Convert column to timestamp - Pandas Dataframe
You can try these as well. Try passing infer_datetime_format = True while reading the file.
if the above method fails try the following
df2 = pd.to_datetime(df.col1)
or
df2 = pd.to_datetime(df['col1'])
df2
Note the above methods will only convert the str to datetime format and return them in df2. In short df2 will have only the datetime format of str without a column name for it. If you want to retain other columns of the dataframe and want to give a header to the converted column you can try the following
df['col1_converetd'] = pd.to_datetime(df.col1)
or
df['col1_converetd'] = pd.to_datetime(df['col1'])
This is comforatble if you dont want to create a dataframe or want to refer the converted column in future together with other attributes of the dataframe.
For the first format you can simply pass to_datetime, for the latter you need to explicitly describe the date format (see the table of available directives in the python docs):
In [21]: df
Out[21]:
col1 col2
0 04-APR-2018 11:04:29 2018040415203
In [22]: pd.to_datetime(df.col1)
Out[22]:
0 2018-04-04 11:04:29
Name: col1, dtype: datetime64[ns]
In [23]: pd.to_datetime(df.col2, format="%Y%m%d%H%M%S")
Out[23]:
0 2018-04-04 15:20:03
Name: col2, dtype: datetime64[ns]