scatter绘制散点图示例

1、example 1

from sklearn import datasetsdigits = datasets.load_digits()import matplotlib.pyplot as pltcolors = ['black', 'blue', 'purple', 'yellow', 'white', 'red', 'lime', 'cyan', 'orange', 'gray']for i in range(len(colors)):    x = reduced_data_rpca[:, 0][digits.target == i]    y = reduced_data_rpca[:, 1][digits.target == i]    plt.scatter(x, y, c=colors[i])plt.legend(digits.target_names, bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)plt.xlabel('First Principal Component')plt.ylabel('Second Principal Component')plt.title("PCA Scatter Plot")plt.show()

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2、example 2

from sklearn import datasetsimport matplotlib.pyplot as pltimport pylab as Plotimport numpy as npimport scipy.io as siocolors = ['black', 'blue', 'purple', 'yellow', 'white', 'red', 'lime', 'cyan', 'orange', 'gray']mat_ = sio.loadmat('softmax.mat')X = mat_['dataset_feats']data = X[0:200,:]data = np.array(data)labels = mat_['dataset_labels']labels = labels[0,0:200]labels = np.array(labels)l = np.unique(labels)Y = sio.loadmat('Y.mat')Y = Y['Y']Y = np.array(Y)colors = ['black', 'blue', 'purple', 'yellow', 'white', 'red', 'lime', 'cyan', 'orange', 'gray']idx = []for i in range(len(colors)):    idx = np.where(labels==i)    plt.scatter(Y[idx,0], Y[idx,1],color = colors[i], label= l[i] , s = 20)plt.legend(loc='upper right')plt.show()

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3、example 3

import matplotlib.pyplot as pltimport numpy as npn = 100for color in ['red','blue','green']:    x,y=np.random.rand(2,n)    scale=100*np.random.rand(n)    plt.scatter(x,y,c=color,s=scale,label=color,alpha=0.6,edgecolors='white')plt.title('Scatter')plt.xlabel('x')plt.ylabel('y')plt.legend()plt.grid(True)plt.show()

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