how to aggregate the sells by date i want to know the total of sells for each day
|DATE | SELLS |
|2022-01-27 |48$ |
|2022-01-27 | 25$ |
|2022-01-27 | 150$ |
|2022-01-25 | 55$ |
no idea about the query
perhaps i should creat an other table which hold only total sells per day
Do a GROUP BY
select date, sum(sells)
from tablename
group by date
(No need for another table. Such copying of data too often leads to data inconsistency.)
Related
The column "activitie_time_enter" has the times.
The column "activitie_still" indicates the type of activity.
The column "activitie_walking" indicates the other type of activity.
Table example:
activitie_time_enter | activitie_still | activitie_walking
17:30:20 | Still |
17:31:32 | Still |
17:32:24 | | Walking
17:33:37 | | Walking
17:34:20 | Still |
17:35:37 | Still |
17:45:13 | Still |
17:50:23 | Still |
17:51:32 | | Walking
What I need is to sum up the total minutes for each activity separately.
Any suggestions or solution?
First calculate the duration for each activity (the with CTE) and then do conditional sum.
with t as
(
select
*, lead(activitie_time_enter) over (order by activitie_time_enter) - activitie_time_enter as duration
from _table
)
select
sum (duration) filter (where activitie_still = 'Still') as total_still,
sum (duration) filter (where activitie_walking = 'Walking') as total_walking
from t;
/** Result:
total_still|total_walking|
-----------+-------------+
00:19:16| 00:01:56|
*/
BTW do you really need two columns (activitie_still and activitie_walking)? Only one activity column with those values will do. This will allow more activities (Running, Sleeping, Working etc.) w/o having to change the table structure.
My goal is to join a sales program table to a calendar table so that there would be a joined table with the full trailing 52 weeks by day, and then the sales data would be joined to it. The idea would be that there are nulls I could COALESCE after the fact. However, my problem is that I only get results without nulls from my sales data table.
The questions I've consulted so far are:
Join to Calendar Table - 5 Business Days
Joining missing dates from calendar table Which points to
MySQL how to fill missing dates in range?
My Calendar table is all 364 days previous to today (today being day 0). And the sales data has a program field, a store field, and then a start date and an end date for the program.
Here's what I have coded:
SELECT
CAL.DATE,
CAL.DAY,
SALES.ITEM,
SALES.PROGRAM,
SALES.SALE_DT,
SALES.EFF_BGN_DT,
SALES.EFF_END_DT
FROM
CALENDAR_TABLE AS CAL
LEFT JOIN
SALES_TABLE AS SALES
ON CAL.DATE = SALES.SALE_DT
WHERE 1=1
and SALES.ITEM = 1 or SALES.ITEM is null
ORDER BY DATE ASC
What I expected was 365 records with dates where there were nulls and dates where there were filled in records. My query resulted in a few dates with null values but otherwise just the dates where a program exists.
DATE | ITEM | PROGRAM | SALE_DT | PRGM_BGN | PRGM_END |
----------|--------|---------|----------|-----------|-----------|
8/27/2020 | | | | | |
8/26/2020 | | | | | |
8/25/2020 | | | | | |
8/24/2020 | | | | | |
6/7/2020 | 1 | 5 | 6/7/2020 | 2/13/2016 | 6/7/2020 |
6/6/2020 | 1 | 5 | 6/6/2020 | 2/13/2016 | 6/7/2020 |
6/5/2020 | 1 | 5 | 6/5/2020 | 2/13/2016 | 6/7/2020 |
6/4/2020 | 1 | 5 | 6/4/2020 | 2/13/2016 | 6/7/2020 |
Date = Calendar day.
Item = Item number being sold.
Program = Unique numeric ID of program.
Sale_Dt = Field populated if at least one item was sold under this program.
Prgm_bgn = First day when item was eligible to be sold under this program.
Prgm_end = Last day when item was eligible to be sold under this program.
What I would have expected would have been records between June 7 and August 24 which just had the DATE column populated for each day and null values as what happens in the most recent four records.
I'm trying to understand why a calendar table and what I've written are not providing the in-between dates.
EDIT: I've removed the request for feedback to shorten the question as well as an example I don't think added value. But please continue to give feedback as you see necessary.
