1.1_Creating_functions.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import datetime as dt\n",
    "%matplotlib inline\n",
    "plt.style.use('ggplot')\n",
    "pd.set_option('display.max_rows', 50)\n",
    "pd.set_option('display.max_columns', 30)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('https://raw.githubusercontent.com/anilkumarpanda/python-training-2021/main/data/UCI_Credit_Card.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>LIMIT_BAL</th>\n",
       "      <th>SEX</th>\n",
       "      <th>EDUCATION</th>\n",
       "      <th>MARRIAGE</th>\n",
       "      <th>AGE</th>\n",
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       "      <th>BILL_AMT4</th>\n",
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       "      <td>3</td>\n",
       "      <td>90000.0</td>\n",
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       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>5000.0</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>50000.0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>37</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>46990.0</td>\n",
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       "      <td>28314.0</td>\n",
       "      <td>28959.0</td>\n",
       "      <td>29547.0</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>2019.0</td>\n",
       "      <td>1200.0</td>\n",
       "      <td>1100.0</td>\n",
       "      <td>1069.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
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       "      <td>50000.0</td>\n",
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       "   ID  LIMIT_BAL  SEX  EDUCATION  MARRIAGE  AGE  PAY_0  PAY_2  PAY_3  PAY_4  \\\n",
       "0   1    20000.0    2          2         1   24      2      2     -1     -1   \n",
       "1   2   120000.0    2          2         2   26     -1      2      0      0   \n",
       "2   3    90000.0    2          2         2   34      0      0      0      0   \n",
       "3   4    50000.0    2          2         1   37      0      0      0      0   \n",
       "4   5    50000.0    1          2         1   57     -1      0     -1      0   \n",
       "\n",
       "   PAY_5  PAY_6  BILL_AMT1  BILL_AMT2  BILL_AMT3  BILL_AMT4  BILL_AMT5  \\\n",
       "0     -2     -2     3913.0     3102.0      689.0        0.0        0.0   \n",
       "1      0      2     2682.0     1725.0     2682.0     3272.0     3455.0   \n",
       "2      0      0    29239.0    14027.0    13559.0    14331.0    14948.0   \n",
       "3      0      0    46990.0    48233.0    49291.0    28314.0    28959.0   \n",
       "4      0      0     8617.0     5670.0    35835.0    20940.0    19146.0   \n",
       "\n",
       "   BILL_AMT6  PAY_AMT1  PAY_AMT2  PAY_AMT3  PAY_AMT4  PAY_AMT5  PAY_AMT6  \\\n",
       "0        0.0       0.0     689.0       0.0       0.0       0.0       0.0   \n",
       "1     3261.0       0.0    1000.0    1000.0    1000.0       0.0    2000.0   \n",
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       "4    19131.0    2000.0   36681.0   10000.0    9000.0     689.0     679.0   \n",
       "\n",
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       "0                           1  \n",
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     "execution_count": 33,
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   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "   ID  LIMIT_BAL  SEX  EDUCATION  MARRIAGE  AGE  PAY_0  PAY_2  PAY_3  PAY_4  \\\n",
       "0   1          0    2          2         1   24      2      2     -1     -1   \n",
       "1   2          0    2          2         2   26     -1      2      0      0   \n",
       "2   3          0    2          2         2   34      0      0      0      0   \n",
       "3   4          0    2          2         1   37      0      0      0      0   \n",
       "4   5          0    1          2         1   57     -1      0     -1      0   \n",
       "\n",
       "   PAY_5  PAY_6  BILL_AMT1  BILL_AMT2  BILL_AMT3  BILL_AMT4  BILL_AMT5  \\\n",
       "0     -2     -2     3913.0     3102.0      689.0        0.0        0.0   \n",
       "1      0      2     2682.0     1725.0     2682.0     3272.0     3455.0   \n",
