Python3使用matplotlib绘制直方图
Python3使用matplotlib绘制直方图代码及解析。
频数分布直方图
代码
from matplotlib import pyplot as plt
from matplotlib import font_manager
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]
# 数据如果在100以内分为5-12组
# 组距:指的是每个小组两个端点的距离
# 组数:极差/组距
# 计算组数
d = 6 # 组距
num_bins = (max(a) - min(a)) // d
# a为传入的数据 其中数据应该都是数字类型的 num_bins为需要将数据分为多少组
plt.hist(a, num_bins)
plt.xticks(range(min(a), max(a) + d, d))
# 设置网格
plt.grid()
plt.show()
效果图
频率分布直方图
from matplotlib import pyplot as plt
from matplotlib import font_manager
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]
# 数据如果在100以内分为5-12组
# 组距:指的是每个小组两个端点的距离
# 组数:极差/组距
# 计算组数
d = 6 # 组距
num_bins = (max(a) - min(a)) // d
# a为传入的数据 其中数据应该都是数字类型的 num_bins为需要将数据分为多少组
# density为1或者为True时 可以改变为频率分布直方图
plt.hist(a, num_bins,density=1)
plt.xticks(range(min(a), max(a) + d, d))
# 设置网格
plt.grid()
plt.savefig("./05.png")
plt.show()
效果图
注意
相对于频数分布直方图,频率分布直方图在hist函数中添加了一个参数density(或者normed),当其为1或者True时,就可以生成频率分布直方图,要注意的是normed在以后的版本会被替换.
一般来说hist都是绘制没有经过统计过的数据,hist拿到数据后会自动对数据进行分组.
The 'normed' kwarg was deprecated in Matplotlib 2.1 and will be removed in 3.1. Use 'density' instead.
统计过的数据绘制直方图
代码
from matplotlib import pyplot as plt
from matplotlib import font_manager
# 时间段
interval = [0,5,10,15,20,25,30,35,40,45,60,90]
# 组距
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]
# 设置图形大小
plt.figure(figsize=(20,8),dpi=80)
plt.bar(range(len(quantity)),quantity,width=1)
# 设置x轴数字
_x = [i-0.5 for i in range(13)]
_xtick_lacel = interval+[150]
plt.xticks(_x,_xtick_lacel)
plt.grid(alpha=0.4)
plt.savefig("./06.png")
plt.show()
效果图
