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Groups > comp.lang.python > #106886
| From | Daiyue Weng <daiyueweng@gmail.com> |
|---|---|
| Newsgroups | comp.lang.python |
| Subject | python pandas convert strings to datetime problems |
| Date | 2016-04-11 17:08 +0100 |
| Message-ID | <mailman.32.1460390927.15650.python-list@python.org> (permalink) |
| References | <CAF_EDkvyR4Ri7R+pEWNQdEenVi6pir9zGC6ZKew2eCw93ZuJ8Q@mail.gmail.com> |
Hi, I need to compare the years in a Series. The values in the Series is like '1996', '2015', '2006-01-02' or '20130101' etc. The code I created is, col_value_series = pd.to_datetime(col_value_series, infer_datetime_format=True) min_year = col_value_series.min().year max_year = col_value_series.max().year current_year = datetime.date.today().year res1 = min_year > 1970 res2 = max_year < current_year return min_year > 1970 and max_year < current_year the code is working fine on the values like '20030101' and '2006-01-02', which are converted to datetime, i.e. '2003-01-01'. But it converted values '1996' or '2015' to '1970-01-01 00:00:00.000001996' and '1970-01-01 00:00:00.000002015', which are completely wrong (meaning the years are all 1970 now). So how to resolve the issue. thanks
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python pandas convert strings to datetime problems Daiyue Weng <daiyueweng@gmail.com> - 2016-04-11 17:08 +0100
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