Using the Fractile() function to generate quartiles
by Ferran Garcia Pagans, Neeraj Kharpate, Philip Hand, James Richardson, Dr. Henric
Qlik Sense: Advanced Data Visualization for Your Organization
- Qlik Sense: Advanced Data Visualization for Your Organization
- Table of Contents
- Qlik Sense: Advanced Data Visualization for Your Organization
- Credits
- Preface
- 1. Module 1
- 1. Qlik Sense® and Data Discovery
- 2. Overview of a Qlik Sense® Application's Life Cycle
- 3. Empowering Next Generation Data Discovery Consumers
- 4. Contributing to Data Discovery
- 5. Authoring Engaging Applications
- 6. Building Qlik Sense® Data Models
- 7. Qlik Sense® Apps in the Cloud
- 8. Extending the Qlik® Analytic Platform
- 9. Administering Qlik Sense®
- 10. Sales Discovery
- 11. Human Resource Discovery
- 12. Travel Expense Discovery
- 13. Demographic Data Discovery
- 2. Module 2
- 1. Getting Started with the Data
- Introduction
- Extracting data from databases and data files
- Extracting data from Web Files
- Activating the Legacy Mode in Qlik Sense® desktop
- Extracting data from custom databases
- Invoking help while in the data load editor or the expression editor
- Previewing data in the Data model viewer
- Creating a Master Library from the Data model viewer
- Using a Master Library in the Edit mode
- 2. Visualizations
- Introduction
- Creating Snapshots
- Creating and adding content to a story
- Adding embedded sheets to the story
- Highlighting the performance measure in a bar chart
- Associating persistent colors to field values
- Using the ColorMix1 function
- Composition
- Relationships
- Comparison
- Distribution
- Structuring visualizations
- 3. Scripting
- Introduction
- Structuring the script
- Efficiently debugging the script
- Packaging the code in script files
- How to use sub routines in Qlik Sense®
- Optimizing the UI calculation speed
- Optimizing the reload time of the application
- Using a For Each loop to load data from multiple files
- Using the Concat function to store multiple field values in a single cell
- 4. Managing Apps and User Interface
- Introduction
- Publishing a Qlik Sense® application created in Qlik Sense® desktop
- Creating private, approved, and community sheets
- Publishing a Qlik Sense® application to Qlik Sense® cloud
- Creating geo maps in Qlik Sense®
- Reference lines in Sales versus Target gauge chart
- Effectively using the KPI object in Qlik Sense®
- Creating Tree Maps
- Creating dimensionless bar charts in Qlik Sense®
- Adding Reference Lines to trendline charts
- Creating text and images
- Applying limitations to charts
- Adding thumbnails – a clear environment
- Navigating many data points in a scatter chart
- 5. Useful Functions
- Introduction
- Using an extended interval match to handle Slowly Changing Dimensions
- Using the Previous() function to identify the latest record for a dimensional value
- Using the NetworkDays() function to calculate the working days in a calendar month
- Using the Concat() function to display a string of field values as a dimension
- Using the Minstring() function to calculate the age of the oldest case in a queue
- Using the Rangesum() function to plot cumulative figures in trendline charts
- Using the Fractile() function to generate quartiles
- Using the FirstSortedValue() function to identify the median in a quartile range
- Using the Declare and Derive functions to generate Calendar fields
- Setting up a moving annual total figure
- Using the For Each loop to extract files from a folder
- Using the Peek() function to create a currency Exchange Rate Calendar
- Using the Peek() function to create a Trial Balance sheet
- 6. Set Analysis
- Introduction
- Cracking the syntax for Set Analysis
- Using flags in Set Analysis
- Using the = sign with variables in Set Analysis
- Point in time using Set Analysis
- Using comparison sets in Set Analysis
- Using embedded functions in Set Analysis
- Creating a multi-measure expression in Set Analysis
- Using search strings inside a set modifier
- Capturing a list of field values using a concat() function in Set Analysis
- Using the element functions P() and E() in Set Analysis
- 7. Extensions in Qlik Sense®
- 8. What's New in Version 2.1.1?
- Introduction
- Using the visual exploration capability in Qlik Sense® 2.1.1
- Defining variables in Qlik Sense®
- Exporting stories to MS PowerPoint
- Using the Qlik Dev Hub in Qlik Sense® 2.1.1
- Using Extension editor in Qlik Dev Hub
- Using Qlik Dev Hub to generate mashups
- Embedding Qlik Sense® application on a website using a single configurator
- Using the Qlik DataMarket
- Creating dynamic charts in Qlik Sense®
- Using Smart Search
- Using smart data load profiling
- Conclusion
- A. Appendix
- 1. Getting Started with the Data
- 3. Module 3
- 1. Getting Ready with Predictive Analytics
- 2. Preparing Your Data
- 3. Exploring and Understanding Your Data
- 4. Creating Your First Qlik Sense Application
- 5. Clustering and Other Unsupervised Learning Methods
- 6. Decision Trees and Other Supervised Learning Methods
- 7. Model Evaluation
- 8. Visualizations, Data Applications, Dashboards, and Data Storytelling
- 9. Developing a Complete Application
- A. Bibliography
- Index
Qlik Sense provides a host of statistical functions that can be put to effective use based on requirements in user reports. At a recent implementation, one of the requirements that popped out was to divide the data values into four quartiles. Quartiles are equivalent to percentiles which divide the data into four groups.
The first quartile is determined by every value which is equal to and less than the 25th percentile. The second quartile is determined by every value which is between the 25th and the 50th percentile. The third quartile is determined by every value which is between the 50th and the 75th percentile. The fourth quartile will be all the data values above and beyond the value of 75th percentile.
In order to generate quartiles in Qlik Sense, we make use of the Fractile() function. The following recipe explains the process.
For the sake of this recipe we create a hypothetical situation and make use of an inline data load which gives a case level information for an insurance company. Load the following script in Qlik Sense:
Case: LOAD * INLINE [ CaseID,Value,Status 101,1500,Active 102,1800,Active 103,800,Closed 104,2590,Closed 105,3500,Closed 106,1200,Active 107,5600,Active 108,8000,Closed 109,5960,Closed 110,5000,Active 111,4000,Active 112,2500,Active ];
- Click on App overview under the Navigation dropdown and create a new sheet.
- Enter the Edit mode by clicking on
. - Drag the Table object on to the sheet.
- Add the following calculated dimension and label it
Quartile:=If (Value <= Fractile (TOTAL Value, 0.25), 'Quartile 1', If (Value <= Fractile (TOTAL Value, 0.50), 'Quartile 2', If (Value <= Fractile (TOTAL Value, 0.75),'Quartile 3', 'Quartile 4')))
- Add second dimension
CaseID. - Add the following measure and label it
Value:Sum(Value)
- Under Sorting, promote
Valueto the top and sort it as numeric descending. - The resultant table would be as follows:
- As seen in the preceding screenshot, each
CaseIDvalue is now grouped under the Quartile.
The Fractile () function finds the value corresponding to the stated quartile in the range of the data values given by the expression. For example, a Fractile (TOTAL Value, 0.25) works in the following way.
A value corresponding to the 25th percentile is calculated. The total qualifier disregards the chart dimensions.
In our calculated dimension, every CaseID having the value below the 25th percentile mark is tagged as Quartile 1, between 25th and 50th as Quartile 2, and so on.
We can make use of a distinct qualifier inside the Fractile() function. In such a case, only the unique values of the field Value are evaluated.
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