🎁 New Features

You can now copy datasets and projects between Graphext teams.

We've also made it easier to inspect text or quantitative values in greater detail with new text tooltips in data tables and the ability to save variables that capture zoom-ins on quantitative ranges.

We're also pretty excited to announce that you can now customize the thumbnails inside your project card - using uploads or new Graph captures.

01. Move + Copy | Datasets + Projects

You can now move or copy datasets across workspaces as well as making copies of key projects. Click the menu icon from your Graphext team workspace and choose 'Move to' or 'Make a copy in' to give other teams access to your data and analysis.

We've added this feature to make it easier for you to collaborate on and share important analyses that you create. Making changes in a copied project won't affect the state of your original project.

How can I start using it?

• Find a dataset or project in one of your Graphext teams.

• Click the 3 dots to bring up the menu options.

• For datasets - choose either Move to or Make a copy in. Then, choose a team destination.

• For projects - choose Make a copy in. Then, choose a team destination.

• Click Accept and head over to your destination team to inspect your relocated resources.

02. Changing Project Thumbnails

You now can upload, regenerate or enlarge your project thumbnail images! Head to your project settings, click on the project image and choose how to set your new one!

The size of project thumbnails is set to optimal dimensions - meaning that any image you set is guaranteed to look snazzy!

How can I start using it?

• Open your project info.

• Click the current image associated with your project.

• Choose to either upload, enlarge or regenerate your project thumbnail.

• Save your changes and head to your workspace to check your changes.

03. Save Zoomed In Quantitative Ranges

Zooming in on specific value ranges isn't a new Graphext feature. But up until this point - any zoom-ins you make on quantitative variables will disappear as soon as you reload a project. Now ... they won't!

Zooming in on quantitative ranges helps you account for extreme values in your data. Zoom in on specific ranges to explore data distribution between two points.

How can I start using it?

• Choose a quantitative variable in your project.

• Set a filter range by clicking and dragging on the variable sidebar chart.

• Click the 3 dots and choose Zoom In from the menu list.

• That's it ... your new zoomed-in variable will be saved to your project.

04. Inspect Text with Tooltips

We've added tooltips to the table in your Details panel - helping you inspect the full content of text in your data. Hover over a text value to reveal its full content.

You can also copy the content of a text value by right-clicking on it and selecting Copy!

How can I start using it?

• Head over to the Details panel of your project.

• Find a text variable and hover over it.

• Check out the full content of that value inside the tooltip.

05. Remove Any Variable

Now you can remove any variable from your project. Click the right menu next to the variable card in your project sidebar and choose Remove from the menu list.

Cleaning up your analysis is a useful habit to get into. Removing a variable from a project will delete any reference to it in all of your project panels.

🐞 Bug Fixes & Improvements

Core Improvement

When filtering data in your projects, your sidebar charts will now jump to Relative mode by default. Relative mode means that data in your selection is shown in proportion to the distribution of values in your whole dataset.

We feel that Relative mode gives a clearer indication of patterns in your data but you can prevent automatic relative mode by choosing another option from the Relative | Absolute dropdown at the top of your project's right sidebar.

• Added the ability to view and edit the project recipe from the project settings window.

• Removed automatic filtering on datasets of any size so that - by default - projects will be built using the full dataset.

• Fixed a bug stopping labels from appearing when users hover above nodes in the Graph.

• The wrong factor tagged columns in Cluster Flow

• Fixed a bug stopping users from sending data to the trash from panels outside of the Graph.

• Fixed a bug causing mixed JSON data to crash on upload.

📖 Stories worth Sharing

Sentiment Analysis & The Billboard Top 100: The Changing Mood of Popular Music

We used sentiment analysis to model 5100 Billboard chart-toppers between 1964 and 2015. Our analysis predicted whether song lyrics were positive, negative or neutral as well as detecting the topic and intent behind the most popular tunes in music history.

🎁 New Features

You can refresh and recreate Graphext projects created with data from Google Sheets or database integrations. On top of this, it's now simple to change the color of values from anywhere in your projects and you can switch color palettes inside of your project settings!

01. Refresh Data Integrations & Recreate Projects

We've added the ability to refresh and recreate projects built with integrated datasets from Google Sheets, SQL databases and more remotely hosted sources.

