Pandas_Dataframe_Tutorial_Example_Code.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Python Pandas Dataframe Tutorial\n",
    "This is the example code for the [Pandas Dataframe Tutorial](https://www.marsja.se/pandas-dataframe-read-csv-excel-subset) on my blog."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Import Pandas\n",
    "First, we import pandas and then we can se what version of pandas that we are using:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.25.1\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "print(pd.__version__)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Pandas Create Dataframe Example\n",
    "First, we are going to use Pandas to create a dataframe from a dictionary of lists:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "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>Condition</th>\n",
       "      <th>Subject_ID</th>\n",
       "      <th>Trial</th>\n",
       "      <th>Group</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Affect</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Control</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Affect</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Control</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Affect</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Control</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>Control</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>Control</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Condition  Subject_ID  Trial    Group\n",
       "0    Affect           1      1  Control\n",
       "1    Affect           1      2  Control\n",
       "2    Affect           1      3  Control\n",
       "3   Neutral           1      4  Control\n",
       "4   Neutral           1      5  Control"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create some variables\n",
    "trials = [1, 2, 3, 4, 5, 6]\n",
    "subj_id = [1]*6\n",
    "group = ['Control']*6\n",
    "condition = ['Affect']*3 + ['Neutral']*3\n",
    "\n",
    "# Create a dictionairy\n",
    "data = {'Condition':condition, 'Subject_ID':subj_id,\n",
    "        'Trial':trials, 'Group':group}\n",
    "\n",
    "# Create the dataframe\n",
    "df = pd.DataFrame(data)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Pandas Read Excel Example\n",
    "In the next code chunk we will read data from an Excel file. First we create a string variable pointing to an URL with the xlsx file we are going to load into a dataframe. Next, we load that using Pandas read_excel method."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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>Year</th>\n",
       "      <th>EventType</th>\n",
       "      <th>Actor1</th>\n",
       "      <th>Actor2</th>\n",
       "      <th>Country</th>\n",
       "      <th>Region</th>\n",
       "      <th>Location</th>\n",
       "      <th>ConflictLat</th>\n",
       "      <th>ConflictLong</th>\n",
       "      <th>StationID</th>\n",
       "      <th>YrMoDy</th>\n",
       "      <th>MaxTemp</th>\n",
       "      <th>StationName</th>\n",
       "      <th>StationLong</th>\n",
       "      <th>StationLat</th>\n",
       "      <th>TempCat</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>2005</td>\n",
       "      <td>Riots</td>\n",
       "      <td>Protesters (Algeria)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Algeria</td>\n",
       "      <td>Chlef</td>\n",
       "      <td>Sidi Ammar</td>\n",
       "      <td>36.47</td>\n",
       "      <td>1.45</td>\n",
       "      <td>604300</td>\n",
       "      <td>20050125</td>\n",
       "      <td>35.79</td>\n",
       "      <td>MILIANA</td>\n",
       "      <td>2.23</td>\n",
       "      <td>36.29</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>2003</td>\n",
       "      <td>Riots</td>\n",
       "      <td>Protesters (Algeria)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Algeria</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Tadjenanet</td>\n",
       "      <td>36.11</td>\n",
       "      <td>5.98</td>\n",
       "      <td>604680</td>\n",
       "      <td>20030201</td>\n",
       "      <td>38.50</td>\n",
       "      <td>BATNA</td>\n",
       "      <td>6.31</td>\n",
       "      <td>35.75</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>2002</td>\n",
       "      <td>Battles</td>\n",
       "      <td>Military Forces of Ethiopia (1991-)</td>\n",
       "      <td>ONLF: Ogaden National Liberation Front</td>\n",
