{"id":15662455,"url":"https://github.com/csinva/data-viz-utils","last_synced_at":"2025-05-05T23:42:20.196Z","repository":{"id":53582242,"uuid":"231766256","full_name":"csinva/data-viz-utils","owner":"csinva","description":"Functions for easily making publication-quality figures with matplotlib.","archived":false,"fork":false,"pushed_at":"2024-01-20T01:23:55.000Z","size":10359,"stargazers_count":19,"open_issues_count":0,"forks_count":3,"subscribers_count":2,"default_branch":"master","last_synced_at":"2025-05-02T08:51:13.528Z","etag":null,"topics":["big-data","data-analysis","data-science","data-visualization","eda","legend","matplotlib","python","python3","scatterplot","time-series"],"latest_commit_sha":null,"homepage":"https://csinva.io/data-viz-utils/","language":"Jupyter 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Notebook","readme":"\u003ch1 align=\"center\"\u003e Data-viz utils 📈\u003c/h1\u003e\n\u003cp align=\"center\"\u003e Functions for data visualization in matplotlib\n\u003c/p\u003e\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"https://img.shields.io/badge/license-mit-blue.svg\"\u003e\n  \u003cimg src=\"https://img.shields.io/badge/python-3.6--3.8-blue\"\u003e\n  \u003cimg src=\"https://img.shields.io/github/checks-status/csinva/data-viz-utils/master\"\u003e\n  \u003cimg src=\"https://img.shields.io/pypi/v/dvu?color=orange\"\u003e\n\u003c/p\u003e  \n\u003cp align=\"center\" fontsize=40\u003e\u003ca href=\"https://csinva.io/data-viz-utils/docs/dvu.html\"\u003e 📚 API \u003c/a\u003e\n\u003c/p\u003e\n\n\nCan be installed using `pip install dvu` and then imported with `import dvu`. \n\nYou can also just copy the relatively short source code for the functions (easily viewable [here](https://csinva.io/data-viz-utils/docs/dvu.html)). \n\nHelps create a bunch of different plots such as these:\n\n![](https://csinva.io/data-viz-utils/img/plots_screenshot.png)\n\n\n\nOne particularly useful function is `dvu.line_legend()` which replaces a typical matplotlib legend with labels for each line:\n\n\n| Using `plt.legend()`                                | Using `dvu.line_legend()`                      |\n| --------------------------------------------------- | ---------------------------------------------- |\n| ![plt_legend](docs/img/plot_labeled_lines_orig.png) | ![dvu_legend](docs/img/plot_labeled_lines.png) |\n\n\n\nAnother one is `dvu.invert_plot()` which can be called after generating a plot to invert everything besides the line colors\n\n| Original plot                                  | After `dvu.invert_plot()`                           |\n| ---------------------------------------------- | --------------------------------------------------- |\n| ![plt_legend](docs/img/plot_labeled_lines.png) | ![dvu_legend](docs/img/plot_labeled_lines_dark.png) |\n\n\n\n# Reference\n\n- for updates, star the repo or follow [@csinva_](https://twitter.com/csinva_)\n- super-related and wonderful [matplotlib-label-lines](https://github.com/cphyc/matplotlib-label-lines) project\n- [PR](https://t.co/lTe19vdETE?amp=1) for implementing line-labeling into matplotlib\n- feel free to use openly!\n- built with jekyll + github pages\n- theme from [here](https://github.com/inded/Jekyll_modern-blog)\n    - based off of this [article from Codrops](http://tympanus.net/codrops/?p=24222)","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcsinva%2Fdata-viz-utils","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcsinva%2Fdata-viz-utils","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcsinva%2Fdata-viz-utils/lists"}