Postgresql calculate difference between rows

Unleashing the power of LAG()

The magic of LAG

The key to understanding LAG lies in its ability to peer into the past, i.e., to tap into data from an earlier row, without invoking a self-join. A window, like OVER (ORDER BY column), is like a magnifying glass ensuring our data is sorted and ready for computation.

About the first row

The pioneer row, having no ancestors, can create a hiccup in our cool calculations. Giving it a default step-sibling value, such as 0 or null, ensures uniformity.

SELECT
  value - LAG(value, 1, 0) OVER (ORDER BY id) AS diff
FROM
  your_table;


Watch out for stumbling stones

Just like you don't want to trip on an unseen pebble, beware of unsorted data or false gaps! The order column - id in our case, should dance to the rhythm of your data sequence for accurate difference computation.

Nitty-gritty query crafting

The need for a sequence

It's like arranging your sock drawer – sorting matters. A timestamp for time series data, an auto-incrementing ID, or any column that lays down a logical progression is your friend in the ORDER BY clause of the LAG function.

Leaping across intervals

Need to count the stars weekly or tally the cookie jars monthly? Manipulate your ORDER BY clause to ride on the back of LAG(value, n), with n being the rows to look backward.

Custom built defaults

Inject a contextually-aware default for the first row's difference. It elevates the relevancy of your result and gives your analysis that extra credibility.

Extending usage scenarios

Reversing the trend with LEAD

Occasionally, you might desire to be a sort of time-travelling data wizard, comparing a row with the next one. LEAD is your magic spell here; it's a mirror reflection of LAG, peeping into the future.

SELECT
  -- Rumor has it, LEAD can see the future!
  LEAD(value) OVER (ORDER BY id) - value AS lead_diff
FROM
  your_table;


Mastering partitions

Dabbling with a multi-category dataset? PARTITION BY is your superpower to distinguish calculations by each category.

SELECT
  -- They say you should partition your hard drive, why not your data too? 
  value - LAG(value) OVER (PARTITION BY category ORDER BY id) AS partitioned_diff
FROM
  your_table;


Nullifying NULLs

NULL values have been known to play spoilsport in difference calculations. Be proactive by ensuring the domain of non-null values, or dabble in some logic to tame NULL values in your calculations.