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()

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?

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()

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