7. Handling a MultiIndex.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 7. Handling a MultiIndex\n",
    "A MultiIndex or multi-level index is a cumbersome addition to a Pandas DataFrame that occasionally makes data easier to view, but often makes it much more difficult to manipulate. You usually encounter a MultiIndex after a `groupby` operation with multiple grouping columns or multiple aggregating columns. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "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>instnm</th>\n",
       "      <th>city</th>\n",
       "      <th>stabbr</th>\n",
       "      <th>hbcu</th>\n",
       "      <th>menonly</th>\n",
       "      <th>womenonly</th>\n",
       "      <th>relaffil</th>\n",
       "      <th>satvrmid</th>\n",
       "      <th>satmtmid</th>\n",
       "      <th>distanceonly</th>\n",
       "      <th>...</th>\n",
       "      <th>ugds_2mor</th>\n",
       "      <th>ugds_nra</th>\n",
       "      <th>ugds_unkn</th>\n",
       "      <th>pptug_ef</th>\n",
       "      <th>curroper</th>\n",
       "      <th>pctpell</th>\n",
       "      <th>pctfloan</th>\n",
       "      <th>ug25abv</th>\n",
       "      <th>md_earn_wne_p10</th>\n",
       "      <th>grad_debt_mdn_supp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Alabama A &amp; M University</td>\n",
       "      <td>Normal</td>\n",
       "      <td>AL</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>424.0</td>\n",
       "      <td>420.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0059</td>\n",
       "      <td>0.0138</td>\n",
       "      <td>0.0656</td>\n",
       "      <td>1</td>\n",
       "      <td>0.7356</td>\n",
       "      <td>0.8284</td>\n",
       "      <td>0.1049</td>\n",
       "      <td>30300</td>\n",
       "      <td>33888</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>University of Alabama at Birmingham</td>\n",
       "      <td>Birmingham</td>\n",
       "      <td>AL</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>570.0</td>\n",
       "      <td>565.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0368</td>\n",
       "      <td>0.0179</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.2607</td>\n",
       "      <td>1</td>\n",
       "      <td>0.3460</td>\n",
       "      <td>0.5214</td>\n",
       "      <td>0.2422</td>\n",
       "      <td>39700</td>\n",
       "      <td>21941.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Amridge University</td>\n",
       "      <td>Montgomery</td>\n",
       "      <td>AL</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.2715</td>\n",
       "      <td>0.4536</td>\n",
       "      <td>1</td>\n",
       "      <td>0.6801</td>\n",
       "      <td>0.7795</td>\n",
       "      <td>0.8540</td>\n",
       "      <td>40100</td>\n",
       "      <td>23370</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>University of Alabama in Huntsville</td>\n",
       "      <td>Huntsville</td>\n",
       "      <td>AL</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>595.0</td>\n",
       "      <td>590.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0172</td>\n",
       "      <td>0.0332</td>\n",
       "      <td>0.0350</td>\n",
       "      <td>0.2146</td>\n",
       "      <td>1</td>\n",
       "      <td>0.3072</td>\n",
       "      <td>0.4596</td>\n",
       "      <td>0.2640</td>\n",
       "      <td>45500</td>\n",
       "      <td>24097</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Alabama State University</td>\n",
       "      <td>Montgomery</td>\n",
       "      <td>AL</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>425.0</td>\n",
       "      <td>430.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0098</td>\n",
       "      <td>0.0243</td>\n",
       "      <td>0.0137</td>\n",
       "      <td>0.0892</td>\n",
       "      <td>1</td>\n",
       "      <td>0.7347</td>\n",
       "      <td>0.7554</td>\n",
       "      <td>0.1270</td>\n",
       "      <td>26600</td>\n",
       "      <td>33118.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                instnm        city stabbr  hbcu  menonly  \\\n",
       "0             Alabama A & M University      Normal     AL   1.0      0.0   \n",
       "1  University of Alabama at Birmingham  Birmingham     AL   0.0      0.0   \n",
       "2                   Amridge University  Montgomery     AL   0.0      0.0   \n",
       "3  University of Alabama in Huntsville  Huntsville     AL   0.0      0.0   \n",
       "4             Alabama State University  Montgomery     AL   1.0      0.0   \n",
       "\n",
       "   womenonly  relaffil  satvrmid  satmtmid  distanceonly  ...  ugds_2mor  \\\n",
       "0        0.0         0     424.0     420.0           0.0  ...     0.0000   \n",
       "1        0.0         0     570.0     565.0           0.0  ...     0.0368   \n",
       "2        0.0         1       NaN       NaN           1.0  ...     0.0000   \n",
       "3        0.0         0     595.0     590.0           0.0  ...     0.0172   \n",
       "4        0.0         0     425.0     430.0           0.0  ...     0.0098   \n",
       "\n",
       "   ugds_nra  ugds_unkn  pptug_ef  curroper  pctpell  pctfloan  ug25abv  \\\n",
       "0    0.0059     0.0138    0.0656         1   0.7356    0.8284   0.1049   \n",
       "1    0.0179     0.0100    0.2607         1   0.3460    0.5214   0.2422   \n",
