My query is to fetch data for last 5 weeks.
select z.week,
sum(case when i.severity=1 then 1 else 0 end) as 1
sum(case when i.severity=2 then 1 else 0 end) as 2
sum(case when i.severity=3 then 1 else 0 end) as 3
sum(case when i.severity=4 then 1 else 0 end) as 4
from instance as i
and left outer join year as z on convert(varchar(10),z.date,101)=convert(varchar(10),i.created,101)
and left outer join year as z on convert(varchar(10),z.date,101)=convert(varchar(10),i.closed,101)
where i.group in '%Teams%'
and z.year=2013
and z.week<=6 and z.week>1
here there are few weeks in my instance table, where there will be not even an single row. so here im not getting null or zero... instead the entire row is not at all prompting.
my present output.
week | 1 | 2 | 3 | 4
---------------------
2 | 0 | 1 | 8 | 5
3 | 2 | 3 | 4 | 9
5 | 1 | 0 | 0 | 0
but i need output like the below...
week | 1 | 2 | 3 | 4
---------------------
2 | 0 | 1 | 8 | 5
3 | 2 | 3 | 4 | 9
4 | 0 | 0 | 0 | 0
5 | 1 | 0 | 0 | 0
6 | 0 | 0 | 0 | 0
How to get the desired outputi n sql
try this
select z.week,
sum(case when i.severity=1 then 1 else 0 end) as 1
sum(case when i.severity=2 then 1 else 0 end) as 2
sum(case when i.severity=3 then 1 else 0 end) as 3
sum(case when i.severity=4 then 1 else 0 end) as 4
from year as z
left outer join instance as i on
convert(varchar(10),z.date,101)=convert(varchar(10),i.created,101)
and convert(varchar(10),z.date,101)=convert(varchar(10),i.closed,101)
where (i.group is null or i.group in '%Teams%')
and z.year=2013
and z.week<=6 and z.week>1
I'm not sure how the query works where you alias year twice to z. But, assuming that's not a problem, you can change the LEFT OUTER JOIN to RIGHT OUTER JOIN. Or, if you don't like the RIGHT OUTER JOIN, rework the SELECT so that the FROM clause references the year table.
Related
Consider the following 2 tables.
TableDE
ID country key1 key2
------------------------
1 US 1 null
1 US 1 null
1 US 1 null
2 US null null
3 US 1 1
4 DE 1 1
5 DE null null
5 DE null null
TableUS
ID key1 key2
--------------
1 null null
2 null 1
4 1 1
8 null 1
2 null 1
2 null 1
9 1 null
I need a distinct overview of all IDs, combining data from both tables:
ID inTableDe country DEkey1 DEkey2 inTableUS USkey1 USKey2
-----------------------------------------------------------------
1 1 US 1 0 1 0 0
2 1 US 0 0 1 0 1
3 1 US 1 1 0 0 0
4 1 DE 1 1 1 1 1
5 1 DE 0 0 0 0 0
8 0 0 0 1 1 0 1
9 0 0 0 1 1 1 0
I hope it speaks for itself:
ID 8 and ID 9 have 0 in the first column bc they aren't in tableDE
ID 8 and ID 9 have 0 in the country column bc this field doesn't exist in tableUS
ID 3 has 0 in inTableUS bc it only exists in tableDE
the key values are copied from the original tables
an ID is not unique: it can appear many times in both tables. However: the values for key1 and key2 will always be the same for each ID within the same table.
I have been messing for hours now with this; I have this now:
select de.[ID],
de.[country],
case when (de.[ID] in (select distinct [ID] from [tableDE]) then 1 else 0 end as [inTableDE],
case when (de.[ID] in (select distinct [ID] from [tableUS]) then 1 else 0 end as [inTableUS],
de.[key1] as [DEKey1],
de.[key2] as [DEKey2],
us.[key1] as [USKey1],
us.[key2] as [USKey2],
from dbo.[tableDE] de
full outer join dbo.[tableUS] us on de.[ID] = us.[ID]
where de.[country] = 'US'
and (de.[key1] = 1 or de.[key2] = 1 or us.[key1] = 1 or us.[key2] = 1)
group by de.[ID], us.[ID]
But this keeps giving me only values that are in both tables.
What am I doing wrong?
