I need to show my table data with group by - group-by

i have data like this in table
ROLL_NO SHOE_NO SHOCKS CAP SHIRT TROUSER JACKET
21 7 12 32 28 22 32
22 7 15 30 22 12 22
23 8 16 31 21 14 20
24 9 17 33 28 19 26
25 7 16 30 22 12 22
26 7 15 31 22 12 22
27 8 15 30 22 12 22
28 7 17 30 22 12 22
29 8 15 30 12 22
31 8 15 30 22 12
now i need some grouping tricks to show data like this
ITEM SIZE COUNT
SHOE 7 5
SHOE 8 4
SHOE 9 1
SHOCKS 12 1
SHOCKS 15 5
SHOCKS 16 2
SHOCKS 17 2
CAP 32 1
CAP 30 6
CAP 31 2
CAP 33 1
SHIRT 28 2
SHIRT 22 6
SHIRT 21 1
SHIRT NULL 1
TROUSER 22 1
TROUSER 12 7
TROUSER 14 1
TROUSER 19 1
JACKET 32 1
JACKET 22 6
JACKET 20 1
JACKET 26 1
JACKET NULL 1
create table script and insert satement is as follow-
create table uniform_size (
ROLL_NO NUMBER UNIQUE,
SHOE_NO NUMBER,
SHOCKS NUMBER,
CAP NUMBER,
SHIRT NUMBER,
TROUSER number,
JACKET NUMBER
);
INSERT INTO UNIFORM_SIZE VALUES ( 21,7,12,32,28,22,32);
INSERT INTO UNIFORM_SIZE VALUES ( 22,7,15,30,22,12,22);
INSERT INTO UNIFORM_SIZE VALUES ( 23,8,16,31,21,14,20);
INSERT INTO UNIFORM_SIZE VALUES ( 24,9,17,33,28,19,26);
INSERT INTO UNIFORM_SIZE VALUES ( 25,7,16,30,22,12,22);
INSERT INTO UNIFORM_SIZE VALUES ( 26,7,15,31,22,12,22);
INSERT INTO UNIFORM_SIZE VALUES ( 27,8,15,30,22,12,22);
INSERT INTO UNIFORM_SIZE VALUES ( 28,7,17,30,22,12,22);
INSERT INTO UNIFORM_SIZE VALUES ( 29,8,15,30,NULL,12,22);
INSERT INTO UNIFORM_SIZE VALUES ( 31,8,15,30,22,12,NULL);
INSERT INTO UNIFORM_SIZE VALUES ( 32,NULL,15,30,22,12,23);
INSERT INTO UNIFORM_SIZE VALUES ( 33,NULL,15,31,22,12,23);
INSERT INTO UNIFORM_SIZE VALUES ( 34,9,NULL,30,22,12,23);
INSERT INTO UNIFORM_SIZE VALUES ( 35,9,18,31,22,12,23);
INSERT INTO UNIFORM_SIZE VALUES ( 36,9,NULL,30,28,12,23);
INSERT INTO UNIFORM_SIZE VALUES ( 37,9,18,30,22,12,24);
INSERT INTO UNIFORM_SIZE VALUES ( 38,10,19,30,22,12,24);
INSERT INTO UNIFORM_SIZE VALUES ( 39,10,19,30,22,14,24);
INSERT INTO UNIFORM_SIZE VALUES ( 40,NULL,NULL,NULL,NULL,NULL,NULL);
thank you and regards
i have tried some grouping tricks but didn't got the desired result

