随笔分类 - python可视化
摘要：import numpy as npimport matplotlib.pyplot as pltfrom sklearn import linear_modelfrom sklearn import datasets%matplotlib inlinediabetes = datasets.loa
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摘要：from sklearn import linear_modellinreg = linear_model.LinearRegression()from sklearn import datasetsdiabetes = datasets.load_diabetes()diabetesx_train
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摘要：import numpy as npimport matplotlib.pyplot as pltfrom matplotlib.colors import ListedColormapfrom sklearn import datasetsfrom sklearn.neighbors import
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摘要：import numpy as npfrom sklearn import datasetsfrom sklearn.neighbors import KNeighborsClassifiernp.random.seed(0)iris = datasets.load_iris()x = iris.d
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摘要：import matplotlib.pyplot as pltfrom mpl_toolkits.mplot3d import Axes3Dfrom sklearn import datasetsfrom sklearn.decomposition import PCAiris = datasets
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摘要：import matplotlib.pyplot as pltimport matplotlib.patches as mpatchesfrom sklearn import datasetsiris = datasets.load_iris()x = iris.data[:,0]y = iris.
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摘要：import matplotlib.pyplot as pltimport numpy as npgs = plt.GridSpec(3,3)fig = plt.figure(figsize=(6,6))x1 = np.array([1,3,2,5])y1 = np.array([4,3,7,2])
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摘要：import matplotlib.pyplot as pltimport numpy as npfig = plt.figure()ax = fig.add_axes([0.1,0.1,0.8,0.8])inner_ax = fig.add_axes([0.6,0.6,0.25,0.25])x1
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摘要：import matplotlib.pyplot as pltimport numpy as npfrom mpl_toolkits.mplot3d import Axes3Dx = np.arange(8)y = np.random.randint(0,10,8)y2 = y + np.rando
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摘要：import matplotlib.pyplot as pltimport numpy as npfrom mpl_toolkits.mplot3d import Axes3Dxs = np.random.randint(30,40,100)ys = np.random.randint(20,30,
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摘要：from mpl_toolkits.mplot3d import Axes3Dimport matplotlib.pyplot as pltimport numpy as npfig = plt.figure()ax = Axes3D(fig)X = np.arange(-2,2,0.1)Y = n
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摘要：from mpl_toolkits.mplot3d import Axes3Dimport matplotlib.pyplot as pltfig = plt.figure()ax = Axes3D(fig)X = np.arange(-2,2,0.1)Y = np.arange(-2,2,0.1)
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摘要：import matplotlib.pyplot as pltimport numpy as npN=8theta = np.arange(0.,2*np.pi,2*np.pi/N)radii = np.array([4,7,5,3,1,5,6,7])plt.axes([0.025,0.025,0.
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摘要：import matplotlib.pyplot as pltimport numpy as npdx = 0.01; dy = 0.01x = np.arange(-2.0,2.0,dx)y = np.arange(-2.0,2.0,dy)X,Y = np.meshgrid(x,y)#def f(
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摘要：import matplotlib.pyplot as pltlabels = ['Nokia','apple','sumsug','lumai']values = [10,30,45,15]colors = ['yellow','green','red','blue']explode = [0.3
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摘要：import matplotlib.pyplot as pltimport numpy as npimport pandas as pddata = {'series1':[1,3,4,3,5], 'series2':[2,4,5,2,4], 'series3':[3,2,3,1,3]}df = p
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摘要：import matplotlib.pyplot as pltimport numpy as npindex = np.arange(5)values1 = [5,7,3,4,6]values2 = [6,6,4,5,7]values3 = [5,6,5,4,6]bw = 0.3plt.axis([
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摘要：import matplotlib.pyplot as pltimport numpy as npindex = np.arange(5)values1 = [5,7,3,4,6]std1 = [0.8,1,0.4,0.9,1.3]plt.title('A Bar Chart')plt.barh(i
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摘要：import matplotlib.pyplot as plt import numpy as np index = [0,1,2,3,4] #index = np.arange(5) values = [5,7,3,4,6] plt.bar(index,values) plt.xticks(ind
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摘要：import matplotlib.pyplot as plt import numpy as np import pandas as pd data = {'series1':[1,3,4,3,5], 'series2':[2,4,5,2,4], 'series3':[3,2,3,1,3]} df
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