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How to Get the maximum value from the Pandas dataframe in Python?

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  • 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)

Python3




# 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)

Python3




# 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()

Python3




# 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:


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