I'm working with patient-level data in Azure Databricks and I'm trying to build out a cohort of patients that have at least 2 diagnoses from a list of specific diagnosis codes. This is essentially what the table looks like:
CLAIM_ID | PTNT_ID | ICD_CD | DATE
---------+---------+--------+------------
1 101 2500 01_25_2020
2 101 3850 03_13_2018
3 222 2500 10_26_2018
4 222 8888 11_30_2018
5 222 9155 04_01_2019
6 871 2500 02_17_2020
7 871 3200 09_09_2019
The list of ICD_CD codes of interest is something like [2500, 3850, 8888]. In this case, I would want to return TOTAL UNIQUE PTNT_ID = 2. These would be PTNT_ID = (101, 222) as these are the only two patients that have at least 2 ICD_CD codes of interest.
When I use something like this, I'm able to return all of the relevant PTNT_ID values, but I'm not able to get the total count of these PTNT_ID:
select mc.PTNT_ID
from MEDICAL_CLAIMS mc
where mc.PTNT_ID in ( # list of ICD_CD of interest
)
group by mc.PTNT_ID
having count(distinct mc.PTNT) >= 2
When I try to add a COUNT statement in, it returns an error
Just select from the query:
select count(*)
from
(
select mc.PTNT_ID
from MEDICAL_CLAIMS mc
where mc.PTNT_ID in ( # list of ICD_CD of interest )
group by mc.PTNT_ID
having count(distinct mc.PTNT) >= 2
) ptnts;
Related
I have a table with user shopping data as shown below
I want an output similar to running total but instead I want the running total of the count of unique categories that the user has shopped for by date.
I know I have to make use of ROWS PRECEDING AND FOLLOWING in the count function but I am not able to user count(distinct category) in a window function
Dt category userId
4/10/2022 Grocery 123
4/11/2022 Grocery 123
4/12/2022 MISC 123
4/13/2022 SERVICES 123
4/14/2022 RETAIl 123
4/15/2022 TRANSP 123
4/20/2022 GROCERY 123
Desired output
Dt userID number of unique categories
4/10/2022 123 1
4/11/2022 123 1
4/12/2022 123 2
4/13/2022 123 3
4/14/2022 123 4
4/15/2022 123 5
4/20/2022 123 5
Consider below approach
select Dt, userId,
( select count(distinct category)
from t.categories as category
) number_of_unique_categories
from (
select *, array_agg(lower(category)) over(partition by userId order by Dt) categories
from your_table
) t
if applied to sample data in your question - output is
i have a table TB_Orders , i save orders in thatl ,ike below :
userid
factorid
productname
economy
vip
count
1
A-123
name1
13000
18000
3
1
A-123
name2
9000
13000
4
2
A-124
name2
2000
5000
2
For example, user 1: has registered two orders with invoice number A-123.
And user 2 has only registered one order
I want to report as follows:
userid
factorid
total economy
total vip
total count
1
A-123
21000
31000
7
2
A-124
2000
5000
2
thanks for your help
This is an aggregation query:
select userid, factorid, sum(economy), sum(vip), sum(count)
from tb_orders
group by userid, factorid;
Aggregation is a very basic part of SQL functionality. If you don't recognize it, I would suggest that you brush up on your SQL skills with a tutorial, book, or something like that.
I have been searching the forum and found a single post that is a little smilair to my problem here: Calculate average for Top n combined with SQL Group By.
My situation is:
I have a table tblWEIGHT that contains: ID, Date, idPONR, Weight
I have a second table tblSALES that contains: ID, Date, Sales, idPONR
I have a third table tblPONR that contains: ID, PONR, idProduct
And a fouth table tblPRODUCT that contais: ID, Product
The linking:
tblWEIGHT.idPONR = tblPONR.ID
tblSALES.idPONR = tblPONR.ID
tblPONR.idProduct = tblPRODUCT.ID
The maintable of my query is tblSALES. I want to all my sales listed, with the moving average of the top5
weights of the PRODUCT where the date of the weight is less than the sales date, and the product is the same as the sold product. Its IMPORTANT that the result isn't grouped by the date. I need all the records of tblSALES.
i have gotten as far as to get the top 1 weight, but im not able to get the moving average instread.
