👀 Views: 10 💬 Answers: 1 📅 Created: 2025-06-11

pandas dataframe merge multi-index Python

I'm converting an old project and I'm sure I'm missing something obvious here, but I'm currently working with two DataFrames in pandas that both have a multi-level index, and I'm having trouble merging them while ensuring that data integrity is maintained. The first DataFrame, `df1`, has columns `['A', 'B']` and is indexed by `['Category', 'Subcategory']`. The second DataFrame, `df2`, contains columns `['C', 'D']` and is indexed similarly. Here’s what the DataFrames look like: ```python import pandas as pd # Sample DataFrame 1 df1 = pd.DataFrame({ 'A': [1, 2, 3], 'B': [4, 5, 6] }, index=pd.MultiIndex.from_tuples([ ('Fruits', 'Citrus'), ('Fruits', 'Berries'), ('Vegetables', 'Root') ])) # Sample DataFrame 2 df2 = pd.DataFrame({ 'C': [7, 8], 'D': [9, 10] }, index=pd.MultiIndex.from_tuples([ ('Fruits', 'Citrus'), ('Vegetables', 'Leafy') ])) ``` When I try to merge these DataFrames using the `pd.merge()` function, I get unexpected results, and it appears that the rows from `df2` that don't match `df1` are dropped instead of filling with NaN. Here’s the code I'm using: ```python merged_df = pd.merge(df1, df2, left_index=True, right_index=True, how='outer') ``` I expected the resulting DataFrame to include all rows from both DataFrames and fill in NaN where there is no match, but instead, I receive a smaller DataFrame with only the common indices: ```python # Output I'm getting A B C D Category Subcategory Fruits Citrus 1.0 4.0 7.0 9.0 Vegetables Root 3.0 6.0 NaN NaN ``` I’m not sure why the rows from `df2` with the index `('Vegetables', 'Leafy')` are completely missing from the merged DataFrame. Additionally, I want to ensure that if one of the DataFrames has an index that doesn’t match, it should still appear in the merged result with NaN for the other DataFrame’s columns. Am I missing a parameter in the `pd.merge()` method or is there something else I should consider? I’m using pandas version 1.4.2. Any insights on how to achieve the desired merging behavior would be greatly appreciated! What's the best practice here? My development environment is Windows. I'd really appreciate any guidance on this. I'm developing on macOS with Python. What's the best practice here?