bigframes.pandas.api.typing.DataFrameGroupBy.max#

DataFrameGroupBy.max(numeric_only:bool=False,*args)→DataFrame[source]#

Compute max of group values.

Examples:

For SeriesGroupBy:

>>>lst=['a','a','b','b']>>>ser=bpd.Series([1,2,3,4],index=lst)>>>ser.groupby(level=0).max()a     2b     4dtype: Int64

For DataFrameGroupBy:

>>>data=[[1,8,2],[1,2,5],[2,5,8],[2,6,9]]>>>df=bpd.DataFrame(data,columns=["a","b","c"],...index=["tiger","leopard","cheetah","lion"])>>>df.groupby(by=["a"]).max()   b  ca1  8  52  6  9[2 rows x 2 columns]
Parameters:

  • numeric_only (bool,default False) – Include only float, int, boolean columns.

  • min_count (int,default 0) – The required number of valid values to perform the operation. If fewerthanmin_count and non-NA values are present, the result will be NA.

Returns:

Computed max of values within each group.

Return type:

bigframes.pandas.DataFrame orbigframes.pandas.Series

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