2f:T6b6,testYourKnowledge([ { title: 'Aggregation', backText: [`You don't always need a GROUP BY clause to aggregate values in SQL. You only need a GROUP BY when you are aggregating by some value. To aggregate all values, exclude the GROUP BY clause and only use aggregation functions in the SELECT clause.`, `If you try to aggregate values in a SQL query by some column name, then you will need a GROUP BY clause, and will see an error message if its missing.`], question: "To aggregate values in a SQL query, you always need a GROUP BY clause", answer: false }, { title: 'DuckDB', backText: ['While a database just about ducks would sure be nice, DuckDB is not that.', 'DuckDB is a database framework and is used in Observable to create SQL databases in notebooks.'], question: 'DuckDB is a database on the various types of duck breeds, their wingspan, and bill length.', answer: false }, { title: 'Ordering Clauses', backText: [`Order matter in SQL queries! If you write your clauses in the wrong order, you will get an error message`, `Every SELECT statement will start with the SELECT clause`, `The general order is SELECT ➡️ FROM ➡️ WHERE ➡️ GROUP BY ➡️ HAVING ➡️ ORDER BY ➡️ LIMIT`], question: `The order of your SELECT clauses does not matter in SQL.`, answer: false }, { title: 'Star Operator', backText: [`While you can use the star operator for multiply two values, it's also the short-hand to pull all the columns from a table.`, `For example, SELECT * FROM myTable will pull all the data from myTable.`], question: `The star operator (*) in SQL is only for multiplying two numerical values.`, answer: false }, ], 300, 300)30:[] 2d:{"title":"SQL Course: Session 1","cells":[{"id":0,"value":"# SQL Course: Session 1","pinned":false,"hidden":false,"mode":"md"},{"id":40,"value":"- [Session 1 slide deck](https://docs.google.com/presentation/d/19CTi6r8VDtptlL4l60J6NOKmYXEyPsTBVmgefs-P0m0/edit?usp=sharing)","pinned":false,"hidden":false,"mode":"md"},{"id":5,"value":"For the hands-on portion of this course, we'll use the [Pizza Paradise](https://observablehq.com/@observablehq/pizza-paradise-data) dataset. ","pinned":false,"hidden":false,"mode":"md"},{"id":8,"value":"import { pizzeriaDB } from \"@observablehq/pizza-paradise-data\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":29,"value":"note(md`__Note:__ This is a large, realistic mock dataset, so it may take a few seconds for it to load in your notebook.`)","pinned":false,"hidden":false,"mode":"ojs"},{"id":43,"value":"---\n## Activity 1\n
","pinned":false,"hidden":false,"mode":"md"},{"id":57,"value":"### Observable Setup\n1. Sign-in / Sign-up\n2. Fork this notebook\n4. Edit and run the cell below","pinned":false,"hidden":false,"mode":"md"},{"id":72,"value":"note(md`__Note:__ You can run a cell by clicking on the play button to the right of the code, or using Shift + Enter`)","pinned":false,"hidden":false,"mode":"ojs"},{"id":63,"value":"whereIHaveLived = [\n { location: \"Long Island, New York\", date: \"2000-01-01\" },\n { location: \"Poughkeepsie\", date: \"2005-09-01\" },\n { location: \"Prague\", date: \"2007-09-01\" },\n { location: \"Poughkeepsie\", date: \"2008-01-01\" },\n { location: \"Brooklyn\", date: \"2009-06-01\" },\n { location: \"Boulder\", date: \"2011-08-01\" },\n { location: \"Brooklyn\", date: \"2013-04-01\" },\n { location: \"Boulder\", date: \"2019-12-01\" }\n]","pinned":true,"hidden":false,"mode":"ojs"},{"id":67,"value":"SELECT * FROM whereIHaveLived","pinned":true,"hidden":false,"mode":"sql","output":"","database":"var:whereIHaveLived"},{"id":55,"value":"---\n## Activity 2\n
","pinned":false,"hidden":false,"mode":"md"},{"id":12,"value":"### Select * Query\n- Use `*` to select all the columns","pinned":false,"hidden":false,"mode":"md"},{"id":27,"value":"SELECT * FROM stores","pinned":true,"hidden":false,"mode":"sql","output":"","database":"var:pizzeriaDB"},{"id":79,"value":"---\n## Activity 3\n
