data-analysis/040-pandas-sort_values/pandas-sort_values.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Pandas sort_values()\n",
    "\n",
    "This is a notebook for the medium article [11 Tricks to Master Values Sorting in Pandas](https://bindichen.medium.com/11-tricks-to-master-values-sorting-in-pandas-7f2cfbf19730)\n",
    "\n",
    "Please check out article for instructions\n",
    "\n",
    "**License**: [BSD 2-Clause](https://opensource.org/licenses/BSD-2-Clause)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
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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>product</th>\n",
       "      <th>category</th>\n",
       "      <th>year</th>\n",
       "      <th>cost</th>\n",
       "      <th>promotion_time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>keyboard</td>\n",
       "      <td>C</td>\n",
       "      <td>2002</td>\n",
       "      <td>$52</td>\n",
       "      <td>20hr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>mouse</td>\n",
       "      <td>C</td>\n",
       "      <td>2002</td>\n",
       "      <td>$24</td>\n",
       "      <td>30hr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>desk</td>\n",
       "      <td>O</td>\n",
       "      <td>2005</td>\n",
       "      <td>$250</td>\n",
       "      <td>20hr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>monitor</td>\n",
       "      <td>C</td>\n",
       "      <td>2001</td>\n",
       "      <td>$500</td>\n",
       "      <td>20hr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chair</td>\n",
       "      <td>O</td>\n",
       "      <td>2003</td>\n",
       "      <td>$150</td>\n",
       "      <td>2hr</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    product category  year  cost promotion_time\n",
       "0  keyboard        C  2002   $52           20hr\n",
       "1     mouse        C  2002   $24           30hr\n",
       "2      desk        O  2005  $250           20hr\n",
       "3   monitor        C  2001  $500           20hr\n",
       "4     chair        O  2003  $150            2hr"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame({\n",
    "    'product': ['keyboard', 'mouse', 'desk', 'monitor', 'chair'],\n",
    "    'category': ['C', 'C', 'O', 'C', 'O'],\n",
    "    'year': [2002, 2002, 2005, 2001, 2003],\n",
    "    'cost': ['$52', '$24', '$250', '$500', '$150'],\n",
    "    'promotion_time': ['20hr', '30hr', '20hr', '20hr', '2hr'],\n",
    "})\n",
    "\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1.Sorting a Series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3    2001\n",
       "0    2002\n",
       "1    2002\n",
       "4    2003\n",
       "2    2005\n",
       "Name: year, dtype: int64"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Sorting a series, result is in ASC by default\n",
    "df['year'].sort_values()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2    2005\n",
       "4    2003\n",
       "1    2002\n",
       "0    2002\n",
       "3    2001\n",
       "Name: year, dtype: int64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# For a DESC result\n",
    "df['year'].sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Sorting a Dataframe by a single column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>product</th>\n",
       "      <th>category</th>\n",
       "      <th>year</th>\n",
       "      <th>cost</th>\n",
       "      <th>promotion_time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>monitor</td>\n",
       "      <td>C</td>\n",
       "      <td>2001</td>\n",
       "      <td>$500</td>\n",
       "      <td>20hr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>keyboard</td>\n",
       "      <td>C</td>\n",
       "      <td>2002</td>\n",
       "      <td>$52</td>\n",
       "      <td>20hr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>mouse</td>\n",
       "      <td>C</td>\n",
       "      <td>2002</td>\n",
       "      <td>$24</td>\n",
       "      <td>30hr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chair</td>\n",
       "      <td>O</td>\n",
       "      <td>2003</td>\n",
       "      <td>$150</td>\n",
       "      <td>2hr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>desk</td>\n",
       "      <td>O</td>\n",
       "      <td>2005</td>\n",
       "      <td>$250</td>\n",
       "      <td>20hr</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    product category  year  cost promotion_time\n",
       "3   monitor        C  2001  $500           20hr\n",
       "0  keyboard        C  2002   $52           20hr\n",
       "1     mouse        C  2002   $24           30hr\n",
       "4     chair        O  2003  $150            2hr\n",
       "2      desk        O  2005  $250           20hr"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sort_values('year')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>product</th>\n",
       "      <th>category</th>\n",
       "      <th>year</th>\n",
       "      <th>cost</th>\n",
       "      <th>promotion_time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>desk</td>\n",
       "      <td>O</td>\n",
       "      <td>2005</td>\n",
       "      <td>$250</td>\n",
       "      <td>20hr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chair</td>\n",
       "      <td>O</td>\n",
       "      <td>2003</td>\n",
       "      <td>$150</td>\n",
       "      <td>2hr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>keyboard</td>\n",
       "      <td>C</td>\n",
       "      <td>2002</td>\n",
       "      <td>$52</td>\n",
       "      <td>20hr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>mouse</td>\n",
       "      <td>C</td>\n",
       "      <td>2002</td>\n",
