Impute Missing Values in Pandas

We will provide an example of how you can impute missing values in Pandas following the rules below:

• If the variable is numeric then impute the missing values with the mean
• If the variable is object dtype then impute the missing values with the mode

import pandas as pd
import numpy as np

df = pd.DataFrame({'id':list(range(10)),
                   'A':[10,9,8,7,np.nan,np.nan,20,15,12,np.nan], 
                   'B':["A","B","A","A",np.nan,"B","A","B",np.nan,"A"],
                   'C':[np.nan,"BB","CC","BB","BB","CC","AA","BB",np.nan,"AA"],
                   'D':[np.nan,20,18,22,18,17,19,np.nan,17,23]})
df

for i in df.columns:
    if (df[i].dtype=='object'):
        df[i].fillna(df[i].mode()[0], inplace=True)
    elif (df[i].dtype=='float64' or df[i].dtype=='int64'):
        df[i].fillna(df[i].mean(), inplace=True)

df