I have a table with similar data to the following:
Agent | TCV | Parent AccountID | AccountID | Month
------+-----+------------------+-----------+--------
John | 100 | ABC12345 | Sept13445 | 2
John | 200 | ABC12345 | Sept345 | 2
John | 150 | CDE12345 | Sept546 | 2
John | 200 | FTE1456 | Oct3467 | 2
John | 100 | ABC12345 | Sept13445 | 3
John | 200 | ABC12345 | Sept345 | 3
John | 150 | CDE12345 | Sept546 | 3
John | 200 | FTE1456 | Oct3467 | 3
What I need is a way to show a grouped ranking by agent, then parent accounrDID each month for each agent. The idea being that in the export, there'd be a column for agent, TCV, parentaccountDID, and month.
So if all agents had 10 parentaccountDIDs (but potentially multiple accountDIDs under each), it would rank them by the grouped TCV of the parentAccountDID. So there'd be 10 lines of data for John's 10 parentaccountDIDs based off of grouped TCV in month 2, then 10 lines of data for the 10 parentaccountDIDs based off of grouped TCV in month 3, etc. etc.
SELECT agent, tcv, parent_accnt_id, accnt_id, curr_month
, ROW_NUMBER() OVER (PARTITION BY curr_month, parent_accnt_id ORDER BY curr_month) rnk
FROM your_table
/
With your data this is what you get:
AGENT TCV PARENT_ACCNT_ID ACCNT_ID CURR_MONTH RNK
------------------------------------------------------------------
John 100 ABC12345 Sept13445 2 1
John 200 ABC12345 Sept345 2 2
John 150 CDE12345 Sept546 2 1
John 200 FTE1456 Oct3467 2 1
John 100 ABC12345 Sept13445 3 1
John 200 ABC12345 Sept345 3 2
John 150 CDE12345 Sept546 3 1
John 200 FTE1456 Oct3467 3 1
In case you have Oracle SQL Database
Try the below query it might help you as needed:
select Agent ,TCV ,ParentAccountID,Month,count(1) from table group by Agent ,TCV ,ParentAccountID,Month
order by 5 desc
Also you could check(google) "Dense Rank Over" function something as below:
select Agent ,TCV ,ParentAccountID,Month,dense rank over(Agent ,TCV ,ParentAccountID,Month) from table group by Agent ,TCV ,ParentAccountID,Month
it ranks the values and the sorts the result.
Related
I want to group the rows on the basis of a specific condition.
The table structure is something like this
EmpID | EmpName | TaskId | A_Shift_Status | B_Shift_Status | C_Shift_Status | D_Shift_Status
1 | John | 1 | 1 | null | 2 | 1
1 | John | 2 | 1 | null | 1 | 1
2 | Mike | 3 | 1 | 1 | 2 | 1
2 | Mike | 4 | null | 1 | null | 1
3 | Steve | 5 | null | 1 | 2 | 1
3 | Steve | 6 | 1 | null | 2 | 1
The criteria will be
Done 1
Pending 2
NA 3
The expected output is to group the employees by task and the status will be on the following condition
if ALL tasks are done by any employee then the status will be done
(i.e. 1)
if ANY of the tasks is incomplete then the status will be
incomplete/pending (i.e. 2)
So the desired output will be
EmpID | EmpName | A_Shift_Status | B_Shift_Status | C_Shift_Status | D_Shift_Status
1 | John | 1 | null | 2 | 1
2 | Mike | 1 | 1 | 2 | 1
3 | Steve | 1 | 1 | 2 | 1
So in other terms summary/grouping should only show complete/done (i.e. 1) when all the rows of a particular shift column of an employee have status as complete/done (i.e. 1)
Based on your data (where the criteria are 1, 2 and NULL for n/a), a simple 'group by' the employee, and MAX of the columns, should work e.g.,
SELECT
yt.EmpID,
yt.EmpName,
MAX(yt.A_Shift_Status) AS A_Shift_Status,
MAX(yt.B_Shift_Status) AS B_Shift_Status,
MAX(yt.C_Shift_Status) AS C_Shift_Status,
MAX(yt.D_Shift_Status) AS D_Shift_Status
FROM
yourtable yt
GROUP BY
yt.EmpID,
yt.EmpName;
For the shift statuses
If any of them are 2, it returns 2
otherwise if any of them are 1, it returns 1
otherwise it returns NULL
Notes re 1/2/3 (which was specified as criteria) vs 1/2/NULL (which is in the data)
It gets a little tricker if the inputs are supposed to use 1/2/3 instead of 1/2/NULL. Let us know if you are changing the inputs to reflect that.