","pinned":false,"hidden":false,"mode":"md"},{"id":88,"value":"### Select specific columns\n- Separate column names with a comma","pinned":false,"hidden":false,"mode":"md"},{"id":81,"value":"SELECT city\n , zipcode\n , state \n FROM stores","pinned":true,"hidden":false,"mode":"sql","output":"","database":"var:pizzeriaDB"},{"id":92,"value":"---\n## Activity 4\n
","pinned":false,"hidden":false,"mode":"md"},{"id":98,"value":"### Select distinct values\n- Use SELECT DISTINCT to get distinct values of states from the stores table","pinned":false,"hidden":false,"mode":"md"},{"id":100,"value":"SELECT DISTINCT state \n FROM stores","pinned":true,"hidden":false,"mode":"sql","output":"","database":"var:pizzeriaDB"},{"id":218,"value":"- Use SELECT DISTINCT to get distinct values of states and cities from the stores table","pinned":false,"hidden":false,"mode":"md"},{"id":132,"value":"SELECT DISTINCT state\n , city\n FROM stores","pinned":true,"hidden":false,"mode":"sql","output":"","database":"var:pizzeriaDB"},{"id":118,"value":"---\n## Activity 5\n
","pinned":false,"hidden":false,"mode":"md"},{"id":117,"value":"### Aggregate values\n- Count the number of stores by state using GROUP BY","pinned":false,"hidden":false,"mode":"md"},{"id":119,"value":"SELECT state\n , count(id) as num_stores\n FROM stores\n GROUP BY state","pinned":true,"hidden":false,"mode":"sql","output":"","database":"var:pizzeriaDB"},{"id":138,"value":"- Count the number of stores","pinned":false,"hidden":false,"mode":"md"},{"id":143,"value":"SELECT count(*) as num_stores\n FROM stores","pinned":true,"hidden":false,"mode":"sql","output":"","database":"var:pizzeriaDB"},{"id":257,"value":"SELECT count(distinct state) as num_stores\n FROM stores","pinned":true,"hidden":false,"mode":"sql","output":"","database":"var:pizzeriaDB"},{"id":140,"value":"- Count the number of products","pinned":false,"hidden":false,"mode":"md"},{"id":150,"value":"SELECT count(*) as num_products\n FROM products","pinned":true,"hidden":false,"mode":"sql","output":"","database":"var:pizzeriaDB"},{"id":148,"value":"- Count the number of products by category, and find the average price","pinned":false,"hidden":false,"mode":"md"},{"id":153,"value":"SELECT Category\n , avg(Price) as avg_price\n , count(*) as num_products\n FROM products\n GROUP BY Category","pinned":true,"hidden":false,"mode":"sql","output":"","database":"var:pizzeriaDB"},{"id":160,"value":"- Count the number of distinct prices by category","pinned":false,"hidden":false,"mode":"md"},{"id":165,"value":"","pinned":true,"hidden":false,"mode":"sql","output":"","database":"var:pizzeriaDB"},{"id":185,"value":"- Count the number of products by category AND size","pinned":false,"hidden":false,"mode":"md"},{"id":190,"value":"SELECT Category\n , \"Size\"\n , avg(Price) as avg_price\n , count(*) as num_products\n FROM products\n GROUP BY Category\n , \"Size\"","pinned":true,"hidden":false,"mode":"sql","output":"","database":"var:pizzeriaDB"},{"id":198,"value":"---\n## Wrap Up\nTest your knowledge from session one with these short questions.","pinned":false,"hidden":false,"mode":"md"},{"id":200,"value":"$2f","pinned":false,"hidden":false,"mode":"ojs"},{"id":21,"value":"

","pinned":false,"hidden":false,"mode":"md"},{"id":23,"value":"

","pinned":false,"hidden":false,"mode":"md"},{"id":24,"value":"

","pinned":false,"hidden":false,"mode":"md"},{"id":16,"value":"---\n## Appendix","pinned":false,"hidden":false,"mode":"md"},{"id":18,"value":"import {note} from \"@observablehq/callout-boxes\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":51,"value":"import { showMe } from \"@observablehq/show-me\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":195,"value":"import {testYourKnowledge} from \"@observablehq/test-your-knowledge-cards\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":105,"value":"color = d3.schemeBlues[7]","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W30","stdlib":"1","titling":"auto"}