按索引+列按 pandas 分组 [英] Group by index + column in pandas

问题描述

我有一个包含列的数据框

I have a dataframe that has the columns

1. user_id
2. item_bought

这里的user_id是df的索引.我想同时按user_id和item_bought分组，并为用户获取明智的商品计数.我该怎么做.

Here user_id is the index of the df. I want to group by both user_id and item_bought and get the item wise count for the user. How do I do that.

谢谢

推荐答案

从版本 0.20.1 更简单:

作为 by 参数传递给 DataFrame.groupby()的字符串现在可以引用列名称或索引级别名称

Strings passed to DataFrame.groupby() as the by parameter may now reference either column names or index level names

arrays = [['bar', 'bar', 'baz', 'baz', 'foo', 'foo', 'qux', 'qux'],
          ['one', 'two', 'one', 'two', 'one', 'two', 'one', 'two']]

index = pd.MultiIndex.from_arrays(arrays, names=['first', 'second'])

df = pd.DataFrame({'A': [1, 1, 1, 1, 2, 2, 3, 3],
                   'B': np.arange(8)}, index=index)

print (df)

              A  B
first second      
bar   one     1  0
      two     1  1
baz   one     1  2
      two     1  3
foo   one     2  4
      two     2  5
qux   one     3  6
      two     3  7

print (df.groupby(['second', 'A']).sum())
          B
second A   
one    1  2
       2  4
       3  6
two    1  4
       2  5
       3  7

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