how to Get week number from specified year date in python? - python-3.x

Question

I have a time-series data and i want to get the week number from the initial date
date
20180401
20180402
20180902
20190130
20190401
Things Tried
Code
df["date"]= pd.to_datetime(df.date,format='%Y%m%d')
df["week_no"]= df.date.dt.week
But the week getting reset in 2019 results in getting a common week number of 2018.
is there anything we can do in it ??

Answer 1

You can use this function that will calculate the difference between two days in weeks:
def Wdiff(fromdate, todate):
d = pd.to_datetime(todate) - pd.to_datetime(fromdate)
return int(d / np.timedelta64(1, 'W'))

Answer 2

You can create a datetime object with the specified date, then retrieve the week number using the isocalendar method:
import datetime
myDate = datetime.date(2018, 4, 1)
week = myDate.isocalendar()[1]
print(week)
You could then calculate the total number of remaining weeks in 2018, then add the total number of weeks in each year in between, and finally add the week number of the current date.
For example, this code would print the number of weeks from the 1st of April 2018 to the 6th May 2020:
import datetime
myDate = datetime.date(2018, 4, 1)
currentDate = datetime.date(2020, 5, 6)
weeks = datetime.date(myDate.year, 12, 28).isocalendar()[1] -
myDate.isocalendar()[1]
for i in range(myDate.year, currentDate.year):
weeks += datetime.date(i, 12, 28).isocalendar()[1]
weeks += currentDate.isocalendar()[1]
print(weeks)
Note that because of the way isocalendar works, the 28th of December will always be in the last week of the given year.
The ISO year consists of 52 or 53 full weeks, and where a week starts on a Monday and ends on a Sunday. The first week of an ISO year is the first (Gregorian) calendar week of a year containing a Thursday. This is called week number 1, and the ISO year of that Thursday is the same as its Gregorian year.
You can get more information about isocalendar here: https://docs.python.org/3/library/datetime.html

Answer 3

To get the week number, but as a 2-digit string (with leading zero),
you can run:
df['week_no'] = df.date.dt.strftime('%W')
The result, for slightly extended source data is:
date week_no
0 2018-04-01 13
1 2018-04-02 14
2 2018-09-02 35
3 2018-12-30 52
4 2018-12-31 53
5 2019-01-01 00
6 2019-01-02 00
7 2019-01-03 00
8 2019-01-04 00
9 2019-01-05 00
10 2019-01-06 00
11 2019-01-07 01
12 2019-01-30 04
13 2019-04-01 13
Note that the last day of 2018 (monday) has week No == 53 and "initial" days
in 2019 (up to 2019-01-06 - Sunday) have week No == 00.
If you want this column as int, append .astype(int) to the above code.