application_vnd.jupyter.stderr_output_1.png
train = dt.fread(os.path.join(root_path, 'train.csv')).to_pandas().query('weight > 0').pipe(reduce_mem_usage).reset_index(drop=True)
train['action'] = (train.resp > 0).astype(int)
resp_cols = [i for i in train.columns if 'resp' in i]
features_names = [i for i in train.columns if 'feature_' in i]
features_index = list(map(lambda x: int(re.sub('feature_', '', x)), features_names))
features_tuples = sorted(list(zip(features_names, features_index)), key=lambda x: x[1])
just_features = [i[0] for i in features_tuples]