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

AttributeError: ‘DataFrameGroupBy’ object has no attribute ‘set_index’ occurs because you try to call the set_index() method on a DataFrameGroupBy object, but it is available for a DataFrame object and not DataFrameGroupBy object.

To fix the error, 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.

DataFrameGroupBy objects are intermediate objects used to store information about the groups. They are not DataFrames themselves but can be used to apply operations to each group.

After performing these operations (like sum, mean, aggregate, etc.), you will get a regular DataFrame on which you can use methods like set_index.

Flow chart

Diagram of How to Fix AttributeError: 'DataFrameGroupBy' object has no attribute 'set_index'

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

The set_index() method is used to set the DataFrame index using existing columns and applies directly to DataFrame objects, not to DataFrameGroupBy objects.

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