Question

我有一个如下所示的数据框

Category Date   Value
   A      Jan     1
   A      Feb     1
   A      Mar     1
   B      Jan     1
   B      Feb     1
   C      Jan     1
   C      Mar     1

我想用0填满每个类别的缺失月份，即

Category Date   Value
   A      Jan     1
   A      Feb     1
   A      Mar     1
   B      Jan     1
   B      Feb     1
   B      Mar     0
   C      Jan     1
   C      Feb     0
   C      Mar     1

我不太确定从哪里开始。预先感谢！

Answer 1

您可以unstack和fill_value=0和stack来获得结果

df.set_index(["Category","Date"]).unstack(fill_value=0).stack().reset_index()

输出

   Category     Date    Value
0   A            Feb    1
1   A            Jan    1
2   A            Mar    1
3   B            Feb    1
4   B            Jan    1
5   B            Mar    0
6   C            Feb    0
7   C            Jan    1
8   C            Mar    1

Answer 2

您可以reindex使用多索引：

multi = [(x,y) for x in df["Category"].unique() for y in df["Date"].unique()]

print (df.set_index(["Category","Date"]).reindex(multi).fillna(0).reset_index())

  Category Date  Value
0        A  Jan    1.0
1        A  Feb    1.0
2        A  Mar    1.0
3        B  Jan    1.0
4        B  Feb    1.0
5        B  Mar    0.0
6        C  Jan    1.0
7        C  Feb    0.0
8        C  Mar    1.0

Answer 3

另一种方法

df.pivot_table(index=['Category'], columns='Date', values='Value').fillna(0).stack().reset_index()

  Category Date    0
0        A  Feb  1.0
1        A  Jan  1.0
2        A  Mar  1.0
3        B  Feb  1.0
4        B  Jan  1.0
5        B  Mar  0.0
6        C  Feb  0.0
7        C  Jan  1.0
8        C  Mar  1.0

熊猫：如何填充按两列分组的缺失值

3 个答案: