Writing the data to local

# Write out final data for each feature set
sampleX_train[raw_original_features].to_csv('train_features_raw.csv', index=False)
sampleX_val[raw_original_features].to_csv('val_features_raw.csv', index=False)
sampleX_test[raw_original_features].to_csv('test_features_raw.csv', index=False)

X_train[all_features].to_csv('train_features_all.csv', index=False)
X_val[all_features].to_csv('val_features_all.csv', index=False)
X_test[all_features].to_csv('test_features_all.csv', index=False)

df_train[transformed_features].to_csv('train_features_transformed.csv', index=False)
df_val[transformed_features].to_csv('val_features_transformed.csv', index=False)
df_test[transformed_features].to_csv('test_features_transformed.csv', index=False)

X_train[reduced_features].to_csv('train_features_reduced.csv', index=False)
X_val[reduced_features].to_csv('val_features_reduced.csv', index=False)
X_test[reduced_features].to_csv('test_features_reduced.csv', index=False)

# Write out labels to final directory
sampley_train.to_csv('train_labels.csv', index=False)
sampley_val.to_csv('val_labels.csv', index=False)
sampley_test.to_csv('test_labels.csv', index=False)