Question

如何总结此数据框。

OCT NOV DEC JAN Feb Mar Apr May Jun Jul Aug Sep Total Sales
0   0   0   0   0   1   0   0   0   0   0   0   0   4825379.818
1   0   0   0   0   1   0   0   0   0   0   0   0   5522382.297
2   0   0   0   0   1   0   0   0   0   0   0   0   5721183.289
3   0   0   0   0   1   0   0   0   0   0   0   0   5374047.083
4   0   0   0   0   0   1   0   0   0   0   0   0   4917456.971

我希望它的格式为

Month    Sales
JAN    1235
FEB    5454
..     ..

..

Answer 1

您可以先将mul提取的列乘以pop，再对sum行Series行，对大写的月份名称行rename，再添加{{3 }}表示正确的顺序，reindex表示带有rename_axis的nw列名称：

cats = ['JAN', 'FEB', 'MAR', 'APR', 'MAY', 'JUN', 'JUL',
       'AUG', 'SEP', 'OCT', 'NOV', 'DEC']

df1 = (df.mul(df.pop('Total Sales'), axis=0)
         .sum()
         .rename(str.upper)
         .reindex(cats)
         .rename_axis('Month')
         .reset_index(name='Sales'))
print (df1)
   Month         Sales
0    JAN  0.000000e+00
1    FEB  2.144299e+07
2    MAR  4.917457e+06
3    APR  0.000000e+00
4    MAY  0.000000e+00
5    JUN  0.000000e+00
6    JUL  0.000000e+00
7    AUG  0.000000e+00
8    SEP  0.000000e+00
9    OCT  0.000000e+00
10   NOV  0.000000e+00
11   DEC  0.000000e+00

根据二进制值进行汇总

1 个答案: