import numpy as np # linear algebra
import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)
import os
import gc # We're gonna be clearing memory a lot
import matplotlib.pyplot as plt
import seaborn as sns

p = sns.color_palette()

print('# File sizes')
for f in os.listdir('../input'):
    if 'zip' not in f:
        print(f.ljust(30) + str(round(os.path.getsize('../input/' + f) / 1000000, 2)) + 'MB')
        

df_train = pd.read_csv('../input/clicks_train.csv')
df_test = pd.read_csv('../input/clicks_test.csv')
print(type(df_train))
print(type(df_test))

sizes_train = df_train.groupby('display_id')['ad_id'].count().value_counts()
sizes_test = df_test.groupby('display_id')['ad_id'].count().value_counts()
sizes_train = sizes_train / np.sum(sizes_train)
sizes_test = sizes_test / np.sum(sizes_test)
print(type(sizes_train))
print(type(sizes_test))
print(sizes_train)