How to Fix ‘DataFrameGroupBy’ object has no attribute ‘set_index’

To fix the ‘DataFrameGroupBy’ object has no attribute ‘set_index’ error in Pandas, you need to “apply an aggregation function (such as sum(), mean(), etc.)” on the groupby object first, which will return a DataFrame and then you can call the set_index() method on the resulting DataFrame.

The error ‘DataFrameGroupBy’ object has no attribute ‘set_index’ occurs when you try to call the set_index() method on a DataFrameGroupBy object. This is because the set_index() method is not available for the groupby object but only for a DataFrame object.

Example

import pandas as pd

# Sample data
data = {'A': ['foo', 'foo', 'foo', 'bar', 'bar', 'bar'],
 'B': ['one', 'one', 'two', 'two', 'one', 'one'],
 'C': [2.5, 1, 4.5, 6, 7.5, 8],
 'D': [10, 20, 30, 40, 50, 60]}

# DataFrame
df = pd.DataFrame(data)

# Group by columns 'A' and 'B', and compute the sum of columns 'C' and 'D'
grouped_df = df.groupby(['A', 'B']).agg({'C': 'sum', 'D': 'sum'})

# Reset the index of the resulting DataFrame
grouped_df = grouped_df.reset_index()

print(grouped_df)

Output

   A   B   C    D
0 bar one 15.5 110
1 bar two 6.0  40
2 foo one 3.5  30
3 foo two 4.5  30

In this example, we first group the DataFrame df by columns ‘A’ and ‘B’, then apply the “agg()” function to compute the sum of columns ‘C’ and ‘D’.

The resulting DataFrame grouped_df is then reset to have a new index using the reset_index() method.