pandas.DataFrame.min — pandas 0.24.0rc1 documentation (original) (raw)
DataFrame. min(axis=None, skipna=None, level=None, numeric_only=None, **kwargs)[source]¶
Return the minimum of the values for the requested axis.
If you want the index of the minimum, use
idxmin. This is the equivalent of thenumpy.ndarraymethodargmin.
| Parameters: | axis : {index (0), columns (1)} 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 Series. 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: | min : Series or DataFrame (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
Min using level names, as well as indices.
s.min(level='blooded') blooded warm 2 cold 0 Name: legs, dtype: int64
s.min(level=0) blooded warm 2 cold 0 Name: legs, dtype: int64