Creating a Range of Dates in Python

Creating a range of dates in Python

Marginally better...

base = datetime.datetime.today()
date_list = [base - datetime.timedelta(days=x) for x in range(numdays)]

Generate list of months between interval in python

>>> from datetime import datetime, timedelta
>>> from collections import OrderedDict
>>> dates = ["2014-10-10", "2016-01-07"]
>>> start, end = [datetime.strptime(_, "%Y-%m-%d") for _ in dates]
>>> OrderedDict(((start + timedelta(_)).strftime(r"%b-%y"), None) for _ in xrange((end - start).days)).keys()
['Oct-14', 'Nov-14', 'Dec-14', 'Jan-15', 'Feb-15', 'Mar-15', 'Apr-15', 'May-15', 'Jun-15', 'Jul-15', 'Aug-15', 'Sep-15', 'Oct-15', 'Nov-15', 'Dec-15', 'Jan-16']

Update: a bit of explanation, as requested in one comment. There are three problems here: parsing the dates into appropriate data structures (strptime); getting the date range given the two extremes and the step (one month); formatting the output dates (strftime). The datetime type overloads the subtraction operator, so that end - start makes sense. The result is a timedelta object that represents the difference between the two dates, and the .days attribute gets this difference expressed in days. There is no .months attribute, so we iterate one day at a time and convert the dates to the desired output format. This yields a lot of duplicates, which the OrderedDict removes while keeping the items in the right order.

Now this is simple and concise because it lets the datetime module do all the work, but it's also horribly inefficient. We're calling a lot of methods for each day while we only need to output months. If performance is not an issue, the above code will be just fine. Otherwise, we'll have to work a bit more. Let's compare the above implementation with a more efficient one:

from datetime import datetime, timedelta
from collections import OrderedDict

dates = ["2014-10-10", "2016-01-07"]

def monthlist_short(dates):
    start, end = [datetime.strptime(_, "%Y-%m-%d") for _ in dates]
    return OrderedDict(((start + timedelta(_)).strftime(r"%b-%y"), None) for _ in xrange((end - start).days)).keys()

def monthlist_fast(dates):
    start, end = [datetime.strptime(_, "%Y-%m-%d") for _ in dates]
    total_months = lambda dt: dt.month + 12 * dt.year
    mlist = []
    for tot_m in xrange(total_months(start)-1, total_months(end)):
        y, m = divmod(tot_m, 12)
        mlist.append(datetime(y, m+1, 1).strftime("%b-%y"))
    return mlist

assert monthlist_fast(dates) == monthlist_short(dates)

if __name__ == "__main__":
    from timeit import Timer
    for func in "monthlist_short", "monthlist_fast":
        print func, Timer("%s(dates)" % func, "from __main__ import dates, %s" % func).timeit(1000)

On my laptop, I get the following output:

monthlist_short 2.3209939003
monthlist_fast 0.0774540901184

The concise implementation is about 30 times slower, so I would not recommend it in time-critical applications :)

Python generating a list of dates between two dates

You can use pandas.date_range() for this:

import pandas
pandas.date_range(sdate,edate-timedelta(days=1),freq='d')

---

DatetimeIndex(['2019-03-22', '2019-03-23', '2019-03-24', '2019-03-25',
           '2019-03-26', '2019-03-27', '2019-03-28', '2019-03-29',
           '2019-03-30', '2019-03-31', '2019-04-01', '2019-04-02',
           '2019-04-03', '2019-04-04', '2019-04-05', '2019-04-06',
           '2019-04-07', '2019-04-08'],
          dtype='datetime64[ns]', freq='D')

Iterating through a range of dates in Python

Why are there two nested iterations? For me it produces the same list of data with only one iteration:

for single_date in (start_date + timedelta(n) for n in range(day_count)):
    print ...

And no list gets stored, only one generator is iterated over. Also the "if" in the generator seems to be unnecessary.

After all, a linear sequence should only require one iterator, not two.

Update after discussion with John Machin:

Maybe the most elegant solution is using a generator function to completely hide/abstract the iteration over the range of dates:

from datetime import date, timedelta

def daterange(start_date, end_date):
    for n in range(int((end_date - start_date).days)):
        yield start_date + timedelta(n)

start_date = date(2013, 1, 1)
end_date = date(2015, 6, 2)
for single_date in daterange(start_date, end_date):
    print(single_date.strftime("%Y-%m-%d"))

NB: For consistency with the built-in range() function this iteration stops before reaching the end_date. So for inclusive iteration use the next day, as you would with range().

How to create a date range on specific dates for each month in Python?

