Python Feature Engineering Cookbook

How to do it...

First, let's import the necessary Python libraries:

1. Import the required Python libraries:

import pandas as pdimport matplotlib.pyplot as plt

2. Let's load a few variables from the dataset into a pandas dataframe and inspect the first five rows:

cols = ['AGE', 'NUMCHLD', 'INCOME', 'WEALTH1', 'MBCRAFT', 'MBGARDEN', 'MBBOOKS', 'MBCOLECT', 'MAGFAML','MAGFEM', 'MAGMALE']

data = pd.read_csv('cup98LRN.txt', usecols=cols)data.head()

After loading the dataset, this is how the output of head() looks like when we run it from a Jupyter Notebook:

3. Let's calculate the number of missing values in each variable:

data.isnull().sum()

The number ...