I have this table
I want to group by age with case and count the gender type
This case:
age <= 20 then 'Group <= 20'
age between 21-40 then 'Group 21-40'
age between 41-60 then 'Group 41-60'
age > 60 then 'Group > 60'
I've tried this code but I get an error:
%%sql
select customer_id, birthdate, extract('year' from current_date) - extract('year' from birthdate ) age
case when age <= 20 then 'Group <= 20'
when age between 21 and 40 then 'Group 21 - 40'
when age between 41 and 60 then 'Group 41 - 60'
else 'Group > 60' end gender
from dim_customer
group by 1
Any solution? Thanks in advance.
BTW: I use this code in Python
Alias columns are not used in SELECT but it's used at GROUP BY and ORDER BY clause.
-- PostgreSQL
SELECT t.*
, CASE WHEN age <= 20 THEN 'Group <= 20'
WHEN age BETWEEN 21 AND 40 THEN 'Group 21 - 40'
WHEN age BETWEEN 41 AND 60 THEN 'Group 41 - 60'
ELSE 'Group > 60' END gender
FROM (SELECT customer_id, birthdate
, extract('year' from current_date) - extract('year' from birthdate ) age
from dim_customer) t
Please check from url https://dbfiddle.uk/?rdbms=postgres_11&fiddle=38c6ba05adc779aed3063e490bcc6376
N.B.: Use date_part('year', current_timestamp :: DATE) - date_part('year', birthdate) for age calculation.
Count gender and use alias at group by section
SELECT CASE WHEN age <= 20 THEN 'Group <= 20'
WHEN age BETWEEN 21 AND 40 THEN 'Group 21 - 40'
WHEN age BETWEEN 41 AND 60 THEN 'Group 41 - 60'
ELSE 'Group > 60' END gender
, COUNT(t.gender) count_gender
, COUNT(CASE WHEN t.gender = 'M' THEN 1 END) gen_male
, COUNT(CASE WHEN t.gender = 'F' THEN 1 END) gen_female
FROM (SELECT customer_id, birthdate, gender
, extract('year' from current_date) - extract('year' from birthdate ) age
, date_part('year', current_timestamp :: DATE) - date_part('year', birthdate) age1
from dim_customer) t
GROUP BY CASE WHEN age <= 20 THEN 'Group <= 20'
WHEN age BETWEEN 21 AND 40 THEN 'Group 21 - 40'
WHEN age BETWEEN 41 AND 60 THEN 'Group 41 - 60'
ELSE 'Group > 60' END
Please check from url https://dbfiddle.uk/?rdbms=postgres_11&fiddle=ad8af9dd9b82ede20452377615ca7fde
I have a table that has data of user_id and the timestamp they joined.
If I need to display the data month-wise I could just use:
select
count(user_id),
date_trunc('month',(to_timestamp(users.timestamp))::timestamp)::date
from
users
group by 2
The date_trunc code allows to use 'second', 'day', 'week' etc. Hence I could get data grouped by such periods.
How do I get data grouped by "n-day" period say 45 days ?
Basically I need to display number users per 45 day period.
Any suggestion or guidance appreciated!
Currently I get:
Date Users
2015-03-01 47
2015-04-01 72
2015-05-01 123
2015-06-01 132
2015-07-01 136
2015-08-01 166
2015-09-01 129
2015-10-01 189
I would like the data to come in 45 days interval. Something like :-
Date Users
2015-03-01 85
2015-04-15 157
2015-05-30 192
2015-07-14 229
2015-08-28 210
2015-10-12 294
UPDATE:
I used the following to get the output, but one problem remains. I'm getting values that are offset.
with
new_window as (
select
generate_series as cohort
, lag(generate_series, 1) over () as cohort_lag
from
(
select
*
from
generate_series('2015-03-01'::date, '2016-01-01', '45 day')
)
t
)
select
--cohort
cohort_lag -- This worked. !!!
, count(*)
from
new_window
join users on
user_timestamp <= cohort
and user_timestamp > cohort_lag
group by 1
order by 1
But the output I am getting is:
Date Users
2015-04-15 85
2015-05-30 157
2015-07-14 193
2015-08-28 225
2015-10-12 210
Basically The users displayed at 2015-03-01 should be the users between 2015-03-01 and 2015-04-15 and so on.
But I seem to be getting values of users upto a date. ie: upto 2015-04-15 users 85. which is not the results I want.
Any help here ?
