I have a pandas data frame, df, that looks like this;
index  New  Old  MAP      Limit  count
1       93   35   54       > 18      1
2      163   93  116       > 18      1
3      134   78   96       > 18      1
4      117   81   93       > 18      1
5      194  108  136       > 18      1
6      125   57   79      <= 18      1
7       66   39   48       > 18      1
8      120   83   95       > 18      1
9      150   98  115       > 18      1
10     149   99  115       > 18      1
11     148   85  106       > 18      1
12      92   55   67      <= 18      1
13      64   24   37       > 18      1
14      84   53   63       > 18      1
15      99   70   79       > 18      1
I need to create a pivot table that looks like this
Limit   <=18   >18
New      xx1   xx2
Old      xx3   xx4
MAP      xx5   xx6
where values xx1, xx2, xx3, xx4, xx5, and xx6 are the mean of New, Old and Map for respective Limit. How can I achieve this? I tried the following without success.
table = df.pivot_table('count', index=['New', 'Old', 'MAP'], columns=['Limit'], aggfunc='mean')
                df.groupby('Limit')['New', 'Old', 'MAP'].mean().T
Limit  <= 18        > 18
New    108.5  121.615385
Old     56.0   72.769231
MAP     73.0   88.692308
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