Seeking some help after spending alot of time on searching but to no avail and decided to post this here as I'm rather new to SQL, so any help is greatly appreciated. I've tried a few functions but can't seem to get it right. e.g. GROUP BY, BETWEEN etc
On the PrestoSQL server, I have a table as shown below starting with columns Date, ID and COVID. Using GROUP BY ID, I would like to create a column EverCOVIDBefore which looks back at all past dates of the COVID column to see if there was ever COVID = 1 or not, as well as another column called COVID_last_2_mth which checks if there was ever COVID = 1 within the past 2 months
(Highlighted columns are my expected outcomes)
Link to dataset: https://drive.google.com/file/d/1Sc5Olrx9g2A36WnLcCFMU0YTQ3-qWROU/view?usp=sharing
You can do:
select *,
max(covid) over(partition by id order by date) as ever_covid_before,
max(covid) over(partition by id order by date
range between interval '2 month' preceding and current row)
as covid_last_two_months
from t
Result:
date id covid ever_covid_before covid_last_two_months
----------- --- ------ ------------------ ---------------------
2020-01-15 1 0 0 0
2020-02-15 1 0 0 0
2020-03-15 1 1 1 1
2020-04-15 1 0 1 1
2020-05-15 1 0 1 1
2020-06-15 1 0 1 0
2020-01-15 2 0 0 0
2020-02-15 2 1 1 1
2020-03-15 2 0 1 1
2020-04-15 2 0 1 1
2020-05-15 2 0 1 0
2020-06-15 2 1 1 1
See running example at db<>fiddle.
Related
I have a table that currently looks like this (simplified to illustate my issue):
Thing| Date
1 2022-12-12
2 2022-11-05
3 2022-11-18
4 2022-12-01
1 2022-11-02
2 2022-11-21
5 2022-12-03
5 2022-12-08
2 2022-11-18
1 2022-11-20
I would like to generate the following:
Thing| 2022-11 | 2022-12
1 2 1
2 3 0
3 1 0
4 0 1
5 0 2
I'm new to SQL and can't quite figure this out - would I use some sort of FOR loop equivalent in my SELECT clause? I'm happy to figure out the exact syntax myself, I just need someone to point me in the right direction.
Thank you!
You may use conditional aggregation as the following:
Select Thing,
Count(Case When Date Between '2022-11-01' And '2022-11-30' Then 1 End) As '2022-11',
Count(Case When Date Between '2022-12-01' And '2022-12-31' Then 1 End) As '2022-12'
From table_name
Group By Thing
Order By Thing
See a demo.
The count function counts only the not null values, so for each row not matching the condition inside the count function a null value is returned, hence not counted.
I'm trying to extract the stock in an specific date. To do so, I'm doing a cumulative of stock movements by date, product and warehouse.
select m.codart AS REF,
m.descart AS 'DESCRIPTION',
m.codalm AS WAREHOUSE,
m.descalm AS WAREHOUSEDESCRIP,
m.unidades AS UNITS,
m.entran AS 'IN',
m.salen AS 'OUT',
m.entran*1 + m.salen*-1 as MOVEMENT,
(select sum(m1.entran*1 + m1.salen*-1)
from MOVSTOCKS m1
where m1.codart = m.codart and m1.codalm = m.codalm and m.fecdoc >= m1.fecdoc) as 'CUMULATIVE',
m.PRCMEDIO as 'VALUE',
m.FECDOC as 'DATE',
m.REFERENCIA as 'REF',
m.tipdoc as 'DOCUMENT'
from MOVSTOCKS m
where (m.entran <> 0 or m.salen <> 0)
and (select max(m2.fecdoc) from MOVSTOCKS m2) < '2020-11-30T00:00:00.000'
order by m.fecdoc
Without the and (select max(m2.fecdoc) from MOVSTOCKS m2) < '2020-11-30T00:00:00.000' it shows data like this, which is ok.
REF WAREHOUSE UNITS IN OUT MOVEMENT CUMULATIVE DATE
1 0 2 0 2 -2 -7 2020-11-25
1 1 3 0 3 -3 -3 2020-11-25
1 0 5 0 5 -5 -7 2020-11-25
1 0 9 9 0 9 2 2020-11-26
2 0 2 2 0 2 2 2020-11-26
1 0 1 1 0 1 3 2020-12-01
The problem is, with the subselect in the where clause it returns no results (I think it is because it just looks for the max date and says it is bigger than 2020-11-30). I would like it to show the closest dates (all of them, for each product and warehouse) to the selected one, in this case 2020-11-30.
