如何过滤具有 MultiIndex 级别 2 的多个条目的行？

Question

I have a dataframe, df with a MultiIndex.

df.columns
Index(['all', 'month', 'day', 'year'], dtype='object')

        all       month day year
  match             

7   0   10/24/89    10  24  89
8   0   3/7/86      3   7   86
    1   10          NaN NaN 10
9   0   4/10/71     4   10  71
10  0   5/11/85     5   11  85
    1   96          NaN NaN 96
    2   26          NaN NaN 26
11  0   10          NaN NaN 10
    1   4/09/75     4   09  75    
12  0   8/01/98     8   01  98

How can I select the rows with more than 1 entry at the MultiIndex level 2?

For example, here I need the rows 8,10 and 11.

Answer 1

you can use groupby.transform by the first level of index and use len . Then get True where the len is greater and equal ( ge ) to the value you want (here 2) to get the boolean mask you want and select the rows.

print(df[df.groupby(level=0)['month'].transform(len).ge(2)])
                0  month   day  year
   match                            
8  0       3/7/86    3.0   7.0    86
   1           10    NaN   NaN    10
10 0      5/11/85    5.0  11.0    85
   1           96    NaN   NaN    96
   2           26    NaN   NaN    26
11 0           10    NaN   NaN    10
   1      4/09/75    4.0   9.0    75

Here I use 'month' as column after the groupby operation, but any column in your dataframe would work.

You can also use groupby.filter and get the same result with:

print(df.groupby(level=0).filter(lambda x: len(x)>=2))