{"id":13633615,"url":"https://github.com/vizzuhq/ipyvizzu","last_synced_at":"2025-05-14T05:11:32.343Z","repository":{"id":36958923,"uuid":"444969649","full_name":"vizzuhq/ipyvizzu","owner":"vizzuhq","description":"Build animated charts in Jupyter Notebook and similar environments with a simple Python syntax.","archived":false,"fork":false,"pushed_at":"2025-02-26T17:21:53.000Z","size":23390,"stargazers_count":963,"open_issues_count":13,"forks_count":84,"subscribers_count":17,"default_branch":"main","last_synced_at":"2025-05-12T20:17:16.857Z","etag":null,"topics":["animation","chart","charting","charts","data-visualization","dataviz","graphing","graphs","ipython","jupyter","jupyter-notebook","plotting","python","storytelling","vizzu"],"latest_commit_sha":null,"homepage":"https://ipyvizzu.vizzuhq.com","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/vizzuhq.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":"CONTRIBUTING.md","funding":null,"license":"LICENSE","code_of_conduct":"CODE_OF_CONDUCT.md","threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2022-01-05T22:37:39.000Z","updated_at":"2025-05-01T12:58:17.000Z","dependencies_parsed_at":"2023-12-21T15:29:38.768Z","dependency_job_id":"84d42b25-5f30-468a-9f4d-ca2fae62944a","html_url":"https://github.com/vizzuhq/ipyvizzu","commit_stats":{"total_commits":771,"total_committers":21,"mean_commits":"36.714285714285715","dds":0.6251621271076524,"last_synced_commit":"8514ad458b486dd2b3bfa6e3e50200613d15f087"},"previous_names":[],"tags_count":25,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vizzuhq%2Fipyvizzu","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vizzuhq%2Fipyvizzu/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vizzuhq%2Fipyvizzu/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vizzuhq%2Fipyvizzu/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/vizzuhq","download_url":"https://codeload.github.com/vizzuhq/ipyvizzu/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":254076850,"owners_count":22010611,"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":["animation","chart","charting","charts","data-visualization","dataviz","graphing","graphs","ipython","jupyter","jupyter-notebook","plotting","python","storytelling","vizzu"],"created_at":"2024-08-01T23:00:49.030Z","updated_at":"2025-05-14T05:11:27.320Z","avatar_url":"https://github.com/vizzuhq.png","language":"Jupyter Notebook","funding_links":[],"categories":["Interactive Widgets \u0026 Visualization","Visualization"],"sub_categories":[],"readme":"\u003cp align=\"center\"\u003e\n  \u003ca href=\"https://ipyvizzu.vizzuhq.com/latest/\"\u003e\n    \u003cimg src=\"https://lib.vizzuhq.com/latest/readme/infinite-60.gif\" alt=\"Vizzu\" /\u003e\n  \u003c/a\u003e\n  \u003cp align=\"center\"\u003e\u003cb\u003eipyvizzu\u003c/b\u003e - Build animated charts in Jupyter Notebook and similar environments with a simple Python syntax\u003c/p\u003e\n  \u003cp align=\"center\"\u003e\n    \u003ca href=\"https://ipyvizzu.vizzuhq.com/latest/\"\u003eDocumentation\u003c/a\u003e\n    · \u003ca href=\"https://ipyvizzu.vizzuhq.com/latest/examples/\"\u003eExamples\u003c/a\u003e\n    · \u003ca href=\"https://ipyvizzu.vizzuhq.com/latest/reference/ipyvizzu/\"\u003eCode reference\u003c/a\u003e\n    · \u003ca href=\"https://github.com/vizzuhq/ipyvizzu\"\u003eRepository\u003c/a\u003e\n    · \u003ca