pandas.DataFrame.max — pandas 2.2.3 documentation (original) (raw)

DataFrame.max(axis=0, skipna=True, numeric_only=False, **kwargs)[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.

Parameters:

axis{index (0), columns (1)}

Axis for the function to be applied on. For Series this parameter is unused and defaults to 0.

For DataFrames, specifying axis=None will apply the aggregation across both axes.

Added in version 2.0.0.

skipnabool, default True

Exclude NA/null values when computing the result.

numeric_onlybool, default False

Include only float, int, boolean columns. Not implemented for Series.

**kwargs

Additional keyword arguments to be passed to the function.

Returns:

Series or scalar

Examples

idx = pd.MultiIndex.from_arrays([ ... ['warm', 'warm', 'cold', 'cold'], ... ['dog', 'falcon', 'fish', 'spider']], ... names=['blooded', 'animal']) s = pd.Series([4, 2, 0, 8], name='legs', index=idx) s blooded animal warm dog 4 falcon 2 cold fish 0 spider 8 Name: legs, dtype: int64