Python - How to reset index after Groupby pandas?

When you perform a groupby operation in pandas, the grouped column becomes the index. To convert this index back to a regular column, use reset_index().

Import Required Library

First, import pandas ?

import pandas as pd

Creating Sample DataFrame

Let's create a DataFrame with car names and prices ?

import pandas as pd

dataFrame = pd.DataFrame({
    "Car": ["Audi", "Lexus", "Audi", "Mercedes", "Audi", "Lexus", "Mercedes", "Lexus", "Mercedes"],
    "Reg_Price": [1000, 1400, 1100, 900, 1700, 1800, 1300, 1150, 1350]
})

print("Original DataFrame:")
print(dataFrame)

Original DataFrame:
       Car  Reg_Price
0     Audi       1000
1    Lexus       1400
2     Audi       1100
3 Mercedes        900
4     Audi       1700
5    Lexus       1800
6 Mercedes       1300
7    Lexus       1150
8 Mercedes       1350

GroupBy Operation

Group by the "Car" column and calculate the mean price ?

import pandas as pd

dataFrame = pd.DataFrame({
    "Car": ["Audi", "Lexus", "Audi", "Mercedes", "Audi", "Lexus", "Mercedes", "Lexus", "Mercedes"],
    "Reg_Price": [1000, 1400, 1100, 900, 1700, 1800, 1300, 1150, 1350]
})

# Group by Car and calculate mean
grouped_df = dataFrame.groupby("Car").mean()
print("After GroupBy (Car becomes index):")
print(grouped_df)

After GroupBy (Car becomes index):
          Reg_Price
Car                
Audi      1266.666667
Lexus     1450.000000
Mercedes  1183.333333

Reset Index After GroupBy

Use reset_index() to convert the index back to a column ?

import pandas as pd

dataFrame = pd.DataFrame({
    "Car": ["Audi", "Lexus", "Audi", "Mercedes", "Audi", "Lexus", "Mercedes", "Lexus", "Mercedes"],
    "Reg_Price": [1000, 1400, 1100, 900, 1700, 1800, 1300, 1150, 1350]
})

# Group by Car and calculate mean
grouped_df = dataFrame.groupby("Car").mean()

# Reset index to make Car a regular column again
result_df = grouped_df.reset_index()
print("After reset_index():")
print(result_df)

After reset_index():
       Car   Reg_Price
0     Audi  1266.666667
1    Lexus  1450.000000
2 Mercedes  1183.333333

Alternative: Using drop Parameter

You can also use reset_index(drop=True) to drop the old index completely ?

import pandas as pd

dataFrame = pd.DataFrame({
    "Car": ["Audi", "Lexus", "Audi", "Mercedes"],
    "Price": [1000, 1400, 1100, 900],
    "Year": [2020, 2021, 2019, 2022]
})

# Group by Car and get first row of each group
grouped_df = dataFrame.groupby("Car").first()

# Reset index and drop the old index
result_df = grouped_df.reset_index(drop=False)  # Keep grouped column
print(result_df)

       Car  Price  Year
0     Audi   1000  2020
1    Lexus   1400  2021
2 Mercedes    900  2022

Conclusion

Use reset_index() after groupby() to convert the grouped column back to a regular column. This is essential when you need the grouped column for further operations or display purposes.