       "2      0      0    29239.0    14027.0    13559.0    14331.0    14948.0   \n",
       "3      0      0    46990.0    48233.0    49291.0    28314.0    28959.0   \n",
       "4      0      0     8617.0     5670.0    35835.0    20940.0    19146.0   \n",
       "\n",
       "   BILL_AMT6  PAY_AMT1  PAY_AMT2  PAY_AMT3  PAY_AMT4  PAY_AMT5  PAY_AMT6  \\\n",
       "0        0.0       0.0     689.0       0.0       0.0       0.0       0.0   \n",
       "1     3261.0       0.0    1000.0    1000.0    1000.0       0.0    2000.0   \n",
       "2    15549.0    1518.0    1500.0    1000.0    1000.0    1000.0    5000.0   \n",
       "3    29547.0    2000.0    2019.0    1200.0    1100.0    1069.0    1000.0   \n",
       "4    19131.0    2000.0   36681.0   10000.0    9000.0     689.0     679.0   \n",
       "\n",
       "   default.payment.next.month  \n",
       "0                           1  \n",
       "1                           1  \n",
       "2                           0  \n",
       "3                           0  \n",
       "4                           0  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def function_with_good_docstring(df,column):\n",
    "    \"\"\"\n",
    "    Function to change the dataframe.\n",
    "    Args :\n",
    "        df(Dataframe) : Dataframe to change\n",
    "        column(String): Column name\n",
    "        \n",
    "    Returns:\n",
    "        df(Dataframe) : Returns changed dataframe. \n",
    "    \"\"\"\n",
    "    df[column] = 0\n",
    "    return df\n",
    "\n",
    "function_with_good_docstring(df, column='LIMIT_BAL').head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>LIMIT_BAL</th>\n",
       "      <th>SEX</th>\n",
       "      <th>EDUCATION</th>\n",
       "      <th>MARRIAGE</th>\n",
       "      <th>AGE</th>\n",
       "      <th>PAY_0</th>\n",
       "      <th>PAY_2</th>\n",
       "      <th>PAY_3</th>\n",
       "      <th>PAY_4</th>\n",
       "      <th>PAY_5</th>\n",
       "      <th>PAY_6</th>\n",
       "      <th>BILL_AMT1</th>\n",
       "      <th>BILL_AMT2</th>\n",
       "      <th>BILL_AMT3</th>\n",
       "      <th>BILL_AMT4</th>\n",
       "      <th>BILL_AMT5</th>\n",
       "      <th>BILL_AMT6</th>\n",
       "      <th>PAY_AMT1</th>\n",
       "      <th>PAY_AMT2</th>\n",
       "      <th>PAY_AMT3</th>\n",
       "      <th>PAY_AMT4</th>\n",
       "      <th>PAY_AMT5</th>\n",
       "      <th>PAY_AMT6</th>\n",
       "      <th>default.payment.next.month</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>20000.0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>24</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>-2</td>\n",
       "      <td>-2</td>\n",
       "      <td>3913.0</td>\n",
       "      <td>3102.0</td>\n",
       "      <td>689.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>689.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>120000.0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>26</td>\n",
       "      <td>-1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2682.0</td>\n",
       "      <td>1725.0</td>\n",
       "      <td>2682.0</td>\n",
       "      <td>3272.0</td>\n",
       "      <td>3455.0</td>\n",
       "      <td>3261.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>90000.0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>34</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>29239.0</td>\n",
       "      <td>14027.0</td>\n",
       "      <td>13559.0</td>\n",
       "      <td>14331.0</td>\n",
       "      <td>14948.0</td>\n",
       "      <td>15549.0</td>\n",
       "      <td>1518.0</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>50000.0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>37</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>46990.0</td>\n",
       "      <td>48233.0</td>\n",
       "      <td>49291.0</td>\n",
       "      <td>28314.0</td>\n",
       "      <td>28959.0</td>\n",
       "      <td>29547.0</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>2019.0</td>\n",
       "      <td>1200.0</td>\n",
       "      <td>1100.0</td>\n",
       "      <td>1069.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>50000.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>57</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8617.0</td>\n",
