Python date time formatting - String to a specified format

Question

I am looking to convert raw string to a specified data time format.

Here's the sample data:

0              47 mins
1       1 hour 25 mins
2       1 hour 27 mins
3               6 mins

Is the above one of the supported date time formats in python that can be transformed using some function - to_datetime or strftime? or would this need to handled/parsed out differently.

Expected format:

jpp · Accepted Answer · 2018-10-05 13:28:51Z

3

You have 2 potential formats, so you can try them each:

s = pd.Series(['47 mins', '1 hour 25 mins', '1 hour 27 mins', '6 mins'])

dt1 = pd.to_datetime(s, format='%H hour %M mins', errors='coerce')
dt2 = pd.to_datetime(s, format='%M mins', errors='coerce')

res = dt1.fillna(dt2).dt.strftime('%H:%M')

print(res)

0    00:47
1    01:25
2    01:27
3    00:06
dtype: object

answered Oct 5, 2018 at 13:28

jpp

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Comments

piRSquared · Accepted Answer · 2018-10-05 13:43:13Z

2

You can convert some keywords to appropriate things to be passed to pandas.Timedelta

d = {'mins': 'minutes', 'secs': 'seconds', 'hour': 'hours'}
td = [
    pd.Timedelta(**dict(zip(s[1::2], map(float, s[::2]))))
    for s in [s.split() for s in s.replace(d, regex=True)]
]

pd.Series(td, s.index)

0   00:47:00
1   01:25:00
2   01:27:00
3   00:06:00
dtype: timedelta64[ns]

answered Oct 5, 2018 at 13:43

piRSquared

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2 Comments

kms Over a year ago

Solution looks elegant. If you don't mind, can you add a few comments around the td block.

jpp Over a year ago

This solution does look neat :). I have sneaky feeling that repeated built-in str.replace without regex will be more efficient than pd.Series.replace(regex=True).

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