Percentage by year - sql

I have this dataset
Year score count
2007 20 grade 2000
2006 20 2385
2006 20 grade 10
2006 20 grade_N 3
2005 40 grade 428
2006 40 grade 815
2006 40 grade_1 15
2006 40 grade 3
...
Generated by
SEL years,
Score,
,count(0)
,100.0*count(0)/sum(count(*)) over () as pct
From table1
Group by 1,2
If I add a condition
Where years =2006 it gives me the right percentage
2006 20 73.8
2006 20 grade 0.0
...
But if I do not specify it, it returns lower number.
How can I determine percentage by year?

Try this.
sum(count(*)) over (partition by YEAR)

Related

sql query to find student having average of 90 from last 2 years?

I was trying this on test table
create table years (
yr bigint,
average decimal(10,2),
rollno bigint
)
i created this table year for storing 2 years like 2020 and 2021
average of marks scored in average
Condition is to find only those students whose avg is above 54 from last 2 years.
data is as follows
year average rollno
2021 55.20 1
2020 55.50 1
2020 54.50 2
2020 55.50 3
2021 55.40 3
select rollno
from years
where average > 54
and yr = (YEAR(GETDATE())-1)
and yr = (YEAR(GETDATE())-2)
i tried this query but it is not working when i want to specifically find those values where the condition is true.
if i use this query like this
select rollno
from years
where average > 54
and yr = (YEAR(GETDATE())-1) or yr = (YEAR(GETDATE())-2)
it works but doesnt give me the desired result.
result i want is as follows
year average rollno
2020 55.50 1
2021 55.20 1
2020 55.50 3
2021 55.40 3
but i am getting roll no 2 in the output
I'm checking your request after a review in you query, seems there are some parentheses missing in your expression.
Follows the example, based on your query
SELECT * FROM years WHERE
average > 55
and --below the bracket P1
(--Open P1
(--Open P2
yr = year(getdate())-1
)--Close P2
or
(--Open P3
yr = year(getdate())-2
)--Close P3
)--Close P1
What does it mean in the WHERE clause is the average > 55(mandatory) AND all what we have inside in the bracket P1 as another condition.
The result
year average rollno
2020 55.50 1
2021 55.20 1
2020 55.50 3
2021 55.40 3
Best Regards

Compare data from for specific column grouping and Update based on criteria

I have a table with the following structure:
Employee Project Task Accomplishment Score Year
John A 1 5 60 2016
John A 1 6 40 2018
John A 2 3 30 2016
Simon B 2 0 30 2017
Simon B 2 4 30 2019
David C 1 3 20 2015
David C 1 2 40 2016
David C 3 0 25 2017
David C 3 5 35 2017
I want to create a view with Oracle SQLout of the above table which looks like as follows:
Employee Project Task Accomplishment Score Year UpdateScore Comment
John A 1 5 60 2016 60
John A 1 6 40 2018 100 (=60+40)
John A 2 3 30 2016 30
Simon B 2 0 30 2017 30
Simon B 2 4 40 2019 40 (no update because Accomplishement was 0)
David C 1 3 20 2015 20
David C 1 2 40 2016 60 (=20+40)
David C 3 0 25 2017 25
David C 3 5 35 2017 35 (no update because Accomplishement was 0)
The Grouping is: Employee-Project-Task.
The Rule of the UpdateScore column:
If for a specific Employee-Project-Task group Accomplishment column value is greater than 0 for the previous year, add the previous year's score to the latest year for the same Employee-Project-Task group.
For example: John-A-1 is a group which is different from John-A-2. So as we can see for John-A-1 the Accomplishment is 5 (which is greater than 0) in 2016, so we add the Score from 2016 with the score of 2018 for the John-A-1 and the updated score becomes 100.
For Simon-B-2, the accomplishment was 0, so there will be no update for 2019 for Simon-B-2.
Note: I don't need the Comment field, it is there just for more clarification.
Use analytic functions to determine if there was a score for the previous year, and if so, add it to the UpdatedScore.
select Employee, Project, Task, Accomplishment, Score, Year,
case when lag(Year) over (partition by Employee, Project order by Year) = Year - 1
then lag(Score) over (partition by Employee, Project order by Year)
else 0
end + Score as UpdatedScore
from EmployeeScore;
This is a bit strange -- you are counting the accomplishment of 0 in one year but not the next. Okay.
Use analytic functions:
select t.*,
(case when lag(accomplishment) over (partition by Employee, Project, Task order by year) > 0
then lag(score) over (partition by Employee, Project, Task order by year)
else 0
end) + score as update_score
from t;
from t

