How to Preserve Original Date Formats When Reading Excel with Pandas
This article explains why pandas adds a time component when reading dates from Excel or CSV files and provides three practical methods—specifying column formats, using datetime.strptime, and setting a date parser for Excel—to keep dates unchanged while still enabling further datetime operations.
The author encountered a pandas issue where dates read from Excel or CSV files were automatically converted to full datetime values (e.g., "2023-01-01 00:00:00").
Solution Overview
Specify column format : Use pandas.read_csv with the parse_dates parameter and treat the date column as a string.
Use datetime.strptime : Convert the column with pd.to_datetime and an explicit format to avoid the default time part.
Specify format when reading Excel : Use pandas.read_excel with the date_parser argument to define the desired date format.
When saving data back to Excel, pandas writes full datetime values; to keep only the date part, format the column with strftime('%Y-%m-%d') before exporting.
These approaches let you read dates without the unwanted time component while still allowing later datetime calculations if needed.
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