       "      <td>5670.0</td>\n",
       "      <td>35835.0</td>\n",
       "      <td>20940.0</td>\n",
       "      <td>19146.0</td>\n",
       "      <td>19131.0</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>36681.0</td>\n",
       "      <td>10000.0</td>\n",
       "      <td>9000.0</td>\n",
       "      <td>689.0</td>\n",
       "      <td>679.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ID  LIMIT_BAL  SEX  EDUCATION  MARRIAGE  AGE  PAY_0  PAY_2  PAY_3  PAY_4  \\\n",
       "0   1    20000.0    2          2         1   24      2      2     -1     -1   \n",
       "1   2   120000.0    2          2         2   26     -1      2      0      0   \n",
       "2   3    90000.0    2          2         2   34      0      0      0      0   \n",
       "3   4    50000.0    2          2         1   37      0      0      0      0   \n",
       "4   5    50000.0    1          2         1   57     -1      0     -1      0   \n",
       "\n",
       "   PAY_5  PAY_6  BILL_AMT1  BILL_AMT2  BILL_AMT3  BILL_AMT4  BILL_AMT5  \\\n",
       "0     -2     -2     3913.0     3102.0      689.0        0.0        0.0   \n",
       "1      0      2     2682.0     1725.0     2682.0     3272.0     3455.0   \n",
       "2      0      0    29239.0    14027.0    13559.0    14331.0    14948.0   \n",
       "3      0      0    46990.0    48233.0    49291.0    28314.0    28959.0   \n",
       "4      0      0     8617.0     5670.0    35835.0    20940.0    19146.0   \n",
       "\n",
       "   BILL_AMT6  PAY_AMT1  PAY_AMT2  PAY_AMT3  PAY_AMT4  PAY_AMT5  PAY_AMT6  \\\n",
       "0        0.0       0.0     689.0       0.0       0.0       0.0       0.0   \n",
       "1     3261.0       0.0    1000.0    1000.0    1000.0       0.0    2000.0   \n",
       "2    15549.0    1518.0    1500.0    1000.0    1000.0    1000.0    5000.0   \n",
       "3    29547.0    2000.0    2019.0    1200.0    1100.0    1069.0    1000.0   \n",
       "4    19131.0    2000.0   36681.0   10000.0    9000.0     689.0     679.0   \n",
       "\n",
       "   default.payment.next.month  \n",
       "0                           1  \n",
       "1                           1  \n",
       "2                           0  \n",
       "3                           0  \n",
       "4                           0  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Do you notice how the dataframe is now permanently changed after applying the function?\n",
    "\n",
    "This is subtle but we most likely do not want this. We want the original object to stay the same and a separate transformed dataframe. How do we achieve this?\n",
    "\n",
    "Enter `.copy()`\n",
    "\n",
    "This allows us to stop continously overwriting our objects"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Chaining\n",
    "\n",
    "Pandas has a great method for chaining that most people don't seem to use. \n",
    "Let's take a look at some common (and mostly bad) methods of applying multiple functions\n",
    "\n",
    "Let's say we need to calculate the following for the balance (x):\n",
    "\n",
    "`y = 3x**2 + 4`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "def first_transformation(df, column='LIMIT_BAL'):\n",
    "    \"\"\"\n",
    "    Squares a given column. \n",
    "    \n",
    "    Args:\n",
    "        df (pandas DataFrame): The transactional data\n",
    "        column (str): The name of the column which we square\n",
    "        \n",
    "    Returns:\n",
    "        df with squared column\n",
    "    \"\"\"\n",
    "    df[column] = df[column]**2\n",
    "    return df\n",
    "\n",
    "def second_transformation(df, column='LIMIT_BAL', factor=3):\n",
    "    \"\"\"\n",
    "    Multiplies a given column by a given factor. \n",
    "    \n",
    "    Args:\n",
    "        df (pandas DataFrame): The transactional data\n",
    "        column (str): The name of the column on which we multiple the factor.\n",
    "        factor (float): The factor\n",
    "        \n",
    "    Returns:\n",
    "        df with multipled column\n",
    "    \"\"\"\n",
    "    df[column] = df[column]*factor\n",
    "    return df\n",
