Datashader

@datashader

is an library for rasterizing large amounts of data into beautiful, accurate images. Datashader is a project of .

Vrijeme pridruživanja: lipanj 2017.

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  1. Prikvačeni tweet
    28. lip 2017.
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  2. proslijedio/la je Tweet
    3. velj

    Turbo-telegram update: Made Taxi Dashboard SQL based & added a Notebook to download & pre-process Jan - Dec 2015 yellow cab data w/ ! >20GB CSV downloaded, transformed, rewritten, read back & visualized in 7min 52sec w/ a single T4 on AWS.

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  3. proslijedio/la je Tweet
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  4. proslijedio/la je Tweet
    30. sij

    Visualizing where I went to run using , , and .

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  5. proslijedio/la je Tweet
    23. sij

    With a single T4 we can start up BlazingSQL, load & query 10M+ rows of NYC Taxi data, and visualize the results thru all in 2-3 seconds, what a time to be alive!

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  6. proslijedio/la je Tweet
    22. sij

    Visualizing large amounts of information crashing your browser? Say no more

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  7. 22. sij

    Datashader's GPU Quadmesh support was funded by to help speed up working with climate data. Thanks, !

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  8. 22. sij

    Thanks to and for contributing support for most of these configurations, and get in touch if you want to help with support for any of the combinations not yet covered!

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  9. 22. sij

    Datashader v0.10.0 now includes details for how to store your data to get maximum rendering speed from your CPUs or GPUs: It supports , , , and DataFrames, and multidimensional arrays.

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  10. 22. sij

    Datashader v0.10.0 is out! Datashader tames even the biggest data-visualization problem using server-side rasterizing. Thanks to it can now render polygons (choropleths), and it can use your GPU for quadmesh arrays (20-50x speedups).

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  11. proslijedio/la je Tweet
    17. sij

    Anaconda's tools help you understand what your algorithms are doing. Check out and to get started!

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  12. proslijedio/la je Tweet
    17. sij

    Really interesting visualisation of how various DR techniques (including ) embed a complex dataset. 1,000,000 points visualised with the help of .

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  13. proslijedio/la je Tweet
    24. pro 2019.

    Last minute fun with before heading out this Christmas Eve!

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  14. proslijedio/la je Tweet
    20. pro 2019.

    Rendered from 4GB of raw data in less than a second with my new favourite tool ❤️

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  15. proslijedio/la je Tweet
    12. pro 2019.

    should be intuitive to use and easy to integrate. In this example we derive & display cost ratios from NYC Taxi data, then pass the results of nesting that query to for visualization of $12+ per mile per person rides.

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  16. proslijedio/la je Tweet
    10. pro 2019.
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  17. proslijedio/la je Tweet
    5. pro 2019.

    After further fiddling with I've updated this so it looks even prettier now. Full res here:

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  18. proslijedio/la je Tweet
    8. pro 2019.
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  19. proslijedio/la je Tweet
    8. pro 2019.

    Super excited to have had the chance to work on adding GPU support to . Amazing that it was possible to do this in pure Python. I don't say this lightly; and are game-changing technologies for the PyData ecosystem.

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  20. proslijedio/la je Tweet
    7. pro 2019.
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  21. 7. pro 2019.

    Datashader Release 0.9.0 is out, now supporting GPUs at last! Short story is that in our testing a NVIDIA GPU was 40X faster than single-core Pandas and 4.5x faster than multi-core Dask for rendering 100 million points. See for the details.

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