Extracting Data for Administrative Weeks of a Month

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In this article, we will explore how to extract data for administrative weeks of a month. This involves determining the start and end dates of each week that falls under the concept of an “administrative” week, which is defined as a Monday to Sunday period.

Understanding Administrative Weeks

The term “administrative week” refers to a period of seven days starting on any day of the week. In this context, we are interested in extracting data for each administrative week that falls within a given month. This requires us to determine the start and end dates of these weeks, which can vary depending on when the first week of the month begins.

The Problem with Current Queries

The original query provided in the Stack Overflow question attempts to extract data from a database based on the current date. However, it lacks the necessary logic to accurately identify the start and end dates of each administrative week within a given month. This is because the query does not account for the fact that the first week of the month may begin on a day other than Monday.

A New Approach Using Date Arithmetic

To solve this problem, we can use date arithmetic to determine the start and end dates of each administrative week. One approach involves using the generate_series function to generate a range of dates prior to the current date, offset by the number of days between the current day of the week and Monday.

Step 1: Determine the Current Day of the Week

The first step is to determine the current day of the week. This can be done using the EXTRACT function in PostgreSQL, which returns the value of a specified date part (in this case, the day of the week).

{< highlight pgsql >}
-- Get the current day of the week
SELECT EXTRACT(DOW FROM NOW()) AS current_day_of_week;
{/highlight}

Step 2: Calculate the Offset for Administrative Weeks

Next, we need to calculate the offset in days between the current day of the week and Monday. This value will be used to generate a range of dates prior to the current date.

{< highlight pgsql >}
-- Calculate the offset for administrative weeks
SELECT (EXTRACT(DOW FROM NOW()) - 1) * 7 AS offset_days;
{/highlight}

Step 3: Generate a Range of Dates Prior to the Current Date

Using the offset calculated in the previous step, we can generate a range of dates prior to the current date using the generate_series function.

{< highlight pgsql >}
-- Generate a range of dates prior to the current date
SELECT dt FROM (
  SELECT NOW() - (EXTRACT(DOW FROM NOW())::text || ' days')::interval - ((7-v)::text|| ' days')::interval dt 
  FROM generate_series(1,7) v
) AS p1
WHERE EXTRACT(MONTH FROM p1.dt) = EXTRACT(MONTH FROM NOW() - (EXTRACT(DOW FROM NOW())::text || ' days')::interval)
{/highlight}

Step 4: Extract Data for Administrative Weeks

Finally, we can extract the data for administrative weeks by filtering the generated dates based on the date part of the datecreation column in the database table.

{< highlight pgsql >}
-- Extract data for administrative weeks
SELECT p.datecreation 
FROM panneau p 
WHERE date(p.datecreation) IN (
  SELECT date(p1.dt) 
  FROM (
    SELECT NOW() - (EXTRACT(DOW FROM NOW())::text || ' days')::interval - ((7-v)::text|| ' days')::interval dt 
    FROM generate_series(1,7) v
  ) p1 
  WHERE EXTRACT(MONTH FROM p1.dt) = EXTRACT(MONTH FROM NOW() - (EXTRACT(DOW FROM NOW())::text || ' days')::interval))
{/highlight}

Example Use Case: July 2022

To illustrate this concept, let’s consider the month of July 2022. The first week of July would fall on a Monday (July 4th), and subsequent weeks would begin on Sundays.

Week Number	Start Date	End Date
1	July 4th	July 10th
2	July 11th	July 17th
3	July 18th	July 24th
4	July 25th	July 31st
5	August 1st	August 7th

By using the generate_series function to generate a range of dates prior to the current date, we can extract data for each administrative week within the month.

Conclusion

In this article, we explored how to extract data for administrative weeks of a month. By using date arithmetic and generating a range of dates prior to the current date, we can accurately identify the start and end dates of each administrative week. This approach provides a flexible solution for extracting data from databases that require a specific date format.