You sem to want aggregation on top of the full join:
select
coalesce(de.id, us.id) as id,
case when de.id is null then 0 else 1 end as intablede,
max(de.country) as country,
coalesce(max(de.key1), 0) as dekey1,
coalesce(max(de.key2), 0) as dekey2,
case when us.id is null then 0 else 1 end as intableus,
coalesce(max(us.key1), 0) as uskey1,
coalesce(max(us.key2), 0) as uskey2
from dbo.tablede de
full join dbo.tableus us on de.id = us.id
group by de.id, us.id
order by id
Demo on DB Fiddle:
id | intablede | country | dekey1 | dekey2 | intableus | uskey1 | uskey2
-: | --------: | :------ | -----: | -----: | --------: | -----: | -----:
1 | 1 | US | 1 | 0 | 1 | 0 | 0
2 | 1 | US | 0 | 0 | 1 | 0 | 1
3 | 1 | US | 1 | 1 | 0 | 0 | 0
4 | 1 | DE | 1 | 1 | 1 | 1 | 1
5 | 1 | DE | 0 | 0 | 0 | 0 | 0
8 | 0 | null | 0 | 0 | 1 | 0 | 1
9 | 0 | null | 0 | 0 | 1 | 1 | 0
Edit. This is a follow up from another question. To simplify the question. Assume a table
date | id | type
01/01 | 1 | F
02/01 | 1 | F
02/01 | 1 | F
03/01 | 1 | S
03/01 | 1 | S
04/01 | 1 | F
04/01 | 1 | S
05/01 | 1 | S
I am looking for a way to summarise the above table by combination of transaction types per day. If a person (id) has only one transaction per day it counts as a Single type. If they have more than one it counts as a Multiple one. I've done that with my original query and it works. The output from the above table would be:
date | Single | Multiple
01/01 | 1 | 0
02/01 | 0 | 1
03/01 | 0 | 1
04/01 | 0 | 1
05/01 | 1 | 0
I got that far and it works. What's I'm struggling with (ie. don't have a clue of how to start) is how set up a query to show all possible combinations of Type (SS, FF, FS) instead of just counting the multiple transactions. The desired output would be like:
date | Single | # FF | # FS | # SS
01/01 | 1 | 0 | 0 | 0
02/01 | 0 | 1 | 0 | 0
03/01 | 0 | 0 | 0 | 1
04/01 | 0 | 0 | 1 | 0
05/01 | 1 | 0 | 0 | 0
Any constructive hints or ideas will be much appreciated.
this is assuming that you have max 2 types per date.
You can use the CASE WHEN statement with MIN() and MAX() to check for combination of FF, FS or SS
select [date],
case when count(*) = 1 then 1 else 0 end as Single,
case when count(*) >= 2
and min([type]) = 'F'
and max([type]) = 'F'
then 1
else 0
end as [# FF],
case when count(*) >= 2
and min([type]) = 'F'
and max([type]) = 'S'
then 1
else 0
end as [# FS],
case when count(*) >= 2
and min([type]) = 'S'
and max([type]) = 'S'
then 1
else 0
end as [# SS]
from yourtable
group by [date]
EDIT :
for more then 3 types, just change the count(*) = 2 to count(*) >= 2 as long as the type are either F or S
I have a table which gives information about when a particular user has used an offer. It has 3 columns
Date: Date at which the offer was used
user_id: Identifier for a particular user
txn_id: Transaction id when a user uses an offer. It is always unique in the table.
The offer is such that a particular user can use it for 5 times.
I want to know at each date the number of users are in which stage of offer usage.
For example
On Day 1 there could be 3 users who have used offer once(redemption_1), 2 users who could have used offer twice (redemption_2).
Now on Day 2 there could be users from day 1(repeat users) as well as users who are coming for offer usage for the first time(new users).
For the new users of day 2 the logic is same as that of day 1 users.(May be 2 new users use the offer for 1 time(redemption_1), 3 new users use it for 3 times(redemption_3))
But for the repeat users now I want to add up to there previous day's usage.
