How to Get the maximum value from the Pandas dataframe in Python?
Last Updated :
28 Nov, 2021
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Python Pandas max() function returns the maximum of the values over the requested axis.
Syntax: dataframe.max(axis)
where,
- axis=0 specifies column
- axis=1 specifies row
Example 1: Get maximum value in dataframe row
To get the maximum value in a dataframe row simply call the max() function with axis set to 1.
Syntax: dataframe.max(axis=1)
# import pandas module
import pandas as pd
# create a dataframe
# with 5 rows and 4 columns
data = 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 dataframe
print(data)
# get the maximum in row
data.max(axis=1)
Output:
Example 2: Get the maximum value in column
To get the maximum value in a column simply call the max() function using the axis set to 0.
Syntax: dataframe.max(axis=0)
# import pandas module
import pandas as pd
# create a dataframe
# with 5 rows and 4 columns
data = 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 dataframe
print(data)
# get the maximum in column
data.max(axis=0)
Output:
Example 3: Get the maximum value in a particular column
To get the maximum value in a particular column call the dataframe with the specific column name and max() function.
Syntax: dataframe['column_name'].max()
# import pandas module
import pandas as pd
# create a dataframe
# with 5 rows and 4 columns
data = 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 dataframe
print(data)
# get the max in name column
print(data['name'].max())
# get the max in subjects column
print(data['subjects'].max())
# get the max in age column
print(data['age'].max())
# get the max in marks column
print(data['marks'].max())
Output:
