pandas_method_chaining.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "d2a84bba",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from random import randint, choices"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "60d2bac4",
   "metadata": {},
   "source": [
    "# Chaining Methods in Pandas\n",
    "The `pandas.Series` and `pandas.DataFrame` methods do not modify objects *in-place*.  While many of these methods do provide `in_place` kwargs to allow the object to be modified in place, this typically leads to code that is harder to read.  \n",
    "\n",
    "This notebook demonstrates three different approaches to modifying (transforming) Pandas objects:\n",
    "\n",
    "1. Re-assignment of the modified object\n",
    "2. In-place modification of the object\n",
    "3. Method chaining\n",
    "\n",
    "It is usually best to chain methods--especially when more than one or two transformations are performed. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e0aa4b95",
   "metadata": {},
   "source": [
    "## DataFrame \n",
    "This small dataframe will be used for the examples."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "b787fdcd",
   "metadata": {},
   "outputs": [],
   "source": [
    "categories = list('ABCABC')\n",
    "colors = choices(\n",
    "    ['red', 'green', 'blue', 'orange', 'purple', 'yellow'],\n",
    "    k=len(categories)\n",
    ")\n",
    "sizes = [randint(1,10) for _ in categories]\n",
    "\n",
    "orig_df = pd.DataFrame(dict(\n",
    "    category=categories,\n",
    "    color=colors,\n",
    "    size=sizes\n",
    "))\n",
    "\n",
    "df = orig_df.copy()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "11bc77ae",
   "metadata": {},
   "source": [
    "# Reassignment\n",
    "Suppose we would like to perform the following modifications to the DataFrame `df`:\n",
    "\n",
    "1. Upcase the columns\n",
    "2. Upcase the values of the `color` column\n",
    "3. Divide the `size` column by a maximum size and rename to pct_of_max\n",
    "\n",
    "The following steps would accomplish this.  Note that we must reassign the result of any modification because methods do not operate in place by default. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "c0e004a1",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CATEGORY</th>\n",
       "      <th>COLOR</th>\n",
       "      <th>SIZE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>A</td>\n",
       "      <td>orange</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>B</td>\n",
       "      <td>red</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>C</td>\n",
       "      <td>green</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>A</td>\n",
       "      <td>purple</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>B</td>\n",
       "      <td>orange</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>C</td>\n",
       "      <td>yellow</td>\n",
       "      <td>10</td>\n",
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       "  </tbody>\n",
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      "text/plain": [
       "  CATEGORY   COLOR  SIZE\n",
       "0        A  orange    10\n",
       "1        B     red     3\n",
       "2        C   green     2\n",
       "3        A  purple     1\n",
       "4        B  orange     7\n",
       "5        C  yellow    10"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df.rename(columns=dict(zip(df.columns, df.columns.str.upper())))\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "2b93c9b9",
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   "outputs": [
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       "      <th></th>\n",
       "      <th>CATEGORY</th>\n",
       "      <th>COLOR</th>\n",
       "      <th>SIZE</th>\n",
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       "  </thead>\n",
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       "      <th>0</th>\n",
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       "      <td>B</td>\n",
       "      <td>RED</td>\n",
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       "      <th>2</th>\n",
       "      <td>C</td>\n",
       "      <td>GREEN</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>A</td>\n",
       "      <td>PURPLE</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>B</td>\n",
       "      <td>ORANGE</td>\n",
       "      <td>7</td>\n",
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       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>C</td>\n",
       "      <td>YELLOW</td>\n",
       "      <td>10</td>\n",
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      "text/plain": [
       "  CATEGORY   COLOR  SIZE\n",
       "0        A  ORANGE    10\n",
       "1        B     RED     3\n",
       "2        C   GREEN     2\n",
       "3        A  PURPLE     1\n",
       "4        B  ORANGE     7\n",
       "5        C  YELLOW    10"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Upcase the values of the COLOR column\n",
    "# Use assign\n",
    "df = df.assign(COLOR=df.COLOR.str.upper())\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "3d0c5c3f",
   "metadata": {},
   "outputs": [
    {
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       "      <th>COLOR</th>\n",
       "      <th>PCT_OF_MAX</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>0</th>\n",
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       "      <td>RED</td>\n",
       "      <td>0.3</td>\n",
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       "      <th>2</th>\n",
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       "      <td>A</td>\n",
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       "      <th>4</th>\n",
       "      <td>B</td>\n",
       "      <td>ORANGE</td>\n",
       "      <td>0.7</td>\n",
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       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>C</td>\n",
       "      <td>YELLOW</td>\n",
       "      <td>1.0</td>\n",
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       "  CATEGORY   COLOR  PCT_OF_MAX\n",
       "0        A  ORANGE         1.0\n",
       "1        B     RED         0.3\n",
       "2        C   GREEN         0.2\n",
       "3        A  PURPLE         0.1\n",
       "4        B  ORANGE         0.7\n",
       "5        C  YELLOW         1.0"
      ]
     },
     "execution_count": 24,
     "metadata": {},
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    }
   ],
   "source": [
