PandasPivotsPBPython.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# This info is entirely from the following source: http://pbpython.com/pandas-pivot-table-explained.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "        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>Account</th>\n",
       "      <th>Name</th>\n",
       "      <th>Rep</th>\n",
       "      <th>Manager</th>\n",
       "      <th>Product</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>Price</th>\n",
       "      <th>Status</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>714466</td>\n",
       "      <td>Trantow-Barrows</td>\n",
       "      <td>Craig Booker</td>\n",
       "      <td>Debra Henley</td>\n",
       "      <td>CPU</td>\n",
       "      <td>1</td>\n",
       "      <td>30000</td>\n",
       "      <td>presented</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>714466</td>\n",
       "      <td>Trantow-Barrows</td>\n",
       "      <td>Craig Booker</td>\n",
       "      <td>Debra Henley</td>\n",
       "      <td>Software</td>\n",
       "      <td>1</td>\n",
       "      <td>10000</td>\n",
       "      <td>presented</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>714466</td>\n",
       "      <td>Trantow-Barrows</td>\n",
       "      <td>Craig Booker</td>\n",
       "      <td>Debra Henley</td>\n",
       "      <td>Maintenance</td>\n",
       "      <td>2</td>\n",
       "      <td>5000</td>\n",
       "      <td>pending</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>737550</td>\n",
       "      <td>Fritsch, Russel and Anderson</td>\n",
       "      <td>Craig Booker</td>\n",
       "      <td>Debra Henley</td>\n",
       "      <td>CPU</td>\n",
       "      <td>1</td>\n",
       "      <td>35000</td>\n",
       "      <td>declined</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>146832</td>\n",
       "      <td>Kiehn-Spinka</td>\n",
       "      <td>Daniel Hilton</td>\n",
       "      <td>Debra Henley</td>\n",
       "      <td>CPU</td>\n",
       "      <td>2</td>\n",
       "      <td>65000</td>\n",
       "      <td>won</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Account                          Name            Rep       Manager  \\\n",
       "0   714466               Trantow-Barrows   Craig Booker  Debra Henley   \n",
       "1   714466               Trantow-Barrows   Craig Booker  Debra Henley   \n",
       "2   714466               Trantow-Barrows   Craig Booker  Debra Henley   \n",
       "3   737550  Fritsch, Russel and Anderson   Craig Booker  Debra Henley   \n",
       "4   146832                  Kiehn-Spinka  Daniel Hilton  Debra Henley   \n",
       "\n",
       "       Product  Quantity  Price     Status  \n",
       "0          CPU         1  30000  presented  \n",
       "1     Software         1  10000  presented  \n",
       "2  Maintenance         2   5000    pending  \n",
       "3          CPU         1  35000   declined  \n",
       "4          CPU         2  65000        won  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_excel(\"/home/enumtheworld/Downloads/sales-funnel.xlsx\")\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Define status column as a category and set the order we want to view"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[\"Status\"] = df[\"Status\"].astype(\"category\")\n",
    "df[\"Status\"].cat.set_categories([\"won\", \"pending\", \"presented\", \"declined\"], inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>sum</th>\n",
       "      <th>count</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>Price</th>\n",
       "      <th>Price</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Manager</th>\n",
       "      <th>Rep</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">Debra Henley</th>\n",
       "      <th>Craig Booker</th>\n",
       "      <td>80000</td>\n",
       "      <td>4</td>\n",
       "      <td>35000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Daniel Hilton</th>\n",
       "      <td>115000</td>\n",
       "      <td>3</td>\n",
       "      <td>65000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>John Smith</th>\n",
       "      <td>40000</td>\n",
       "      <td>2</td>\n",
       "      <td>35000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">Fred Anderson</th>\n",
       "      <th>Cedric Moss</th>\n",
       "      <td>110000</td>\n",
       "      <td>4</td>\n",
       "      <td>65000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wendy Yule</th>\n",
       "      <td>177000</td>\n",
       "      <td>4</td>\n",
       "      <td>100000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                sum count     max\n",
       "                              Price Price   Price\n",
       "Manager       Rep                                \n",
       "Debra Henley  Craig Booker    80000     4   35000\n",
       "              Daniel Hilton  115000     3   65000\n",
       "              John Smith      40000     2   35000\n",
       "Fred Anderson Cedric Moss    110000     4   65000\n",
       "              Wendy Yule     177000     4  100000"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.pivot_table(df, index=[\"Manager\", \"Rep\"], values=[\"Price\"], aggfunc=[np.sum, 'count', 'max'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## same pivot with columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th colspan=\"4\" halign=\"left\">sum</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th colspan=\"4\" halign=\"left\">Price</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>Product</th>\n",
       "      <th>CPU</th>\n",
       "      <th>Maintenance</th>\n",
       "      <th>Monitor</th>\n",
       "      <th>Software</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Manager</th>\n",
       "      <th>Rep</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">Debra Henley</th>\n",
       "      <th>Craig Booker</th>\n",
       "      <td>65000.0</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Daniel Hilton</th>\n",
       "      <td>105000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>John Smith</th>\n",
       "      <td>35000.0</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">Fred Anderson</th>\n",
       "      <th>Cedric Moss</th>\n",
       "      <td>95000.0</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wendy Yule</th>\n",
       "      <td>165000.0</td>\n",
       "      <td>7000.0</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                  sum                             \n",
       "                                Price                             \n",
       "Product                           CPU Maintenance Monitor Software\n",
       "Manager       Rep                                                 \n",
       "Debra Henley  Craig Booker    65000.0      5000.0     NaN  10000.0\n",
       "              Daniel Hilton  105000.0         NaN     NaN  10000.0\n",
       "              John Smith      35000.0      5000.0     NaN      NaN\n",
