Window Functions

Window Functions

Learn how OVER, PARTITION BY, and ranking/analytic functions let you compute running totals, rankings, and row-to-row comparisons without collapsing rows.

Window Functions

Functions that compute values across a set of related rows without collapsing them into a single output row, using OVER().

SQL for Data Science Cheat Sheet

Reference for SQL aggregations, window functions, joins, and CTEs commonly used to analyze and reshape data during exploratory data science work.

What are Window Functions in SQL?

A window function computes a value across a set of related rows (its window) for each row individually, without collapsing those rows into a single output row…

ROW_NUMBER vs RANK vs DENSE_RANK: What is the Difference?

ROW_NUMBER assigns a unique, strictly increasing integer to every row with no ties, RANK assigns the same rank to tied rows but then skips the following rank n…

What Does PARTITION BY Do in SQL?

PARTITION BY divides the rows visible to a window function into independent groups, so the function's calculation restarts from scratch for each group instead…

What are LEAD and LAG Functions in SQL?

LAG and LEAD are offset window functions that let a row directly access a column's value from a preceding row (LAG) or a following row (LEAD) within the same o…

How Do You Calculate a Running Total with Window Functions?

A running total is calculated with SUM(column) OVER (ORDER BY sequence_column), which sums the target column across all rows from the start of the window up to…