       "      <td>$24</td>\n",
       "      <td>30hr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>monitor</td>\n",
       "      <td>C</td>\n",
       "      <td>2001</td>\n",
       "      <td>$500</td>\n",
       "      <td>20hr</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    product category  year  cost promotion_time\n",
       "2      desk        O  2005  $250           20hr\n",
       "4     chair        O  2003  $150            2hr\n",
       "0  keyboard        C  2002   $52           20hr\n",
       "1     mouse        C  2002   $24           30hr\n",
       "3   monitor        C  2001  $500           20hr"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sort_values('year', ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. Sorting a DataFrame by multiple columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>product</th>\n",
       "      <th>category</th>\n",
       "      <th>year</th>\n",
       "      <th>cost</th>\n",
       "      <th>promotion_time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>monitor</td>\n",
       "      <td>C</td>\n",
       "      <td>2001</td>\n",
       "      <td>$500</td>\n",
       "      <td>20hr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>keyboard</td>\n",
       "      <td>C</td>\n",
       "      <td>2002</td>\n",
       "      <td>$52</td>\n",
       "      <td>20hr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>mouse</td>\n",
       "      <td>C</td>\n",
       "      <td>2002</td>\n",
       "      <td>$24</td>\n",
       "      <td>30hr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chair</td>\n",
       "      <td>O</td>\n",
       "      <td>2003</td>\n",
       "      <td>$150</td>\n",
       "      <td>2hr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>desk</td>\n",
       "      <td>O</td>\n",
       "      <td>2005</td>\n",
       "      <td>$250</td>\n",
       "      <td>20hr</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    product category  year  cost promotion_time\n",
       "3   monitor        C  2001  $500           20hr\n",
       "0  keyboard        C  2002   $52           20hr\n",
       "1     mouse        C  2002   $24           30hr\n",
       "4     chair        O  2003  $150            2hr\n",
       "2      desk        O  2005  $250           20hr"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sort_values(['category', 'year'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>product</th>\n",
       "      <th>category</th>\n",
       "      <th>year</th>\n",
       "      <th>cost</th>\n",
       "      <th>promotion_time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>keyboard</td>\n",
       "      <td>C</td>\n",
       "      <td>2002</td>\n",
       "      <td>$52</td>\n",
       "      <td>20hr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>mouse</td>\n",
       "      <td>C</td>\n",
       "      <td>2002</td>\n",
       "      <td>$24</td>\n",
       "      <td>30hr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>monitor</td>\n",
       "      <td>C</td>\n",
       "      <td>2001</td>\n",
       "      <td>$500</td>\n",
       "      <td>20hr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>desk</td>\n",
       "      <td>O</td>\n",
       "      <td>2005</td>\n",
       "      <td>$250</td>\n",
       "      <td>20hr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chair</td>\n",
       "      <td>O</td>\n",
       "      <td>2003</td>\n",
       "      <td>$150</td>\n",
       "      <td>2hr</td>\n",
       "    </tr>\n",
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      "text/plain": [
       "    product category  year  cost promotion_time\n",
       "0  keyboard        C  2002   $52           20hr\n",
       "1     mouse        C  2002   $24           30hr\n",
       "3   monitor        C  2001  $500           20hr\n",
       "2      desk        O  2005  $250           20hr\n",
       "4     chair        O  2003  $150            2hr"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sort_values(['category', 'year'], ascending=[True, False])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4. Applying transformation before sorting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>product</th>\n",
       "      <th>category</th>\n",
       "      <th>year</th>\n",
       "      <th>cost</th>\n",
       "      <th>promotion_time</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chair</td>\n",
       "      <td>O</td>\n",
       "      <td>2003</td>\n",
       "      <td>$150</td>\n",
       "      <td>2hr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>mouse</td>\n",
       "      <td>C</td>\n",
       "      <td>2002</td>\n",
       "      <td>$24</td>\n",
       "      <td>30hr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>desk</td>\n",
       "      <td>O</td>\n",
       "      <td>2005</td>\n",
       "      <td>$250</td>\n",
       "      <td>20hr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>monitor</td>\n",
       "      <td>C</td>\n",
       "      <td>2001</td>\n",
       "      <td>$500</td>\n",
       "      <td>20hr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>keyboard</td>\n",
       "      <td>C</td>\n",
       "      <td>2002</td>\n",
       "      <td>$52</td>\n",
       "      <td>20hr</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      "text/plain": [
       "    product category  year  cost promotion_time\n",
       "4     chair        O  2003  $150            2hr\n",
       "1     mouse        C  2002   $24           30hr\n",
       "2      desk        O  2005  $250           20hr\n",
       "3   monitor        C  2001  $500           20hr\n",
