pandas :按A列对数据进行分组，按B列的现有值过滤A [英] Pandas: Group Data by column A, Filter A by existing values of column B

问题描述

我是熊猫的新手，想创建一个包含分组和过滤后数据的新数据集.现在，我的数据集包含两列如下所示(第一列包含A，B或C，第二列包含值):

I'm new to pandas and want to create a new dataset with grouped and filtered data. Right now, my dataset contains two columns looking like this (first column with A, B or C, second with value):

A 1 

A 2

A 3

A 4 

B 1

B 2

B 3 

C 4

->现在，我想按第一列的键(A，B，C)进行分组，并仅显示存在值1和2的键.这样我的新数据集看起来就像:

--> now I want to group by the keys of the first column (A,B,C) , and show only the keys, where the values 1 AND 2 exist. So that my new data set looks like:

A 1

A 2

B 1

B 2

直到现在，我只能打印所有内容，但不知道如何过滤:

Until now, I'm only able to print everything but I don't know how to filter:

for name, group in data.groupby('keys'):
   print(name)
   print(group)

感谢您的帮助！

推荐答案

您可以使用:

df = df.loc[(df['col2'] == 1) | (df['col2'] == 2)]

然后过滤不包含两个值的组:

And then filter the groups that dont contains both values:

df = df.groupby('col1').filter(lambda x: any(x['col2'] == 2))
df = df.groupby('col1').filter(lambda x: any(x['col2'] == 1))

示例:

  col1  col2
0    A     1
1    A     2
2    A     3
3    A     4
4    B     1
5    B     2
6    B     3
7    C     4
8    C     1

输出:

  col1  col2
0    A     1
1    A     2
4    B     1
5    B     2

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