    "\n",
    "def third_transformation(df, column='LIMIT_BAL', factor=4):\n",
    "    \"\"\"\n",
    "    Adds a given factor to a given column. \n",
    "    \n",
    "    Args:\n",
    "        df (pandas DataFrame): The transactional data\n",
    "        column (str): The name of the column on which we add the factor.\n",
    "        factor (float): The factor\n",
    "        \n",
    "    Returns:\n",
    "        df with divided column\n",
    "    \"\"\"\n",
    "    df[column] = df[column] + factor\n",
    "    return df\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Ugly method number 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('data/UCI_Credit_Card.csv')\n",
    "df = third_transformation(second_transformation(first_transformation(df)))"
   ]
  },
  {
   "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>ID</th>\n",
       "      <th>LIMIT_BAL</th>\n",
       "      <th>SEX</th>\n",
       "      <th>EDUCATION</th>\n",
       "      <th>MARRIAGE</th>\n",
       "      <th>AGE</th>\n",
       "      <th>PAY_0</th>\n",
       "      <th>PAY_2</th>\n",
       "      <th>PAY_3</th>\n",
       "      <th>PAY_4</th>\n",
       "      <th>PAY_5</th>\n",
       "      <th>PAY_6</th>\n",
       "      <th>BILL_AMT1</th>\n",
       "      <th>BILL_AMT2</th>\n",
       "      <th>BILL_AMT3</th>\n",
       "      <th>BILL_AMT4</th>\n",
       "      <th>BILL_AMT5</th>\n",
       "      <th>BILL_AMT6</th>\n",
       "      <th>PAY_AMT1</th>\n",
       "      <th>PAY_AMT2</th>\n",
       "      <th>PAY_AMT3</th>\n",
       "      <th>PAY_AMT4</th>\n",
       "      <th>PAY_AMT5</th>\n",
       "      <th>PAY_AMT6</th>\n",
       "      <th>default.payment.next.month</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1.200000e+09</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>24</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>-2</td>\n",
       "      <td>-2</td>\n",
       "      <td>3913.0</td>\n",
       "      <td>3102.0</td>\n",
       "      <td>689.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>689.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>4.320000e+10</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>26</td>\n",
       "      <td>-1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2682.0</td>\n",
       "      <td>1725.0</td>\n",
       "      <td>2682.0</td>\n",
       "      <td>3272.0</td>\n",
       "      <td>3455.0</td>\n",
       "      <td>3261.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>2.430000e+10</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>34</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>29239.0</td>\n",
       "      <td>14027.0</td>\n",
       "      <td>13559.0</td>\n",
       "      <td>14331.0</td>\n",
       "      <td>14948.0</td>\n",
       "      <td>15549.0</td>\n",
       "      <td>1518.0</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>7.500000e+09</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>37</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>46990.0</td>\n",
       "      <td>48233.0</td>\n",
       "      <td>49291.0</td>\n",
       "      <td>28314.0</td>\n",
       "      <td>28959.0</td>\n",
       "      <td>29547.0</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>2019.0</td>\n",
       "      <td>1200.0</td>\n",
       "      <td>1100.0</td>\n",
       "      <td>1069.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>7.500000e+09</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>57</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8617.0</td>\n",
       "      <td>5670.0</td>\n",
       "      <td>35835.0</td>\n",
       "      <td>20940.0</td>\n",
       "      <td>19146.0</td>\n",
       "      <td>19131.0</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>36681.0</td>\n",
       "      <td>10000.0</td>\n",
       "      <td>9000.0</td>\n",
       "      <td>689.0</td>\n",
       "      <td>679.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ID     LIMIT_BAL  SEX  EDUCATION  MARRIAGE  AGE  PAY_0  PAY_2  PAY_3  \\\n",
       "0   1  1.200000e+09    2          2         1   24      2      2     -1   \n",
       "1   2  4.320000e+10    2          2         2   26     -1      2      0   \n",
