I have a table set up like this:
Description Jan | Feb | Mar | Apr .....
Volume
Days in Month
Gal/Day Average
I would like to be able to divide the volume for each month by the Days (and multiply by 100) to fill in the gal/day average row for each month.
The farthest I've gotten code wise is:
Update Table
set [Jan] = ?
where Description = 'Gal/Day Average'
Not a very good data format, but you could do:
Update toupdate
set [Jan] = volume.jan / dim.jan
from table toupdate cross join
table volume cross join
table dim
where toupdate.description = 'Gal/Day Average' and
volume.description = 'Volume' and
dim.description = 'Days In Month';
A much better data format would have the columns:
month
(possibly year)
volume
daysinmonth
average
Related
I am struggling with the time in order_date column. I deleted the time from date format (order_date) but THE SUM doesn't calculate the result. Let's say that we have 3 orders (20$, 15$,10$) in 1st Jul 2022 and it doesn't show the result 45$. It shows 3 line for 1st July 2022.I suspected that time influenced the solution which I would like to achieve.
PS I set the data for discount number is 1 - function WHERE
SELECT
TO_CHAR(ORDER_DATE, 'DD/MM/YYYY'),
SUM(order_total) as total
FROM
oe.orders
WHERE promotion_id = 1
GROUP BY order_date;
I cut the time in date column (order_date) and I can't move on.
2ND QUESTION
If I would like to add the second discount (WHERE promotion_id = 1 or promotion_id = 2) and after I need to sum up the amount for separate discounts (promotion_id = 1 & 2). How could I calculate this?
Could you use the trunc function to remove the time part of the order_date column before grouping the records by date?
Like:
SELECT
TRUNC(order_date) AS order_date,
SUM(order_total) as total
FROM
oe.orders
WHERE promotion_id = 1
GROUP BY TRUNC(order_date);
I have a dataset of 2 columns: 'Date' and 'Total Sales'. My dates are 01-01-2021, 02-01-2021... so on and so forth up until 12-01-2022. I basically want to add another row where I have a "previous month" column that gives me the total sales for the previous month in the same row as the current month (else null) -- e.g. say I have 2 rows in my date column 01-01-2021 and 02-01-2021 and total sales would be $10 and $20 respectively. How do can I create a column that would show the following:
Date |Sales | Previous Month Sales|
---------------------------------------------
01-01-2021 | $10 | null
02-01-2021 | $20 | $10
So on and so forth; this is my query:
CASE
WHEN `Date` > DATE_SUB(`Date`, INTERVAL 1 MONTH)
THEN `Monthly Sales`
ELSE 'null'
END
Thanks in advance
Well, Domo's back-end is running a MySQL back-engine (from what I recall the last time I touched Domo [2018])
I think this is just a SQL question, and I wonder if a simple windowing function would do the trick.
select Date,
Sales,
max (case when *month* = *this month -1* then Sales else null end) over (order by 1) as "Previous Month Sales"
from table
You just need to figure out how to break down the Date into the month based on whatever SQL dialect Domo uses nowadays.
Cheers
I think domo support MySQL-like language, so you could do something like this:
with cte as
(
select date,
date + interval 1 month as next_month,
sales
from sales
)
select a.date,
a.sales as current_sales,
b.sales as prior_month_sales
from sales a
left join cte b
on b.next_month = a.date
order by a.date
I do this by joining the table onto itself with a LEFT OUTER JOIN. The outer join allows you to keep the null value for previous month. You match the date such that 1 column is calculated to show the previous month (I do this with EOMONTH() to ensure I always get the previous month and account for the year, if say it is January).
