data-analysis/017-pandas-custom-sort/pandas-custom-sort.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Pandas Custom Sort\n",
    "\n",
    "This is a notebook for the medium article [How to do a Custom Sort on Pandas DataFrame](https://bindichen.medium.com/how-to-do-a-custom-sort-on-pandas-dataframe-ac18e7ea5320)\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": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "from pandas.api.types import CategoricalDtype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.DataFrame({\n",
    "    'cloth_id': [1001, 1002, 1003, 1004, 1005, 1006],\n",
    "    'size': ['S', 'XL', 'M', 'XS', 'L', 'S'],\n",
    "})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>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": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Take a look at the problem"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cloth_id</th>\n",
       "      <th>size</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1005</td>\n",
       "      <td>L</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1003</td>\n",
       "      <td>M</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>1</th>\n",
       "      <td>1002</td>\n",
       "      <td>XL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1004</td>\n",
       "      <td>XS</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   cloth_id size\n",
       "4      1005    L\n",
       "2      1003    M\n",
       "0      1001    S\n",
       "5      1006    S\n",
       "1      1002   XL\n",
       "3      1004   XS"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sort_values('size')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Create a new column for custom sorting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_mapping = pd.DataFrame({\n",
    "    'size': ['XS', 'S', 'M', 'L', 'XL'],\n",
    "})\n",
    "\n",
    "sort_mapping = df_mapping.reset_index().set_index('size')"
   ]
  },
  {
   "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>index</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>size</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>XS</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>S</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>L</th>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>XL</th>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      index\n",
       "size       \n",
       "XS        0\n",
       "S         1\n",
       "M         2\n",
       "L         3\n",
       "XL        4"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sort_mapping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<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",
       "      <th>size_num</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1001</td>\n",
       "      <td>S</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1002</td>\n",
       "      <td>XL</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1003</td>\n",
       "      <td>M</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1004</td>\n",
       "      <td>XS</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1005</td>\n",
       "      <td>L</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1006</td>\n",
       "      <td>S</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   cloth_id size  size_num\n",
       "0      1001    S         1\n",
       "1      1002   XL         4\n",
       "2      1003    M         2\n",
       "3      1004   XS         0\n",
       "4      1005    L         3\n",
       "5      1006    S         1"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create a new column size_num\n",
    "df['size_num'] = df['size'].map(sort_mapping['index'])\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<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",
       "      <th>size_num</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1004</td>\n",
       "      <td>XS</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1001</td>\n",
       "      <td>S</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1006</td>\n",
       "      <td>S</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1003</td>\n",
       "      <td>M</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1005</td>\n",
       "      <td>L</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1002</td>\n",
       "      <td>XL</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   cloth_id size  size_num\n",
       "3      1004   XS         0\n",
       "0      1001    S         1\n",
       "5      1006    S         1\n",
       "2      1003    M         2\n",
       "4      1005    L         3\n",
       "1      1002   XL         4"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sort_values('size_num')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. Cast data to category type with orderedness using `CategoricalDtype`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pandas.api.types import CategoricalDtype\n",
    "\n",
    "df = pd.DataFrame({\n",
    "    'cloth_id': [1001, 1002, 1003, 1004, 1005, 1006],\n",
    "    'size': ['S', 'XL', 'M', 'XS', 'L', 'S'],\n",
    "})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "cat_size_order = CategoricalDtype(\n",
    "    ['XS', 'S', 'M', 'L', 'XL'], \n",
    "    ordered=True\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['size'] = df['size'].astype(cat_size_order)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "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": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['size']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>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": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sort_values('size')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.1 View category codes property with the `Series.cat` accessor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "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>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": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from pandas.api.types import CategoricalDtype\n",
    "\n",
    "df = pd.DataFrame({\n",
    "    'cloth_id': [1001, 1002, 1003, 1004, 1005, 1006],\n",
    "    'size': ['S', 'XL', 'M', 'XS', 'L', 'S'],\n",
    "})\n",
    "\n",
    "cat_size_order = CategoricalDtype(\n",
    "    ['XS', 'S', 'M', 'L', 'XL'], \n",
    "    ordered=True\n",
    ")\n",
    "df['size'] = df['size'].astype(cat_size_order)\n",
    "df.sort_values('size')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['codes'] = df['size'].cat.codes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
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       "    }\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",
       "      <th>codes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1001</td>\n",
       "      <td>S</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1002</td>\n",
       "      <td>XL</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1003</td>\n",
       "      <td>M</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1004</td>\n",
       "      <td>XS</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1005</td>\n",
       "      <td>L</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1006</td>\n",