       "Fred Anderson Cedric Moss     95000.0      5000.0     NaN  10000.0\n",
       "              Wendy Yule     165000.0      7000.0  5000.0      NaN"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.pivot_table(df,index=[\"Manager\",\"Rep\"],values=[\"Price\"],\n",
    "               columns=[\"Product\"],aggfunc=[np.sum])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "  <thead>\n",
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       "      <th colspan=\"5\" halign=\"left\">count</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th colspan=\"5\" halign=\"left\">Price</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>Product</th>\n",
       "      <th>CPU</th>\n",
       "      <th>Maintenance</th>\n",
       "      <th>Monitor</th>\n",
       "      <th>Software</th>\n",
       "      <th>All</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Manager</th>\n",
       "      <th>Rep</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",
       "      <th rowspan=\"3\" valign=\"top\">Debra Henley</th>\n",
       "      <th>Craig Booker</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Daniel Hilton</th>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>John Smith</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">Fred Anderson</th>\n",
       "      <th>Cedric Moss</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wendy Yule</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>All</th>\n",
       "      <th></th>\n",
       "      <td>9</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            count                                 \n",
       "                            Price                                 \n",
       "Product                       CPU Maintenance Monitor Software All\n",
       "Manager       Rep                                                 \n",
       "Debra Henley  Craig Booker      2           1       0        1   4\n",
       "              Daniel Hilton     2           0       0        1   3\n",
       "              John Smith        1           1       0        0   2\n",
       "Fred Anderson Cedric Moss       2           1       0        1   4\n",
       "              Wendy Yule        2           1       1        0   4\n",
       "All                             9           4       1        3  17"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.pivot_table(df, index=[\"Manager\", \"Rep\"], values=[\"Price\"], \n",
    "aggfunc=['count'], columns=[\"Product\"], fill_value=0, margins=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Note how status is ordered based on our earlier category definition"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>sum</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Manager</th>\n",
       "      <th>Status</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">Debra Henley</th>\n",
       "      <th>declined</th>\n",
       "      <td>70000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pending</th>\n",
       "      <td>50000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>presented</th>\n",
       "      <td>50000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>won</th>\n",
       "      <td>65000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">Fred Anderson</th>\n",
       "      <th>declined</th>\n",
       "      <td>65000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pending</th>\n",
       "      <td>5000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>presented</th>\n",
       "      <td>45000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>won</th>\n",
       "      <td>172000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>All</th>\n",
       "      <th></th>\n",
       "      <td>522000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            sum\n",
       "                          Price\n",
       "Manager       Status           \n",
       "Debra Henley  declined    70000\n",
       "              pending     50000\n",
       "              presented   50000\n",
       "              won         65000\n",
       "Fred Anderson declined    65000\n",
       "              pending      5000\n",
       "              presented   45000\n",
       "              won        172000\n",
       "All                      522000"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.pivot_table(df, index=[\"Manager\", \"Status\"], values=[\"Price\"], \n",
    "               aggfunc=[np.sum], fill_value=0, margins=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Filter the data using standard DataFrame functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Account</th>\n",
       "      <th>Name</th>\n",
       "      <th>Rep</th>\n",
       "      <th>Manager</th>\n",
       "      <th>Product</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>Price</th>\n",
       "      <th>Status</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>714466</td>\n",
       "      <td>Trantow-Barrows</td>\n",
       "      <td>Craig Booker</td>\n",
       "      <td>Debra Henley</td>\n",
       "      <td>Maintenance</td>\n",
       "      <td>2</td>\n",
       "      <td>5000</td>\n",
       "      <td>pending</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>146832</td>\n",
       "      <td>Kiehn-Spinka</td>\n",
       "      <td>Daniel Hilton</td>\n",
       "      <td>Debra Henley</td>\n",
       "      <td>CPU</td>\n",
       "      <td>2</td>\n",
       "      <td>65000</td>\n",
       "      <td>won</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>218895</td>\n",
       "      <td>Kulas Inc</td>\n",
       "      <td>Daniel Hilton</td>\n",
       "      <td>Debra Henley</td>\n",
       "      <td>CPU</td>\n",
       "      <td>2</td>\n",
       "      <td>40000</td>\n",
       "      <td>pending</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>412290</td>\n",
       "      <td>Jerde-Hilpert</td>\n",
       "      <td>John Smith</td>\n",
       "      <td>Debra Henley</td>\n",
       "      <td>Maintenance</td>\n",
       "      <td>2</td>\n",
       "      <td>5000</td>\n",
       "      <td>pending</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Account             Name            Rep       Manager      Product  \\\n",
       "2   714466  Trantow-Barrows   Craig Booker  Debra Henley  Maintenance   \n",
       "4   146832     Kiehn-Spinka  Daniel Hilton  Debra Henley          CPU   \n",
       "5   218895        Kulas Inc  Daniel Hilton  Debra Henley          CPU   \n",
       "7   412290    Jerde-Hilpert     John Smith  Debra Henley  Maintenance   \n",
       "\n",
       "   Quantity  Price   Status  \n",
       "2         2   5000  pending  \n",
       "4         2  65000      won  \n",
       "5         2  40000  pending  \n",
       "7         2   5000  pending  "
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "_.query('Status == [\"pending\", \"won\"]')"
   ]
  }
 ],
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