Find a project you've created with integrated data and choose to Refresh and Recreate the project. Graphext will then retrieve a new - up to date - dataset from your source and automatically create a new project using the data.

How can I start using it?

• Make sure you've created a project using data that you've integrated with Graphext from Google Sheets or a remotely hosted database.

• Find the project inside your Graphext workspace and click the 3 dots on the project card.

• Choose 'Refresh and Recreate' from the menu list.

• Graphext will recreate your project using up to date data from your integrated source.

• Graphext will store a new dataset in your Datasets panel containing up to date data from your integrated source.

02. Changing Colors Across Graphext: Trends & Compare

Your Compare and Trends charts now support the full spectrum of variable colors. Not only this, but you can change the color of any categorical value across the interface.

Recently, we extended the number of automatically generated variable colors but - up until now - these weren't available in Compare or Trends charts. Now, you can see the full range of colors across all interface panels as well as changing these colors directly in either Compare or Trends charts.

How can I start using it?

• Inside a project, open up Compare and add values into your charts.

• Click on a color dot associated with a value from the top of your panel.

• Choose a new color using the color picker and click OK.

03. Switching Color Palette

You can now switch the color palettes used to represent data in your projects. Color is crucial to grouping and spotting connections between data. Head over to the Appearance tab inside your project settings to change color palettes.

Choose Horus for the standard Graphext color palette. Choose Osiris for a more vivid color palette. We'll be adding more color palettes to this list very soon!

How can I start using it?

• Navigate to the Appearance tab inside your project settings.

• Select a color palette from the dropdown list.

• Click Save.

• That's it. Check out the new colors representing data in your project.

04. Expand Charts in Compare and Correlations

You can now expand charts in Compare & Correlations. Because expanded charts are BIGGER, they let you inspect more values at the same time.

To expand Compare or Correlations charts, click on the 3 dots from the top right of your chart card and choose Expand chart. Insights that you save from expanded charts will also be bigger and contain more values than standard-sized charts.

How can I start using it?

• Inside a project, generate charts in either Compare or Correlations.

• Click on the 3 dots inside a chart card.

• Choose Expand chart from the menu list.

• Check out your chart in all of its glory!

🐞 Bug Fixes & Improvements

🍏 Core Improvement

We've improved the way that data is presented inside Trends charts. You can now represent values in time-series charts using a Cumulative Sum - which works like a running total. Choosing Cumulative Sum - instead of a count or an average - means that the y-axis in your Trends charts can now represent the total sum of data as it grows over time.

• Added the ability for users to set up more than one SQL integration.

• Fixed an issue with Amazon S3 Data Integrations.

• Fixed a bug in the Text - Keywords analysis type.

• Fixed a bug with the Social Media - Analyze Author Bios analysis type.

• Fixed an issue with dataset names containing a long sequence of characters.

📖 Stories worth Sharing

A Beginners Guide to Market Segmentation

Market Segmentation means splitting your customer base into distinct communities based on the similarity of their features. This guide walks through the fundamental techniques, tools & types of market segmentation and shows you how to perform advanced market segmentation with Graphext. Read more.

A Guide to Clustering Supermarket Transactions

This guide is intended to walk you through the process of creating a clustering model to group your data. We'll build a project using a dataset of 1000 supermarket transactions from stores in Myanmar and expose the supermarket's most valuable market segment. Read More.

How to Study Brand Conversations with Advanced Text Analysis?

How can we use text analysis of data from Twitter to improve our understanding of markets? This is the question prompting Paul, a strategist in our business team, to scrape tweets about Lloyds bank and conduct a Twitter topic analysis using advanced NLP and network creation. Read More.

🎁 New Features

Graphext is now more powerful at text analysis. We've added support for the incredible range of NLP models at Hugging Face including intent detection and sentiment analysis. On top of this, we've built a new enrichment to group location values that are spelt differently

01. Support for Hugging Face Models

We've integrated Hugging Face models with Graphext. You can now build, train and deploy state of the art models for common NLP tasks including intent detection, sentiment analysis and token classification. Hugging Face also has models for translation, image classification and speech recognition.

