🎁 New Features

You can now customize the values shown in Compare & Correlations charts. We've added a search bar to help you add important categories to these visualisations. 

We've also added a new color palette to your projects that uses a dynamic color scale that updates depending on the number of values belonging to a variable.

01. Add Custom Categories in Compare & Correlations

Up until now, charts in Compare and Correlations presented only the most frequently occurring values from a variable. You can now choose which values to present in these charts using the search bar at the top right of each chart card.

Open up Compare or Correlations and choose a chart with hidden values. Click the search bar from the top of the chart and add in your new value.

How can I start using it?

• Choose a Compare or Correlations chart featuring some hidden values.
• Click the search icon at the top of your chart. 
• Start typing the name of the value you want to add into the chart.
• Select the value and click the tick icon to add it into your chart.

02. New Color Palette: RE

We've added a new color palette to your projects. Re is slightly different to Horus and Osiris in that it offers a dynamic scale of colors that will update depending on the number of values belonging to a variable. 

Re is particularly useful when exploring a small to medium range of categorical values. Its colors move from light blue through orange and red to purple on a scale that is calculated according to the number of values in a category.

How can I start using it?

• Open up your project settings.
• Navigate to the Appearance tab. 
• Choose Re from the dropdown list of color palettes.
• Clicking Save will update the color palette in your project settings.

🐞 Bug Fixes & Improvements

• When you upload a new dataset - Graphext will now be able to tell the difference between Categorical values and Text values with greater precision.
• Your color palette will now be saved to your project settings. This means that closing then returning to the project will not affect your choice of color palette.
• We've improved the way URL variables are presented throughout your datasets and projects. URL variables will now be presented in the same way that categorical variables are presented. 

📖 Stories worth Sharing

01. What is Exploratory Data Analysis?

For our first Data Academy release - we've gone back to basics with Exploratory Data Analysis. This article covers what cleaning, transforming and enriching data means as well as explaining why different visualisation types can be useful for studying different types of variable relationships.