       "      <td>Ethiopia</td>\n",
       "      <td>Degeh Bur</td>\n",
       "      <td>Afweyne</td>\n",
       "      <td>9.38</td>\n",
       "      <td>43.06</td>\n",
       "      <td>696754</td>\n",
       "      <td>20020224</td>\n",
       "      <td>39.20</td>\n",
       "      <td>CAMP LEMONIER</td>\n",
       "      <td>43.15</td>\n",
       "      <td>11.55</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>2003</td>\n",
       "      <td>Riots</td>\n",
       "      <td>Protesters (Algeria)</td>\n",
       "      <td>Police Forces of Algeria (1999-)</td>\n",
       "      <td>Algeria</td>\n",
       "      <td>Bordj Bou Arreridj</td>\n",
       "      <td>Bordj Bou Arerridj</td>\n",
       "      <td>36.07</td>\n",
       "      <td>4.77</td>\n",
       "      <td>604440</td>\n",
       "      <td>20030217</td>\n",
       "      <td>39.40</td>\n",
       "      <td>BORDJ-BOU-ARRERIDJ</td>\n",
       "      <td>4.76</td>\n",
       "      <td>36.06</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>1999</td>\n",
       "      <td>Violence against civilians</td>\n",
       "      <td>GIA: Armed Islamic Group of Algeria</td>\n",
       "      <td>Civilians (Algeria)</td>\n",
       "      <td>Algeria</td>\n",
       "      <td>Relizane</td>\n",
       "      <td>Relizane</td>\n",
       "      <td>35.74</td>\n",
       "      <td>0.55</td>\n",
       "      <td>605060</td>\n",
       "      <td>19991217</td>\n",
       "      <td>39.90</td>\n",
       "      <td>MASCARA-MATEMORE</td>\n",
       "      <td>0.30</td>\n",
       "      <td>35.59</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year                   EventType                               Actor1  \\\n",
       "0  2005                       Riots                 Protesters (Algeria)   \n",
       "1  2003                       Riots                 Protesters (Algeria)   \n",
       "2  2002                     Battles  Military Forces of Ethiopia (1991-)   \n",
       "3  2003                       Riots                 Protesters (Algeria)   \n",
       "4  1999  Violence against civilians  GIA: Armed Islamic Group of Algeria   \n",
       "\n",
       "                                   Actor2   Country              Region  \\\n",
       "0                                     NaN   Algeria               Chlef   \n",
       "1                                     NaN   Algeria                 NaN   \n",
       "2  ONLF: Ogaden National Liberation Front  Ethiopia           Degeh Bur   \n",
       "3        Police Forces of Algeria (1999-)   Algeria  Bordj Bou Arreridj   \n",
       "4                     Civilians (Algeria)   Algeria            Relizane   \n",
       "\n",
       "             Location  ConflictLat  ConflictLong  StationID    YrMoDy  \\\n",
       "0          Sidi Ammar        36.47          1.45     604300  20050125   \n",
       "1          Tadjenanet        36.11          5.98     604680  20030201   \n",
       "2             Afweyne         9.38         43.06     696754  20020224   \n",
       "3  Bordj Bou Arerridj        36.07          4.77     604440  20030217   \n",
       "4            Relizane        35.74          0.55     605060  19991217   \n",
       "\n",
       "   MaxTemp         StationName  StationLong  StationLat TempCat  \n",
       "0    35.79             MILIANA         2.23       36.29       C  \n",
       "1    38.50               BATNA         6.31       35.75       C  \n",
       "2    39.20       CAMP LEMONIER        43.15       11.55       C  \n",
       "3    39.40  BORDJ-BOU-ARRERIDJ         4.76       36.06       C  \n",
       "4    39.90    MASCARA-MATEMORE         0.30       35.59       C  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Load a XLSX file from a URL\n",
    "xlsx_source = 'http://ww2.amstat.org/publications' \\\n",
    "              '/jse/v20n3/delzell/conflictdata.xlsx'\n",
    "# Reading the excel file to a dataframe.\n",
    "# Note, there's only one sheet in the example file\n",
    "df = pd.read_excel(xlsx_source, sheet_name='conflictdata')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Second Pandas Read XLSX Example\n",
    "How to set column names:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Col1</th>\n",
       "      <th>Col2</th>\n",
       "      <th>Col3</th>\n",
       "      <th>Col4</th>\n",
       "      <th>Col5</th>\n",
       "      <th>Col6</th>\n",
       "      <th>Col7</th>\n",
       "      <th>Col8</th>\n",
