I want to generate a python list containing all months occurring between two dates, with the input and output formatted as follows:
date1 = "2014-10-10" # input start date
date2 = "2016-01-07" # input end date
month_list = ['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'] # output
I found a very succinct way to do this with Pandas, sharing in case it helps anybody:
UPDATE: I've got it down to a one-liner with the help of this post :)
pd.date_range('2014-10-10','2016-01-07',
freq='MS').strftime("%Y-%b").tolist()
OLD ANSWER:
daterange = pd.date_range('2014-10-10','2016-01-07' , freq='1M')
daterange = daterange.union([daterange[-1] + 1])
daterange = [d.strftime('%y-%b') for d in daterange]
The second line prevents the last date from getting clipped off the list.
>>> 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 :)
With pandas, you can have a one liner like this:
import pandas as pd
date1 = "2014-10-10" # input start date
date2 = "2016-01-07" # input end date
month_list = [i.strftime("%b-%y") for i in pd.date_range(start=date1, end=date2, freq='MS')]
You have to use Calendar and Datetime
import calendar
from datetime import *
date1 = datetime.strptime("2014-10-10", "%Y-%m-%d")
date2 = datetime.strptime("2016-01-07", "%Y-%m-%d")
date1 = date1.replace(day = 1)
date2 = date2.replace(day = 1)
months_str = calendar.month_name
months = []
while date1 < date2:
month = date1.month
year = date1.year
month_str = months_str[month][0:3]
months.append("{0}-{1}".format(month_str,str(year)[-2:]))
next_month = month+1 if month != 12 else 1
next_year = year + 1 if next_month == 1 else year
date1 = date1.replace( month = next_month, year= next_year)
print months
This code returns
['Oct-14', 'Nov-14', 'Dec-14', 'Jan-14', 'Feb-15', 'Mar-15', 'Apr-15', 'May-15', 'Jun-15', 'Jul-15', 'Aug-15', 'Sep-15', 'Oct-15', 'Nov-15', 'Dec-15', 'Jan-15']
Here is my solution with a simple list comprehension which uses range to know where months must start and end
from datetime import datetime as dt
sd = dt.strptime('2014-10-10', "%Y-%m-%d")
ed = dt.strptime('2016-01-07', "%Y-%m-%d")
lst = [dt.strptime('%2.2d-%2.2d' % (y, m), '%Y-%m').strftime('%b-%y') \
for y in xrange(sd.year, ed.year+1) \
for m in xrange(sd.month if y==sd.year else 1, ed.month+1 if y == ed.year else 13)]
print lst
produces
['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']
If you're interested in keeping your dates in a Python format, you can try using to_pydatetime().
import pandas as pd
from datetime import datetime
datemin = datetime(2010, 1, 1)
datemax = datetime(2019, 12, 31)
# First day of month
pd.date_range(datemin, datemax, freq='MS').to_pydatetime().tolist()
# Last day of month
pd.date_range(datemin, datemax, freq='M').to_pydatetime().tolist()
Having done similar stuff previously, I took a stab at solving this. Using distinct components for doing this is more flexible and enables you to mix and match them for different use-cases. They also can be tested more easily this way, as you can see by the doctests in iterate_months.
Also I suggest to use datetime.date objects for your input as you can just do more with those. To do that you'll have to first parse your input string, but this is very easily done.
Parsing the date-strings
def datify(date):
if isinstance(date, datetime.date):
return date
elif isinstance(date, datetime.datetime):
return date.date()
else:
# taken from simleo's answer
return datetime.strptime(date, "%Y-%m-%d")
import datetime
def iterate_months(start_date, end_date):
"""Iterate monthly between two given dates.
Emitted will be the first day of each month.
