SQL在多行中計數相同的響應

Question

我正在使用由data.world創建的SQL版本，這似乎很通用（可能是MySql的版本）
我的數據如下所示：

ID   |SSM         | Abortion   | Climate     |
1     High          Low           Medium
2     High          High          Lo 
3     Low           High          High
4     Medium        Low           Low 

我想生成一條輸出每列計數的SQL語句，希望它看起來像下面的樣子：

 Priority |  SSM    | Abortion | Climate |
 High        2           2         1
 Medium      1           0         1
 Low         1           1         2

Answer 1

在任何數據庫中工作的相對簡單的方法是使用union all ：

select 'High' as priority,
       sum(case when SSM = 'High' then 1 else 0 end) as SSM,
       sum(case when Abortion = 'High' then 1 else 0 end) as Abortion,
       sum(case when Climate = 'High' then 1 else 0 end) as climate
from t
union all
select 'Medium' as priority,
       sum(case when SSM = 'Medium' then 1 else 0 end) as SSM,
       sum(case when Abortion = 'Medium' then 1 else 0 end) as Abortion,
       sum(case when Climate = 'Medium' then 1 else 0 end) as climate
from t
union all
select 'Low' as priority,
       sum(case when SSM = 'Low' then 1 else 0 end) as SSM,
       sum(case when Abortion = 'Low' then 1 else 0 end) as Abortion,
       sum(case when Climate = 'Low' then 1 else 0 end) as climate
from t;

在大多數數據庫中，您可以將其組合為：

select p.priority,
       sum(case when t.SSM = p.priority then 1 else 0 end) as SSM,
       sum(case when t.Abortion = p.priority then 1 else 0 end) as Abortion,
       sum(case when t.Climate = p.priority then 1 else 0 end) as climate
from (select 'High' as priority, 1 as ord union all
      select 'Medium' as priority, 2 as ord union all
      select 'Low' as priority, 3 as ord
     ) p cross join
     t
group by p.priority, p.ord
order by p.ord;

Answer 2

我接受@Gordon Linoffs的答案，因為這是問題的答案。 但是草莓讓我想到我把問題概念化了。 我需要做的是將一個寬數據集轉換成一個長數據集，然后進行計數。 我是從使用PIVOT將數據從寬到高翻轉的

以我的示例為例：

SELECT t.condition, t.prioirty, count(t.priority)
FROM(
SELECT "Abortion" as condition, df.abortion
  FROM df
  WHERE df.abortion!=""
UNION ALL
SELECT "SSM" as condition, df.SSM
  FROM df
  WHERE df.SSM!=""
UNION ALL
SELECT "Climate" as condition, df.climate
  FROM df
  WHERE df.climate!="" ) as t
GROUP BY t.condition, t.priority

也許有一種更簡單的方法可以做到這一點，但是data.world不支持CROSS APPLY