For example
On Day 1, 3 users had used offer once(redemption_1) but on day 2 if they use it one more time then they should be counted in redemption_2.(And not in redemption_1 since they are using it for second time since the offer has started/or there last usage)
In this way I want to go on adding cumulatively the number of time a user has used a offer and the count the number of users who have used offer for 1 time(redemption_1), 2 time(redemption_2) and so on for each date
Table
+------------+---------+------------+
| Date | user_id | txn_id |
+------------+---------+------------+
| 2019-06-04 | 1 | 1ACSA0-ABA |
| 2019-06-04 | 2 | 1BEAA0-CSC |
| 2019-06-04 | 3 | 1AGHF0-CBA |
| 2019-06-04 | 1 | 1AVFA0-GAA |
| 2019-06-05 | 1 | 1BCFA0-AAA |
| 2019-06-05 | 1 | 1AVFB0-GAC |
| 2019-06-05 | 2 | 1AVFA0-GVA |
| 2019-06-05 | 4 | 1AVFA0-GVB |
| 2019-06-05 | 5 | 1AVFA0-BCF |
| 2019-06-06 | 6 | 1AGHF0-CCA |
| 2019-06-06 | 1 | 1BXHF0-CCA |
| 2019-06-06 | 2 | 1AGHF0-CBG |
| 2019-06-06 | 3 | 1AGHF0-CAW |
| 2019-06-06 | 2 | 1AGHF0-CTU |
+------------+---------+------------+
Desired Output
+------------+--------------+--------------+--------------+--------------+--------------+
| Date | redemption_1 | redemption_2 | redemption_3 | redemption_4 | redemption_5 |
+------------+--------------+--------------+--------------+--------------+--------------+
| 2019-06-04 | 2 | 1 | 0 | 0 | 0 |
| 2019-06-05 | 2 | 1 | 0 | 1 | 0 |
| 2019-06-06 | 1 | 1 | 0 | 1 | 1 |
+------------+--------------+--------------+--------------+--------------+--------------+
I will walk you through the rows of output for better understanding
In row one with date 2019-06-04 there are two users who used offer once (2,3) and one user who used offer twice(1)
In row with date 2019-06-05 there are 2 user who used offer once(4,5). Note that they have never used offer before that so they counted for redemption_1.
In the same row there is 1 user who has used offer 2 times (2: Once on 2019-06-04 and then on 2019-06-05) so he is counted for redemption_2
In the same row there is 1 user who has used offer 4 times (1: Twice on 2019-06-04 and then again twice on 2019-06-05) so he is counted for redemption_4
And so on for row with date 2019-06-06
Please let me know for any kind of clarification
Not a paragon of efficiency, but it works.
Test data:
Create Table offer_used(date DateTime, user_id Int, txn_id Varchar(50))
Insert Into dbo.offer_used (date,
user_id,
txn_id)
Values
('2019-06-04', 1, '1ACSA0-ABA'),
('2019-06-04', 2, '1BEAA0-CSC'),
('2019-06-04', 3, '1AGHF0-CBA'),
('2019-06-04', 1, '1AVFA0-GAA'),
('2019-06-05', 1, '1BCFA0-AAA'),
('2019-06-05', 1, '1AVFB0-GAC'),
('2019-06-05', 2, '1AVFA0-GVA'),
('2019-06-05', 4, '1AVFA0-GVB'),
('2019-06-05', 5, '1AVFA0-BCF'),
('2019-06-06', 6, '1AGHF0-CCA'),
('2019-06-06', 1, '1BXHF0-CCA'),
('2019-06-06', 2, '1AGHF0-CBG'),
('2019-06-06', 3, '1AGHF0-CAW'),
('2019-06-06', 2, '1AGHF0-CTU')
Query:
; With
Dates As (Select Distinct date From dbo.offer_used OU),
Users As (Select user_id, FirstTime = Min(date) From dbo.offer_used OU Group By user_id),
UserCounts As (Select
Dates.date,
Users.user_id,
Users.FirstTime,
UsedCount = (Select Count(*) From dbo.offer_used As Used
Where Used.date <= Dates.date
And Used.user_id = Users.user_id)
From
Dates
Cross Join Users)
Select
date = UserCounts.date,
[first time today] = Sum(Case When UserCounts.date = UserCounts.FirstTime
And UserCounts.UsedCount = 1 Then 1 Else 0 End),
[2 times total] = Sum(Case When UserCounts.UsedCount = 2 Then 1 Else 0 End),
[3 times total] = Sum(Case When UserCounts.UsedCount = 3 Then 1 Else 0 End),
[4 times total] = Sum(Case When UserCounts.UsedCount = 4 Then 1 Else 0 End),
[5 times total] = Sum(Case When UserCounts.UsedCount = 5 Then 1 Else 0 End),
