Group by index + column in pandas -

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i have dataframe has columns

  1. user_id
  2. item_bought

here user_id index of df. want group both user_id , item_bought , item wise count user. how do that.

thanks

this should work:

>>> df = pd.dataframe(np.random.randint(0,5,(6, 2)), columns=['col1','col2']) >>> df['ind1'] = list('aaabcc') >>> df['ind2'] = range(6) >>> df.set_index(['ind1','ind2'], inplace=true) >>> df             col1  col2 ind1 ind2                0        3     2      1        2     0      2        2     3 b    3        2     4 c    4        3     1      5        0     0   >>> df.groupby([df.index.get_level_values(0),'col1']).count()             col2 ind1 col1          2        2      3        1 b    2        1 c    0        1      3        1

i had same problem using 1 of columns multiindex. multiindex, cannot use df.index.levels[0] since has distinct values particular index level , of different size whole dataframe...

check http://pandas.pydata.org/pandas-docs/stable/generated/pandas.index.get_level_values.html - get_level_values "return vector of label values requested level, equal length of index"


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