>>> list(iterate_months(datetime.date(1999, 11, 1),
... datetime.date(2000, 2, 1)))
[datetime.date(1999, 11, 1), datetime.date(1999, 12, 1),\
datetime.date(2000, 1, 1), datetime.date(2000, 2, 1)]
"""
assert isinstance(start_date, datetime.date)
assert isinstance(end_date, datetime.date)
assert start_date < end_date
year = start_date.year
month = start_date.month
while True:
current = datetime.date(year, month, 1)
yield current
if current.month == end_date.month and current.year == end_date.year:
break
else:
month = ((month + 1) % 12) or 12
if month == 1:
year += 1
if __name__ == '__main__':
import doctest
doctest.testmod()
def format_month(date):
return date.strftime(r"%b-%y")
start = datify("2014-10-10")
end = datify("2016-01-07")
for entry in iterate_months(start, end):
print format_month(entry)
Or save it as a list:
result = list(iterate_months(start, end))
Find below my approach to this problem using split and simple modulo-based iterations without importing any special module.
date1 = "2014-10-10"
date2 = "2016-01-07"
y0 = int( date1.split('-')[0] ) # 2014
y1 = int( date2.split('-')[0] ) # 2016
m0 = int( date1.split('-')[1] ) - 1 # 10-1 --> 9 because will be used for indexing
m1 = int( date2.split('-')[1] ) - 1 # 01-1 --> 0 because will be used for indexing
months = ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec']
result = []
start = m0
for y in range(y0, y1+1):
for m in range(start,12):
result.append( str( months[m % 12])+'-'+str(y) )
if y == y1 and (m % 12) == m1:
break
start = 0
print result
$ python dates.py
['Oct-2014', 'Nov-2014', 'Dec-2014', 'Jan-2015', 'Feb-2015', 'Mar-2015', 'Apr-2015', 'May-2015', 'Jun-2015', 'Jul-2015', 'Aug-2015', 'Sep-2015', 'Oct-2015', 'Nov-2015', 'Dec-2015', 'Jan-2016']
I came to a solution that uses python-dateutil and works with Python 3.8+:
https://gist.github.com/anatoly-scherbakov/593770d446a06f109438a134863ba969
def month_range(
start: datetime.date,
end: datetime.date,
) -> Iterator[datetime.date]:
"""Yields the 1st day of each month in the given date range."""
yield from itertools.takewhile(
lambda date: date < end,
itertools.accumulate(
itertools.repeat(relativedelta(months=1)),
operator.add,
initial=start,
)
)
If you want a dictionary that contains pair of month's starting date and ending date between your desired years, then here's how to get that.
start_year = int(input("Enter Starting Year: "))
end_year = int(input("Enter Ending Year: "))
import calendar
month_dict = {}
for x in range(start_year, end_year):
for y in range(1, 13):
if y < 10:
start_date = '01'+'-'+'0'+str(y)+'-'+str(x)
end_date = str(calendar.monthrange(x, y)[1])+'-'+'0'+str(y)+'-'+str(x)
month_dict[start_date] = end_date
else:
start_date = '01'+'-'+str(y)+'-'+str(x)
end_date = str(calendar.monthrange(x, y)[1])+'-'+str(y)+'-'+str(x)
month_dict[start_date] = end_date
This gives the following output:
{'01-01-2000': '31-01-2000',
'01-02-2000': '29-02-2000',
'01-03-2000': '31-03-2000',
'01-04-2000': '30-04-2000',
'01-05-2000': '31-05-2000',
'01-06-2000': '30-06-2000',
'01-07-2000': '31-07-2000',
'01-08-2000': '31-08-2000',
'01-09-2000': '30-09-2000',
'01-10-2000': '31-10-2000',
'01-11-2000': '30-11-2000',
'01-12-2000': '31-12-2000',
'01-01-2001': '31-01-2001',
'01-02-2001': '28-02-2001',
'01-03-2001': '31-03-2001',
'01-04-2001': '30-04-2001',
'01-05-2001': '31-05-2001',