       "0  keyboard        C  2002   $52           20hr"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# sort by the string value because of the $ symbol\n",
    "df.sort_values('cost')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>product</th>\n",
       "      <th>category</th>\n",
       "      <th>year</th>\n",
       "      <th>cost</th>\n",
       "      <th>promotion_time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>mouse</td>\n",
       "      <td>C</td>\n",
       "      <td>2002</td>\n",
       "      <td>$24</td>\n",
       "      <td>30hr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>keyboard</td>\n",
       "      <td>C</td>\n",
       "      <td>2002</td>\n",
       "      <td>$52</td>\n",
       "      <td>20hr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chair</td>\n",
       "      <td>O</td>\n",
       "      <td>2003</td>\n",
       "      <td>$150</td>\n",
       "      <td>2hr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>desk</td>\n",
       "      <td>O</td>\n",
       "      <td>2005</td>\n",
       "      <td>$250</td>\n",
       "      <td>20hr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>monitor</td>\n",
       "      <td>C</td>\n",
       "      <td>2001</td>\n",
       "      <td>$500</td>\n",
       "      <td>20hr</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    product category  year  cost promotion_time\n",
       "1     mouse        C  2002   $24           30hr\n",
       "0  keyboard        C  2002   $52           20hr\n",
       "4     chair        O  2003  $150            2hr\n",
       "2      desk        O  2005  $250           20hr\n",
       "3   monitor        C  2001  $500           20hr"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sort_values(\n",
    "    'cost', \n",
    "    key=lambda val: val.str.replace('$', '').astype('float64')\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5. Apply transformation on multiple columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "def sort_by_cost_time(x):\n",
    "    if x.name == 'cost':\n",
    "        return x.str.replace('$', '').astype('float64')\n",
    "    elif x.name == 'promotion_time':\n",
    "        return x.str.replace('hr', '').astype('int')\n",
    "    else:\n",
    "        return x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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>product</th>\n",
       "      <th>category</th>\n",
       "      <th>year</th>\n",
       "      <th>cost</th>\n",
       "      <th>promotion_time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>monitor</td>\n",
       "      <td>C</td>\n",
       "      <td>2001</td>\n",
       "      <td>$500</td>\n",
       "      <td>20hr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>keyboard</td>\n",
       "      <td>C</td>\n",
       "      <td>2002</td>\n",
       "      <td>$52</td>\n",
       "      <td>20hr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>mouse</td>\n",
       "      <td>C</td>\n",
       "      <td>2002</td>\n",
       "      <td>$24</td>\n",
       "      <td>30hr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chair</td>\n",
       "      <td>O</td>\n",
       "      <td>2003</td>\n",
       "      <td>$150</td>\n",
       "      <td>2hr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>desk</td>\n",
       "      <td>O</td>\n",
       "      <td>2005</td>\n",
       "      <td>$250</td>\n",
       "      <td>20hr</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    product category  year  cost promotion_time\n",
       "3   monitor        C  2001  $500           20hr\n",
       "0  keyboard        C  2002   $52           20hr\n",
       "1     mouse        C  2002   $24           30hr\n",
       "4     chair        O  2003  $150            2hr\n",
       "2      desk        O  2005  $250           20hr"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sort_values(['year', 'promotion_time', 'cost'], key=sort_by_cost_time)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 6. Dealing with Custom Sort"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "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>cloth_id</th>\n",
       "      <th>size</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1001</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1002</td>\n",
       "      <td>XL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1003</td>\n",
       "      <td>M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1004</td>\n",
       "      <td>XS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1005</td>\n",
       "      <td>L</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1006</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   cloth_id size\n",
       "0      1001    S\n",
       "1      1002   XL\n",
       "2      1003    M\n",
       "3      1004   XS\n",
       "4      1005    L\n",
       "5      1006    S"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame({\n",
    "    'cloth_id': [1001, 1002, 1003, 1004, 1005, 1006],\n",
    "    'size': ['S', 'XL', 'M', 'XS', 'L', 'S'],\n",
    "})\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pandas.api.types import CategoricalDtype\n",
    "\n",
    "cat_size_order = CategoricalDtype(\n",
    "    ['XS', 'S', 'M', 'L', 'XL'], \n",
    "    ordered=True\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     S\n",
       "1    XL\n",
       "2     M\n",
       "3    XS\n",
       "4     L\n",
       "5     S\n",
       "Name: size, dtype: category\n",
       "Categories (5, object): ['XS' < 'S' < 'M' < 'L' < 'XL']"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['size'] = df['size'].astype(cat_size_order)\n",
