HardSQL challenge #203CASEPIVOTAGGREGATION

Pivot Order Status Counts into Columns with CASE WHEN

Return one row with a separate count column for pending and for shipped orders.

The challenge runs on the SQLabHub practice database (SQLite) and uses the orders table. You can solve it in the browser, with nothing to install.

Solve This SQL Challenge

The task

Count orders by status in columns.

A correct answer returns 1 row with 2 columns: pending, shipped.

Tables used in this challenge

orders 200 rows

id INTEGER (PK) · user_id INTEGER · total REAL · discount REAL · item_count INTEGER · status TEXT · order_date TEXT · shipped_date TEXT · shipping_city TEXT · shipping_country TEXT

First 3 rows of the orders table
iduser_idtotaldiscountitem_countstatusorder_dateshipped_dateshipping_cityshipping_country
1432638.110.253cancelled2024-04-24NULLLos AngelesUSA
2829470.195delivered2024-03-152023-04-09ChicagoUSA
3136683.240.082delivered2023-02-152023-07-10Los AngelesUSA

The first rows of each table are shown. See how all the tables relate on the database schema page.

Expected output

Expected output of the challenge
pendingshipped
2321

The complete result: 1 row. This is the output of the model solution on the practice database.

What you practise

  • Summarising many rows into one value with COUNT, SUM, AVG, MIN or MAX
  • Turning conditions into values with CASE WHEN

Hint and approach

Try the challenge first. Open these only when you need them.

Show the hint

CASE WHEN

Show the step-by-step approach

How the model solution is built, in the order the database evaluates it:

  1. Read from the orders table.
  2. Aggregate over all the rows that are left: compute a conditional count (SUM(CASE WHEN … THEN 1 ELSE 0 END)) of the rows where status equals 'pending' and a conditional count (SUM(CASE WHEN … THEN 1 ELSE 0 END)) of the rows where status equals 'shipped'. With no GROUP BY, the result is a single row.

Model solution

Checking your session…

What to watch for

SQLite has no PIVOT keyword. Each output column is a SUM over a CASE that yields 1 for the wanted status and 0 otherwise. Statuses without a column of their own are simply not counted.

  • CASE WHEN. CASE stops at the first WHEN that is true, so overlapping conditions must be ordered from most to least specific. Without an ELSE, unmatched rows get NULL.
  • Aggregate functions. Aggregates skip NULLs. AVG divides by the number of non-NULL values and COUNT(column) can be smaller than COUNT(*).
Solve This SQL Challenge

Keep learning