If the input is fine as NULLs, but you need the output to have '3' for n/a (nulls), you can put an ISNULL or COALESCE around the MAX statements e.g., ISNULL(MAX(yt.A_Shift_Status), 3) AS A_Shift_Status
I am trying to learn sql.I do some practices.I created a table which called Student.
Id | Name | Amount
1 | Jone | 100
2 | Jack | 200
3 | Emily | 300
4 |Haaland | 500
7 |Ted | 700
I also created Orders table like that:
Id | Name | Amount | Dıscount
1 | Jone | 100 | 10
2 | Jack | 112 | 20
3 | Emily | 300 | 30
4 |Haaland | 500 | 50
5 |Jack | 88 | 12
7 |Ted | 150 | 235
My query is:
select a1.Id Id ,a1.Name Name, a1.Amount Amount , sum(a2.discount)
from student a1
left outer join orders a2
on a1.Id=a2.Id
and a1.Name=a2.Name
and a1.Amount = a2.Amount
group by a1.Id, a1.Name, a1.Amount
Result:
Id | Name | Amount | Dıscount
1 | Jone | 100 | 10
3 | Emily | 300 | 30
4 |Haaland | 500 | 50
2 | Jack | 200 | null
7 | Ted | 700 | null
I get null value for the jack row.I have to use a1.Amount=a2.Amount because I remove amount constraint Ted'discount also appears.
Expected Result :
Id | Name | Amount | Dıscount
1 | Jone | 100 | 10
3 | Emily | 300 | 30
4 |Haaland | 500 | 50
2 | Jack | 200 | 32
7 | Ted |700 | null
I think the logic you want is to pre-aggregate the orders of each name in a subquery, then join by name and amount:
select s.id , s.name, s.amount, o.discount
from student s
left join (
select name, sum(amount) amount, sum(discount) discount
from orders
group by name
) o on o.name = s.name and o.amount = s.amount
What is the confusion? In one row you have:
id name amount
2 Jack 200
And in the other:
id name amount
2 Jack 112
Your join requires equality on all three columns. The amounts don't match, so there is no match for Jack's row and the amount is null.
Your question is not clear on what you actually want to do, so I'll stop here.
The amount for Jack does not match (200 in Student, 88 and 112 in Orders), so nothing can be joined ON a1.Amount = a2.Amount for that record. However, Please be advised that even if one of the values in Amount does match, the GROUP BY function will still not know which Amount you want associated with 'Jack'.
This post is enhanced version of my previous post here.
Please Note: This is not duplicate post or thread.
