👀 Views: 48 💬 Answers: 1 📅 Created: 2025-06-10

pandas datetime timezone Python

I need some guidance on I'm relatively new to this, so bear with me. I tried several approaches but none seem to work. I'm experiencing an scenario while trying to convert a column of datetime strings that include timezone information into actual datetime objects using Pandas version 1.3.2. The strings are formatted like this: `"2023-10-01T12:30:00+00:00"`, and I want them to be converted to timestamps in UTC. I tried using `pd.to_datetime()` but it seems to ignore the timezone data and just treats it as a naive datetime. Here's what I've done so far: ```python import pandas as pd date_strings = ["2023-10-01T12:30:00+00:00", "2023-10-02T14:45:00+00:00"] df = pd.DataFrame(date_strings, columns=["date_string"]) # Attempting to convert the strings to datetime try: df["date_converted"] = pd.to_datetime(df["date_string"]) except Exception as e: print(e) ``` However, when I check the `df.head()` output, the `date_converted` column seems to be in local time rather than UTC. I expected to see the timezone-aware datetime objects, but instead, I get something like this: ``` date_string date_converted 0 2023-10-01T12:30:00+00:00 2023-10-01 12:30:00 1 2023-10-02T14:45:00+00:00 2023-10-02 14:45:00 ``` I've also tried passing the `utc=True` parameter to `pd.to_datetime()`, but it doesn't seem to change the outcome. Is there something I'm missing or a specific way to handle timezones in this context? Any advice on how to ensure that the timezone information is respected during this conversion would be greatly appreciated! Am I missing something obvious? This is for a application running on Debian. Thanks for your help in advance! Could this be a known issue?