From 4bbbdee8a93cc272f0e010a0bd4d1d4f3d53a89c Mon Sep 17 00:00:00 2001
From: Alistair Johnson <alistairewj@gmail.com>
Date: Thu, 25 May 2017 10:42:06 -0400
Subject: [PATCH] add tutorial on using cross-tab in postgresql

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 tutorials/sql-crosstab.md | 99 +++++++++++++++++++++++++++++++++++++++++++++++
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 create mode 100644 tutorials/sql-crosstab.md

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+# Cross Tabulation
+
+Cross tabulation, shortened to `crosstab`, is a very common operation when working with data.
+The goal is to count the number of observations stratified by two groups.
+
+PostgreSQL is packaged with an extension which allows cross tabulation.
+First, enable the extension for the database (requires PostgreSQL v9.1 or higher):
+
+```sql
+CREATE EXTENSION tablefunc;
+```
+
+You only need to run this operation *once* per database.
+
+Let's try cross tabulating the admission and discharge locations for all hospital admissions.
+
+First, we need to find out the unique values for the two columns:
+
+```sql
+select distinct admission_location from admissions order by admission_location;
+```
+
+... returns:
+
+```
+    admission_location
+---------------------------
+ CLINIC REFERRAL/PREMATURE
+ EMERGENCY ROOM ADMIT
+ HMO REFERRAL/SICK
+ ** INFO NOT AVAILABLE **
+ PHYS REFERRAL/NORMAL DELI
+ TRANSFER FROM HOSP/EXTRAM
+ TRANSFER FROM OTHER HEALT
+ TRANSFER FROM SKILLED NUR
+ TRSF WITHIN THIS FACILITY
+(9 rows)
+```
+
+
+```sql
+select distinct admission_type from admissions order by admission_type;
+```
+
+... returns:
+
+```
+ admission_type
+----------------
+ ELECTIVE
+ EMERGENCY
+ NEWBORN
+ URGENT
+(4 rows)
+```
+
+Now, with knowledge of the unique values, we can cross tabulate data:
+
+```sql
+SELECT *
+FROM crosstab(
+       'SELECT admission_location, admission_type, count(*) as ct
+        FROM   admissions
+        GROUP BY admission_location, admission_type
+        ORDER BY 1,2'
+      -- below, we list all the unique values in admission_type
+      -- these will become the columns
+      ,'SELECT DISTINCT admission_type FROM admissions ORDER BY 1'
+    )
+AS ct (
+  -- first column has each unique value for the rows
+  "Admission Location" text,
+  -- now we list the columns
+  "ELECTIVE" text, "EMERGENCY" text,
+  "NEWBORN" text, "URGENT" text
+);
+```
+
+... returns:
+
+```
+    Admission Location     | ELECTIVE | EMERGENCY | NEWBORN | URGENT
+---------------------------+----------+-----------+---------+--------
+ CLINIC REFERRAL/PREMATURE | 25       | 10002     | 1987    | 18
+ EMERGENCY ROOM ADMIT      |          | 22754     |         |
+ HMO REFERRAL/SICK         |          | 1         | 101     |
+ ** INFO NOT AVAILABLE **  |          | 5         | 199     |
+ PHYS REFERRAL/NORMAL DELI | 7646     | 1432      | 5553    | 448
+ TRANSFER FROM HOSP/EXTRAM | 19       | 7565      | 23      | 849
+ TRANSFER FROM OTHER HEALT | 3        | 61        |         | 7
+ TRANSFER FROM SKILLED NUR | 13       | 246       |         | 14
+ TRSF WITHIN THIS FACILITY |          | 5         |         |
+(9 rows)
+```
+
+Which is an interesting view of the data! In particular, we can see some sensible counts.
+Elective patients and newborn patients are never admitted from the emergency room.
+Interestingly, urgent patients are never admitted from the emergency room either,
+which helps highlight the subtle differences between `EMERGENCY` and `URGENT`.