import pandas as pd dates=['2017-01-05','Jan 5,2017','20170105'] pd.to_datetime(dates) I am expecting the date would be 2017-01-5(YY/mm/dd).But I found Value error: Traceback (most recent call last): File "<stdin>", line 1, in <module> File "C:\dev\Python312\Lib\site-packages\pandas\core\tools\datetimes.py", line 1099, in to_datetime result = convert_listlike(argc, format) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "C:\dev\Python312\Lib\site-packages\pandas\core\tools\datetimes.py", line 433, in _convert_listlike_datetimes return _array_strptime_with_fallback(arg, name, utc, format, exact, errors) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "C:\dev\Python312\Lib\site-packages\pandas\core\tools\datetimes.py", line 467, in _array_strptime_with_fallback result, tz_out = array_strptime(arg, fmt, exact=exact, errors=errors, utc=utc) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "strptime.pyx", line 501, in pandas._libs.tslibs.strptime.array_strptime File "strptime.pyx", line 451, in pandas._libs.tslibs.strptime.array_strptime File "strptime.pyx", line 583, in pandas._libs.tslibs.strptime._parse_with_format ValueError: time data "Jan 5,2017" doesn't match format "%Y-%m-%d", at position 1. You might want to try: - passing `format` if your strings have a consistent format; - passing `format='ISO8601'` if your strings are all ISO8601 but not necessarily in exactly the same format; - passing `format='mixed'`, and the format will be inferred for each element individually. You might want to use `dayfirst` alongside this. Please give me a solution. Please tell me the right way to do it. I want the date would be same. Continue reading...