I have a table with 2 columns date and sales, from this I need to pick up the dates on which sales have increased from previous date. Below is a sample table
Date Sales
-------------------
1/8/2020 10
1/9/2020 12
1/10/2020 8
1/11/2020 7
1/12/2020 13
Output should be as below:
Date
---------
1/9/2020
1/12/2020
Query:
Select data
from table
where sales > sales of previous day
You can use LAG to calculate this:
with cte
as (select date_c
, sales
, lag(sales) over (order by date_c) sales2
from Test)
select date_c, sales from cte
where sales > sales2;
Here is a DEMO
If you have gaps in days, you can consider this following logic with sub query-
DEMO HERE
WITH CTE AS
(
SELECT Date,Sales,
(
SELECT Sales
FROM your_table
WHERE Date = (SELECT MAX(Date) FROM your_table WHERE Date < A.Date)
) Last_day_sales
FROM your_table A
)
SELECT Date,Sales
FROM CTE
WHERE Sales > Last_day_sales*emphasized text*
You can use self join for this requirement.
select
A.date
from TableA as A
inner join TableA as B on B.date = (A.date - interval '1 day')
and A.sales > B.sales;
Related
I just want to generate the months between data range using SQL Query.
example
You can use a table generator:
select '2022-07-04'::date +
row_number() over(partition by 1 order by null) - 1 GENERATED_DATE
from table(generator(rowcount => 365))
;
Just change the start date and the number of days into the series. You can use the datediff function to calculate the number of days between the start end end dates.
Edit: I just realized the generator table function requires a constant for the number of rows. That's easily solvable. Just set a higher number of rows than you'll need and specify the end of the series in a qualify clause:
set startdate = (select '2022-04-15'::date);
set enddate = (select '2022-07-04'::date);
select $startdate::date +
row_number() over(partition by 1 order by null) - 1 GENERATED_DATE
from table(generator(rowcount => 100000))
qualify GENERATED_DATE <= $enddate
;
You can use a table generator in the CTE, and then select from the CTE and cartesian join to your table with data and use a case statement to see if the date in the generator is between your start and to dates.
Then select from it:
select user_id, x_date
from (
with dates as (
select '2019-01-01'::date + row_number() over(order by 0) x_date
from table(generator(rowcount => 1500))
)
select d.x_date, t.*,
case
when d.x_date between t.from_date and t.to_date then 'Y' else 'N' end target_date
from dates d, my_table t --deliberate cartesian join
)
where target_date = 'Y'
order by 1,2
Output:
USER_ID X_DATE
1 2/20/2019
1 2/21/2019
1 2/22/2019
1 2/23/2019
2 2/22/2019
2 2/23/2019
2 2/24/2019
2 2/25/2019
2 2/26/2019
2 2/27/2019
2 2/28/2019
3 3/1/2019
3 3/2/2019
3 3/3/2019
3 3/4/2019
3 3/5/2019
=======EDIT========
Based on your comments below, you are actually looking for something different than your original screenshots. Ok, so here we are still using the table generator, and then we're truncating the month to the first day of the month where the x-date is YES.
select distinct t.user_id, t.from_date, t.to_date, date_trunc('MONTH', z.x_date) as trunc_month
from (
with dates as (
select '2019-01-01'::date + row_number() over(order by 0) x_date
from table(generator(rowcount => 1500))
)
select d.x_date, t.*,
case
when d.x_date between t.from_date and t.to_date then 'Y' else 'N' end target_date
from dates d, my_table t
)z
join my_table t
on z.user_id = t.user_id
where z.target_date = 'Y'
order by 1,2
Output (modified User ID 3 to span 2 months):
USER_ID FROM_DATE TO_DATE TRUNC_MONTH
1 2/20/2019 2/23/2019 2/1/2019
2 2/22/2019 2/28/2019 2/1/2019
3 2/25/2019 3/5/2019 2/1/2019
3 2/25/2019 3/5/2019 3/1/2019
I have a transactions table for a single year with the amount indicating the debit transaction if the value is negative or credit transaction values are positive.
Now in a given month if the number of debit records is less than 3 or if the sum of debits for a month is less than 100 then I want to charge a fee of 5.
I want to build and sql query for this in postgre:
select sum(amount), count(1), date_part('month', date) as month from transactions where amount < 0 group by month;
I am able get records per month level, I am stuck on how to proceed further and get the result.