[bonus: never] = Sum(Case When UserCounts.UsedCount = 0 Then 1 Else 0 End)
From UserCounts
Group By UserCounts.date
Order By UserCounts.date
Results:
date first time today 2 times total 3 times total 4 times total 5 times total bonus: never
----------- ---------------- ------------- ------------- ------------- ------------- ------------
2019-06-04 2 1 0 0 0 3
2019-06-05 2 1 0 1 0 1
2019-06-06 1 1 0 1 1 0
I think you want conditional aggregation:
select t.date,
sum(case when seqnum = 1 then 1 else 0 end) as redemption_1,
sum(case when seqnum = 2 then 1 else 0 end) as redemption_2,
sum(case when seqnum = 3 then 1 else 0 end) as redemption_3,
sum(case when seqnum = 4 then 1 else 0 end) as redemption_4,
sum(case when seqnum = 5 then 1 else 0 end) as redemption_5
from (select t.*, row_number() over (partition by user_id order by date) as seqnum
from table t
) t
group by t.date
order by t.date
I wish SQL for SUM each column(IPO and UOR) in TOTAL in second last. And GRAND TOTAL(Sum IPO + UOR) in the last one. Thank you so much
No Code IPO UOR
----------------------
1 D173 1 0
2 D176 3 0
3 D184 1 1
4 D185B 1 0
5 D187 1 2
6 F042 3 0
7 ML004 12 3
8 TTPMC 2 0
9 Z00204 1 0
------------------
TOTAL (NOS) 25 6
-------------------------
GRAND TOTAL (NOS) 31
Here is my code, :
SELECT
SUM(CASE WHEN IPOType = 'IPO' THEN 1 ELSE 0 END) as IPO,
SUM(CASE WHEN IPOType = 'UOR' THEN 1 ELSE 0 END) as UOR
FROM IPO2018
GROUP BY OriProjNo
it can show like this
No Code IPO UOR
----------------------
1 D173 1 0
2 D176 3 0
3 D184 1 1
4 D185B 1 0
5 D187 1 2
6 F042 3 0
7 ML004 12 3
8 TTPMC 2 0
9 Z00204 1 0
------------------
Generally speaking, you want to leave totals and sub-totals to whatever tool you are presenting your data in, as they will be able to handle the formatting with significantly more ease. In addition, your desired output does not have the same number of columns (Grand Total row only has one numeric) so even if you did shoehorn this in to the same dataset, the column headings wouldn't make sense.
That said, you can return group totals via the with rollup statement. This will provide an additional row with the aggregate totals for the group. Where there is more than one group in your data, you will get a sub-total row for each group and a total row for the entire dataset:
declare #t table(c nvarchar(10),t nvarchar(3));
insert into #t values ('D173','IPO'),('D176','IPO'),('D176','IPO'),('D176','IPO'),('D184','IPO'),('D184','UOR'),('D185B','IPO'),('D187','IPO'),('D187','UOR'),('D187','UOR'),('F042','IPO'),('F042','IPO'),('F042','IPO'),('TTPMC','IPO'),('TTPMC','IPO'),('Z00204','IPO'),('ML004','UOR'),('ML004','UOR'),('ML004','UOR'),('ML004','IPO'),('ML004','IPO'),('ML004','IPO'),('ML004','IPO'),('ML004','IPO'),('ML004','IPO'),('ML004','IPO'),('ML004','IPO'),('ML004','IPO'),('ML004','IPO'),('ML004','IPO'),('ML004','IPO');
select row_number() over (order by grouping(c),c) as n
,case when grouping(c) = 1 then 'TOTAL (NOS)' else c end as c
,sum(case when t = 'IPO' then 1 else 0 end) as IPO
,sum(case when t = 'UOR' then 1 else 0 end) as UOR
from #t
group by c
with rollup
order by grouping(c)
,c;
Output:
+----+-------------+-----+-----+
| n | c | IPO | UOR |
+----+-------------+-----+-----+
| 1 | D173 | 1 | 0 |
| 2 | D176 | 3 | 0 |
| 3 | D184 | 1 | 1 |
| 4 | D185B | 1 | 0 |
| 5 | D187 | 1 | 2 |
| 6 | F042 | 3 | 0 |
| 7 | ML004 | 12 | 3 |
| 8 | TTPMC | 2 | 0 |
| 9 | Z00204 | 1 | 0 |
| 10 | TOTAL (NOS) | 25 | 6 |
+----+-------------+-----+-----+
I am trying (and failing) to craft a simple SQL query (for SQL Server 2012) that counts the number of occurrences of a value for a given date range.
This is a collection of results from a survey.