I have 3 tables:
1. REQUIRED_AUDITS (Independent table)
2. SCORE_ENTRY (SCORE_ENTRY is One to Many relationship with ERROR table)
3. ERROR
Below are the dummy data and table structure:
REQUIRED_AUDITS TABLE
+-------+------+----------+---------------+-----------------+------------+----------------+---------+
| ID | VP | Director | Manager | Employee | Req_audits | Audit_eligible | Quarter |
+-------+------+----------+---------------+-----------------+------------+----------------+---------+
| 10001 | John | King | susan#com.com | jake#com.com | 2 | Y | FY18Q1 |
| 10002 | John | King | susan#com.com | beth#com.com | 4 | Y | FY18Q1 |
| 10003 | John | Maria | tony#com.com | david#com.com | 6 | N | FY18Q1 |
| 10004 | John | Maria | adam#com.com | william#com.com | 3 | Y | FY18Q1 |
| 10005 | John | Smith | alex#com.com | rose#com.com | 6 | Y | FY18Q1 |
+-------+------+----------+---------------+-----------------+------------+----------------+---------+
SCORE_ENTRY TABLE
+----------------+------+----------+---------------+-----------------+-------+---------+
| SCORE_ENTRY_ID | VP | Director | Manager | Employee | Score | Quarter |
+----------------+------+----------+---------------+-----------------+-------+---------+
| 1 | John | King | susan#com.com | jake#com.com | 100 | FY18Q1 |
| 2 | John | King | susan#com.com | jake#com.com | 90 | FY18Q1 |
| 3 | John | King | susan#com.com | beth#com.com | 98.45 | FY18Q1 |
| 4 | John | King | susan#com.com | beth#com.com | 95 | FY18Q1 |
| 5 | John | King | susan#com.com | beth#com.com | 100 | FY18Q1 |
| 6 | John | King | susan#com.com | beth#com.com | 100 | FY18Q1 |
| 7 | John | Maria | adam#com.com | william#com.com | 99 | FY18Q1 |
| 8 | John | Maria | adam#com.com | william#com.com | 98.1 | FY18Q1 |
| 9 | John | Smith | alex#com.com | rose#com.com | 96 | FY18Q1 |
| 10 | John | Smith | alex#com.com | rose#com.com | 100 | FY18Q1 |
+----------------+------+----------+---------------+-----------------+-------+---------+
ERROR TABLE
+----------+-----------------------------+----------------+
| ERROR_ID | ERROR | SCORE_ENTRY_ID |
+----------+-----------------------------+----------------+
| 10 | Words Missing | 2 |
| 11 | Incorrect document attached | 2 |
| 12 | No results | 3 |
| 13 | Value incorrect | 4 |
| 14 | Words Missing | 4 |
| 15 | No files attached | 4 |
| 16 | Document read error | 7 |
| 17 | Garbage text | 8 |
| 18 | No results | 8 |
| 19 | Value incorrect | 9 |
| 20 | No files attached | 9 |
+----------+-----------------------------+----------------+
I have query that give below output:
+----------+---------------+------------------+------------------+------------------+
| | | Director Summary | | |
+----------+---------------+------------------+------------------+------------------+
| Director | Manager | Audits Required | Audits Performed | Percent Complete |
| King | susan#com.com | 6 | 6 | 100% |
| Maria | adam#com.com | 3 | 2 | 67% |
| Smith | alex#com.com | 6 | 2 | 33% |
+----------+---------------+------------------+------------------+------------------+
Now I would like to add column where I want the number of scores that have an error associated with them divided by total count of scores:
It's not total count of errors divided by count of scores. Instead its count of each occurrence of error and divide by count of score. Please find below example:
Considering
Director:King
Manager:susan#com.com
From SCORE_ENTRY TABLE and ERROR table,
King has 6 entries in SCORE_ENTRY TABLE
6 entries in ERROR TABLE
Instead of 6 entries in ERROR TABLE, I would like to have occurrence of error ie., 3 errors.
Formula to calculate Quality:
Quality = 1 - (sum of error occurrence / total score)*100
For King:
Quality = 1 - (3/6)*100
Quality = 50
Please Note: It's not 1 - (6/6)*100
For Maria:
Quality = 1 - (2/2)*100
Quality = 0
Below is the new output I need with new column called Quality:
+----------+---------------+---------+------------------+------------------+------------------+
| | | | Director Summary | | |
+----------+---------------+---------+------------------+------------------+------------------+
| Director | Manager | Quality | Audits Required | Audits Performed | Percent Complete |
| King | susan#com.com | 50% | 6 | 6 | 100% |
| Maria | adam#com.com | 0% | 3 | 2 | 67% |
| Smith | alex#com.com | 50% | 6 | 2 | 33% |
+----------+---------------+---------+------------------+------------------+------------------+
Below is the query am having (Thanks to #Kaushik Nayak, #APC and others) and need to add new column to this query:
WITH aud(manager_email, director, quarter, total_audits_required)
AS (SELECT manager_email,
director,
quarter,
SUM (CASE
WHEN audit_eligible = 'Y' THEN required_audits
END)
FROM required_audits
GROUP BY manager_email,
director,
quarter), --Total_audits
scores(manager_email, director, quarter, audits_completed)
AS (SELECT manager_email,
director,
quarter,
Count (score)
FROM oq_score_entry s
GROUP BY manager_email,
director,
quarter) --Audits_Performed
SELECT a.director,
a.manager_email manager,
a.total_audits_required,
s.audits_completed,
Round(( ( s.audits_completed ) / ( a.total_audits_required ) * 100 ), 2)
percentage_complete,
a.quarter
FROM aud a
left outer join scores s
ON a.manager_email = s.manager_email
WHERE ( :P4_MANAGER_EMAIL = a.manager_email
OR :P4_MANAGER_EMAIL IS NULL )
AND ( :P4_DIRECTOR = a.director
OR :P4_DIRECTOR IS NULL )
AND ( :P4_QUARTER = a.quarter
OR :P4_QUARTER IS NULL )
ORDER BY a.total_audits_required DESC nulls last
Please let me know if its confusing or need more details. Am open for any suggestions and feedback.