       "      <th>Col9</th>\n",
       "      <th>Col10</th>\n",
       "      <th>Col11</th>\n",
       "      <th>Col12</th>\n",
       "      <th>Col13</th>\n",
       "      <th>Col14</th>\n",
       "      <th>Col15</th>\n",
       "      <th>Col16</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>2005</td>\n",
       "      <td>Riots</td>\n",
       "      <td>Protesters (Algeria)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Algeria</td>\n",
       "      <td>Chlef</td>\n",
       "      <td>Sidi Ammar</td>\n",
       "      <td>36.47</td>\n",
       "      <td>1.45</td>\n",
       "      <td>604300</td>\n",
       "      <td>20050125</td>\n",
       "      <td>35.79</td>\n",
       "      <td>MILIANA</td>\n",
       "      <td>2.23</td>\n",
       "      <td>36.29</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>2003</td>\n",
       "      <td>Riots</td>\n",
       "      <td>Protesters (Algeria)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Algeria</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Tadjenanet</td>\n",
       "      <td>36.11</td>\n",
       "      <td>5.98</td>\n",
       "      <td>604680</td>\n",
       "      <td>20030201</td>\n",
       "      <td>38.50</td>\n",
       "      <td>BATNA</td>\n",
       "      <td>6.31</td>\n",
       "      <td>35.75</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>2002</td>\n",
       "      <td>Battles</td>\n",
       "      <td>Military Forces of Ethiopia (1991-)</td>\n",
       "      <td>ONLF: Ogaden National Liberation Front</td>\n",
       "      <td>Ethiopia</td>\n",
       "      <td>Degeh Bur</td>\n",
       "      <td>Afweyne</td>\n",
       "      <td>9.38</td>\n",
       "      <td>43.06</td>\n",
       "      <td>696754</td>\n",
       "      <td>20020224</td>\n",
       "      <td>39.20</td>\n",
       "      <td>CAMP LEMONIER</td>\n",
       "      <td>43.15</td>\n",
       "      <td>11.55</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>2003</td>\n",
       "      <td>Riots</td>\n",
       "      <td>Protesters (Algeria)</td>\n",
       "      <td>Police Forces of Algeria (1999-)</td>\n",
       "      <td>Algeria</td>\n",
       "      <td>Bordj Bou Arreridj</td>\n",
       "      <td>Bordj Bou Arerridj</td>\n",
       "      <td>36.07</td>\n",
       "      <td>4.77</td>\n",
       "      <td>604440</td>\n",
       "      <td>20030217</td>\n",
       "      <td>39.40</td>\n",
       "      <td>BORDJ-BOU-ARRERIDJ</td>\n",
       "      <td>4.76</td>\n",
       "      <td>36.06</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>1999</td>\n",
       "      <td>Violence against civilians</td>\n",
       "      <td>GIA: Armed Islamic Group of Algeria</td>\n",
       "      <td>Civilians (Algeria)</td>\n",
       "      <td>Algeria</td>\n",
       "      <td>Relizane</td>\n",
       "      <td>Relizane</td>\n",
       "      <td>35.74</td>\n",
       "      <td>0.55</td>\n",
       "      <td>605060</td>\n",
       "      <td>19991217</td>\n",
       "      <td>39.90</td>\n",
       "      <td>MASCARA-MATEMORE</td>\n",
       "      <td>0.30</td>\n",
       "      <td>35.59</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Col1                        Col2                                 Col3  \\\n",
       "0  2005                       Riots                 Protesters (Algeria)   \n",
       "1  2003                       Riots                 Protesters (Algeria)   \n",
       "2  2002                     Battles  Military Forces of Ethiopia (1991-)   \n",
       "3  2003                       Riots                 Protesters (Algeria)   \n",
       "4  1999  Violence against civilians  GIA: Armed Islamic Group of Algeria   \n",
       "\n",
       "                                     Col4      Col5                Col6  \\\n",
       "0                                     NaN   Algeria               Chlef   \n",
       "1                                     NaN   Algeria                 NaN   \n",
       "2  ONLF: Ogaden National Liberation Front  Ethiopia           Degeh Bur   \n",
       "3        Police Forces of Algeria (1999-)   Algeria  Bordj Bou Arreridj   \n",
       "4                     Civilians (Algeria)   Algeria            Relizane   \n",
       "\n",
       "                 Col7   Col8   Col9   Col10     Col11  Col12  \\\n",
       "0          Sidi Ammar  36.47   1.45  604300  20050125  35.79   \n",
       "1          Tadjenanet  36.11   5.98  604680  20030201  38.50   \n",