href=\"https://blog.vizzuhq.com\"\u003eBlog\u003c/a\u003e\n  \u003c/p\u003e\n\u003c/p\u003e\n\n[![PyPI version](https://badge.fury.io/py/ipyvizzu.svg)](https://badge.fury.io/py/ipyvizzu)\n[![Conda Version](https://img.shields.io/conda/vn/conda-forge/ipyvizzu.svg)](https://anaconda.org/conda-forge/ipyvizzu)\n[![CI-CD](https://github.com/vizzuhq/ipyvizzu/actions/workflows/cicd.yml/badge.svg?branch=main)](https://github.com/vizzuhq/ipyvizzu/actions/workflows/cicd.yml)\n\n# ipyvizzu\n\n## About The Project\n\n`ipyvizzu` is an animated charting tool for [Jupyter](https://jupyter.org),\n[Google Colab](https://colab.research.google.com),\n[Databricks](https://docs.databricks.com/notebooks),\n[Kaggle](https://www.kaggle.com/code) and [Deepnote](https://deepnote.com)\nnotebooks among other platforms. `ipyvizzu` enables data scientists and analysts\nto utilize animation for storytelling with data using `Python`. It's built on\nthe open-source `JavaScript`/`C++` charting library\n[Vizzu](https://github.com/vizzuhq/vizzu-lib).\n\n**There is a new extension of `ipyvizzu`,\n[ipyvizzu-story](https://vizzuhq.github.io/ipyvizzu-story/)** with which the\nanimated charts can be presented right from the notebooks. Since\n`ipyvizzu-story`'s syntax is a bit different to `ipyvizzu`'s, we suggest you to\nstart from the [ipyvizzu-story repo](https://github.com/vizzuhq/ipyvizzu-story)\nif you're interested in using animated charts to present your findings live or\nto share your presentation as an HTML file.\n\nSimilarly to `Vizzu`, `ipyvizzu` utilizes a generic dataviz engine that\ngenerates many types of charts and seamlessly animates between them. It is\ndesigned for building animated data stories as it enables showing different\nperspectives of the data that the viewers can easily follow.\n\nMain features:\n\n- Designed with animation in focus;\n- Defaults based on data visualization guidelines;\n- Works with `Pandas` dataframe, while also `JSON` and inline data input is\n    available;\n- Auto scrolling feature to keep the actual chart in position while executing\n    multiple cells.\n\n## Installation\n\n```sh\npip install ipyvizzu\n```\n\nVisit [Installation chapter](https://ipyvizzu.vizzuhq.com/latest/installation/)\nfor more options and details.\n\n## Usage\n\nYou can create the animation below with the following code snippet.\n\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"https://ipyvizzu.vizzuhq.com/latest/assets/ipyvizzu-promo.gif\" alt=\"ipyvizzu\" /\u003e\n\u003c/p\u003e\n\n```python\nimport pandas as pd\nfrom ipyvizzu import Chart, Data, Config\n\ndf = pd.read_csv(\n    \"https://ipyvizzu.vizzuhq.com/latest/showcases/titanic/titanic.csv\"\n)\ndata = Data()\ndata.add_df(df)\n\nchart = Chart(width=\"640px\", height=\"360px\")\n\nchart.animate(data)\n\nchart.animate(\n    Config(\n        {\n            \"x\": \"Count\",\n            \"y\": \"Sex\",\n            \"label\": \"Count\",\n            \"title\": \"Passengers of the Titanic\",\n        }\n    )\n)\nchart.animate(\n    Config(\n        {\n            \"x\": [\"Count\", \"Survived\"],\n            \"label\": [\"Count\", \"Survived\"],\n            \"color\": \"Survived\",\n        }\n    )\n)\nchart.animate(Config({\"x\": \"Count\", \"y\": [\"Sex\", \"Survived\"]}))\n```\n\n## Documentation\n\nVisit our [Documentation site](https://ipyvizzu.vizzuhq.com/latest/) for more\ndetails and a step-by-step tutorial into `ipyvizzu` or check out our\n[Example gallery](https://ipyvizzu.vizzuhq.com/latest/examples/).