Pandas To_Datetime Transformation, Format with Dots
I Want to Aggregate Rows with Time Data Which Were Measured Every Minute to Rows Summing up the Data for Hours/Days. I'm Using the Pandas Resample Method for...
I want to aggregate rows with time data which were measured every minute to rows summing up the data for hours/days. I'm using the pandas resample method for that. Beforehand I need to convert the data type of the column containg the timestamp from object to datetime.
I'm using the pandas to_datetime()-Method for that with the following line of code:
df_resampled['DateTime'] = pd.to_datetime(df_resampled['DateTime'], format="%d.%m.%y %H:%M")
Here I always get the error: "time data '03.11.2020 15:34' does not match format '%d.%m.%y %H:%M' (match)"
I don't really understand why I get this error since the timestamp has the format "day.month.year hour:minute"
1 Answer
Use Y (with a capital) for the YYYY format with century, see strptime documentation:
| Directive | Meaning | Example |
|---|---|---|
| %y | Year without century as a zero-padded decimal number. | 00, 01, …, 99 |
| %Y | Year with century as a decimal number. | 0001, 0002, …, 2013, 2014, …, 9998, 9999 |
df_resampled['DateTime'] = pd.to_datetime(df_resampled['DateTime'],
format="%d.%m.%Y %H:%M")
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