text_plain_output_1.png
import pandas as pd

train = pd.read_feather('../input/amex-train-dropped-1/train_dropped.feather')

typeTable = pd.concat([train.filter(regex='D_').dtypes, train.filter(regex='S_').dtypes], axis=1)

with pd.option_context('display.max_rows', 1000):
    print('Count of NaN of D: \n' + str(train.filter(regex='D_').isna().sum()))
print('Count of NaN of S: \n' + str(train.filter(regex='S_').isna().sum()))
print('Count of NaN of P: \n' + str(train.filter(regex='P_').isna().sum()))
print('Count of NaN of B: \n' + str(train.filter(regex='B_').isna().sum()))
print('Count of NaN of R: \n' + str(train.filter(regex='R_').isna().sum()))