1. Lighthouse

Level 8 · Price tags when a cost is missing

The request

From Jessica Turner, Merchandising Manager

“For the buyers' review sheet I need one line per product: a price tag with the name and price, and a short cost note. Some products have no cost on file. Those should say so instead of showing a blank.”

Your goal

From products, return product_id, price_tag (name, then ' - $', then unit_price, e.g. 'Alder Oak Coffee Table - $919.00') and cost_note ('cost $' followed by unit_cost, e.g. 'cost $503.50', or the text 'cost unknown' when unit_cost is NULL). Include every product.

  • Read from the products tablenot done yet
  • Show exactly product_id price_tag cost_notenot done yet
  • 120 rowsnot done yet

Your query

SQL

Loading the editor…

    ResultPreview of products · press Run to see yours
    Preview of products
    product_idnamecategorysubcategoryunit_price
    101Vale Velvet LoveseatFurnitureSofas1659.00
    102Alder Oak Coffee TableFurnitureTables919.00
    103Orchard Rattan Dining ChairFurnitureChairs789.00
    104Upland Oak BookcaseFurnitureStorage429.00

    Mote checks your result

    Press Run. Each row that matches the goal becomes a firefly in your lantern.

    Tables

    Harbor & Pine store data, ready to query.

    products120 rows · 8 columns
    • product_idinteger
    • namevarchar
    • categoryvarchar
    • subcategoryvarchar
    • unit_pricedecimal
    • unit_costdecimal
    • launched_ondate
    • is_activeboolean
    First 5 rows of products
    product_idnamecategorysubcategoryunit_priceunit_costlaunched_onis_active
    101Vale Velvet LoveseatFurnitureSofas1659.00NULL2023-09-11true
    102Alder Oak Coffee TableFurnitureTables919.00503.502024-05-16true
    103Orchard Rattan Dining ChairFurnitureChairs789.00429.872023-05-27true
    104Upland Oak BookcaseFurnitureStorage429.00214.702022-12-20true
    105Avery Leather Bed FrameFurnitureBeds449.00232.702021-08-31true
    customers2,018 rows · 9 columns
    • customer_idinteger
    • first_namevarchar
    • last_namevarchar
    • emailvarchar
    • cityvarchar
    • statevarchar
    • signup_datedate
    • segmentvarchar
    • referral_sourcevarchar
    First 5 rows of customers
    customer_idfirst_namelast_nameemailcitystatesignup_datesegmentreferral_source
    1OwenHudsonowen.hudson@icloud.comSan FranciscoCA2022-06-02consumersearch
    2DouglasMendozadmendoza69@gmail.comAtlantaGA2022-06-02consumerNULL
    3HenryBrookshbrooks@lakesidecafe.comLos AngelesCA2022-06-04businessNULL
    4BrianGrahambgraham@bluecedarhomes.comSeattleWA2022-06-06businesspinterest
    5KyleJimenezkjimenez27@yahoo.comIndianapolisIN2022-06-07consumerNULL
    orders12,000 rows · 7 columns
    • order_idinteger
    • customer_idinteger
    • order_datetimestamp
    • statusvarchar
    • channelvarchar
    • shipping_feedecimal
    • coupon_codevarchar
    First 5 rows of orders
    order_idcustomer_idorder_datestatuschannelshipping_feecoupon_code
    10011252023-01-01 20:51:19completedweb0.00NULL
    10021562023-01-02 07:58:46completedweb0.00NULL
    1003222023-01-02 10:25:27completedmarketplace4.99WELCOME10
    1004482023-01-02 11:21:51completedmarketplace4.99WELCOME10
    1005822023-01-02 11:43:36completedweb0.00WELCOME10
    order_items30,338 rows · 6 columns
    • order_item_idinteger
    • order_idinteger
    • product_idinteger
    • quantityinteger
    • unit_pricedecimal
    • discount_pctdecimal
    First 5 rows of order_items
    order_item_idorder_idproduct_idquantityunit_pricediscount_pct
    11001121931.990.00
    21001154311.990.00
    31002154411.990.00
    410021941149.000.00
    51002193219.990.00
    returns1,673 rows · 5 columns
    • return_idinteger
    • order_item_idinteger
    • returned_ondate
    • reasonvarchar
    • refund_amountdecimal
    First 5 rows of returns
    return_idorder_item_idreturned_onreasonrefund_amount
    1142023-01-10damaged83.69
    2422023-01-10wrong_item19.99
    31052023-01-14wrong_item10.99
    4242023-01-16changed_mind26.99
    51262023-01-16late20.99
    employees60 rows · 8 columns
    • employee_idinteger
    • first_namevarchar
    • last_namevarchar
    • departmentvarchar
    • titlevarchar
    • manager_idinteger
    • hire_datedate
    • salaryinteger
    First 5 rows of employees
    employee_idfirst_namelast_namedepartmenttitlemanager_idhire_datesalary
    1CatherineHaleExecutiveChief Executive OfficerNULL2016-03-01285000
    2RobertKimExecutiveChief Operating Officer12017-01-09235000
    3MeganCollinsSalesHead of Sales12018-04-16172000
    4ChloeGutierrezSalesAccount Executive32020-01-2172000
    5FrankBellSalesAccount Executive32023-05-2173000
    web_sessions40,000 rows · 7 columns
    • session_idinteger
    • customer_idinteger
    • started_attimestamp
    • devicevarchar
    • sourcevarchar
    • pages_viewedinteger
    • convertedboolean
    First 5 rows of web_sessions
    session_idcustomer_idstarted_atdevicesourcepages_viewedconverted
    1NULL2023-01-01 23:02:24mobilepaid1false
    2182023-01-01 15:07:49desktoppaid1false
    3NULL2023-01-01 16:55:46desktopdirect7false
    4NULL2023-01-01 12:43:28mobileorganic3false
    5NULL2023-01-01 13:06:21mobilesocial2false
    marketing_spend3,276 rows · 3 columns
    • spend_datedate
    • channelvarchar
    • amountdecimal
    First 5 rows of marketing_spend
    spend_datechannelamount
    2023-01-01paid492.99
    2023-01-01email37.38
    2023-01-01social200.53
    2023-01-02paid709.13
    2023-01-02email64.13

