i use psql v.10.5
and i have a structure table like this :
| date | total |
-------------------------
| 01-01-2018 | 50 |
| 05-01-2018 | 90 |
| 30-01-2018 | 20 |
how to get recap data by month, but the data showed straight 30 days, i want the data showed like this :
| date | total |
-------------------------
| 01-01-2018 | 50 |
| 02-01-2018 | 0 |
| 03-01-2018 | 0 |
| 04-01-2018 | 0 |
| 05-01-2018 | 90 |
.....
| 29-01-2018 | 0 |
| 30-01-2018 | 20 |
i've tried this query :
SELECT * FROM date
WHERE EXTRACT(month FROM "date") = 1 // dynamically
AND EXTRACT(year FROM "date") = 2018 // dynamically
but the result is not what i expected. also the params of month and date i create dynamically.
any help will be appreciated
Use the function generate_series(start, stop, step interval), e.g.:
select d::date, coalesce(total, 0) as total
from generate_series('2018-01-01', '2018-01-31', '1 day'::interval) d
left join my_table t on d::date = t.date
Working example in rextester.
Related
I have these records returned from a query
+---------+--------------+-----------+----------+
| Country | other fields | sales | date |
+---------+--------------+-----------+----------+
| US | 1 | $100.00 | 01/01/21 |
| CA | 1 | $100.00 | 01/01/21 |
| UK | 1 | $100.00 | 01/01/21 |
| FR | 1 | $100.00 | 01/01/21 |
| US | 1 | $200.00 | 01/02/21 |
| CA | 1 | $200.00 | 01/02/21 |
| UK | 1 | $200.00 | 01/02/21 |
| FR | 1 | $200.00 | 01/02/21 |
And I want to show the sales variation from one month to previous, like this:
| Country | 01/02/21 | 01/01/21 | Var% |
| US | $200.00 | $100.00 | 100% |
| CA | $200.00 | $100.00 | 100% |
| FR | $200.00 | $100.00 | 100% |
+---------+--------------+-----------+----------+
How could be done with a Postgres query?
if you always comparing two month only :
select country
, sum(sales) filter (where date ='01/01/21') month1
, sum(sales) filter (where date ='01/02/21') month2
, ((sum(sales) filter (where date ='01/02/21') /sum(sales) filter (where date ='01/01/21')) - 1) * 100 var
from tablename
where date in ('01/01/21' , '01/02/21')
group by country
you also can look at crosstab from tablefunc extension which basically does the same as above query.
CREATE EXTENSION IF NOT EXISTS tablefunc;
select * ,("01/02/21" /"01/01/21") - 1) * 100 var
from(
select * from crosstab ('select Country,date , sales from tablename')
as ct(country varchar(2),"01/01/21" money , "01/02/21" money)
) t
for more info about crosstab , see tablefunc
but if you want to show date in rows instead of columns, you can easily generalize it for all the dates :
select *
, ((sales / LAG(sales,1,1) over (partition by country order by date)) -1)* 100 var
from
country
Im trying to do a cumulative sum over specific periods of time for every row in Postgres, example:
|---------------------|------------------|------------------|
| Date | Value | Employee |
|---------------------|------------------|------------------|
| 25-01-1990 | 34 | Aaron |
|---------------------|------------------|------------------|
| 15-02-1990 | 4 | Aaron |
|---------------------|------------------|------------------|
| 02-03-1990 | 3 | Aaron |
|---------------------|------------------|------------------|
| 22-05-1990 | 7 | Aaron |
|---------------------|------------------|------------------|
Expected result, taking a range of 60 days:
|---------------------|------------------|------------------|
| Date | Value | Employee |
|---------------------|------------------|------------------|
| 25-01-1990 | 34 | Aaron |
|---------------------|------------------|------------------|
| 15-02-1990 | 38 | Aaron |
|---------------------|------------------|------------------|
| 02-03-1990 | 41 | Aaron |
|---------------------|------------------|------------------|
| 01-05-1990 | 10 | Aaron |
|---------------------|------------------|------------------|
I tried with the following but the results are not correct:
WITH tab AS (SELECT * FROM table_with_values)
SELECT tab.Date, SUM(tab.Value)
FILTER (WHERE tab.Date<=tab.Date AND tab.Date >=t.Date - INTERVAL '60 DAY')
OVER(PARTITION BY tab.Employee ORDER BY tab.Date ROWS BETWEEN UNBOUND PRECEDENT AND CURRENT ROW)
AS values_cumulative, tab.Employee
FROM tab
Try this:
SELECT date, employee, sum(bvalue)
FROM (
SELECT a.*, b.date as bdate, b.value as bvalue
FROM testtable a
LEFT JOIN testtable b ON
a.employee = b.employee AND
b.date <= a.date AND
b.date >= a.date - integer '60') c
GROUP BY employee, date
ORDER BY date ASC;
date | employee | sum
------------+----------+-----
1990-01-25 | Aaron | 34
1990-02-15 | Aaron | 38
1990-03-02 | Aaron | 41
1990-05-01 | Aaron | 10
(4 Zeilen)
I had to create a cross tab table from a Query where dates will be changed into column names. These order dates can be increase or decrease as per the dates passed in the query. The order date is in Unix format which is changed into normal format.
