Python Pandas если столбец содержит определенный int

Question

Я хочу ограничить свой вывод, как я сделал с .str.contains(), но на этот раз с int. Как заставить этот код работать с (обычным) Python с помощью Pandas?

import pandas as pd 

df = pd.DataFrame({ 
     'yearweek' : [201604, 201604, 201604, 201604, 201605, 201605, 201605, 201605, 201606, 201606, 201606], 
     'manufacturer' : ['F', 'F', 'S', 'S', 'F', 'F', 'S', 'S', 'F', 'S', 'S'], 
     'reprint_reason_id' : [1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1], 
     'tot_volume' : [100, 150, 80, 90, 120, 98, 77, 250, 33, 110, 56]}) 

    df1 = df.groupby(by=['yearweek', 'manufacturer']) ['tot_volume'].sum() 
    df2 = df1.reset_index() 
    df3 = df2[df2['manufacturer'].str.contains('F') ] 
    df4 = df3.reset_index() 
    df5 = df4[df4['yearweek'].int.contains(201604)] 
    print df5 

Answer 1

Я думаю, что вы можете использовать boolean indexing:

df = pd.DataFrame({ 
     'yearweek' : [201604, 201604, 201604, 201604, 201605, 201605, 201605, 201605, 201606, 201606, 201606], 
     'manufacturer' : ['F', 'F', 'S', 'S', 'F', 'F', 'S', 'S', 'F', 'S', 'S'], 
     'reprint_reason_id' : [1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1], 
     'tot_volume' : [100, 150, 80, 90, 120, 98, 77, 250, 33, 110, 56]}) 

#convert to int is not necessary in this sample 
#df['yearweek'] = df['yearweek'].astype(int) 

df1 = df.groupby(by=['yearweek', 'manufacturer'])['tot_volume'].sum().reset_index() 
#or you can use 
#df1 = df.groupby(by=['yearweek', 'manufacturer'], as_index=False)['tot_volume'].sum() 
print df1 
    yearweek manufacturer tot_volume 
0 201604   F   250 
1 201604   S   170 
2 201605   F   218 
3 201605   S   327 
4 201606   F   33 
5 201606   S   166 

print (df1['manufacturer'].str.contains('F')) & (df1['yearweek'] == 201604) 
0  True 
1 False 
2 False 
3 False 
4 False 
5 False 
dtype: bool 

df2 = df1[(df1['manufacturer'].str.contains('F')) & (df1['yearweek'] == 201604)] 
print df2 
    yearweek manufacturer tot_volume 
0 201604   F   250 

Answer 2

Вы можете использовать .astype(int) для преобразования, что integer. Как это df4[df4['yearweek'].astype(int).contains(201604)]