What's new on Hex

The modern analytics workspace for data teams

New
November 23, 2021

πŸ™ GitHub package import

Make use of the utility code you've got stashed in GitHub or get access to functions in private repos! All you need to do is connect your GitHub account to Hex to access the files and function you need for your analysis!

New
November 23, 2021

🚻 Share projects with a group

Gather your #squad, you can now subset users into groups! Groups make sharing projects with a set of folks easy; plus we'll be adding more abilities and permissions to groups soon, stay tuned!

New
November 23, 2021

πŸͺ‘ Display tables for SQL cells

Having to add a Display Table right after previewing the output of a SQL cell always felt a little repetitive in the redundancy department. Now, not only can you add the output of your SQL table directly to your apps, you can also enrich that output as a fully-fledged Display Table!

New
November 09, 2021

πŸ’… Conditional Formatting in Table Display Cells

Following up on last month's all-new Table Display cell that included column string formatting (for currency, percentages, etc.), this month we're landing Conditional Formatting. You can now color-code tabular data according to multiple rules that can use numerical, string, boolean, and date expressions β€” no more Pandas style tables! Check out all the options in the docs.

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New
November 09, 2021

πŸ“œ Edit History

We've always had version history in Hex to let you restore previous iterations of your projects, but now we're releasing a rich edit history to let you know what actually has recently changed. You'll now find all edits, versions, and comments for a project in one unified chronological timeline.

We've also changed how you access this historyβ€” You'll no longer see it in the top bar, find it instead in the "History & versions" sidebar tab. See the docs for the full story.

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New
November 09, 2021

🧞‍♀️ Dataframe Columns in Input Parameters

If you've ever created a code cell that just runs input_list = input_df['column_of_interest'].unique() to feed into an Input parameter, you'll be excited about this one. Dynamic Input parameters can now select a dataframe column as the value source, without needing to generate a list!

This is a big time saver and helps keep apps tidy with fewer unnecessary code cells and one-off arrays.

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