You can start by generating the series of month with generate_series(). Then join that with an aggregate query on transactions, and finally implement the business logic in the outer query:
select sum(t.balance)
- 5 * count(*) filter(where coalesce(t.cnt, 0) < 3 or coalesce(t.debit, 0) < 100) as balance
from generate_series(date '2020-01-01', date '2020-12-01', '1 month') as d(dt)
left join (
select date_trunc('month', date) as dt, count(*) cnt, sum(amount) as balance,
sum(-amount) filter(where amount < 0) as debit
from transactions t
group by date_trunc('month', date)
) t on t.dt = d.dt
Demo on DB Fiddle:
| balance |
| ------: |
| 2746 |
How about this approach?
SELECT
SUM(
CASE
WHEN usage.amount_s > 100
OR usage.event_c > 3
THEN 0
ELSE 5
END
) AS YEAR_FEE
FROM (SELECT 1 AS month UNION
SELECT 2 UNION
SELECT 3 UNION
SELECT 4 UNION
SELECT 5 UNION
SELECT 6 UNION
SELECT 7 UNION
SELECT 8 UNION
SELECT 9 UNION
SELECT 10 UNION
SELECT 11 UNION
SELECT 12
) months
LEFT OUTER JOIN
(
SELECT
sum(amount) AS amount_s,
count(1) event_c,
date_part('month', date) AS month
FROM transactions
WHERE amount < 0
GROUP BY month
) usage ON months.month = usage.month;
First you must use a resultset that returns all the months (1-12) and join it with a LEFT join to your table.
Then aggregate to get the the sum of each month's amount and with conditional aggregation subtract 5 from the months that meet your conditions.
Finally use SUM() window function to sum the result of each month:
SELECT DISTINCT SUM(
COALESCE(SUM(t.Amount), 0) -
CASE
WHEN SUM((t.Amount < 0)::int) < 3
OR SUM(CASE WHEN t.Amount < 0 THEN -t.Amount ELSE 0 END) < 100 THEN 5
ELSE 0
END
) OVER () total
FROM generate_series(1, 12, 1) m(month) LEFT JOIN transactions t
ON m.month = date_part('month', t.date) AND date_part('year', t.date) = 2020
GROUP BY m.month
See the demo.
Results:
> | total |
> | ----: |
> | 2746 |
I think you can use the hanving clause.
Select ( sum(a.total) - (12- count(b.cnt ))*5 ) as result From
(Select sum(amount) as total , 'A' as name from transactions ) as a left join
(Select count(amount) as cnt , 'A' as name
From transactions
where amount <0
group by month(date)
having not(count(amount) <3 or sum(amount) >-100) ) as b
on a.name = b.name
select
sum(amount) - 5*(12-(
select count(*)
from(select month, count(amount),sum(amount)
from transactions
where amount<0
group by month
having Count(amount)>=3 And Sum(amount)<=-100))) as balance
from transactions ;
I have searched the forum many times but couldn't find a solution for my situation. I am working with an Oracle database.
I have a table with all Order Numbers and Customer Numbers by Day. It looks like this:
Day | Customer Nbr | Order Nbr
2018-01-05 | 25687459 | 256
2018-01-09 | 36478592 | 398
2018-03-07 | 25687459 | 1547
and so on....
Now I need a SQL Query which gives me a table by day and Customer Nbr and counts the number of unique Order Numbers within the last 365 days starting from column 1.
For the example above the resulting table should look like:
Day | Customer Nbr | Order Cnt
2019-01-01 | 25687459 | 2
2019-01-02 | 25687459 | 2
...
2019-03-01 | 25687459 | 1
One method is to generate values for all days of interest for each customer and then use a correlated subquery:
with dates as (
select date '2019-01-01' + rownum as dte from dual
connect by date '2019-01-01' + rownum < sysdate
)
select d.dte, t.customer_nbr,
(select count(*)
from t t2
where t2.customer_nbr = t.customer_nbr and
t2.day <= t.dte and
t2.date > t.dte - 365
) as order_cnt
from dates d cross join
(select distinct customer_nbr from t) ;
Edit:
I've just seen you clarify the question, which I've interpreted to mean:
For every day in the last year, show how many orders there were for each customer between that date, and 1 year previously. Working on an answer now...
Updated Answer:
For each customer, we count the number of records between the order day, and 365 days before it...
