Pandas Series: min() function

Last update on September 15 2022 12:54:13 (UTC/GMT +8 hours)

Minimum values in Pandas requested axis

The min() function is used to get the minimum of the values for the requested axis.

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

Syntax:

Series.min(self, axis=None, skipna=None, level=None, numeric_only=None, **kwargs)

Parameters:

Name	Description	Type/Default Value	Required / Optional
axis	Axis for the function to be applied on.	{index (0)}	Required
skipna	Exclude NA/null values when computing the result.	bool Default Value: True	Required
level	If the axis is a MultiIndex (hierarchical), count along a particular level, collapsing into a scalar.	int or level name Default Value: None	Required
numeric_only	Include only float, int, boolean columns. If None, will attempt to use everything, then use only numeric data. Not implemented for Series.	bool Default Value: None	Required
**kwargs	Additional keyword arguments to be passed to the function.		Required

Returns: scalar or Series (if level specified)

Example:

Python-Pandas Code:

import numpy as np
import pandas as pd
idx = pd.MultiIndex.from_arrays([
    ['warm', 'warm', 'cold', 'cold'],
    ['fox', 'lion', 'snake', 'spider']],
    names=['blooded', 'animal'])
s = pd.Series([4, 4, 0, 8], name='legs', index=idx)
s

Output:

blooded  animal
warm     fox       4
         lion      4
cold     snake     0
         spider    8
Name: legs, dtype: int64

Python-Pandas Code:

import numpy as np
import pandas as pd
idx = pd.MultiIndex.from_arrays([
    ['warm', 'warm', 'cold', 'cold'],
    ['fox', 'lion', 'snake', 'spider']],
    names=['blooded', 'animal'])
s = pd.Series([4, 4, 0, 8], name='legs', index=idx)
s.min()

Output:

Example - Min using level names, as well as indices:

Python-Pandas Code:

import numpy as np
import pandas as pd
idx = pd.MultiIndex.from_arrays([
    ['warm', 'warm', 'cold', 'cold'],
    ['fox', 'lion', 'snake', 'spider']],
    names=['blooded', 'animal'])
s = pd.Series([4, 4, 0, 8], name='legs', index=idx)
s.min(level='blooded')

Output:

blooded
warm    4
cold    0
Name: legs, dtype: int64

Python-Pandas Code:

import numpy as np
import pandas as pd
idx = pd.MultiIndex.from_arrays([
    ['warm', 'warm', 'cold', 'cold'],
    ['fox', 'lion', 'snake', 'spider']],
    names=['blooded', 'animal'])
s = pd.Series([4, 4, 0, 8], name='legs', index=idx)
s.min(level=0)

Output:

blooded
warm    4
cold    0
Name: legs, dtype: int64

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