Good afternoon, tell me how to remove a row from the header of the table of this frame, which contains NaN? 
Came to this with such code:
data = df.groupby(['Тип газопровода', 'Диаметр'])['Протяженность'] data = data.agg([{'Средняя протяженность':'mean', 'Кол-во объектов':'count', 'Общая протяженность':'sum'}]) data = data.reset_index(col_level=True) 
Replace:
[{'Средняя протяженность':'mean', 'Кол-во объектов':'count', 'Общая протяженность':'sum'}] on
{'Средняя протяженность':'mean', 'Кол-во объектов':'count', 'Общая протяженность':'sum'} Example:
Source DataFrame:
In [94]: df Out[94]: type dm length 0 1 50 110 1 1 50 111 2 1 63 112 3 2 32 113 4 2 32 114 5 2 32 115 6 3 50 116 7 3 50 117 8 3 50 118 9 3 80 119 Decision:
In [95]: funcs = { ...: 'count': 'count', ...: 'total length': 'sum', ...: 'avg. length': 'mean' ...: } ...: In [96]: df.groupby(['type','dm'])['length'].agg(funcs).reset_index() Out[96]: type dm count total length avg. length 0 1 50 2 221 110.5 1 1 63 1 112 112.0 2 2 32 3 342 114.0 3 3 50 3 351 117.0 4 3 80 1 119 119.0 for comparison, your option:
In [97]: df.groupby(['type','dm'])['length'].agg([funcs]).reset_index() Out[97]: type dm NaN count total length avg. length 0 1 50 2 221 110.5 1 1 63 1 112 112.0 2 2 32 3 342 114.0 3 3 50 3 351 117.0 4 3 80 1 119 119.0 Universal version of the transformation of multi-level columns into ordinary ones:
In [98]: rslt = df.groupby(['type','dm'])['length'].agg([funcs]).reset_index() In [99]: rslt Out[99]: type dm NaN count total length avg. length 0 1 50 2 221 110.5 1 1 63 1 112 112.0 2 2 32 3 342 114.0 3 3 50 3 351 117.0 4 3 80 1 119 119.0 In [100]: rslt.columns = [tup[1] if tup[1] else tup[0] for tup in rslt.columns] In [101]: rslt Out[101]: type dm count total length avg. length 0 1 50 2 221 110.5 1 1 63 1 112 112.0 2 2 32 3 342 114.0 3 3 50 3 351 117.0 4 3 80 1 119 119.0 [{...}] construct, and I use {...} - MaxUSource: https://ru.stackoverflow.com/questions/662229/
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