'01-06-2001': '30-06-2001',
'01-07-2001': '31-07-2001',
'01-08-2001': '31-08-2001',
'01-09-2001': '30-09-2001',
'01-10-2001': '31-10-2001',
'01-11-2001': '30-11-2001',
'01-12-2001': '31-12-2001',
'01-01-2002': '31-01-2002',
'01-02-2002': '28-02-2002',
'01-03-2002': '31-03-2002',
'01-04-2002': '30-04-2002',
'01-05-2002': '31-05-2002',
'01-06-2002': '30-06-2002',
'01-07-2002': '31-07-2002',
'01-08-2002': '31-08-2002',
'01-09-2002': '30-09-2002',
'01-10-2002': '31-10-2002',
'01-11-2002': '30-11-2002',
'01-12-2002': '31-12-2002',
'01-01-2003': '31-01-2003',
'01-02-2003': '28-02-2003',
'01-03-2003': '31-03-2003',
'01-04-2003': '30-04-2003',
'01-05-2003': '31-05-2003',
'01-06-2003': '30-06-2003',
'01-07-2003': '31-07-2003',
'01-08-2003': '31-08-2003',
'01-09-2003': '30-09-2003',
'01-10-2003': '31-10-2003',
'01-11-2003': '30-11-2003',
'01-12-2003': '31-12-2003',
'01-01-2004': '31-01-2004',
'01-02-2004': '29-02-2004',
'01-03-2004': '31-03-2004',
'01-04-2004': '30-04-2004',
'01-05-2004': '31-05-2004',
'01-06-2004': '30-06-2004',
'01-07-2004': '31-07-2004',
'01-08-2004': '31-08-2004',
'01-09-2004': '30-09-2004',
'01-10-2004': '31-10-2004',
'01-11-2004': '30-11-2004',
'01-12-2004': '31-12-2004',
'01-01-2005': '31-01-2005',
'01-02-2005': '28-02-2005',
'01-03-2005': '31-03-2005',
'01-04-2005': '30-04-2005',
'01-05-2005': '31-05-2005',
'01-06-2005': '30-06-2005',
'01-07-2005': '31-07-2005',
'01-08-2005': '31-08-2005',
'01-09-2005': '30-09-2005',
'01-10-2005': '31-10-2005',
'01-11-2005': '30-11-2005',
'01-12-2005': '31-12-2005',
'01-01-2006': '31-01-2006',
'01-02-2006': '28-02-2006',
'01-03-2006': '31-03-2006',
'01-04-2006': '30-04-2006',
'01-05-2006': '31-05-2006',
'01-06-2006': '30-06-2006',
'01-07-2006': '31-07-2006',
'01-08-2006': '31-08-2006',
'01-09-2006': '30-09-2006',
'01-10-2006': '31-10-2006',
'01-11-2006': '30-11-2006',
'01-12-2006': '31-12-2006',
'01-01-2007': '31-01-2007',
'01-02-2007': '28-02-2007',
'01-03-2007': '31-03-2007',
'01-04-2007': '30-04-2007',
'01-05-2007': '31-05-2007',
'01-06-2007': '30-06-2007',
'01-07-2007': '31-07-2007',
'01-08-2007': '31-08-2007',
'01-09-2007': '30-09-2007',
'01-10-2007': '31-10-2007',
'01-11-2007': '30-11-2007',
'01-12-2007': '31-12-2007',
'01-01-2008': '31-01-2008',
'01-02-2008': '29-02-2008',
'01-03-2008': '31-03-2008',
'01-04-2008': '30-04-2008',
'01-05-2008': '31-05-2008',
'01-06-2008': '30-06-2008',
'01-07-2008': '31-07-2008',
'01-08-2008': '31-08-2008',
'01-09-2008': '30-09-2008',
'01-10-2008': '31-10-2008',
'01-11-2008': '30-11-2008',
'01-12-2008': '31-12-2008',
'01-01-2009': '31-01-2009',
'01-02-2009': '28-02-2009',
'01-03-2009': '31-03-2009',
'01-04-2009': '30-04-2009',
'01-05-2009': '31-05-2009',
'01-06-2009': '30-06-2009',
'01-07-2009': '31-07-2009',
'01-08-2009': '31-08-2009',
'01-09-2009': '30-09-2009',
'01-10-2009': '31-10-2009',
'01-11-2009': '30-11-2009',
'01-12-2009': '31-12-2009',
'01-01-2010': '31-01-2010',
'01-02-2010': '28-02-2010',
'01-03-2010': '31-03-2010',
'01-04-2010': '30-04-2010',
'01-05-2010': '31-05-2010',
'01-06-2010': '30-06-2010',
'01-07-2010': '31-07-2010',
'01-08-2010': '31-08-2010',
'01-09-2010': '30-09-2010',
'01-10-2010': '31-10-2010',
'01-11-2010': '30-11-2010',
'01-12-2010': '31-12-2010',
'01-01-2011': '31-01-2011',
'01-02-2011': '28-02-2011',
'01-03-2011': '31-03-2011',
'01-04-2011': '30-04-2011',