    "# Divide size values by 10 and set the column name\n",
    "# to PCT_OF_MAX\n",
    "df = df.assign(PCT_OF_MAX=df.SIZE / 10.0)\n",
    "df = df.drop(columns=['SIZE'])\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9bbc8635",
   "metadata": {},
   "source": [
    "### All Reassignment Expressions Collected\n",
    "Here are all the expressions we used in this section combined into a single cell. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "1e566fb6",
   "metadata": {},
   "outputs": [
    {
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       "      <th>COLOR</th>\n",
       "      <th>PCT_OF_MAX</th>\n",
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       "      <td>RED</td>\n",
       "      <td>0.3</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>C</td>\n",
       "      <td>GREEN</td>\n",
       "      <td>0.2</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>A</td>\n",
       "      <td>PURPLE</td>\n",
       "      <td>0.1</td>\n",
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       "      <th>4</th>\n",
       "      <td>B</td>\n",
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       "      <td>0.7</td>\n",
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       "      <th>5</th>\n",
       "      <td>C</td>\n",
       "      <td>YELLOW</td>\n",
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       "  CATEGORY   COLOR  PCT_OF_MAX\n",
       "0        A  ORANGE         1.0\n",
       "1        B     RED         0.3\n",
       "2        C   GREEN         0.2\n",
       "3        A  PURPLE         0.1\n",
       "4        B  ORANGE         0.7\n",
       "5        C  YELLOW         1.0"
      ]
     },
     "execution_count": 38,
     "metadata": {},
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    }
   ],
   "source": [
    "df = orig_df.copy()\n",
    "df = df.rename(columns=dict(zip(df.columns, df.columns.str.upper())))\n",
    "df = df.assign(COLOR=df.COLOR.str.upper())\n",
    "df = df.assign(PCT_OF_MAX=df.SIZE / 10.0)\n",
    "df = df.drop(columns=['SIZE'])\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "67845624",
   "metadata": {},
   "source": [
    "## Inplace Modifications\n",
    "Recall that we need to use the original dataframe and make the following modifications:\n",
    "- Upcase the columns\n",
    "- Upcase the values of the color column\n",
    "- Divide the size column by a maximum size and rename to pct_of_max\n",
    "\n",
    "The following steps would accomplish this. Here, we do not need to reassign because we are using the `inplace=True` kwarg."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "aebae5e8",
   "metadata": {},
   "outputs": [
    {
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       "      <th>category</th>\n",
       "      <th>color</th>\n",
       "      <th>size</th>\n",
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       "  </thead>\n",
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       "      <th>0</th>\n",
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       "      <th>1</th>\n",
       "      <td>B</td>\n",
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       "      <th>2</th>\n",
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       "      <td>green</td>\n",
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       "      <th>3</th>\n",
       "      <td>A</td>\n",
       "      <td>purple</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>B</td>\n",
       "      <td>orange</td>\n",
       "      <td>7</td>\n",
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       "      <th>5</th>\n",
       "      <td>C</td>\n",
       "      <td>yellow</td>\n",
       "      <td>10</td>\n",
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       "  category   color  size\n",
       "0        A  orange    10\n",
       "1        B     red     3\n",
       "2        C   green     2\n",
       "3        A  purple     1\n",
       "4        B  orange     7\n",
       "5        C  yellow    10"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Start over with the original df\n",
    "df = orig_df.copy()\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "9d04ea82",
   "metadata": {},
   "outputs": [
    {
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       "      <th>COLOR</th>\n",
       "      <th>SIZE</th>\n",
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       "      <th>0</th>\n",
       "      <td>A</td>\n",
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       "      <th>2</th>\n",
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       "      <td>green</td>\n",
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       "      <th>3</th>\n",
       "      <td>A</td>\n",
       "      <td>purple</td>\n",
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       "      <th>4</th>\n",
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       "  CATEGORY   COLOR  SIZE\n",
       "0        A  orange    10\n",
       "1        B     red     3\n",
       "2        C   green     2\n",
       "3        A  purple     1\n",
       "4        B  orange     7\n",
       "5        C  yellow    10"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.rename(columns=dict(zip(df.columns, df.columns.str.upper())), inplace=True)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "f3634bea",
   "metadata": {},
   "outputs": [
    {
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       "      <td>red</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>C</td>\n",
       "      <td>green</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>A</td>\n",
       "      <td>purple</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>B</td>\n",
       "      <td>orange</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>C</td>\n",
       "      <td>yellow</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  CATEGORY   COLOR  SIZE\n",
       "0        A  orange    10\n",
       "1        B     red     3\n",
       "2        C   green     2\n",
       "3        A  purple     1\n",
       "4        B  orange     7\n",
       "5        C  yellow    10"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Upcase the values of the COLOR column\n",
    "# Use assign\n",
    "df.assign(COLOR=df.COLOR.str.upper(), inplace=True)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "4d3c4814",
   "metadata": {},
   "outputs": [
    {
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       "      <th>CATEGORY</th>\n",
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       "      <th>3</th>\n",
