I have a dataset with the structure below.
I want to calculate a monthly average of the views.
I attempted to calculate the yearly frequency with the following code and I believe it is correct
SELECT
EXTRACT (YEAR FROM TO_DATE("date",'Month YYYY') ) AS "year",
AVG("views")
FROM talks
GROUP BY EXTRACT (YEAR FROM TO_DATE("date",'Month YYYY') )
ORDER BY "year" DESC
When it comes to the monthly analysis I have the problem that there several records for the same month in a year and there several years with the same months (in reality the dataset has information for many years - this a reduced version).
How can I go to implement this?
If you want the average per month then just group by your current date field.
If you want the average per month regardless of year then you would have to extract the month part of the current date field and group by that.
But your date field now appears to be having string data type; it would be better to use proper date data type. Then your analysis would be much easier, more flexible, better performing.
Related
I am using standard SQL and am trying to add the weekly sum for product usage by week.
Using code below, I was able to add to each row the respective week and year it falls into. How would I go about summing the totals for an item by week and outputting it in columns, say up to the last 8 weeks.
extract(week from Metrics_Date) as week, EXTRACT(YEAR FROM Metrics_Date) AS year
Image is my raw data with the week and year next to an item:
This image is of above raw data being analyzed further(grouping them together). Here is where I would want to add columns, current_week & firstday of week date, and a sum of that weeks totals.
Any help would be appreciated.
You don't need the extract() by the way, you can do truncation DATE_TRUNC(your_date, WEEK) and it will truncate it to the week, usually easier.
Also, because the result of the truncation is a date, you will have the first day of the week already.
The rest I believe you have it figured out already, but just in case:
SELECT DATE_TRUNC(your_date_field, WEEK) AS week, SUM(message_count) AS total_messages FROM your_table GROUP BY 1
I am trying to create a calculation measure to compare revenue from one date to last year's equivalent date.
I have this "last year's equivalent date" stored in my date dimension.
So for example, my fact table of DailySummary has a measure of TotalRevenue and it is granular by date. If I wanted to show today's revenue (12/06/2019), the equivalent date from last year that is stored in the Date dimension would be 12/07/2018. I would want to show both those day's revenue side by side. I would then create other measures, like growth.
I am sure it is obvious, but if it helps, the DailySummary fact and the Date dimension are joined by the date, so today's date, not the last year equivalent.
Let me know if this doesn't make sense or if you need more information.
I think that you will need to use the PreviousPeriod MDX function.
In a form on Ms ACCESS, a user can select a commodity (such as copper, nickel, etc.) from a list and a commodity price date from a list. A trailing 12 month average commodity price should then be calculated.
For example: the user selects Copper as commodity and February 1st 2010, 02/01/2010. I then want the average price to be calculated over the time period: [02/01/2009 - 02/01/2010].
I'm not sure how to write this in query form. This is the current incomplete code;
SELECT Avg(CommPrices.Price) AS Expr1,
FROM CommPrices
WHERE (((CommPrices.Commodity)=[Forms]![Tool Should Cost]![List243]))
AND CommPrices.DateComm = [Forms]![Tool Should Cost]![List55];
List243 is the list of commodities the user can select from, list55 is the list of dates the user can select. All data is obtained from the table CommPrices.
Note: the earliest dates in the column DateComm is 01/01/2008. So if the user selects a date for example 02/01/2008, then calculating the average over the past 12 months before 02/01/2008 won't be possible. I do want the code to still calculate the average using the dates available. (in the example it would just be the average over the past month)
Second Note: the column DateComm only has monthly dates for the first day of every month (e.g 01/01/2008, 02/01/2008, 03/01/2008). The dates listed in list55 can refer to different days in the month (e.g 03/16/2009), in that case I want the code to still calculate the past 12 month average using the closest commodity dates possible. So if the user selects date 03/16/2009, I want the code to calculate the 12 month average for 03/01/2008 - 03/01/2009.
For "integer" months it would be:
SELECT
Avg(CommPrices.Price) AS AveragePrice,
FROM
CommPrices
WHERE
CommPrices.Commodity=[Forms]![Tool Should Cost]![List243]
AND
CommPrices.DateComm = BETWEEN
DateSerial(Year([Forms]![Tool Should Cost]![List55]) - 1, Month([Forms]![Tool Should Cost]![List55]), 1)
AND
DateSerial(Year([Forms]![Tool Should Cost]![List55]), Month([Forms]![Tool Should Cost]![List55]), 1)
I have a situation where the metric calculation(Month to Date Sales) is based on the month from the report date filter.
We want the month to date filter to be for the report month and not the current month - in other words, if the user selects 03/10/2015 for the report date, we want the month sales to be the sales for March,
and not the sales for June.
Is there a way to parse the report date to extract the report month into a variable that can be used in the ‘where' clause of the metrics in order to generate the desired results.
Thanks in advance.
I am not entirely sure if this answers your question, but achieving something like this may be possible when using disconnected timeline date filter. Your metric should look like this:
SELECT Sales_metric BY Month/Year (Date) ALL OTHER WHERE Month/Year (Date) = (SELECT MAX(Month/Year (Timeline)) BY ALL OTHER EXCEPT Date (Timeline))
I hope this helps, in case if it doesn't feel free to log a ticket to GoodData Support at support#gooddata.com.
I want to summarize sql query result week wise and month wise at the same time in a grid view. Is this even possible or I am just dreaming?
Requirement:
Show last one month data and next two month's data week wise in the grid.
Example-
If the current month is September then I want to show data from 1st August to 31st October categorized in weeks.
Show the data after the next month of current month in month wise view in the same grid.
Example-
data for month November and December will be shown categorized in month not in weeks.
grid or result should look something like below -
Please suggest something to achieve this
If you want a maintainable solution, use two independent queries, one for weekly aggregation other for monthly. Depending on the input run corresponding query.
I think you must work with group by or group by ... cube
SELECT x , y from <tabel> GROUP BY date_feld( to_char( 'MM' ))
but i don't now your DBMS so i can't give you a exact example for the date handling.