To install Chart Studio's python package, use the package manager pip inside your terminal.
If you don't have pip installed on your machine, click here for pip's installation instructions.
Chart Studio provides a web-service for hosting graphs! Create a free account to get started. Graphs are saved inside your online Chart Studio account and you control the privacy. Public hosting is free, for private hosting, check out our paid plans.
import chart_studio
chart_studio.tools.set_credentials_file(username='DemoAccount', api_key='lr1c37zw81')
You'll need to replace 'DemoAccount' and 'lr1c37zw81' with your Plotly username and API key.
Find your API key here.
Plot can be set to three different type of privacies: public, private or secret.
By default all plots are set to public. Users with free account have the permission to keep one private plot. If you need to save private plots, upgrade to a pro account. If you're a Personal or Professional user and would like the default setting for your plots to be private, you can edit your Chart Studio configuration:
import chart_studio
chart_studio.tools.set_config_file(world_readable=False,
sharing='private')
For more examples on privacy settings please visit Python privacy documentation
Your API key for account on the public cloud will be different than the API key in Chart Studio Enterprise. Visit https://plotly.your-company.com/settings/api/ to find your Chart Studio Enterprise API key. Remember to replace "your-company.com" with the URL of your Chart Studio Enterprise server. If your company has a Chart Studio Enterprise server, change the Python API endpoint so that it points to your company's Plotly server instead of Plotly's cloud.
import chart_studio
chart_studio.tools.set_config_file(
plotly_domain='https://plotly.your-company.com',
plotly_api_domain='https://plotly.your-company.com',
plotly_streaming_domain='https://stream-plotly.your-company.com'
)
Make sure to replace "your-company.com" with the URL of your Chart Studio Enterprise server.
Additionally, you can set your configuration so that you generate private plots by default. For more information on privacy settings see: https://plotly.com/python/privacy/
import chart_studio
chart_studio.tools.set_config_file(
plotly_domain='https://plotly.your-company.com',
plotly_api_domain='https://plotly.your-company.com',
plotly_streaming_domain='https://stream-plotly.your-company.com',
world_readable=False,
sharing='private'
)
Python's virtualenv allows us create multiple working Python environments which can each use different versions of packages. We can use virtualenv from the command line to create an environment using plotly.py version 3.3.0 and a separate one using plotly.py version 2.7.0. See the virtualenv documentation for more info.
Install virtualenv globally
$ sudo pip install virtualenv
Create your virtualenvs
$ mkdir ~/.virtualenvs
$ cd ~/.virtualenvs
$ python -m venv plotly2.7
$ python -m venv plotly3.3
Activate the virtualenv.
You will see the name of your virtualenv in parenthesis next to the input promt.
$ source ~/.virtualenvs/plotly2.7/bin/activate
(plotly2.7) $
Install plotly locally to virtualenv (note that we don't use sudo).
(plotly2.7) $ pip install plotly==2.7
Deactivate to exit
Install Jupyter into a virtualenv
$ source ~/.virtualenvs/plotly3.3/bin/activate
(plotly3.3) $ pip install notebook
Start the Jupyter kernel from a virtualenv
(plotly3.3) $ jupyter notebook
When plotting online, the plot and data will be saved to your cloud account. There are two methods for plotting online: py.plot() and py.iplot(). Both options create a unique url for the plot and save it in your Plotly account.
py.plot() to return the unique url and optionally open the url.py.iplot() when working in a Jupyter Notebook to display the plot in the notebook.Copy and paste one of the following examples to create your first hosted Plotly graph using the Plotly Python library:
import chart_studio.plotly as py
import plotly.graph_objects as go
trace0 = go.Scatter(
x=[1, 2, 3, 4],
y=[10, 15, 13, 17]
)
trace1 = go.Scatter(
x=[1, 2, 3, 4],
y=[16, 5, 11, 9]
)
data = [trace0, trace1]
py.plot(data, filename = 'basic-line', auto_open=True)
'https://plotly.com/~PythonPlotBot/27/'
Checkout the docstrings for more information:
import chart_studio.plotly as py
help(py.plot)
Help on function plot in module chart_studio.plotly.plotly:
plot(figure_or_data, validate=True, **plot_options)
Create a unique url for this plot in Plotly and optionally open url.
plot_options keyword arguments:
filename (string) -- the name that will be associated with this figure
auto_open (default=True) -- Toggle browser options
True: open this plot in a new browser tab
False: do not open plot in the browser, but do return the unique url
sharing ('public' | 'private' | 'secret') -- Toggle who can view this
graph
- 'public': Anyone can view this graph. It will appear in your profile
and can appear in search engines. You do not need to be
logged in to Plotly to view this chart.
