pandas.Series.min — pandas 3.0.0.dev0+2101.g9bfbe9e339 documentation (original) (raw)

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