Check the Hugging Face model documentation to browse the models you can now use in Graphext, check how to use them and try them out! We'll soon be adding an easier way to deploy Hugging Face models on your text but for now - open up the code editor and paste in a code snippet from our docs.

How can I start using it?

• Start building a project with data containing some text.

• Open up the code editor.

• Somewhere towards the end of the script - copy and paste the code snippet from our docs.

• Replace the name of the model with the name of your chosen model.

• Don't forget to add parameters if you need them!

• Execute the project.

02. New Enrichment: Extract URL Components

When working with URLs in your data, it is often useful to extract new variables containing the domain, path and schema of the URL. Using this enrichment you can parse the URL values in your data and use the components of a URL to filter your data.

After you built a project that extracts URL components - look for the new variables in your data; path, domain, query, schema and more ...

How can I start using it?

• Select Extract URL Components as an enrichment using the Data Enrichment tab during your project setup.

• Tell Graphext which column contains the URL values in your data.

• That's it. Open the project and look out for the new variables containing the components of your URL values.

03. New Enrichment: Standardize Locations

Variation in the way that people write and record location data can make for a messy analysis.

Similar to the way that our Group Similar Spellings enrichment works, standardizing location data means grouping variations that refer to the same place but are spelt differently.

For instance, without deploying this enrichment, 'Manchester' and 'Manchester, UK' would be considered as two separate places. Our enrichment has been designed to let you collect these two values and filter your data more accurately with locations.

How can I start using it?

• Select Standardize Locations as an enrichment using the Data Enrichment tab during your project setup.

• Tell Graphext which column contains the location values you want to group.

• Set a threshold to control the strength of your merges.

• That's it. Open the project and look out for the new merged variable.

🐞 Bug Fixes & Improvements

• Fixed a bug preventing the saving of new team names.

• Fixed a bug causing quantitative filter ranges to jump unexpectedly.

• Fixed a bug allowing incorrectly formatted data sources to be referenced (not an URL).

📖 Stories worth Sharing

01. Using Mutual Information to Cluster Variables and Discover the Associations Between Survey Questions

Our team set out to build a type of analysis that could be used to measure the strength of association between variables in a dataset. Read more.

02. Mapping New York's Airbnb Listings

Our team set out to build a type of analysis that could be used to measure the strength of association between variables in a dataset. Read more.

🎁 New Features

It's been a colorful month ... we've added the ability to change the color of any categorical variable and extended the spectrum of colors automatically generated for your values. We've also added a new enrichment letting you fill missing values in your data!

01. Extended Variable Colors

We've increased the scale of our default color palette to include 30 colors!

On top of this - clicking to show more categorical values will add appropriate color to nodes in your Graph that would previously have been grey.

Color is a powerful analytical tool and lets you quickly identify the features of your data points inside visualisations. Up until now, we've used grey to color any categorical value beyond the 10 most frequently occurring.

We believe that more color means more clarity. Clicking to see more categorical values will extend the colors presented in your Graph.

How can I start using it?

• Open a project with a categorical variable that contains many values.

• Apply color mapping to this variable in your project's Graph.

• Click to show moreshow more values.

• Notice how your color palette extends inside the Graph and variable sidebar chart.

02. Changing Colors For Any Categorical Value

You can now change the color of any categorical value!

Although every value in your categorical variable will be automatically assigned a color - you can change these by editing the variable and selecting a new one using the color picker.

How can I start using it?

• Open up a project and find a categorical variable.

• Click the edit button at the top of your variable card.

• Now, click the color picker icon.

• Choose a new color and save your changes!

03. New Enrichment: Fill Missing Values

We've built an enrichment to fill missing values in your data. Missing values can be annoying, misleading and disruptive to your analysis. Replacing them with specific values can help to clean up and prepare your dataset for analysis.

Choose Fill Missing Values from the data enrichment tab inside of the project setup wizard to start replacing missing values. Then, select a variable with missing values and tell Graphext how you would like to fill these values. You can choose from options like using a constant value, using the most or least frequently occurring value and using the column's minimum or maximum value. Look for the replaced variable in your transformed dataset.

If you'd prefer, you can always use a different enrichment to predict missing values!

How can I start using it?

• Start building a project using a dataset with missing values.

