plotly

Plotly's Python graphing library makes interactive, publication-quality graphs online. Examples of how to make line plots, scatter plots, area charts, bar charts, error bars, box plots, histograms, heatmaps, subplots, multiple-axes, polar charts and bubble charts.


Keywords
d3, dashboard, declarative, graph-library, jupyter-notebook, plotly, plotly-dash, plotlyjs, python, regl, sparkles, visualization, webgl
License
MIT
Install
conda install -c anaconda plotly

Documentation

plotly.py

Latest Release
PyPI Downloads
License

Quickstart

pip install plotly==4.4.1

Inside Jupyter notebook (installable with pip install "notebook>=5.3" "ipywidgets>=7.2"):

import plotly.graph_objects as go
fig = go.Figure()
fig.add_trace(go.Scatter(y=[2, 1, 4, 3]))
fig.add_trace(go.Bar(y=[1, 4, 3, 2]))
fig.update_layout(title = 'Hello Figure')
fig.show()

See the Python documentation for more examples.

Read about what's new in plotly.py v4

Overview

plotly.py is an interactive, open-source, and browser-based graphing library for Python

Built on top of plotly.js, plotly.py is a high-level, declarative charting library. plotly.js ships with over 30 chart types, including scientific charts, 3D graphs, statistical charts, SVG maps, financial charts, and more.

plotly.py is MIT Licensed. Plotly graphs can be viewed in Jupyter notebooks, standalone HTML files, or hosted online using Chart Studio Cloud.

Contact us for consulting, dashboard development, application integration, and feature additions.



Installation

plotly.py may be installed using pip...

pip install plotly==4.4.1

or conda.

conda install -c plotly plotly=4.4.1

Jupyter Notebook Support

For use in the Jupyter Notebook, install the notebook and ipywidgets packages using pip...

pip install "notebook>=5.3" "ipywidgets==7.5"

or conda.

conda install "notebook>=5.3" "ipywidgets=7.5"

JupyterLab Support (Python 3.5+)

For use in JupyterLab, install the jupyterlab and ipywidgets packages using pip...

pip install jupyterlab==1.2 "ipywidgets==7.5"

or conda.

conda install jupyterlab=1.2
conda install "ipywidgets=7.5"

Then run the following commands to install the required JupyterLab extensions (note that this will require node to be installed):

# Avoid "JavaScript heap out of memory" errors during extension installation
# (OS X/Linux)
export NODE_OPTIONS=--max-old-space-size=4096
# (Windows)
set NODE_OPTIONS=--max-old-space-size=4096

# Jupyter widgets extension
jupyter labextension install @jupyter-widgets/jupyterlab-manager@1.1 --no-build

# FigureWidget support
jupyter labextension install plotlywidget@1.4.0 --no-build

# and jupyterlab renderer support
jupyter labextension install jupyterlab-plotly@1.4.0 --no-build

# Build extensions (must be done to activate extensions since --no-build is used above)
jupyter lab build

# Unset NODE_OPTIONS environment variable
# (OS X/Linux)
unset NODE_OPTIONS
# (Windows)
set NODE_OPTIONS=

Static Image Export

plotly.py supports static image export using the to_image and write_image functions in the plotly.io package. This functionality requires the installation of the plotly orca command line utility and the psutil Python package.

These dependencies can both be installed using conda:

conda install -c plotly plotly-orca psutil

Or, psutil can be installed using pip...

pip install psutil

and orca can be installed according to the instructions in the orca README.

Troubleshooting

Wrong Executable found

If you get an error message stating that the orca executable that was found is not valid, this may be because another executable with the same name was found on your system. Please specify the complete path to the Plotly-Orca binary that you downloaded (for instance in the Miniconda folder) with the following command:

plotly.io.orca.config.executable = '/home/your_name/miniconda3/bin/orca'

Extended Geo Support

Some plotly.py features rely on fairly large geographic shape files. The county choropleth figure factory is one such example. These shape files are distributed as a separate plotly-geo package. This package can be installed using pip...

pip install plotly-geo==1.0.0

or conda

conda install -c plotly plotly-geo=1.0.0

Chart Studio support

The chart-studio package can be used to upload plotly figures to Plotly's Chart Studio Cloud or On-Prem service. This package can be installed using pip...

pip install chart-studio==1.0.0

or conda

conda install -c plotly chart-studio=1.0.0

Migration

If you're migrating from plotly.py v3 to v4, please check out the Version 4 migration guide

If you're migrating from plotly.py v2 to v3, please check out the Version 3 migration guide

Copyright and Licenses

Code and documentation copyright 2019 Plotly, Inc.

Code released under the MIT license.

Docs released under the Creative Commons license.