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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
 Advanced Notebook
Step1:  BQPlot
Examples here are shamelessly stolen from the amazing
Step2:  ipyvolume
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Python Code:
%matplotlib inline
import numpy as np
import pandas as pd
from pandas.tools.plotting import scatter_matrix
from sklearn.datasets import load_boston
import matplotlib as mpl
import matplotlib.pyplot as plt
import seaborn as sns
sns.set_context('poster')
sns.set_style('whitegrid')
plt.rcParams['figure.figsize'] = 12, 8  # plotsize
import warnings
warnings.filterwarnings('ignore')
Explanation: Advanced Notebook
End of explanation
# mixed feelings about this import
import bqplot.pyplot as plt
import numpy as np
x = np.linspace(0, 2, 50)
y = x**2
fig = plt.figure()
scatter = plt.scatter(x, y)
plt.show()
fig.animation_duration = 500
scatter.y = 2 * x**.5
scatter.selected_style = {'stroke':'red', 'fill': 'orange'}
plt.brush_selector();
scatter.selected
scatter.selected = [1,2,10,40]
Explanation: BQPlot
Examples here are shamelessly stolen from the amazing: https://github.com/maartenbreddels/jupytercon-2017/blob/master/jupytercon2017-widgets.ipynb
End of explanation
import ipyvolume as ipv
N = 1000
x, y, z = np.random.random((3, N))
fig = ipv.figure()
scatter = ipv.scatter(x, y, z, marker='box')
ipv.show()
scatter.x = scatter.x - 0.5
scatter.x = x
scatter.color = "green"
scatter.size = 5
scatter.color = np.random.random((N,3))
scatter.size = 2
ex = ipv.datasets.animated_stream.fetch().data
ex.shape
ex[:, ::, ::4].shape
ipv.figure()
ipv.style.use('dark')
quiver = ipv.quiver(*ipv.datasets.animated_stream.fetch().data[:,::,::4], size=5)
ipv.animation_control(quiver, interval=200)
ipv.show()
ipv.style.use('light')
ipv.style.use('light')
quiver.geo = "cat"
N = 1000*1000
x, y, z = np.random.random((3, N)).astype('f4')
ipv.figure()
s = ipv.scatter(x, y, z, size=0.2)
ipv.show()
ipv.save("3d-example-plot.html")
!open 3d-example-plot.html
Explanation: ipyvolume
End of explanation
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