       "2             Afweyne   9.38  43.06  696754  20020224  39.20   \n",
       "3  Bordj Bou Arerridj  36.07   4.77  604440  20030217  39.40   \n",
       "4            Relizane  35.74   0.55  605060  19991217  39.90   \n",
       "\n",
       "                Col13  Col14  Col15 Col16  \n",
       "0             MILIANA   2.23  36.29     C  \n",
       "1               BATNA   6.31  35.75     C  \n",
       "2       CAMP LEMONIER  43.15  11.55     C  \n",
       "3  BORDJ-BOU-ARRERIDJ   4.76  36.06     C  \n",
       "4    MASCARA-MATEMORE   0.30  35.59     C  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xlsx_source = 'http://ww2.amstat.org/publications' \\\n",
    "              '/jse/v20n3/delzell/conflictdata.xlsx'\n",
    "\n",
    "# Creating a list of column names\n",
    "col_names = ['Col' + str(i) for i in range (1, 17)]\n",
    "\n",
    "# Reading the excel file\n",
    "df = pd.read_excel(xlsx_source, sheet_name='conflictdata',\n",
    "                   header=None, names=col_names, skiprows=[0])\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Write Excel File Example\n",
    "Next we learn how to write to an Excel file using to_excel (remove the '#' to run the code)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# df.to_excel('newfilename.xlsx', sheet_name='NewColNames', index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Read CSV using Pandas Python"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>t42</th>\n",
       "      <th>t54</th>\n",
       "      <th>t45</th>\n",
       "      <th>t46</th>\n",
       "      <th>t23</th>\n",
       "      <th>t24</th>\n",
       "      <th>t27</th>\n",
       "      <th>t10</th>\n",
       "      <th>t51</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>t42</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.554</td>\n",
       "      <td>0.227</td>\n",
       "      <td>0.189</td>\n",
       "      <td>0.461</td>\n",
       "      <td>0.506</td>\n",
       "      <td>0.408</td>\n",
       "      <td>0.280</td>\n",
       "      <td>0.241</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>t54</td>\n",
       "      <td>0.554</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.296</td>\n",
       "      <td>0.219</td>\n",
       "      <td>0.479</td>\n",
       "      <td>0.530</td>\n",
       "      <td>0.425</td>\n",
       "      <td>0.311</td>\n",
       "      <td>0.311</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>t45</td>\n",
       "      <td>0.227</td>\n",
       "      <td>0.296</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.769</td>\n",
       "      <td>0.237</td>\n",
       "      <td>0.243</td>\n",
       "      <td>0.304</td>\n",
       "      <td>0.718</td>\n",
       "      <td>0.730</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>t46</td>\n",
       "      <td>0.189</td>\n",
       "      <td>0.219</td>\n",
       "      <td>0.769</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.212</td>\n",
       "      <td>0.226</td>\n",
       "      <td>0.291</td>\n",
       "      <td>0.681</td>\n",
       "      <td>0.661</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>t23</td>\n",
       "      <td>0.461</td>\n",
       "      <td>0.479</td>\n",
       "      <td>0.237</td>\n",
       "      <td>0.212</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.520</td>\n",
       "      <td>0.514</td>\n",
       "      <td>0.313</td>\n",
       "      <td>0.245</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Unnamed: 0    t42    t54    t45    t46    t23    t24    t27    t10    t51\n",
       "0        t42  1.000  0.554  0.227  0.189  0.461  0.506  0.408  0.280  0.241\n",
       "1        t54  0.554  1.000  0.296  0.219  0.479  0.530  0.425  0.311  0.311\n",
       "2        t45  0.227  0.296  1.000  0.769  0.237  0.243  0.304  0.718  0.730\n",
       "3        t46  0.189  0.219  0.769  1.000  0.212  0.226  0.291  0.681  0.661\n",
       "4        t23  0.461  0.479  0.237  0.212  1.000  0.520  0.514  0.313  0.245"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('https://vincentarelbundock.github.io/' \\\n",
    "                 'Rdatasets/csv/psych/Tucker.csv', sep=',')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Pandas to_csv Example\n",
    "We can also write to a csv file using Pandas to_csv (remember to remove '#' to run the code)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# df.to_csv('newfilename.csv', sep=';', index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Working With Pandas Dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    .dataframe tbody tr th {\n",
