Our first engine, bqplot, is a Jupyter-based interactive plotting system.
It presents two principal interfaces:
pyplot-like interface, for making the transition from matplotlib easierWe will be using the latter far more frequently than the former.
Now that we've learned a bit about widgets, we can start to dig into bqplot.
bqplot is based around traitlets and widget objects; every object you work
with will have traits and may be represented as a widget.
When we use bqplot we will be constructing Figure objects, which will
contain marks and axes. To use these, we will build mark objects (Bars,
Lines, Scatter, Map, etc) and describe the relationship between points
using Scale objects.
We will be building out these objects and their relationships to develop interactivity.
Lines to
represent.Scale objects describe relationships between visual attributes (position)
and data values.Axis objects are where data are placed.Figure objects contain marks and axes, as well as interaction.Our first example will be a simple lineplot.
import bqplot
import numpy as np
x = np.arange(100)
y = np.random.random(100) + 5
x_sc = bqplot.LinearScale()
y_sc = bqplot.LinearScale()
lines = bqplot.Lines(x = x, y = y, scales = {'x': x_sc, 'y': y_sc})
ax_x = bqplot.Axis(scale = x_sc, label = 'X value')
ax_y = bqplot.Axis(scale = y_sc, label = 'Y value', orientation = 'vertical')
fig = bqplot.Figure(marks = [lines], axes = [ax_x, ax_y])
display(fig)This week we will not have an assignment.
However, you are encouraged to practice the work we've done with traitlets,
ipywidgets and bqplot.
Today we are going to build comparisons with our (virtual) hands.