plotly alternatives and similar packages
Based on the "Data Visualization" category.
Alternatively, view plotly alternatives based on common mentions on social networks and blogs.
Apache Superset9.8 9.9 L2 plotly VS Apache SupersetApache Superset is a Data Visualization and Data Exploration Platform [Moved to: https://github.com/apache/superset]
diagrams9.7 9.0 plotly VS diagrams:art: Diagram as Code for prototyping cloud system architectures
redash9.7 8.6 L4 plotly VS redashMake Your Company Data Driven. Connect to any data source, easily visualize, dashboard and share your data.
matplotlib9.6 9.9 L3 plotly VS matplotlibmatplotlib: plotting with Python
bokeh9.5 9.7 L4 plotly VS bokehInteractive Data Visualization in the browser, from Python
seaborn9.2 9.4 L2 plotly VS seabornStatistical data visualization in Python
folium8.8 0.0 plotly VS foliumPython Data. Leaflet.js Maps.
Altair8.7 9.5 plotly VS AltairDeclarative statistical visualization library for Python
PyQtGraph7.9 9.4 L2 plotly VS PyQtGraphFast data visualization and GUI tools for scientific / engineering applications
ggplot7.7 0.0 L4 plotly VS ggplotggplot port for python
bqplot7.5 6.9 plotly VS bqplotPlotting library for IPython/Jupyter notebooks
VisPy7.4 9.3 L3 plotly VS VisPyMain repository for Vispy
Flask JSONDash7.2 2.1 plotly VS 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.
plotnine7.1 4.0 plotly VS plotnineA grammar of graphics for Python
pygal6.9 0.0 L2 plotly VS pygalPYthon svg GrAph plotting Library
vincent6.7 0.0 L4 plotly VS vincentA Python to Vega translator.
SnakeViz5.9 6.9 L4 plotly VS SnakeVizAn in-browser Python profile viewer
Cartopy5.7 9.0 plotly VS CartopyCartopy - a cartographic python library with matplotlib support
Graphviz5.4 7.5 plotly VS GraphvizSimple Python interface for Graphviz
pygraphviz4.5 7.7 L3 plotly VS pygraphvizPython interface to Graphviz graph drawing package
pydot4.4 0.0 plotly VS pydotPython interface to Graphviz's Dot language
tuna4.3 4.6 plotly VS tuna:fish: Python profile viewer
ipyvizzu4.2 8.3 plotly VS ipyvizzuBuild animated charts in Jupyter Notebook and similar environments with a simple Python syntax.
gif3.5 0.0 plotly VS gifThe matplotlib Animation Extension
GR3.0 7.4 plotly VS GRGR framework: a graphics library for visualisation applications
GooPyCharts2.5 0.0 L4 plotly VS GooPyChartsA Google Charts API for Python, meant to be used as an alternative to matplotlib.
SVGIS1.5 2.1 L4 plotly VS SVGISDraw SVG maps with geodata
chart1.3 0.0 plotly VS chartCharts with pure python
ONLYOFFICE Docs — document collaboration in your environment
* Code Quality Rankings and insights are calculated and provided by Lumnify.
They vary from L1 to L5 with "L5" being the highest.
Do you think we are missing an alternative of plotly or a related project?
Latest Release User forum PyPI Downloads License
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.
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
- Code of Conduct
- Version 4 Migration Guide
- New! Announcing Dash 1.0
- Community forum
plotly.py may be installed using pip...
pip install plotly==5.11.0
conda install -c plotly plotly=5.11.0
For use in JupyterLab, install the
pip install "jupyterlab>=3" "ipywidgets>=7.6"
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
pip install "notebook>=5.3" "ipywidgets>=7.5"
conda install "notebook>=5.3" "ipywidgets>=7.5"
Static Image Export
plotly.py supports static image export,
using either the
package (recommended, supported as of
plotly version 4.9) or the orca
command line utility (legacy as of
plotly version 4.9).
kaleido package has no dependencies and can be installed
pip install -U kaleido
conda install -c conda-forge python-kaleido
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
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
plotly-geo package. This package can be installed using pip...
pip install plotly-geo==1.0.0
conda install -c plotly plotly-geo=1.0.0
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.