bfelds / bqplot

Plotting library for IPython/Jupyter Notebooks

bqplot

bqplot is a Grammar of Graphics based interactive plotting framework for the Jupyter notebook.

Goals

• provide a unified framework for 2d visualizations with a pythonic API.
• provide a sensible API for adding user interactions (panning, zooming, selection, etc)

Two APIs are provided

• Users can build custom visualizations using the internal object model, which is inspired by the constructs of the Grammar of Graphics (figure, marks, axes, scales), and enrich their visualization with our Interaction Layer.
• Or they can use the context-based API similar to Matplotlib's pyplot, which provides sensible default choices for most parameters.

Getting Started

Dependencies

This package depends on the following packages:

• numpy
• ipywidgets (version >=5.0.0)

Installation

Using pip:

$ pip install bqplot
$ jupyter nbextension enable --py bqplot

Using conda

$ conda install -c conda-forge bqplot

For a development installation (requires npm):

$ git clone https://github.com/bloomberg/bqplot.git
$ cd bqplot
$ pip install -e .
$ jupyter nbextension install --py --symlink --user bqplot
$ jupyter nbextension enable --py --user bqplot

Note for developers: the --symlink argument on Linux or OS X allows one to modify the JavaScript code in-place. This feature is not available with Windows.

Loading bqplot

# In a Jupyter notebook
import bqplot

That's it! You're ready to go!

Examples

Using the pyplot API

from bqplot import pyplot as plt
import numpy as np

plt.figure(1)
np.random.seed(0)
n = 200
x = np.linspace(0.0, 10.0, n)
y = np.cumsum(np.random.randn(n))
plt.plot(x,y, axes_options={'y': {'grid_lines': 'dashed'}})
plt.show()

Using the bqplot internal object model

import numpy as np
from IPython.display import display
import bqplot as bq

size = 20
np.random.seed(0)

x_data = np.arange(size)

x_ord = bq.OrdinalScale()
y_sc = bq.LinearScale()

bar = bq.Bars(x=x_data, y=np.random.randn(2, size), scales={'x': x_ord, 'y': y_sc},
              type='stacked')
line = bq.Lines(x=x_data, y=np.random.randn(size), scales={'x': x_ord, 'y': y_sc},
                stroke_width=3, colors=['red'], display_legend=True, labels=['Line chart'])

ax_x = bq.Axis(scale=x_ord)
ax_y = bq.Axis(scale=y_sc, orientation='vertical', tick_format='0.2f', grid_lines='solid')

fig = bq.Figure(marks=[bar, line], axes=[ax_x, ax_y])
display(fig)

Help / Documentation

• API reference documentation:

• Talk to us on our Gitter chat:

License

This software is licensed under the Apache 2.0 license. See the LICENSE file for details.