Matplotlib之饼图、直方图、极坐标图、散点图

文章目录

• 1.饼图
• 2.直方图
• 3.极坐标图
• 4.散点图

1.饼图

import matplotlib.pyplot as plt

labels = 'Frogs', 'Hogs', 'Dogs', 'Logs'  #标签
sizes = [15, 30, 45, 10]  # 尺寸
explode = (0, 0.1, 0, 0)  # 哪一块凸出来
plt.pie(sizes, explode=explode, labels=labels, autopct='%1.1f%%', shadow=False, startangle=90)
#autopct：中间显示%的方式，shadow：饼图阴影，startangle：饼图起始角度

plt.axis('equal')  # 正向饼图
plt.show()

2.直方图

import numpy as np
import matplotlib.pyplot as plt

np.random.seed(0)
mu, sigma = 100, 20  # 均值和标准差
a = np.random.normal(mu, sigma, size=100)
plt.hist(a, 20, normed=1, histtype='stepfilled', facecolor='b', alpha=0.75)
plt.title('Histogram')

plt.show()

3.极坐标图

import numpy as np
import matplotlib.pyplot as plt

N=20  # 数据的个数
theta = np.linspace(0.0, 2 * np.pi, N, endpoint=False)
radii = 10 * np. random.rand(N)
width = np.pi / 4 * np. random. rand(N)

ax = plt. subplot(111, projection= 'polar')
bars = ax.bar(theta, radii, width=width, bottom=0.0)

for r, bar in zip(radii, bars):
    bar.set_facecolor(plt.cm.viridis(r / 10.))
    bar.set_alpha(0.5)

plt.show()

4.散点图

import numpy as np
import matplotlib.pyplot as plt

fig, ax = plt. subplots()
ax.plot(10*np. random.randn(100), 10*np.random.randn(100), 'o')
ax.set_title('Simple Scatter')

plt.show()