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       "    }\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>Unnamed: 0</th>\n",
       "      <th>id</th>\n",
       "      <th>days</th>\n",
       "      <th>duration</th>\n",
       "      <th>sex</th>\n",
       "      <th>age</th>\n",
       "      <th>piq</th>\n",
       "      <th>viq</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3358</td>\n",
       "      <td>30</td>\n",
       "      <td>4</td>\n",
       "      <td>Male</td>\n",
       "      <td>20.67077</td>\n",
       "      <td>87</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3535</td>\n",
       "      <td>16</td>\n",
       "      <td>17</td>\n",
       "      <td>Male</td>\n",
       "      <td>55.28816</td>\n",
       "      <td>95</td>\n",
       "      <td>77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3547</td>\n",
       "      <td>40</td>\n",
       "      <td>1</td>\n",
       "      <td>Male</td>\n",
       "      <td>55.91513</td>\n",
       "      <td>95</td>\n",
       "      <td>116</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>3592</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Male</td>\n",
       "      <td>61.66461</td>\n",
       "      <td>59</td>\n",
       "      <td>73</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0    id  days  duration   sex       age  piq  viq\n",
       "0           1  3358    30         4  Male  20.67077   87   89\n",
       "1           2  3535    16        17  Male  55.28816   95   77\n",
       "2           3  3547    40         1  Male  55.91513   95  116\n",
       "3           4  3592    13        10  Male  61.66461   59   73"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('https://vincentarelbundock.github.io/' \\\n",
    "    'Rdatasets/csv/carData/Wong.csv', sep=',')\n",
    "df.head(4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "\n",
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       "        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>Unnamed: 0</th>\n",
       "      <th>id</th>\n",
       "      <th>days</th>\n",
       "      <th>duration</th>\n",
       "      <th>sex</th>\n",
       "      <th>age</th>\n",
       "      <th>piq</th>\n",
       "      <th>viq</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>326</td>\n",
       "      <td>327</td>\n",
       "      <td>2600</td>\n",
       "      <td>3337</td>\n",
       "      <td>9</td>\n",
       "      <td>Male</td>\n",
       "      <td>43.939770</td>\n",
       "      <td>101</td>\n",
       "      <td>84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>327</td>\n",
       "      <td>328</td>\n",
       "      <td>3835</td>\n",
       "      <td>4933</td>\n",
       "      <td>14</td>\n",
       "      <td>Male</td>\n",
       "      <td>25.993160</td>\n",
       "      <td>91</td>\n",
       "      <td>88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>328</td>\n",
       "      <td>329</td>\n",
       "      <td>2773</td>\n",
       "      <td>7631</td>\n",
       "      <td>42</td>\n",
       "      <td>Male</td>\n",
       "      <td>6.513347</td>\n",
       "      <td>88</td>\n",
       "      <td>103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>329</td>\n",
       "      <td>330</td>\n",
       "      <td>5142</td>\n",
       "      <td>11628</td>\n",
       "      <td>57</td>\n",
       "      <td>Male</td>\n",
       "      <td>16.432580</td>\n",
       "      <td>101</td>\n",
       "      <td>95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>330</td>\n",
       "      <td>331</td>\n",
       "      <td>5964</td>\n",
       "      <td>11038</td>\n",
       "      <td>0</td>\n",
       "      <td>Male</td>\n",
       "      <td>12.544830</td>\n",
       "      <td>71</td>\n",
       "      <td>73</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Unnamed: 0    id   days  duration   sex        age  piq  viq\n",
       "326         327  2600   3337         9  Male  43.939770  101   84\n",
       "327         328  3835   4933        14  Male  25.993160   91   88\n",
       "328         329  2773   7631        42  Male   6.513347   88  103\n",
       "329         330  5142  11628        57  Male  16.432580  101   95\n",
       "330         331  5964  11038         0  Male  12.544830   71   73"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    87\n",
