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Linked Brushing Example

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Linked Brushing Example

This example uses the standard Iris dataset and plots it with a linked brushing tool for dynamically exploring the data. The paintbrush button at the bottom left can be used to enable and disable the behavior.

Python source code: [download source: linked_brush.py]


import numpy as np
import matplotlib
import matplotlib.pyplot as plt
from sklearn.datasets import load_iris

import mpld3
from mpld3 import plugins, utils


data = load_iris()
X = data.data
y = data.target

# dither the data for clearer plotting
X += 0.1 * np.random.random(X.shape)

fig, ax = plt.subplots(4, 4, sharex="col", sharey="row", figsize=(8, 8))
fig.subplots_adjust(left=0.05, right=0.95, bottom=0.05, top=0.95,
                    hspace=0.1, wspace=0.1)

for i in range(4):
    for j in range(4):
        points = ax[3 - i, j].scatter(X[:, j], X[:, i],
                                      c=y, s=40, alpha=0.6)

# remove tick labels
for axi in ax.flat:
    for axis in [axi.xaxis, axi.yaxis]:
        axis.set_major_formatter(plt.NullFormatter())

# Here we connect the linked brush plugin
plugins.connect(fig, plugins.LinkedBrush(points))

mpld3.show()

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