Pandas Series - min() function

The Pandas Series min() function returns the minimum of the values over the specified axis. The syntax for using this function is mentioned below:

Syntax

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

Parameters

`axis`	`Optional.` Specify {0 or 'index'}. Specify axis for the function to be applied on.
`skipna`	`Optional.` Specify True to exclude NA/null values when computing the result. Default is True.
`level`	`Optional.` Specify level (int or str). If the axis is a MultiIndex (hierarchical), count along a particular level, collapsing into a scalar. A str specifies the level name.
`numeric_only`	`Optional.` Specify True to include only float, int or boolean data. Default: False

Return Value

Returns scalar or Series if a level is specified.

Example: using min() on a Series

In the example below, the min() function is used to get the minimum of values of a given series.

import pandas as pd
import numpy as np

idx = pd.MultiIndex.from_arrays([
    ['even', 'even', 'even', 
     'odd', 'odd', 'odd']],
    names=['DataType'])

x = pd.Series([10, 20, 30, 5, 7, 9], 
              name='Numbers', index=idx)

print("The Series contains:")
print(x)

#minimum of all values in the series
print("\nx.min() returns:")
print(x.min())

#minimum of all values within given level
print("\nx.min(level='DataType') returns:")
print(x.min(level='DataType'))
print("\nx.min(level=0) returns:")
print(x.min(level=0))

The output of the above code will be:

The Series contains:
DataType
even    10
even    20
even    30
odd      5
odd      7
odd      9
Name: Numbers, dtype: int64

x.min() returns:
5

x.min(level='DataType') returns:
DataType
even    10
odd      5
Name: Numbers, dtype: int64

x.min(level=0) returns:
DataType
even    10
odd      5
Name: Numbers, dtype: int64

Example: using min() on selected series in a DataFrame

Similarly, the min() function can be applied on selected series/column of a given DataFrame. Consider the following example.

import pandas as pd
import numpy as np

df = pd.DataFrame({
  "Bonus": [5, 3, 2, 4],
  "Last Salary": [58, 60, 63, 57],
  "Salary": [60, 62, 65, 59]},
  index= ["John", "Marry", "Sam", "Jo"]
)

print("The DataFrame is:")
print(df)

#minimum of all values of 'Salary' series
print("\ndf['Salary'].min() returns:")
print(df["Salary"].min())

The output of the above code will be:

The DataFrame is:
       Bonus  Last Salary  Salary
John       5           58      60
Marry      3           60      62
Sam        2           63      65
Jo         4           57      59

df['Salary'].min() returns:
59

❮ Pandas Series - Functions