Appreciate any help.
Thanks,
Richa
Update:
Well my first guess has been wrong, and I hope now I'm getting it right.
According to your and shawnt00's comments, you need to compute the count of score entries that have corresponding entries in ERROR table, and use it in quality calculation.
This count you get with the expression:
COUNT ((select max(1) from "ERROR" o where o.score_entry_id=s.score_entry_id)) AS error_occurences
max(1) returns 1 when there is an entry in "ERROR" and NULL otherwise. COUNT skips nulls.
I hope this is clear.
Quality is computed as
(1 - error_occurences/audits_completed)*100%
Below is the full script, where manager_email renamed to manager and oq_score_entry renamed to score_entry.
This is in accordance with your scheme. Also I removed unnecessary WITH column mapping, it just complicates things in this case.
WITH aud AS (SELECT manager, director, quarter, SUM (CASE
WHEN audit_eligible = 'Y' THEN req_audits
END) total_audits_required
FROM required_audits
GROUP BY manager, director, quarter), --Total_audits
scores AS (
SELECT manager, director, quarter,
Count (score) audits_completed,
COUNT ((select max(1) from "ERROR" o where o.score_entry_id=s.score_entry_id)
) error_occurences -- ** Added **
FROM score_entry s
GROUP BY manager, director, quarter
) --Audits_Performed
SELECT a.director,
a.manager manager,
a.total_audits_required,
s.audits_completed,
Round(( 1 - ( s.error_occurences ) / ( s.audits_completed )) * 100, 2), -- ** Added **
Round(( ( s.audits_completed ) / ( a.total_audits_required ) * 100 ), 2)
percentage_complete,
a.quarter
FROM aud a
left outer join scores s ON a.manager = s.manager
WHERE ( :P4_manager = a.manager
OR :P4_manager IS NULL )
AND ( :P4_DIRECTOR = a.director
OR :P4_DIRECTOR IS NULL )
AND ( :P4_QUARTER = a.quarter
OR :P4_QUARTER IS NULL )
ORDER BY a.total_audits_required DESC nulls last
About total_errors:
To add this column you can either use a technique similar to the one used before in scores:
scores AS (
SELECT manager, director, quarter,
count (score) audits_completed,
count ((select max(1) from "ERROR" o where o.score_entry_id=s.score_entry_id )
) error_occurences,
sum ( ( SELECT count(*) from "ERROR" o where o.score_entry_id=s.score_entry_id )
) total_errors -- summing error counts for matched score_entry_ids
FROM score_entry s
GROUP BY manager, director, quarter
)
Or you can rewrite the scores CTE joining score_entry and error, and that would require using DISTINCT on score_entry fields to avoid duplication of rows:
scores AS (
SELECT manager, director, quarter,
count(DISTINCT s.score_entry_id) audits_completed,
count(DISTINCT e.score_entry_id ) error_occurences, -- counting distinct score_entry_ids present in Error
count(e.score_entry_id) total_errors -- counting total rows in Error
FROM score_entry s
LEFT JOIN "ERROR" e ON s.score_entry_id=e.score_entry_id
GROUP BY manager, director, quarter
)
The latter approach is a bit less maintable, since it requires to be careful about unwanted duplication.
Yet another (and may be the most proper) way is to make a separate(third) CTE, but I don't think the query is complex enough to warrant this.
