first ,i need to get the sum of TotalPrice of sport's and music's departments from the first 3 months of 2016,second, i need to get the result of what i wrote before dividing to sum of all TotalPrice at the year of 2016 from all departments, and third- i need to get the first result dividing to sum of all Total price from all over the years.
all this at the same query!
thanks!
the table called Sales and the attributes are: S_id, date, department, totalPrice.
THIS IS MY CHRY :
Select sum(TotalPrice) as sportMusic, sportMusic/sum(TotalPrice)
From Sales
Where (Department="MUSIC" OR Department="SPORT") and
DATE BETWEEN "2016/01/01" AND "2016/03/31"
You can use your query and two more queries as subqueries (also called "derived tables") in your from clause. Cross join the three result rows and use the totals in your select clause. Something along the lines of:
select
ms_2016_q1.total as ms_2016_q1_total,
ms_2016_q1.total / all_2016.total as rate_2016,
ms_2016_q1.total / all_years.total as rate_all
from
(
select sum(totalprice) as total
from sales
where department in ('MUSIC', 'SPORT')
and date between date '2016-01-01' and date '2016-03-31'
) ms_2016_q1
cross join
(
select sum(totalprice) as total
from sales
where date between date '2016-01-01' and date '2016-12-31'
) all_2016
cross join
(
select sum(totalprice) as total
from sales
) all_years;
Related
I'm having great difficulty writing this query and cannot find any answers online which could be applied to my problem.
I have a couple of tables which looks similar to the below with. Each purchase date corresponds with an item purchased.
Cust_ID
Purchase_Date
123
08/01/2022
123
08/20/2022
123
09/05/2022
123
10/08/2022
123
12/25/2022
123
01/26/2023
The result I am looking for should contain the customers ID, a range of the purchases, the number of consecutive months they had made a purchase (regardless of which day they purchased), and a count of how many purchases they had made in the time frame. The result should look something like the below for my example.
Cust_ID
Min Purchase Date
Max Purchase Date
Consecutive Months
No. Items Purchased
123
08/01/2022
10/08/2022
3
4
123
12/25/2022
01/26/2023
2
2
I have tried using CTEs with querys similar to
WITH CTE as
(
SELECT
PaymentDate PD,
CustomerID CustID,
DATEADD(m, -ROW_NUMBER() OVER (PARTITION BY c.CustomerID ORDER BY
DATEPART(m,PaymentDate)), PaymentDate) as TempCol1,
FROM customers as c
LEFT JOIN payments as p on c.customerid = p.customerid
GROUP BY c.CustomerID, p.PaymentDate
)
SELECT
CustID,
MIN(PD) AS MinPaymentDate,
MAX(PD) AS MaxPaymentDate,
COUNT(*) as ConsecutiveMonths,
FROM CTE
GROUP BY CustID, TempCol1
However, the above failed to properly count consecutive months. When the payment dates matched a month apart (e.g. 1/1/22 - 2/1/22), the query properly counts the consecutive months. However, if the dates do not match from month to month (e.g. 1/5/22 - 2/15/22), the count breaks.
Any guidance/help would be much appreciated!
This is just a small enhancement on the answer already given by ahmed. If your date range for this query is more than a year, then year(M.Purchase_Date) + month(M.Purchase_Date) will be 2024 for both 2022-02-01 and 2023-01-01 as YEAR() and MONTH() both return integer values. This will return incorrect count of consecutive months. You can change this to use CONCAT() or FORMAT(). Also, the COUNT(*) for ItemsPurchased should be counting the right hand side of the join, as it is a LEFT JOIN.
WITH consecutive_months AS
(
SELECT *,
DATEADD(
month,
-DENSE_RANK() OVER (
PARTITION BY CustomerID
ORDER BY YEAR(PaymentDate), MONTH(PaymentDate)
),
PaymentDate
) AS grp_date
FROM payments
)
SELECT
C.CustomerID AS CustID,
MIN(M.PaymentDate) AS MinPaymentDate,
MAX(M.PaymentDate) AS MaxPaymentDate,
COUNT(DISTINCT FORMAT(M.PaymentDate, 'yyyyMM')) AS ConsecutiveMonths,
COUNT(M.CustomerID) AS ItemsPurchased
FROM customers C
LEFT JOIN consecutive_months M
ON C.CustomerID = M.CustomerID
GROUP BY C.CustomerID, YEAR(M.grp_date), MONTH(M.grp_date)
Here's a db<>fiddle
You need to use the dense_rank function instead of the row_number, this will give the same rank for the same months and avoid breaking the grouping column. Also, you need to aggregate for 'year-month' of the grouping date column.
