Python Pandas基于列值的条件替换字符串 [英] Python pandas conditional replace string based on column values

问题描述

给出这些数据框...:

Given these data frames...:

DF = pd.DataFrame({'COL1': ['A', 'B', 'C', 'D','D','D'], 
                   'COL2': [11032, 1960, 11400, 11355, 8, 7], 
                   'year': ['2016', '2017', '2018', '2019', '2020', '2021']})
DF

   COL1 COL2    year
0   A   11032   2016
1   B   1960    2017
2   C   11400   2018
3   D   11355   2019
4   D   8       2020
5   D   7       2021

DF2 = pd.DataFrame({'ColX': ['D'], 'ColY':['2021'], 'ColZ':[100]
DF2
        ColX   ColY    ColZ
   0     D      2021   100

如果满足以下条件:

COL1 =来自DF2的ColX

COL1 = ColX from DF2

year = DF2的ColY

year = ColY from DF2

然后将COL2中的值从DF2更改为ColZ.

Then change the value in COL2 to ColZ from DF2.

推荐答案

这似乎是您想update DF使用来自DF2的数据.

This looks like you want to update DF with data from DF2.

假定DF2中的所有值对于ColX和ColY中的给定值对都是唯一的:

Assuming that all values in DF2 are unique for a given pair of values in ColX and ColY:

DF = DF.merge(DF2.set_index(['ColX', 'ColY'])[['ColZ']], 
              how='left', 
              left_on=['COL1', 'year'], 
              right_index=True)
DF.COL2.update(DF.ColZ)
del DF['ColZ']

>>> DF
  COL1   COL2  year
0    A  11032  2016
1    B   1960  2017
2    C  11400  2018
3    D  11355  2019
4    D      8  2020
5    D    100  2021

我将一个临时数据帧(DF2.set_index(['ColX', 'ColY'])[['ColZ']])合并到DF中，这将添加来自ColZ的所有值，其中其索引(ColX和ColY)的索引与DF中的COL1和year的值匹配.所有不匹配的值都用NA填充.

I merge a temporary dataframe (DF2.set_index(['ColX', 'ColY'])[['ColZ']]) into DF, which adds all the values from ColZ where its index (ColX and ColY) match the values from COL1 and year in DF. All non-matching values are filled with NA.

然后我使用update从DF.ColZ中的非空值覆盖DF.COL2中的值.

I then use update to overwrite the values in DF.COL2 from the non-null values in DF.ColZ.

然后我删除DF ['ColZ']进行清理.

I then delete DF['ColZ'] to clean-up.

如果ColZ与DF中的现有列名称匹配，则需要进行一些调整.

If ColZ matches an existing column name in DF, then you would need to make some adjustments.

替代解决方案如下:

DF = DF.set_index(['COL1', 'year']).update(DF2.set_index(['ColX', 'ColY']))
DF.reset_index(inplace=True)

输出与上面的输出相同.

The output is identical to that above.

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