File: saving_charts.rst

package info (click to toggle)
python-altair 5.0.1-4
  • links: PTS, VCS
  • area: main
  • in suites: forky, sid
  • size: 6,952 kB
  • sloc: python: 25,649; sh: 14; makefile: 6
file content (227 lines) | stat: -rw-r--r-- 6,460 bytes parent folder | download | duplicates (2)
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
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
.. currentmodule:: altair

.. _user-guide-saving:

Saving Altair Charts
--------------------
Altair chart objects have a :meth:`Chart.save` method which allows charts
to be saved in a variety of formats. 

.. saving-json:

JSON format
~~~~~~~~~~~
The fundamental chart representation output by Altair is a JSON string format;
one of the core methods provided by Altair is :meth:`Chart.to_json`, which
returns a JSON string that represents the chart content.
Additionally, you can save a chart to a JSON file using :meth:`Chart.save`,
by passing a filename with a ``.json`` extension.

For example, here we save a simple scatter-plot to JSON:

.. code-block:: python

    import altair as alt
    from vega_datasets import data

    chart = alt.Chart(data.cars.url).mark_point().encode(
        x='Horsepower:Q',
        y='Miles_per_Gallon:Q',
        color='Origin:N'
    )

    chart.save('chart.json')

The contents of the resulting file will look something like this:

.. code-block:: json

    {
      "$schema": "https://vega.github.io/schema/vega-lite/v5.json",
      "config": {
        "view": {
          "continuousHeight": 300,
          "continuousWidth": 300
        }
      },
      "data": {
        "url": "https://vega.github.io/vega-datasets/data/cars.json"
      },
      "encoding": {
        "color": {
          "field": "Origin",
          "type": "nominal"
        },
        "x": {
          "field": "Horsepower",
          "type": "quantitative"
        },
        "y": {
          "field": "Miles_per_Gallon",
          "type": "quantitative"
        }
      },
      "mark": {"type": "point"}
    }

This JSON can then be inserted into any web page using the vegaEmbed_ library.

.. saving-html:

HTML format
~~~~~~~~~~~
If you wish for Altair to take care of the HTML embedding for you, you can
save a chart directly to an HTML file using

.. code-block:: python

    chart.save('chart.html')

This will create a simple HTML template page that loads Vega, Vega-Lite, and
vegaEmbed, such that when opened in a browser the chart will be rendered.

For example, saving the above scatter-plot to HTML creates a file with
the following contents, which can be opened and rendered in any modern
javascript-enabled web browser:

.. code-block:: HTML

    <!DOCTYPE html>
    <html>
    <head>
      <script src="https://cdn.jsdelivr.net/npm/vega@5"></script>
      <script src="https://cdn.jsdelivr.net/npm/vega-lite@5"></script>
      <script src="https://cdn.jsdelivr.net/npm/vega-embed@6"></script>
    </head>
    <body>
      <div id="vis"></div>
      <script type="text/javascript">
        var spec = {
          "$schema": "https://vega.github.io/schema/vega-lite/v5.json",
          "config": {
            "view": {
              "continuousHeight": 300,
              "continuousWidth": 300
            }
          },
          "data": {
            "url": "https://vega.github.io/vega-datasets/data/cars.json"
          },
          "encoding": {
            "color": {
              "field": "Origin",
              "type": "nominal"
            },
            "x": {
              "field": "Horsepower",
              "type": "quantitative"
            },
            "y": {
              "field": "Miles_per_Gallon",
              "type": "quantitative"
            }
          },
          "mark": {"type": "point"}
        };
        var opt = {"renderer": "canvas", "actions": false};
        vegaEmbed("#vis", spec, opt);
      </script>
    </body>
    </html>

You can view the result here: `chart.html </_static/chart.html>`_.

By default, ``canvas`` is used for rendering the visualization in vegaEmbed. To 
change to ``svg`` rendering, use the ``embed_options`` as such:

.. code-block:: python

    chart.save('chart.html', embed_options={'renderer':'svg'})


.. note::

   This is not the same as ``alt.renderers.enable('svg')``, what renders the 
   chart as a static ``svg`` image within a Jupyter notebook.

.. _saving-png:

PNG, SVG, and PDF format
~~~~~~~~~~~~~~~~~~~~~~~~
To save an Altair chart object as a PNG, SVG, or PDF image, you can use

.. code-block:: python

    chart.save('chart.png')
    chart.save('chart.svg')
    chart.save('chart.pdf')

Saving these images requires an additional extension to run the
javascript code necessary to interpret the Vega-Lite specification and output
it in the form of an image. There are two packages that can be used to enable
image export: vl-convert_ or altair_saver_.

vl-convert
^^^^^^^^^^
The vl-convert_ package can be installed with::

    conda install -c conda-forge vl-convert-python

or::

    pip install vl-convert-python

.. note::
   
   Conda packages are not yet available for the Apple Silicon architecture.
   See `conda-forge/vl-convert-python-feedstock#9 <https://github.com/conda-forge/vl-convert-python-feedstock/issues/9>`_.

Unlike altair_saver_, vl-convert_ does not require any external dependencies.
However, it only supports saving charts to PNG and SVG formats. To save directly to
PDF, altair_saver_ is still required. See the vl-convert documentation for information
on other `limitations <https://github.com/vega/vl-convert#limitations>`_.

altair_saver
^^^^^^^^^^^^

.. note::
   
   altair_saver does not yet support Altair 5.


The altair_saver_ package can be installed with::

    conda install -c conda-forge altair_saver

or::

    pip install altair_saver

See the altair_saver_ documentation for information about additional installation
requirements.

Engine Argument
^^^^^^^^^^^^^^^
If both vl-convert and altair_saver are installed, vl-convert will take precedence.
The engine argument to :meth:`Chart.save` can be used to override this default
behavior. For example, to use altair_saver for PNG export when vl-convert is also
installed you can use::

    chart.save('chart.png', engine="altair_saver")


Figure Size/Resolution
^^^^^^^^^^^^^^^^^^^^^^
When using ``chart.save()`` above, the resolution of the resulting PNG is
controlled by the resolution of your screen. The easiest way to produce a
higher-resolution PNG image is to scale the image to make it larger, and thus
to contain more pixels at a given resolution.

This can be done with the ``scale_factor`` argument, which defaults to 1.0::

    chart.save('chart.png', scale_factor=2.0)


.. _vl-convert: https://github.com/vega/vl-convert
.. _altair_saver: http://github.com/altair-viz/altair_saver/
.. _vegaEmbed: https://github.com/vega/vega-embed