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import numpy as np
import bqplot.pyplot as plt
import string

Basic Pie Chart



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data = np.random.rand(3)

fig = plt.figure(animation_duration=1000)
pie = plt.pie(data, display_labels='outside', labels=list(string.ascii_uppercase))
fig

Update Data



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n = np.random.randint(1, 10)
pie.sizes = np.random.rand(n)

Display Values



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with pie.hold_sync():
    pie.display_values = True
    pie.values_format = '.1f'

Enable sort



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pie.sort = True

Set different styles for selected slices



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pie.selected_style = {'opacity': 1, 'stroke': 'white', 'stroke-width': 2}
pie.unselected_style = {'opacity': 0.2}
pie.selected = [1]



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pie.selected = None

For more on piechart interactions, see the Mark Interactions notebook

Modify label styling



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pie.label_color = 'Red'
pie.font_size = '20px'
pie.font_weight = 'bold'

Update pie shape and style



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fig1 = plt.figure(animation_duration=1000)
pie1 = plt.pie(np.random.rand(6), inner_radius=0.05)
fig1

Change pie dimensions



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# As of now, the radius sizes are absolute, in pixels
with pie1.hold_sync():
    pie1.radius = 150
    pie1.inner_radius = 100



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# Angles are in radians, 0 being the top vertical
with pie1.hold_sync():
    pie1.start_angle = -90
    pie1.end_angle = 90

Move the pie around

x and y attributes control the position of the pie in the figure. If no scales are passed for x and y, they are taken in absolute figure coordinates, between 0 and 1.



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pie1.y = 0.1
pie1.x = 0.6
pie1.radius = 180

Change slice styles

Pie slice colors cycle through the colors and opacities attribute, as the Lines Mark.



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pie1.stroke = 'brown'
pie1.colors = ['orange', 'darkviolet']
pie1.opacities = [.1, 1]
fig1

Represent an additional dimension using Color

The Pie allows for its colors to be determined by data, that is passed to the color attribute. A ColorScale with the desired color scheme must also be passed.



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from bqplot import ColorScale, ColorAxis

n = 7
size_data = np.random.rand(n)
color_data = np.random.randn(n)

fig2 = plt.figure()
plt.scales(scales={'color': ColorScale(scheme='Reds')})
pie2 = plt.pie(size_data, color=color_data)
fig2