Try this query :
SELECT to_char(i::date,'YYYY-MM-DD') as date, 0 as users
FROM generate_series('2015-03-01', '2015-11-30','45 day'::interval) as i;
OUTPUT :
date users
2015-03-01 0
2015-04-15 0
2015-05-30 0
2015-07-14 0
2015-08-28 0
2015-10-12 0
2015-11-26 0
This looks like a hot mess, and it might be better wrapped in a function where you could use some variables, but would something like this work?
with number_of_intervals as (
select
min (timestamp)::date as first_date,
ceiling (extract (days from max (timestamp) - min (timestamp)) / 45)::int as num
from users
),
intervals as (
select
generate_series(0, num - 1, 1) int_start,
generate_series(1, num, 1) int_end
from number_of_intervals
),
date_spans as (
select
n.first_date + 45 * i.int_start as interval_start,
n.first_date + 45 * i.int_end as interval_end
from
number_of_intervals n
cross join intervals i
)
select
d.interval_start, count (*) as user_count
from
users u
join date_spans d on
u.timestamp >= d.interval_start and
u.timestamp < d.interval_end
group by
d.interval_start
order by
d.interval_start
With this sample data:
User Id timestamp derived range count
1 3/1/2015 3/1-4/15
2 3/26/2015 "
3 4/4/2015 "
4 4/6/2015 " (4)
5 5/6/2015 4/16-5/30
6 5/19/2015 " (2)
7 6/16/2015 5/31-7/14
8 6/27/2015 "
9 7/9/2015 " (3)
10 7/15/2015 7/15-8/28
11 8/8/2015 "
12 8/9/2015 "
13 8/22/2015 "
14 8/27/2015 " (5)
Here is the output:
2015-03-01 4
2015-04-15 2
2015-05-30 3
2015-07-14 5
I have a stock transaction table like this:
StockID Item TransDate TranType BatchNo Qty Price
10001 ABC 01-Apr-2012 IN 71001000 200 750.0
10002 ABC 02-Apr-2012 OUT 100
10003 ABC 03-Apr-2012 IN 71001001 50 700.0
10004 ABC 04-Apr-2012 IN 71001002 75 800.0
10005 ABC 10-Apr-2012 OUT 125
10006 XYZ 05-Apr-2012 IN 71001003 150 350.0
10007 XYZ 05-Apr-2012 OUT 120
10008 XYZ 15-Apr-2012 OUT 10
10009 XYZ 20-Apr-2012 IN 71001004 90 340.0
10010 PQR 06-Apr-2012 IN 71001005 50 510.0
10011 PQR 15-Apr-2012 IN 71001006 60 505.0
10012 MNO 01-Apr-2012 IN 71001007 76 410.0
10013 MNO 11-Apr-2012 OUT 76
Each of my IN transactions has price associated to it and a batch number (lot number). Now I would like to calculate the remaining quantity by First In First Out (FIFO) rule, meaning the first in should be adjusted with first out. After adjusting the quantities the remaining balances are to be calculated against each IN transaction for the same item as shown below:
StockID Item TransDate TranType BatchNo Qty Price RemainingQty
10001 ABC 01-Apr-2012 IN 71001000 200 750.0 0
10002 ABC 02-Apr-2012 OUT 100
10003 ABC 03-Apr-2012 IN 71001001 50 700.0 25
10004 ABC 04-Apr-2012 IN 71001002 75 800.0 75
10005 ABC 10-Apr-2012 OUT 125
10006 XYZ 05-Apr-2012 IN 71001003 150 350.0 20
10007 XYZ 05-Apr-2012 OUT 120
10008 XYZ 15-Apr-2012 OUT 10
10009 XYZ 20-Apr-2012 IN 71001004 90 340.0 90
10010 PQR 06-Apr-2012 IN 71001005 50 510.0 50
10011 PQR 15-Apr-2012 IN 71001006 60 505.0 60
10012 MNO 01-Apr-2012 IN 71001007 76 410.0 0
10013 MNO 11-Apr-2012 OUT 76
As we can see from the above table for item ABC, after adjusting (125 + 100) OUT qty against the IN qty (100 + 50 + 75) using FIFO the quantity remaining for the batch 71001000 is 0, 71001001 is 25 and for batch 71001002 is 75. From the remaining quantity the value can be derived.
Please help me to achieve this using any of the methods (either cursor based or CTE or JOINS, etc)
Thanks in advance for the help.