I'd be more than happy to delete this whole question or have someone else give a better answer, but after staring at the logic in some of the answers in this thread (MySQL how to fill missing dates in range?) long enough, I came up with this:
SELECT
CAL.DATE,
t.* EXCEPT (DATE)
FROM
CALENDER_TABLE AS CAL
LEFT JOIN
(SELECT
CAL.DATE,
CAL.DAY,
SALES.ITEM,
SALES.PROGRAM,
SALES.SALE_DT,
SALES.EFF_BGN_DT,
SALES.EFF_END_DT
FROM
CALENDAR_TABLE AS CAL
LEFT JOIN
SALES_TABLE AS SALES
ON CAL.DATE = SALES.SALE_DT
WHERE 1=1
and SALES.ITEM = 1 or SALES.ITEM is null
ORDER BY DATE ASC) **t**
ON CAL.DATE = t.DATE
From what I can tell, it seems to be what I needed. It allows for the subquery to connect a date to all those records, then just joins on the calendar table again solely on date to allow for those nulls to be created.
We have a Microsoft Access Database at work to track an ongoing list of customers. Each customer has to sign a contract with several departments - totally 13 (!) departments - for which we want to keep track about the current progress for each customer when a contract is sent and received. This structure looks similar to something like this:
Table 1
-------------------------------------------------------------------------------------------------------------------
CUSTOMER_ID | ... | DEP_A_SENT | DEP_A_RECEIVED | DEP_B_SENT | DEP_B_RECEIVED | DEP_C_SENT | DEP_C_RECEIVED | ... |
-------------------------------------------------------------------------------------------------------------------
1 | ... | 2015-05-01 | 2015-05-03 | 2015-05-04 | 2015-05-09 | 2015-05-01 | 2015-05-05 | ... |
2 | ... | 2015-05-01 | 2015-05-05 | 2015-05-01 | 2015-05-03 | 2015-05-13 | --- | ... |
...
I want to be able to calculate the timespan between DEP_X_SENT with DEP_X_RECEIVED for customer and department (such as "department A: 2 days, department B: 5 days..." for customer ID 1)
More importantly, I want to compare all the DEP_X_RECEIVED dates with each other for one customer: Determining the first (MIN) and the last (MAX) date a contract has been received to finding how many days it takes for each customer until all contracts are received. (such as "the contracts were received within 6 days" for customer ID 1, because the first was received on May 3rd. and the last on May 9th). Furthermore, I want to calculate the average timespan this took for all customers. If the contract is not received yet, the is no value in that field.
In MySQL I can work with functions such GREATEST and LEAST to compare values between different columns, but in Access I have to rely for now on VBA and I think it is considered bad practice. How can I normalize and restructure my table for archieving my goals with rather simple MAX, MIN and AVGoperations? Many thanks!
Simply fold your existing table into this structure:
create table TABLE_1 (
CUSTOMER_ID int,
DEPARTMENT_ID int, -- foreign key reference to DEPARTMENT table
SENT date,
RECEIVED date
);
Now you can perform the required analysis simply, and retrieve the original layout as either a Pivot report or LEFT OUTER JOIN from the DEPARTMENT table to the new TABLE_1.
I want to combine two tables into one:
The first table: Payments
id | 2010_01 | 2010_02 | 2010_03
1 | 3.000 | 500 | 0
2 | 1.000 | 800 | 0
3 | 200 | 2.000 | 300
4 | 700 | 1.000 | 100
The second table is ID and some date (different for every ID)
id | date |
1 | 2010-02-28 |
2 | 2010-03-01 |
3 | 2010-01-31 |
4 | 2011-02-11 |
What I'm trying to achieve is to create table which contains all payments before the date in ID table to create something like this:
id | date | T_00 | T_01 | T_02
1 | 2010-02-28 | 500 | 3.000 |
2 | 2010-03-01 | 0 | 800 | 1.000
3 | 2010-01-31 | 200 | |
4 | 2010-02-11 | 1.000 | 700 |
Where T_00 means payment in the same month as 'date' value, T_01 payment in previous month and so on.
Is there a way to do this?
EDIT:
I'm trying to achieve this in MS Access.
The problem is that I cannot connect name of the first table's column with the date in the second (the easiest way would be to treat it as variable)
I added T_00 to T_24 columns in the second (ID) table and was trying to UPDATE those fields
set T_00 =
iif(year(date)&"_"&month(date)=2010_10,
but I realized that that would be to much code for access to handle if I wanted to do this for every payment period and every T_xx column.