    "df['size']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "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>cloth_id</th>\n",
       "      <th>size</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1004</td>\n",
       "      <td>XS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1001</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1006</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1003</td>\n",
       "      <td>M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1005</td>\n",
       "      <td>L</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1002</td>\n",
       "      <td>XL</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   cloth_id size\n",
       "3      1004   XS\n",
       "0      1001    S\n",
       "5      1006    S\n",
       "2      1003    M\n",
       "4      1005    L\n",
       "1      1002   XL"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sort_values('size')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 7. Handling missing values"
   ]
  },
  {
   "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>id</th>\n",
       "      <th>name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2.0</td>\n",
       "      <td>B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3.0</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4.0</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5.0</td>\n",
       "      <td>F</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>6.0</td>\n",
       "      <td>E</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NaN</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    id name\n",
       "1  2.0    B\n",
       "2  3.0    C\n",
       "0  4.0    A\n",
       "5  5.0    F\n",
       "4  6.0    E\n",
       "3  NaN    D"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame({\n",
    "    'id': [4, 2, 3, np.nan, 6, 5],\n",
    "    'name': ['A', 'B', 'C', 'D', 'E', 'F'],\n",
    "})\n",
    "\n",
    "df.sort_values('id')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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>id</th>\n",
       "      <th>name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NaN</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2.0</td>\n",
       "      <td>B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3.0</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4.0</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5.0</td>\n",
       "      <td>F</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>6.0</td>\n",
       "      <td>E</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    id name\n",
       "3  NaN    D\n",
       "1  2.0    B\n",
       "2  3.0    C\n",
       "0  4.0    A\n",
       "5  5.0    F\n",
       "4  6.0    E"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sort_values('id', na_position='first')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 8. Sorting values in place"
   ]
  },
  {
   "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>id</th>\n",
       "      <th>name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4.0</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2.0</td>\n",
       "      <td>B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3.0</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NaN</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>6.0</td>\n",
       "      <td>E</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5.0</td>\n",
       "      <td>F</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    id name\n",
       "0  4.0    A\n",
       "1  2.0    B\n",
       "2  3.0    C\n",
       "3  NaN    D\n",
       "4  6.0    E\n",
       "5  5.0    F"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame({\n",
    "    'id': [4, 2, 3, np.nan, 6, 5],\n",
    "    'name': ['A', 'B', 'C', 'D', 'E', 'F'],\n",
    "})\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.sort_values('id', inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .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>id</th>\n",
       "      <th>name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2.0</td>\n",
       "      <td>B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3.0</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4.0</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5.0</td>\n",
       "      <td>F</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>6.0</td>\n",
       "      <td>E</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NaN</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    id name\n",
       "1  2.0    B\n",
       "2  3.0    C\n",
       "0  4.0    A\n",
       "5  5.0    F\n",
       "4  6.0    E\n",
       "3  NaN    D"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 9. Ignoring the index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\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>id</th>\n",
       "      <th>name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4.0</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2.0</td>\n",
       "      <td>B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3.0</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NaN</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>6.0</td>\n",
       "      <td>E</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5.0</td>\n",
       "      <td>F</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    id name\n",
       "0  4.0    A\n",
       "1  2.0    B\n",
       "2  3.0    C\n",
       "3  NaN    D\n",
       "4  6.0    E\n",
       "5  5.0    F"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame({\n",
    "    'id': [4, 2, 3, np.nan, 6, 5],\n",
    "    'name': ['A', 'B', 'C', 'D', 'E', 'F'],\n",