One of the users of StockOverflow suggested this answer:
SELECT 10001 as stockid,'ABC' as item,'01-Apr-2012' as transdate,'IN' as trantype, 71001000 as batchno, 200 as qty, 750.0 as price INTO #sample
UNION ALL SELECT 10002 ,'ABC','02-Apr-2012','OUT', NULL ,100,NULL
UNION ALL SELECT 10003 ,'ABC','03-Apr-2012','IN', 71001001, 50 , 700.0
UNION ALL SELECT 10004 ,'ABC','04-Apr-2012','IN', 71001002, 75 , 800.0
UNION ALL SELECT 10005 ,'ABC','10-Apr-2012','OUT', NULL ,125,NULL
UNION ALL SELECT 10006 ,'XYZ','05-Apr-2012','IN', 71001003, 150 , 350.0
UNION ALL SELECT 10007 ,'XYZ','05-Apr-2012','OUT', NULL , 120 ,NULL
UNION ALL SELECT 10008 ,'XYZ','15-Apr-2012','OUT', NULL , 10 ,NULL
UNION ALL SELECT 10009 ,'XYZ','20-Apr-2012','IN', 71001004, 90 , 340.0
UNION ALL SELECT 10010 ,'PQR','06-Apr-2012','IN', 71001005, 50 , 510.0
UNION ALL SELECT 10011 ,'PQR','15-Apr-2012','IN', 71001006, 60 , 505.0
UNION ALL SELECT 10012 ,'MNO','01-Apr-2012','IN', 71001007, 76 , 410.0
UNION ALL SELECT 10013 ,'MNO','11-Apr-2012','OUT', NULL ,76 ,NULL
;WITH remaining AS
(
SELECT *,
CASE
WHEN trantype = 'IN' THEN 1
ELSE -1
END * qty AS stock_shift,
ROW_NUMBER() OVER(PARTITION BY item ORDER BY transdate) AS row,
CASE
WHEN trantype = 'OUT' THEN NULL
ELSE ROW_NUMBER()OVER(PARTITION BY item, CASE WHEN trantype = 'IN' THEN 0 ELSE 1 END ORDER BY transdate)
END AS in_row,
SUM(CASE WHEN trantype = 'OUT' THEN qty END) OVER(PARTITION BY item) AS total_out
FROM #sample
)
,remaining2 AS
(
SELECT r1.item,
r1.stockid,
MAX(r1.transdate) AS transdate,
MAX(r1.trantype) AS trantype,
MAX(r1.batchno) AS batchno,
MAX(r1.qty) AS qty,
MAX(r1.price) AS price,
MAX(r1.total_out) AS total_out,
MAX(r1.in_row) AS in_row,
CASE
WHEN MAX(r1.trantype) = 'OUT' THEN NULL
WHEN SUM(CASE WHEN r1.trantype = 'IN' THEN r2.qty ELSE 0 END) - MAX(r1.total_out) < 0 THEN SUM(CASE WHEN r1.trantype = 'IN' THEN r2.qty ELSE 0 END)
- MAX(r1.total_out)
ELSE 0
END AS running_in
FROM remaining r1
LEFT OUTER JOIN remaining r2
ON r2.row <= r1.row
AND r2.item = r1.item
GROUP BY
r1.item,
r1.stockid
)
SELECT r2.item,
r2.stockid,
MAX(r2.transdate) AS transdate,
MAX(r2.trantype) AS trantype,
MAX(r2.batchno) AS batchno,
MAX(r2.qty) AS qty,
MAX(r2.price) AS price,
MAX(CASE WHEN r2.trantype = 'OUT' THEN NULL ELSE ISNULL(r2.qty + r3.running_in, 0) END) AS remaining_stock
FROM remaining2 r2
LEFT OUTER JOIN remaining2 r3
ON r2.in_row - 1 = r3.in_row
AND r2.item = r3.item
GROUP BY
r2.item,
r2.stockid
This sql is having a problem and the result is attached here The records for which the value are not matching are indicated in yellow color. Kindly help to solve the problem.
I think this should do the trick?
