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  • matplotlib直方图

    1、学会绘制直方图

    一个小demo:

    假设你获取了250部电影的时长(列表a中),希望统计出这些电影时长的分布状态(比如时长为100分钟到120分钟电影的数量,出现的频率)等信息,你应该如何呈现这些数据?

    a=[131, 98, 125, 131, 124, 139, 131, 117, 128, 108, 135, 138, 131, 102, 107, 114, 119, 128, 121, 142, 127, 130, 124, 101, 110, 116, 117, 110, 128, 128, 115, 99, 136, 126, 134, 95, 138, 117, 111,78, 132, 124, 113, 150, 110, 117, 86, 95, 144, 105, 126, 130,126, 130, 126, 116, 123, 106, 112, 138, 123, 86, 101, 99, 136,123, 117, 119, 105, 137, 123, 128, 125, 104, 109, 134, 125, 127,105, 120, 107, 129, 116, 108, 132, 103, 136, 118, 102, 120, 114,105, 115, 132, 145, 119, 121, 112, 139, 125, 138, 109, 132, 134,156, 106, 117, 127, 144, 139, 139, 119, 140, 83, 110, 102,123,107, 143, 115, 136, 118, 139, 123, 112, 118, 125, 109, 119, 133,112, 114, 122, 109, 106, 123, 116, 131, 127, 115, 118, 112, 135,115, 146, 137, 116, 103, 144, 83, 123, 111, 110, 111, 100, 154,136, 100, 118, 119, 133, 134, 106, 129, 126, 110, 111, 109, 141,120, 117, 106, 149, 122, 122, 110, 118, 127, 121, 114, 125, 126,114, 140, 103, 130, 141, 117, 106, 114, 121, 114, 133, 137, 92,121, 112, 146, 97, 137, 105, 98, 117, 112, 81, 97, 139, 113,134, 106, 144, 110, 137, 137, 111, 104, 117, 100, 111, 101, 110,105, 129, 137, 112, 120, 113, 133, 112, 83, 94, 146, 133, 101,131, 116, 111, 84, 137, 115, 122, 106, 144, 109, 123, 116, 111,111, 133, 150]

    import matplotlib.pyplot as plt
    import matplotlib.font_manager as font
    
    my_font = font.FontProperties(fname="C:WindowsFontssimhei.ttf")
    
    # 设置图形大小
    plt.figure(figsize=(20, 15), dpi=80)
    
    a = [131, 98, 125, 131, 124, 139, 131, 117, 128, 108, 135, 138, 131, 102, 107, 114, 119, 128, 121, 142,
         127, 130, 124, 101, 110, 116, 117, 110, 128, 128, 115, 99, 136, 126, 134, 95, 138, 117, 111, 78,
         132, 124, 113, 150, 110, 117, 86, 95, 144, 105, 126, 130, 126, 130, 126, 116, 123, 106, 112, 138,
         123, 86, 101, 99, 136, 123, 117, 119, 105, 137, 123, 128, 125, 104, 109, 134, 125, 127, 105, 120,
         107, 129, 116, 108, 132, 103, 136, 118, 102, 120, 114, 105, 115, 132, 145, 119, 121, 112, 139, 125,
         138, 109, 132, 134, 156, 106, 117, 127, 144, 139, 139, 119, 140, 83, 110, 102, 123, 107, 143, 115,
         136, 118, 139, 123, 112, 118, 125, 109, 119, 133, 112, 114, 122, 109, 106, 123, 116, 131, 127, 115, 118,
         112, 135, 115, 146, 137, 116, 103, 144, 83, 123, 111, 110, 111, 100, 154, 136, 100, 118, 119, 133, 134, 106,
         129, 126, 110, 111, 109, 141, 120, 117, 106, 149, 122, 122, 110, 118, 127, 121, 114, 125, 126, 114, 140, 103,
         130, 141, 117, 106, 114, 121, 114, 133, 137, 92, 121, 112, 146, 97, 137, 105, 98, 117, 112, 81, 97, 139, 113,
         134, 106, 144, 110, 137, 137, 111, 104, 117, 100, 111, 101, 110, 105, 129, 137, 112, 120, 113, 133, 112, 83,
         94, 146, 133, 101, 131, 116, 111, 84, 137, 115, 122, 106, 144, 109, 123, 116, 111, 111, 133, 150]
    
    # 组数要适当,太少会有较大的统计误差,大多规律不明显
    # 组数=极差/组距
    # 计算组数
    d = 3  # 组距
    num_bins = (max(a)-min(a))//d
    
    # 设置x轴刻度
    plt.xticks(range(min(a), max(a)+d, d))
    
    # 添加描述信息
    plt.xlabel("电影时长(min)", fontproperties=my_font)
    plt.ylabel("出现频率", fontproperties=my_font)
    plt.title("250部电影时长", fontproperties=my_font)
    
    
    # 绘制直方图
    plt.hist(a, num_bins, density=True, color="coral")  # normed(规范的)替换成density
    plt.grid()
    
    plt.show()
    
    

    image.png

    从图中可以清晰看出,时长主要集中在105~141min

    2、自我测试

    在美国2004年人口普查发现有124 million的人在离家相对较远的地方工作。根据他们从家到上班地点所需要的时间,通过抽样统计(最后一列)出了下表的数据,这些数据能够绘制成直方图么?

    image.png

    interval = [0,5,10,15,20,25,30,35,40,45,60,90]

    width = [5,5,5,5,5,5,5,5,5,15,30,60]

    quantity = [836,2737,3723,3926,3596,1438,3273,642,824,613,215,47]

    数据来源:https://en.wikipedia.org/wiki/Histogram

    普查报告地址:https://www.census.gov/prod/2004pubs/c2kbr-33.pdf

    前面的问题中给出的数据都是统计之后的数据,所以为了达到直方图的效果,需要绘制条形图,所以:一般来说能够使用plt.hist方法的的是那些没有统计过的数据

    import matplotlib.pyplot as plt
    import matplotlib.font_manager as font
    
    my_font = font.FontProperties(fname="C:WindowsFontssimhei.ttf")
    
    # 设置图形大小
    plt.figure(figsize=(20, 15), dpi=80)
    
    interval = [0, 5, 10, 15, 20, 25, 30, 35, 40, 45, 60, 90]
    
    width = [5, 5, 5, 5, 5, 5, 5, 5, 5, 15, 30, 60]
    
    quantity = [836, 2737, 3723, 3926, 3596, 1438, 3273, 642, 824, 613, 215, 47]
    
    # 绘制条形图
    plt.bar(range(len(quantity)), quantity, width=1, color="#ffefff")
    
    # 设置x轴刻度
    x = [i-0.5 for i in range(len(quantity)+1)]
    xtick_label = interval+[150]
    plt.xticks(x, xtick_label)
    
    # 添加描述信息
    plt.xlabel("通行时长(min)", fontproperties=my_font)
    plt.ylabel("人口数量(百万)", fontproperties=my_font)
    plt.title("Date by absolute numbers", fontproperties=my_font)
    
    plt.grid(alpha=0.5)
    plt.show()
    

    image.png

    通过条形图绘制出直方图的样式,可以看出通行时间在5~35min的人较多

    直方图还可以运用的场景:

    • 用户的年龄分布状态

    • 一段时间内用户点击次数的分布状态

    • 用户活跃时间的分布状态

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  • 原文地址:https://www.cnblogs.com/wangzheming35/p/15325155.html
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