{"id":13449399,"url":"https://github.com/holoviz/datashader","last_synced_at":"2026-04-01T19:42:52.370Z","repository":{"id":37432154,"uuid":"48504165","full_name":"holoviz/datashader","owner":"holoviz","description":"Quickly and accurately render even the largest data.","archived":false,"fork":false,"pushed_at":"2024-12-12T10:23:53.000Z","size":60548,"stargazers_count":3335,"open_issues_count":139,"forks_count":367,"subscribers_count":92,"default_branch":"main","last_synced_at":"2024-12-15T14:04:54.960Z","etag":null,"topics":["data-visualizations","datashader","holoviz","rasterization"],"latest_commit_sha":null,"homepage":"http://datashader.org","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"bsd-3-clause","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/holoviz.png","metadata":{"files":{"readme":"README.md","changelog":"CHANGELOG.rst","contributing":null,"funding":".github/FUNDING.yml","license":"LICENSE.txt","code_of_conduct":"CODE_OF_CONDUCT.md","threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":"ROADMAP.md","authors":null,"dei":null,"publiccode":null,"codemeta":null},"funding":{"open_collective":"holoviz"}},"created_at":"2015-12-23T18:02:20.000Z","updated_at":"2024-12-12T10:23:57.000Z","dependencies_parsed_at":"2024-11-07T08:25:17.227Z","dependency_job_id":"8b9066bb-beb9-4358-94b2-0377e293c7f1","html_url":"https://github.com/holoviz/datashader","commit_stats":{"total_commits":1246,"total_committers":64,"mean_commits":19.46875,"dds":0.7030497592295345,"last_synced_commit":"f7de27162a6b06216599ddbb197a89215bc8478f"},"previous_names":["bokeh/datashader"],"tags_count":113,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/holoviz%2Fdatashader","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/holoviz%2Fdatashader/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/holoviz%2Fdatashader/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/holoviz%2Fdatashader/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/holoviz","download_url":"https://codeload.github.com/holoviz/datashader/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":245029153,"owners_count":20549656,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["data-visualizations","datashader","holoviz","rasterization"],"created_at":"2024-07-31T06:00:37.036Z","updated_at":"2026-04-01T19:42:52.365Z","avatar_url":"https://github.com/holoviz.png","language":"Python","funding_links":["https://opencollective.com/holoviz"],"categories":["Python","数据可视化","Data Visualization","1. Core Frameworks \u0026 Libraries","🐍 Python"],"sub_categories":["Data Management","Useful Python Tools for Data Analysis"],"readme":"\u003cimg src=\"https://github.com/holoviz/datashader/raw/main/doc/_static/logo_horizontal.svg\" data-canonical-src=\"https://github.com/holoviz/datashader/raw/main/doc/_static/logo_horizontal.svg\" width=\"400\"/\u003e\u003cbr\u003e\n\n-----------------\n\n# Turn even the largest data into images, accurately\n\n|    |    |\n| --- | --- |\n| Downloads | ![https://pypistats.org/packages/datashader](https://img.shields.io/pypi/dm/datashader?label=pypi) ![https://anaconda.org/pyviz/datashader](https://pyviz.org/_static/cache/datashader_conda_downloads_badge.svg)\n| Build Status | [![Build Status](https://github.com/holoviz/datashader/actions/workflows/test.yaml/badge.svg?branch=main)](https://github.com/holoviz/datashader/actions/workflows/test.yaml?query=branch%3Amain) |\n| Coverage | [![codecov](https://codecov.io/gh/holoviz/datashader/branch/main/graph/badge.svg)](https://codecov.io/gh/holoviz/datashader) |\n| Latest dev release | [![Github tag](https://img.shields.io/github/tag/holoviz/datashader.svg?label=tag\u0026colorB=11ccbb)](https://github.com/holoviz/datashader/tags) [![dev-site](https://img.shields.io/website-up-down-green-red/https/holoviz-dev.github.io/datashader.svg?label=dev%20website)](https://holoviz-dev.github.io/datashader/) |\n| Latest release | [![Github release](https://img.shields.io/github/release/holoviz/datashader.svg?label=tag\u0026colorB=11ccbb)](https://github.com/holoviz/datashader/releases) [![PyPI version](https://img.shields.io/pypi/v/datashader.svg?colorB=cc77dd)](https://pypi.python.org/pypi/datashader) [![datashader version](https://img.shields.io/conda/v/pyviz/datashader.svg?colorB=4488ff\u0026style=flat)](https://anaconda.org/pyviz/datashader) [![conda-forge version](https://img.shields.io/conda/v/conda-forge/datashader.svg?label=conda%7Cconda-forge\u0026colorB=4488ff)](https://anaconda.org/conda-forge/datashader) [![defaults