Transpose rows to columns in SQLite - sqlite

Question

I have data like this:
I am trying to transform it to this (using SQLite). In the desired result, within each id, each start should be on the same row as the chronologically closest end. If an id has a start but no end (like id=4), then the corresponding end, will be empty (as shown below).
I have tried this
select
id,
max( case when start_end = "start" then date end) as start,
max(case when start_end = "end" then date end ) as end
from df
group by id
But the result is this, which is wrong because id=5 only have one row, when it should have two:
id start end
1 2 1994-05-01 1996-11-04
2 4 1979-07-18 <NA>
3 5 2010-10-01 2012-10-06
Any help is much appreciated
CREATE TABLE mytable(
id INTEGER NOT NULL PRIMARY KEY
,start_end VARCHAR(5) NOT NULL
,date DATE NOT NULL
);
INSERT INTO mytable(id,start_end,date) VALUES (2,'start','1994-05-01');
INSERT INTO mytable(id,start_end,date) VALUES (2,'end','1996-11-04');
INSERT INTO mytable(id,start_end,date) VALUES (4,'start','1979-07-18');
INSERT INTO mytable(id,start_end,date) VALUES (5,'start','2005-02-01');
INSERT INTO mytable(id,start_end,date) VALUES (5,'end','2009-09-17');
INSERT INTO mytable(id,start_end,date) VALUES (5,'start','2010-10-01');
INSERT INTO mytable(id,start_end,date) VALUES (5,'end','2012-10-06');

Answer 1

select
s.id as id,
s.date as 'start',
min(e.date) as 'end' -- earliest end date from "same id&start"
from
-- only start dates
(select id, date
from intable
where start_end='start'
) as s
left join -- keep the start-only lines
-- only end dates
(select id, date
from intable
where start_end='end'
) as e
on s.id = e.id
and s.date < e.date -- not too early
group by s.id, s.date -- "same id&start"
order by s.id, s.date; -- ensure sequence
Left join (to keep the start-only line for id "4") two on-the-fly tables, start dates and end dates.
Take the minimal end date which is just higher than start date (same id, using min()and group by.
Order by id, then start date.
I tested this on a test table which is similar to your dump, but has no "NOT NULL" and no "PRIMARY KEY". I guess for this test table that is irrelevant; otherwise explain the effect, please.
Note:
Internally three pairs of dates for id 5 (those that match end>start) are found, but only those are forwarded with the lowest end (min(end)) for each of the two different combinations of ID and start group by ID, start. The line where end>start but end not being the minimum is therefor not returned. That makes two lines with start/end pairs as desired.
Output (with .headers on):
id|start|end
2|1994-05-01|1996-11-04
4|1979-07-18|
5|2005-02-01|2009-09-17
5|2010-10-01|2012-10-06
UPDATE: Incorporate helpful comments by #MatBailie.

Answer 2

Thank you! This is exactly what I needed to do, only with a few changes:
SELECT
s.value AS 'url',
"AVGDATE" AS 'fieldname',
sum(e.value)/count(*) AS 'value'
FROM
(SELECT url, value
FROM quicktag
WHERE fieldname='NAME'
) AS s
LEFT JOIN
(SELECT url, substr(value,1,4) AS value
FROM quicktag
WHERE fieldname='DATE'
) AS e
ON s.url = e.url
WHERE e.value != ""
GROUP BY s.value;
I had a table like this:
url fieldname value
---------- ---------- ----------
1000052801 NAME Thomas
1000052801 DATE 2007
1000131579 NAME Morten
1000131579 DATE 2005
1000131929 NAME Tanja
1000131929 DATE 2014
1000158449 NAME Knud
1000158449 DATE 2007
1000158450 NAME Thomas
1000158450 DATE 2003
I needed to correlate NAME and DATE in columns based on url as a key, and generate a field with average DATE grouped by multiple NAME fields.
So my result looks like this:
url fieldname value
---------- ---------- ----------
Thomas AVGDATE 2005
Morten AVGDATE 2005
Tanja AVGDATE 2014
Knud AVGDATE 2007
Unfortunately I not have enough posts to make my vote count yet.