如何根据条件将数据框中的一列切片为多个系列 [英] How can I slice one column in a dataframe to several series based on a condition

问题描述

我有一个看起来像这样的数据框:

I have a data frame that looks like this:

       'A' diff('A')
    0   1    NaN
    1   2     1
    2   5     3
    3   2    -3
    4   4     2
    5   6     2
    6   1    -5
    7   7     6
    8   9     2

我想获得的是这样的东西:

What I would like to obtain is something like this:

       'B'
    0   1
    1   2
    2   5

       'C'
    0   2
    1   4
    2   6

       'D'
    0   1
    1   7
    2   9

我想将'A'列切成几个新列；切片原始列的条件是，列 diff('A')上的值是负数.我当时认为迭代器应该遍历数据帧，并且只要它在 diff('A')中遇到负值，就应该对该列进行切片并将其传递给Series，然后继续进行操作，直到它到达列的末尾.

I would like to slice the column 'A' into several new columns; the condition to slice the original column is that value on the column diff('A') is negative. I was thinking that an iterator should go through the dataframe and, whenever it encounters a negative value in diff('A'), it should slice the column and pass it to a Series, and then continue until it reaches the end of the column.

有人有什么想法吗?

提前谢谢！

推荐答案

我相信您的想法很好，但是使用pandas内置选择器会更有效:

I believe your idea works fine, but it will be more efficient to use the pandas built-in selector:

decreased_value = df[df['diff'] < 0]['A'].reset_index(drop=True)

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