bigframes.pandas.DataFrame.aggregate#

DataFrame.aggregate(func) → DataFrame | Series#

Aggregate using one or more operations over columns.

Examples:

>>> df = bpd.DataFrame({"A": [3, 1, 2], "B": [1, 2, 3]})
>>> df
    A       B
0   3       1
1   1       2
2   2       3

[3 rows x 2 columns]

Using a single function:

>>> df.agg('sum')
A    6
B    6
dtype: Int64

Using a list of functions:

>>> df.agg(['sum', 'mean'])
          A   B
sum     6.0 6.0
mean        2.0     2.0

[2 rows x 2 columns]

Parameters:

func (function) Function to use for aggregating the data. Accepted combinations are: string function name, list of function names, e.g. ['sum', 'mean'].

Returns:

Aggregated results.

Return type:

bigframes.pandas.DataFrame or bigframes.pandas.Series