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  • Python 条形图绘制

    import numpy as np
    import matplotlib.pyplot as plt

    plt.style.use('ggplot')
    logistic_regression = [
    [184, 111, 76],
    [116, 80, 62],
    [15, 6, 3]
    ]

    engines = ['Hadoop', 'HadoopBinMem', 'Spark']
    colors = 'rgb'

    fig, ax1 = plt.subplots(ncols=1)

    idx = np.arange(len(logistic_regression[0]))

    n = len(logistic_regression)
    width = 1.0 / (n + 1)
    for i in range(n):
    ax1.bar(idx + i * width, logistic_regression[i], width, color=colors[i], alpha=0.5)
    xpos = idx + (i + 0.5) * width
    ypos = logistic_regression[i]
    #for j in range(len(ypos)):
    #ax1.text(xpos[j], ypos[j], str(ypos[j]), ha='center', va='bottom', rotation=90)
    ax1.legend(engines)
    #ax1.set_xticks(idx + 0.5, [25, 50, 100])
    ax1.set_xticks(idx+1*0.25)
    ax1.set_xticklabels(["ISSC","kmeans","Spectralclustering"])
    #ax1.set_xlim([1, 4])

    ax1.set_xlabel('Number of machines')
    ax1.set_ylabel('Iteration time (s)')
    ax1.set_title('Logistic Regression')

    plt.show()





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  • 原文地址:https://www.cnblogs.com/altlb/p/7890132.html
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