So the end result would show there are only 3 lots of values matching '2' and
6 values matching '1'.
Even better if the final result could return 3 values:
MatchZero = 62
MatchOne = 6
MatchTwo = 3
Something Like (I know this is horribly out):
SELECT
COUNT(0) AS MatchZero,
COUNT(1) AS MatchOne,
COUNT(2) As MatchTwo
WHERE dated BETWEEN '2014-01-01' AND '2014-02-01'
I don't need it grouped by date or anything, simply a total value for each.
Any insights would be greatly received.
+------------+----------+--------------+-------------+------+-----------+------------+
| QuestionId | friendly | professional | comfortable | rate | recommend | dated |
+------------+----------+--------------+-------------+------+-----------+------------+
| 3 | 0 | 0 | 0 | 0 | 0 | 2014-02-12 |
| 9 | 0 | 0 | 0 | 0 | 0 | 2014-02-12 |
| 14 | 0 | 0 | 0 | 2 | 0 | 2014-02-13 |
| 15 | 0 | 0 | 0 | 0 | 0 | 2014-01-06 |
| 19 | 0 | 1 | 2 | 0 | 0 | 2014-01-01 |
| 20 | 0 | 0 | 0 | 0 | 0 | 2013-12-01 |
| 21 | 0 | 1 | 0 | 0 | 0 | 2014-01-01 |
| 22 | 0 | 1 | 0 | 0 | 0 | 2014-01-01 |
| 23 | 0 | 0 | 0 | 0 | 0 | 2014-01-24 |
| 27 | 0 | 0 | 0 | 0 | 0 | 2014-01-31 |
| 30 | 0 | 1 | 2 | 0 | 0 | 2014-01-27 |
| 31 | 0 | 0 | 0 | 0 | 0 | 2014-01-11 |
| 36 | 0 | 0 | 0 | 1 | 1 | 2014-01-22 |
+------------+----------+--------------+-------------+------+-----------+------------+
You can use conditional aggregation:
SELECT SUM((CASE WHEN friendly = 0 THEN 1 ELSE 0 END) +
(CASE WHEN professional = 0 THEN 1 ELSE 0 END) +
(CASE WHEN comfortable = 0 THEN 1 ELSE 0 END) +
(CASE WHEN rate = 0 THEN 1 ELSE 0 END) +
(CASE WHEN recommend = 0 THEN 1 ELSE 0 END) +
) AS MatchZero,
SUM((CASE WHEN friendly = 1 THEN 1 ELSE 0 END) +
(CASE WHEN professional = 1 THEN 1 ELSE 0 END) +
(CASE WHEN comfortable = 1 THEN 1 ELSE 0 END) +
(CASE WHEN rate = 1 THEN 1 ELSE 0 END) +
(CASE WHEN recommend = 1 THEN 1 ELSE 0 END) +
) AS MatchOne,
SUM((CASE WHEN friendly = 2 THEN 1 ELSE 0 END) +
(CASE WHEN professional = 2 THEN 1 ELSE 0 END) +
(CASE WHEN comfortable = 2 THEN 1 ELSE 0 END) +
(CASE WHEN rate = 2 THEN 1 ELSE 0 END) +
(CASE WHEN recommend = 2 THEN 1 ELSE 0 END) +
) AS MatchTwo
FROM . . .
WHERE dated BETWEEN '2014-01-01' AND '2014-02-01';
If I understand you correctly, you want to count the zeros, ones and twos for a particular (or each) column in your table. If this is correct, then you could do something like this:
select sum(case when your_column = 0 then 1 else 0 end) as zeros
, sum(case when your_column = 1 then 1 else 0 end) as ones
--- and so on
from your_table
-- where conditions go here
If you want to count the total for more than one column, enclose the needed case...ends in the sum():
sum(
(case when column1 = 0 then 1 else 0 end) +
(case when column2 = 0 then 1 else 0 end)
-- and so on
) as zeros
Going with a simple unpivot you can get the desired result with less coding.
By simply changing the date range the correct count of each question type is counted.
SELECT
RANKING, COUNT(*) AS CNT
FROM
(SELECT
friendly,professional,comfortable,rate,recommend
FROM
your_table
WHERE
dated >= '1/1/1900' AND dated <= '1/1/2015'
) AS U UNPIVOT
(RANKING FOR QUESTION IN (friendly,professional,comfortable,rate,recommend)) AS UNP
GROUP BY
RANKING