The query that gest the top 1 is the following, and i am guessing that the query i need is going to look a lot like it.
SELECT tblSALES.ID, tblSALES.Dato, tblPONR.idPRODUCT,
(
SELECT top 1 Weight FROM tblWEIGHT INNER JOIN tblPONR ON tblWeight.idPONR = tblPONR.ID
WHERE tblPONR.idPRODUCT = idPRODUCT AND
SALES.Date > tblWEIGHT.Date
ORDER BY tblWEIGHT.Date desc
) AS LatestWeight
FROM tblSALES INNER JOIN VtblPONR ON tblSALES.idPONR = tblPONR.ID
this is not my exact query since im danish and i wouldnt make sense. I know im not supposed to use Date as a fieldname.
i imagine the filan query would be something like:
SELECT tblSALES.ID..... avg(SELECT TOP 5 weight .........)
but doing this i keep getting error at max 1 record can be returned by this subquery
Final Question.
How do i make a query that creates a moving average of the top 5 weights of my sold product, where the date of the weight is earlier than the date i sold the product?
EDIT Sampledata:
DATEFORMAT: dd/mm/yyyy
tblWEIGHT
ID Date idPONR Weight
1 01-01-2020 1 100
2 02-01-2020 2 200
3 03-01-2020 3 200
4 04-01-2020 3 400
5 05-01-2020 2 250
6 06-01-2020 1 150
7 07-01-2020 2 200
tblSALES
ID Date Sales(amt) idPONR
1 05-01-2020 30 1
2 06-01-2020 15 2
3 10-01-2020 20 3
tblPONR
ID PONR(production Number) idProduct
1 2521 1
2 1548 1
3 5484 2
tblPRODUCT
ID Product
1 Bricks
2 Tiles
Desired outcome read comments for AvgWeight
tblSALES.ID tblSALES.Date tblSales.Sales(amt) AvgWeigt
1 05-01-2020 30 123 -->avg(top 5 newest weight of both idPONR 1 And 2 because they are the same product, and where tblWeight.Date<05-01-2020)
2 06-01-2020 15 123 -->avg(top 5 newest weight of both idPONR 1 And 2 because they are the same product, and where tblWeight.Date<06-01-2020)
3 10-01-2020 20 123 -->avg(top 5 newest weight of idPONR 3 since thats the only idPONR with that product, and where tblWeight.Date<10-01-2020)
Consider:
Query1
SELECT tblWeight.ID AS WeightID, tblWeight.Date AS WtDate,
tblWeight.idPONR, tblPONR.PONR, tblPONR.idProduct, tblWeight.Weight, tblSales.SalesAmt,
tblSales.ID AS SalesID, tblSales.Date AS SalesDate
FROM (tblPONR INNER JOIN tblWeight ON tblPONR.ID = tblWeight.idPONR)
INNER JOIN tblSales ON tblPONR.ID = tblSales.idPONR;
Query2
SELECT * FROM Query1 WHERE WeightID IN (
SELECT TOP 5 WeightID FROM Query1 AS Dupe WHERE Dupe.idProduct = Query1.idProduct
AND Dupe.WtDate<Query1.SalesDate ORDER BY Dupe.WtDate);
Query3
SELECT Query2.SalesID, Query2.SalesDate, Query2.SalesAmt,
First(DAvg("Weight","Query2","idProduct=" & [idProduct] & " AND WtDate<#" & [SalesDate] & "#")) AS AvgWt
FROM Query2
GROUP BY Query2.SalesID, Query2.SalesDate, Query2.SalesAmt;
Below is the table where I have customer_id and different phones they have.
customer_id phone_number
101 123456789
102 234567891
103 345678912
102 456789123
101 567891234
104 678912345
105 789123456
106 891234567
106 912345678
106 456457234
101 655435664
107 453426782
Now, I want to find customer_id and distinct phone number count.
