image_output_1.png
import pandas as pd

import pandas as pd
import numpy as np
import seaborn as sns
baseDir = '../input/'
people = pd.read_csv('{0}people.csv'.format(baseDir)).drop_duplicates()
act_train = pd.read_csv('{0}act_train.csv'.format(baseDir)).drop_duplicates()
act_test = pd.read_csv('{0}act_test.csv'.format(baseDir)).drop_duplicates()

unqTrain = act_train.drop(['activity_id', 'outcome'], axis=1).drop_duplicates()
unqTest = act_test.drop(['activity_id'], axis=1).drop_duplicates()
total = pd.concat([unqTrain, unqTest], axis=0)
print('{0} rows duplicated between train and test'.format(len(total) - len(total.drop_duplicates())))
print('{0} columns diff between train and test'.format([c for c in act_train.columns if c not in act_test.columns and c != 'outcome']))