How to merge two DataFrames with differing column names while preserving original DataFrames in Pandas?
I recently switched to I'm upgrading from an older version and This might be a silly question, but I'm working on a project and hit a roadblock..... After trying multiple solutions online, I still can't figure this out. I'm trying to merge two DataFrames in Pandas, but they have different column names for the keys. I want to perform a left merge and still be able to access the original DataFrames after the merge. This is my current approach: ```python import pandas as pd df1 = pd.DataFrame({ 'id': [1, 2, 3], 'value': ['A', 'B', 'C'] }) df2 = pd.DataFrame({ 'key': [1, 2, 4], 'description': ['Apple', 'Banana', 'Date'] }) # Attempting to merge with different key names merged_df = pd.merge(df1, df2, how='left', left_on='id', right_on='key') print(merged_df) ``` When I run this code, the output is as follows: ``` id value key description 0 1 A 1.0 Apple 1 2 B 2.0 Banana 2 3 C NaN NaN ``` However, I notice that the merged DataFrame contains NaN values where there was no matching key in `df2`. My goal is to keep both original DataFrames intact and still perform the merge. I also want to preserve the original column names in the merged DataFrame. Is there a way to achieve this without modifying `df1` or `df2`? Additionally, is there a way to fill the NaN values with a specific default value instead of leaving them as NaN? I've seen some solutions that involve renaming the columns before the merge, but I want to avoid that to maintain the integrity of the original DataFrames. Any insights or best practices would be appreciated! I'm using Pandas version 1.5.3. This is part of a larger CLI tool I'm building. I'm working on a application that needs to handle this. Am I missing something obvious? This is for a application running on Ubuntu 22.04. I appreciate any insights! I'm coming from a different tech stack and learning Python. Could someone point me to the right documentation? The project is a CLI tool built with Python.