I'm not sure whats happening with my X Axis on a Line Chart once I apply measures I've created for Upper and Lower Control Limits.
The X Axis should display the Month and year from January 2022 to the previous month using the Month offset <= 0 on a calendar lookup Date.
The value im displaying is the Annual Leave FTE and the DAX formula for the Upper/Lower Control Limits are listed below.
Upper Control Limit
EO_AL UCL = CALCULATE(AVERAGE(ORM_EO_Resource[AnnualLeaveFTE]),ALLSelected(ORM_EO_Resource)) +1*CALCULATE(STDEV.P(ORM_EO_Resource[AnnualLeaveFTE]),ALLSELECTED(ORM_EO_Resource))
Lower Control Limit
EO_AL LCL = CALCULATE(AVERAGE(ORM_EO_Resource[AnnualLeaveFTE]),ALLSELECTED(ORM_EO_Resource)) -1*CALCULATE(STDEV.S(ORM_EO_Resource[AnnualLeaveFTE]),ALLSELECTED(ORM_EO_Resource))
As you can see from the graph it displays the remaining months for the rest of 2023 regardless of what filters I apply.
As I intend on publishing the dashboard I want it to be a Set & Forget dashboard where I wont have to go in every month to renew filters etc.
Any thoughts where I might be going wrong with this, I'm assuming the issue lies within the measure I've written as if i remove the measure from the Graph, the Axis rectifies itself as below.
Related
I want to have a time series visualization showing the amount of existing open issues per, e.g., week, whose range can be adjusted with the time picker.
Say I have an index with issues, which has openDate, closeDate, and a list of other fields like, team, department that I would use to filter the issues shown in the visualization.
In Kibana it would be trivial to show issues opened or closed each week, as counting events is trivial.
However, showing open issues is counting states. It is not rocket science, if you have a timeStart and timeEnd, the number of open issues is given by the filter:
openDate < timeEnd and (not exists(closeDate) or closeDate>timeStart)
Is there any way of solving this with Kibana? I imagine that it is possible to write such a query with ES, but how to link it to the time picker? how to use the values it return in a visualization, etc....
I have weekly sales data from 201601-201835 and i have to create a graph to see the trend. Since the data is categorical, a scroll bar is appearing on the graph. I want to view the complete graph at once.
I tried converting the data to continuous, but there is a gap in the graph as there is no data from 201653 to 201699 and hence the graph is wrong.
Is there a way of viewing the complete data without a scroll bar?
I would add summary fields to the Axis above the Week, e.g. Year, Month, Quarter. You will probably need a reference table for your weeks or some fancy calculations.
With those fields in place, you can expand or drill into the levels before getting down to the Week level. As the higher levels are Categorical and have fewer categories, you are less likely to see scroll bars.
A side benefit is the user has more control e.g. they can drill down on just a section of the weeks, e.g. for one year.
I'm facing a following problem. In Kibana 4 I've created a line chart based on my input from elasticeasrch but I can only display average, min, max instead of an actual value of the field per time, e.g. sent bytes.
Most answears to that question on stackoverflow are about Kibana 3 (How to create value over time chart with Kibana 3?) and seem to include a Histogram on a X axis, yet I can't seem to find one which will enable me to apply them to Kibana 4. I was unable to find the histogram panel and once I click on the discover tab there is the constant Searching loading.
If I have the following fields in my _source:
{"timestamp":"2015-06-02T10:16:44.0855","time":587,"threadName":"Thread Group 1-957","byte":1372,"status":"false","latence":306,"registerCall":"404"}
and I would like to have the number of bytes on the Y-axis and on the X-axis my timestamp.
Any help in the right direction will be appreciated :)
To create a value over time line chart in Kibana, follow these steps:
Go to visualize tab and select line chart
In the X-axis, select X-axis, Aggregation as Date Histogram and then select your timestamp field as the date field.
Next for the Y-Axis, select Sum as the aggregation and then bytes as the field.
For the X axis, what Alcanzar said is good, but as you notice, the Y axis is problematic.
Sum (suggested by "Limit") works, but since it's aggregated, it shows the total used in each aggregated bucket, but that may be meaningless depending on what you are trying to show. Your question isn't clear on what you want, so I'm just guessing here. One hour of requests, each of which ran for one minute and sent 1 megabyte is indeed 60 megabytes-minutes, if you are trying to show total capacity used over than hour (maybe you are paying a bill based on usage per time). On the other hand, if you are trying to show peak usage in each time, it would be wrong.
You said you already looked and Max and Min and they don't meet your needs. I don't suppose Standard Deviation would be any better?
I have the same concern. The best I've been able to do so far is
display Min and Max simultaneously in the Y axis. When they diverge, I know I'm zoomed out too far, so I zoom in until they align.
This is how I know I'm seeing individual events.
In any case, I share your frustration. I too would like to be able to show time series as easily as I can in, say, Excel.
I need to calculate the nearest dataPoint in a time series chart from a specific point in a chart
I obviously cannot use d=sqrt(x*x+y*y) as my x axis is in time series, hence it wont make sense to have an equation where I am adding distance and time together (x,y need to have same units). Moreover visually it may seem right, but it still depends upon the scale of the x axis.
So what best logic can I use to find the nearest point?
I can think of using a quadratic form of x (i.e. time) so as that my final function can ne f(x*x,y), but then it is just a subjective equation.
Does anyone have a better and more logical approach to this. If there is an intuitive logical approach I will love it. And if there is a complicated model I would still like to know about it and explore it.
Thanks
EDIT
TO give background: I am polling people to predict where the stock price will be in April(they have to mention exact date when the expect price to be there) ... How do I measure their performance?
One intuitive way is by calculating the average absolute change per day.
i.e.
Sum of Absolute changes every day from previous day / Total number of days in series.
Thereafter I can translate each day in terms of prices i.e. the average price change per day.
Thus if average absolute change per day is lets say 2, then a price that is 10 days away can be said to be 20 price points away.
Thereafter I can calculate the distance based on sqrt(x*x+y*y) formula.
This can be fine tuned by using a bell curve (std dev and mean) rather than just mean of absolute change per day. But then it will make solution more ocmplicated.
I am developing a rails application where I need a "success rate" system similar to RetailMeNot. I noticed that they use jQuery Sparkline library (http://omnipotent.net/jquery.sparkline/) to generate a success rate trend for each coupon.
For example, in their source code:
<em>84%</em> Success<br/><span class="trend">14,18,18,22,19,16,15,28,21,17</span>
<em>20%</em> Success<br/><span class="trend">-1,1,-1,-1,-2,-2,1,-1,1,-1</span>
Can someone explain to me the best way to develop a similar trending system for success rate?
A trend is just a number calculated at regular intervals. In this case it looks like the site is just binning the data they get from the "Did this coupon work for you?" question, and then plotting those values in the chart. In other words, they take the number of (successes - failures) in some time interval (e.g. 12 hours) and plot that number for each interval.
As time passes, they probably rebin to keep the number of bars on the x axis acceptable. For example, if they only want to show 8 bars on the plot, then after 4 hours they'll have to widen the bins.