Even if I would write the code for T_00 I would have to repeat it for next 23 periods.
Your Payments table is de-normalized. Those date columns are repeating groups, meaning you've violated First Normal Form (1NF). It's especially difficult because your field names are actually data. As you've found, repeating groups are a complete pain in the ass when you want to relate the table to something else. This is why 1NF is so important, but knowing that doesn't solve your problem.
You can normalize your data by creating a view that UNIONs your Payments table.
Like so:
CREATE VIEW NormalizedPayments (id, Year, Month, Amount) AS
SELECT id,
2010 AS Year,
1 AS Month,
2010_01 AS Amount
FROM Payments
UNION ALL
SELECT id,
2010 AS Year,
2 AS Month,
2010_02 AS Amount
FROM Payments
UNION ALL
SELECT id,
2010 AS Year,
3 AS Month,
2010_03 AS Amount
FROM Payments
And so on if you have more. This is how the Payments table should have been designed in the first place.
It may be easier to use a date field with the value '2010-01-01' instead of a Year and Month field. It depends on your data. You may also want to add WHERE Amount IS NOT NULL to each query in the UNION, or you might want to use Nz(2010_01,0.000) AS Amount. Again, it depends on your data and other queries.
It's hard for me to understand how you're joining from here, particularly how the id fields relate because I don't see how they do with the small amount of data provided, so I'll provide some general ideas for what to do next.
Next you can join your second table with this normalized Payments table using a method similar to this or a method similar to this. To actually produce the result you want, include a calculated field in this view with the difference in months. Then, create an actual Pivot Table to format your results (like this or like this) which is the proper way to display data like your tables do.
I do quite a bit of data analysis and use SQL on a daily basis but my queries are rather simple, usually pulling a lot of data which I thereafter manipulate in excel, where I'm a lot more experienced.
This time though I'm trying to generate some Live Charts which have as input a single SQL query. I will now have to create complex tables without the aid of the excel tools I'm so familiar with.
The problem is the following:
We have telesales agents that book appointments by answering to inbound calls and making outbound cals. These will generate leads that might potentially result in a sale. The relevant tables and fields for this problem are these:
Contact Table
Agent
Sales Table
Price
OutboundCallDate
I want to know for each telesales agent their respective Total Sales amount in one column, and their outbound sales value in another.
The end result should look something like this:
+-------+------------+---------------+
| Agent | TotalSales | OutboundSales |
+-------+------------+---------------+
| Tom | 30145 | 0 |
| Sally | 16449 | 1000 |
| John | 10500 | 300 |
| Joe | 50710 | 0 |
+-------+------------+---------------+
With the below SQL I get the following result:
SELECT contact.agent, SUM(sales.price)
FROM contact, sales
WHERE contact.id = sales.id
GROUP BY contact.agent
+-------+------------+
| Agent | TotalSales |
+-------+------------+
| Tom | 30145 |
| Sally | 16449 |
| John | 10500 |
| Joe | 50710 |
+-------+------------+
I want to add the third column to this query result, in which the price is summed only for records where the OutboundCallDate field contains data. Something a bit like (where sales.OutboundCallDate is Not Null)
I hope this is clear enough. Let me know if that's not the case.
Use CASE
SELECT c.Agent,
SUM(s.price) AS TotalSales,
SUM(CASE
WHEN s.OutboundCallDate IS NOT NULL THEN s.price
ELSE 0
END) AS OutboundSales
FROM contact c, sales s
WHERE c.id = s.id
GROUP BY c.agent
I think the code would look
SELECT contact.agent, SUM(sales.price)
FROM contact, sales
WHERE contact.id = sales.id AND SUM(WHERE sales.OutboundCallDate)
GROUP BY contact.agent
notI'm assuming your Sales table contains something like Units and Price. If it's just a sales amount, then replace the calculation with the sales amount field name.
The key thing here is that the value summed should only be the sales amount if the OutboundCallDate exists. If the OutboundCallDate is not NULL, then we're using a value of 0 for that row.
select Agent.Agent, TotalSales = sum (sales.Price*Units)
, OutboundSales = sum (
case when Outboundcalldate is not null then price*Units
else 0
end)
From Sales inner join Agent on Sales.Agent = Agent.Agent
Group by Agent.Agent