27 December 2022 Calculating fractiles in Qlik Share this message Every Friday at Bitmetric we’re posting a new Qlik certification practice question to our LinkedIn company page. Last Friday we asked the following Qlik Data Architect certification practice question about calculating fractiles in Qlik. It seems like a lot of you have spend a great time around Christmas, since we are normally used to more answers. The correct answer is B Fractile Fractile is a function which allows you to calculate a fractile of a set of values in a field. A fractile is a value that divides a set of data into intervals. For example, the 50th fractile of a set of values would be the value that divides the set into two equal parts: the values below the 50th fractile and the values above it. The syntax for Fractile is as follows: Fractile([{SetExpression}] [DISTINCT] [TOTAL [<fld{, fld}>]] expr, fraction) To illustrate how fractiles work please see the diagram below: Here we can see that the 50th fractile is the exact median of the range. The first quartile will be the first 25% of values and so on for each quartile and the interesting to focus on is the deciles. This is all the values divided in parts of ten. So in order to get to that top 10% we need to use 0.9 as the fraction in the syntax. This will give us the value at the 90th percentile. Everything above this will be the top 10%. AGGR This brings us to the second part of the answer. To properly calculate the value of the 90th percentile, we need to use another aggregation. Fractile needs to be calculated on a dimension. In this case per person. So by using the Aggr function we first calculate the following (if you need to refreshen the Aggr function, please refer to this blog post): Aggr(Sum(Nice) - Sum(Naughty), Person) This calculates per person the score of each individual. Now it is possible to wrap this in the fractile expression to give the end result of the 90th fractile for all values of the score per person. Use cases Decile Analysis One very interesting feature is to do decile analysis. Decile analysis is a useful tool for understanding how a particular variable is distributed within a dataset and for identifying trends or patterns in the data. It is done by dividing the dataset in ten equal parts (deciles) and then calculate various statistics on these. It is often used in finance and economics to analyze income or wealth distribution. Below is an example of a decile analysis for sales per car brand: This gives great insights in revenue and which brands are responsible for the majority of revenue. This chart is made by using the following expression as a calculated dimension, so it it possible to also select the deciles. =Aggr(IF(Sum(Revenue) <= Fractile(total Aggr(Sum(Revenue), brandName), 0.1), 10,IF(Sum(Revenue) <= Fractile(total Aggr(Sum(Revenue), brandName), 0.2), 9,IF(Sum(Revenue) <= Fractile(total Aggr(Sum(Revenue), brandName), 0.3), 8,IF(Sum(Revenue) <= Fractile(total Aggr(Sum(Revenue), brandName), 0.4), 7,IF(Sum(Revenue) <= Fractile(total Aggr(Sum(Revenue), brandName), 0.5), 6,IF(Sum(Revenue) <= Fractile(total Aggr(Sum(Revenue), brandName), 0.6), 5,IF(Sum(Revenue) <= Fractile(total Aggr(Sum(Revenue), brandName), 0.7), 4,IF(Sum(Revenue) <= Fractile(total Aggr(Sum(Revenue), brandName), 0.8), 3,IF(Sum(Revenue) <= Fractile(total Aggr(Sum(Revenue), brandName), 0.9), 2, 1))))))))), brandName) Other things to notice By default the fractile will be calculated over the used selections, you can use set expressions to change this. Use DISTINCT to calculate the fractiles over distinct values Use TOTAL to calculate fractiles over all possible values regarding the current selections. Nested calculations are not possible with use of Fractile() unless you use the Aggr() function. Fractile() is a chart function. In the script you can use FractileExc in combination with a Group By clause. That’s it for this week! See you at QlikWorld 2023 in Vegas? Come see us at QlikWorld 2023 for a chance to win a free, lifetime SenseTheme subscription and get some cool swag. Want more Friday Qlik Test Prep? Check out the Friday Qlik Test Prep archive for more Qlik questions and answers. Friday Qlik Test Prep Solution How can we help? Feel free to contact us if you have any comments or questions. Call us Mail us 23 May 2023 What’s New in Qlik Sense May 2023 for Administrators This blog post provides Qlik Sense administrators a summary of the new administrative features and improvements available in Qlik Sense Enterprise on Windows. Let’s get started on what’s new in Qlik Sense for May 2023. New Release Qlik 23 May 2023 What’s New in Qlik Sense May 2023 for Business Users, Analytic Creators and Data Integrators This blog post provides Qlik Sense business users, analytic creators, and data integrators a summary of the features and improvements available in Qlik Sense Enterprise on Windows. Let’s get started with what’s new in Qlik Sense for May 2023. New Release Qlik 11 May 2023 How to make seasonal trendlines in Qlik Sense Every Friday at Bitmetric we’re posting a new Qlik certification practice question to our LinkedIn company page. Last Friday we asked the following Qlik Data Architect certification practice question about how to make seasonal trendlines: The correct answer was B! Trend analysis Qlik has added Time series decomposition modifier functions to the line chart. This can […] Friday Qlik Test Prep Solution
23 May 2023 What’s New in Qlik Sense May 2023 for Administrators This blog post provides Qlik Sense administrators a summary of the new administrative features and improvements available in Qlik Sense Enterprise on Windows. Let’s get started on what’s new in Qlik Sense for May 2023. New Release Qlik
23 May 2023 What’s New in Qlik Sense May 2023 for Business Users, Analytic Creators and Data Integrators This blog post provides Qlik Sense business users, analytic creators, and data integrators a summary of the features and improvements available in Qlik Sense Enterprise on Windows. Let’s get started with what’s new in Qlik Sense for May 2023. New Release Qlik
11 May 2023 How to make seasonal trendlines in Qlik Sense Every Friday at Bitmetric we’re posting a new Qlik certification practice question to our LinkedIn company page. Last Friday we asked the following Qlik Data Architect certification practice question about how to make seasonal trendlines: The correct answer was B! Trend analysis Qlik has added Time series decomposition modifier functions to the line chart. This can […] Friday Qlik Test Prep Solution