pandas.Series.max — pandas 0.24.0rc1 documentation (original) (raw)
Series. max(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 thenumpy.ndarraymethodargmax.
| Parameters: | axis : {index (0)} Axis for the function to be applied on. skipna : bool, default True Exclude NA/null values when computing the result. level : int or level name, default None If the axis is a MultiIndex (hierarchical), count along a particular level, collapsing into a scalar. numeric_only : bool, 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: | max : 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