How to convert csv date and time with milliseconds to datetime with milliseconds-CodePudding

I have a difficult time converting separated date and time columns from a csv file into a merged dataframe datetime column with milliseconds.

original data:

    Date    Time
0   2014/9/2    08:30:00.0
1   2014/9/2    08:37:39.21
2   2014/9/2    08:39:41.2
3   2014/9/2    08:41:23.9
4   2014/9/2    09:13:01.1
5   2014/9/2    09:43:02.49
6   2014/9/2    10:49:16.115
7   2014/9/2    10:58:46.39
8   2014/9/2    11:46:18.5
9   2014/9/2    12:03:43.0
10  2014/9/2    12:56:22.0
11  2014/9/2    13:13:01.0
12  2014/9/2    14:42:22.39
13  2014/9/2    14:50:00.74
14  2014/9/3    08:30:00.0
15  2014/9/3    08:30:11.57
16  2014/9/3    08:39:02.18
17  2014/9/3    08:44:31.74
18  2014/9/3    08:45:16.105
19  2014/9/3    08:47:52.57

concatenating date time column

df['datetime'] = df.Date   str(' ')   df.Time 

0      2014/9/2 08:30:00.0
1     2014/9/2 08:37:39.21
2      2014/9/2 08:39:41.2
3      2014/9/2 08:41:23.9
4      2014/9/2 09:13:01.1
5     2014/9/2 09:43:02.49
6    2014/9/2 10:49:16.115
7     2014/9/2 10:58:46.39
8      2014/9/2 11:46:18.5
9      2014/9/2 12:03:43.0

Trying to parse the string to datetime object:

df['datetime'] = df['datetime'].apply(lambda x: datetime.strptime(x, '%Y/%m/%d %H:%M:%S.f%'))

fails:

ValueError: stray % in format '%Y/%m/%d %H:%M:%S.f%'

What is wrong with that and how to solve it?

CodePudding user response：

The format code for microseconds is %f and not f% as per the documentation.

Try this :

df['datetime'] = df['datetime'].apply(lambda x: datetime.strptime(x, '%Y/%m/%d %H:%M:%S.%f'))

Or, in one shot :

(
    pd.read_csv("test.csv")
        .astype(str).agg(" ".join, axis=1)
        .to_frame("datetime")
        .apply(lambda _: pd.to_datetime(_, format= '%Y/%m/%d %H:%M:%S.%f'))
)

# Output :

                  datetime
0  2014-09-02 08:30:00.000
1  2014-09-02 08:37:39.210
2  2014-09-02 08:39:41.200
3  2014-09-02 08:41:23.900
4  2014-09-02 09:13:01.100
..                     ...
15 2014-09-03 08:30:11.570
16 2014-09-03 08:39:02.180
17 2014-09-03 08:44:31.740
18 2014-09-03 08:45:16.105
19 2014-09-03 08:47:52.570

[20 rows x 1 columns]

#dtypes
datetime    datetime64[ns]
dtype: object