with consecutive_months as
(
select *,
Purchase_Date - interval
dense_rank() over (partition by Cust_ID order by year(Purchase_Date), month(Purchase_Date))
month as grp_date
from payments
)
select C.Cust_ID,
min(M.Purchase_Date) as MinPurchaseDate,
max(M.Purchase_Date) as MaxPurchaseDate,
count(distinct year(M.Purchase_Date), month(M.Purchase_Date)) as ConsecutiveMonthsNo,
count(M.Cust_ID) as ItemsPurchased
from customers C left join consecutive_months M
on C.Cust_ID = M.Cust_ID
group by C.Cust_ID, year(M.grp_date), month(M.grp_date)
See demo on MySQL
You tagged your question with MySQL, while it seems that you posted an SQL Server query syntax, for SQL Server just use dateadd(month, -dense_rank() over (partition by Cust_ID order by year(Purchase_Date), month(Purchase_Date)), Purchase_Date).
See demo on SQL Server.
How do I query the following:
For each customer, product and month, count the number of sales transactions that were between the previous and the following month's average sales quantities. For January and December, display NULL or 0.
Can only use: 5 aggregate functions (sum, count, avg, max & min)
This is the table reference:
create table sales
(
cust varchar(20),
prod varchar(20),
day integer,
month integer,
year integer,
state char(2),
quant integer,
date date
);
Schema:
Example of my Desired Result
I am stuck with the following codes. I'm having a hard time how to execute it.
SELECT cust, prod, month, COUNT(*) AS SALES_COUNT_BETWEEN_AVGS
FROM sales
I use MySQL. Please guide me thank you.
Maybe try a query like below
the first part is to calculate averages using group by
second part is to use to those averages in a JOIN twice for past month and future month
third part is WHERE clause in which we compare data. Note we have used greatest and least functions to determine min and max between two values from past and next month
Query
WITH T AS
(SELECT cust, prod, month, AVG(quant) AS avg_quantity
FROM sales
group by cust, prod, month
)
SELECT S.cust, S.prod, S.month, COUNT(1) AS Sales_count
FROM sales S
LEFT JOIN T T1
ON T1.cust=S.Cust AND
T1.prod=S.Prod AND
T1.Month=S.Month-1
LEFT JOIN T T2
ON T2.cust=S.Cust AND
T2.prod=S.Prod AND
T2.Month=S.Month+1
WHERE S.quant BETWEEN IFNULL(LEAST(T1.avg_quantity,T2.avg_quantity),0) AND IFNULL(GREATEST(T1.avg_quantity,T2.avg_quantity),0)
I have 2 tables
1st: order
columns: id, date, price
2nd: paypal
columns: id, posted_date, amount
the columns date and posted_date contains the full date & time details; day/month/year hrs:minute:seconds
I need to get the data by grouping by the day from the both tables
order.date (day by day)
count all orders from order table for each day
sum of all price records from order table for each day
sum of all amount records from the another table paypal table for the same days
I can't imagine if I should use join, union, union all, or just merge by comma
SELECT DATE(O.`dater`) AS Dates,
COUNT(O.orders) AS Order_count,
SUM(O.price) as Total_Price,
(SELECT SUM(amount) FROM paypal WHERE DATE(O.`dater`)=`posted_date`) AS Total_Amount
FROM orders O
GROUP BY DATE(O.`dater`)
Note:(I have used column dater instead of column date)
Hope this helps.
This one working for me :)
SELECT DATE(O.`date`) AS Dates,
COUNT(O.order) AS Order_count,
SUM(O.price) as Total_Price,
(SELECT SUM(amount) FROM paypal WHERE DATE(O.`date`)=`posted_date`) AS Total_Amount
FROM order O
GROUP BY DATE(O.`date`)
How to optimize the below query:
I have two tables, 'calendar_table' and 'consumption', Here I use this query to calculate monthly consumption for each year.
The calendar table has day, month and year for years 2005 - 2009 and consumption table has billed consumption data for monthly bill cycle. This query will count the number of days for each bill and use that the find the consumption for each month.
SELECT id,
date_from as bill_start_date,
theYear as Year,
MONTHNAME(STR_TO_DATE(theMonth, '%m')) as month,
sum(DaysOnBill),
TotalDaysInTheMonth,
sum(perDayConsumption * DaysOnBill) as EstimatedConsumption
FROM
(
SELECT
id,
date_from,
theYear,
theMonth, # use theMonth for displaying the month as a number
COUNT(*) AS DaysOnBill,
TotalDaysInTheMonth,
perDayConsumption
FROM
(
SELECT
c.id,
c.date_from as date_from,
ct.dt,
y AS theYear,
month AS theMonth,
DAY(LAST_DAY(ct.dt)) as TotalDaysInTheMonth,
perDayConsumption
FROM
consumption AS c
INNER JOIN
calendar_table AS ct
ON ct.dt >= c.date_from
AND ct.dt<= c.date_to
) AS allDates
GROUP BY
id,
date_from,
theYear,
theMonth ) AS estimates
GROUP BY
id,
theYear,
theMonth;
It is taking around 1000 seconds to go through around 1 million records. Can something be done to make it faster?.