'01-05-2011': '31-05-2011',
'01-06-2011': '30-06-2011',
'01-07-2011': '31-07-2011',
'01-08-2011': '31-08-2011',
'01-09-2011': '30-09-2011',
'01-10-2011': '31-10-2011',
'01-11-2011': '30-11-2011',
'01-12-2011': '31-12-2011',
'01-01-2012': '31-01-2012',
'01-02-2012': '29-02-2012',
'01-03-2012': '31-03-2012',
'01-04-2012': '30-04-2012',
'01-05-2012': '31-05-2012',
'01-06-2012': '30-06-2012',
'01-07-2012': '31-07-2012',
'01-08-2012': '31-08-2012',
'01-09-2012': '30-09-2012',
'01-10-2012': '31-10-2012',
'01-11-2012': '30-11-2012',
'01-12-2012': '31-12-2012',
'01-01-2013': '31-01-2013',
'01-02-2013': '28-02-2013',
'01-03-2013': '31-03-2013',
'01-04-2013': '30-04-2013',
'01-05-2013': '31-05-2013',
'01-06-2013': '30-06-2013',
'01-07-2013': '31-07-2013',
'01-08-2013': '31-08-2013',
'01-09-2013': '30-09-2013',
'01-10-2013': '31-10-2013',
'01-11-2013': '30-11-2013',
'01-12-2013': '31-12-2013',
'01-01-2014': '31-01-2014',
'01-02-2014': '28-02-2014',
'01-03-2014': '31-03-2014',
'01-04-2014': '30-04-2014',
'01-05-2014': '31-05-2014',
'01-06-2014': '30-06-2014',
'01-07-2014': '31-07-2014',
'01-08-2014': '31-08-2014',
'01-09-2014': '30-09-2014',
'01-10-2014': '31-10-2014',
'01-11-2014': '30-11-2014',
'01-12-2014': '31-12-2014',
'01-01-2015': '31-01-2015',
'01-02-2015': '28-02-2015',
'01-03-2015': '31-03-2015',
'01-04-2015': '30-04-2015',
'01-05-2015': '31-05-2015',
'01-06-2015': '30-06-2015',
'01-07-2015': '31-07-2015',
'01-08-2015': '31-08-2015',
'01-09-2015': '30-09-2015',
'01-10-2015': '31-10-2015',
'01-11-2015': '30-11-2015',
'01-12-2015': '31-12-2015',
'01-01-2016': '31-01-2016',
'01-02-2016': '29-02-2016',
'01-03-2016': '31-03-2016',
'01-04-2016': '30-04-2016',
'01-05-2016': '31-05-2016',
'01-06-2016': '30-06-2016',
'01-07-2016': '31-07-2016',
'01-08-2016': '31-08-2016',
'01-09-2016': '30-09-2016',
'01-10-2016': '31-10-2016',
'01-11-2016': '30-11-2016',
'01-12-2016': '31-12-2016',
'01-01-2017': '31-01-2017',
'01-02-2017': '28-02-2017',
'01-03-2017': '31-03-2017',
'01-04-2017': '30-04-2017',
'01-05-2017': '31-05-2017',
'01-06-2017': '30-06-2017',
'01-07-2017': '31-07-2017',
'01-08-2017': '31-08-2017',
'01-09-2017': '30-09-2017',
'01-10-2017': '31-10-2017',
'01-11-2017': '30-11-2017',
'01-12-2017': '31-12-2017',
'01-01-2018': '31-01-2018',
'01-02-2018': '28-02-2018',
'01-03-2018': '31-03-2018',
'01-04-2018': '30-04-2018',
'01-05-2018': '31-05-2018',
'01-06-2018': '30-06-2018',
'01-07-2018': '31-07-2018',
'01-08-2018': '31-08-2018',
'01-09-2018': '30-09-2018',
'01-10-2018': '31-10-2018',
'01-11-2018': '30-11-2018',
'01-12-2018': '31-12-2018',
'01-01-2019': '31-01-2019',
'01-02-2019': '28-02-2019',
'01-03-2019': '31-03-2019',
'01-04-2019': '30-04-2019',
'01-05-2019': '31-05-2019',
'01-06-2019': '30-06-2019',
'01-07-2019': '31-07-2019',
'01-08-2019': '31-08-2019',
'01-09-2019': '30-09-2019',
'01-10-2019': '31-10-2019',
'01-11-2019': '30-11-2019',
'01-12-2019': '31-12-2019',
'01-01-2020': '31-01-2020',
'01-02-2020': '29-02-2020',
'01-03-2020': '31-03-2020',
'01-04-2020': '30-04-2020',
'01-05-2020': '31-05-2020',
'01-06-2020': '30-06-2020',
'01-07-2020': '31-07-2020',
'01-08-2020': '31-08-2020',
'01-09-2020': '30-09-2020',
'01-10-2020': '31-10-2020',
'01-11-2020': '30-11-2020',
'01-12-2020': '31-12-2020',
'01-01-2021': '31-01-2021',
'01-02-2021': '28-02-2021',
'01-03-2021': '31-03-2021',