- 'private': Only you can view this plot. It will not appear in the
Plotly feed, your profile, or search engines. You must be
logged in to Plotly to view this graph. You can privately
share this graph with other Plotly users in your online
Plotly account and they will need to be logged in to
view this plot.
- 'secret': Anyone with this secret link can view this chart. It will
not appear in the Plotly feed, your profile, or search
engines. If it is embedded inside a webpage or an IPython
notebook, anybody who is viewing that page will be able to
view the graph. You do not need to be logged in to view
this plot.
world_readable (default=True) -- Deprecated: use "sharing".
Make this figure private/public
import chart_studio.plotly as py
import plotly.graph_objects as go
trace0 = go.Scatter(
x=[1, 2, 3, 4],
y=[10, 15, 13, 17]
)
trace1 = go.Scatter(
x=[1, 2, 3, 4],
y=[16, 5, 11, 9]
)
data = [trace0, trace1]
py.iplot(data, filename = 'basic-line')
See more examples in our IPython notebook documentation or check out the py.iplot() docstring for more information.
import chart_studio.plotly as py
help(py.iplot)
Help on function iplot in module chart_studio.plotly.plotly:
iplot(figure_or_data, **plot_options)
Create a unique url for this plot in Plotly and open in IPython.
plot_options keyword arguments:
filename (string) -- the name that will be associated with this figure
sharing ('public' | 'private' | 'secret') -- Toggle who can view this graph
- 'public': Anyone can view this graph. It will appear in your profile
and can appear in search engines. You do not need to be
logged in to Plotly to view this chart.
- 'private': Only you can view this plot. It will not appear in the
Plotly feed, your profile, or search engines. You must be
logged in to Plotly to view this graph. You can privately
share this graph with other Plotly users in your online
Plotly account and they will need to be logged in to
view this plot.
- 'secret': Anyone with this secret link can view this chart. It will
not appear in the Plotly feed, your profile, or search
engines. If it is embedded inside a webpage or an IPython
notebook, anybody who is viewing that page will be able to
view the graph. You do not need to be logged in to view
this plot.
world_readable (default=True) -- Deprecated: use "sharing".
Make this figure private/public
You can also create plotly graphs with matplotlib syntax. Learn more in our matplotlib documentation.
Plotly allows you to create graphs offline and save them locally. There are also two methods for interactive plotting offline: plotly.io.write_html() and plotly.io.show().
plotly.io.write_html() to create and standalone HTML that is saved locally and opened inside your web browser.plotly.io.show() when working offline in a Jupyter Notebook to display the plot in the notebook.For information on all of the ways that plotly figures can be displayed, see Displaying plotly figures with plotly for Python.
Copy and paste one of the following examples to create your first offline Plotly graph using the Plotly Python library:
import plotly.graph_objects as go
import plotly.io as pio
fig = go.Figure(go.Scatter(x=[1, 2, 3, 4], y=[4, 3, 2, 1]))
fig.update_layout(title_text='hello world')
pio.write_html(fig, file='hello_world.html', auto_open=True)
Learn more by calling help():
import plotly
help(plotly.io.write_html)
Help on function write_html in module plotly.io._html:
write_html(fig, file, config=None, auto_play=True, include_plotlyjs=True, include_mathjax=False, post_script=None, full_html=True, animation_opts=None, validate=True, default_width='100%', default_height='100%', auto_open=False)
Write a figure to an HTML file representation
Parameters
----------
fig:
Figure object or dict representing a figure
file: str or writeable
A string representing a local file path or a writeable object
(e.g. an open file descriptor)
config: dict or None (default None)
Plotly.js figure config options
auto_play: bool (default=True)
Whether to automatically start the animation sequence on page load
if the figure contains frames. Has no effect if the figure does not
contain frames.
include_plotlyjs: bool or string (default True)
Specifies how the plotly.js library is included/loaded in the output
div string.
If True, a script tag containing the plotly.js source code (~3MB)
is included in the output. HTML files generated with this option are
fully self-contained and can be used offline.
If 'cdn', a script tag that references the plotly.js CDN is included
in the output. HTML files generated with this option are about 3MB
smaller than those generated with include_plotlyjs=True, but they
require an active internet connection in order to load the plotly.js
library.
