How to handle timezone-aware datetime columns when merging two DataFrames in Pandas?
I'm optimizing some code but I'm performance testing and I am working with two DataFrames in Pandas that both contain a datetime column with timezone information. When I attempt to merge these DataFrames, I encounter issues due to the differing timezones, leading to unexpected results. Here's what I have: ```python import pandas as pd from datetime import datetime # DataFrame 1 with timezone 'UTC' df1 = pd.DataFrame({ 'id': [1, 2], 'date': [ pd.Timestamp(datetime(2023, 1, 1, 12, 0), tz='UTC'), pd.Timestamp(datetime(2023, 1, 2, 12, 0), tz='UTC') ] }) # DataFrame 2 with timezone 'America/New_York' df2 = pd.DataFrame({ 'id': [1, 2], 'date': [ pd.Timestamp(datetime(2023, 1, 1, 7, 0), tz='America/New_York'), pd.Timestamp(datetime(2023, 1, 2, 7, 0), tz='America/New_York') ] }) # Attempting to merge on 'id' and 'date' merged_df = pd.merge(df1, df2, on=['id', 'date'], how='inner') print(merged_df) ``` Upon running this code, I receive the following warning: `UserWarning: The 'date' column has timezone-aware dates. These will not be compared correctly unless you convert them to a common timezone.` Consequently, the merged DataFrame ends up being empty because the dates from both DataFrames do not match in terms of timezone. I have tried converting the timezone of both DataFrames to UTC before the merge, but it still doesn't resolve the issue as the dates need to be the same for a successful match. Here's the code I attempted: ```python df2['date'] = df2['date'].dt.tz_convert('UTC') merged_df = pd.merge(df1, df2, on=['id', 'date'], how='inner') ``` This still results in an empty DataFrame. How can I properly handle merging these timezone-aware datetime columns while ensuring that the datetime values are compared correctly? Any suggestions or best practices would be greatly appreciated. This is part of a larger web app I'm building. Any ideas what could be causing this? Has anyone else encountered this? I'm developing on Debian with Python. Any ideas what could be causing this?