seaborn


Nameseaborn JSON
Version 0.7.1 PyPI version JSON
download
home_pagehttp://stanford.edu/~mwaskom/software/seaborn/
SummarySeaborn: statistical data visualization
upload_time2016-06-05 02:39:11
maintainerNone
docs_urlNone
authorMichael Waskom
requires_pythonNone
licenseBSD (3-clause)
keywords
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
Coveralis test coverage No Coveralis.
            Seaborn is a library for making attractive and informative statistical graphics in Python. It is built on top of matplotlib and tightly integrated with the PyData stack, including support for numpy and pandas data structures and statistical routines from scipy and statsmodels.

Some of the features that seaborn offers are

- Several built-in themes that improve on the default matplotlib aesthetics
- Tools for choosing color palettes to make beautiful plots that reveal patterns in your data
- Functions for visualizing univariate and bivariate distributions or for comparing them between subsets of data
- Tools that fit and visualize linear regression models for different kinds of independent and dependent variables
- Functions that visualize matrices of data and use clustering algorithms to discover structure in those matrices
- A function to plot statistical timeseries data with flexible estimation and representation of uncertainty around the estimate
- High-level abstractions for structuring grids of plots that let you easily build complex visualizations
            

Raw data

            {
    "maintainer": null, 
    "docs_url": null, 
    "requires_python": null, 
    "maintainer_email": null, 
    "cheesecake_code_kwalitee_id": null, 
    "keywords": null, 
    "upload_time": "2016-06-05 02:39:11", 
    "author": "Michael Waskom", 
    "home_page": "http://stanford.edu/~mwaskom/software/seaborn/", 
    "download_url": "https://pypi.python.org/packages/ed/dc/f168ff9db34f8c03c568987b4f81603cd3df40dd8043722d526026381a91/seaborn-0.7.1.tar.gz", 
    "platform": "UNKNOWN", 
    "version": "0.7.1", 
    "cheesecake_documentation_id": null, 
    "description": "Seaborn is a library for making attractive and informative statistical graphics in Python. It is built on top of matplotlib and tightly integrated with the PyData stack, including support for numpy and pandas data structures and statistical routines from scipy and statsmodels.\n\nSome of the features that seaborn offers are\n\n- Several built-in themes that improve on the default matplotlib aesthetics\n- Tools for choosing color palettes to make beautiful plots that reveal patterns in your data\n- Functions for visualizing univariate and bivariate distributions or for comparing them between subsets of data\n- Tools that fit and visualize linear regression models for different kinds of independent and dependent variables\n- Functions that visualize matrices of data and use clustering algorithms to discover structure in those matrices\n- A function to plot statistical timeseries data with flexible estimation and representation of uncertainty around the estimate\n- High-level abstractions for structuring grids of plots that let you easily build complex visualizations", 
    "lcname": "seaborn", 
    "bugtrack_url": "", 
    "github": false, 
    "name": "seaborn", 
    "license": "BSD (3-clause)", 
    "summary": "Seaborn: statistical data visualization", 
    "split_keywords": [], 
    "author_email": "mwaskom@stanford.edu", 
    "urls": [
        {
            "has_sig": false, 
            "upload_time": "2016-06-05T02:39:11", 
            "comment_text": "", 
            "python_version": "source", 
            "url": "https://pypi.python.org/packages/ed/dc/f168ff9db34f8c03c568987b4f81603cd3df40dd8043722d526026381a91/seaborn-0.7.1.tar.gz", 
            "md5_digest": "ef07e29e0f8a1f2726abe506c1a36e93", 
            "downloads": 0, 
            "filename": "seaborn-0.7.1.tar.gz", 
            "packagetype": "sdist", 
            "path": "ed/dc/f168ff9db34f8c03c568987b4f81603cd3df40dd8043722d526026381a91/seaborn-0.7.1.tar.gz", 
            "size": 158146
        }
    ], 
    "_id": null, 
    "cheesecake_installability_id": null
}