       "2    0.0000     0.2715    0.4536         1   0.6801    0.7795   0.8540   \n",
       "3    0.0332     0.0350    0.2146         1   0.3072    0.4596   0.2640   \n",
       "4    0.0243     0.0137    0.0892         1   0.7347    0.7554   0.1270   \n",
       "\n",
       "   md_earn_wne_p10  grad_debt_mdn_supp  \n",
       "0            30300               33888  \n",
       "1            39700             21941.5  \n",
       "2            40100               23370  \n",
       "3            45500               24097  \n",
       "4            26600             33118.5  \n",
       "\n",
       "[5 rows x 27 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "college = pd.read_csv('data/college.csv')\n",
    "college.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's use a result similar to the one at the end of the previous notebook, except this time group by both state and religious affiliation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th colspan=\"2\" halign=\"left\">satmtmid</th>\n",
       "      <th colspan=\"2\" halign=\"left\">satvrmid</th>\n",
       "      <th>ugds</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>min</th>\n",
       "      <th>max</th>\n",
       "      <th>min</th>\n",
       "      <th>max</th>\n",
       "      <th>mean</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stabbr</th>\n",
       "      <th>relaffil</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=\"2\" valign=\"top\">AK</th>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3509.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>503.0</td>\n",
       "      <td>503.0</td>\n",
       "      <td>555.0</td>\n",
       "      <td>555.0</td>\n",
       "      <td>123.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">AL</th>\n",
       "      <th>0</th>\n",
       "      <td>420.0</td>\n",
       "      <td>590.0</td>\n",
       "      <td>424.0</td>\n",
       "      <td>595.0</td>\n",
       "      <td>3249.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>400.0</td>\n",
       "      <td>560.0</td>\n",
       "      <td>420.0</td>\n",
       "      <td>565.0</td>\n",
       "      <td>980.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">AR</th>\n",
       "      <th>0</th>\n",
       "      <td>427.0</td>\n",
       "      <td>565.0</td>\n",
       "      <td>410.0</td>\n",
       "      <td>555.0</td>\n",
       "      <td>1794.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>495.0</td>\n",
       "      <td>600.0</td>\n",
       "      <td>425.0</td>\n",
       "      <td>600.0</td>\n",
       "      <td>918.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AS</th>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1276.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">AZ</th>\n",
       "      <th>0</th>\n",
       "      <td>503.0</td>\n",
       "      <td>580.0</td>\n",
       "      <td>535.0</td>\n",
       "      <td>565.0</td>\n",
       "      <td>4364.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>480.0</td>\n",
       "      <td>480.0</td>\n",
       "      <td>485.0</td>\n",
       "      <td>485.0</td>\n",
       "      <td>693.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CA</th>\n",
       "      <th>0</th>\n",
       "      <td>445.0</td>\n",
       "      <td>785.0</td>\n",
       "      <td>435.0</td>\n",
       "      <td>765.0</td>\n",
       "      <td>3802.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                satmtmid        satvrmid           ugds\n",
       "                     min    max      min    max    mean\n",
       "stabbr relaffil                                        \n",
       "AK     0             NaN    NaN      NaN    NaN  3509.0\n",
       "       1           503.0  503.0    555.0  555.0   123.0\n",
       "AL     0           420.0  590.0    424.0  595.0  3249.0\n",
       "       1           400.0  560.0    420.0  565.0   980.0\n",
       "AR     0           427.0  565.0    410.0  555.0  1794.0\n",
       "       1           495.0  600.0    425.0  600.0   918.0\n",
       "AS     0             NaN    NaN      NaN    NaN  1276.0\n",
       "AZ     0           503.0  580.0    535.0  565.0  4364.0\n",
       "       1           480.0  480.0    485.0  485.0   693.0\n",
       "CA     0           445.0  785.0    435.0  765.0  3802.0"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = college.groupby(['stabbr', 'relaffil']).agg({'satmtmid': ['min', 'max'],\n",
    "                                                  'satvrmid': ['min', 'max'],\n",
    "                                                  'ugds': 'mean'}).round(0)\n",
    "df.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## A MultiIndex in both the index and columns\n",
    "Both the rows and columns have a MultiIindex with two levels. Let's verify their types."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.indexes.multi.MultiIndex"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(df.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "type(df.columns)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Selection and further processing is difficult with a MultiIndex\n",
    "There is no magic extra functionality that a MultiIndex possesses (outside of some trickery). They are harder to remember how to make selections from and more difficult to call other methods on. I suggest working with DataFrames that have a simpler, single-level index.\n",
