我有一个代码，它输出特定月份在所有商店购买产品的次数；然而，我想知道如何获得3个条件的总和，python将添加特定月份和特定商店的产品。
这是我迄今为止的代码：
df = df.groupby(['Month_Bought'])['Amount_Bought'].sum()
print(df)
输出：
01-2020 27
02-2020 26
03-2020 24
04-2020 23
05-2020 31
06-2020 33
07-2020 26
08-2020 30
09-2020 33
10-2020 26
11-2020 30
12-2020 30
需要分离数据以使数据帧看起来像这样：
Store1 Store2
01-2020 3 24
02-2020 4 22
03-2020 8 16
04-2020 4 19
05-2020 10 21
06-2020 11 21
07-2020 12 14
08-2020 10 20
09-2020 3 30
10-2020 14 12
11-2020 21 9
12-2020 9 21
假设您的数据很长(一列包含购买产品的商店的值(，您可以按商店和月份进行分组：
import pandas as pd
records = [
{'Month_Bought':'01-2020', 'Amount_Bought':1, 'Store': 'Store1'},
{'Month_Bought':'01-2020', 'Amount_Bought':2, 'Store': 'Store2'},
{'Month_Bought':'02-2020', 'Amount_Bought':2, 'Store': 'Store1'},
{'Month_Bought':'02-2020', 'Amount_Bought':4, 'Store': 'Store2'}
]
df = pd.DataFrame.from_records(records)
# Initial dataframe
Month_Bought Amount_Bought Store
0 01-2020 1 Store1
1 01-2020 2 Store2
2 02-2020 2 Store1
3 02-2020 4 Store2
# Now groupby store and month
df_agg = df.groupby(['Store', 'Month_Bought'], as_index=False)['Amount_Bought'].sum()
# Convert from long to wide:
df_agg_pivot = df_agg.pivot(index='Month_Bought', columns='Store', values='Amount_Bought')
# Reformat
df_agg_pivot = df_agg_pivot.reset_index()
df_agg_pivot.columns.name = None
# Final result:
Month_Bought Store1 Store2
0 01-2020 1 2
1 02-2020 2 4