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45 lines
1.4 KiB
Markdown
45 lines
1.4 KiB
Markdown
# Compute Median Instead Of Average
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One of the first aggregate functions we might use in PostgreSQL, besides `sum`,
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is `avg`.
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```sql
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select avg(book_count) as average_books_read
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from (
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select users.id, count(books.id) as book_count
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from users
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left join books
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on books.user_id = users.id
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where books.read_in_year = 2025
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group by users.id
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) as user_book_counts;
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```
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This computes the average of the set of values which sums them all up
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and divides by the count. The average (maybe you've heard this also called the
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_mean_) is not always the best way to understand data, especially when there are
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outliers.
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Instead, we might want to compute the _median_ value of our set of data. There
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is no easily identifiable `median` aggregate function. Instead, we can use
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`percentile_cont` with a value of `0.5`. This gets us the 50th percentile of our
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set of data which is the definition of the _median_.
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```sql
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select percentile_cont(0.5) within group (
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order by book_count
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) as median_books_read
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from (
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select users.id, count(books.id) as book_count
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from users
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left join books on books.user_id = users.id and books.read_in_year = 2025
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group by users.id
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) as user_book_counts;
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```
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The full syntax for `percentile_cont` is `percentile_cong(precision) within
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group (order by ...)` because this is an aggregiate that has to work with an
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ordered-set of data.
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[source](https://www.postgresql.org/docs/current/functions-aggregate.html)
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