matplotlib的基本用法

import matplotlib.pyplot as plt
import numpy as np

labels = [‘A‘,‘B‘,‘C‘,‘D‘,‘E‘]
x1 = [20,15,30,25,18]
x2 = [23,30,20,12,10]
lps = np.arange(len(labels))  # 设置刻度标签的位置
width = 0.35

# fig = plt.figure(figsize=(6,5))
# ax = fig.add_subplot()  # 与下面的等价
fig, ax = plt.subplots(figsize=(6,5))  # fig表示绘图窗口，ax表示窗口里的坐标系,可以创建多个子图
# ax1,ax2 = ax.ravel()  # 有多个子图时，获得每个子图的句柄

# 显示柱状高度
for i,j in zip(lps, x1):
    plt.text(i-width/2, j+0.005, j, ha=‘center‘, va=‘bottom‘)
for i,j in zip(lps, x2):
    plt.text(i+width/2, j+0.005, j, ha=‘center‘, va=‘bottom‘)

ax.bar(lps-width/2, x1, width=width, label=‘G1‘)
ax.bar(lps+width/2, x2, width=width, label=‘G2‘)
ax.set_xticks(lps)          # 设置柱状图的标签位置
ax.set_xticklabels(labels)  # 设置柱状图的标签，与上式联用
ax.set_ylabel(‘scores‘)
ax.set_title(‘scores of G1 and G2‘)
ax.legend()

fig.tight_layout()
plt.show()

‘‘‘
# 画多条并列的柱状图
ax.bar(lps, x1, width=width, label=‘G1‘)
ax.bar(lps+width, x2, width=width, label=‘G2‘)
ax.bar(lps+2*width, x3, width=width, label=‘G3‘)
ax.set_xticks(lps+width) 
ax.set_xticklabels(labels)  
‘‘‘

import matplotlib.pyplot as plt
import numpy as np
from scipy.stats import norm

mu,sigma = 0, 1
x = mu + sigma*np.random.randn(10000)

n, bins, patches = plt.hist(x, bins=50, density=True, facecolor=‘b‘, alpha=0.35)
y = norm.pdf(bins, mu, sigma)  # 画概率分布曲线
plt.plot(bins, y, ‘r--‘)
plt.ylabel(‘Probability‘)
plt.text(-3, .4, r‘$\mu=0,\ \sigma=1$‘)
plt.grid()
plt.show()

import matplotlib.pyplot as plt
import numpy as np

x = np.random.randint(10, 100, 6)
label = list(‘abcdef‘)
explode = (0.05,0,0,0,0,0)  # 突出显示第一块
plt.pie(x, labels=label, autopct=‘%1.1f%%‘, explode=explode)
# bbox_to_anchor 定位图例的框
plt.legend(loc="center left", bbox_to_anchor=(1, 0, 0.5, 1))
plt.show()