[Python] Read-in a csv to Pandas dataframe with timestamp and convert it to isoformat...

I have a csv-file I read in with pandas to a dataframe. The time column is formatted in days since 01-01-1900. The aim is to gain an isoformatted column with the "T" between date and time.

The csv-file looks like:

DateTime,column1,column2,column3,column4,column5
43621.6210327662,1.234,2.665,0.888,3.891,3.762
43621.6210445023,2.232,1.233,0.888,3.789,3.524


My code to read in is:

import pandas as pd
df = pd.read_csv(myfile.csv)
df


and the dataframe contains days since 01-01-1900:

DateTime column1 column2 column3 column4 column5
0 43621.621033 1.234 2.665 0.888 3.891 3.762
1 43621.621045 2.232 1.233 0.888 3.789 3.524


Now I convert the days-formatted date to a more common look:

from datetime import datetime, timedelta
df['DateTime'] = pd.to_datetime('1900-01-01') + pd.to_timedelta(df['DateTime'],'D')
df
DateTime column1 column2 column3 column4 column5
0 2019-06-07 14:54:17.230999464 1.234 2.665 0.888 3.891 3.762
1 2019-06-07 14:54:18.244998936 2.232 1.233 0.888 3.789 3.524


My aim is to have a isoformatted DateTime column that has the "T" between date and time like:

DateTime column1 column2 column3 column4 column5
0 2019-06-07T14:54:17.230999464 1.234 2.665 0.888 3.891 3.762
1 2019-06-07T14:54:18.244998936 2.232 1.233 0.888 3.789 3.524


But the DateTime column seems to be a series instead of a date? I can`t apply something like:

df['DateTime'].isoformat()


How would I proceed?

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