I want to create a calculated field at the end of the columns where it will count all the Columns having values greater than 0.
Below is a sample Data Set.
Account_number DAY_0 DAY_30 DAY_60 DAY_90 DAY_120
acc_001 99 10 0 0.2 0
You can use case expressions:
select t.*,
( (case when day_0 > 0 then 1 else 0 end) +
(case when day_30 > 0 then 1 else 0 end) +
(case when day_60 > 0 then 1 else 0 end) +
(case when day_90 > 0 then 1 else 0 end) +
(case when day_120 > 0 then 1 else 0 end)
) as num_gt_zero
from t;
That said, you probably constructed this from a group by query. You might be able to put this logic directly into that query. If that is the case, ask a new question, with sample data, desired results, and an appropriate database tag.
Related
is that anyway to write similar query without using union?
select sum(decode(p.sumsend,0,1,0)) recvcnt,
sum(decode(p.sumsend,0,1,0)*p.sumserv) recvsum
from some_table p
where p.polefilter = 5
union
select sum(decode(p.sumsend,0,1,0)) recvcnt,
sum(decode(p.sumsend,0,1,0)*p.sumserv) recvsum
from some_table p
where p.polefilter != 5
If you are OK with having all 4 columns on one row, then one option is conditional aggregation:
select
sum(case when polefilter = 5 and sumsend = 0 then 1 else 0 end) recvcnt1,
sum(case when polefilter = 5 and sumsend = 0 then 1 else 0 end * sumserv) recvsum1,
sum(case when polefilter <> 5 and sumsend = 0 then 1 else 0 end) recvcnt2,
sum(case when polefilter <> 5 and sumsend = 0 then 1 else 0 end * sumserv) recvsum2
from some_table p
where polefilter is not null
On the other hand, if you want two rows in the resultset, then you can use aggregation and a case expression to define the groups:
select
case when polefilter = 5 then 1 else 0 end as polefilter_is_5
sum(case when sumsend = 0 then 1 else 0 end) recvcnt,
sum(case when sumsend = 0 then 1 else 0 end * sumserv) recvsum1
from some_table p
where p.polefilter is not null
group by case when polefilter = 5 then 1 else 0 end
Note that I changed the decode() functions to case expressions; both do the same thing, but the latest is standard SQL (and is somehow more flexible).
A query like the one below should work. Please provide sample data and expected output when asking a question next time.
SELECT SUM (CASE WHEN p.sumsend = 0 THEN 1 ELSE 0 END) recvcnt,
SUM (CASE WHEN p.sumsend = 0 THEN 1 ELSE 0 END * p.sumserv) recvsum
FROM some_table p
GROUP BY CASE p.polefilter WHEN 5 THEN 1 ELSE 0 END;
I'm querying the bin table to get the total active bins, total counted bins and calculate the percent of bins counted. Here's my query:
SELECT bin.location_id
,SUM(CASE WHEN bin.delete_flag = 'N' THEN 1 ELSE 0 END) AS total_active
,SUM(CASE WHEN bin.date_last_counted > 0 THEN 1 ELSE 0 END) AS total_counted
--,(total_counted / total_active) as pct_counted
From bin
Group by bin.location_id
Order by bin.location_id
When I try to use the code to create my pct_counted, it tells me "invalid column name" for both of the columns I'm using to calculate that value. Data looks like below.
location_id total_active total_counted
2 11502 484
6 2281 108
15 1772 253
Can anyone help?
You need to repeat the expressions (or use a subquery or CTE). I would recommend:
SELECT bin.location_id,
SUM(CASE WHEN bin.delete_flag = 'N' THEN 1 ELSE 0 END) AS total_active,
SUM(CASE WHEN bin.date_last_counted > 0 THEN 1 ELSE 0 END) AS total_counted
(SUM(CASE WHEN bin.date_last_counted > 0 THEN 1.0 ELSE 0 END) /
SUM(CASE WHEN bin.delete_flag = 'N' THEN 1 END)
) AS as pct_counted
FROM bin
GROUP BY bin.location_id
ORDER BY bin.location_id;
Note that I removed the ELSE clause for the second expression. This avoids divide-by-zero. The 1.0 also ensures decimal division even if your database does integer division.
