“丢弃随机行"从 pandas 数据框 [英] "Drop random rows" from pandas dataframe

问题描述

在熊猫数据框中，如何删除服从条件的行的随机子集?

In a pandas dataframe, how can I drop a random subset of rows that obey a condition?

换句话说，如果我有一个带有 Label 列的Pandas数据框，我想删除 Label == 1 ，但保留其余所有内容:

In other words, if I have a Pandas dataframe with a Label column, I'd like to drop 50% (or some other percentage) of rows where Label == 1, but keep all of the rest:

Label A     ->    Label A
0     1           0     1
0     2           0     2
0     3           0     3
1     10          1     11
1     11          1     12
1     12
1     13

我很想知道这样做的最简单，最pythonic/panda方式！

I'd love to know the simplest and most pythonic/panda-ish way of doing this!

这个问题提供了部分答案，但只讨论了按索引删除行，而忽略了行值.我仍然想知道如何仅从标记有特定方式的行中删除.

This question provides part of an answer, but it only talks about dropping rows by index, disregarding the row values. I'd still like to know how to drop only from rows that are labeled a certain way.

推荐答案

使用 frac 参数

df.sample(frac=.5)

如果您定义要放入变量 n

If you define the amount you want to drop in a variable n

n = .5
df.sample(frac=1 - n)

要包含条件，请使用 drop

df.drop(df.query('Label == 1').sample(frac=.5).index)

   Label   A
0      0   1
1      0   2
2      0   3
4      1  11
6      1  13

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