Showing 4 open source projects for "maps"

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  • 1
    rayshader

    rayshader

    R Package for 2D and 3D mapping and data visualization

    This is an R package designed for producing beautiful and interactive 2D and 3D visualizations — especially maps and terrain renderings — using elevation/gridded data and ray-tracing / hill-shading methods. At its core, rayshader takes a matrix of elevations and applies shading, texture, ambient occlusion, overlays, and light modeling (ray shade, lambertian shading, etc.) to produce realistic relief maps. Users can rotate, zoom, and animate the scenes or script camera trajectories...
    Downloads: 3 This Week
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  • 2
    R Color Palettes

    R Color Palettes

    Comprehensive list of color palettes available in R

    This repository is a curated collection of color palettes crafted or curated for data visualization in R. The goal is to provide designers, data scientists, and R users with aesthetically pleasing, perceptually consistent color schemes that work well for plots, maps, and graphics. The repo contains static files listing palette definitions (e.g. hex codes, named hues), sample visualizations showing how each palette performs under different contexts (categorical, sequential, diverging...
    Downloads: 0 This Week
    Last Update:
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  • 3
    Shiny

    Shiny

    Build interactive web apps directly from R with Shiny framework

    Shiny is an R package from RStudio that enables users to build interactive web applications using R without requiring knowledge of JavaScript, HTML, or CSS. It allows statisticians and data scientists to turn their analyses into fully functional web dashboards with reactive elements, data inputs, visualizations, and controls, making data communication more effective and dynamic.
    Downloads: 0 This Week
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  • 4
    NYC Taxi Data

    NYC Taxi Data

    Import public NYC taxi and for-hire vehicle (Uber, Lyft)

    ... of pickups/dropoffs). It also contains example analyses—spatial and temporal visualizations like maps, time-series plots, and hotspot detection—highlighting insights such as patterns of demand, peak times, and geospatial distributions. The repository is often used as a benchmark dataset and example for teaching, benchmarking, and demonstration purposes in the data science and urban analytics communities.
    Downloads: 0 This Week
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