Pandas DataFrame Not Updating After GroupBy and Transform Operations
I'm confused about I'm building a feature where I've been working on this all day and After trying multiple solutions online, I still can't figure this out... I'm encountering an issue with updating a pandas DataFrame after performing a `groupby` followed by a `transform` operation. I want to calculate the mean of a specific column grouped by another column and then update the original DataFrame with these computed values. However, the changes don't seem to reflect in my original DataFrame. Here's what I've tried: ```python import pandas as pd # Sample DataFrame np.random.seed(0) data = { 'category': ['A', 'A', 'B', 'B', 'C', 'C'], 'value': [10, 20, 30, 40, 50, 60] } df = pd.DataFrame(data) # Attempting to calculate the mean by category mean_value = df.groupby('category')['value'].transform('mean') # Trying to update the original DataFrame # This is where I'm expecting the DataFrame to be updated # I thought this would work, but it does not seem to reflect changes in 'value' df['mean_value'] = mean_value print(df) ``` The output shows the `mean_value` column correctly populated, but I expected the `value` column to be replaced by the mean values. Instead, I see the original values still present. I considered using `apply`, but I’m concerned about performance overhead. Here’s the output I get for clarity: ``` category value mean_value 0 A 10 15.0 1 A 20 15.0 2 B 30 35.0 3 B 40 35.0 4 C 50 55.0 5 C 60 55.0 ``` I am using pandas version 1.3.3 and Python 3.9.7. Can anyone shed light on whether I'm misunderstanding how `transform` works in this context? I would appreciate any insights or suggestions for achieving my goal effectively. Has anyone else encountered this? What am I doing wrong? I'm developing on macOS with Python. Any pointers in the right direction? I'm working with Python in a Docker container on Debian. I'd love to hear your thoughts on this.