目录
matplotlib
- 图形可视化，主要用来画图
- 别问，问就是看不懂
条形图
import matplotlib.pyplot as plt# 只识别英语，所以通过以下两行增加中文字体from matplotlib.font_manager import FontProperties# 字体路径根据电脑而定font = FontProperties(fname='M:\STKAITI.TTF')# jupyter 默认不显示图片，通过这一行告诉他显示%matplotlib inlineclasses = ['1班', '2班', '3班', '4班'] # 相当于columnsstudent_amounts = [30, 20, 30, 40] # 值classes_index = range(len(classes)) # [0, 1, 2, 3]plt.bar(classes_index, student_amounts)plt.xticks(classes_index, classes, FontProperties=font)for ind,student_amount in enumerate(student_amounts): print(ind,student_amount) plt.text(ind,student_amount+1,student_amount)plt.xlabel('班级', FontProperties=font)plt.ylabel('学生人数', FontProperties=font)plt.title('班级-学生人数', FontProperties=font)plt.show() 0 301 202 303 40
## 直方图
import numpy as npimport matplotlib.pyplot as pltfrom matplotlib.font_manager import FontProperties%matplotlib inlinefont = FontProperties(fname='M:\STKAITI.TTF')mu1, mu2, sigma = 50, 100, 10x1 = mu2 + sigma * np.random.randn(10000)print(x1)
[ 93.49947877 86.87378653 98.0194217 ... 108.33555519 90.58512015 102.19048574]
x1 = np.random.randn(10000)print(x1)
[ 0.85927045 -0.8061112 1.30878058 ... -0.32700199 -0.67669564 0.25750884]
x2 = mu2 + sigma*np.random.randn(10000)print(x2)
[101.62589858 109.86489987 117.41374105 ... 97.52364544 107.21076273 99.56765772]
plt.hist(x1, bins=100)plt.hist(x2, bins=100)plt.show()
plt.style.use('ggplot')fig = plt.figure()# 相当于把一整块画板分成了1行2列的两个画板ax1 = fig.add_subplot(121)ax1.hist(x1, bins=100, color='red')ax1.set_title('红色', fontproperties=font)ax2 = fig.add_subplot(122)ax2.hist(x2, bins=100, color='yellow')ax2.set_title('黄色', fontproperties=font)fig.suptitle('大标题', fontproperties=font, fontsize=15, weight='bold')plt.show() 
折线图
import numpy as npimport matplotlib.pyplot as pltfrom matplotlib.font_manager import FontProperties%matplotlib inlinefont = FontProperties(fname='M:\STKAITI.TTF')
plt.style.use('ggplot')np.random.seed(1)data1 = np.random.rand(40).cumsum()data2 = np.random.rand(40).cumsum()data3 = np.random.rand(40).cumsum()data4 = np.random.rand(40).cumsum() plt.plot(data1, color='r', linestyle='-', alpha=0.5, label='红色')plt.plot(data2, color='green', linestyle='--', label='绿色')plt.plot(data3, color='yellow', linestyle=':', label='黄色')plt.plot(data4, color='blue', linestyle='-.', label='蓝色')plt.legend(prop=font)plt.show()
arr = np.array([1, 2, 3, 4])arr.cumsum()# 1,1+2,1+2+3,1+2+3+4
array([ 1, 3, 6, 10], dtype=int32)
散点图
import numpy as npimport matplotlib.pyplot as pltfrom matplotlib.font_manager import FontProperties%matplotlib inlinefont = FontProperties(fname='M:\STKAITI.TTF')
x = np.arange(1, 20)x
array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19])
y_linear = x**2y_linear
array([ 1, 4, 9, 16, 25, 36, 49, 64, 81, 100, 121, 144, 169, 196, 225, 256, 289, 324, 361], dtype=int32)
y_log = np.log(x)y_log
array([0. , 0.69314718, 1.09861229, 1.38629436, 1.60943791, 1.79175947, 1.94591015, 2.07944154, 2.19722458, 2.30258509, 2.39789527, 2.48490665, 2.56494936, 2.63905733, 2.7080502 , 2.77258872, 2.83321334, 2.89037176, 2.94443898])
fig = plt.figure()ax1 = fig.add_subplot(311)ax1.scatter(x, y_linear, color='red', marker='o', s=100)ax1.scatter(x, y_log, color='blue', marker='*', s=30)ax1.set_title('scatter')ax2 = fig.add_subplot(313)ax2.plot(x, y_linear)ax2.plot(x, y_log)ax2.set_title('plot')plt.plotplt.show() 