13-Hierarchical Indexing.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Hierarchical Indexing in Pandas"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Hi Guys, Welcome to [Tirendaz Academy](https://youtube.com/c/tirendazacademy) 😀\n",
    "</br>\n",
    "In this notebook, I'm going to show hierarchical indexing in Pandas.\n",
    "</br>\n",
    "Happy Learning 🐱‍🏍 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "a  1    0.022235\n",
       "   2    0.007393\n",
       "   3   -3.081152\n",
       "b  1   -0.673017\n",
       "   2   -0.034024\n",
       "   3    0.679701\n",
       "c  1    1.175051\n",
       "   2    0.916181\n",
       "dtype: float64"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data=pd.Series(np.random.randn(8),\n",
    "               index=[[\"a\",\"a\",\"a\",\"b\",\n",
    "                       \"b\",\"b\",\"c\",\"c\"],\n",
    "                      [1,2,3,1,2,3,1,2]])\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "MultiIndex([('a', 1),\n",
       "            ('a', 2),\n",
       "            ('a', 3),\n",
       "            ('b', 1),\n",
       "            ('b', 2),\n",
       "            ('b', 3),\n",
       "            ('c', 1),\n",
       "            ('c', 2)],\n",
       "           )"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1    0.022235\n",
       "2    0.007393\n",
       "3   -3.081152\n",
       "dtype: float64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[\"a\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "b  1   -0.673017\n",
       "   2   -0.034024\n",
       "   3    0.679701\n",
       "c  1    1.175051\n",
       "   2    0.916181\n",
       "dtype: float64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[\"b\":\"c\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "a  1    0.022235\n",
       "   2    0.007393\n",
       "   3   -3.081152\n",
       "c  1    1.175051\n",
       "   2    0.916181\n",
       "dtype: float64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.loc[[\"a\",\"c\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "a    0.022235\n",
       "b   -0.673017\n",
       "c    1.175051\n",
       "dtype: float64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.loc[:,1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
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       "      <th>b</th>\n",
       "      <td>-0.673017</td>\n",
       "      <td>-0.034024</td>\n",
       "      <td>0.679701</td>\n",
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       "      <th>c</th>\n",
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      "text/plain": [
       "          1         2         3\n",
       "a  0.022235  0.007393 -3.081152\n",
       "b -0.673017 -0.034024  0.679701\n",
       "c  1.175051  0.916181       NaN"
      ]
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     "execution_count": 8,
     "metadata": {},
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   ],
   "source": [
    "data.unstack()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "a  1    0.022235\n",
       "   2    0.007393\n",
       "   3   -3.081152\n",
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       "   2   -0.034024\n",
       "   3    0.679701\n",
       "c  1    1.175051\n",
       "   2    0.916181\n",
       "dtype: float64"
      ]
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     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "data.unstack().stack()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "     num      ver\n",
       "    math stat geo\n",
       "a 1    0    1   2\n",
       "  2    3    4   5\n",
       "b 1    6    7   8\n",
       "  2    9   10  11"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df=pd.DataFrame(\n",
    "    np.arange(12).reshape(4,3),\n",
    "    index=[[\"a\",\"a\",\"b\",\"b\"],\n",
    "           [1,2,1,2]],\n",
    "    columns=[[\"num\",\"num\",\"ver\"],\n",
    "             [\"math\",\"stat\",\"geo\"]])\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
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       "      <th>ver</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>lesson</th>\n",
       "      <th>math</th>\n",
       "      <th>stat</th>\n",
       "      <th>geo</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>class</th>\n",
       "      <th>exam</th>\n",
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       "field       num      ver\n",
       "lesson     math stat geo\n",
       "class exam              \n",
       "a     1       0    1   2\n",
       "      2       3    4   5\n",
       "b     1       6    7   8\n",
       "      2       9   10  11"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.index.names=[\"class\",\"exam\"]\n",
    "df.columns.names=[\"field\",\"lesson\"]\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>lesson</th>\n",
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       "    <tr>\n",
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       "      <th rowspan=\"2\" valign=\"top\">b</th>\n",
       "      <th>1</th>\n",
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      "text/plain": [
       "lesson      math  stat\n",
       "class exam            \n",
       "a     1        0     1\n",
       "      2        3     4\n",
       "b     1        6     7\n",
       "      2        9    10"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"num\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
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       "      <th colspan=\"2\" halign=\"left\">num</th>\n",
       "      <th>ver</th>\n",
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       "    <tr>\n",
       "      <th></th>\n",
       "      <th>lesson</th>\n",
       "      <th>math</th>\n",
       "      <th>stat</th>\n",
       "      <th>geo</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>exam</th>\n",
       "      <th>class</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th>1</th>\n",
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       "      <th>2</th>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <th>b</th>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <th>b</th>\n",
       "      <td>9</td>\n",
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       "      <td>11</td>\n",
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      "text/plain": [
       "field       num      ver\n",
       "lesson     math stat geo\n",
       "exam class              \n",
       "1    a        0    1   2\n",
       "2    a        3    4   5\n",
       "1    b        6    7   8\n",
       "2    b        9   10  11"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.swaplevel(\"class\",\"exam\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