    The lesson

    The starter almost works. Run it and scroll to product 101, the Vale Velvet Loveseat: its price tag is fine, but its cost note is NULL. Nine products have no cost on file, and each of them loses the whole note.

    One NULL blanks the string

    || follows the same rule as arithmetic: anything combined with NULL is NULL. “cost $ plus an unknown number” is unknown, so the database returns NULL rather than guessing. COALESCE takes a list of values and returns the first one that is not NULL, which makes it the standard way to supply a fallback:

    SELECT
      product_id,
      COALESCE('cost $' || unit_cost, 'cost unknown') AS cost_note
    FROM products;

    Product 102 gets ‘cost $503.50’ and product 101 gets ‘cost unknown’. Wrapping the whole concatenation in COALESCE uses the NULL rule on purpose: the label is either complete or replaced, never half-built.

    unit_price and unit_cost are decimals, and || turns them into text with both decimal places, so the coffee table’s tag reads ‘Alder Oak Coffee Table - $919.00’.

    CONCAT behaves differently

    CONCAT(a, b, c) treats a NULL argument as empty text. CONCAT('cost $', unit_cost) therefore gives ‘cost $’ with nothing after it, which looks like a formatting glitch rather than missing data. That is handy for optional parts, such as a middle name, and wrong when the reader needs to know a value is missing.

    Common mistakes

    • COALESCE(unit_cost, 0). It runs, but it states a cost of zero, and anyone computing margin from your sheet gets 100%. Unknown should stay visibly unknown.
    • Forgetting the spaces inside the quotes. ' - $' has a space on each side of the dash; without them the tag reads ‘Alder Oak Coffee Table-$919.00’.
    • COALESCE(unit_cost, 'unknown') on its own. The two values have different types (a decimal and a text), so the database complains. Convert first, or wrap the concatenation as above.

    In SQL Server

    + joins text there, a NULL also blanks the result, and ISNULL(a, b) is the two-argument cousin of COALESCE. A decimal must be converted before it is joined to text:

    SELECT COALESCE('cost $' + CAST(StandardCost AS varchar(20)), 'cost unknown') AS CostNote
    FROM Production.Product;

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