IF OBJECT_ID('TEMPDB..#TEMP') IS NOT NULL
DROP TABLE #TEMP
CREATE TABLE #TEMP(
[Date] DATE
,[Sales] INT
)
INSERT INTO #TEMP([Date],[Sales])
VALUES ('2020-12-20',50)
,('2021-01-20',100)
,('2021-02-20',200)
,('2021-03-20',300)
,('2021-04-20',400)
,('2021-05-20',500)
SELECT #TEMP.[Date]
,#TEMP.Sales
,TEMPII.Date [PREV M]
,TEMPII.Sales [PREV M SALES]
FROM #TEMP
LEFT OUTER JOIN #TEMP TEMPII
ON YEAR(EOMONTH(#TEMP.[Date],-1))*100+MONTH(EOMONTH(#TEMP.[Date],-1)) = YEAR(TEMPII.[Date])*100+MONTH(TEMPII.[Date])
ORDER BY #TEMP.[Date]
Output:
So let's say I have a table like this:
subscriber_id
package_id
package_start_date
package_end_date
package_price_per_day
1081
231
2014-01-13
2014-12-31
$3.
1084
231
2014-03-21
2014-06-05
$3
1086
235
2014-06-21
2014-09-09
$4
Now I want the result for top 3 packages based on total revenue for each month for year 2014.
Note: For example for package 231 Revenue should be calculated such as 18 days of Jan * $3 +
28 days of feb * $3 + .... and so on.
For the second row the calculation would be same as first row (9 days of March* $3 + 30 days of April *$3 ....)
On the result the package should group by according to month and show rank depending on total revenue.
Sample result:
Month
Package_id
Revenue
Rank
Jan
231.
69499
1.
Jan.
235.
34345.
2.
Jan.
238.
23455.
3.
Feb.
231.
89274
1.
I wrote a query to filter the dates so that I get the active subscriber throughout the year 2014 (since initially there were values from different years),which shows the first table in the question, but I am not sure how do I break the months and days afterwards.
select subscriber_id, package_id, package_start_date, package_end_date
from (
select subscriber_id, package_id
, case when year(package_start_date) < '2014' then package_start_date = '01-Jan-2014' else package_start_date end as package_start_date
, case when year(package_start_date) > '2014' then package_end_date = '31-Dec-2014' else package_start_date end as package_end_date
, price_per_day
from subscription
) a
where year(package_start_date) = '2014' and year(package_end_date) = '2014'
Please do not emphasize on syntax - I am just trying to understand the logical approach in SQL.
Suppose you have a table that is a list of unique dates in a column called d, and the table is called d
It is then relatively trivial to do
SELECT *
FROM t
INNER JOIN d on d.d >= t.package_start_date AND d.d < t.package_end_date
Assuming you class a start date of jan 1 and an end date of jan 2 as 1 day. If you class as two, use <=
This will cause your package rows to multiply into the number of days, so start and end days of jan 1 and jan 11 would mean that row repeats 10 times. The d.d date is different on every row and you can extract the month from d.d and then group on it to give you totals for each month per package
Suppose you've CTEd that query above as x, it's like
SELECT DATEPART(month, x.dd), --the d.d date
package_id,
SUM(revenue)
FROM x
GROUP BY DATEPART(month, x.dd), package_id
Because the rows from T are repeated by Cartesian explosion when joined to d, you can safely group them or aggregate them to get them back to single values per month per package. If you have packages that stay with you more than a year you should also group on datepart year, to avoid mixing up the months from packages that stay from eg jan 2020 to feb 2021(they stay for two jans and two febs)
Then all you need to do is add the ranking of the revenue in, which looks like it would go in at the first step with something like
RANK(DATEDIFF(DAY, start, end)*revenue) OVER(PARTITION BY package_id)
I think I understand it correctly that you rank packages on total revenue over the entire period rather than per month.. look up the difference between rank and dense rank too as you may want dense instead
I am trying to figure out if an event occurred in the three consecutive previous years by month. For example:
Item Type Month Year
Hat S May 2015
Shirt P June 2015
Hat S June 2015
Hat S May 2016
Shirt P May 2016
Hat S May 2017
I am interested in seeing what item was purchased/sold for three consecutive years in the same month. Hat was sold in May in 2015, 2016, and 2017; therefore, I would like to identify that. Shirt was purchased in June 2015 and May 2016. Since this is different months in consecutive years, it does not qualify.
