Select row with maximum and minimum value in Pandas dataframe

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: