从pandas df列中选择的函数 [英] Function to select from columns pandas df

问题描述

我在熊猫数据框中有这个测试表

i have this test table in pandas dataframe

   Leaf_category_id  session_id  product_id
0               111           1         987
3               111           4         987
4               111           1         741
1               222           2         654
2               333           3         321

我想要的是

for leaf_category_id 111:

结果应该是.

 session_id   product_id
 1            987,741
 4            987

类似地，我可以定义一个对所有leaf_category id都执行相同操作的函数，我的表包含更多行，这只是它的快照.

Similarly can i define a function that does the same for all the leaf_category id's, my table contains more rows, it was just a snapshot of it.

推荐答案

您可以使用 boolean indexing ，然后通过评论

print (df.groupby(['Leaf_category_id','session_id'])['product_id']
         .apply(lambda x: ','.join(x.astype(str)))
         .reset_index())
   Leaf_category_id  session_id product_id
0               111           1    987,741
1               111           4        987
2               222           2        654
3               333           3        321

或者如果需要Leaf_category_id DataFrame中的每个唯一值:

Or if need for each unique value in Leaf_category_id DataFrame:

for i in df.Leaf_category_id.unique():
    print (df[df.Leaf_category_id == i] \
                .groupby('session_id')['product_id'] \
                .apply(lambda x: ','.join(x.astype(str))) \
                .reset_index())

   session_id product_id
0           1    987,741
1           4        987
   session_id product_id
0           2        654
   session_id product_id
0           3        321

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