SQL count ocurrences within time periods

I recently started up working with Access database in a project at my work (hospital) and got lots of useful tips from this site. However, I have now a problem that I can't figure out how to solve.
I have a table containing treatment dates (as well as other data) for lots of patients. My task is to count the number of treatments given within each week (and possibly month/quarter/year as well). The treatment dates are located in the column 'TreatDate' in the table 'Data'.
I have used DatePart to separate out year and week number as:
SELECT
DatePart('yyyy',[TreatStart]) AS Year, DatePart('ww',[TreatStart]) AS Week
FROM Data
ORDER BY DatePart('yyyy',[TreatStart]),DatePart('ww',[TreatStart]);
Which gives me:
Year Week
2006 16
2006 16
2006 16
2006 17
2006 17
2006 18
2006 19
2006 19
2006 19
... ...
How do I count the number of occurances in each week in order to get something like:
Year Week N
2006 16 3
2006 17 2
2006 18 1
2006 19 3
... ... ...
Best regards,
Mattias
Just add the group by on the same values by which you want count and add the count aggregate function to get the total count of the appointments at that given group.
SELECT DatePart('yyyy',[TreatStart]) AS Year, DatePart('ww',[TreatStart]) AS Week , COUNT(*) As N
FROM Data
GROUP BY DatePart('yyyy',[TreatStart]),DatePart('ww',[TreatStart])
ORDER BY DatePart('yyyy',[TreatStart]),DatePart('ww',[TreatStart]);
Use GROUP BY and COUNT:
SELECT DatePart('yyyy',[TreatStart]) AS Year,
DatePart('ww',[TreatStart]) AS Week,
COUNT(*) as N
FROM Data
GROUP BY DatePart('yyyy',[TreatStart]),DatePart('ww',[TreatStart])
ORDER BY DatePart('yyyy',[TreatStart]),DatePart('ww',[TreatStart]);
The output will be:
Year Week N
2006 16 3
2006 17 2
2006 18 1
2006 19 3

Count and where conditions leades to perfomance issues?

I am working on a million data rows table.The table look likes below
Departement year Candidate Spent Saved
Electrical 2013 A 50 50
Electrical 2013 B 25 50
Electrical 2013 C 11 50
Electrical 2013 D 25 0
Electrical 2013 Dt 86 50
Electrical 2014 AA 50 50
Electrical 2014 BB 25 0
Electrical 2014 CH 11 50
Electrical 2014 DG 25 0
Electrical 2014 DH 0 50
Computers 2013 Ax 50 50
Computers 2013 Bc 25 50
Computers 2013 Cx 11 50
Computers 2013 Dx 25 0
Computers 2013 Dx 86 50
I am looking output like below.
Departement year NoOfCandidates NoOfCandidatesWith50$save NoOfCandidatesWith0$save
Electrical 2013 5 4 1
Electrical 2014 5 3 2
Computers 2013 5 4 1
I am using #TEMP tables for every count where conditions and left outer joining at last .So it takes me more time.
Is there any way so i can perform better for above Table .
Thanks in advance.
You want to do this as a single aggregation query. There is no need for temporary tables:
select department, year, count(*) as NumCandidates,
sum(case when saved = 50 then 1 else 0 end) as NumCandidatesWith50Save
sum(case when saved = 0 then 1 else 0 end) as NumCandidatesWith00Save
from table t
group by department, year
order by 1, 2;

Get count per year of data with begin and end dates

I have a set of data that lists each employee ever employed in a certain type of department at many cities, and it lists each employee's begin and end date.
For example:
name city_id start_date end_date
-----------------------------------------
Joe Public 54 3-19-1994 9-1-2002
Suzi Que 54 10-1-1995 9-1-2005
What I want is each city's employee count for each year in a particular period. For example, if this was all the data for city 54, then I'd show this as the query results if I wanted to show city 54's employee count for the years 1990-2005:
city_id year employee_count
-----------------------------
54 1990 0
54 1991 0
54 1992 0
54 1993 0
54 1994 1
54 1995 2
54 1996 2
54 1997 2
54 1998 2
54 1999 2
54 2000 2
54 2001 2
54 2002 2
54 2003 1
54 2004 1
54 2005 1
(Note that I will have many cities, so the primary key here would be city and year unless I want to have a separate id column.)
Is there an efficient SQL query to do this? All I can think of is a series of UNIONed queries, with one query for each year I wanted to get numbers for.
My dataset has a few hundred cities and 178,000 employee records. I need to find a few decades' worth of this yearly data for each city on my dataset.
replace 54 with your parameter
select
<city_id>, c.y, count(t.city_id)
from generate_series(1990, 2005) as c(y)
left outer join Table1 as t on
c.y between extract(year from t.start_date) and extract(year from t.end_date) and
t.city_id = <city_id>
group by c.y
order by c.y
sql fiddle demo