WITH yourTable AS
(
SELECT SYSDATE - 1 Day, 'Alex' CustomerNbr FROM DUAL
UNION ALL
SELECT SYSDATE - 2, 'Alex' FROM DUAL
UNION ALL
SELECT SYSDATE - 366, 'Alex'FROM DUAL
UNION ALL
SELECT SYSDATE - 400, 'Alex'FROM DUAL
UNION ALL
SELECT SYSDATE - 500, 'Alex'FROM DUAL
UNION ALL
SELECT SYSDATE - 1, 'Joe'FROM DUAL
UNION ALL
SELECT SYSDATE - 300, 'Chris'FROM DUAL
UNION ALL
SELECT SYSDATE - 1, 'Chris'FROM DUAL
)
SELECT Day, CustomerNbr, OrdersLast365Days
FROM yourTable t
OUTER APPLY
(
SELECT COUNT(1) OrdersLast365Days
FROM yourTable t2
WHERE t.CustomerNbr = t2.CustomerNbr
AND TRUNC(t2.Day) >= TRUNC(t.Day) - 364
AND TRUNC(t2.Day) <= TRUNC(t.Day)
)
ORDER BY t.Day DESC, t.CustomerNbr;
If you want to report on just the days you have orders for, then a simple WHERE clause should be enough:
SELECT Day, CustomerNbr, COUNT(1) OrderCount
FROM <yourTable>
WHERE TRUNC(DAY) >= TRUNC(SYSDATE -364)
GROUP BY Day, CustomerNbr
ORDER BY Day Desc;
If you want to report on every day, you'll need to generate them first. This can be done by a recursive CTE, which you then join to your table:
WITH last365Days AS
(
SELECT TRUNC (SYSDATE - ROWNUM + 1) dt
FROM DUAL CONNECT BY ROWNUM < 365
)
SELECT d.Day, COALESCE(t.CustomerNbr, 'None') CustomerNbr, SUM(CASE WHEN t.CustomerNbr IS NULL THEN 0 ELSE 1 END) OrderCount
FROM last365Days d
LEFT OUTER JOIN <yourTable> t
ON d.Day = TRUNC(t.Day)
GROUP BY d.Day, t.CustomerNbr
ORDER BY d.Day Desc;
I would probably have done it with and analytic function. In your windowing clause, you can specify a number of rows before, or a range. In this case I will use a range.
This will give you, For Each customer for each day the number of orders during one rolling year before the date displayed
WITH DATES AS (
SELECT * FROM
(SELECT TRUNC(SYSDATE)-(LEVEL-1) AS DAY FROM DUAL CONNECT BY TRUNC(SYSDATE)-(LEVEL-1) >= ( SELECT MIN(TRUNC(DAY)) FROM MY_TABLE ))
CROSS JOIN
(SELECT DISTINCT CUST_ID FROM MY_TABLE))
SELECT DISTINCT
DATES.DAY,
DATES.CUST_ID,
COUNT(ORDER_ID) OVER (PARTITION BY DATES.CUST_ID ORDER BY DATES.DAY RANGE BETWEEN INTERVAL '1' YEAR PRECEDING AND INTERVAL '1' SECOND PRECEDING)
FROM
DATES
LEFT JOIN
MY_TABLE
ON DATES.DAY=TRUNC(MY_TABLE.DAY) AND DATES.CUST_ID=MY_TABLE.CUST_ID
ORDER BY DATES.CUST_ID,DATES.DAY;
I have a problem with writing a query.
Row data is as follow :
DATE CUSTOMER_ID AMOUNT
20170101 1 150
20170201 1 50
20170203 1 200
20170204 1 250
20170101 2 300
20170201 2 70
I want to know when(which date) the sum of amount for each customer_id becomes more than 350,
How can I write this query to have such a result ?
CUSTOMER_ID MAX_DATE
1 20170203
2 20170201
Thanks,
Simply use ANSI/ISO standard window functions to calculate the running sum:
select t.*
from (select t.*,
sum(t.amount) over (partition by t.customer_id order by t.date) as running_amount
from t
) t
where running_amount - amount < 350 and
running_amount >= 350;
If for some reason, your database doesn't support this functionality, you can use a correlated subquery:
select t.*
from (select t.*,
(select sum(t2.amount)
from t t2
where t2.customer_id = t.customer_id and
t2.date <= t.date
) as running_amount
from t
) t
where running_amount - amount < 350 and
running_amount >= 350;
ANSI SQL
Used for the test: TSQL and MS SQL Server 2012
select
"CUSTOMER_ID",
min("DATE")
FROM
(
select
"CUSTOMER_ID",
"DATE",
(
SELECT
sum(T02."AMOUNT") AMOUNT
FROM "TABLE01" T02
WHERE
T01."CUSTOMER_ID" = T02."CUSTOMER_ID"
AND T02."DATE" <= T01."DATE"
) "AMOUNT"
from "TABLE01" T01
) T03
where
T03."AMOUNT" > 350
group by
"CUSTOMER_ID"
GO
CUSTOMER_ID | (No column name)
----------: | :------------------
1 | 03/02/2017 00:00:00
2 | 01/02/2017 00:00:00
db<>fiddle here
DB-Fiddle
SELECT
tmp.`CUSTOMER_ID`,
MIN(tmp.`DATE`) as MAX_DATE
FROM
(
SELECT
`DATE`,
`CUSTOMER_ID`,
`AMOUNT`,
(
SELECT SUM(`AMOUNT`) FROM tbl t2 WHERE t2.`DATE` <= t1.`DATE` AND `CUSTOMER_ID` = t1.`CUSTOMER_ID`
) AS SUM_UP
FROM
`tbl` t1
ORDER BY
`DATE` ASC
) tmp
WHERE
