PANDAS, CSV FILES, AND MISSING DATA

This section contains several subsections with Python-based code samples that create Pandas data frames and then replace missing values in the data frames. First we’ll look at small CSV files with one column and then we’ll look at small CSV files with two columns. Later we’ll look at skewed CSV files as well as multi-row CSV files.

Single Column CSV Files

Listing 3.1 displays the contents of the CSV file one_char_column1.csv and Listing 3.2 displays the contents of one_char_column1.py that fills in missing values in the CSV file.

Listing 3.1: one_char_column1.csv

gender
Male
Male
NaN
Female
Male

Listing 3.2: one_char_column1.py

import pandas as pd

df1 = pd.read_csv('one_char_column1.csv')

print("=> initial dataframe contents:")
print(df1)
print()

df = df1.fillna("FEMALE")
print("dataframe after fillna():")
print(df)
print()

Listing 3.2 starts with two import statements and then initializes...