Unexpected NaN values when merging DataFrames with different index types in Pandas 1.4.0
I'm prototyping a solution and I'm working through a tutorial and I'm working with an scenario when trying to merge two DataFrames that have different index types... I have two DataFrames, one with a default integer index and another with a string index, and when I perform the merge, I end up with NaN values in my result that I wasn't expecting. Here's a simplified version of what I'm doing: ```python import pandas as pd # DataFrame with default integer index left_df = pd.DataFrame({ 'key': ['A', 'B', 'C'], 'value': [1, 2, 3] }) # DataFrame with string index right_df = pd.DataFrame({ 'value': [4, 5, 6]}, index=['A', 'B', 'D']) # Attempt to merge on 'key' result = pd.merge(left_df, right_df, left_on='key', right_index=True, how='left') print(result) ``` I expected to see `NaN` for the 'D' row in the result, but I also see `NaN` values for 'C', which is not even present in the `right_df`. The output looks like this: ``` key value_x value_y 0 A 1 4.0 1 B 2 5.0 2 C 3 NaN ``` The scenario seems to stem from the fact that my left DataFrame's 'key' column is being treated differently than the index in the right DataFrame. I tried resetting the index on the right DataFrame but that didn't solve the question. ```python right_df_reset = right_df.reset_index() result = pd.merge(left_df, right_df_reset, left_on='key', right_on='index', how='left') print(result) ``` This gives me the following output, where I still get `NaN` for 'C', but now I also get an additional column for index. I want to understand the best practice here to avoid getting unwanted NaNs when merging DataFrames with different index types. How should I structure my merge to ensure I'm only getting NaNs where appropriate? This is my first time working with Python stable. What's the correct way to implement this? This is for a application running on Windows 10. I'd be grateful for any help. I'm coming from a different tech stack and learning Python. Could someone point me to the right documentation?