Original answer:
I might be wrong, but it seems to me that by "count of each occurrence of error" you are trying to describe COUNT(DISTINCT expr). That is to count unique occurences of error for each (manager_email, director, quarter).
If so, change the query a bit:
WITH aud(manager_email, director, quarter, total_audits_required)
AS (SELECT manager_email,
director,
quarter,
SUM (CASE
WHEN audit_eligible = 'Y' THEN required_audits
END)
FROM required_audits
GROUP BY manager_email,
director,
quarter), --Total_audits
scores(manager_email, director, quarter, audits_completed, distinct_errors)
AS (SELECT manager_email,
director,
quarter,
Count (score),
COUNT (DISTINCT o.error_id) -- ** Added **
FROM oq_score_entry s join error o on o.score_entry_id=s.score_entry_id
GROUP BY manager_email,
director,
quarter) --Audits_Performed
SELECT a.director,
a.manager_email manager,
a.total_audits_required,
s.audits_completed,
Round(( ( s.distinct_errors ) / ( s.audits_completed ) * 100 ), 2) quality, -- ** Added **
Round(( ( s.audits_completed ) / ( a.total_audits_required ) * 100 ), 2)
percentage_complete,
a.quarter
FROM aud a
left outer join scores s
ON a.manager_email = s.manager_email
WHERE ( :P4_MANAGER_EMAIL = a.manager_email
OR :P4_MANAGER_EMAIL IS NULL )
AND ( :P4_DIRECTOR = a.director
OR :P4_DIRECTOR IS NULL )
AND ( :P4_QUARTER = a.quarter
OR :P4_QUARTER IS NULL )
ORDER BY a.total_audits_required DESC nulls last
The join on your main query will need to include director and quarter once you have more data.
I suppose the easiest way to fix this is to follow the structure you've got and add another table expression joining it to the rest of your results in the same way as the original two.
select manager_email, director, quarter,
100.0 - 100.0 * count (distinct e.score_entry_id) / count (*) as quality
from score_entry se left outer join error e
on e.score_entry_id = se.score_entry_id
group by manager_email, director, quarter
What would have made most of your explanation unnecessary is to have simply said that you want the number of scores that have an error associated with them. It was difficult to draw that out from the information you provided.
I have the following set of data:
player | score | day
--------+-------+------------
John | 3 | 02-01-2014
John | 5 | 02-02-2014
John | 7 | 02-03-2014
John | 9 | 02-04-2014
John | 11 | 02-05-2014
John | 13 | 02-06-2014
Mark | 2 | 02-01-2014
Mark | 4 | 02-02-2014
Mark | 6 | 02-03-2014
Mark | 8 | 02-04-2014
Mark | 10 | 02-05-2014
Mark | 12 | 02-06-2014
Given two time ranges:
02-01-2014..02-03-2014
02-04-2014..02-06-2014
I need to get average score for each player within a given time range. Ultimate result I'm trying to achieve is this:
player | period_1_score | period_2_score
--------+----------------+----------------
John | 5 | 11
Mark | 4 | 10
The original algorithm I came up with was:
perform SELECT with two values, derived by partitioning the set of scores into two for each time period
over the first SELECT, perform another one, grouping the set by player name.
I'm stuck on step 1: running the following query:
SELECT
player,
AVG(score) OVER (PARTITION BY day BETWEEN '02-01-2014' AND '02-03-2014') AS period_1,
AVG(score) OVER (PARTITION BY day BETWEEN '02-04-2014' AND '02-06-2014') AS period_2;
Gets me incorrect result (note how period1 and period2 average scores scores are the same:
player | period_1_score | period_2_score
--------+----------------+----------------
John | 5 | 5
John | 5 | 5
John | 5 | 5
John | 5 | 5
John | 5 | 5
John | 5 | 5
Mark | 4 | 4
Mark | 4 | 4
Mark | 4 | 4
Mark | 4 | 4
Mark | 4 | 4
Mark | 4 | 4
I think I don't fully understand how window functions work... I have 2 questions:
What is wrong with my query?
How do I do it right?
You don't need window function for this.
