modin.pandas.DataFrame.max

DataFrame.max(axis: Axis | None = 0, skipna: bool = True, numeric_only: bool = False, **kwargs: Any)[source] (https://github.com/snowflakedb/snowpark-python/blob/v1.26.0/snowpark-python/src/snowflake/snowpark/modin/plugin/extensions/base_overrides.py#L724-L741)

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.

  • skipna (bool, default True) – Exclude NA/null values when computing the result.

  • numeric_only (bool, default False) – If True, Include only float, int, boolean columns. Not implemented for Series.

  • **kwargs – Additional keyword arguments to be passed to the function.

Return type:

Series

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
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>>> s.max()
8
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