How do I specify certain date as the first week and calculate the week number in pandas?-CodePudding

year_start = '2019-05-21'

year_end = '2020-02-22'

How do I get the week number based on the date that I set as first week? For example 2019-05-21 should be Week 1 instead of 2019-01-01

CodePudding user response：

If you just need a function to calculate week no, based on given start and end date:

import pandas as pd
import numpy as np

start_date = "2019-05-21"
end_date = "2020-02-22"
start_datetime = pd.to_datetime(start_date)
end_datetime = pd.to_datetime(end_date)

def get_week_no(date):
    given_datetime = pd.to_datetime(date)
    # if date in range
    if start_datetime <= given_datetime <= end_datetime:
        x =  given_datetime - start_datetime
        # adding 1 as it will return 0 for 1st week
        return int(x / np.timedelta64(1, 'W'))   1
    raise ValueError(f"Date is not in range {start_date} - {end_date}")

print(get_week_no("2019-05-21"))

In the function, we are calculating week no by finding difference between given date and start date in weeks.

CodePudding user response：

Try the following code.

import numpy as np
import pandas as pd

year_start = '2019-05-21'
year_end = '2020-02-22'

# Create a sample dataframe
df = pd.DataFrame(pd.date_range(year_start, year_end, freq='D'), columns=['date'])

# Add the week number
df['week_number'] = (((df.date.view(np.int64) - pd.to_datetime([year_start]).view(np.int64)) / (1e9 * 60 * 60 * 24) - df.date.dt.day_of_week   7) // 7   1).astype(np.int64)

date	week_number
2019-05-21	1
2019-05-22	1
2019-05-23	1
2019-05-24	1
2019-05-25	1
2019-05-26	1
2019-05-27	2
2019-05-28	2

2020-02-18	40
2020-02-19	40
2020-02-20	40
2020-02-21	40
2020-02-22	40

CodePudding user response：

If you do not have dates outside of year_start/year_end, use isocalendar().week and perform a simple subtraction with modulo:

year_start = pd.to_datetime('2019-05-21')
#year_end = pd.to_datetime('2020-02-22')

df = pd.DataFrame({'date': pd.date_range('2019-05-21', '2020-02-22', freq='30D')})

df['week'] = (df['date'].dt.isocalendar().week.astype(int)-year_start.isocalendar()[1])R 1

Output:

        date  week
0 2019-05-21     1
1 2019-06-20     5
2 2019-07-20     9
3 2019-08-19    14
4 2019-09-18    18
5 2019-10-18    22
6 2019-11-17    26
7 2019-12-17    31
8 2020-01-16    35
9 2020-02-15    39