Try:
select
player
,avg(case when day BETWEEN '02-01-2014' AND '02-03-2014' then score else null end) as period_1_score
,avg(case when day BETWEEN '02-04-2014' AND '02-06-2014' then score else null end) as period_1_score
from <your data>
group by player
I need to create a form to summarize wage of each employees according to Date_start and Date_end that I selected.
I have 3 related tables.
tbl_labor
lb_id | lb_name | lb_OT ($/day) | If_social_sec
1 | John | 10 | yes
2 | Mary | 10 | no
tbl_production
pdtn_date | lb_id | pdtn_qty(pcs) | pd_making_id
5/9/12 | 1 | 200 | 12
5/9/12 | 1 | 40 | 13
5/9/12 | 2 | 300 | 12
7/9/12 | 1 | 48 | 13
13/9/12 | 2 | 220 | 14
15/9/12 | 1 | 20 | 12
20/9/12 | 1 | 33 | 14
21/9/12 | 2 | 55 | 14
21/9/12 | 1 | 20 | 12
tbl_pdWk_process
pd_making_id | pd_cost($/dozen) | pd_id
12 | 2 | 001
13 | 5 | 001
14 | 6 | 002
The outcome will look like this:
lb_name | no.working days | Total($)| OT payment | Social_sec($)| Net Wage |
John | 4 | 98.83 | 20 (2x10) | 15 | 103.83 (98.83+20-15)|
Mary | 2 | 160 | 10 (1x10) | 0 | 170 (160+10-0) |
My conditions are:
Wage are calculate between 2 dates that i specify eg. 5/9/12 - 20/9/12
Wage must be calculated from (pd_cost * pdtn_qty). However, pdtn_qty was kept in 'pieces' whereas pd_cost was kept in 'dozen'. Therefore the formula should be (pdtn_qty * pd_cost)/12
Add OT * no. of OT days that each worker did (eg. John had 2 OT days, Mary 1 OT day)
Total wages must be deducted eg. 15$ if If_social_sec are "TRUE"
Count no. of working days that each employees had worked.
I've tried but i couldn't merge all this condition together in one SQL statement, so could you please help me. Thank you.
OK this is really messy. Mainly because Access has no COUNT(DISTINCT ) option. So counting the working days is a mess. If you can skip that, then you can drop all the pdn1,pdn2,pdn3 stuff. But id does work. Couple of notes
1. I think your maths is not quite right in the example given, I make it like this:
2 I've used the IIF clause to simulate 2 OT for john, 1 for mary. You'll need to change that. Good luck.
select
lab.lb_name,
max(days),
sum(prod.pdtn_qty * pdWk.pd_cost / 12) as Total ,
max(lab.lb_OT * iif(lab.lb_id=1,2,1)) as OTPayment,
max(iif(lab.if_social_sec='yes' , 15,0 ) ) as Social_Sec,
sum(prod.pdtn_qty * pdWk.pd_cost / 12.00) +
max(lab.lb_OT * iif(lab.lb_id=1,2,1)) -
max(iif(lab.if_social_sec='yes' , 15,0 ) ) as NetWage
from
tbl_labor as lab,
tbl_production as prod,
tbl_pdWk_process as pdwk,
(select pdn2.lb_id, count(pdn2.lb_id) as days from
(select lb_id
from tbl_production pdn1
where pdn1.pdtn_date >= #9/5/2012#
and pdn1.pdtn_date <= #2012-09-20#
group by lb_id, pdtn_date ) as pdn2
group by pdn2.lb_id) as pdn3
where prod.pdtn_date >= #9/5/2012#
and prod.pdtn_date <= #2012-09-20#
and prod.lb_id = lab.lb_id
and prod.pd_making_id = pdwk.pd_making_id
and lab.lb_id = pdn3.lb_id
group by lab.lb_name
OK to add the items not in production table, you'll need to append something like this:
Union
select lab.lb_name,
0,
0,
max(lab.lb_OT * iif(lab.lb_id=1,2,1)) ,
max(iif(lab.if_social_sec='yes' , 15,0 ) ),0
from tbl_labor lab
where lb_id not in ( select lb_id from tbl_production where pdtn_date >= #2012-09-05# and pdtn_date <= #2012-09-20# )
group by lab.lb_name
Hope this helps.