It seems like you are trying to get unique values from each column and get the count of each value. Not sure if this is what you are looking for, but it seems helpful to me.
select 'SHOE' article, SHOE_NO size, count(SHOE_NO) cnt from uniform_size group by SHOE_NO
union all
select 'SHOCKS' article, SHOCKS size, count(SHOCKS) cnt from uniform_size group by SHOCKS
union all
select 'CAP' article, CAP size, count(CAP) cnt from uniform_size group by CAP
union all
select 'SHIRT' article, SHIRT size, count(SHIRT) cnt from uniform_size group by SHIRT
union all
select 'TROUSER' article, TROUSER size, count(TROUSER) cnt from uniform_size group by TROUSER
union all
select 'JACKET' article, JACKET size, count(JACKET) cnt from uniform_size group by JACKET;
result
SHOE||0
SHOE|7|5
SHOE|8|4
SHOE|9|5
SHOE|10|2
SHOCKS||0
SHOCKS|12|1
SHOCKS|15|7
SHOCKS|16|2
SHOCKS|17|2
SHOCKS|18|2
SHOCKS|19|2
CAP||0
CAP|30|12
CAP|31|4
CAP|32|1
CAP|33|1
SHIRT||0
SHIRT|21|1
SHIRT|22|13
SHIRT|28|3
TROUSER||0
TROUSER|12|14
TROUSER|14|2
TROUSER|19|1
TROUSER|22|1
JACKET||0
JACKET|20|1
JACKET|22|6
JACKET|23|5
JACKET|24|3
JACKET|26|1
JACKET|32|1

Related

PostgreSQL query with UNIQUE values returned based on condition

Its an example of a table from PostgreSQL.
I learning the SQL query and cant find anything to help me pass this.
What I`m working to achieve is:
Return UNIQ(DISTINCT) values of WNR WHEN tdate >='2020-01-13 00:00:01.757000'
WNR tdate T1 T2 T3
2 '2020-01-06 00:05:23.229000' 8 18 15
2 '2020-01-06 00:05:23.725000' 11 4 7
2 '2020-01-06 00:05:31.578000' 19 12 6
3 '2020-01-13 00:00:01.655000' 9 9 3
3 '2020-01-13 00:00:01.757000' 5 11 16
3 '2020-01-13 00:00:05.778000' 16 17 16
4 '2020-01-20 00:00:11.925000' 18 13 4
4 '2020-01-20 00:00:12.177000' 18 3 15
4 '2020-01-20 00:00:12.694000' 7 12 7
5 '2020-01-27 00:00:04.860000' 19 3 14
5 '2020-01-27 00:00:05.056000' 14 18 8
5 '2020-01-27 00:00:05.107000' 18 7 14
Result expected should be 3,4,5
Thank you!
To select distinct values in Postgresql you can use DISTINCT clause.
From Postgresql documentation: SELECT DISTINCT eliminates duplicate rows from the result. SELECT DISTINCT ON eliminates rows that match on all the specified expressions. SELECT ALL (the default) will return all candidate rows, including duplicates. (See DISTINCT Clause below.)
SELECT DISTINCT WNR
FROM table_name
WHERE tdate >='2020-01-13 00:00:01.757000';

How can I evaluate data over time in Postgresql?

I need to find users who have posted three times or more, three months in a row. I wrote this query:
select count(id), owneruserid, extract(month from creationdate) as postmonth from posts
group by owneruserid, postmonth
having count(id) >=3
order by owneruserid, postmonth
And I get this:
count owneruserid postmonth
36 -1 1
23 -1 2
45 -1 3
41 -1 4
18 -1 5
24 -1 6
31 -1 7
78 -1 8
83 -1 9
17 -1 10
88 -1 11
127 -1 12
3 6 11
3 7 12
4 8 1
8 8 12
4 12 4
3 12 5
3 22 2
4 22 4
(truncated)
Which is great. How can I query for users who posted three times or more, three months or more in a row? Thanks.
This is called the Islands and Gaps problem, specifically it's an Island problem with a date range. You should,
Fix this question up.
Flag it to be sent to dba.stackexchange.com
To solve this,
Create a pseudo column with a window that has 1 if the row preceding it does not correspond to the preceding mont
Create groups out of that with COUNT()
Check to make sure the count(*) for the group is greater than or equal to three.
Query,
SELECT l.id, creationdaterange, count(*)
FROM (
SELECT t.id,
t.creationdate,
count(range_reset) OVER (PARTITION BY t.id ORDER BY creationdate) AS creationdaterange
FROM (
SELECT id,
creationdate,
CASE
WHEN date_trunc('month',creationdate::date)::date - interval '1 month' = date_trunc('month',lag(creationdate))::date OVER (PARTITION BY id ORDER BY creationdate)
THEN 1
END AS range_reset
FROM post
ORDER BY id, creationdate
) AS t;
) AS l
GROUP BY t.id, creationdaterange
HAVING count(*) >= 3;

