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import numpy as np
import bqplot.pyplot as plt

Basic Histogram



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np.random.seed(0)
x_data = np.random.randn(100)



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fig = plt.figure(padding_y=0)
hist = plt.hist(x_data)
fig



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hist.count



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# Changing the number of bins
hist.bins = 20

Properties of Histogram



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# normalizing the count
fig = plt.figure(padding_y=0)
hist = plt.hist(x_data, normalized=True)
fig



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# changing the color
hist.colors=['orangered']



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# stroke and opacity update
hist.stroke = 'orange'
hist.opacities = [0.5] * hist.bins



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fig = plt.figure(padding_y=0)
hist = plt.hist(x_data, normalized=True)
fig



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# count is the number of elements in each interval
hist.count



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# mid points are the mid points of each interval
hist.midpoints