Unexpected DataFrame Index Resetting After Filtering with Pandas v1.3.4
I am experiencing an scenario where the index of my DataFrame is resetting unexpectedly after I apply a filter. Here’s the situation: I have a DataFrame containing sales data that looks like this: ```python import pandas as pd # Sample DataFrame data = { 'Product': ['A', 'B', 'C', 'D'], 'Sales': [100, 150, 200, 250], 'Region': ['North', 'South', 'East', 'West'] } df = pd.DataFrame(data) ``` When I filter this DataFrame to only include products with sales greater than 150, I expect the index to remain intact: ```python filtered_df = df[df['Sales'] > 150] print(filtered_df) ``` However, when I print `filtered_df`, I see that the index has been reset to start from 0: ``` Product Sales Region 0 C 200 East 1 D 250 West ``` I tried using `reset_index(drop=True)` to control this behavior, but it seems to be applied automatically. I want to retain the original indices for further analysis. I also checked the `drop` parameter documentation, but I still need to find a way to preserve the original index directly during the filtering step. Is there a way to filter a DataFrame while keeping its original index intact in Pandas v1.3.4?