If need also get first and last value add Index.isin by last and first value - so get all values unique, not duplicates if first or last day is 10:

dates = pd.date_range(start=start_date, end=end_date)
dates = dates[dates.isin(dates[[0,-1]]) | (dates.day == querydate)]

print (dates)
DatetimeIndex(['2020-01-03', '2020-01-10', '2020-02-10', '2020-03-10',
               '2020-04-10', '2020-05-10', '2020-06-10', '2020-07-10',
               '2020-08-10', '2020-09-10', '2020-10-10', '2020-10-19'],
              dtype='datetime64[ns]', freq=None)

If need list:

print (list(dates.strftime('%Y-%m-%d')))
['2020-01-03', '2020-01-10', '2020-02-10', '2020-03-10', 
 '2020-04-10', '2020-05-10', '2020-06-10', '2020-07-10', 
 '2020-08-10', '2020-09-10', '2020-10-10', '2020-10-19']

Changed sample data:

start_date = '2020-01-10'
end_date = '2020-10-10'
querydate = 10

dates = pd.date_range(start=start_date, end=end_date)
dates = dates[dates.isin(dates[[0,-1]]) | (dates.day == querydate)]

print (dates)
DatetimeIndex(['2020-01-10', '2020-02-10', '2020-03-10', '2020-04-10',
               '2020-05-10', '2020-06-10', '2020-07-10', '2020-08-10',
               '2020-09-10', '2020-10-10'],
              dtype='datetime64[ns]', freq=None)

Create a dataframe from a date range in python

I hope I coded exactly what you need.

import pandas as pd

def create_interval(ts1, ts2, interval_name):
    ts_list_dt = pd.date_range(start=ts1, end=ts2).to_pydatetime().tolist()
    ts_list = list(map(lambda x: ''.join(str(x)), ts_list_dt))
    d = {'date': ts_list, 'interval_name': [interval_name]*len(ts_list)}
    df = pd.DataFrame(data=d)
    return df

df = create_interval('2022-01-12', '2022-01-17', 'Holidays')
print(df)

output:

         date             interval_name
0  2022-01-12 00:00:00      Holidays
1  2022-01-13 00:00:00      Holidays
2  2022-01-14 00:00:00      Holidays
3  2022-01-15 00:00:00      Holidays
4  2022-01-16 00:00:00      Holidays
5  2022-01-17 00:00:00      Holidays

If you want DataFrame without Index column, use df = df.set_index('date') after creating DataFrame df = pd.DataFrame(data=d). And then you will get:

    date             interval_name      
2022-01-12 00:00:00      Holidays
2022-01-13 00:00:00      Holidays
2022-01-14 00:00:00      Holidays
2022-01-15 00:00:00      Holidays
2022-01-16 00:00:00      Holidays
2022-01-17 00:00:00      Holidays

Creating datetime range from unique dates and list of time range

You can use nested list comprehension to achieve this:

import datetime

date = [datetime.date(2020, 12, 28), datetime.date(2020, 12, 29), datetime.date(2020, 12, 30), datetime.date(2020, 12, 31)]
time = [datetime.time(9, 15), datetime.time(10, 30), datetime.time(11, 45), datetime.time(13, 0), datetime.time(14, 15)]

output_list = ["{} {}".format(d, t) for d in date for t in time]

where output_list contains:

[
'2020-12-28 09:15:00', 
'2020-12-28 10:30:00', 
'2020-12-28 11:45:00', 
'2020-12-28 13:00:00', 
'2020-12-28 14:15:00', 
'2020-12-29 09:15:00', 
'2020-12-29 10:30:00', 
'2020-12-29 11:45:00', 
'2020-12-29 13:00:00', 
'2020-12-29 14:15:00', 
'2020-12-30 09:15:00', 
'2020-12-30 10:30:00', 
'2020-12-30 11:45:00', 
'2020-12-30 13:00:00', 
'2020-12-30 14:15:00', 
'2020-12-31 09:15:00', 
'2020-12-31 10:30:00', 
'2020-12-31 11:45:00', 
'2020-12-31 13:00:00', 
'2020-12-31 14:15:00'
]

Creating date range pairs in pandas

There was a typo (start=end) that caused dates to have only 1 value.

But fixing the typo only gives you a flat range of dates. If you want those nested pairs, you could shift dates by 4 hours and zip():

dates = pandas.date_range(start=start, end=end, freq='4H')
shift = dates + pandas.Timedelta(hours=4)

pairs = list(zip(dates, shift))

# [(Timestamp('2021-04-02 20:40:00', freq='4H'),
#   Timestamp('2021-04-03 00:40:00', freq='4H')),
#  (Timestamp('2021-04-03 00:40:00', freq='4H'),
#   Timestamp('2021-04-03 04:40:00', freq='4H')),
#  (Timestamp('2021-04-03 04:40:00', freq='4H'),
#   Timestamp('2021-04-03 08:40:00', freq='4H')),
# ...

Or for a list of lists instead of list of tuples:

pairs = list(map(list, zip(dates, shift)))

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