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seaborn: statistical data visualization
=======================================
[![PyPI Version](https://img.shields.io/pypi/v/seaborn.svg)](https://pypi.org/project/seaborn/)
[![License](https://img.shields.io/pypi/l/seaborn.svg)](https://github.com/mwaskom/seaborn/blob/master/LICENSE)
[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.592845.svg)](https://doi.org/10.5281/zenodo.592845)
[![Build Status](https://travis-ci.org/mwaskom/seaborn.svg?branch=master)](https://travis-ci.org/mwaskom/seaborn)
[![Code Coverage](https://codecov.io/gh/mwaskom/seaborn/branch/master/graph/badge.svg)](https://codecov.io/gh/mwaskom/seaborn)
Seaborn is a Python visualization library based on matplotlib. It provides a high-level interface for drawing attractive statistical graphics.
Documentation
-------------
Online documentation is available at [seaborn.pydata.org](https://seaborn.pydata.org).
The docs include a [tutorial](https://seaborn.pydata.org/tutorial.html), [example gallery](https://seaborn.pydata.org/examples/index.html), [API reference](https://seaborn.pydata.org/api.html), and other useful information.
To build the documentation locally, please refer to [`doc/README.md`](doc/README.md).
Dependencies
------------
Seaborn supports Python 3.6+ and no longer supports Python 2.
Installation requires [numpy](https://numpy.org/), [scipy](https://www.scipy.org/), [pandas](https://pandas.pydata.org/), and [matplotlib](https://matplotlib.org/). Some functions will optionally use [statsmodels](https://www.statsmodels.org/) if it is installed.
Installation
------------
The latest stable release (and older versions) can be installed from PyPI:
pip install seaborn
You may instead want to use the development version from Github:
pip install git+https://github.com/mwaskom/seaborn.git#egg=seaborn
Testing
-------
Testing seaborn requires installing additional packages listed in `ci/utils.txt`.
To test the code, run `make test` in the source directory. This will exercise both the unit tests and docstring examples (using [pytest](https://docs.pytest.org/)) and generate a coverate report.
The doctests require a network connection (unless all example datasets are cached), but the unit tests can be run offline with `make unittests`.
Code style is enforced with `flake8` using the settings in the [`setup.cfg`](./setup.cfg) file. Run `make lint` to check.
Development
-----------
Seaborn development takes place on Github: https://github.com/mwaskom/seaborn
Please submit bugs that you encounter to the [issue tracker](https://github.com/mwaskom/seaborn/issues) with a reproducible example demonstrating the problem. Questions about usage are more at home on StackOverflow, where there is a [seaborn tag](https://stackoverflow.com/questions/tagged/seaborn).
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seaborn-0.11.0.tar.gz
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Python库是一组预先编写的代码模块,旨在帮助开发者实现特定的编程任务,无需从零开始编写代码。这些库可以包括各种功能,如数学运算、文件操作、数据分析和网络编程等。Python社区提供了大量的第三方库,如NumPy、Pandas和Requests,极大地丰富了Python的应用领域,从数据科学到Web开发。Python库的丰富性是Python成为最受欢迎的编程语言之一的关键原因之一。这些库不仅为初学者提供了快速入门的途径,而且为经验丰富的开发者提供了强大的工具,以高效率、高质量地完成复杂任务。例如,Matplotlib和Seaborn库在数据可视化领域内非常受欢迎,它们提供了广泛的工具和技术,可以创建高度定制化的图表和图形,帮助数据科学家和分析师在数据探索和结果展示中更有效地传达信息。
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seaborn-0.11.0.tar.gz (54个子文件)
seaborn-0.11.0
licences
HUSL_LICENSE 1KB
setup.py 3KB
LICENSE 1KB
PKG-INFO 2KB
seaborn
_testing.py 2KB
_statistics.py 14KB
utils.py 21KB
__init__.py 744B
relational.py 37KB
_decorators.py 2KB
colors
__init__.py 88B
crayons.py 4KB
xkcd_rgb.py 35KB
matrix.py 50KB
tests
__init__.py 0B
test_categorical.py 105KB
test_statistics.py 12KB
test_utils.py 13KB
test_docstrings.py 1KB
test_core.py 39KB
test_axisgrid.py 54KB
test_miscplot.py 967B
test_rcmod.py 9KB
test_algorithms.py 7KB
test_regression.py 21KB
test_distributions.py 65KB
test_relational.py 55KB
test_matrix.py 47KB
test_palettes.py 14KB
test_decorators.py 3KB
regression.py 38KB
miscplot.py 1KB
_core.py 51KB
axisgrid.py 78KB
cm.py 64KB
widgets.py 15KB
distributions.py 88KB
_docstrings.py 6KB
rcmod.py 16KB
palettes.py 31KB
external
__init__.py 0B
husl.py 7KB
docscrape.py 23KB
categorical.py 138KB
conftest.py 5KB
algorithms.py 4KB
seaborn.egg-info
SOURCES.txt 1KB
top_level.txt 8B
PKG-INFO 2KB
requires.txt 52B
dependency_links.txt 1B
MANIFEST.in 87B
setup.cfg 169B
README.md 3KB
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