In this article, we will discuss how to get the minimum value from the Pandas dataframe in Python.
We can get the minimum value by using the min() function
Syntax:
dataframe.min(axis)
where,
- axis=0 specifies column
- axis=1 specifies row
Get minimum value in dataframe row
To get the minimum value in a dataframe row simply call the min() function with axis set to 1.
Syntax:
dataframe.min(axis=1)
Example: Get minimum value in a dataframe row
Python3
# import pandas moduleimport pandas as pd# create a dataframe# with 5 rows and 4 columnsdata = pd.DataFrame({ 'name': ['sravan', 'ojsawi', 'bobby', 'rohith', 'gnanesh'], 'subjects': ['java', 'php', 'html/css', 'python', 'R'], 'marks': [98, 90, 78, 91, 87], 'age': [11, 23, 23, 21, 21]})# display dataframeprint(data)# get the minimum in rowdata.min(axis=1) |
Output:
Get the minimum value in column
To get the minimum value in a column simply call the min() function using axis set to 0.
Syntax:
dataframe.min(axis=0)
Example: Get minimum value in a column
Python3
# import pandas moduleimport pandas as pd# create a dataframe# with 5 rows and 4 columnsdata = pd.DataFrame({ 'name': ['sravan', 'ojsawi', 'bobby', 'rohith', 'gnanesh'], 'subjects': ['java', 'php', 'html/css', 'python', 'R'], 'marks': [98, 90, 78, 91, 87], 'age': [11, 23, 23, 21, 21]})# display dataframeprint(data)# get the minimum in columndata.min(axis=0) |
Output:
Get the minimum value in a particular column
To get the minimum value in a particular column call the dataframe with the specific column name and min() function.
Syntax:
dataframe['column_name'].min()
Example: Get the minimum value in a particular column
Python3
# import pandas moduleimport pandas as pd# create a dataframe# with 5 rows and 4 columnsdata = pd.DataFrame({ 'name': ['sravan', 'ojsawi', 'bobby', 'rohith', 'gnanesh'], 'subjects': ['java', 'php', 'html/css', 'python', 'R'], 'marks': [98, 90, 78, 91, 87], 'age': [11, 23, 23, 21, 21]})# display dataframeprint(data)# get the minimum in name columnprint(data['name'].min())# get the minimum in subjects columnprint(data['subjects'].min())# get the minimum in age columnprint(data['age'].min())# get the minimum in marks columnprint(data['marks'].min()) |
Output:
