I have following DataFrame:
data = {'year': [2010, 2010, 2011, 2012, 2011, 2012, 2010, 2011, 2012, 2013],
'store_number': ['1944', '1945', '1946', '1947', '1948', '1949', '1947', '1948', '1949', '1947'],
'retailer_name': ['Walmart','Walmart', 'CRV', 'CRV', 'CRV', 'Walmart', 'Walmart', 'CRV', 'CRV', 'CRV'],
'product': ['a', 'b', 'a', 'a', 'b', 'a', 'b', 'a', 'a', 'c'],
'amount': [5, 5, 8, 6, 1, 5, 10, 6, 12, 11]}
stores = pd.DataFrame(data, columns=['retailer_name', 'store_number', 'year', 'product', 'amount'])
stores.set_index(['retailer_name', 'store_number', 'year', 'product'], inplace=True)
stores.groupby(level=[0, 1, 2, 3]).sum()
I want to transform following Dataframe:
amount
retailer_name store_number year product
CRV 1946 2011 a 8
1947 2012 a 6
2013 c 11
1948 2011 a 6
b 1
1949 2012 a 12
Walmart 1944 2010 a 5
1945 2010 b 5
1947 2010 b 10
1949 2012 a 5
将数据转换为行的数据框:
retailer_name store_number year a b c
CRV 1946 2011 8 0 0
CRV 1947 2012 6 0 0
etc...
产品需要提前进行公示。你知道如何做吗?
reset_index()
和fillna(0)
,并且发帖文而不是图片。stores.groupby(level=[0, 1, 2, 3]).sum().unstack().fillna(0).reset_index()
- EdChumstores.groupby(level=[0, 1, 2, 3])['amount'].sum().unstack().fillna(0).reset_index()
基本上你可以在groupby
对象上使用[]
进行选择。 - EdChum