Pandas strptime returns a string instead of DateTime object [duplicate] - python-3.x

Question

This question already has answers here:
How to convert string to datetime format in pandas python?
(3 answers)
Closed 1 year ago.
I have the following pandas DataFrame:
data = pd.DataFrame({"id": [1, 2, 3, 4, 5],
"end_time": ["2016-01-13", "2016-01-01", "2016-11-12", "2016-01-17", "2016-03-13"]})
I want to transform the end_time column to a column of datetime objects. But when I do it like this (like it is suggested everywhere):
data["end"] = data["end_time"].apply(lambda x: datetime.datetime.strptime(x, "%Y-%m-%d"))
the output is still a string column:
id end_time end
0 1 2016-01-13 2016-01-13
1 2 2016-01-01 2016-01-01
2 3 2016-11-12 2016-11-12
3 4 2016-01-17 2016-01-17
4 5 2016-03-13 2016-03-13
How to solve this?

Answer 1

strftime is designed to return a string object, details.
If we want to convert end_time to datetime64[ns] and assign to new column named end then we can use:
data['end'] = pd.to_datetime(data.end_time)
strptime will also covert the string to datetime64[ns]. But preferable is to_datetime method.
data["end"] = data["end_time"].apply(lambda x: datetime.datetime.strptime(x, "%Y-%m-%d"))
data.info()
Output
id end_time end
0 1 2016-01-13 2016-01-13
1 2 2016-01-01 2016-01-01
2 3 2016-11-12 2016-11-12
3 4 2016-01-17 2016-01-17
4 5 2016-03-13 2016-03-13
Datatypes:
data.info()
Output
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 5 entries, 0 to 4
Data columns (total 3 columns):
# Column Non-Null Count Dtype
--- ------ -------------- -----
0 id 5 non-null int64
1 end_time 5 non-null object
2 end 5 non-null datetime64[ns]
dtypes: datetime64[ns](1), int64(1), object(1)
memory usage: 248.0+ bytes