Python - Converting Datetime objects in series while keeping non-date time objects the same

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I have the following series:

myseries = pd.Series([' Period : From 1 February 2020 to 31 January 2021',
                         ' Period : 1 January 2020 to 31 December 2020',
                         ' Period 67 months',
                         ' Period: 8 Months'])

I want to convert the datetime objects where there are two dates (only the first 2) into datetime format, while keeping the others in their original format.

i.e - [('02-01-2020', '01-31-2021'), ('01-01-2020', '12-31-2020'), 'Period: 67 Months', 'Period: 8 Months']

I tried the following, but I'm getting a datetime object for the ones that don't have a proper date.

for i,v in myseries.iteritems():
    matches = list(datefinder.find_dates(v))
    if len(matches) > 0:
        print(matches)

I've tried using the staticmethod argument in datefinder's find_dates(), which gives me the following. I can work with this however, I'm unable to extract the objects I require.

[(datetime.datetime(2020, 2, 1, 0, 0), '1 February 2020'), (datetime.datetime(2021, 1, 31, 0, 0), '31 January 2021')]
[(datetime.datetime(2020, 1, 1, 0, 0), '1 January 2020'), (datetime.datetime(2020, 12, 31, 0, 0), '31 December 2020')]
[(datetime.datetime(2067, 4, 4, 0, 0), '67 mon')]
[(datetime.datetime(2020, 4, 8, 0, 0), '8 Mon')]

My desired output is 2 lists:

date_1 = ['1 February 2020', '1 January 2020', '67 mon', '8 Mon']
date_2 = ['31 January 2021', '31 December 2020', '67 mon', '8 Mon']
pandas python-3.x datetime python
1 Answers

IIUC:

myseries.apply(lambda x: [x[1] for x in datefinder.find_dates(x, source=True)][:2] if not pd.isna(x) else [])

Basically, use the source parameter to get the original date, then if the list of dates is bigger than 2, get the first 2.

If you want date_1 and date_2:

date_1 = []
date_2 = []

dates = myseries.apply(lambda x: [x[1] for x in datefinder.find_dates(x, source=True)][:2])
for date in dates:
    if len(date)==0:
        date_1.append(np.nan)
        date_2.append(np.nan)
    if len(date)>0:
        date_1.append(date[0])

    if len(date)>1:
        date_2.append(date[1])

    elif len(date)>0:
        date_2.append(date[0])
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