'01-04-2021': '30-04-2021',
'01-05-2021': '31-05-2021',
'01-06-2021': '30-06-2021',
'01-07-2021': '31-07-2021',
'01-08-2021': '31-08-2021',
'01-09-2021': '30-09-2021',
'01-10-2021': '31-10-2021',
'01-11-2021': '30-11-2021',
'01-12-2021': '31-12-2021'}
here is the similar version of what Pynchia suggestioned, the below implementation is for python 3.8 the one he implemented is for python 2.x
import datetime
st="2020-06-24"
ed="2020-11-24"
start_date = datetime.datetime.strptime(st.strip(), '%Y-%m-%d')
end_date = datetime.datetime.strptime(ed.strip(), '%Y-%m-%d')
months = [datetime.datetime.strptime('%2.2d-%2.2d' % (y, m), '%Y-%m').strftime('%b-%y')
for y in range(start_date.year, end_date.year + 1)
for m in range(start_date.month if y == start_date.year else 1, end_date.month + 1 if y == end_date.year else 13)]
print(months)
Try this out, it will list down all the month from start to end as a continuous chain starting from the start date.
import datetime
a='2021-12-1'
b='2022-1-2'
d1=datetime.datetime.strptime(a,'%Y-%m-%d')
d2=datetime.datetime.strptime(b,'%Y-%m-%d')
months = ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec']
totalmonts=(d2.year-d1.year)*12+d2.month-11+12-d1.month
print(totalmonts)
for i in range(totalmonts):
print(months[(d1.month+i-1)%12])
You could solve this by using Calendar and Datetime libraries.
import calendar
from datetime import datetime, timedelta
# set start and end dates
start_month = datetime.strptime("2022-12", "%Y-%m")
end_month = datetime.now()
# loop and print all in between months
months_list = list()
current_month = start_month
while current_month < end_month:
# append current month
months_list.append(
f"{calendar.month_name[current_month.month][:3]}-{current_month.strftime('%y')}"
)
# increment current month by adding 33 days to 'current_month'
current_month += timedelta(days=33)
# reset day to starting day (i.e. 1st day of the month)
current_month = current_month.replace(day=1)
print(months_list)
The output looks like this:
['Dec-22', 'Jan-23', 'Feb-23', 'Mar-23', 'Apr-23', 'May-23', 'Jun-23', 'Jul-23']
I just joined so don't have enough to comment on atkat12's post, but if you are like me and found that their answer seems to miss the first or last month, it's because they use a frequency of MS:
>>> pandas.date_range("2023-01-25","2023-08-12",freq="MS").strftime("%Y-%m-%d").tolist()
['2023-02-01', '2023-03-01', '2023-04-01', '2023-05-01', '2023-06-01', '2023-07-01', '2023-08-01']
>>> pandas.date_range("2023-01-25","2023-08-12",freq="M").strftime("%Y-%m-%d").tolist()
['2023-01-31', '2023-02-28', '2023-03-31', '2023-04-30', '2023-05-31', '2023-06-30', '2023-07-31']
>>>
M means use the first day of the month, whereas MS means use the last day.
See the docs here for more information.
Based on this however, I found you can make a slightly hacky workaround which gets all months:
>>> pandas.date_range("2023-01-25","2023-08-12",freq="1D").strftime("%Y %B").drop_duplicates().tolist()
['2023 January', '2023 February', '2023 March', '2023 April', '2023 May', '2023 June', '2023 July', '2023 August']
This basically sets the frequency to a day, converts it into the desired monthly output and removes any duplicates. I intially tried this with set(list(...)) but then you end up with things being ordered alphabetically rather than chronologically.
