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. (Replacing the four effect* columns.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. If the number of effects vary or you have additional information per effect, you might consider an n:m relationship between ingredients and effects, implemented by an additional table. If every ingredient has 4 effects your db design is fine. , (SELECT e.name FROM effects e WHERE e.id = i.effect4) AS effect4 , (SELECT e.name FROM effects e WHERE e.id = i.effect3) AS effect3 , (SELECT e.name FROM effects e WHERE e.id = i.effect2) AS effect2 , (SELECT e.name FROM effects e WHERE e.id = i.effect1) AS effect1 You can achieve the same with correlated subqueries: SELECT i.name The query depends on effects.id being unique. LEFT JOIN still keeps the ingredient if any of the effects is missing. LEFT JOIN effects e4 ON e4.id = i.effect4 LEFT JOIN effects e3 ON e3.id = i.effect3 LEFT JOIN effects e2 ON e2.id = i.effect2 LEFT JOIN effects e1 ON e1.id = i.effect1 You need a distinct join for every column: SELECT i.name Any ideas how I can get that effect for all 4 effects? This works for 1, but if I try to do multiple it just crashes. This is the effect I'm going for, but on more than one of the effect columns SELECT i.name, i.weight,i.value, e.name AS 'effect 1'įROM ingredients i JOIN effects e ON effects._id=i.effect1 At the same time I managed how to forget to do it, lol A lot ofitems are going to share the same effects, so instead of inflating this already large database with redundant data, I decided to use a join to save space. columns are the id number for the corresponding item in the effect table. Id, name, weight, value, effect1,effect2,effect3,effect4 I want it to display toast, burned, untoasted, wet, texas So, say I have an item that has values like this: Toast, 1, 2, 3, 4 Something like: SELECT i.name,e.name AS effect1, e.name AS effect2, e.name AS effect3, What I'm trying to do is run a query that will pull those names for each of those effects. The effects reference another table that only has a, id, and name columns. Like this: id, name, effect1, effect2, effect3, effect4 What I have is an item with few columns in it that reference another table for the name of that field. I've not worked with SQL much lately and seem to have forgotten how to do this. This is pretty much just a simple join statemnet I believe.
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