Select row with max and min value in Pandas dataframe

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Consider this dataset.

Output:

Using max on Dataframe —

Code # 1: shows the maximum of Driver, Points, Age columns.

# pandas and numpy imports

import pandas as pd

import numpy as np


# 2018 Driving World Championship data

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 ]}


# create a data frame using the DataFrame constructor

df = pd.DataFrame (dict1)

print (df. head ( 10 ))

# pandas and numpy imports

import pandas as pd

import numpy as np


# 2018 Driving World Championship data

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 ]}


# create a data frame using the DataFrame constructor

df = pd.DataFrame (dict1)


# the result shows a maximum of
# Driver, Points, Age columns.

print (df. max ())

Output:

Code # 2: Who scored maximum points

# pandas and numpy imports

import pandas as pd

import numpy as np


# 2018 Driving World Championship data

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 ]}


# create a data frame using the constructor DataFrame

df = pd.DataFrame ( dict1)


# Who scored more points?

print (df [df.Points = = df.Points. max ( )])

Output:

Code # 3: What is the maximum age

# pandas and numpy imports

import pandas as pd

import numpy as np


# 2018 Driving World Championship data

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 ]}


# create a data frame using the DataFrame constructor

df = pd.DataFrame (dict1)


# what is the maximum age?

print (df.Age. max ())

Output:

Code # 4: Which line has the maximum age in the data frame | who is the oldest driver?

# pandas and numpy imports

import pandas as pd

import numpy as np


# 2018 Driving World Championship data

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 ]}


# create a data frame using the DataFrame constructor

df = pd.DataFrame (dict1)


# Which one the row has a maximum age |
# who is the oldest driver?

print (df [df.Age = = df.Age. max ()])

Output:

Using min on Dataframe —

Code # 1: shows the minimum number of Driver columns, Points "," Age ".

# pandas and numpy imports

import pandas as pd

import numpy as np

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Oliver Danburry

Shanghai | 2023-02-04

Thanks for explaining! I was stuck with Select row with max and min value in Pandas dataframe for some hours, finally got it done 🤗. I am just not quite sure it is the best method

Marie Nickolson

Abu Dhabi | 2023-02-04

Thanks for explaining! I was stuck with Select row with max and min value in Pandas dataframe for some hours, finally got it done 🤗. Checked yesterday, it works!

Davies OConnell

Shanghai | 2023-02-04

Thanks for explaining! I was stuck with Select row with max and min value in Pandas dataframe for some hours, finally got it done 🤗. Checked yesterday, it works!

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