Query is following:
Select cd.cust_id
, od.order_id
, od.order_size
, (TIMESTAMP 'epoch' + od.order_date * INTERVAL '1 second')::Date As order_date
From consumer_details cd,
consumer_order od,
Where cd.cust_id = od.cust_id
And od.order_date Between 1469212200 And 1469212600
Order By od.order_id, od.order_date
Table as follows:
cust_id | order_id | order_size | order_date
-----------|----------------|---------------|--------------
210721008 | 0437756 | 4323 | 2016-07-22
210721008 | 0437756 | 4586 | 2016-09-24
210721019 | 10749881 | 0 | 2016-07-28
210721019 | 10749881 | 0 | 2016-07-28
210721033 | 13639 | 2286145 | 2016-09-06
210721033 | 13639 | 2300040 | 2016-10-03
Result will be:
cust_id | order_id | 2016-07-22 | 2016-09-24 | 2016-07-28 | 2016-09-06 | 2016-10-03
-----------|----------------|---------------|---------------|---------------|---------------|---------------
210721008 | 0437756 | 4323 | 4586 | | |
210721019 | 10749881 | | | 0 | |
210721033 | 13639 | | | | 2286145 | 2300040
I have this table named Samples. The Date column values are just symbolic date values.
+----+------------+-------+------+
| Id | Product_Id | Price | Date |
+----+------------+-------+------+
| 1 | 1 | 100 | 1 |
| 2 | 2 | 100 | 2 |
| 3 | 3 | 100 | 3 |
| 4 | 1 | 100 | 4 |
| 5 | 2 | 100 | 5 |
| 6 | 3 | 100 | 6 |
...
+----+------------+-------+------+
I want to group by product_id such that I have the 1'th sample in descending date order and a new colomn added with the Price of the 7'th sample row in each product group. If the 7'th row does not exist, then the value should be null.
Example:
+----+------------+-------+------+----------+
| Id | Product_Id | Price | Date | 7thPrice |
+----+------------+-------+------+----------+
| 4 | 1 | 100 | 4 | 120 |
| 5 | 2 | 100 | 5 | 100 |
| 6 | 3 | 100 | 6 | NULL |
+----+------------+-------+------+----------+
I belive I can achieve the table without the '7thPrice' with the following
SELECT * FROM (
SELECT ROW_NUMBER() OVER (PARTITION BY Product_Id ORDER BY date DESC) r, * FROM Samples
) T WHERE T.r = 1
Any suggestions?
You can try something like this. I used your query to create a CTE. Then joined rank1 to rank7.
;with sampleCTE
as
(SELECT ROW_NUMBER() OVER (PARTITION BY Product_Id ORDER BY date DESC) r, * FROM Samples)
select *
from
(select * from samplecte where r = 1) a
left join
(select * from samplecte where r=7) b
on a.product_id = b.product_id
I have a table like this
Event ID | Contract ID | Event date | Amount |
----------------------------------------------
1 | 1 | 2009-01-01 | 100 |
2 | 1 | 2009-01-02 | 20 |
3 | 1 | 2009-01-03 | 50 |
4 | 2 | 2009-01-01 | 80 |
5 | 2 | 2009-01-04 | 30 |
For each contract I need to fetch the latest event and amount associated with the event and get something like this
Event ID | Contract ID | Event date | Amount |
----------------------------------------------
3 | 1 | 2009-01-03 | 50 |
5 | 2 | 2009-01-04 | 30 |
I can't figure out how to group the data correctly. Any ideas?
Thanks in advance.
SQL 2k5/2k8:
with cte_ranked as (
select *
, row_number() over (
partition by ContractId order by EvantDate desc) as [rank]
from [table])
select *
from cte_ranked
where [rank] = 1;
SQL 2k:
select t.*
from table as t
join (
select max(EventDate) as MaxDate
, ContractId
from table
group by ContractId) as mt
on t.ContractId = mt.ContractId
and t.EventDate = mt.MaxDate