按列表顺序从列表中选择 pandas 数据框的行 [英] Select rows of pandas dataframe from list, in order of list

问题描述

该问题最初是

The question was originally asked here as a comment but could not get a proper answer as the question was marked as a duplicate.

对于给定的pandas.DataFrame，让我们说

df = DataFrame({'A' : [5,6,3,4], 'B' : [1,2,3, 5]})
df

     A   B
0    5   1
1    6   2
2    3   3
3    4   5

我们如何基于列中的值(例如，'A')从列表中选择行

How can we select rows from a list, based on values in a column ('A' for instance)

例如

# from
list_of_values = [3,4,6]

# we would like, as a result
#      A   B
# 2    3   3
# 3    4   5
# 1    6   2

使用提及的isin here 不能令人满意，因为它没有保持'A'值输入列表的顺序.

Using isin as mentioned here is not satisfactory as it does not keep order from the input list of 'A' values.

如何实现上述目标?

推荐答案

一种克服此问题的方法是将'A'列设置为index，并在新生成的pandas.DataFrame上使用loc.最终，可以重置欠采样数据帧的索引.

One way to overcome this is to make the 'A' column an index and use loc on the newly generated pandas.DataFrame. Eventually, the subsampled dataframe's index can be reset.

方法如下:

ret = df.set_index('A').loc[list_of_values].reset_index(inplace=False)

# ret is
#      A   B
# 0    3   3
# 1    4   5
# 2    6   2 

请注意，此方法的缺点是在此过程中丢失了原始索引.

Note that the drawback of this method is that the original indexing has been lost in the process.

关于pandas索引的更多信息:索引的意义是什么在熊猫里?

More on pandas indexing: What is the point of indexing in pandas?

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