So I used this query:
select distinct customer_id ,count(distinct phone_number)
from customer_phone;
customer_id no of phones
101 3
102 2
103 1
104 1
105 1
106 3
107 1
And, from the above table my final goal is to achieve the below output which takes the counts and puts in different buckets and then count number of consumers that fall in those buckets.
Buckets no of consumers
3 2
2 1
1 4
There are close to 200 million records. Can you please explain an efficient way to work on this?
You can use width_bucket for that:
select bucket, count(*)
from (
select width_bucket(count(distinct phone_number), 1, 10, 10) as bucket
from customer_phone
group by customer_id
) t
group by bucket;
width_bucket(..., 1, 10, 10) creates ten buckets for the values 1 through 10.
Online Example: http://dbfiddle.uk/?rdbms=oracle_11.2&fiddle=1e6d55305570499f363837aba21bdc7e
Use two aggregations:
select cnt, count(*), min(customer_id), max(customer_id)
from (select customer_id, count(distinct phone_number) as cnt
from customer_phone
group by customer_id
) c
group by cnt
order by cnt;
I have a table like the one below. It is a record of daily featured products and the customers that purchased them (similar to a daily deal site). A given client can only purchase a product one time per feature, but they may purchase the same product if it is featured multiple times.
FeatureID | ClientID | FeatureDate | ProductID
1 1002 2011-05-01 500
1 2333 2011-05-01 500
1 4458 2011-05-01 500
2 8888 2011-05-10 700
2 2333 2011-05-10 700
2 1111 2011-05-10 700
3 1002 2011-05-20 500
3 4444 2011-05-20 500
4 4444 2011-05-30 500
4 2333 2011-05-30 500
4 1002 2011-05-30 500
I want to count by FeatureID the number of clients that purchased FeatureID X AND who purchased the same productID during a previous feature.
For the table above the expected result would be:
FeatureID | CountofReturningClients
1 0
2 0
3 1
4 3
Ideally I would like to do this with SQL, but am also open to doing some manipulation in Excel/PowerPivot. Thanks!!
If you join your table to itself, you can find the data you're looking for. Be careful, because this query can take a long time if the table has a lot of data and is not indexed well.
SELECT t_current.FEATUREID, COUNT(DISTINCT t_prior.CLIENTID)
FROM table_name t_current
LEFT JOIN table_name t_prior
ON t_current.FEATUREDATE > t_prior.FEATUREDATE
AND t_current.CLIENTID = t_prior.CLIENTID
AND t_current.PRODUCTID = t_prior.PRODUCTID
GROUP BY t_current.FEATUREID
"Per feature, count the clients who match for any earlier Features with the same product"
SELECT
Curr.FeatureID
COUNT(DISTINCT Prev.ClientID) AS CountofReturningClients --edit thanks to feedback
FROM
MyTable Curr
LEFT JOIN
MyTable Prev WHERE Curr.FeatureID > Prev.FeatureID
AND Curr.ClientID = Prev.ClientID
AND Curr.ProductID = Prev.ProductID
GROUP BY
Curr.FeatureID
Assumptions: You have a table called Features that is:
FeatureID, FeatureDate, ProductID
If not then you could always create one on the fly with a temporary table, cte or view.
Then:
SELECT
FeatureID
, (
SELECT COUNT(DISTINCT ClientID) FROM Purchases WHERE Purchases.FeatureDate < Feature.FeatureDate AND Feature.ProductID = Purchases.ProductID
) as CountOfReturningClients
FROM Features
ORDER BY FeatureID
New to this, but wouldn't the following work?
SELECT FeatureID, (CASE WHEN COUNT(clientid) > 1 THEN COUNT(clientid) ELSE 0 END)
FROM table
GROUP BY featureID