While loop to add data for pivot

Currently i have a requirement which needs a table to look like this:
Instrument Long Short 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 ....
Fixed 41 41 35 35 35 35 35 35 35 53 25 25
Index 16 16 22 22 22 32 12 12 12 12 12 12
Credits 29 29 41 16 16 16 16 16 16 16 16 16
Short term 12 12 5 5 5 5 5 5 5 5 5 17
My worktable looks like the following:
Instrument Long Short Annual Coupon Maturity Date Instrument ID
Fixed 10 10 10 01/01/2025 1
Index 5 5 10 10/05/2016 2
Credits 15 15 16 25/06/2020 3
Short term 12 12 5 31/10/2022 4
Fixed 13 13 15 31/03/2030 5
Fixed 18 18 10 31/01/2019 6
Credits 14 14 11 31/12/2013 7
Index 11 11 12 31/10/2040 8
..... etc
So basically the long and the short in the pivot should be the sum of each distinct instrument ID. And then for each year i need to take the sum of each Annual Coupon until the maturity date year where the long and the coupon rate are added together.
My thinking was that i had to create a while loop which would populate a table with a record for each year for each instrument until the maturity date, so that i could then pivot using an sql pivot some how. Does this seem feasible? Any other ideas on the best way of doing this, particularly i might need help on the while loop?
The following solution uses a numbers table to unfold ranges in your table, performs some special processing on some of the data columns in the unfolded set, and finally pivots the results:
WITH unfolded AS (
SELECT
t.Instrument,
Long = SUM(z.Long ) OVER (PARTITION BY Instrument),
Short = SUM(z.Short) OVER (PARTITION BY Instrument),
Year = y.Number,
YearValue = t.AnnualCoupon + z.Long + z.Short
FROM YourTable t
CROSS APPLY (SELECT YEAR(t.MaturityDate)) x (Year)
INNER JOIN numbers y ON y.Number BETWEEN YEAR(GETDATE()) AND x.Year
CROSS APPLY (
SELECT
Long = CASE y.Number WHEN x.Year THEN t.Long ELSE 0 END,
Short = CASE y.Number WHEN x.Year THEN t.Short ELSE 0 END
) z (Long, Short)
),
pivoted AS (
SELECT *
FROM unfolded
PIVOT (
SUM(YearValue) FOR Year IN ([2013], [2014], [2015], [2016], [2017], [2018], [2019], [2020],
[2021], [2022], [2023], [2024], [2025], [2026], [2027], [2028], [2029], [2030],
[2031], [2032], [2033], [2034], [2035], [2036], [2037], [2038], [2039], [2040])
) p
)
SELECT *
FROM pivoted
;
It returns results for a static range years. To use it for a dynamically calculated year range, you'll first need to prepare the list of years as a CSV string, something like this:
SET #columnlist = STUFF(
(
SELECT ', [' + CAST(Number) + ']'
FROM numbers
WHERE Number BETWEEN YEAR(GETDATE())
AND (SELECT YEAR(MAX(MaturityDate)) FROM YourTable)
ORDER BY Number
FOR XML PATH ('')
),
1, 2, ''
);
then put it into the dynamic SQL version of the query:
SET #sql = N'
WITH unfolded AS (
...
PIVOT (
SUM(YearValue) FOR Year IN (' + #columnlist + ')
) p
)
SELECT *
FROM pivoted;
';
and execute the result:
EXECUTE(#sql);
You can try this solution at SQL Fiddle.