It should look slike this:
REF WAREHOUSE UNITS IN OUT MOVEMENT CUMULATIVE DATE
1 1 3 0 3 -3 -3 2020-11-25
1 0 9 9 0 9 2 2020-11-26
2 0 2 2 0 2 2 2020-11-26
Sorry if I'm not clear. Ask me if I have to clarify anything
Thank you
I am guessing that you want something like this:
select t.*
from (select m.*,
sum(m.entran - m1.salen) over (partition by m.codart, m.codalm order by fecdoc) as cumulative,
max(fecdoc) over (partition by m.codart, m.codalm) as max_fecdoc
from MOVSTOCKS m
where fecdoc < '2020-11-30'
) m
where fecdoc = max_fecdoc;
The subquery calculates the cumulative amount of stock using window functions and filters for records before the cutoff date. The outer query selects the most recent record from the combination of codeart/codalm, which seems to be how you are identifying a product.
I have a dataframe with ID and date ( and calculated day difference between the rows for the same ID)
ID date day_difference
1 27/06/2019 0
1 28/06/2019 1
1 29/06/2019 1
1 01/07/2019 2
1 02/07/2019 1
1 03/07/2019 1
1 05/07/2019 2
2 27/06/2019 0
2 28/06/2019 1
2 29/06/2019 1
2 01/08/2019 33
2 02/08/2019 1
2 03/08/2019 1
2 04/08/2019 1
which i would like to group by ID and calculate total duration with a condition if day difference is bigger than 30 days re-use that ID again and create a new group starting counting duration from that day after a 30day gap.
Desired result
ID Duration
1 8
2 3
2 4
Thanks.
You can do:
(df.groupby(['ID', df.day_difference.gt(30).cumsum()])
.agg(ID=('ID','first'), Duration=('ID','count'))
.reset_index(drop=True)
)
Output:
ID Duration
0 1 7
1 2 3
2 2 4
I'm not sure how else to explain it other than the title. I'm basically trying to get the number of rows per id before the date on that specific row. I've tried a bunch of things and scoured the internet to no avail. Please help!
Before
id date
1 3/3/2015
2 3/27/2015
2 4/15/2015
2 5/1/2015
3 3/7/2015
3 5/17/2015
3 7/9/2015
3 7/19/2015
After
id date count
1 3/3/2015 0
2 3/27/2015 0
2 4/15/2015 1
2 5/1/2015 2
3 3/7/2015 0
3 5/17/2015 1
3 7/9/2015 2
3 7/19/2015 3
-1 + row_number() over (partition by id order by date)
So I have data like this:
Date EMPLOYEE_ID HEADCOUNT TERMINATIONS
1/31/2011 1 1 0
2/28/2011 1 1 0
3/31/2011 1 1 0
4/30/2011 1 1 0
...
1/31/2012 1 1 0
2/28/2012 1 1 0
3/31/2012 1 1 0
1/31/2012 2 1 0
2/28/2011 2 1 0
3/31/2011 2 1 0
4/30/2011 2 0 1
1/31/2012 3 1 0
2/28/2011 3 1 0
3/31/2011 3 1 0
4/30/2011 3 1 0
...
1/31/2012 3 1 0
2/28/2012 3 1 0
3/31/2012 3 1 0
And I want to sum up the headcount, but I need to remove the duplicate entries from the sum by the employee_id. From the data you can see employee_id 1 occurs many times in the table, but I only want to add its headcount column once. For example if I rolled up on year I might get a report using this query:
with member [Measures].[Distinct HeadCount] as
??? how do I define this???
select { [Date].[YEAR].children } on ROWS,
{ [Measures].[Distinct HeadCount] } on COLUMNS
from [someCube]
It would product this output:
YEAR Distinct HeadCount
2011 3
2012 2
Any ideas how to do this with MDX? Is there a way to control which row is used in the sum for each employee?
You can use an expression like this:
WITH MEMBER [Measures].[Distinct HeadCount] AS
Sum(NonEmpty('the set of the employee ids', 'all the dates of the current year (ie [Date].[YEAR].CurrentMember)'), [Measures].[HeadCount])
If you want a more generic expression you can use this:
WITH MEMBER [Measures].[Distinct HeadCount] AS
Sum(NonEmpty('the set of the employee ids',
Descendants(Axis(0).Item(0).Item(0).Hierarchy.CurrentMember, Axis(0).Item(0).Item(0).Hierarchy.CurrentMember.Level, LEAVES)),
IIf(IsLeaf(Axis(0).Item(0).Item(0).Hierarchy.CurrentMember),
[Measures].[HeadCount],
NULL))