Using comparison sets in Set Analysis
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
The following figure is of a stacked bar chart, a standard way of comparing separate entities. Each value that you select is displayed as a segment in each bar by year:
Using a comparative analysis lets you group the separate selections dynamically, so that you can compare them against each other. In the preceding example we can group together Plum and Apple versus Fig and Orange.
For the purpose of this recipe,we will make use of an inline data load which gives yearly sales information for different fruits. Load the following script in the Qlik Sense data load editor:
Data:
LOAD * INLINE [
Fruit, Year, Sales
Apple, 2013, 63
Apple, 2014, 4
Cherry, 2014, 1150
Cherry, 2013, 1180
Fig, 2013, 467
Fig, 2013, 374
Fig, 2014, 162
Orange, 2013, 131
Orange, 2013, 145
Orange, 2014, 102
Pear, 2014, 489
Pear, 2014, 782
Plum, 2013, 148
Plum, 2014, 412
];
DataIslandFruit:
LOAD * INLINE [
FruitAlt
Apple
Cherry
Fig
Orange
Pear
Plum
];- Drag a bar chart onto the content area and title it
Comparison Analysis. - Add Year as a dimension.
- Add the following expression and label it as
Group 1 Sales:Sum(Sales)
- Add the following expression and label it as
Group 2 Sales:Sum({<Fruit={$(=GetFieldSelections(FruitAlt))}>}Sales) - Under Appearance | Colors and legend switch on the Show legend option.
- Create a Filter pane object and add the first dimension as Fruit. Label the dimension as
Group 1. - Add FruitAlt as the second dimension to the Filter pane and label the dimension as
Group 2. - The final chart should resemble one of the following images if you have already made the selections to test the comparative analysis.
The following is an example where no selections are made:
The following is an example where selections are made:
The second table we loaded is what's known as a data island, this table is not connected to the rest of the data model in any way. However, we can use its contents in our Set Analysis expression to compare different groups of the same field.
The first expression is completely standard. The second expression gives the total sales where the Fruit field (part of the complete dataset) matches the values selected in the FruitAlt field (part of the disconnected data island). This method allows us to select groups of data for aggregation in our graph that we can not do normally by effectively breaking the association (green, white, and grey) using Set Analysis.
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