Complicated AVG within date range

I've got a table with a tracking of a plant's equipment installation.
Here is a sample:
ID Name Date Percentage
1 GT-001 2011-01-08 30
2 GT-002 2011-01-11 40
3 GT-003 2011-02-02 30
4 GT-001 2011-02-03 50
5 GT-003 2011-02-15 50
6 GT-004 2011-02-15 30
7 GT-002 2011-02-15 60
8 GT-001 2011-02-20 60
9 GT-003 2011-03-01 60
10 GT-004 2011-03-05 50
11 GT-001 2011-03-10 70
12 GT-004 2011-03-15 60
And the corresponding script:
CREATE TABLE [dbo].[SampleTable](
[ID] [int] NOT NULL,
[Name] [nvarchar](50) NULL,
[Date] [date] NULL,
[Percentage] [int] NULL) ON [PRIMARY]
GO
--Populate the table with values
INSERT INTO [dbo].[SampleTable] VALUES
('1', 'GT-001', '2011-01-08', '30'),
('2', 'GT-002', '2011-01-11', '40'),
('3', 'GT-003', '2011-02-02', '30'),
('4', 'GT-001', '2011-02-03', '50'),
('5', 'GT-003', '2011-02-15', '50'),
('6', 'GT-004', '2011-02-15', '30'),
('7', 'GT-002', '2011-02-15', '60'),
('8', 'GT-001', '2011-02-20', '60'),
('9', 'GT-003', '2011-03-01', '60'),
('10', 'GT-004', '2011-03-05', '50'),
('11', 'GT-001', '2011-03-10', '70'),
('12', 'GT-004', '2011-03-15', '60');
GO
What i need is to create a chart with Date on the X and Average Percentage on the Y. Average Percentage is an average percentage of all equipment by that particular date starting from the beggining of the installation process (MIN(Fields!Date.Value, "EquipmentDataset"))
Having no luck in implementing this using SSRS only, i decided to create a more complicated dataset for it using T-SQL.
I guess that it is nessesary to add a calculated column named 'AveragePercentage' that should store an average percentage on that date, calculating only the most latest equipment percentage values in a range between the beggining of the installation process (MIN(Date)) and the current row's date. Smells like a recursion, but i'm newbie to T-SQL....))
Here is the desired output
ID Name Date Percentage Average
1 GT-001 2011-01-08 30 30
2 GT-002 2011-01-11 40 35
3 GT-003 2011-02-02 30 33
4 GT-001 2011-02-03 50 40
5 GT-003 2011-02-15 50 48
6 GT-004 2011-02-15 30 48
7 GT-002 2011-02-15 60 48
8 GT-001 2011-02-20 60 50
9 GT-003 2011-03-01 60 53
10 GT-004 2011-03-05 50 58
11 GT-001 2011-03-10 70 60
12 GT-004 2011-03-15 60 63
What do you think?
I'll be very appreciated for any help.
You could use cross apply with row_number to find the latest value for each machine. An additional subquery is required because you cannot use row_number in the where clause directly. Here's the query:
select t1.id
, t1.Name
, t1.Date
, t1.Percentage
, avg(1.0*last_per_machine.percentage)
from SampleTable t1
outer apply
(
select *
from (
select row_number() over (partition by Name order by id desc)
as rn
, *
from SampleTable t2
where t2.date <= t1.date
) as numbered
where rn = 1
) as last_per_machine
group by
t1.id
, t1.Name
, t1.Date
, t1.Percentage
Working example on SE Data.

