Mode release notes
Mode release notes

Python 3.9 and Updated Libraries Are Live Across All Notebooks




Mode now supports Python 3.9 in the standard Notebook environment.

In addition, popular libraries such as pandas, plotly, NumPy, matplotlib, and statsmodels have been updated and added to the standard environment. Visit our help site for a full list of the updated Python libraries.

R Version 4.2.0 and Updated Libraries Now Available!




Two new R updates are now live in Mode’s Notebook environment:

  • The current version of R has been updated from 3.6.1 to 4.2.0
  • R libraries have been updated including plotly, ggplot2, and stringr. For a full list of libraries visit our help docs

Make sure to test the compatibility of your notebooks and reports with these new updates. Happy analyzing!

New ways to manage visualizing large data fields




Manual Update Mode enables you to make multiple changes to your visualization without waiting for it to render after every alteration. In Manual Update Mode, you can make multiple changes, click Apply changes, and see all updates at once.

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You’ll also see guidance on how to stay within browser limits when you come up against them. When you try to pull in a field that surpasses the limits, you’ll see a popup with instructions on how to adjust your data and continue with your analysis.

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Read more about these updates here.

Update: Infrastructure Upgrades




Mode is performing infrastructure upgrades for Helix, Mode’s in-memory database. We are changing our backing storage technology to modernize our platform, and as a result, a few of the details about how Calculated Fields and visualizations are displayed will change.

Please note: In testing & evaluation, these changes were observable in just 0.25% of customer visualizations. Any changes are likely very minor. If you have additional questions on the specific changes, please contact the support team.

These infrastructure upgrades will be rolled out starting on Wednesday, September 28, 2022 and all customers will be on the new infrastructure by Thursday, October 6, 2022.

Python 3.9 and Library Updates Now in Edge




There are two new updates to Mode’s Edge environment.

  1. Python 3.9 has been added to Edge.
  2. Popular Python libraries such as pandas, NumPy, Matplotlib, and statsmodels have also been updated in Edge. See the full list of updated libraries on our help site.

Make sure to test your reports' and notebooks' compatibility before updates are rolled out to the standard notebook environment on October 25. Read this blog post for instructions on how to get started with Edge.

Top/Bottom N Filters Available in Visual Explorer




Top/Bottom N filters have been added as new filter types in Visual Explorer. Easily apply a top or bottom N filter to see the highest or lowest values in your dataset without writing additional code.

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Applying a top or bottom N filter can help you understand a new dataset faster by loading a small batch of data instead of the entire table.

Read more about top/bottom N filters here.

Conditional Formatting using Background Color




When applying conditional formatting, you can now add background colors to easily identify patterns and trends in pivot tables.

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With this improvement, you have the option to either add color to text or background. Simply click the Color channel and select Apply to text or Apply to background.

Read more about this improvement on our help docs.

Enhanced Data Prep with Data View




You now have more control over how you prep your data with our enhanced Data View in the SQL editor.

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We replaced our grid results with the new Data View. Here you can see your results, field information, and source SQL. In addition, you can now add calculated fields to prep your data before moving a visual exploration. Double click or drag on the navigation here to minimize or expand your results.

Read more about Data View here.

Update: July 8, 2022




This week we made an update to the PDF export loading modal.

  • If you experience a failed PDF export attempt, you will see a new modal informing you of the generation error.


Updated behavior of function in Calculated Fields

On Tuesday, July 5th, we will update the DATEDIFF function in Calculated Fields. The new functionality will more closely match the way this is calculated in common databases such as MySQL, Redshift, and SQL Server.

Currently, DATEDIFF uses complete partitions to estimate the date difference. It looks at the time difference between two dates in the specified time unit, and then returns the number of full units that have passed.

The new behavior will use incomplete partitions to estimate the date difference. It will count how many times the “clock” has crossed the threshold that increases the unit count for that specified time unit. For example, going from 23:59:59 to 00:00:00 will increase the day count by 1. See examples on our Help Site.

Please note: When this change is made, existing visualizations may change by one (1) unit, such as minutes, days, or weeks, if they were previously calculated using partial units. We recommend reviewing a few of your most commonly viewed reports that use DATEDIFF to see if the changes described above will impact the results.

If you determine that you need to make changes based on this updated functionality, you can do one of two things:

  • Move the logic out of the Calculated Field and into your query. This can be done at any time.

  • Wait until we roll out the changes on Tuesday, July 5th, and then make the appropriate adjustment to the Calculated Fields.

Please reach out to our Support team if you need help identifying potentially impacted reports.