Remove categories
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We've already seen category 6 hurricanes – scientists want to make it official

Hacker News

Intensifying storms may warrant a new category of hurricane wind speeds.

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Sanitizing the Data – Merging Disparate Data Sources on Common Categories

Analytics Vidhya

The post Sanitizing the Data – Merging Disparate Data Sources on Common Categories appeared first on Analytics Vidhya. Introduction In general terms, this article is going to be about data cleansing. Specifically, the process I would like to explore is actually a.

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RZK: Experimental proof assistant for synthetic ?-categories

Hacker News

An experimental proof assistant based on a type theory for synthetic ∞-categories. GitHub - rzk-lang/rzk: An experimental proof assistant based on a type theory for synthetic ∞-categories.

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Applied Category Theory: Textbook (2019)

Hacker News

MIT OpenCourseWare is a web based publication of virtually all MIT course content. OCW is open and available to the world and is a permanent MIT activity

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New Study: 2018 State of Embedded Analytics Report

Why do some embedded analytics projects succeed while others fail? We surveyed 500+ application teams embedding analytics to find out which analytics features actually move the needle. Read the 6th annual State of Embedded Analytics Report to discover new best practices. Brought to you by Logi Analytics.

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? Chart Options for When You Have Lots of Categories

FlowingData

When you visualize a dataset with a lot of categories, a long bar chart can be a bit much, so here are simple options to make it less jumble-ish. Welcome to The Process , where we look closer at how the charts get made. This is issue #251. I’m Nathan Yau. Become a member for access to this — plus tutorials, courses, and guides.

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How to Create Custom Categories in Tableau: Engagement Analysis

phData

As explained in this topic’s sister blog , effectively splitting data into categories is very important for effective analysis. These custom categories are required to be MECE (Mutually Exclusive and Collectively Exhaustive) in most business scenarios. As you can see, the conditions in these categories have considerable overlap.

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How to Build Data Experiences for End Users

End users fall into 4 different categories along the data literacy continuum when it comes to their skill level with data: Data challenged: Users have no-to-low levels of analytics skills or data access. Product managers need to research and recognize their end users' data literacy when building an application with analytic features.