48 lines
1.4 KiB
Markdown
48 lines
1.4 KiB
Markdown
# lec7
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## Lab Activity
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This lecture has two correspondnig lab activities in `lab/` using `1994-census-summary.sql` with instrucctions on `aggregation-lab.pdf` and `nested-subqueries-lab.pdf`.
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## Null Operations
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take the following table as a trivial example of working data
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```
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a | b
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-----
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1 | 2
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3 | N
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```
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Where `a` and `b` are attributes and N signifiies a NULL value.
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If we `select a+b from table` we only get back 2 rows like normal but the second row is left empty since we are operating with a NULL value.
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Even if we use multiplication or some kind of comparison against null we simply ignore that row since NULL in sqlite3 doesn't mean 0.
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Instead NULL in sqlite3 actually represents something that doesn't exist.
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> count will treat NULL as 0 however
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This is the only exception to the _ignore NULL_ "rule".
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## Aggregation
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This section we'll deal with functions similar to `count average min max`.
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We call these functions _aggreagate_ functions because they aggregate multiple data points into one.
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> round(integer)
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Rounds off the floating point number to some level of precision.
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> group by _attr_
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This will group attributes to gether in the result of a query
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> having(attribute)
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Similar to `where` however we only care about group scope in this case.
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## Nested Subqueries
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Recall that when we perform a query the result is a table.
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We can leverage this and perform some query to query a resultant table to further our ability to filter results from a table.
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