pandas.Series.max — pandas 1.0.5 documentation (original) (raw)

Series. max(self, axis=None, skipna=None, level=None, numeric_only=None, **kwargs)[source]¶

Return the maximum of the values for 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)}

Axis for the function to be applied on.

skipnabool, default True

Exclude NA/null values when computing the result.

levelint or level name, default None

If the axis is a MultiIndex (hierarchical), count along a particular level, collapsing into a scalar.

numeric_onlybool, default None

Include only float, int, boolean columns. If None, will attempt to use everything, then use only numeric data. Not implemented for Series.

**kwargs

Additional keyword arguments to be passed to the function.

Returns

scalar or Series (if level specified)

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

Max using level names, as well as indices.

s.max(level='blooded') blooded warm 4 cold 8 Name: legs, dtype: int64

s.max(level=0) blooded warm 4 cold 8 Name: legs, dtype: int64