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Re: Counting different strings (OK%, FB%) in same table, grouped by week number

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Thank you David -

On Wed, Feb 22, 2012 at 9:56 PM, David Johnston <polobo@xxxxxxxxx> wrote:
> SELECT SUM(CASE WHEN id ~ '^FB' THEN 1 ELSE 0 END) AS fb_cnt, repeat for each known type (and I generally code one for unknown as well).
>
> Depending of your use case building out the non-column version and pushing it into a PivotTable would work.  There is also a crosstab module that you can use as well - though I have not used it myself.
>

this works well, but I'm curious
how'd you count unknown users here?

pref=> SELECT yw,
SUM(CASE WHEN id ~ '^OK' THEN 1 ELSE 0 END) AS "Odnoklassniki",
SUM(CASE WHEN id ~ '^MR' THEN 1 ELSE 0 END) AS "Mail.ru",
SUM(CASE WHEN id ~ '^VK' THEN 1 ELSE 0 END) AS "Vkontakte",
SUM(CASE WHEN id ~ '^FB' THEN 1 ELSE 0 END) AS "Facebook",
SUM(CASE WHEN id ~ '^GG' THEN 1 ELSE 0 END) AS "Google",
SUM(CASE WHEN id ~ '^DE' THEN 1 ELSE 0 END) AS "Preferans.de",
count(*) AS "Total"
from pref_money group by yw order by yw desc;

   yw    | Odnoklassniki | Mail.ru | Vkontakte | Facebook | Google |
Preferans.de | Total
---------+---------------+---------+-----------+----------+--------+--------------+-------
 2012-08 |          2260 |     245 |       185 |       32 |      0 |
       314 |  3036
 2012-07 |          3074 |     338 |       267 |       32 |      0 |
       386 |  4097
 2012-06 |          3044 |     328 |       288 |       37 |      0 |
       393 |  4090
 2012-05 |          3092 |     347 |       268 |       46 |      2 |
       400 |  4155
 2012-04 |          3091 |     334 |       249 |       41 |      0 |
       402 |  4117

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