I am looking for a way to group my data which has a column with datetime in it.
I want to group it such that, the business requirement is to have the records by a fixed week definition of (1-7, 8-14, 15-21, 22-28, 29-31).
While MongoDB $week would group by calendar weeks.
Any idea how to go about this custom grouping?
Related
I need to create an attendence list showing days in rows and employee names in colums. The list will always cover one full month chosen in parameters.
How can I create a recordset of days of chosen month? I've done it in command section but, due to ERP system limitations, it must done otherways.
Thank you,
Przemek
A good approach is to create a Calendar table (aka Date Dimension in data warehousing lingo). It makes it easy to show days without any attendance. If you don't need that aspect, you can simply create a formula that returns the attendance date month's day, and Group on that formula. The Day() function gets you the day of month. For example,
Day ({Orders.Order Date})
If you search 'creating a data dimension or calendar table' you'll find many helpful sources such as this one: https://www.mssqltips.com/sqlservertip/4054/creating-a-date-dimension-or-calendar-table-in-sql-server/
For your case, I agree with the comments in that post about using date instead of integer as the primary key. Integer PK makes more sense for true data warehousing scenarios as opposed to legacy databases.
So, pretend I'm looking at sales of an item vs time. One item I started selling 3 years ago and one is from only a year ago.
I want to look at how the performance of both items change starting from first date sold as "day 0" not from first date sold as say "march 2016".
My date field is a calendar date and I'm not sure the best way line everything up from within tableau that will allow me to display the result on a single graph. I'd also like an option that will scale to 10+ items
Any approaches would be great!
Create a calculated field called first_Sale_date_per_item defined as {fixed Item : min(sale_date)}
Then you can define days_since_first_sale as datediff('day', first_sale_date_per_item, sale_date)
This might be a simple one but I haven't got a solution yet. I have a create_date field which is a date type, and a revenue number. I want to see weekly break down of revenue.
I can get the numbers easily in tableau because of built in functionality but doing it in PostgreSQL is where I need some help.
If you want the revenue by week, you'll need to group and aggregate:
select extract (week from create_date) as week, sum(revenue) from table group by week
My actual documents are more complex than this but simplifying them like so will explain the problem I want to solve. I have daily and weekly documents.
Daily Document: ObjectId, Type, Count, Date
Weekly Documents: ObjectId, Type, Count, StartDate, EndDate
If I wanted a daily report I can run a query that will select documents with Date field value between range X to Y and Type equal to 'daily'. I can do the same thing for Weekly reports and it all works.
The problem:
For weekly reports if the start date is not the first day of the week and the end date is not exactly the last day of the week, selecting documents with Type 'weekly' will produce inaccurate reports since weekly documents store the data for the entire week. This may seem strange but Google Analytics lets you do it:
In the above screenshot Jul 3rd isn't the beginning of that week, nor is Jul 17th the end of that week. But Google Analytics lets you see the data as you want.
Possible Solution:
One possible solution is to produce a daily report for the overflowing days and subtract it from the weekly report.
The question:
Is there a nicer solution to solving the problem I described? I'm open to redesigning the documents
For weekly reports if the start date is not the first day of the week
and the end date is not exactly the last day of the week, selecting
documents with Type 'weekly' will produce inaccurate reports since
weekly documents store the data for the entire week. This may seem
strange but Google Analytics lets you do it:
Because they don't store documents like that.
The way this works (I reckon) is that Google just summerises the daily documents and ignores your "week" range and applies their own range of saying:
get as many full weeks as possible and aggregate the daily documents that
come under that range
and then:
Just throw the others ontop making each the end and start point
I wouldn't try to mix week and daily documents here I would just query over daily documents only and aggregate client side.
In my application I have to store data month wise and year wise. So for this, I have to store the data along with date into database.
My requirement is how to store in terms of date and how to retrieve data with group by month and year. In my app I am showing a table of years and months, based on selected month and year. I have to show the data in a dashboard.
My problem is in storing and retrieving date data types.
Use the following syntax
SELECT * FROM DATABASE WHERE REQUIREDDATEFIELD LIKE '%2011-01%';
2011 is supposed to be the year
01 is supposed to be the month
DATABASE is supposed to be your mysql database name
REQUIREDDATEFIELD is supposed to be the field you are hoping to sort from month and year.
like '%2011-01%' is supposed to be meaning, all the records containing 2011-01 in the given field. It could be in the beginning or the end or in the middle of a large text, so having % in both the beginning and end of the search criteria is a good habit.
You just select either for a specific month or year or month and year. Or if you want all, you use GROUP BY.
I know this answer is quite vague and generic, but that's because your question is vague. You probably need to be more specific. Explain not only what you want to do, but what you have tried, and in which way that didn't work.