       "1    95\n",
       "2    95\n",
       "3    59\n",
       "Name: piq, dtype: int64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "piq = df.piq\n",
    "piq[0:4]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Pandas Get all Column Names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Unnamed: 0', 'id', 'days', 'duration', 'sex', 'age', 'piq', 'viq'], dtype='object')"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.keys()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### How to Add Column to Dataframe Pandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    }\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>Unnamed: 0</th>\n",
       "      <th>id</th>\n",
       "      <th>days</th>\n",
       "      <th>duration</th>\n",
       "      <th>sex</th>\n",
       "      <th>age</th>\n",
       "      <th>piq</th>\n",
       "      <th>viq</th>\n",
       "      <th>iq</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3358</td>\n",
       "      <td>30</td>\n",
       "      <td>4</td>\n",
       "      <td>Male</td>\n",
       "      <td>20.67077</td>\n",
       "      <td>87</td>\n",
       "      <td>89</td>\n",
       "      <td>88.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3535</td>\n",
       "      <td>16</td>\n",
       "      <td>17</td>\n",
       "      <td>Male</td>\n",
       "      <td>55.28816</td>\n",
       "      <td>95</td>\n",
       "      <td>77</td>\n",
       "      <td>86.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3547</td>\n",
       "      <td>40</td>\n",
       "      <td>1</td>\n",
       "      <td>Male</td>\n",
       "      <td>55.91513</td>\n",
       "      <td>95</td>\n",
       "      <td>116</td>\n",
       "      <td>105.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>3592</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Male</td>\n",
       "      <td>61.66461</td>\n",
       "      <td>59</td>\n",
       "      <td>73</td>\n",
       "      <td>66.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>3728</td>\n",
       "      <td>19</td>\n",
       "      <td>6</td>\n",
       "      <td>Male</td>\n",
       "      <td>30.12731</td>\n",
       "      <td>67</td>\n",
       "      <td>73</td>\n",
       "      <td>70.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0    id  days  duration   sex       age  piq  viq     iq\n",
       "0           1  3358    30         4  Male  20.67077   87   89   88.0\n",
       "1           2  3535    16        17  Male  55.28816   95   77   86.0\n",
       "2           3  3547    40         1  Male  55.91513   95  116  105.5\n",
       "3           4  3592    13        10  Male  61.66461   59   73   66.0\n",
       "4           5  3728    19         6  Male  30.12731   67   73   70.0"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['iq'] = (df['piq'] + df['viq'])/2\n",
    "# df['iq'] = df[['piq', 'viq']].mean(axis=1) # same result as above\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Add an Empty Column to Pandas Dataframe:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['NewCol'] = ''"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### How to Drop a Column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop(['NewCol', 'Unnamed: 0'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Pandas Subset Guide"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>days</th>\n",
       "      <th>duration</th>\n",
       "      <th>sex</th>\n",
       "      <th>age</th>\n",
       "      <th>piq</th>\n",
       "      <th>viq</th>\n",
       "      <th>iq</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>3358</td>\n",
       "      <td>30</td>\n",
       "      <td>4</td>\n",
       "      <td>Male</td>\n",
       "      <td>20.67077</td>\n",
       "      <td>87</td>\n",
       "      <td>89</td>\n",
       "      <td>88.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>3535</td>\n",
       "      <td>16</td>\n",
       "      <td>17</td>\n",
       "      <td>Male</td>\n",
       "      <td>55.28816</td>\n",
       "      <td>95</td>\n",
       "      <td>77</td>\n",
       "      <td>86.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>3547</td>\n",
       "      <td>40</td>\n",
       "      <td>1</td>\n",
       "      <td>Male</td>\n",
       "      <td>55.91513</td>\n",
       "      <td>95</td>\n",
       "      <td>116</td>\n",
       "      <td>105.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>3808</td>\n",