    "\n",
    "### Convert to a single level index - Rename the columns and reset the index\n",
    "We can convert this DataFrame so that only single-level indexes rename. There is no direct way to rename columns of a DataFrame during a groupby (yes, something so simple is impossible with pandas), so we must overwrite them manually. Let's do that now."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>min satmtmid</th>\n",
       "      <th>max satmtmid</th>\n",
       "      <th>min satvrmid</th>\n",
       "      <th>max satvrmid</th>\n",
       "      <th>mean ugds</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stabbr</th>\n",
       "      <th>relaffil</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=\"2\" valign=\"top\">AK</th>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3509.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>503.0</td>\n",
       "      <td>503.0</td>\n",
       "      <td>555.0</td>\n",
       "      <td>555.0</td>\n",
       "      <td>123.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">AL</th>\n",
       "      <th>0</th>\n",
       "      <td>420.0</td>\n",
       "      <td>590.0</td>\n",
       "      <td>424.0</td>\n",
       "      <td>595.0</td>\n",
       "      <td>3249.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>400.0</td>\n",
       "      <td>560.0</td>\n",
       "      <td>420.0</td>\n",
       "      <td>565.0</td>\n",
       "      <td>980.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AR</th>\n",
       "      <th>0</th>\n",
       "      <td>427.0</td>\n",
       "      <td>565.0</td>\n",
       "      <td>410.0</td>\n",
       "      <td>555.0</td>\n",
       "      <td>1794.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 min satmtmid  max satmtmid  min satvrmid  max satvrmid  \\\n",
       "stabbr relaffil                                                           \n",
       "AK     0                  NaN           NaN           NaN           NaN   \n",
       "       1                503.0         503.0         555.0         555.0   \n",
       "AL     0                420.0         590.0         424.0         595.0   \n",
       "       1                400.0         560.0         420.0         565.0   \n",
       "AR     0                427.0         565.0         410.0         555.0   \n",
       "\n",
       "                 mean ugds  \n",
       "stabbr relaffil             \n",
       "AK     0            3509.0  \n",
       "       1             123.0  \n",
       "AL     0            3249.0  \n",
       "       1             980.0  \n",
       "AR     0            1794.0  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns = ['min satmtmid', 'max satmtmid', 'min satvrmid', 'max satvrmid', 'mean ugds']\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From here, we can use the `reset_index` method to make each index level an actual column."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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>stabbr</th>\n",
       "      <th>relaffil</th>\n",
       "      <th>min satmtmid</th>\n",
       "      <th>max satmtmid</th>\n",
       "      <th>min satvrmid</th>\n",
       "      <th>max satvrmid</th>\n",
       "      <th>mean ugds</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AK</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3509.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AK</td>\n",
       "      <td>1</td>\n",
       "      <td>503.0</td>\n",
       "      <td>503.0</td>\n",
       "      <td>555.0</td>\n",
       "      <td>555.0</td>\n",
       "      <td>123.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AL</td>\n",
       "      <td>0</td>\n",
       "      <td>420.0</td>\n",
       "      <td>590.0</td>\n",
       "      <td>424.0</td>\n",
       "      <td>595.0</td>\n",
       "      <td>3249.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AL</td>\n",
       "      <td>1</td>\n",
       "      <td>400.0</td>\n",
       "      <td>560.0</td>\n",
       "      <td>420.0</td>\n",
       "      <td>565.0</td>\n",
       "      <td>980.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AR</td>\n",
       "      <td>0</td>\n",
       "      <td>427.0</td>\n",
       "      <td>565.0</td>\n",
       "      <td>410.0</td>\n",
       "      <td>555.0</td>\n",
       "      <td>1794.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  stabbr  relaffil  min satmtmid  max satmtmid  min satvrmid  max satvrmid  \\\n",
       "0     AK         0           NaN           NaN           NaN           NaN   \n",
       "1     AK         1         503.0         503.0         555.0         555.0   \n",
       "2     AL         0         420.0         590.0         424.0         595.0   \n",
       "3     AL         1         400.0         560.0         420.0         565.0   \n",
       "4     AR         0         427.0         565.0         410.0         555.0   \n",
       "\n",
       "   mean ugds  \n",
       "0     3509.0  \n",
       "1      123.0  \n",
       "2     3249.0  \n",
       "3      980.0  \n",
       "4     1794.0  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_final = df.reset_index()\n",
    "df_final.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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