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)

train = pd.merge(act_train, people, on='people_id', how='left')
print(train.shape)
test = pd.merge(act_test, people, on='people_id', how='left')
print(test.shape)
print(train.columns)