Extract Unique Time Slices in Oracle

I use Oracle 10g and I have a table that stores a snapshot of data on a person for a given day. Every night an outside process adds new rows to the table for any person whose had any changes to their core data (stored elsewhere). This allows a query to be written using a date to find out what a person 'looked' like on some past day. A new row is added to the table even if only a single aspect of the person has changed--the implication being that many columns have duplicate values from slice to slice since not every detail changed in each snapshot.
Below is a data sample:
SliceID PersonID StartDt Detail1 Detail2 Detail3 Detail4 ...
1 101 08/20/09 Red Vanilla N 23
2 101 08/31/09 Orange Chocolate N 23
3 101 09/15/09 Yellow Chocolate Y 24
4 101 09/16/09 Green Chocolate N 24
5 102 01/10/09 Blue Lemon N 36
6 102 01/11/09 Indigo Lemon N 36
7 102 02/02/09 Violet Lemon Y 36
8 103 07/07/09 Red Orange N 12
9 104 01/31/09 Orange Orange N 12
10 104 10/20/09 Yellow Orange N 13
I need to write a query that pulls out time slices records where some pertinent bits, not the whole record, have changed. So, referring to the above, if I only want to know the slices in which Detail3 has changed from its previous value, then I would expect to only get rows having SliceID 1, 3 and 4 for PersonID 101 and SliceID 5 and 7 for PersonID 102 and SliceID 8 for PersonID 103 and SliceID 9 for PersonID 104.
I'm thinking I should be able to use some sort of Oracle Hierarchical Query (using CONNECT BY [PRIOR]) to get what I want, but I have not figured out how to write it yet. Perhaps YOU can help.
Thanks you for your time and consideration.
Here is my take on the LAG() solution, which is basically the same as that of egorius, but I show my workings ;)
SQL> select * from
2 (
3 select sliceid
4 , personid
5 , startdt
6 , detail3 as new_detail3
7 , lag(detail3) over (partition by personid
8 order by startdt) prev_detail3
9 from some_table
10 )
11 where prev_detail3 is null
12 or ( prev_detail3 != new_detail3 )
13 /
SLICEID PERSONID STARTDT N P
---------- ---------- --------- - -
1 101 20-AUG-09 N
3 101 15-SEP-09 Y N
4 101 16-SEP-09 N Y
5 102 10-JAN-09 N
7 102 02-FEB-09 Y N
8 103 07-JUL-09 N
9 104 31-JAN-09 N
7 rows selected.
SQL>
The point about this solution is that it hauls in results for 103 and 104, who don't have slice records where detail3 has changed. If that is a problem we can apply an additional filtration, to return only rows with changes:
SQL> with subq as (
2 select t.*
3 , row_number () over (partition by personid
4 order by sliceid ) rn
5 from
6 (
7 select sliceid
8 , personid
9 , startdt
10 , detail3 as new_detail3
11 , lag(detail3) over (partition by personid
12 order by startdt) prev_detail3
13 from some_table
14 ) t
15 where t.prev_detail3 is null
16 or ( t.prev_detail3 != t.new_detail3 )
17 )
18 select sliceid
19 , personid
20 , startdt
21 , new_detail3
22 , prev_detail3
23 from subq sq
24 where exists ( select null from subq x
25 where x.personid = sq.personid
26 and x.rn > 1 )
27 order by sliceid
28 /
SLICEID PERSONID STARTDT N P
---------- ---------- --------- - -
1 101 20-AUG-09 N
3 101 15-SEP-09 Y N
4 101 16-SEP-09 N Y
5 102 10-JAN-09 N
7 102 02-FEB-09 Y N
SQL>
edit
As egorius points out in the comments, the OP does want hits for all users, even if they haven't changed, so the first version of the query is the correct solution.
In addition to OMG Ponies' answer: if you need to query slices for all persons, you'll need partition by:
SELECT s.sliceid
, s.personid
FROM (SELECT t.sliceid,
t.personid,
t.detail3,
LAG(t.detail3) OVER (
PARTITION BY t.personid ORDER BY t.startdt
) prev_val
FROM t) s
WHERE (s.prev_val IS NULL OR s.prev_val != s.detail3)
I think you'll have better luck with the LAG function:
SELECT s.sliceid
FROM (SELECT t.sliceid,
t.personid,
t.detail3,
LAG(t.detail3) OVER (PARTITION BY t.personid ORDER BY t.startdt) 'prev_val'
FROM TABLE t) s
WHERE s.personid = 101
AND (s.prev_val IS NULL OR s.prev_val != s.detail3)
Subquery Factoring alternative:
WITH slices AS (
SELECT t.sliceid,
t.personid,
t.detail3,
LAG(t.detail3) OVER (PARTITION BY t.personid ORDER BY t.startdt) 'prev_val'
FROM TABLE t)
SELECT s.sliceid
FROM slices s
WHERE s.personid = 101
AND (s.prev_val IS NULL OR s.prev_val != s.detail3)