convert a series of strings to a series of pandas Timestamp objects

Question

The way I am doing this looks inefficient, so I figured that there had to be a better way that I am just not seeing.

Current approach:

dates = pd.DataFrame(['2019-10-15', '2019-10-15', '2017-05-24', '2019-11-01', '2019-11-01',
     '2019-11-01', '2019-11-01', '2019-11-01', '2020-01-11', '2019-11-01'], columns=['string'])
dates['timestamp'] = [pd.Timestamp(x) for x in dates['string']]

does this help you? https://stackoverflow.com/questions/466345/converting-string-into-datetime — Ehsan, May 28 '20 at 02:36
dates['timestamp'] = pd.to_datetime(dates['string']) this will works fine — Darkknight, May 28 '20 at 03:01

score 1 · Accepted Answer · answered May 28 '20 at 02:30

1

The following code did the trick for me:

Since I am using inbuilt function and it is a vectorized operation. This would be relatively faster.

dates['timestamp'] = pd.to_datetime(dates['string'])

answered May 28 '20 at 02:30

oreopot

3,392
2
19
28

score 0 · Answer 2 · answered May 28 '20 at 02:24

0

You can use the apply function if you don't want to use a python list comprehension

dates['timestamp'] = dates['string'].apply(pd.Timestamp)

Won't be all that much faster but is a little cleaner imo

answered May 28 '20 at 02:24

Milan

344
1
10

convert a series of strings to a series of pandas Timestamp objects

2 Answers2