The query is a bit dubious pretending to do one grouping first and then building on that with another, which actually isn't the case.
First the bill gets joined with all its days. Then we group by bill plus month and year thus getting a monthly view on the data. This could be done in one pass, but the query is joining first and then using the result as a derived table which gets aggregated. At last the results are taken again and "another" group is built, which is actually the same as before (bill plus month and year) and some pseudo aggregations are done (e.g. sum(perDayConsumption * DaysOnBill) which is the same as perDayConsumption * DaysOnBill, as SUM sums one record only here).
This can simply written as:
SELECT
c.id,
c.date_from as bill_start_date,
ct.y AS Year,
MONTHNAME(STR_TO_DATE(ct.month, '%m')) as month,
COUNT(*) AS DaysOnBill,
DAY(LAST_DAY(ct.dt)) as TotalDaysInTheMonth,
SUM(c.perDayConsumption) as EstimatedConsumption
FROM consumption AS c
INNER JOIN calendar_table AS ct ON ct.dt BETWEEN c.date_from AND c.date_to
GROUP BY
c.id,
ct.y,
ct.month;
I don't know if this will be faster or if MySQL's optimizer doesn't see through your query itself and boils it down to this anyhow.
Here my table is having filed as following:
employee_id,
expense_id,
expense_type,
expense_cost,
expense_date and etc,
And i want to display as month wise expenses as row wise for particular employee.
in my table data has stored like
2wheeler 01/03/2014 99 Santhosh 4493.00 March 500.00
Auto 03/02/2014 99 Santhosh 0.00 February 80.00
Food 01/02/2014 99 Santhosh 0.00 February 200.00
Phone Expense 01/03/2014 99 Santhosh 0.00 March 500.00
In this table i want to get out as
single user row with concat of expense type and sum of cost for every month that mean : march have single row with concat of expense type & sum of cost.
I would suggest doing a sub query that sums up all the occurances of an expenses per employee per month per expense. Then use that as a source to get the list of employees, months and the GROUP_CONCATed list of expense types and the total cost of them.
Like this:-
SELECT employee_id, expense_month, GROUP_CONCAT(CONCAT_WS('=', expense_type, monthly_exployee_expense))
FROM
(
SELECT employee_id, MONTH(expense_date) AS expense_month, expense_type, SUM(expense_cost) AS monthly_exployee_expense
FROM some_table
GROUP BY employee_id, expense_month, expense_type
) Sub1
GROUP BY employee_id, expense_month
EDIT
Reading you comment it seems that you need an expense listed even when an employee has not incurred that expense that month.
To do that I think you will need to cross join the employees (I have assumed a table name of tbl_employee) with the table of expenses types, and also all the possible months (assuming you want a row for a month for an employee when that employee has had no expenses that month). I have got the possible months by just selecting the distinct year / month from the table listing all the expenses (but there are other ways to get this - depends if there are any months where no employees had any expenses and if you want to put these out anyway).
Once those are cross joined to get every combination of employee, month and expense you can left join the actual expenses in the sub query, and then do the GROUP_CONCAT much as before.
Not tested, but something like this:-
SELECT employee_id, expense_month, GROUP_CONCAT(CONCAT_WS('=', exp_type_text, monthly_exployee_expense))
FROM
(
SELECT tbl_employee.employee_id, expense_months.expense_month, tbl_expense_type.exp_type_id, tbl_expense_type.exp_type_text, SUM(expense_cost) AS monthly_exployee_expense
FROM tbl_employee
CROSS JOIN tbl_expense_type
CROSS JOIN
(
SELECT DISTINCT DATE_FORMAT(expense_date, '%Y%m') AS expense_month
FROM some_table
) expense_months
LEFT OUTER JOIN some_table
ON tbl_employee.employee_id = some_table.employee_id
AND tbl_expense_type.exp_type_id = some_table.expense_type
AND expense_months.expense_month = DATE_FORMAT(some_table.expense_date, '%Y%m')
GROUP BY tbl_employee.employee_id, expense_months.expense_month, tbl_expense_type.exp_type_id, tbl_expense_type.exp_type_text
) Sub1
GROUP BY employee_id, expense_month