How to group by week in postgresql

sql

prompt-engineering

join

dataframe

byNikita Barsukov·Nov 17, 2024

To group records by week in PostgreSQL, you'll use date_trunc function and specify a 'week' precision. This groups your records right from the start of every week (Monday). Here's an example to illustrate it:

SELECT 
    date_trunc('week', your_date_column) as week_start,  //-- It's just another manic Monday
    COUNT(*) 
FROM 
    your_table 
GROUP BY 
    1
ORDER BY 
    1;  //-- Ascending, just as my aspirations

Notice that you replace your_date_column with the specific date field in your table and your_table with your table's name. This query is set up to count records, grouped by the starting date of each week.

Covering multiple years

Your data might span over multiple years, and it's imperative to include the year in the grouping process. This is crucial to avoid mix-ups when dealing with similar week numbers from different years:

SELECT 
    date_part('year', author_date::date) as year,  //-- A throwback to the 90s (or any year)
    date_trunc('week', author_date::date) as week_start, 
    COUNT(author_email) as commit_count
FROM 
    your_table
GROUP BY 
    1, 2
ORDER BY 
    1, 2;  //-- Like sorting my music playlist

In this case, you replace author_date with your date column and your_table with your table's name. Now your data will get grouped by week, with the year still in sight!

Thorough weekly data analysis

To make sure no week goes unnoticed, even if there's no data for that week, generate a sequence of weeks and join it with your original data:

WITH weekly_series AS (
    SELECT generate_series(
        MIN(date_trunc('week', author_date))::DATE,  //-- Let's start at the very beginning...
        MAX(author_date)::DATE,  //-- ...to infinity and beyond
        '1 week'::INTERVAL  //-- One week at a time
    ) as week_start
    FROM your_table
)
SELECT
    w.week_start,
    To_char(w.week_start, 'YYYY-WW') AS formatted_week,  //-- Week in, week out
    COALESCE(COUNT(yt.author_email), 0) AS commit_count  //-- Count 'em all
FROM 
    weekly_series w
LEFT OUTER JOIN 
    your_table yt
ON 
    date_trunc('week', yt.author_date) = w.week_start  //-- The week is yet young, and so is the data
GROUP BY 
    w.week_start
ORDER BY 
    w.week_start;  //-- set, order, match!

The generate_series function creates a smooth weekly timeline ensuring data consistency with a left outer join, weeks with no data will still show up in your final report.

Addressing data discontinuity

Is your data not evenly spread? Notice some weeks with no activity? A calendar table or a series generation can help address this:

WITH calendar AS (
    SELECT generate_series('2023-01-01'::DATE, '2023-12-31'::DATE, '1 week') AS week_start  //-- A year-long journey
)
SELECT
    c.week_start,
    COUNT(yt.your_date_column)
FROM 
    calendar c
LEFT JOIN 
    your_table yt
ON 
    date_trunc('week', yt.your_date_column) = c.week_start
GROUP BY 
    c.week_start
ORDER BY 
    c.week_start;  //-- Isn't it orderly

Just replace '2023-01-01' and '2023-12-31' with your start and end dates, respectively, to generate an exhaustive weekly report regardless of the gaps in original data.

Formatting for readability

The To_char function enhances readability of your weekly reports:

SELECT
    To_char(date_trunc('week', author_date)::date, 'IYYY-IW') as formatted_week,  //-- It's a date
    COUNT(author_email)
FROM 
    your_table
GROUP BY 
    formatted_week
ORDER BY 
    formatted_week;  //-- Order is maintained, so is my sanity