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Select row with maximum and minimum value in Pandas dataframe

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  • Last Updated : 06 Jan, 2019

Let’s see how can we select row with maximum and minimum value in Pandas dataframe with help of different examples.

Consider this dataset.




# importing pandas and numpy
import pandas as pd
import numpy as np
  
# data of 2018 drivers world championship
dict1 ={'Driver':['Hamilton', 'Vettel', 'Raikkonen',
                  'Verstappen', 'Bottas', 'Ricciardo',
                  'Hulkenberg', 'Perez', 'Magnussen'
                  'Sainz', 'Alonso', 'Ocon', 'Leclerc',
                  'Grosjean', 'Gasly', 'Vandoorne',
                  'Ericsson', 'Stroll', 'Hartley', 'Sirotkin'],
                    
        'Points':[408, 320, 251, 249, 247, 170, 69, 62, 56,
                   53, 50, 49, 39, 37, 29, 12, 9, 6, 4, 1],
                     
        'Age':[33, 31, 39, 21, 29, 29, 31, 28, 26, 24, 37,
                      22, 21, 32, 22, 26, 28, 20, 29, 23]}
                        
# creating dataframe using DataFrame constructor
df = pd.DataFrame(dict1)
print(df.head(10))

Output:

Using max on Dataframe –

Code #1: Shows max on Driver, Points, Age columns.




# importing pandas and numpy
import pandas as pd
import numpy as np
  
# data of 2018 drivers world championship
dict1 ={'Driver':['Hamilton', 'Vettel', 'Raikkonen',
                  'Verstappen', 'Bottas', 'Ricciardo',
                  'Hulkenberg', 'Perez', 'Magnussen'
                  'Sainz', 'Alonso', 'Ocon', 'Leclerc',
                  'Grosjean', 'Gasly', 'Vandoorne',
                  'Ericsson', 'Stroll', 'Hartley', 'Sirotkin'],
                    
        'Points':[408, 320, 251, 249, 247, 170, 69, 62, 56,
                   53, 50, 49, 39, 37, 29, 12, 9, 6, 4, 1],
                     
        'Age':[33, 31, 39, 21, 29, 29, 31, 28, 26, 24, 37,
                      22, 21, 32, 22, 26, 28, 20, 29, 23]}
                        
# creating dataframe using DataFrame constructor
df = pd.DataFrame(dict1)
  
# the result shows max on
# Driver, Points, Age columns.
print(df.max())

Output:

 
Code #2: Who scored max points




# importing pandas and numpy
import pandas as pd
import numpy as np
  
# data of 2018 drivers world championship
dict1 ={'Driver':['Hamilton', 'Vettel', 'Raikkonen',
                  'Verstappen', 'Bottas', 'Ricciardo',
                  'Hulkenberg', 'Perez', 'Magnussen'
                  'Sainz', 'Alonso', 'Ocon', 'Leclerc',
                  'Grosjean', 'Gasly', 'Vandoorne',
                  'Ericsson', 'Stroll', 'Hartley', 'Sirotkin'],
                    
        'Points':[408, 320, 251, 249, 247, 170, 69, 62, 56,
                   53, 50, 49, 39, 37, 29, 12, 9, 6, 4, 1],
                     
        'Age':[33, 31, 39, 21, 29, 29, 31, 28, 26, 24, 37,
                      22, 21, 32, 22, 26, 28, 20, 29, 23]}
                        
# creating dataframe using DataFrame constructor
df = pd.DataFrame(dict1)
  
# Who scored more points ?
print(df[df.Points == df.Points.max()])

Output:

 

Code #3: What is the maximum age




# importing pandas and numpy
import pandas as pd
import numpy as np
  
# data of 2018 drivers world championship
dict1 ={'Driver':['Hamilton', 'Vettel', 'Raikkonen',
                  'Verstappen', 'Bottas', 'Ricciardo',
                  'Hulkenberg', 'Perez', 'Magnussen'
                  'Sainz', 'Alonso', 'Ocon', 'Leclerc',
                  'Grosjean', 'Gasly', 'Vandoorne',
                  'Ericsson', 'Stroll', 'Hartley', 'Sirotkin'],
                    
        'Points':[408, 320, 251, 249, 247, 170, 69, 62, 56,
                   53, 50, 49, 39, 37, 29, 12, 9, 6, 4, 1],
                     
        'Age':[33, 31, 39, 21, 29, 29, 31, 28, 26, 24, 37,
                      22, 21, 32, 22, 26, 28, 20, 29, 23]}
                        
# creating dataframe using DataFrame constructor
df = pd.DataFrame(dict1)
  
# what is the maximum age ?
print(df.Age.max())

Output:

Code #4: Which row has maximum age in the dataframe | who is the oldest driver ?