       "2   3  2.430000e+10    2          2         2   34      0      0      0   \n",
       "3   4  7.500000e+09    2          2         1   37      0      0      0   \n",
       "4   5  7.500000e+09    1          2         1   57     -1      0     -1   \n",
       "\n",
       "   PAY_4  PAY_5  PAY_6  BILL_AMT1  BILL_AMT2  BILL_AMT3  BILL_AMT4  BILL_AMT5  \\\n",
       "0     -1     -2     -2     3913.0     3102.0      689.0        0.0        0.0   \n",
       "1      0      0      2     2682.0     1725.0     2682.0     3272.0     3455.0   \n",
       "2      0      0      0    29239.0    14027.0    13559.0    14331.0    14948.0   \n",
       "3      0      0      0    46990.0    48233.0    49291.0    28314.0    28959.0   \n",
       "4      0      0      0     8617.0     5670.0    35835.0    20940.0    19146.0   \n",
       "\n",
       "   BILL_AMT6  PAY_AMT1  PAY_AMT2  PAY_AMT3  PAY_AMT4  PAY_AMT5  PAY_AMT6  \\\n",
       "0        0.0       0.0     689.0       0.0       0.0       0.0       0.0   \n",
       "1     3261.0       0.0    1000.0    1000.0    1000.0       0.0    2000.0   \n",
       "2    15549.0    1518.0    1500.0    1000.0    1000.0    1000.0    5000.0   \n",
       "3    29547.0    2000.0    2019.0    1200.0    1100.0    1069.0    1000.0   \n",
       "4    19131.0    2000.0   36681.0   10000.0    9000.0     689.0     679.0   \n",
       "\n",
       "   default.payment.next.month  \n",
       "0                           1  \n",
       "1                           1  \n",
       "2                           0  \n",
       "3                           0  \n",
       "4                           0  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Ugly (but common) method number 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('data/UCI_Credit_Card.csv')\n",
    "df = df.copy()\n",
    "df = first_transformation(df)\n",
    "df = second_transformation(df)\n",
    "df = third_transformation(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "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>LIMIT_BAL</th>\n",
       "      <th>SEX</th>\n",
       "      <th>EDUCATION</th>\n",
       "      <th>MARRIAGE</th>\n",
       "      <th>AGE</th>\n",
       "      <th>PAY_0</th>\n",
       "      <th>PAY_2</th>\n",
       "      <th>PAY_3</th>\n",
       "      <th>PAY_4</th>\n",
       "      <th>PAY_5</th>\n",
       "      <th>PAY_6</th>\n",
       "      <th>BILL_AMT1</th>\n",
       "      <th>BILL_AMT2</th>\n",
       "      <th>BILL_AMT3</th>\n",
       "      <th>BILL_AMT4</th>\n",
       "      <th>BILL_AMT5</th>\n",
       "      <th>BILL_AMT6</th>\n",
       "      <th>PAY_AMT1</th>\n",
       "      <th>PAY_AMT2</th>\n",
       "      <th>PAY_AMT3</th>\n",
       "      <th>PAY_AMT4</th>\n",
       "      <th>PAY_AMT5</th>\n",
       "      <th>PAY_AMT6</th>\n",
       "      <th>default.payment.next.month</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1.200000e+09</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>24</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>-2</td>\n",
       "      <td>-2</td>\n",
       "      <td>3913.0</td>\n",
       "      <td>3102.0</td>\n",
       "      <td>689.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>689.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>4.320000e+10</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>26</td>\n",
       "      <td>-1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2682.0</td>\n",
       "      <td>1725.0</td>\n",
       "      <td>2682.0</td>\n",
       "      <td>3272.0</td>\n",
       "      <td>3455.0</td>\n",
       "      <td>3261.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>2.430000e+10</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>34</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>29239.0</td>\n",
       "      <td>14027.0</td>\n",
       "      <td>13559.0</td>\n",
       "      <td>14331.0</td>\n",
       "      <td>14948.0</td>\n",
       "      <td>15549.0</td>\n",
       "      <td>1518.0</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>7.500000e+09</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>37</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>46990.0</td>\n",