tmp.`SUM_UP` > 350
GROUP BY
tmp.`CUSTOMER_ID`
Explaination:
First I select all rows and subselect all rows with SUM and ID where the current row DATE is smaller or same as all rows for the customer. From this tabe i select the MIN date, which has a current sum of >350
I think it is not an easy calculation and you have to calculate something. I know It could be seen a little mixed but i want to calculate step by step. As fist step if we can get success for your scenario, I believe it can be made better about performance. If anybody can make better my query please edit my post;
Unfortunately the solution that i cannot try on computer is below, I guess it will give you expected result;
-- Get the start date of customers
SELECT MIN(DATE) AS DATE
,CUSTOMER_ID
INTO #table
FROM TABLE t1
-- Calculate all possible date and where is sum of amount greater than 350
SELECT t1.CUSTOMER_ID
,SUM(SELECT Amount FROM TABLE t3 WHERE t3.DATE BETWEEN t1.DATE
AND t2.DATE) AS total
,t2.DATE AS DATE
INTO #tableCalculated
FROM #table t1
INNER JOIN TABLE t2 ON t.ID = t2.ID
AND t1.DATE != t2.DATE
WHERE total > 350
-- SELECT Min amount and date for per Customer_ID
SELECT CUSTOMER_ID, MIN(DATE) AS DATE
FROM #tableCalculated
GROUP BY ID
SELECT CUSTOMER_ID, MIN(DATE) AS GOALDATE
FROM ( SELECT cd1.*, (SELECT SUM(AMOUNT)
FROM CustData cd2
WHERE cd2.CUSTOMER_ID = cd1.CUSTOMER_ID
AND cd2.DATE <= cd1.DATE) AS RUNNINGTOTAL
FROM CustData cd1) AS custdata2
WHERE RUNNINGTOTAL >= 350
GROUP BY CUSTOMER_ID
DB Fiddle
I have monthly time series data in table where dates are as a last day of month. Some of the dates are missing in the data. I want to insert those dates and put zero value for other attributes.
Table is as follows:
id report_date price
1 2015-01-31 40
1 2015-02-28 56
1 2015-04-30 34
2 2014-05-31 45
2 2014-08-31 47
I want to convert this table to
id report_date price
1 2015-01-31 40
1 2015-02-28 56
1 2015-03-31 0
1 2015-04-30 34
2 2014-05-31 45
2 2014-06-30 0
2 2014-07-31 0
2 2014-08-31 47
Is there any way we can do this in Postgresql?
Currently we are doing this in Python. As our data is growing day by day and its not efficient to handle I/O just for one task.
Thank you
You can do this using generate_series() to generate the dates and then left join to bring in the values:
with m as (
select id, min(report_date) as minrd, max(report_date) as maxrd
from t
group by id
)
select m.id, m.report_date, coalesce(t.price, 0) as price
from (select m.*, generate_series(minrd, maxrd, interval '1' month) as report_date
from m
) m left join
t
on m.report_date = t.report_date;
EDIT:
Turns out that the above doesn't quite work, because adding months to the end of month doesn't keep the last day of the month.
This is easily fixed:
with t as (
select 1 as id, date '2012-01-31' as report_date, 10 as price union all
select 1 as id, date '2012-04-30', 20
), m as (
select id, min(report_date) - interval '1 day' as minrd, max(report_date) - interval '1 day' as maxrd
from t
group by id
)
select m.id, m.report_date, coalesce(t.price, 0) as price
from (select m.*, generate_series(minrd, maxrd, interval '1' month) + interval '1 day' as report_date
from m
) m left join
t
on m.report_date = t.report_date;
The first CTE is just to generate sample data.
This is a slight improvement over Gordon's query which fails to get the last date of a month in some cases.
Essentially you generate all the month end dates between the min and max date for each id (using generate_series) and left join on this generated table to show the missing dates with 0 price.
with minmax as (
select id, min(report_date) as mindt, max(report_date) as maxdt
from t
group by id
)
select m.id, m.report_date, coalesce(t.price, 0) as price
from (select *,
generate_series(date_trunc('MONTH',mindt+interval '1' day),
date_trunc('MONTH',maxdt+interval '1' day),
interval '1' month) - interval '1 day' as report_date
from minmax
) m
left join t on m.report_date = t.report_date
Sample Demo