Pandas DataFrame not preserving index after pivot_table operation
I'm stuck on something that should probably be simple... I'm working with an scenario where the index of my DataFrame is not preserved after using the `pivot_table` function in Pandas. I'm working with version 1.3.3 and trying to summarize some sales data by region and product. I expected the resulting DataFrame to maintain the original index, but it seems to reset, causing further issues in my analysis. Here's a snippet of the code I'm using: ```python import pandas as pd # Sample DataFrame data = { 'Region': ['North', 'South', 'North', 'South'], 'Product': ['A', 'A', 'B', 'B'], 'Sales': [100, 150, 200, 250] } df = pd.DataFrame(data) # Attempting to create a pivot table pivot_df = df.pivot_table(index='Region', columns='Product', values='Sales', aggfunc='sum') print(pivot_df) ``` When I run this code, I get the following output: ``` Product A B Region North 100 200 South 150 250 ``` My scenario is that after the pivot operation, the resulting DataFrame `pivot_df` does not retain the original DataFrame's index, which complicates subsequent data manipulations since I rely on the index for merging with another DataFrame later. I've tried resetting the index before the pivot operation using `df.reset_index(drop=True)`, but that doesn't seem to help, as the pivot table still does not maintain the expected index structure. Is there a way to ensure that my index remains intact throughout this operation? Any insights on best practices for handling this would be greatly appreciated! Is there a better approach? I'd love to hear your thoughts on this. I'm coming from a different tech stack and learning Python. Thanks, I really appreciate it!