plotly alternatives and similar packages
Based on the "Data Visualization" category.
Alternatively, view plotly alternatives based on common mentions on social networks and blogs.
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Apache Superset
DISCONTINUED. Apache Superset is a Data Visualization and Data Exploration Platform [Moved to: https://github.com/apache/superset] -
redash
Make Your Company Data Driven. Connect to any data source, easily visualize, dashboard and share your data. -
#<Sawyer::Resource:0x00007fbd82367850>
Panel: The powerful data exploration & web app framework for Python -
Flask JSONDash
:snake: :bar_chart: :chart_with_upwards_trend: Build complex dashboards without any front-end code. Use your own endpoints. JSON config only. Ready to go. -
ipyvizzu
Build animated charts in Jupyter Notebook and similar environments with a simple Python syntax.
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README
plotly.py
Latest Release User forum PyPI Downloads License
Quickstart
pip install plotly==5.11.0
Inside Jupyter (installable with pip install "jupyterlab>=3" "ipywidgets>=7.6"
):
import plotly.express as px
fig = px.bar(x=["a", "b", "c"], y=[1, 3, 2])
fig.show()
See the Python documentation for more examples.
Overview
plotly.py is an interactive, open-source, and browser-based graphing library for Python :sparkles:
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 integrated into Dash applications.
Contact us for consulting, dashboard development, application integration, and feature additions.
- Online Documentation
- Contributing to plotly
- Changelog
- Code of Conduct
- Version 4 Migration Guide
- New! Announcing Dash 1.0
- Community forum
Installation
plotly.py may be installed using pip...
pip install plotly==5.11.0
or conda.
conda install -c plotly plotly=5.11.0
JupyterLab Support
For use in JupyterLab, install the jupyterlab
and ipywidgets
packages using pip
:
pip install "jupyterlab>=3" "ipywidgets>=7.6"
or conda
:
conda install "jupyterlab>=3" "ipywidgets>=7.6"
The instructions above apply to JupyterLab 3.x. For JupyterLab 2 or earlier, run the following commands to install the required JupyterLab extensions (note that this will require node
to be installed):
# JupyterLab 2.x renderer support
jupyter labextension install [email protected] @jupyter-widgets/jupyterlab-manager
Please check out our Troubleshooting guide if you run into any problems with JupyterLab.
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"
Static Image Export
plotly.py supports static image export,
using either the kaleido
package (recommended, supported as of plotly
version 4.9) or the orca
command line utility (legacy as of plotly
version 4.9).
Kaleido
The kaleido
package has no dependencies and can be installed
using pip...
pip install -U kaleido
or conda.
conda install -c conda-forge python-kaleido
Orca
While Kaleido is now the recommended image export approach because it is easier to install
and more widely compatible, static image export
can also be supported
by the legacy orca command line utility and the
psutil
Python package.
These dependencies can both be installed using conda:
conda install -c plotly plotly-orca==1.3.1 psutil
Or, psutil
can be installed using pip...
pip install psutil
and orca can be installed according to the instructions in the orca README.
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
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.
*Note that all licence references and agreements mentioned in the plotly README section above
are relevant to that project's source code only.