I would format the sub-query this way:
Select
a.location_id
total_counted/total_active as pct_counted
from(select
bin.location_id
,SUM(CASE WHEN bin.delete_flag = 'N' THEN 1 ELSE 0 END) AS total_active
,SUM(CASE WHEN bin.date_last_counted > 0 THEN 1 ELSE 0 END) AS total_counted
From bin
Group by bin.location_id
Order by bin.location_id) a
I'm gonna to make a SUM function with these columns of Profile table when each column is greater than 1.
How can I do it?
bank docs personal
2 1 2
The following counts the rows where the values are greater than 1:
select sum(case when bank > 1 then 1 else 0 end) as bank,
sum(case when docs > 1 then 1 else 0 end) as docs,
sum(case when personal > 1 then 1 else 0 end) as personal
from Profile;
The following counts the number of columns within a row with values greater than 1:
select p.*,
(case when bank > 1 then 1 else 0 end +
case when docs > 1 then 1 else 0 end +
case when personal > 1 then 1 else 0 end
) as cnt
from Profile p;
These are the two most sensible interpretations of our question.
The sum of rows where each column value is greater than one:
select sum(bank + docs + personal)
from Profile
where bank > 1 and docs > 1 and personal > 1
;
with t as (
select 0 as v0, 1 as v1 from dual
union all select 3 as v0, 2 as v1 from dual
)
select sum(v0 + v1)
from t
where v0 > 1 and v1 > 1
;
| SUM(V0+V1) |
| ---------: |
| 5 |
db<>fiddle here
The sum of each individual column when the column is greater than 1: (untested)
select sum(case when isnull(bank,0) > 1 then bank else 0 end) banktotal
,sum(case when isnull(docs,0) > 1 then docs else 0 end) docstotal
,sum(case when isnull(personal,0) > 1 then personal else 0 end) personaltotal
from Profile
isnull() may or may not be needed based on your data and table design.
Hej,
I needed help with a case when statement in SQL Server.
Basically, I got three products and when the sum is equal to 2, then I want it to it be counted as 1 else 0. I wanted to know if the logic is write with this code or can it be improved?
case when sum(hase=1 OR hasd=1 OR hasf=1)=2 then 1 else 0 end as Xavc
What I was trying with this code is this: The customer might not have all three products however, if he has two products or the three the three , then it is equal to 2 and count is 1.
Something like this?
SELECT
CASE
WHEN hase + hasd + hasf = 2 THEN 1
ELSE 0
END AS Xavc
I think you are trying to do something like this...
CASE WHEN SUM(CASE WHEN hase=1 THEN 1 ELSE 0 END)
+ SUM(CASE WHEN hasd=1 THEN 1 ELSE 0 END)
+ SUM(CASE WHEN hasf=1 THEN 1 ELSE 0 END) = 2
THEN 1 ELSE 0 END AS Xavc
In this case try this ..
CASE WHEN SUM(CASE WHEN hase=1 THEN 1 ELSE 0 END) + SUM(CASE WHEN hasd=1 THEN 1 ELSE 0 END) = 2
OR SUM(CASE WHEN hasd=1 THEN 1 ELSE 0 END) + SUM(CASE WHEN hasf=1 THEN 1 ELSE 0 END) = 2
OR SUM(CASE WHEN hase=1 THEN 1 ELSE 0 END) + SUM(CASE WHEN hasf=1 THEN 1 ELSE 0 END) = 2
THEN 1 ELSE 0 END AS Xavc
How do I convert the following query into a pivot table using crosstab?
