top10_corr.py

# Correlation DF of all classes
corr = final_df.corr().iloc[[-1],:-1]

# Sorting our Correlation DF by their absolute values and selecting the top 10
top10_corr = corr.transpose().apply(abs).sort_values(by='Decision', ascending=False)[:10]

# Creating a new DF with the features from the top10_corr and joing the 'Decision' class labels
top10_corr_df = final_df[top10_corr.index].join(final_df.Decision)

# Pickling the DF for use in our Classification models
with open("top10_corr_df.pkl", "wb") as fp:
    pickle.dump(top10_corr_df, fp)