Essentially, I want it to be able to look back 3 years and identify those purchases/sales that reoccurred in the same month each year, preferably with an indicator variable.
I tried the following code:
select distinct a.*
from dataset as a inner join dataset as b
on a.type = b.type
and a.month = b.month
and a.item = b.item
and a.year = b.year-1
and a.year = b.year-2;
I want to get:
Item Type Month Year
Hat S May 2015
Hat S May 2016
Hat S May 2017
I guess I should add that my data is longer than 2015-2017. It spans 10 years, but I want to see if there are any 3 consecutive years (or more) within that 10 year span.
There are many ways to do this, however, one way in SQL, with the key understanding that rows can be grouped by Item and Month, is to restrict Year to the three years between 2015 and 2017. In order to qualify for 3 consecutive the count of the distinct values of year within the group should be 3. Such criteria will handle data with repetition, such as a group with 3 S-type Hats and 3 P-type Hats.
select item, type, month, year
from have
where year between 2015 and 2017
group by item, month
having count(distinct year) = 3
order by item, type, month, year
For the more generic problem of identifying runs within a group, SAS Data step is very suited and powerful. The serial DOW loop technique loops first over a range of rows based on some condition, whilst computing a group metric -- in this case, consecutive year runlength. A second loops over the same rows and utilizes the group metric within.
Consider this example in which the rungroup is computed based on year adjacency of item/month. Once the rungroups are established, the double DOW technique is applied.
data have;
do comboid = 1 to 1000;
itemid = ceil(10 * ranuni(123));
typeid = ceil(2* ranuni(123));
month = ceil(12 * ranuni(123));
year = 2009 + floor (10 * ranuni(123));
output;
end;
run;
proc sort data=have;
by itemid month year;
run;
data have_rungrouped;
set have;
by itemid month year;
rungroup + (first.month or not first.month and year - lag(year) > 1);
run;
data want;
do index = 1 by 1 until (last.rungroup);
set have_rungrouped;
by rungroup;
* distinct number of years in rungroup;
years_runlength = sum (years_runlength, first.rungroup or year ne lag(year));
end;
do index = 1 to index;
set have_rungrouped;
if years_runlength >= 3 then output;
end;
run;
Here is an example that would check if any item happened in consecutive years and list all from original table that qualify for at least two consecutive years:
DECLARE #table TABLE
(
Item NVARCHAR(MAX),
Type CHAR,
Month NVARCHAR(MAX),
Year INT
)
INSERT INTO #table VALUES
('Hat','S','May','2015'),
('Shirt','P','June','2015'),
('Hat','S','June','2015'),
('Hat','S','May','2016'),
('Shirt','P','May','2016'),
('Hat','S','May','2017')
SELECT * FROM #table
WHERE CONCAT(Item,Month) IN
(
SELECT CONCAT(group1.Item, group1.Month) FROM
(
SELECT Item,Year,Month FROM #table
GROUP BY Year, Item, Month
) group1
FULL OUTER JOIN
(
SELECT Item,Year,Month FROM #table
GROUP BY Year, Item, Month
) group2
ON group1.Year = group2.Year + 1 AND group1.Item = group2.Item AND group1.Month = group2.Month
WHERE group1.Item IS NOT NULL AND group2.Item IS NOT NULL
)
ORDER BY Item,Month,Year
As you can see I found all items that matched year + 1 in the same month.
OUTPUT:
Hat S May 2015
Hat S May 2016
Hat S May 2017
I have a question.
I am trying to find if there is an increment or decrement of sales by comparing the sales of 4 months.
How do we do this in sql.
Months Sales
---- -----
jan 30
feb 10
mar 60
april 20
april 20
Try to make query like below :
SELECT MonthId,
CASE WHEN Sales < (SELECT Sales FROM TestTable WHERE MonthId = TT.MonthId - 1) THEN 'Decremented' ELSE 'Incremented' END
FROM TestTable TT
where you should have int value in MonthId column, otherwise you need to create function which returns int value for passed month name or use case structure.