version](https://img.shields.io/conda/v/anaconda/datashader.svg?label=conda%7Cdefaults\u0026style=flat\u0026colorB=4488ff)](https://anaconda.org/anaconda/datashader) |\n| Python | [![Python support](https://img.shields.io/pypi/pyversions/datashader.svg)](https://pypi.org/project/datashader/)\n| Docs | [![DocBuildStatus](https://github.com/holoviz/datashader/workflows/docs/badge.svg?query=branch%3Amain)](https://github.com/holoviz/datashader/actions?query=workflow%3Adocs+branch%3Amain) [![site](https://img.shields.io/website-up-down-green-red/https/datashader.org.svg)](https://datashader.org) |\n| Support | [![Discourse](https://img.shields.io/discourse/status?server=https%3A%2F%2Fdiscourse.holoviz.org)](https://discourse.holoviz.org/) |\n\n-------\n\n[![History of OS GIS Timeline](examples/assets/images/featured-badge-gh.svg)](https://makepath.com/history-of-open-source-gis/)\n\n-------\n\n## What is it?\n\nDatashader is a data rasterization pipeline for automating the process of\ncreating meaningful representations of large amounts of data. Datashader\nbreaks the creation of images of data into 3 main steps:\n\n1. Projection\n\n   Each record is projected into zero or more bins of a nominal plotting grid\n   shape, based on a specified glyph.\n\n2. Aggregation\n\n   Reductions are computed for each bin, compressing the potentially large\n   dataset into a much smaller *aggregate* array.\n\n3. Transformation\n\n   These aggregates are then further processed, eventually creating an image.\n\nUsing this very general pipeline, many interesting data visualizations can be\ncreated in a performant and scalable way. Datashader contains tools for easily\ncreating these pipelines in a composable manner, using only a few lines of code.\nDatashader can be used on its own, but it is also designed to work as\na pre-processing stage in a plotting library, allowing that library\nto work with much larger datasets than it would otherwise.\n\n## Installation\n\nDatashader supports Python 3.10, 3.11, 3.12, 3.13, and 3.14 on Linux, Windows, and\nMac and can be installed with conda:\n\n    conda install datashader\n\nor with pip:\n\n    pip install datashader\n\nFor the best performance, we recommend using conda so that you are sure\nto get numerical libraries optimized for your platform. The latest\nreleases are available on the pyviz channel `conda install -c pyviz\ndatashader` and the latest pre-release versions are available on the\ndev-labelled channel `conda install -c pyviz/label/dev datashader`.\n\n## Fetching Examples\n\nOnce you've installed datashader as above you can fetch the examples:\n\n    datashader examples\n    cd datashader-examples\n\nThis will create a new directory called\n\u003cspan class=\"title-ref\"\u003edatashader-examples\u003c/span\u003e with all the data\nneeded to run the examples.\n\nTo run all the examples you will need some extra dependencies. If you\ninstalled datashader **within a conda environment**, with that\nenvironment active run:\n\n    conda env update --file environment.yml\n\nOtherwise create a new environment:\n\n    conda env create --name datashader --file environment.yml\n    conda activate datashader\n\n## Developer Instructions\n\n1.  Install Python 3\n    [miniconda](https://docs.conda.io/en/latest/miniconda.html) or\n    [anaconda](https://www.anaconda.com/download/success), if you don't\n    already have it on your system.\n\n2.  Clone the datashader git repository if you do not already have it:\n\n        git clone git://github.com/holoviz/datashader.git\n\n3.  Set up a new conda environment with all of the dependencies needed\n    to run the examples:\n\n        cd datashader\n        conda env create --name datashader --file ./examples/environment.yml\n        conda activate datashader\n\n4.  Put the datashader directory into the Python path in this\n    environment:\n\n        pip install --no-deps -e .\n\n## Learning more\n\nAfter working through the examples, you can find additional resources linked\nfrom the [datashader documentation](https://datashader.org),\nincluding API documentation and papers and talks about the approach.\n\n## Some Examples\n\n![USA census](examples/assets/images/usa_census.jpg)\n\n![NYC races](examples/assets/images/nyc_races.jpg)\n\n![NYC taxi](examples/assets/images/nyc_pickups_vs_dropoffs.jpg)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fholoviz%2Fdatashader","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fholoviz%2Fdatashader","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fholoviz%2Fdatashader/lists"}