text_plain_output_1.png
import pandas as pd

df = pd.read_csv('../input/bank-additional-full.csv', sep=';', decimal='.', header=0, names=['age', 'job', 'marital', 'education', 'default', 'housing', 'loan', 'contact', 'month', 'day_of_week', 'duration', 'campaign', 'pdays', 'previous', 'poutcome', 'emp.var.rate', 'cons.price.idx', 'cons.conf.idx', 'euribor3m', 'nr.employed', 'target'])

print(df['age'].value_counts())
print(df['job'].value_counts())
print(df['marital'].value_counts())
print(df['education'].value_counts())
print(df['default'].value_counts())
print(df['housing'].value_counts())
print(df['loan'].value_counts())
print(df['contact'].value_counts())
print(df['month'].value_counts())
print(df['day_of_week'].value_counts())
print(df['duration'].value_counts())
print(df['campaign'].value_counts())
print(df['pdays'].value_counts())
print(df['previous'].value_counts())
print(df['poutcome'].value_counts())
print(df['emp.var.rate'].value_counts())
print(df['cons.price.idx'].value_counts())
print(df['cons.conf.idx'].value_counts())
print(df['euribor3m'].value_counts())
print(df['nr.employed'].value_counts())
print(df['target'].value_counts())