10. Exploratory Data Analysis

10.1. Missing Values Analysis

Interesting way to plot missing values.

import missingno as msno

missingdata_df = data.columns[data.isnull().any()].tolist()
msno.matrix(data[missingdata_df])

10.2. Correlation Matrix

10.2.1. Plotting correlation Matrix

import seaborn as sns
import matplotlib.pyplot as plt

fig, ax = plt.subplots(figsize=(15, 15))
ax = sns.heatmap(corr, annot=False, ax=ax, cmap="Blues");
ax.set_title("Cramer V Correlation between Variables");