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  3. PostgreSQL Summary Stats and Window Functions
  • 1

    Introduction to window functions

    Free

    In this chapter, you'll learn what window functions are, and the two basic window function subclauses, ORDER BY and PARTITION BY.

  • 2

    Fetching, ranking, and paging

    In this chapter, you'll learn three practical applications of window functions: fetching values from different parts of the table, ranking rows according to their values, and binning rows into different tables.

  • 3

    Aggregate window functions and frames

    In this chapter, you'll learn how to use aggregate functions you're familiar with, like `AVG()` and `SUM()`, as window functions, as well as how to define frames to change a window function's output.

  • 4

    Beyond window functions

    In this last chapter, you'll learn some techniques and functions that are useful when used together with window functions.

Initializing

Exercise

Numbering Olympic games in ascending order

The Summer Olympics dataset contains the results of the games between 1896 and 2012. The first Summer Olympics were held in 1896, the second in 1900, and so on. What if you want to easily query the table to see in which year the 13th Summer Olympics were held? You'd need to number the rows for that.

Instructions

100 XP
  • Assign a number to each year in which Summer Olympic games were held.