两列相加时的NaN值 [英] NaN values when adding two columns

问题描述

我有两个具有不同索引的数据框，我想对两个数据框的同一列求和. 我尝试了以下操作，但给出了NaN值

I have two dataframes with different indexing that I want to sum the same column from the two dataframes. I tried the following but gives NaN values

result['Anomaly'] = df['Anomaly'] + tmp['Anomaly']

df
    date           Anomaly
0 2018-12-06         0
1 2019-01-07         0
2 2019-02-06         1
3 2019-03-06         0
4 2019-04-06         0

tmp
    date           Anomaly
0 2018-12-06         0
1 2019-01-07         1
4 2019-04-06         0

result
    date           Anomaly
0 2018-12-06        0.0
1 2019-01-07        NaN
2 2019-02-06        1.0
3 2019-03-06        0.0
4 2019-04-06        0.0

我想要的实际上是:

result
    date           Anomaly
0 2018-12-06         0
1 2019-01-07         1
2 2019-02-06         1
3 2019-03-06         0
4 2019-04-06         0

推荐答案

您可以尝试

pd.concat([df, tmp]).groupby('date', as_index=False)["Anomaly"].sum()

         date  Anomaly
0  2018-12-06        0
1  2019-01-07        1
2  2019-02-06        1
3  2019-03-06        0
4  2019-04-06        0

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