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:
Last Updated on August 28, 2021 by admin