1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
|
.. raw:: html
<style type="text/css">
.thumbnail {{
position: relative;
float: left;
margin: 10px;
width: 180px;
height: 200px;
}}
.thumbnail img {{
position: absolute;
display: inline;
left: 0;
width: 170px;
height: 170px;
}}
</style>
seaborn: statistical data visualization
=======================================
.. raw:: html
<div style="clear: both"></div>
<div class="container-fluid hidden-xs hidden-sm">
<div class="row">
<a href="examples/scatterplot_matrix.html">
<div class="col-md-2 thumbnail">
<img src="_static/scatterplot_matrix_thumb.png">
</div>
</a>
<a href="examples/errorband_lineplots.html">
<div class="col-md-2 thumbnail">
<img src="_static/errorband_lineplots_thumb.png">
</div>
</a>
<a href="examples/scatterplot_sizes.html">
<div class="col-md-2 thumbnail">
<img src="_static/scatterplot_sizes_thumb.png">
</div>
</a>
<a href="examples/timeseries_facets.html">
<div class="col-md-2 thumbnail">
<img src="_static/timeseries_facets_thumb.png">
</div>
</a>
<a href="examples/horizontal_boxplot.html">
<div class="col-md-2 thumbnail">
<img src="_static/horizontal_boxplot_thumb.png">
</div>
</a>
<a href="examples/regression_marginals.html">
<div class="col-md-2 thumbnail">
<img src="_static/regression_marginals_thumb.png">
</div>
</a>
</div>
</div>
<br>
<div class="container-fluid">
<div class="row">
<div class="col-md-6">
Seaborn is a Python data visualization library based on `matplotlib
<https://matplotlib.org>`_. It provides a high-level interface for drawing
attractive and informative statistical graphics.
For a brief introduction to the ideas behind the library, you can read the
:doc:`introductory notes <introduction>`. Visit the :doc:`installation page
<installing>` to see how you can download the package and get started with it.
You can browse the :doc:`example gallery <examples/index>` to see what you
can do with seaborn, and then check out the :doc:`tutorial <tutorial>` and
:doc:`API reference <api>` to find out how.
To see the code or report a bug, please visit the `GitHub repository
<https://github.com/mwaskom/seaborn>`_. General support questions are most at home
on `stackoverflow <https://stackoverflow.com/questions/tagged/seaborn/>`_ or
`discourse <https://discourse.matplotlib.org/c/3rdparty/seaborn/21>`_, which
have dedicated channels for seaborn.
.. raw:: html
</div>
<div class="col-md-3">
<div class="panel panel-default">
<div class="panel-heading">
<h3 class="panel-title">Contents</h3>
</div>
<div class="panel-body">
.. toctree::
:maxdepth: 1
Introduction <introduction>
Release notes <whatsnew>
Installing <installing>
Example gallery <examples/index>
Tutorial <tutorial>
API reference <api>
.. toctree::
:hidden:
Citing <citing>
Archive <archive>
.. raw:: html
</div>
</div>
</div>
<div class="col-md-3">
<div class="panel panel-default">
<div class="panel-heading">
<h3 class="panel-title">Features</h3>
</div>
<div class="panel-body">
* Relational: :ref:`API <relational_api>` | :doc:`Tutorial <tutorial/relational>`
* Distribution: :ref:`API <distribution_api>` | :doc:`Tutorial <tutorial/distributions>`
* Categorical: :ref:`API <categorical_api>` | :doc:`Tutorial <tutorial/categorical>`
* Regression: :ref:`API <regression_api>` | :doc:`Tutorial <tutorial/regression>`
* Multiples: :ref:`API <grid_api>` | :doc:`Tutorial <tutorial/axis_grids>`
* Style: :ref:`API <style_api>` | :doc:`Tutorial <tutorial/aesthetics>`
* Color: :ref:`API <palette_api>` | :doc:`Tutorial <tutorial/color_palettes>`
.. raw:: html
</div>
</div>
</div>
</div>
</div>
|