I have the following table in SQL:
Start - End - Amount **per day**
06.07.2020 10.07.2020 10
08.07.2020 08.07.2020 5
08.07.2020 15.07.2020 20
02.07.2020 06.07.2020 3
Now I want to filter this table by the calendar week. Let's say "where [calendar week] = cw28". cw28 is from the 06th of july to the 12th of july.
With that I'd like to have the sum of the amount of the days that lie between those two dates. One single number.
I'm using MS SQL Server (SQL Express).
I can't figure out how to distinguish (and break down) if one day lays between the two date values or not. And if yes how much I need to sum up.
I tried to make a picture in excel to create a logic from this:
"Logic" in Excel
Can anyone help me with this? :)
Thx and Best!,
Max
Not sure about your exact requirement. But below is the query to get the sum of values between two dates.
select sum(amount_of_days) from table where date_column between '06-JUL-2020' and '07-JUL-2010';
Change the column name and table name according to your requirement
Related
I have two years worth of data that I'm summing up for instance
Date | Ingredient_cost_Amount| Cost_Share_amount |
I'm looking at two years worth of data for 2012 and 2013,
I want to roll up all the totals so I have only two rows, one row for 2012 and one row for 2013. How do I write a SQL statement that will look at the dates but display only the 4 digit year vs 8 digit daily date. I suspect the sum piece of it will be taken care of by summing those columns withe calculations, so I'm really looking for help in how to tranpose a daily date to a 4 digit year.
Help is greatly appreciated.
select DATEPART(year,[Date]) [Year]
, sum(Ingredient_cost_Amount) Total
from #table
group by DATEPART(year,[Date])
Define a range/grouping table.
Something similar to the following should work in most RDBMSs:
SELECT Grouping.id, SUM(Ingredient.ingredient_cost_amount) AS Ingredient_Cost_Amount,
SUM(Ingredient.cost_share_amount) AS Cost_Share_Amount
FROM (VALUES (2013, DATE('2013-01-01'), DATE('2014-01-01')),
(2012, DATE('2012-01-01'), DATE('2013-01-01'))) Grouping(id, gStart, gEnd)
JOIN Ingredient
ON Ingredient.date >= Grouping.gStart
AND Ingredient.date < Grouping.gEnd
GROUP BY Grouping.id
(DATE() and related conversion functions are heavily DB dependent. Some RDBMSs don't support using VALUES this way, although there are other ways to create the virtual grouping table)
See this blog post for why I used an exclusive upper bound for the range.
Using a range table this way will potentially allow the db to use indices to help with the aggregation. How much this helps depends on a bunch of other factors, like the specific RDBMS used.
I am a novice with SQL and need some help!
I have two fields, MoveInDate and MoveOutDate, both of which are date fields. I want to generate a result that counts the number of move-ins and move-outs per week. The output should look something like this:
Week Start Week End Move-In-Count Move-Out-Count
1/20/2014 1/26/2014 0 4
1/27/2014 2/2/2014 1 0
I am working on SQL Server 2008.
Something Like this should work.
Select COUNT(Primary_Key) As MoveInCount
FROM [dbo].[tableName]
where MoveInDate between WeekStartDate and WeekEndDate
I would suggest using a Date Dimension since you are looking to group by week.
You can get a ready made date dimension here along with script to load into your database:
http://www.kimballgroup.com/wp-content/uploads/2012/06/Ch10-DateDim.xls
Once you have loaded your dimension you can group by Week and count by the number of move in, move out dates.
Long title, easy meaning:
How is it possible to extract from a date like "2014-04-04 10:47:30.000", which is stored in one column, it's components like year, month and day?
I'm not interested in the time.
For example, I have a table called "Incidents". Inside the table we got a column called "IncidentID" and a column called "ReportingDate", in which dates like the above-mentionend are stored. Let's say we have about 50k Incidents, therefore we have also 50k dates.
A year has 365 days. I want to query for the count of the Incidents, which were reported on different dates - for instance on the 5th of October 2013.
So: How can I get the components of the date and put them into another table while having own columns for the components and how can I query for the Incidents as well?
I guess at first I have to change the datatype of the date from DATETIME to DATE, but I'm not quite sure how to go further. May anyone help me while giving me a code and explains me what it does for a sql-noob? :-)
To achieve this
I want to query for the count of the Incidents, which were reported on
different dates - for instance on the 5th of October 2013.
you haven't do this:
I guess at first I have to change the datatype of the date from
DATETIME to DATE, but I'm not quite sure how to go further.
Just query
SELECT
IncidentID
FROM incidents
WHERE ReportingDate >= '20131005'
AND ReportingDate < '20131006'
Suppose ,I have a table which has all the billing records. Now I want to see the sales trend for a user given time duration group by each 3 days ...what should be the sql query regarding this?
please help,Otherwise I am gone ...
I can only give a vague suggestion as per the question, however you may want to have a derived column with a standardised date (as per MS date format, just a number per day) that you could then use a modulus (3) on so that days are equal per 3 day period. You can then group and aggregate over this column to get the values for a 3 day period. Obviously to display the date nicely you would have to multiply back and convert your column as well.
Again I'm not sure of the specifics, but I think this general idea could be achieved to get a result (may well not be the best way so it would help to add more to the question...)
I have an SQLite database with the following fields for example:
date (yyyymmdd fomrat)
total (0.00 format)
There is typically 2 months of records in the database. Does anyone know a SQL query to find a weekly average?
I could easily just execute:
SELECT COUNT(1) as total_records, SUM(total) as total FROM stats_adsense
Then just divide total by 7 but unless there is exactly x days that are divisible by 7 in the db I don't think it will be very accurate, especially if there is less than 7 days of records.
To get a daily summary it's obviously just total / total_records.
Can anyone help me out with this?
You could try something like this:
SELECT strftime('%W', thedate) theweek, avg(total) theaverage
FROM table GROUP BY strftime('%W', thedate)
I'm not sure how the syntax would work in SQLite, but one way would be to parse out the date parts of each [date] field, and then specifying which WEEK and DAY boundaries in your WHERE clause and then GROUP by the week. This will give you a true average regardless of whether there are rows or not.
Something like this (using T-SQL):
SELECT DATEPART(w, theDate), Avg(theAmount) as Average
FROM Table
GROUP BY DATEPART(w, theDate)
This will return a row for every week. You could filter it in your WHERE clause to restrict it to a given date range.
Hope this helps.
Your weekly average is
daily * 7
Obviously this doesn't take in to account specific weeks, but you can get that by narrowing the result set in a date range.
You'll have to omit those records in the addition which don't belong to a full week. So, prior to summing up, you'll have to find the min and max of the dates, manipulate them such that they form "whole" weeks, and then run your original query with a WHERE that limits the date values according to the new range. Maybe you can even put all this into one query. I'll leave that up to you. ;-)
Those values which are "truncated" are not used then, obviously. If there's not enough values for a week at all, there's no result at all. But there's no solution to that, apparently.