       "      <td>48233.0</td>\n",
       "      <td>49291.0</td>\n",
       "      <td>28314.0</td>\n",
       "      <td>28959.0</td>\n",
       "      <td>29547.0</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>2019.0</td>\n",
       "      <td>1200.0</td>\n",
       "      <td>1100.0</td>\n",
       "      <td>1069.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>7.500000e+09</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>57</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8617.0</td>\n",
       "      <td>5670.0</td>\n",
       "      <td>35835.0</td>\n",
       "      <td>20940.0</td>\n",
       "      <td>19146.0</td>\n",
       "      <td>19131.0</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>36681.0</td>\n",
       "      <td>10000.0</td>\n",
       "      <td>9000.0</td>\n",
       "      <td>689.0</td>\n",
       "      <td>679.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ID     LIMIT_BAL  SEX  EDUCATION  MARRIAGE  AGE  PAY_0  PAY_2  PAY_3  \\\n",
       "0   1  1.200000e+09    2          2         1   24      2      2     -1   \n",
       "1   2  4.320000e+10    2          2         2   26     -1      2      0   \n",
       "2   3  2.430000e+10    2          2         2   34      0      0      0   \n",
       "3   4  7.500000e+09    2          2         1   37      0      0      0   \n",
       "4   5  7.500000e+09    1          2         1   57     -1      0     -1   \n",
       "\n",
       "   PAY_4  PAY_5  PAY_6  BILL_AMT1  BILL_AMT2  BILL_AMT3  BILL_AMT4  BILL_AMT5  \\\n",
       "0     -1     -2     -2     3913.0     3102.0      689.0        0.0        0.0   \n",
       "1      0      0      2     2682.0     1725.0     2682.0     3272.0     3455.0   \n",
       "2      0      0      0    29239.0    14027.0    13559.0    14331.0    14948.0   \n",
       "3      0      0      0    46990.0    48233.0    49291.0    28314.0    28959.0   \n",
       "4      0      0      0     8617.0     5670.0    35835.0    20940.0    19146.0   \n",
       "\n",
       "   BILL_AMT6  PAY_AMT1  PAY_AMT2  PAY_AMT3  PAY_AMT4  PAY_AMT5  PAY_AMT6  \\\n",
       "0        0.0       0.0     689.0       0.0       0.0       0.0       0.0   \n",
       "1     3261.0       0.0    1000.0    1000.0    1000.0       0.0    2000.0   \n",
       "2    15549.0    1518.0    1500.0    1000.0    1000.0    1000.0    5000.0   \n",
       "3    29547.0    2000.0    2019.0    1200.0    1100.0    1069.0    1000.0   \n",
       "4    19131.0    2000.0   36681.0   10000.0    9000.0     689.0     679.0   \n",
       "\n",
       "   default.payment.next.month  \n",
       "0                           1  \n",
       "1                           1  \n",
       "2                           0  \n",
       "3                           0  \n",
       "4                           0  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Best practice"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "def read_data(path):\n",
    "    # What is this function missing?\n",
    "    return pd.read_csv(path)\n",
    "\n",
    "def copy_df(df):\n",
    "    # What is this function missing?\n",
    "    return df.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = read_data(path='data/UCI_Credit_Card.csv')\n",
    "\n",
    "df = (\n",
    "    copy_df(df)\n",
    "    .pipe(first_transformation)\n",
    "    .pipe(second_transformation)\n",
    "    .pipe(third_transformation)\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Note the differences with the arguments\n",
    "\n",
    "#### Exercise.\n",
    "1. Write a function that squares BILL_AMT1 if MARRIAGE==1. Save this in a column called \"BILL_MANIPULATION\".\n",
    "2. Write another function that divides this new column by LIMIT_BAL. Overwrite BILL_MANIPULATION.\n",
    "3. Write a final function that sets BILL_AMT2 to 0 if BILL_MANIPULATION > 500\n",
    "4. Chain all of these together\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Exercise\n",
    "\n",
    "Write a function that takes as parameter a number and returns True if it is even and False if it is odd."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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