Week of a month pandas

I'm trying to get week on a month, some months might have four weeks some might have five. For each date i would like to know to which week does it belongs to. I'm mostly interested in the last week of the month.

data = pd.DataFrame(pd.date_range(' 1/ 1/ 2000', periods = 100, freq ='D'))

0  2000-01-01
1  2000-01-02
2  2000-01-03
3  2000-01-04
4  2000-01-05
5  2000-01-06
6  2000-01-07

See this answer and decide which week of month you want.

There's nothing built-in, so you'll need to calculate it with apply. For example, for an easy 'how many 7 day periods have passed' measure.

data['wom'] = data[0].apply(lambda d: (d.day-1) // 7 + 1)

For a more complicated (based on the calender), using the function from that answer.

import datetime
import calendar

def week_of_month(tgtdate):
    tgtdate = tgtdate.to_datetime()

    days_this_month = calendar.mdays[tgtdate.month]
    for i in range(1, days_this_month):
        d = datetime.datetime(tgtdate.year, tgtdate.month, i)
        if d.day - d.weekday() > 0:
            startdate = d
            break
    # now we canuse the modulo 7 appraoch
    return (tgtdate - startdate).days //7 + 1

data['calendar_wom'] = data[0].apply(week_of_month)

I've used the code below when dealing with dataframes that have a datetime index.

import pandas as pd
import math

def add_week_of_month(df):
    df['week_in_month'] = pd.to_numeric(df.index.day/7)
    df['week_in_month'] = df['week_in_month'].apply(lambda x: math.ceil(x))
    return df

If you run this example:

df = test = pd.DataFrame({'count':['a','b','c','d','e']},
                     index = ['2018-01-01', '2018-01-08','2018-01-31','2018-02-01','2018-02-28'])
df.index = pd.to_datetime(df.index)

you should get the following dataframe

               count  week_in_month

2018-01-01     a              1
2018-01-08     b              2
2018-01-31     c              5
2018-02-01     d              1
2018-02-28     e              4

TL;DR

import pandas as pd

def weekinmonth(dates):
    """Get week number in a month.
    
    Parameters: 
        dates (pd.Series): Series of dates.
    Returns: 
        pd.Series: Week number in a month.
    """
    firstday_in_month = dates - pd.to_timedelta(dates.dt.day - 1, unit='d')
    return (dates.dt.day-1 + firstday_in_month.dt.weekday) // 7 + 1
    
    
df = pd.DataFrame(pd.date_range(' 1/ 1/ 2000', periods = 100, freq ='D'), columns=['Date'])
weekinmonth(df['Date'])

0     1
1     1
2     2
3     2
4     2
     ..
95    2
96    2
97    2
98    2
99    2
Name: Date, Length: 100, dtype: int64

Explanation

At first, calculate first day in month (from this answer: How floor a date to the first date of that month?):

df = pd.DataFrame(pd.date_range(' 1/ 1/ 2000', periods = 100, freq ='D'), columns=['Date'])
df['MonthFirstDay'] = df['Date'] - pd.to_timedelta(df['Date'].dt.day - 1, unit='d')
df

         Date MonthFirstDay
0  2000-01-01    2000-01-01
1  2000-01-02    2000-01-01
2  2000-01-03    2000-01-01
3  2000-01-04    2000-01-01
4  2000-01-05    2000-01-01
..        ...           ...
95 2000-04-05    2000-04-01
96 2000-04-06    2000-04-01
97 2000-04-07    2000-04-01
98 2000-04-08    2000-04-01
99 2000-04-09    2000-04-01

[100 rows x 2 columns]

Obtain weekday from first day:

df['FirstWeekday'] = df['MonthFirstDay'].dt.weekday
df

         Date MonthFirstDay  FirstWeekday
0  2000-01-01    2000-01-01             5
1  2000-01-02    2000-01-01             5
2  2000-01-03    2000-01-01             5
3  2000-01-04    2000-01-01             5
4  2000-01-05    2000-01-01             5
..        ...           ...           ...
95 2000-04-05    2000-04-01             5
96 2000-04-06    2000-04-01             5
97 2000-04-07    2000-04-01             5
98 2000-04-08    2000-04-01             5
99 2000-04-09    2000-04-01             5

[100 rows x 3 columns]

Now I can calculate with modulo of weekdays to obtain the week number in a month:

1. Get day of the month by df['Date'].dt.day and make sure that begins with 0 due to modulo calculation df['Date'].dt.day-1.
2. Add weekday number to make sure which day of month starts + df['FirstWeekday']
3. Be safe to use the integer division of 7 days in a week and add 1 to start week number in month from 1 // 7 + 1.

Whole modulo calculation:

df['WeekInMonth'] = (df['Date'].dt.day-1 + df['FirstWeekday']) // 7 + 1
df

         Date MonthFirstDay  FirstWeekday  WeekInMonth
0  2000-01-01    2000-01-01             5            1
1  2000-01-02    2000-01-01             5            1
2  2000-01-03    2000-01-01             5            2
3  2000-01-04    2000-01-01             5            2
4  2000-01-05    2000-01-01             5            2
..        ...           ...           ...          ...
95 2000-04-05    2000-04-01             5            2
96 2000-04-06    2000-04-01             5            2
97 2000-04-07    2000-04-01             5            2
98 2000-04-08    2000-04-01             5            2
99 2000-04-09    2000-04-01             5            2

[100 rows x 4 columns]

This seems to do the trick for me

df_dates = pd.DataFrame({'date':pd.bdate_range(df['date'].min(),df['date'].max())})
df_dates_tues = df_dates[df_dates['date'].dt.weekday==2].copy()
df_dates_tues['week']=np.mod(df_dates_tues['date'].dt.strftime('%W').astype(int),4)