Using the FirstSortedValue() function to identify the median in a quartile range
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
Our next task is to find a claim corresponding to the median value in each quartile. A median is nothing but a value corresponding to the 50th percentile. We can achieve this using the FirstSortedvalue() and median() functions.
- Go to the Edit mode by clicking on
. - Select the table we created just now in the preceding recipe.
- Edit the CaseID dimension and put in the following calculation:
=if(Match(CaseID, '$(=FirstSortedValue(distinct{<Value={"<=$(=Median({<Value= {'>=$(=fractile(Value, 0))<=$(=Fractile(Value, 0.25))'}>} Value))"}>} CaseID, -Value))', '$(=FirstSortedValue(distinct{<Value={"<=$(=Median({<Value= {'>$(=fractile(Value, 0.25))<=$(=fractile(Value, 0.5))'}>} Value))"}>} CaseID, -Value))', '$(=FirstSortedValue(distinct{<Value={"<=$(=Median({<Value= {'>$(=fractile(Value, 0.5))<=$(=fractile(Value, 0.75))'}>} Value))"}>} CaseID, -Value))', '$(=FirstSortedValue(distinct{<Value={"<=$(=Median({<Value= {'>$(=fractile(Value, 0.75))<=$(=fractile(Value, 1))'}>} Value))"}>} CaseID, -Value))' ), CaseID, Null() ) - Uncheck Show Null Values for CaseID.
- The resultant table will look like this:
- As you can see, every quartile is now showing only the claim corresponding to the median value in each quartile.
The calculated dimension for CaseID gives us the claims corresponding to the median values in each quartile. As you can see, a Match() function is being used to match the CaseID with each of the four expressions within.
Let's decipher the first expression inside the Match() function:
'$(=FirstSortedValue(distinct
{<Value={"<=$(=Median({<Value={'>=$(=fractile(Value, 0))<=$(=fractile(Value, 0.25))'}>} Value))"}>} CaseID, -Value))'The details of the expressions are as follows:
- The innermost set gives us the range of values which are between the 0th quartile value and the 25th Quartile value
- The
Median()function then gives us the value which lies at the median of this range - The
FirstSortedvalue()returns the value of the output field (CaseID) based on the sorted values of the value field
In situations where the number of claims in any quartile is an even number, there will be two claims which will correspond to the median values. In such a scenario, we want to select only the claim which is higher in the sorting order. Hence, we use a –Value as the sort weight.
Similar to medians, we can derive the quartiles within quartiles using the Fractile() function.
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