bqplot alternatives and similar packages
Based on the "Data Visualization" category.
Alternatively, view bqplot alternatives based on common mentions on social networks and blogs.
9.8 9.9 L2 bqplot VS Apache SupersetApache Superset is a Data Visualization and Data Exploration Platform [Moved to: https://github.com/apache/superset]
9.6 7.8 L4 bqplot VS redashMake Your Company Data Driven. Connect to any data source, easily visualize, dashboard and share your data.
9.3 9.4 L2 bqplot VS plotlyThe interactive graphing library for Python (includes Plotly Express) :sparkles:
7.7 9.7 L2 bqplot VS PyQtGraphFast data visualization and GUI tools for scientific / engineering applications
* 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 bqplot or a related project?
2-D plotting library for Project Jupyter
bqplot is a 2-D visualization system for Jupyter, based on the constructs of
the Grammar of Graphics.
In bqplot, every component of a plot is an interactive widget. This allows the user to integrate visualizations with other Jupyter interactive widgets to create integrated GUIs with a few lines of Python code.
- Provide a unified framework for 2-D visualizations with a pythonic API
- Provide a sensible API for adding user interactions (panning, zooming, selection, etc)
Two APIs are provided
Object Model, which is inspired by the constructs of the Grammar of Graphics (figure, marks, axes, scales). This API is verbose but is fully customizable
pyplot, which is a context-based API similar to Matplotlib's pyplot.
pyplotprovides sensible default choices for most parameters
Trying it online
To try out bqplot interactively in your web browser, just click on the binder link:
This package depends on the following packages:
ipywidgets(version >=7.0.0, <8.0)
traitlets(version >=4.3.0, <5.0)
traittypes(Version >=0.2.1, <0.3)
$ pip install bqplot
$ conda install -c conda-forge bqplot
If you are using JupyterLab <=2:
$ jupyter labextension install @jupyter-widgets/jupyterlab-manager bqplot
For a development installation (requires JupyterLab (version >= 3) and yarn):
$ git clone https://github.com/bqplot/bqplot.git $ cd bqplot $ pip install -e . $ jupyter nbextension install --py --overwrite --symlink --sys-prefix bqplot $ jupyter nbextension enable --py --sys-prefix bqplot
Note for developers: the
--symlink argument on Linux or OS X allows one to
For the experimental JupyterLab extension, install the Python package, make sure the Jupyter widgets extension is installed, and install the bqplot extension:
$ pip install "ipywidgets>=7.6" $ jupyter labextension develop . --overwrite
cd js yarn run build
Then refreshing the JupyterLab/Jupyter Notebook is enough to reload the changes.
You can install the dependencies necessary to run the tests with:
conda env update -f test-environment.yml
And run it with for Python tests:
cd js to run the JS tests with:
yarn run test
Every time you make a change on your tests it's necessary to rebuild the JS side:
yarn run build
Object Model API
Full documentation is available at https://bqplot.readthedocs.io/
Install a previous bqplot version (Only for JupyterLab <= 2)
For example, in order to install bqplot
0.11.9, you need the labextension version
$ pip install bqplot==0.11.9 $ jupyter labextension install [email protected]
Versions lookup table:
See our [contributing guidelines](CONTRIBUTING.md) to know how to contribute and set up a development environment.
This software is licensed under the Apache 2.0 license. See the [LICENSE](LICENSE) file for details.
*Note that all licence references and agreements mentioned in the bqplot README section above are relevant to that project's source code only.