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");