\n\n## Environments\n\n`ipyvizzu` can be used in a wide variety of environments, visit\n[Environments chapter](https://ipyvizzu.vizzuhq.com/latest/environments/) for\nmore details.\n\n- Notebooks\n    - [Jupyter Notebook](https://ipyvizzu.vizzuhq.com/latest/environments/notebook/jupyternotebook/)\n    - [Colab](https://ipyvizzu.vizzuhq.com/latest/environments/notebook/colab/)\n    - [Databricks](https://ipyvizzu.vizzuhq.com/latest/environments/notebook/databricks/)\n    - [DataCamp](https://ipyvizzu.vizzuhq.com/latest/environments/notebook/datacamp/)\n    - [Deepnote](https://ipyvizzu.vizzuhq.com/latest/environments/notebook/deepnote/)\n    - [JupyterLab](https://ipyvizzu.vizzuhq.com/latest/environments/notebook/jupyterlab/)\n    - [JupyterLite](https://ipyvizzu.vizzuhq.com/latest/environments/notebook/jupyterlite/)\n    - [Kaggle](https://ipyvizzu.vizzuhq.com/latest/environments/notebook/kaggle/)\n    - [Noteable](https://ipyvizzu.vizzuhq.com/latest/environments/notebook/noteable/)\n- App platforms\n    - [Streamlit](https://ipyvizzu.vizzuhq.com/latest/environments/platform/streamlit/)\n    - [Flask](https://ipyvizzu.vizzuhq.com/latest/environments/platform/flask/)\n    - [Panel](https://ipyvizzu.vizzuhq.com/latest/environments/platform/panel/)\n    - [Mercury](https://ipyvizzu.vizzuhq.com/latest/environments/platform/mercury/)\n    - [Voilà](https://ipyvizzu.vizzuhq.com/latest/environments/platform/voila/)\n- BI tools\n    - [Mode](https://ipyvizzu.vizzuhq.com/latest/environments/bi/mode/)\n- IDEs\n    - [PyCharm](https://ipyvizzu.vizzuhq.com/latest/environments/ide/pycharm/)\n    - [VSCode Python](https://ipyvizzu.vizzuhq.com/latest/environments/ide/vscode/)\n\n## Extensions\n\n- [ipyvizzu-story](https://ipyvizzu-story.vizzuhq.com/) adds presentation\n    controls to present data stories live or to share them as an interactive\n    HTML file.\n\n## Contributing\n\nWe welcome contributions to the project, visit our contributing\n[guide](https://ipyvizzu.vizzuhq.com/latest/CONTRIBUTING/) for further info.\n\n## Contact\n\n- Join our Slack if you have any questions or comments:\n    [vizzu-community.slack.com](https://join.slack.com/t/vizzu-community/shared_invite/zt-w2nqhq44-2CCWL4o7qn2Ns1EFSf9kEg)\n    \n\n- Drop us a line at hello@vizzu.io\n\n- Follow us on Twitter: [VizzuHQ](https://twitter.com/VizzuHQ)\n\n## Usage Statistics\n\n`ipyvizzu` collects aggregate usage statistics by default to follow the progress\nand overall trends of our library. This feature is optional, and users can\nchoose to opt-out. However, we do not track, collect, or store any personal data\nor personally identifiable information. Please note that even when this feature\nis enabled, publishing anything made with `ipyvizzu` remains GDPR compatible.\nFor more details, please visit\n[Analytics chapter](https://ipyvizzu.vizzuhq.com/latest/tutorial/chart_settings/#analytics).\n\n## License\n\nCopyright © 2022-2025 [Vizzu Inc.](https://vizzuhq.com)\n\nReleased under the\n[Apache 2.0 License](https://ipyvizzu.vizzuhq.com/latest/LICENSE/).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvizzuhq%2Fipyvizzu","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fvizzuhq%2Fipyvizzu","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvizzuhq%2Fipyvizzu/lists"}