       "      <td>A</td>\n",
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       "    <tr>\n",
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       "  </tbody>\n",
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      "text/plain": [
       "  CATEGORY   COLOR  PCT_OF_MAX\n",
       "0        A  orange         1.0\n",
       "1        B     red         0.3\n",
       "2        C   green         0.2\n",
       "3        A  purple         0.1\n",
       "4        B  orange         0.7\n",
       "5        C  yellow         1.0"
      ]
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     "execution_count": 37,
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   "source": [
    "# Divide size values by 10 and set the column name\n",
    "# to PCT_OF_MAX\n",
    "\n",
    "# Note, assign() does not have an inplace option\n",
    "df = df.assign(PCT_OF_MAX=df.SIZE / 10.0)\n",
    "df.drop(columns=['SIZE'], inplace=True)\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "025193ee",
   "metadata": {},
   "source": [
    "### Inplace Expressions Combined\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "851d5e42",
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>CATEGORY</th>\n",
       "      <th>COLOR</th>\n",
       "      <th>PCT_OF_MAX</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>A</td>\n",
       "      <td>ORANGE</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>B</td>\n",
       "      <td>RED</td>\n",
       "      <td>0.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>C</td>\n",
       "      <td>GREEN</td>\n",
       "      <td>0.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>A</td>\n",
       "      <td>PURPLE</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>B</td>\n",
       "      <td>ORANGE</td>\n",
       "      <td>0.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>C</td>\n",
       "      <td>YELLOW</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
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      "text/plain": [
       "  CATEGORY   COLOR  PCT_OF_MAX\n",
       "0        A  ORANGE         1.0\n",
       "1        B     RED         0.3\n",
       "2        C   GREEN         0.2\n",
       "3        A  PURPLE         0.1\n",
       "4        B  ORANGE         0.7\n",
       "5        C  YELLOW         1.0"
      ]
     },
     "execution_count": 44,
     "metadata": {},
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   ],
   "source": [
    "df = orig_df.copy()\n",
    "df.rename(columns=dict(zip(df.columns, df.columns.str.upper())), inplace=True)\n",
    "df = df.assign(COLOR=df.COLOR.str.upper())\n",
    "df = df.assign(PCT_OF_MAX=df.SIZE / 10.0)\n",
    "df.drop(columns=['SIZE'], inplace=True)\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "376fea38",
   "metadata": {},
   "source": [
    "## Method Chaining\n",
    "Recall that we need to use the original dataframe and make the following modifications:\n",
    "- Upcase the columns\n",
    "- Upcase the values of the color column\n",
    "- Divide the size column by a maximum size and rename to pct_of_max\n",
    "\n",
    "Pandas methods return copies of the object they operate on.  Therefore we can *chain* methods to combine multiple operations.  Recall also that Python ignores whitespace inside parentheses, so we can cleanly format our transformations within them.\n",
    "\n",
    "In the case of method chaining, there are no intermediate expressions to include in a cell on their own, so this is a single cell solution."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "0c0ea20c",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>B</td>\n",
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       "      <td>0.3</td>\n",
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       "      <th>2</th>\n",
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       "      <td>0.2</td>\n",
       "    </tr>\n",
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       "      <th>3</th>\n",
       "      <td>A</td>\n",
       "      <td>PURPLE</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
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       "      <th>4</th>\n",
       "      <td>B</td>\n",
       "      <td>ORANGE</td>\n",
       "      <td>0.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>C</td>\n",
       "      <td>YELLOW</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  CATEGORY   COLOR  PCT_OF_MAX\n",
       "0        A  ORANGE         1.0\n",
       "1        B     RED         0.3\n",
       "2        C   GREEN         0.2\n",
       "3        A  PURPLE         0.1\n",
       "4        B  ORANGE         0.7\n",
       "5        C  YELLOW         1.0"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Note that the orig_df columns are referenced within chained methods\n",
    "df = (\n",
    "    orig_df.copy()\n",
    "    .rename(columns=dict(zip(orig_df.columns, orig_df.columns.str.upper())))\n",
    "    .assign(COLOR=orig_df.color.str.upper()) \n",
    "    .assign(PCT_OF_MAX=orig_df['size'] / 10.0)\n",
    "    .drop(columns=['SIZE'])\n",
    ")\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1cf8ea4d",
   "metadata": {},
   "source": [
    "**Note**: `orig_df['size']` is used to access the `size` column instead of `orig_df.size` because dataframes have a `size` attribute that cannot be overwritten by a column name.  \n",
    "\n",
    "One might argue that the chained method approach is visually similar to the inplace modification approach. The big differences in the chained method approach are:\n",
    "\n",
    "- improved readability\n",
    "- a single assignment statement (no confusion about what is stored to `df`)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1a9e9c0f",
   "metadata": {},
   "source": [
    "# Summary\n",
    "The method chaining approach is strongly encouraged as it encourages us to keep our modifications/tranformations in one place within a module or notebook.  The inplace and reassignment methods both allow for modifications to be made in multiple places within our code which can lead to confusion for readers/reviewers and problems debugging. \n",
    "\n",
    "The method chaining approach leads to transformations that *look like recipes* and are readable *at the location where the assignment is made.*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "06d6546e",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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