Try it out for yourself: SELECT * FROM t1980 INNER JOIN t2014 ON 1 = 2 Ĭonversely, if we use an always true condition for the ON constraint, then it will be true for every possible combination of rows. If we pass in a condition that is always false, such as 1 = 2, then the JOIN clause will always be false for every combination of rows. Logical screwupsīefore we get to the ostensibly desired answer – let's intentionally screw things up. It's pretty much like a WHERE clause, in which we specify a true/false condition that, if true for a given combination of rows, the query will return those rows in the result. With the ON clause, we are able to constrain how the tables are joined. We know from the beginning of this lesson that there are only two shared names, "Emily" and "Elizabeth". the 16 rows are the maximum number of combinations between the two tables, i.e. There are 16 rows because both tables have 4 rows each, i.e. which column or columns have the similarities that we want to find – so, in typical computer-programming fashion, it just gave us every possible combination. …What happened? Well, we didn't tell the interpreter how the two tables should be joined – i.e. However, this simple query makes for an equally simple but nonsensical result: name It's easier to walk through the syntax, step-by-step, starting from scratch: SELECTing the first table In the sequence of a SELECT statement, the JOIN clause occurs after the FROM clause: SELECT * FROM table_a INNER JOIN table_b ON table_a. This corresponds to the aforementioned scenario, in which we're interested in names that appear in both 19. If you want to follow the explanatory examples that use this example data, just run these queries to create 2 tables – t1980 and t2014, which you can delete later – with the data: DROP TABLE IF EXISTS t1980 CREATE TABLE t1980 ( "name" TEXT, "sex" TEXT, "babies" INTEGER ) INSERT INTO t1980 ( "name", "sex", "babies" ) VALUES ( "Jennifer", "F", 58385 ), ( "Amanda", "F", 35818 ), ( "Elizabeth", "F", 19526 ), ( "Emily", "F", 9004 ) DROP TABLE IF EXISTS t2014 CREATE TABLE t2014 ( "name" TEXT, "sex" TEXT, "babies" INTEGER ) INSERT INTO t2014 ( "name", "sex", "babies" ) VALUES ( "Emma", "F", 20799 ), ( "Olivia", "F", 19674 ), ( "Emily", "F", 12562 ), ( "Elizabeth", "F", 9492 ) Use INNER JOIN to find matching entries between two tablesĪn INNER JOIN is used to find entries that match between two tables. In the next chapter, we'll learn how to use LEFT JOIN to filter for names that exist in only one or the other table. In this chapter, we will learn how to use INNER JOIN to derive the third category of names – Names that exist both in 19. Setting up a small exampleįor the sake of demonstration, let's pretend that babynames_1980 and babynames_2014 are much smaller and contain only 4 names each: Learning to use JOIN statements is learning how to describe a way to compare two different lists of things. But even when dealing with lists of just a few dozen rows each, making comparisons can be so difficult as to not just be done. And there's nothing wrong with doing this when we don't have access to a computer.īut while it's easy to pick out the common and different names, it won't be when the lists are thousands or millions of rows each. This is how we would compare two lists on paper, for example. Looking from the left-to-right to make comparisons – this is the old-fashioned, non-computational – but perfectly common sense – way of making comparisons. Putting them side-by-side is much easier than flipping through different tabs/windows: name The easiest way to imagine this is taking two separate tables and smashing them together, so that they're side-by-side.īelow are two baby name tables, one from 1980 and the other from 2014. The purpose of a JOIN query is to bring together two tables. The next lesson looks at LEFT JOINs – which share the same syntax but give us the ability to find when things are missing from tables. This lesson focuses on the overall syntax of joins and the most common type of join: INNER JOIN. For the data journalist, joins are the feature that completely justify the jump from spreadsheets to databases.Ī JOIN is done through yet another clause of a SELECT statement – and so expect things to get even more cluttered.
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