       "      <td>S</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   cloth_id size  codes\n",
       "0      1001    S      1\n",
       "1      1002   XL      4\n",
       "2      1003    M      2\n",
       "3      1004   XS      0\n",
       "4      1005    L      3\n",
       "5      1006    S      1"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 6 entries, 0 to 5\n",
      "Data columns (total 3 columns):\n",
      " #   Column    Non-Null Count  Dtype   \n",
      "---  ------    --------------  -----   \n",
      " 0   cloth_id  6 non-null      int64   \n",
      " 1   size      6 non-null      category\n",
      " 2   codes     6 non-null      int8    \n",
      "dtypes: category(1), int64(1), int8(1)\n",
      "memory usage: 388.0 bytes\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4. Sort by multiple variables"
   ]
  },
  {
   "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>order_id</th>\n",
       "      <th>customer_id</th>\n",
       "      <th>month</th>\n",
       "      <th>day_of_week</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1001</td>\n",
       "      <td>10</td>\n",
       "      <td>Feb</td>\n",
       "      <td>Mon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1002</td>\n",
       "      <td>12</td>\n",
       "      <td>Jan</td>\n",
       "      <td>Wed</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1003</td>\n",
       "      <td>12</td>\n",
       "      <td>Jan</td>\n",
       "      <td>Sun</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1004</td>\n",
       "      <td>12</td>\n",
       "      <td>Feb</td>\n",
       "      <td>Tue</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1005</td>\n",
       "      <td>10</td>\n",
       "      <td>Feb</td>\n",
       "      <td>Sat</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1006</td>\n",
       "      <td>10</td>\n",
       "      <td>Jan</td>\n",
       "      <td>Mon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1007</td>\n",
       "      <td>10</td>\n",
       "      <td>Feb</td>\n",
       "      <td>Thu</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   order_id  customer_id month day_of_week\n",
       "0      1001           10   Feb         Mon\n",
       "1      1002           12   Jan         Wed\n",
       "2      1003           12   Jan         Sun\n",
       "3      1004           12   Feb         Tue\n",
       "4      1005           10   Feb         Sat\n",
       "5      1006           10   Jan         Mon\n",
       "6      1007           10   Feb         Thu"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from pandas.api.types import CategoricalDtype\n",
    "\n",
    "df = pd.DataFrame({\n",
    "    'order_id': [1001, 1002, 1003, 1004, 1005, 1006, 1007],\n",
    "    'customer_id': [10, 12, 12, 12, 10, 10, 10],\n",
    "    'month': ['Feb', 'Jan', 'Jan', 'Feb', 'Feb', 'Jan', 'Feb'],\n",
    "    'day_of_week': ['Mon', 'Wed', 'Sun', 'Tue', 'Sat', 'Mon', 'Thu'],\n",
    "})\n",
    "\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "cat_day_of_week = CategoricalDtype(\n",
    "    ['Mon', 'Tue', 'Wed', 'Thu', 'Fri', 'Sat', 'Sun'], \n",
    "    ordered=True\n",
    ")\n",
    "cat_month = CategoricalDtype(\n",
    "    ['Jan', 'Feb', 'Mar', 'Apr'], \n",
    "    ordered=True,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['day_of_week'] = df['day_of_week'].astype(cat_day_of_week)\n",
    "df['month'] = df['month'].astype(cat_month)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "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>order_id</th>\n",
       "      <th>customer_id</th>\n",
       "      <th>month</th>\n",
       "      <th>day_of_week</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1006</td>\n",
       "      <td>10</td>\n",
       "      <td>Jan</td>\n",
       "      <td>Mon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1002</td>\n",
       "      <td>12</td>\n",
       "      <td>Jan</td>\n",
       "      <td>Wed</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1003</td>\n",
       "      <td>12</td>\n",
       "      <td>Jan</td>\n",
       "      <td>Sun</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1001</td>\n",
       "      <td>10</td>\n",
       "      <td>Feb</td>\n",
       "      <td>Mon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1004</td>\n",
       "      <td>12</td>\n",
       "      <td>Feb</td>\n",
       "      <td>Tue</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1007</td>\n",
       "      <td>10</td>\n",
       "      <td>Feb</td>\n",
       "      <td>Thu</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1005</td>\n",
       "      <td>10</td>\n",
       "      <td>Feb</td>\n",
       "      <td>Sat</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   order_id  customer_id month day_of_week\n",
       "5      1006           10   Jan         Mon\n",
       "1      1002           12   Jan         Wed\n",
       "2      1003           12   Jan         Sun\n",
       "0      1001           10   Feb         Mon\n",
       "3      1004           12   Feb         Tue\n",
       "6      1007           10   Feb         Thu\n",
       "4      1005           10   Feb         Sat"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sort_values(['month', 'day_of_week'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "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>order_id</th>\n",
       "      <th>customer_id</th>\n",
       "      <th>month</th>\n",
       "      <th>day_of_week</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1006</td>\n",
       "      <td>10</td>\n",
       "      <td>Jan</td>\n",
       "      <td>Mon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1001</td>\n",
       "      <td>10</td>\n",
       "      <td>Feb</td>\n",
       "      <td>Mon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1007</td>\n",
       "      <td>10</td>\n",
       "      <td>Feb</td>\n",
       "      <td>Thu</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1005</td>\n",
       "      <td>10</td>\n",
       "      <td>Feb</td>\n",
       "      <td>Sat</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1002</td>\n",
       "      <td>12</td>\n",
       "      <td>Jan</td>\n",
       "      <td>Wed</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1003</td>\n",
       "      <td>12</td>\n",
       "      <td>Jan</td>\n",
       "      <td>Sun</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1004</td>\n",
       "      <td>12</td>\n",
       "      <td>Feb</td>\n",
       "      <td>Tue</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   order_id  customer_id month day_of_week\n",
       "5      1006           10   Jan         Mon\n",
       "0      1001           10   Feb         Mon\n",
       "6      1007           10   Feb         Thu\n",
       "4      1005           10   Feb         Sat\n",
       "1      1002           12   Jan         Wed\n",
       "2      1003           12   Jan         Sun\n",
       "3      1004           12   Feb         Tue"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sort_values(['customer_id', 'month', 'day_of_week'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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