I am trying to create a measure to calculate a monthly average from a set of data that was collected every 15 minutes. I am newer to DAX and am just unsure how to intelligently filter by month without hard setting in the month ID #. The formula I am trying is:
Average Monthly Use:=AVERAGEX(VALUES('Lincoln Data'[Month]),[kWh])
Where kWh is a measure of the total usage in a column
Thanks in advance
DVDV
To get the monthly average usage, You need to sum up the total usage per user and divide by the total number of months for that user.
Without knowing what your tables look like, it's hard to give a very good formula, but your measure might look something like this:
= DIVIDE(SUMX(DataTable, [kWh]), DISTINCTCOUNT(DataTable[Year-Month]))
Related
When I apply Month/Year to Cases or Deaths from my data, the values explode. For Cases it goes from approximately 48 million to over 1 billion, and for Deaths it goes from about 700 thousand to over 22 million. However, when I try the same thing with Initial Claims or the Stringency Index, my values remain correct. I'm trying to find the month over month percentage change by the way. And I'm using the Date column. I only select 2020 and 2021 in the filter for Year.
What I'm asking about is Sheet 21.
Link to workbook: https://public.tableau.com/app/profile/nilajah.rivers/viz/CoronaVirusProject_16323687296770/Sheet21
Your problem is that the data points are daily cumulative deaths. If you change the date aggregation to anything other than days, Tableau will default to summing the numbers for all the days in the month. This will give the wrong result, obviously.
If you want to show the correct total deaths or cases regardless of the time aggregation (months, days, weeks etc.) then you could use the New Case or New Death numbers plus a running sum table calculation. This will always give the correct total for the time period.
Table calculations will also allow automatic calculation of the period to period % change from the same data fields.
This is a common problem when working with datasets that offer pre-calculated aggregations. Tableau doesn't need that as it can dynamically calculate the aggregation of a field over any given time period but it is easy to forget which field has pre-aggregated data and which has raw data. Pre-aggregated fields assume a particular time period and can't be used for different time periods without disentangling that assumption (which is unnecessary if you also have the raw data (in this case daily new deaths/cases).
I am using RANK function in Tableau and I am displaying the Rank of calculated measure (Eg: 1 to 50)
The calculated Measure I have is Total Amount for Combined Periods.
When there is no Period displayed on the dashboard, the Total Amount is the sum of both periods and this is exactly what I want. I am good in this case.
However, When I want to display the Period in the Rows, the Total Amount changes to "Total Amount for Period 1 and Total Amount for Period 2".
How can I add a different axis to show Individual Periods as well as Rank of Total Amount for Combined Period?
I guess this might come down to Dual axis in Tableau and I believe this is not available yet and users are voting for this in Ideas.
Have this data set and when I am trying to plug into tableau to and calculates averages by either Day of Week or weekday/weekend, it always calculates the averages at the hourly level. Please help!
Thanks:)
Data set
Use datetrunc('day',[timestamp]) to reduce your date field to just date, and not date_time. Then average.
I have Tableau 9.1 and have the costs per transaction in a column over the course of 3 years. I also have the dates and locations for all the transactions.
How do i make a calculated field for total cost at a location for a given quarter assigned to each observation?
Generally that depends on how you want to display these values.
An easy way would be via a LOD calculation:
{fixed DATETRUNC('quarter',[Date]), [Location]: SUM([Cost])}
This calculates the SUM([Cost]) for each quarter of [Date] and each [Location]
I am a very basic user of tableau and I have not found an answer to my question.
I have a txt file that has historical daily data for 98% of all the stocks in the US, with their daily capitalization. Each stocks has its TICKER, Daily Market Value for every trading day of the year, and its SECTOR.
I did a simple time series that display SUM([Mktval]) (sum of all individual market values) across all stocks, on a daily daily, and where I can see that the total value as of 2016 is about 24 Trillion USD, as in the image below.
When I change the view column from DAY to YEAR, I don't see the right values, but something a lot larger. So I realized that I need to do SUM([Mktval])/252 to get the right value for a year (there are 252 trading days in a year).
If I change the view to MONTH, as in the chart below, the numbers are again wrong because 252 is not the right value to use in the division.
Is there any way that Tableau can adjust the values automatically to reflect the AVG MktVal across different time intervals?
Thanks
Replace SUM(Mktval) on the Rows shelf with the following calculated field
avg({ fixed day(Date1) : sum(Mktval) })
That solution is all in one step. It is perhaps a bit more clear to use 2 steps. First, create a calculated field called total_daily_market_value defined as
{ fixed day(Date1) : sum(Mktval) }
Then make sure that calculated field is a measure. It is an LOD calculation that you can think of as a separate table with one value for each day showing the total market value for that day.
Drag that measure to a shelf, and then change the aggregation function to AVG(), MEDIAN(), MIN(), MAX() or STDEV() as desired. Tableau will aggregate the total_daily_market_value using your chosen aggregation function for whatever values of Date1 are in your view.