bigframes.pandas.DataFrame.max#

DataFrame.max(axis: str | int = 0, *, numeric_only: bool = False) → Series[source]#

Return the maximum of the values over the requested axis.

If you want the index of the maximum, use idxmax. This is the equivalent of the numpy.ndarray method argmax.

Examples:

>>> df = bpd.DataFrame({"A": [1, 3], "B": [2, 4]})
>>> df
    A       B
0   1       2
1   3       4

[2 rows x 2 columns]

Finding the maximum value in each column (the default behavior without an explicit axis parameter).

>>> df.max()
A    3
B    4
dtype: Int64

Finding the maximum value in each row.

>>> df.max(axis=1)
0    2
1    4
dtype: Int64

Parameters:

• axis ({index (0), columns (1)}) Axis for the function to be applied on. For Series this parameter is unused and defaults to 0.

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

Returns:

Series after the maximum of values.

Return type:

bigframes.pandas.Series