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%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')


    

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# mixed feelings about this import
import bqplot.pyplot as plt
import numpy as np


    

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x = np.linspace(0, 2, 50)
y = x**2


    

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fig = plt.figure()
scatter = plt.scatter(x, y)
plt.show()


    

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fig.animation_duration = 500
scatter.y = 2 * x**.5


    

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scatter.selected_style = {'stroke':'red', 'fill': 'orange'}
plt.brush_selector();


    

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scatter.selected


    

    
Out[7]:





[]

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scatter.selected = [1,2,10,40]


    

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import ipyvolume as ipv


    

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N = 1000
x, y, z = np.random.random((3, N))


    

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fig = ipv.figure()
scatter = ipv.scatter(x, y, z, marker='box')
ipv.show()


    

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scatter.x = scatter.x - 0.5


    

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scatter.x = x


    

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scatter.color = "green"
scatter.size = 5


    

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scatter.color = np.random.random((N,3))


    

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scatter.size = 2


    

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ex = ipv.datasets.animated_stream.fetch().data


    

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ex.shape


    

    
Out[18]:





(6, 200, 1250)

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ex[:, ::, ::4].shape


    

    
Out[19]:





(6, 200, 313)

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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')


    

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ipv.style.use('light')


    

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quiver.geo = "cat"


    

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N = 1000*1000
x, y, z = np.random.random((3, N)).astype('f4')


    

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ipv.figure()
s = ipv.scatter(x, y, z, size=0.2)
ipv.show()


    

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ipv.save("3d-example-plot.html")


    

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!open 3d-example-plot.html


    

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