# importing pandas and numpy
import pandas as pd
import numpy as np
  
# data of 2018 drivers world championship
dict1 ={'Driver':['Hamilton', 'Vettel', 'Raikkonen',
                  'Verstappen', 'Bottas', 'Ricciardo',
                  'Hulkenberg', 'Perez', 'Magnussen'
                  'Sainz', 'Alonso', 'Ocon', 'Leclerc',
                  'Grosjean', 'Gasly', 'Vandoorne',
                  'Ericsson', 'Stroll', 'Hartley', 'Sirotkin'],
                    
        'Points':[408, 320, 251, 249, 247, 170, 69, 62, 56,
                   53, 50, 49, 39, 37, 29, 12, 9, 6, 4, 1],
                     
        'Age':[33, 31, 39, 21, 29, 29, 31, 28, 26, 24, 37,
                      22, 21, 32, 22, 26, 28, 20, 29, 23]}
                        
# creating dataframe using DataFrame constructor
df = pd.DataFrame(dict1)
  
# Which row has maximum age |
# who is the oldest driver ?
print(df[df.Age == df.Age.max()])

Output:

Using min on Dataframe –

Code #1: Shows min on Driver, Points, Age columns.




# importing pandas and numpy
import pandas as pd
import numpy as np
  
# data of 2018 drivers world championship
dict1 ={'Driver':['Hamilton', 'Vettel', 'Raikkonen',
                  'Verstappen', 'Bottas', 'Ricciardo',
                  'Hulkenberg', 'Perez', 'Magnussen'
                  'Sainz', 'Alonso', 'Ocon', 'Leclerc',
                  'Grosjean', 'Gasly', 'Vandoorne',
                  'Ericsson', 'Stroll', 'Hartley', 'Sirotkin'],
                    
        'Points':[408, 320, 251, 249, 247, 170, 69, 62, 56,
                   53, 50, 49, 39, 37, 29, 12, 9, 6, 4, 1],
                     
        'Age':[33, 31, 39, 21, 29, 29, 31, 28, 26, 24, 37,
                      22, 21, 32, 22, 26, 28, 20, 29, 23]}
                        
# creating dataframe using DataFrame constructor
df = pd.DataFrame(dict1)
  
# the result shows min on 
# Driver, Points, Age columns.
print(df.min())

Output:

 

Code #2: Who scored less points




# importing pandas and numpy
import pandas as pd
import numpy as np
  
# data of 2018 drivers world championship
dict1 ={'Driver':['Hamilton', 'Vettel', 'Raikkonen',
                  'Verstappen', 'Bottas', 'Ricciardo',
                  'Hulkenberg', 'Perez', 'Magnussen'
                  'Sainz', 'Alonso', 'Ocon', 'Leclerc',
                  'Grosjean', 'Gasly', 'Vandoorne',
                  'Ericsson', 'Stroll', 'Hartley', 'Sirotkin'],
                    
        'Points':[408, 320, 251, 249, 247, 170, 69, 62, 56,
                   53, 50, 49, 39, 37, 29, 12, 9, 6, 4, 1],
                     
        'Age':[33, 31, 39, 21, 29, 29, 31, 28, 26, 24, 37,
                      22, 21, 32, 22, 26, 28, 20, 29, 23]}
                        
# creating dataframe using DataFrame constructor
df = pd.DataFrame(dict1)
  
# Who scored less points ?
print(df[df.Points == df.Points.min()])

Output:

 
Code #3: Which row has minimum age in the dataframe | who is the youngest driver




# importing pandas and numpy
import pandas as pd
import numpy as np
  
# data of 2018 drivers world championship
dict1 ={'Driver':['Hamilton', 'Vettel', 'Raikkonen',
                  'Verstappen', 'Bottas', 'Ricciardo',
                  'Hulkenberg', 'Perez', 'Magnussen'
                  'Sainz', 'Alonso', 'Ocon', 'Leclerc',
                  'Grosjean', 'Gasly', 'Vandoorne',
                  'Ericsson', 'Stroll', 'Hartley', 'Sirotkin'],
                    
        'Points':[408, 320, 251, 249, 247, 170, 69, 62, 56,
                   53, 50, 49, 39, 37, 29, 12, 9, 6, 4, 1],
                     
        'Age':[33, 31, 39, 21, 29, 29, 31, 28, 26, 24, 37,
                      22, 21, 32, 22, 26, 28, 20, 29, 23]}
                        
# creating dataframe using DataFrame constructor
df = pd.DataFrame(dict1)
  
# Which row has maximum age | 
# who is the youngest driver ?
print(df[df.Age == df.Age.min()])

Output:


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