If 'directory', a script tag is included that references an external
plotly.min.js bundle that is assumed to reside in the same
directory as the HTML file. If `file` is a string to a local file path
and `full_html` is True then
If 'directory', a script tag is included that references an external
plotly.min.js bundle that is assumed to reside in the same
directory as the HTML file. If `file` is a string to a local file
path and `full_html` is True, then the plotly.min.js bundle is copied
into the directory of the resulting HTML file. If a file named
plotly.min.js already exists in the output directory then this file
is left unmodified and no copy is performed. HTML files generated
with this option can be used offline, but they require a copy of
the plotly.min.js bundle in the same directory. This option is
useful when many figures will be saved as HTML files in the same
directory because the plotly.js source code will be included only
once per output directory, rather than once per output file.
If 'require', Plotly.js is loaded using require.js. This option
assumes that require.js is globally available and that it has been
globally configured to know how to find Plotly.js as 'plotly'.
This option is not advised when full_html=True as it will result
in a non-functional html file.
If a string that ends in '.js', a script tag is included that
references the specified path. This approach can be used to point
the resulting HTML file to an alternative CDN or local bundle.
If False, no script tag referencing plotly.js is included. This is
useful when the resulting div string will be placed inside an HTML
document that already loads plotly.js. This option is not advised
when full_html=True as it will result in a non-functional html file.
include_mathjax: bool or string (default False)
Specifies how the MathJax.js library is included in the output html
div string. MathJax is required in order to display labels
with LaTeX typesetting.
If False, no script tag referencing MathJax.js will be included in the
output.
If 'cdn', a script tag that references a MathJax CDN location will be
included in the output. HTML div strings generated with this option
will be able to display LaTeX typesetting as long as internet access
is available.
If a string that ends in '.js', a script tag is included that
references the specified path. This approach can be used to point the
resulting HTML div string to an alternative CDN.
post_script: str or list or None (default None)
JavaScript snippet(s) to be included in the resulting div just after
plot creation. The string(s) may include '{plot_id}' placeholders
that will then be replaced by the `id` of the div element that the
plotly.js figure is associated with. One application for this script
is to install custom plotly.js event handlers.
full_html: bool (default True)
If True, produce a string containing a complete HTML document
starting with an <html> tag. If False, produce a string containing
a single <div> element.
animation_opts: dict or None (default None)
dict of custom animation parameters to be passed to the function
Plotly.animate in Plotly.js. See
https://github.com/plotly/plotly.js/blob/master/src/plots/animation_attributes.js
for available options. Has no effect if the figure does not contain
frames, or auto_play is False.
default_width, default_height: number or str (default '100%')
The default figure width/height to use if the provided figure does not
specify its own layout.width/layout.height property. May be
specified in pixels as an integer (e.g. 500), or as a css width style
string (e.g. '500px', '100%').
validate: bool (default True)
True if the figure should be validated before being converted to
JSON, False otherwise.
auto_open: bool (default True
If True, open the saved file in a web browser after saving.
This argument only applies if `full_html` is True.
Returns
-------
str
Representation of figure as an HTML div string
import plotly.graph_objects as go
import plotly.io as pio
fig = go.Figure(go.Scatter(x=[1, 2, 3, 4], y=[4, 3, 2, 1]))
fig.update_layout(title_text='hello world')
pio.show(fig)
You can also call plotly.io.show directly from the go.Figure object.
fig.show()
import plotly
help(plotly.io.show)
Help on function show in module plotly.io._renderers:
show(fig, renderer=None, validate=True, **kwargs)
Show a figure using either the default renderer(s) or the renderer(s)
specified by the renderer argument
Parameters
----------
fig: dict of Figure
The Figure object or figure dict to display
renderer: str or None (default None)
A string containing the names of one or more registered renderers
(separated by '+' characters) or None. If None, then the default
renderers specified in plotly.io.renderers.default are used.
validate: bool (default True)
True if the figure should be validated before being shown,
False otherwise.
Returns
-------
None
For more examples on plotting offline with Plotly in python please visit our offline documentation.
To use Plotly with Pandas first $ pip install pandas and then import pandas in your code like in the example below.
import chart_studio.plotly as py
import plotly.graph_objects as go
import pandas as pd
df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/gapminder2007.csv')
fig = go.Figure(go.Scatter(x=df.gdpPercap, y=df.lifeExp, text=df.country, mode='markers', name='2007'))
fig.update_xaxes(title_text='GDP per Capita', type='log')
fig.update_yaxes(title_text='Life Expectancy')
py.iplot(fig, filename='pandas-multiple-scatter')
Check out more examples and tutorials for using Plotly in python here!