SELECT 10001 as stockid,'ABC' as item,'01-Apr-2012' as transdate,'IN' as trantype, 71001000 as batchno, 200 as qty, 750.0 as price INTO #sample
UNION ALL SELECT 10002 ,'ABC','02-Apr-2012','OUT', NULL ,100,NULL
UNION ALL SELECT 10003 ,'ABC','03-Apr-2012','IN', 71001001, 50 , 700.0
UNION ALL SELECT 10004 ,'ABC','04-Apr-2012','IN', 71001002, 75 , 800.0
UNION ALL SELECT 10005 ,'ABC','10-Apr-2012','OUT', NULL ,125,NULL
UNION ALL SELECT 10006 ,'XYZ','05-Apr-2012','IN', 71001003, 150 , 350.0
UNION ALL SELECT 10007 ,'XYZ','05-Apr-2012','OUT', NULL , 120 ,NULL
UNION ALL SELECT 10008 ,'XYZ','15-Apr-2012','OUT', NULL , 10 ,NULL
UNION ALL SELECT 10009 ,'XYZ','20-Apr-2012','IN', 71001004, 90 , 340.0
UNION ALL SELECT 10010 ,'PQR','06-Apr-2012','IN', 71001005, 50 , 510.0
UNION ALL SELECT 10011 ,'PQR','15-Apr-2012','IN', 71001006, 60 , 505.0
UNION ALL SELECT 10012 ,'MNO','01-Apr-2012','IN', 71001007, 76 , 410.0
UNION ALL SELECT 10013,'MNO','11-Apr-2012','OUT', NULL ,76 ,NULL
;with remaining_stock as
(
SELECT *
,CASE WHEN trantype = 'IN' THEN 1 ELSE -1 END * qty AS stock_shift
,row_number() OVER (PARTITION BY item ORDER BY transdate) as row
,CASE WHEN trantype = 'OUT' THEN NULL ELSE
row_number()OVER (PARTITION BY item,CASE WHEN trantype = 'IN' THEN 0 ELSE 1 END ORDER BY transdate) END as in_row
,CASE WHEN trantype = 'IN' THEN NULL ELSE
row_number()OVER (PARTITION BY item,CASE WHEN trantype = 'OUT' THEN 0 ELSE 1 END ORDER BY transdate) END as out_row
,ISNULL(SUM(CASE WHEN trantype = 'OUT' THEN qty END) OVER (PARTITION BY item),0) AS total_out
,ISNULL(SUM(CASE WHEN trantype = 'IN' THEN qty END) OVER (PARTITION BY item),0) AS total_in
FROM #sample
)
,remaining_stock2 AS
(
SELECT
r1.item
,r1.stockid
,MAX(r1.transdate) as transdate
,MAX(r1.trantype) as trantype
,MAX(r1.batchno) as batchno
,MAX(r1.qty) as qty
,MAX(r1.price) as price
,MAX(r1.total_in) as total_in
,MAX(r1.total_out) as total_out
,SUM(r2.qty) as running_in
FROM remaining_stock r1
LEFT OUTER JOIN remaining_stock r2 on r2.in_row <= r1.in_row
AND r2.item = r1.item
GROUP BY
r1.item
,r1.stockid
)
SELECT
item
,stockid
,transdate
,trantype
,batchno
,qty
,price
,CASE WHEN trantype = 'OUT' THEN NULL
WHEN total_out >= running_in THEN 0
WHEN (running_in - total_out) < qty THEN (running_in - total_out)
WHEN (running_in - total_out) >= qty THEN qty
END as remaining_stocks
FROM remaining_stock2
Your question isn't very clear to me on how the FIFO logic is to be applied. I'm going to assume that you want to associate each IN record against the next OUT record if one exists. To achieve this you need to join the table on itself like the following
select
t1.BatchNo,
isnull(t1.Qty,0) as 'IN Qty',
isnull(t2.Qty,0) as 'OUT Qty',
isnull(t1.Qty,0) - isnull(t2.Qty,0) as 'Remaining Qty'
from
tbl_test t1
left join tbl_test t2
on t2.StockID = (t1.StockID + 1)
and t2.TranType = 'OUT'
where
t1.TranType = 'IN'
The results will show you the following for the first 5 records for ABC from your question.
BatchNo | IN Qty | OUT Qty | Remaining Qty
71001000 | 200 | 100 | 100
71001001 | 50 | 0 | 50
71001002 | 75 | 125 | -50
The left join works on the assumption that the StockID for each IN record is always one less number than the associated OUT record. I personally think your data model needs improving.
OUT records should have a BatchNo assigned or a reference to the
StockID of the associated IN record
add a timestamp field for sequential ordering
add a DateTime field for handling IN/OUT occuring on same day
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.