    "})\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\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>id</th>\n",
       "      <th>name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2.0</td>\n",
       "      <td>B</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3.0</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4.0</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5.0</td>\n",
       "      <td>F</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>6.0</td>\n",
       "      <td>E</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NaN</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    id name\n",
       "1  2.0    B\n",
       "2  3.0    C\n",
       "0  4.0    A\n",
       "5  5.0    F\n",
       "4  6.0    E\n",
       "3  NaN    D"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sort_values('id')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "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>id</th>\n",
       "      <th>name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2.0</td>\n",
       "      <td>B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3.0</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4.0</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5.0</td>\n",
       "      <td>F</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>6.0</td>\n",
       "      <td>E</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>NaN</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    id name\n",
       "0  2.0    B\n",
       "1  3.0    C\n",
       "2  4.0    A\n",
       "3  5.0    F\n",
       "4  6.0    E\n",
       "5  NaN    D"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sort_values('id', ignore_index=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 10. Sorting a DataFrame by row(s)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "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>Tom</th>\n",
       "      <th>Jacky</th>\n",
       "      <th>Lucy</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Math</th>\n",
       "      <td>70</td>\n",
       "      <td>90</td>\n",
       "      <td>56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Chemistry</th>\n",
       "      <td>67</td>\n",
       "      <td>85</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Physics</th>\n",
       "      <td>90</td>\n",
       "      <td>76</td>\n",
       "      <td>75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Art</th>\n",
       "      <td>50</td>\n",
       "      <td>70</td>\n",
       "      <td>77</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Tom  Jacky  Lucy\n",
       "Math        70     90    56\n",
       "Chemistry   67     85    60\n",
       "Physics     90     76    75\n",
       "Art         50     70    77"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame({\n",
    "    'Tom': [70, 67, 90, 50],\n",
    "    'Jacky': [90, 85, 76, 70],\n",
    "    'Lucy': [56, 60, 75, 77],\n",
    "}, index=['Math', 'Chemistry', 'Physics', 'Art'])\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "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>Lucy</th>\n",
       "      <th>Tom</th>\n",
       "      <th>Jacky</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Math</th>\n",
       "      <td>56</td>\n",
       "      <td>70</td>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Chemistry</th>\n",
       "      <td>60</td>\n",
       "      <td>67</td>\n",
       "      <td>85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Physics</th>\n",
       "      <td>75</td>\n",
       "      <td>90</td>\n",
       "      <td>76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Art</th>\n",
       "      <td>77</td>\n",
       "      <td>50</td>\n",
       "      <td>70</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Lucy  Tom  Jacky\n",
       "Math         56   70     90\n",
       "Chemistry    60   67     85\n",
       "Physics      75   90     76\n",
       "Art          77   50     70"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sort_values('Chemistry', axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 11. Choosing different sorting algorithms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "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>Lucy</th>\n",
       "      <th>Tom</th>\n",
       "      <th>Jacky</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Math</th>\n",
       "      <td>56</td>\n",
       "      <td>70</td>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Chemistry</th>\n",
       "      <td>60</td>\n",
       "      <td>67</td>\n",
       "      <td>85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Physics</th>\n",
       "      <td>75</td>\n",
       "      <td>90</td>\n",
       "      <td>76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Art</th>\n",
       "      <td>77</td>\n",
       "      <td>50</td>\n",
       "      <td>70</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Lucy  Tom  Jacky\n",
       "Math         56   70     90\n",
       "Chemistry    60   67     85\n",
       "Physics      75   90     76\n",
       "Art          77   50     70"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sort_values('Chemistry', kind='heapsort', axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Thanks for reading\n",
    "\n",
    "This is a notebook for the medium article [11 Tricks to Master Values Sorting in Pandas](https://bindichen.medium.com/11-tricks-to-master-values-sorting-in-pandas-7f2cfbf19730)\n",
    "\n",
    "Please check out article for instructions\n",
    "\n",
    "**License**: [BSD 2-Clause](https://opensource.org/licenses/BSD-2-Clause)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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