convert_string_to_date
Differences
This shows you the differences between two versions of the page.
Both sides previous revisionPrevious revisionNext revision | Previous revision | ||
convert_string_to_date [2022/11/28 04:38] – raju | convert_string_to_date [2022/11/28 05:00] (current) – raju | ||
---|---|---|---|
Line 1: | Line 1: | ||
- | ==== single date; without pandas; to datetime.date ==== | + | ===== Convert string to date ===== |
+ | ==== single date string; without pandas; to datetime.date ==== | ||
Use < | Use < | ||
from datetime import datetime | from datetime import datetime | ||
Line 25: | Line 26: | ||
datetime.date | datetime.date | ||
</ | </ | ||
+ | |||
+ | Ref:- | ||
+ | * https:// | ||
+ | * https:// | ||
+ | |||
+ | ==== series of date strings; using pandas ==== | ||
+ | use < | ||
+ | df[col_name] = pd.to_datetime(df[col_name], | ||
+ | </ | ||
+ | For example < | ||
+ | $ ipython | ||
+ | Python 3.10.6 | packaged by conda-forge | (main, Oct 24 2022, 16:02:16) [MSC v.1916 64 bit (AMD64)] | ||
+ | Type ' | ||
+ | IPython 8.4.0 -- An enhanced Interactive Python. Type '?' | ||
+ | |||
+ | In [1]: | ||
+ | import pandas as pd | ||
+ | data = {' | ||
+ | ' | ||
+ | df = pd.DataFrame(data) | ||
+ | |||
+ | In [2]: | ||
+ | print(df) | ||
+ | | ||
+ | 0 2022-10-24 | ||
+ | 1 2022-10-08 | ||
+ | 2 2022-09-06 | ||
+ | 3 2022-08-08 | ||
+ | 4 2022-06-06 | ||
+ | |||
+ | In [3]: | ||
+ | print(df.dtypes) | ||
+ | date object | ||
+ | tag | ||
+ | dtype: object | ||
+ | |||
+ | In [4]: | ||
+ | df[' | ||
+ | |||
+ | In [5]: | ||
+ | print(df) | ||
+ | date tag | ||
+ | 0 2022-10-24 | ||
+ | 1 2022-10-08 | ||
+ | 2 2022-09-06 | ||
+ | 3 2022-08-08 | ||
+ | 4 2022-06-06 | ||
+ | |||
+ | In [6]: | ||
+ | print(df.dtypes) | ||
+ | date datetime64[ns] | ||
+ | tag | ||
+ | dtype: object | ||
+ | </ | ||
+ | |||
+ | See also: https:// | ||
+ |
convert_string_to_date.1669610300.txt.gz · Last modified: 2022/11/28 04:38 by raju