What's New?

March 1, 2021

March 1, 2021

New Features

We've been focusing on improving our data exploration capabilities and have added some features making it easier to build projects with big datasets and dive straight into important aspects of your analysis. On top of this, we are working on making Graphext a more powerful data cleaning and preprocessing tool.

01. Bigger Projects

Projects in Graphext just got bigger. Now, you can create projects using datasets with hundreds of thousands of rows like this one that Victoriano created using 215 thousand rows of data about salary structures in Spain.

To achieve this, we hide the links between nodes when building larger network visualizations. For the technically minded among us - we moved the storage of network links from JSON into our own database and only draw them for local neighbourhoods.

This means that you can still show connections between a node and its neighbours on larger Graphs. We are really excited about the possibilities that this feature opens up.

How does it work?

- Start from your team's Dataset panel.

- Upload a large dataset.

- Build any type of project using it.

- Start discovering communities inside of your enormous network!

02. Shortcut to Compare

Using the dropdown menu inside of your sidebar variable cards, you can now jump straight into the Compare panel to discern which other variables best explain the difference between values belonging to this variable. Select Open in Compare from the menu list to start understanding your data using compare charts.

We added this feature to make it quicker and simpler for you to jump into a more intricate investigation of the distinguishing features of values in your data.

How does it work?

- Start from your project's Graph, Details or Trends panel.

- Find the variable you want to inspect.

- Click the three dots from the top right of the variable card.

- Choose Open in Compare from the menu list.

- Use the compare charts to pick out the defining features of your values.

03. New Variable Types

We've added the ability to set the type of your variables in more detail. Boolean, Sex and Currency are among the new variable types that you can now make use of in Graphext. From inside your team's Dataset panel, inspect a dataset and use the dropdown under a variable name to set its type to one of the nine options now available.

How does it work?

- Start from your team's Dataset panel.

- Inspect a dataset.

- Click on the dropdown menu underneath a variable name to change its type.

- Choose a new type from the menu list.

- The type of this variable will now update.

04. More Projects for Public Users

We've been delighted with the number of new people using Graphext recently. As a result, we've decided to open up the limit of projects that users can create with a free account. Graphext Public users can now create up to 4 projects.

How does it work?

- Sign up for a Graphext Public account .

- Check out our guides on Getting Started.

- Start analysing your data using Graphext.


Fixes and Improvements

- Corrected a problem with clustering configuration in Text → Keyword Co-Occurrence projects.

- Fixed an issue with segment names when performing intersection operations.

- Solved a query text error that was occurring when users searched inside the Graph.

- Added functionality so that longer variable names appear complete rather than incomplete in the Compare panel.

- Fixed issue with dataset vectorization - layout_datset step - as this was occasionally failing on some datasets.


Stories Worth Sharing

01. Super Bowl Ads

Inspired by an analysis by Ryan Best at FiveThirtyEight, Victoriano and Andy clustered 20 years of Super Bowl commercials. They were interested in which popular brands used characteristics like comedy, sex, patriotism and animals to sell their products. Read More.

02. Predicting Employee Behaviour

Our team have been working on a guide to explain how Graphext can be used to interpret the characteristics, attitudes and preferences of employees. This guide looks at how a prediction model built-in to Graphext might be used to understand why sub-communities of people left their jobs. Read More.