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       "      <th colspan=\"2\" halign=\"left\">num</th>\n",
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       "    <tr>\n",
       "      <th></th>\n",
       "      <th>lesson</th>\n",
       "      <th>math</th>\n",
       "      <th>stat</th>\n",
       "      <th>geo</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>class</th>\n",
       "      <th>exam</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>a</th>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>b</th>\n",
       "      <th>1</th>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>a</th>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>b</th>\n",
       "      <th>2</th>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>11</td>\n",
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      ],
      "text/plain": [
       "field       num      ver\n",
       "lesson     math stat geo\n",
       "class exam              \n",
       "a     1       0    1   2\n",
       "b     1       6    7   8\n",
       "a     2       3    4   5\n",
       "b     2       9   10  11"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sort_index(level=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Summary Statistics by Level"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "      <th>field</th>\n",
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       "      <th>ver</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lesson</th>\n",
       "      <th>math</th>\n",
       "      <th>stat</th>\n",
       "      <th>geo</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>exam</th>\n",
       "      <th></th>\n",
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       "      <td>10</td>\n",
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       "      <th>2</th>\n",
       "      <td>12</td>\n",
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      "text/plain": [
       "field   num      ver\n",
       "lesson math stat geo\n",
       "exam                \n",
       "1         6    8  10\n",
       "2        12   14  16"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sum(level=\"exam\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th rowspan=\"2\" valign=\"top\">b</th>\n",
       "      <th>1</th>\n",
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      "text/plain": [
       "field       num  ver\n",
       "class exam          \n",
       "a     1       1    2\n",
       "      2       7    5\n",
       "b     1      13    8\n",
       "      2      19   11"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sum(level=\"field\",axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Indexing with a DataFrame’s columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>two</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
       "      <td>two</td>\n",
       "      <td>2</td>\n",
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       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>two</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   x  y    a  b\n",
       "0  0  8  one  0\n",
       "1  1  7  one  1\n",
       "2  2  6  one  2\n",
       "3  3  5  one  3\n",
       "4  4  4  two  0\n",
       "5  5  3  two  1\n",
       "6  6  2  two  2\n",
       "7  7  1  two  3"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data=pd.DataFrame(\n",
    "    {\"x\":range(8),\"y\":range(8,0,-1),\n",
    "     \"a\":[\"one\",\"one\",\"one\",\"one\",\"two\",\n",
    "          \"two\",\"two\",\"two\"],\n",
    "     \"b\":[0,1,2,3,0,1,2,3]})\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
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       "  <tbody>\n",
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       "      <th>0</th>\n",
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       "      <td>3</td>\n",
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       "    <tr>\n",
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       "      <td>6</td>\n",
       "      <td>2</td>\n",
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      "text/plain": [
       "       x  y\n",
       "a   b      \n",
       "one 0  0  8\n",
       "    1  1  7\n",
       "    2  2  6\n",
       "    3  3  5\n",
       "two 0  4  4\n",
       "    1  5  3\n",
       "    2  6  2\n",
       "    3  7  1"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data2=data.set_index([\"a\",\"b\"])\n",
    "data2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
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       "      <th rowspan=\"4\" valign=\"top\">two</th>\n",
       "      <th>0</th>\n",
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       "      <td>two</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
       "      <td>two</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>two</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       x  y    a  b\n",
       "a   b              \n",
       "one 0  0  8  one  0\n",
       "    1  1  7  one  1\n",
       "    2  2  6  one  2\n",
       "    3  3  5  one  3\n",
       "two 0  4  4  two  0\n",
       "    1  5  3  two  1\n",
       "    2  6  2  two  2\n",
       "    3  7  1  two  3"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data3=data.set_index([\"a\",\"b\"],drop=False)\n",
    "data3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
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       "       x  y\n",
       "a   b      \n",
       "one 0  0  8\n",
       "    1  1  7\n",
       "    2  2  6\n",
       "    3  3  5\n",
       "two 0  4  4\n",
       "    1  5  3\n",
       "    2  6  2\n",
       "    3  7  1"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
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       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>two</td>\n",
       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     a  b  x  y\n",
       "0  one  0  0  8\n",
       "1  one  1  1  7\n",
       "2  one  2  2  6\n",
       "3  one  3  3  5\n",
       "4  two  0  4  4\n",
       "5  two  1  5  3\n",
       "6  two  2  6  2\n",
       "7  two  3  7  1"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data2.reset_index()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Don't forget to follow us on [YouTube](http://youtube.com/tirendazacademy) | [Medium](http://tirendazacademy.medium.com) | [Twitter](http://twitter.com/tirendazacademy) | [GitHub](http://github.com/tirendazacademy) | [Linkedin](https://www.linkedin.com/in/tirendaz-academy) | [Kaggle](https://www.kaggle.com/tirendazacademy) 😎"
   ]
  }
 ],
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