Showing 4 open source projects for "input-leap"

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  • 1
    React DayPicker

    React DayPicker

    Date picker component for React

    ...Use your own translation strings or import those from moment.js, if you use it. react-day-picker is designed to cover the most common needs for a date picker in web applications. This package includes the DayPicker component to render the calendar (see: basic concepts, API), and the DayPickerInput component to render an input field opening the DayPicker in an overlay.
    Downloads: 5 This Week
    Last Update:
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  • 2
    Superstruct

    Superstruct

    A simple and composable way to validate data in JavaScript

    This project is a lightweight validation library for JavaScript and TypeScript that helps you define data “shapes” and validate runtime values against them. Instead of relying only on compile-time typing, it focuses on the reality that many apps receive unknown input from APIs, forms, and external systems, and those values need runtime checks. Its API is intentionally familiar if you’ve used TypeScript, Flow, Go structs, or GraphQL schemas, but the output is oriented around runtime correctness. When validation fails, it can throw or return detailed errors that are useful both for debugging and for communicating issues back to end users or API clients. ...
    Downloads: 2 This Week
    Last Update:
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  • 3
    D-Tale

    D-Tale

    Visualizer for pandas data structures

    ...What was originally a perl script wrapper on top of SAS's insight function is now a lightweight web client on top of Pandas data structures. To help guard against users loading the same data to D-Tale multiple times and thus eating up precious memory, we have a loose check for duplicate input data. If you are running ipython<=5.0 then you also have the ability to adjust the size of your output cell for the most recent instance displayed. JupyterHub has an extension that allows to proxy port for user, JupyterHub Server Proxy.
    Downloads: 0 This Week
    Last Update:
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  • 4
    Facets

    Facets

    Visualizations for machine learning datasets

    The power of machine learning comes from its ability to learn patterns from large amounts of data. Understanding your data is critical to building a powerful machine learning system. Facets contains two robust visualizations to aid in understanding and analyzing machine learning datasets. Get a sense of the shape of each feature of your dataset using Facets Overview, or explore individual observations using Facets Dive. Explore Facets Overview and Facets Dive on the UCI Census Income...
    Downloads: 0 This Week
    Last Update:
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