaway</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7000300000000000000♠3</td>\n",
       "      <td>Bezos, JeffJeff Bezos</td>\n",
       "      <td>$72.8 billion</td>\n",
       "      <td>53</td>\n",
       "      <td>United States</td>\n",
       "      <td>Amazon.com</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>7000400000000000000♠4</td>\n",
       "      <td>Ortega, AmancioAmancio Ortega</td>\n",
       "      <td>$71.3 billion</td>\n",
       "      <td>80</td>\n",
       "      <td>Spain</td>\n",
       "      <td>Inditex, Zara</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>7000500000000000000♠5</td>\n",
       "      <td>Zuckerberg, MarkMark Zuckerberg</td>\n",
       "      <td>$56.0 billion</td>\n",
       "      <td>32</td>\n",
       "      <td>United States</td>\n",
       "      <td>Facebook</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7000600000000000000♠6</td>\n",
       "      <td>Slim, CarlosCarlos Slim</td>\n",
       "      <td>$54.5 billion</td>\n",
       "      <td>77</td>\n",
       "      <td>Mexico</td>\n",
       "      <td>América Móvil, Grupo Carso</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7000700000000000000♠7</td>\n",
       "      <td>Ellison, LarryLarry Ellison</td>\n",
       "      <td>$52.2 billion</td>\n",
       "      <td>72</td>\n",
       "      <td>United States</td>\n",
       "      <td>Oracle Corporation</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>7000800000000000000♠8</td>\n",
       "      <td>Koch, CharlesCharles Koch</td>\n",
       "      <td>$48.3 billion</td>\n",
       "      <td>81</td>\n",
       "      <td>United States</td>\n",
       "      <td>Koch Industries</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>7000800000000000000♠8</td>\n",
       "      <td>Koch, DavidDavid Koch</td>\n",
       "      <td>$48.3 billion</td>\n",
       "      <td>76</td>\n",
       "      <td>United States</td>\n",
       "      <td>Koch Industries</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>7001100000000000000♠10</td>\n",
       "      <td>Bloomberg, MichaelMichael Bloomberg</td>\n",
       "      <td>$47.5 billion</td>\n",
       "      <td>75</td>\n",
       "      <td>United States</td>\n",
       "      <td>Bloomberg L.P.</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         0                                    1  \\\n",
       "0                      No.                                 Name   \n",
       "1    7000100000000000000♠1                Gates, BillBill Gates   \n",
       "2    7000200000000000000♠2        Buffett, WarrenWarren Buffett   \n",
       "3    7000300000000000000♠3                Bezos, JeffJeff Bezos   \n",
       "4    7000400000000000000♠4        Ortega, AmancioAmancio Ortega   \n",
       "5    7000500000000000000♠5      Zuckerberg, MarkMark Zuckerberg   \n",
       "6    7000600000000000000♠6              Slim, CarlosCarlos Slim   \n",
       "7    7000700000000000000♠7          Ellison, LarryLarry Ellison   \n",
       "8    7000800000000000000♠8            Koch, CharlesCharles Koch   \n",
       "9    7000800000000000000♠8                Koch, DavidDavid Koch   \n",
       "10  7001100000000000000♠10  Bloomberg, MichaelMichael Bloomberg   \n",
       "\n",
       "                  2    3              4                           5  \n",
       "0   Net worth (USD)  Age    Nationality         Source(s) of wealth  \n",
       "1     $86.0 billion   61  United States                   Microsoft  \n",
       "2     $75.6 billion   86  United States          Berkshire Hathaway  \n",
       "3     $72.8 billion   53  United States                  Amazon.com  \n",
       "4     $71.3 billion   80          Spain               Inditex, Zara  \n",
       "5     $56.0 billion   32  United States                    Facebook  \n",
       "6     $54.5 billion   77         Mexico  América Móvil, Grupo Carso  \n",
       "7     $52.2 billion   72  United States          Oracle Corporation  \n",
       "8     $48.3 billion   81  United States             Koch Industries  \n",
       "9     $48.3 billion   76  United States             Koch Industries  \n",
       "10    $47.5 billion   75  United States              Bloomberg L.P.  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list_of_tables[1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## excel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>R1</th>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R2</th>\n",
       "      <td>Hello</td>\n",
       "      <td>World</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R3</th>\n",
       "      <td>34</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        0      1\n",
       "R1      2      3\n",
       "R2  Hello  World\n",
       "R3     34   True"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df.to_excel('sampleExcel.xls') #Write to excel file"
   ]
  }
 ],
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