import matplotlib.pyplot as plt
import numpy as np
if __name__ == "__main__":
# 0、修改支持中文的字体
plt.rcParams["font.sans-serif"] = ["SimHei"] # 设置字体
plt.rcParams["axes.unicode_minus"] = False # 解决图像中 "-" 负号乱码问题
# 电影时长分布
time = [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]
plt.figure(figsize=(20, 8), dpi=80)
# 组距
dist = 2
# 组数
group_number = (max(time) - min(time)) // 2
# bins 组数
# density 是否显示频率,不显示频率就是显示频数
# plt.hist(time, bins=group_number)
# 显示频率
plt.hist(time, bins=group_number, density=True)
plt.xticks(range(min(time), max(time) + 2, dist))
plt.grid(linestyle="--", alpha=0.5)
plt.show()
1、组距会影响直方图的显示效果,请注意组距的设置
2、直方图应用场景:用于表示分布情况,通过直方图还可以观察和估计哪些数据比较集中,异常或者孤立数据分布在何处