python - 将数据框中某个值选择的行替换为数据框中某个值选择的另一行

Question

这是我的代码:

import pandas as pd
import numpy
from quilt.data.bussiere import test
ar = numpy.array([[1.1, 2, 3.3, 4], [2.7, 10, 5.4, 7], [5.3, 9, 1.5, 15]])
df = pd.DataFrame(ar, index = ['a1', 'a2', 'a3'], columns = ['A', 'B', 'C', 'D'])
df.loc[df['A'] == 5.3] = df.loc[df['A'] == 2.7] 
df

结果是一行 NaN :

     A        B      C       D
a1  1.1     2.0     3.3     4.0
a2  2.7     10.0    5.4     7.0
a3  NaN     NaN     NaN     NaN

如何正确更换？

Answer 1

pandas 对索引敏感，df.loc[df['A'] == 5.3] 和 df.loc[df['A'] == 2.7] 是 pandas object ，因此当您进行分配时会考虑 index ，因为其中之一是索引是a2，另一个是a3，这就是为什么你收到NaN

df.loc[df['A'] == 5.3] = df.loc[df['A'] == 2.7] .values # using value here,without the index match assign
df
Out[137]: 
      A     B    C    D
a1  1.1   2.0  3.3  4.0
a2  2.7  10.0  5.4  7.0
a3  2.7  10.0  5.4  7.0