select (SUM(CASE WHEN added_customer=false
THEN 1
ELSE 0
END)) AS CUSTOMERS_NOT_ADDED, (SUM(CASE WHEN added_customer=true
THEN 1
ELSE 0
END)) AS CUSTOMERS_ADDED,
(select (SUM(CASE WHEN added_sales_order=false
THEN 1
ELSE 0
END))
FROM shipments_data
) AS SALES_ORDER_NOT_ADDED,
(select (SUM(CASE WHEN added_sales_order=true
THEN 1
ELSE 0
END))
FROM shipments_data
) AS SALES_ORDER_ADDED,
(select (SUM(CASE WHEN added_fulfillment=false
THEN 1
ELSE 0
END))
FROM shipments_data
) AS ITEM_FULFILLMENT_NOT_ADDED,
(select (SUM(CASE WHEN added_fulfillment=true
THEN 1
ELSE 0
END))
FROM shipments_data
) AS ITEM_FULFILLMENT_ADDED,
(select (SUM(CASE WHEN added_invoice=false
THEN 1
ELSE 0
END))
FROM shipments_data
) AS INVOICE_NOT_ADDED,
(select (SUM(CASE WHEN added_invoice=true
THEN 1
ELSE 0
END))
FROM shipments_data
) AS INVOICE_ADDED,
(select (SUM(CASE WHEN added_ra=false
THEN 1
ELSE 0
END))
FROM shipments_data
) AS RA_NOT_ADDED,
(select (SUM(CASE WHEN added_ra=true
THEN 1
ELSE 0
END))
FROM shipments_data
) AS RA_ADDED,
(select (SUM(CASE WHEN added_credit_memo=false
THEN 1
ELSE 0
END))
FROM shipments_data
) AS CREDIT_MEMO_NOT_ADDED,
(select (SUM(CASE WHEN added_credit_memo=true
THEN 1
ELSE 0
END))
FROM shipments_data
) AS CREDIT_MEMO_ADDED
FROM shipments_data;
This query gives me data in a standard row format however I would like to show this as a pivot table in the following format:
Added Not_Added
Customers 100 0
Sales Orders 50 50
Item Fulfillemnts 0 100
Invoices 0 100
...
I am using Heroku PostgreSQL, which is running v9.1.6
Also, I'm not sure if my above query can be optimized or if this is poor form. If it can be optimized/improved I would love to learn how.
The tablefunc module that supplies crosstab() is available for 9.1 (like for any other version this side of the millennium). Doesn't Heroku let you install additional modules? Have you tried:
CREATE EXTENSION tablefunc;
For examples how to use it, refer to the manual or this related question:
PostgreSQL Crosstab Query
OR try this search - there are a couple of good answers with examples on SO.
To get you started (like most of the way ..) use this largely simplified and re-organized query as base for the crosstab() call:
SELECT 'added'::text AS col
,SUM(CASE WHEN added_customer THEN 1 ELSE 0 END) AS customers
,SUM(CASE WHEN added_sales_order THEN 1 ELSE 0 END) AS sales_order
,SUM(CASE WHEN added_fulfillment THEN 1 ELSE 0 END) AS item_fulfillment
,SUM(CASE WHEN added_invoice THEN 1 ELSE 0 END) AS invoice
,SUM(CASE WHEN added_ra THEN 1 ELSE 0 END) AS ra
,SUM(CASE WHEN added_credit_memo THEN 1 ELSE 0 END) AS credit_memo
FROM shipments_data
UNION ALL
SELECT 'not_added' AS col
,SUM(CASE WHEN NOT added_customer THEN 1 ELSE 0 END) AS customers
,SUM(CASE WHEN NOT added_sales_order THEN 1 ELSE 0 END) AS sales_order
,SUM(CASE WHEN NOT added_fulfillment THEN 1 ELSE 0 END) AS item_fulfillment
,SUM(CASE WHEN NOT added_invoice THEN 1 ELSE 0 END) AS invoice
,SUM(CASE WHEN NOT added_ra THEN 1 ELSE 0 END) AS ra
,SUM(CASE WHEN NOT added_credit_memo THEN 1 ELSE 0 END) AS credit_memo
FROM shipments_data;
If your columns are defined NOT NULL, you can further simplify the CASE expressions.
If performance is crucial, you can get all aggregates in a single scan in a CTE and split values into two rows in the next step.
WITH x AS (
SELECT count(NULLIF(added_customer, FALSE)) AS customers
,sum(added_sales_order::int) AS sales_order
...
,count(NULLIF(added_customer, TRUE)) AS not_customers
,sum((NOT added_sales_order)::int) AS not_sales_order
...
FROM shipments_data
)
SELECT 'added'::text AS col, customers, sales_order, ... FROM x
UNION ALL
SELECT 'not_added', not_customers, not_sales_order, ... FROM x;
I also demonstrate two alternative ways to build your aggregates - both built on the assumption that all columns are boolean NOT NULL. Both alternatives are syntactically shorter, but not faster. In previous testes all three methods performed about the same.