将pandas DataFrame行复制到其他多个行 [英] Copy pandas DataFrame row to multiple other rows

问题描述

简单实用的问题，但我找不到解决方法.

Simple and practical question, yet I can't find a solution.

我看的问题如下:

修改熊猫数据框中的行的子集

将某些值更改为多个一次熊猫数据框的列

复制列的最快方法从一个DataFrame到另一个使用Pandas的数据框架?

从pandas.DataFrame中使用复杂条件进行选择

这些和我的主要区别在于，我不需要插入单个值，而是插入一行.

The key difference between those and mine is that I need not to insert a single value, but a row.

我的问题是，我拿起一行数据框，例如df1.因此，我有一个系列.

My problem is, I pick up a row of a dataframe, say df1. Thus I have a series.

现在我有了另一个数据框df2，我已经根据一个条件选择了多行，我想将该系列复制到所有这些行.

Now I have this other dataframe, df2, that I have selected multiple rows according to a criteria, and I want to replicate that series to all those row.

df1:

Index/Col   A   B  C
1           0   0  0
2           0   0  0
3           1   2  3
4           0   0  0

df2:

Index/Col   A   B  C
1           0   0  0
2           0   0  0
3           0   0  0
4           0   0  0

我要完成的工作是将df1 [3]插入到df2 [2]和df3 [3]行中.像这样的无效代码:

What I want to accomplish is inserting df1[3] into the lines df2[2] and df3[3] for example. So something like the non working code:

series = df1[3]
df2[df2.index>=2 and df2.index<=3] = series

返回

df2:

Index/Col   A   B  C
1           0   0  0
2           1   2  3
3           1   2  3
4           0   0  0

推荐答案

使用loc并传递感兴趣的索引标签列表，在以下逗号之后，:表示我们要设置所有列值，我们然后分配序列，但调用属性.values，以便它是一个numpy数组.否则，您将得到ValueError，因为形状将不匹配，因为您打算用单行覆盖2行，如果它是Series，那么它将无法按照您的意愿对齐:

Use loc and pass a list of the index labels of interest, after the following comma the : indicates we want to set all column values, we then assign the series but call attribute .values so that it's a numpy array. Otherwise you will get a ValueError as there will be a shape mismatch as you're intending to overwrite 2 rows with a single row and if it's a Series then it won't align as you desire:

In [76]:
df2.loc[[2,3],:] = df1.loc[3].values
df2

Out[76]:
   A  B  C
1  0  0  0
2  1  2  3
3  1  2  3
4  0  0  0

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