• Choose Fill Missing Values from the data enrichment tab inside your project setup wizard.

• Tell Graphext which column contains your missing values.

• Choose how you want to replace your missing values.

• That's it. Look for the replaced replaced variable in your transformed dataset.

04: Dataset Info: Sources & Descriptions

We've added space to describe your dataset and reference it's original source inside Graphext.

Context is always important but when dealing with data - it is essential. Referencing your data leaves behind a trail that other team members or researchers can trace to validate or continue your analysis.

To start describing and referencing a dataset, find it from inside of your team's Graphext workspace. Then open the dataset info menu using the 3 dots on the far right of your dataset card. Enter the source URL and write a description then click on the dataset to see this information listed above your data.

How Can I Start Using It?

• Find a dataset inside your Graphext workspace and select the three dots from the far right of the dataset card.

• Choose Dataset Info from the menu list.

• Enter a source URL and write a short description.

• Save your changes.

🐞 Bug Fixes & Improvements

• Added the ability to change the name of a team.

• Fixed an issue with info cards not appearing after clicking on a node in the Graph.

• Fixed a bug causing the creation of a new project to fail after moving some data to the trash.

• Added a menu button to instantly open a variable in the Correlations panel.

• Added a legend to list variables. A white circle indicates that white-white-coloured nodes refer to data belonging to more than one list category.

📖 Stories worth Sharing

01. Segmenting 1000 Supermarket Customers Using Sales Data

Our team clustered 1000 supermarket sales in order to segment customers according to their buying habits.

Graphext | Graphtex | Graphnext: Grouping Similar Spellings Using Chars2Vec and Agglomerative Clustering

'España' and 'Españha' are just spelling variations. We built a way of grouping words spelt differently but referring to the same concept and made it available alongside any type of analysis you perform with Graphext.

Getting Started Videos

We've created a collection of Getting Started videos to help guide you in using Graphext's interface panels and core features.

🎁 Correlations

Our new Correlations panel lets you study the relationships between variables. Find it inside of any new Graphext project you create and start discovering the associations in your data.

What is Correlation?

Correlation is a statistical concept referring to the relationship between two variables. We can use correlation to understand whether observing a change in variable A will also mean observing a change in variable B.

Positive correlations refer to a relationship between two variables in which both variables move in the same direction. Negative correlations refer to a relationship between two variables in which an increase in one variable is associated with a decrease in the other.

“Correlation doesn't imply causation, but it does waggle its eyebrows suggestively and gesture furtively while mouthing 'look over there.” - Randall MunroeRandall Munroe

The Correlations Panel

Inside your project's Correlations panel you'll find a series of charts as you would inside the Compare panel. Choose a variable to study using the search bar and Graphext will generate charts showing the correlation between this variable and other variables in your data.

Use correlation charts to understand how the values of one variable are associated with the values of another. You can export charts from the Correlations panel or save them as insights.

Reading Correlation Charts

Charts in your Correlations panel reveal the number of data points where values from two variables meet. Your y-axis represents values from the variable in your search bar and the x-axis represents values from the correlated variable - labelled in the top right of each card.

The blue circles in your correlation charts represent the number of data points at each value intersection. Bigger and brighter circles represent a higher number of data points at an intersection whereas lower and duller circles represent fewer data points at an intersection.

A strong positive correlation would be signified by a trend of big & bright circles moving diagonally upwards from left to right 📈

A strong negative correlation would be signified by a trend of big & bright circles moving diagonally upwards from right to left 📉

The Docs

Correlation is a powerful tool but its key concepts aren't always self-explanatory. Here are a couple of articles to help you use and understand Correlations.

How To | Correlations

Start here. This article walks you around the new Correlations panel - pointing out the different features and showing you how to use them.

Technical Docs | Understanding Correlation

Read about the concepts key to understanding correlation. In this article, we explain how correlation works, the different types of correlation alongside pointing out the common pitfalls associated with misinterpreting correlation.

How can I start using it?

• Build a Graphext project.

• Once your project is ready, navigate to the Correlations panel.

• Chose a variable using the search bar.

• Study the charts to inspect the correlation between this variable and other variables in your data.

• Change the collection of variable charts presented using the dropdown menu at the top left of your Correlations panel.