to_datetime 无法识别的值类型：<class 'str'></class>

Question

I am trying to convert the 'date' column from string to dateime data type

example of the 'date' column:

array(['2015-08-26 10:24:48.127', '2015-08-26 10:26:41.000',
       '2015-08-26 10:27:52.000', ..., '2015-08-26 10:18:11.000',
       '2015-08-26 10:21:39.000', '2015-08-26 10:23:05.000'], dtype=object)

Attempt at converting to datetime data type: To get the date component from the date column The date column in YYYY-MM-DD format.

order_items['date']= pd.to_datetime('date', format="%Y-%m-%d")```



However i got the following error:

```TypeError                                 Traceback (most recent call last)
~/opt/anaconda3/lib/python3.8/site-packages/pandas/core/arrays/datetimes.py in objects_to_datetime64ns(data, dayfirst, yearfirst, utc, errors, require_iso8601, allow_object)
   1857         try:
-> 1858             values, tz_parsed = conversion.datetime_to_datetime64(data)
   1859             # If tzaware, these values represent unix timestamps, so we

pandas/_libs/tslibs/conversion.pyx in pandas._libs.tslibs.conversion.datetime_to_datetime64()

TypeError: Unrecognized value type: <class 'str'>```

Answer 1

you are passing date literal to the pd.to_datetime function, not the actual date.

if you do something like -

pd.to_datetime('2015-08-26 10:24:48.127', format="%Y-%m-%d")

It should work.

Or if it is a column in dataframe(assuming named df)

pd.to_datetime(df['date'], format="%Y-%m-%d")

Answer 2

You actually need to pass the correct format , the format you have passed to the datetime function doesn't match the records that your array has, and and the correct format for the data you have is %Y-%m-%d %H:%M:%S.%f :

pd.to_datetime(data, format='%Y-%m-%d %H:%M:%S.%f')

#Output
DatetimeIndex(['2015-08-26 10:24:48.127000',        '2015-08-26 10:26:41',
                      '2015-08-26 10:27:52',        '2015-08-26 10:18:11',
                      '2015-08-26 10:21:39',        '2015-08-26 10:23:05'],
              dtype='datetime64[ns]', freq=None)

Answer 3

When passing the date to pd.to_dateframe you did not select the column.

The below code gives a df['date'] column which consists of datetime objects.

import pandas as pd

date_dict= {'date': ['2015-08-26 10:24:48.127', '2015-08-26 10:26:41.000',
       '2015-08-26 10:27:52.000', '2015-08-26 10:18:11.000',
       '2015-08-26 10:21:39.000', '2015-08-26 10:23:05.000']}

df = pd.DataFrame(data=date_dict)

df['date']= pd.to_datetime(df['date'], format="%Y-%m-%d %H:%M:%S.%f")

print(df['date'])

prints

0   2015-08-26 10:24:48.127
1   2015-08-26 10:26:41.000
2   2015-08-26 10:27:52.000
3   2015-08-26 10:18:11.000
4   2015-08-26 10:21:39.000
5   2015-08-26 10:23:05.000
Name: date, dtype: datetime64[ns]