bqplot Interactive Demo¶Plotting in JupyterLite
bqplot can be installed in this deployment (it provides the bqplot federated
extension), but you will need to make your own deployment to have access to other
interactive widgets libraries.
%pip install -q bqplot
import numpy as np
from bqplot import *
np.random.seed(0)
n = 100
x = list(range(n))
y = np.cumsum(np.random.randn(n)) + 100.0
sc_x = LinearScale()
sc_y = LinearScale()
lines = Lines(x=x, y=y, scales={"x": sc_x, "y": sc_y})
ax_x = Axis(scale=sc_x, label="Index")
ax_y = Axis(scale=sc_y, orientation="vertical", label="lines")
Figure(marks=[lines], axes=[ax_x, ax_y], title="Lines")
lines.colors = ["green"]
lines.fill = "bottom"
lines.marker = "circle"
n = 100
x = list(range(n))
y = np.cumsum(np.random.randn(n))
sc_x = LinearScale()
sc_y = LinearScale()
bars = Bars(x=x, y=y, scales={"x": sc_x, "y": sc_y})
ax_x = Axis(scale=sc_x, label="Index")
ax_y = Axis(scale=sc_y, orientation="vertical", label="bars")
Figure(marks=[bars], axes=[ax_x, ax_y], title="Bars", animation_duration=1000)
bars.y = np.cumsum(np.random.randn(n))
import numpy as np
from bqplot import *
np.random.seed(0)
y1 = np.cumsum(np.random.randn(150)) + 100.0
y2 = np.cumsum(np.random.randn(150)) + 100.0
y3 = np.cumsum(np.random.randn(150)) + 100.0
y4 = np.cumsum(np.random.randn(150)) + 100.0
sc_x = LinearScale()
sc_y = LinearScale()
lines = Lines(x=np.arange(len(y1)), y=[y1, y2, y3, y4], scales={"x": sc_x, "y": sc_y})
ax_x = Axis(scale=sc_x, label="Index")
ax_y = Axis(scale=sc_y, orientation="vertical", label="lines")
Figure(marks=[lines], axes=[ax_x, ax_y], title="Lines")