I'm wondering if it's possible to summarize all series with value less 1% to "Other" seria.
Related
Here is the snippet of the tableau work sheet i want to add weekly quality and case count data as well along with avg quality and case count
I want to monitor the cpu usage of kafka container, but the graph is chopped up into different pieces. There seem to be gaps in the graph and after each gap a different colored line follows. The time range is last 30 days. For the exporter we use danielqsj/kafka-exporter:v1.4.2
The promql query used to create this graph is:
rate(container_cpu_usage_seconds_total{container="cp-kafka-broker"}[1m])
Can I merge these lines into one continual? If so, with what promql expression/dashboard configuration?
This happens when at least 1 of the labels that are attached to the metric changes. The rate function keeps all the original labels from the underline time series. In Prometheus, each time series is uniquely identified by the metric name container_cpu_usage_seconds_total and any labels (key-value pairs) attached to the metric (container, for instance). This is why Grafana uses different colors because they are different time series.
If you want to get a single series in Grafana you can aggregate using the sum operator:
sum(rate(container_cpu_usage_seconds_total{container="cp-kafka-broker"}[1m]))
which by default will not keep any of the original labels.
I am looking to create a chart in Power BI to compare weekly data from previous years to levels this year, similar to the screenshot below from excel.
5-years of historical data in the shade with this year as a line chart.
Have tried to use similar method to excel
take min and max figures from the weekly data
get the difference between the two values
in charting: take the min value and use stacked area to shade range above with the difference between the min & max
place this years data as a line chart
I've got a bar chart with three months worth of data. Each column in the chart is one month's data showing the percentage of Rows that met a certain criterion for that month. In the first month, 100% of 2 rows meet the measure. In the second month, 24.2% of 641 rows meet the measure. In the 3rd month, 28.3% of 1004 rows meet the measure. My reference line which is supposed to show the average across the entire time-frame is showing 50.8%, the simple average (i.e. [100+24.2+28.3]/3) instead of the weighted average (i.e. [100*2+641*24.2+1004*28.3]/[2+641+1004]).
In the rows shelf, I have a measure called "% that meet the criterion", this is defined as SUM([Criterion])/SUM([NUMBER OF RECORDS])
The criterion measure is 1 for any record that qualifies and null for any that do not qualify.
If I go to Analysis >> Totals >> Show Row Grand Totals, a 4th bar is added, and that bar shows the correct weighted average of the other three bars (26.8%), but I really want this to be shown as a reference line instead of having an extra bar on the chart. (Adding the Grand Total bar also drops the reference line down to 44.8%, which is the simple average of the 4 bars now shown on the chart--I can't think of a less useful piece of information than that).
How can I add the weighted average as a reference line?
Instead of using 'Average' as your aggregation, try using 'Total' instead in the Edit Reference Line dialogue window.
I have to say it's a bit counter-intuitive, but this is what the Tableau online help has to say about it:
http://onlinehelp.tableau.com/current/pro/online/mac/en-us/reflines_addlines.html
Total - places a line at the aggregate of all the values in either the cell, pane, or the entire view. This option is particularly useful when computing a weighted average rather than an average of averages. It is also useful when working with a calculation with a custom aggregation. The total is computed using the underlying data and behaves the same as selecting one of the totals option the Analysis menu.
If you are using Tableau 9, you can make second calculated field using an LOD expression
{ SUM([Criterion]) / SUM([NUMBER OF RECORDS]) }
This will calculate the ratio for the entire data set after applying context and data source filters, without partitioning the data by any of the other dimensions in your view (such as month in your case)
If you place that new field on the detail shelf then you can use it to create a reference line.
There are other ways to generate a weighted average, but this is probably the simplest in your case.
I have a query regarding the table structure for the pie chart on Tableau.
I have below 2 table structures and am not sure which one is more apt for tableau to arrive at a pie chart .
For example I wish to see the percentage of each metric over a particular date contributing towards the total. May be the representation is a pie chart or some other chart. Please suggest me which table lay out works out well for my requirement.
Note : I have done all my calculations to arrive at the total in my database table itself.
Could some one please help me out.Thanks!
Table 1 :
Table2 :
Pie charts first take a series of data and sum the total. Then they calculate the percent of each element of the series and create a pie slice with a unique color. To make a pie chart, you need one measure (the category or label) and one dimension (the amount of that category).
If you need to see how one is made, I would suggest downloading an example workbook and then going to the pie chart sheet. One example is here.
Here is how it looks when set up in Tableau.
Personal note: Despite the name, pie charts are not that delicious. Here is advice from Tableau themselves. And here is something I made up to express my feelings.
Relating to the topic of pie charts, and how to best represent data where contributions to a whole are of interest, I would recommend bullet graphs as well. Here are two papers by Stephen Few that could be of interest:
Save the Pies for Dessert
http://www.perceptualedge.com/articles/08-21-07.pdf
Bullet Graph Design Specification
http://www.perceptualedge.com/articles/misc/Bullet_Graph_Design_Spec.pdf
And, to answer your question on data preparation for Tableau, it looks like the second table would be more appropriate. Here's a good KB for preparing data for analysis, note the last section on the Tableau Reshaper tool for Excel...can save a ton of time.
Preparing Excel Files for Analysis
http://kb.tableausoftware.com/articles/knowledgebase/preparing-excel-files-analysis