Pandas groupby with lambda function causing unexpected results on aggregated data
I'm experiencing unexpected behavior when using the `groupby` method with a lambda function on my DataFrame. I'm trying to calculate the average of the 'score' column grouped by 'category', but the output is not what I expected. Here’s a simplified version of my DataFrame: ```python import pandas as pd data = { 'category': ['A', 'A', 'B', 'B', 'C'], 'score': [10, 20, 30, 40, 50] } df = pd.DataFrame(data) ``` When I run the following code to group by 'category' and calculate the average: ```python result = df.groupby('category')['score'].apply(lambda x: x.mean()) ``` I expect to get a series that shows the average score for each category. Instead, I end up getting the following output: ``` category A 15.0 B 35.0 C 50.0 Name: score, dtype: float64 ``` This output looks correct, but when I try to access the averages with indexing: ```python avg_A = result['A'] ``` I get an behavior: `KeyError: 'A'`. I’ve verified that the key exists in the output, but it seems like it’s not directly accessible as I would expect. I also tried converting `result` to a DataFrame and resetting the index, but that felt like a workaround rather than a solution. What am I missing here? Is this a known behavior with Pandas versions or a quirk I should be aware of? I'm using Pandas version 1.3.3. Any insights would be appreciated!