2. Exploratory Data Analysis and Visualization

Activity 2.01: Summary Statistics and Missing Values

The steps to complete this activity are as follows:

1. Import the required libraries:

   import json
   import pandas as pd
   import numpy as np
   import missingno as msno
   from sklearn.impute import SimpleImputer
   import matplotlib.pyplot as plt
   import seaborn as sns

2. Read the data. Use pandas' .read_csv method to read the CSV file into a pandas DataFrame:

   data = pd.read_csv('../Datasets/house_prices.csv')

3. Use pandas' .info() and .describe() methods to view the summary statistics of the dataset:

   data.info()
   data.describe().T

   The output of info() will be as follows:

   Figure 2.50: The output of the info() method (abbreviated)

   The output of describe() will be as follows:

   Figure 2.51: The output of the describe() method (abbreviated)

4. Find the total count and total percentage of missing values in each column of the DataFrame and display them for columns having at least...