       "      <td>31</td>\n",
       "      <td>7</td>\n",
       "      <td>Male</td>\n",
       "      <td>28.26831</td>\n",
       "      <td>91</td>\n",
       "      <td>110</td>\n",
       "      <td>100.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     id  days  duration   sex       age  piq  viq     iq\n",
       "0  3358    30         4  Male  20.67077   87   89   88.0\n",
       "1  3535    16        17  Male  55.28816   95   77   86.0\n",
       "2  3547    40         1  Male  55.91513   95  116  105.5\n",
       "7  3808    31         7  Male  28.26831   91  110  100.5"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_piq = df.query('piq > 80')\n",
    "df_piq.head(4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "df_piq.piq.min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Male'], dtype=object)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_males = df[df['sex'] == 'Male']\n",
    "df_males.sex.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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>piq</th>\n",
       "      <th>viq</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>95</td>\n",
       "      <td>77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>95</td>\n",
       "      <td>116</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>59</td>\n",
       "      <td>73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>76</td>\n",
       "      <td>69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>13</td>\n",
       "      <td>82</td>\n",
       "      <td>85</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    piq  viq\n",
       "1    95   77\n",
       "2    95  116\n",
       "3    59   73\n",
       "5    76   69\n",
       "13   82   85"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.query('age >= 40 | age < 14')[['piq', 'viq']].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Random Sample of Rows in Pandas Dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_random = df.sample(n=25)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## How to Group Data using Pandas Dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "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>age</th>\n",
       "      <th>piq</th>\n",
       "      <th>viq</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sex</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>Female</td>\n",
       "      <td>30.865025</td>\n",
       "      <td>89.183099</td>\n",
       "      <td>94.352113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Male</td>\n",
       "      <td>32.123035</td>\n",
       "      <td>87.111538</td>\n",
       "      <td>95.130769</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              age        piq        viq\n",
       "sex                                    \n",
       "Female  30.865025  89.183099  94.352113\n",
       "Male    32.123035  87.111538  95.130769"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sex = df.groupby('sex')\n",
    "df_sex[['age', 'piq', 'viq']].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "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 tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"8\" halign=\"left\">iq</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sex</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>Female</td>\n",
       "      <td>71.0</td>\n",
       "      <td>91.767606</td>\n",
       "      <td>14.763573</td>\n",
       "      <td>62.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>100.750</td>\n",
       "      <td>125.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Male</td>\n",
       "      <td>260.0</td>\n",
       "      <td>91.121154</td>\n",
       "      <td>12.846575</td>\n",
       "      <td>61.0</td>\n",
       "      <td>82.5</td>\n",
       "      <td>90.0</td>\n",
       "      <td>99.125</td>\n",
       "      <td>126.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           iq                                                        \n",
       "        count       mean        std   min   25%   50%      75%    max\n",
       "sex                                                                  \n",
       "Female   71.0  91.767606  14.763573  62.0  81.0  91.0  100.750  125.0\n",
       "Male    260.0  91.121154  12.846575  61.0  82.5  90.0   99.125  126.5"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sex[['iq']].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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