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pandas.Series.min — pandas 3.0.0.dev0+2232.ga2315af1df documentation

Series.min(*, axis=0, skipna=True, numeric_only=False, **kwargs)[source]#

Return the minimum of the values over the requested axis.

If you want the index of the minimum, use idxmin. This is the equivalent of the numpy.ndarray method argmin.

Parameters:

axis{index (0)}

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.

**kwargs

Additional keyword arguments to be passed to the function.

Returns:

scalar or Series (if level specified)

The minimum of the values in the 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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