Python Pandas groupby sort within groups

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mahmoud2506

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2022-05-25

174

The groupby() is a simple but very useful concept in pandas. By using groupby(), we can create a grouping of certain values and perform some operations on those values.

The groupby() function split the object, apply some operations, and then combines them to create a group hence a large amount of data and computations can be performed on these groups. Sorting within groups is nothing but arranging the result of groupby() in ascending or descending order.

Syntax:

DataFrame.groupby(
    by=None, 
    axis=0, 
    level=None, 
    as_index=True, 
    sort=True, 
    group_keys=True, 
    squeeze=NoDefault.no_default, 
    observed=False, 
    dropna=True
    )

To work with pandas, we need to import pandas package first, below is the syntax:

import pandas as pd

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mahmoud2506

2022-05-25

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Let us understand with the help of an example.

# Importing pandas package
import pandas as pd

# creating a dictionary of student marks
d={
    "Players":['Sachin','Ganguly','Dravid','Yuvraj','Dhoni','Kohli',
              'Sachin','Ganguly','Dravid','Yuvraj','Dhoni','Kohli'],
    "Format":['Test','Test','Test','Test','Test','Test',
             'ODI','ODI','ODI','ODI','ODI','ODI'],
    "Runs":[15921,7212,13228,1900,4876,8043,
           18426,11363,10889,8701,10773,12311]
}

# Now we will create DataFrame
df = pd.DataFrame(d)

# Viewing the DataFrame
print("DataFrame:\n",df,"\n\n")

# Performing sum on groupby on Players with runs
result = df.groupby(['Players'], sort=True).sum()

# Display Result
print("Grouped result:\n",result)

Output:

Example : Groupby sort within groups