自学教程：Python 数据科学 Matplotlib图库详解

import matplotlib.pyplot as pltx = [1,2,3,4] # step1y = [10,20,25,30]fig = plt.figure() # step2ax = fig.add_subplot(111) # step3ax.plot(x, y, color='lightblue', linewidth=3) # step3/4ax.scatter([2,4,6],             [5,15,25],             color='darkgreen',             marker='^')ax.set_xlim(1, 6.5)plt.savefig('foo.png') # step5plt.show() # step6

import numpy as np x = np.linspace(0, 10, 100)y = np.cos(x) z = np.sin(x)

data = 2 * np.random.random((10, 10))data2 = 3 * np.random.random((10, 10))Y, X = np.mgrid[-3:3:100j, -3:3:100j]U = -1 - X**2 + YV = 1 + X - Y**2from matplotlib.cbook import get_sample_dataimg = np.load('E:/anaconda3/envs/torch/Lib/site-packages/matplotlib/mpl-data/aapl.npz')

import matplotlib.pyplot as plt

fig = plt.figure()fig2 = plt.figure(figsize=plt.figaspect(2.0))

fig.add_axes()ax1 = fig.add_subplot(221) # row-col-numax3 = fig.add_subplot(212) fig3, axes = plt.subplots(nrows=2,ncols=2)fig4, axes2 = plt.subplots(ncols=3)

fig, ax = plt.subplots()lines = ax.plot(x,y) # 用线或标记连接点ax.scatter(x,y) # 缩放或着色未连接的点axes[0,0].bar([1,2,3],[3,4,5]) # 绘制等宽纵向矩形axes[1,0].barh([0.5,1,2.5],[0,1,2]) # 绘制等高横向矩形axes[1,1].axhline(0.45) # 绘制与轴平行的横线axes[0,1].axvline(0.65) # 绘制与轴垂直的竖线ax.fill(x,y,color='blue') # 绘制填充多边形ax.fill_between(x,y,color='yellow') # 填充y值和0之间

import matplotlib.image as imgpltimg = imgplt.imread('C:/Users/Administrator/Desktop/timg.jpg') fig, ax = plt.subplots()im = ax.imshow(img, cmap='gist_earth', interpolation='nearest', vmin=-200, vmax=200)# 色彩表或RGB数组 axes2[0].pcolor(data2) # 二维数组伪彩色图axes2[0].pcolormesh(data) # 二维数组等高线伪彩色图CS = plt.contour(Y,X,U) # 等高线图axes2[2].contourf(data)     axes2[2]= ax.clabel(CS) # 等高线图标签

axes[0,1].arrow(0,0,0.5,0.5) # 为坐标轴添加箭头axes[1,1].quiver(y,z) # 二维箭头axes[0,1].streamplot(X,Y,U,V) # 二维箭头

ax1.hist(y) # 直方图ax3.boxplot(y) # 箱形图ax3.violinplot(z) # 小提琴图

plt.plot(x, x, x, x**2, x, x**3)ax.plot(x, y, alpha = 0.4)ax.plot(x, y, c='k')fig.colorbar(im, orientation='horizontal')im = ax.imshow(img,                                  cmap='seismic')

fig, ax = plt.subplots()ax.scatter(x,y,marker=".")ax.plot(x,y,marker="o")

plt.plot(x,y,linewidth=4.0)plt.plot(x,y,ls='solid') plt.plot(x,y,ls='--')plt.plot(x,y,'--',x**2,y**2,'-.')plt.setp(lines,color='r',linewidth=4.0)

ax.text(1,         -2.1,        'Example Graph',        style='italic')ax.annotate("Sine",            xy=(8, 0),             xycoords='data',            xytext=(10.5, 0),             textcoords='data',            arrowprops=dict(arrowstyle="->",            connectionstyle="arc3"),)

plt.title(r'$sigma_i=15$', fontsize=20)

ax.margins(x=0.0,y=0.1) # 添加内边距ax.axis('equal') # 将图形纵横比设置为1ax.set(xlim=[0,10.5],ylim=[-1.5,1.5]) # 设置x轴与y轴的限ax.set_xlim(0,10.5)

ax.set(title='An Example Axes',       ylabel='Y-Axis',         xlabel='X-Axis') # 设置标题与x、y轴的标签ax.legend(loc='best') # 自动选择最佳的图例位置

ax.xaxis.set(ticks=range(1,5),            ticklabels=[3,100,-12,"foo"]) # 手动设置X轴刻度ax.tick_params(axis='y',                                     direction='inout',                 length=10) # 设置Y轴长度与方向

fig3.subplots_adjust(wspace=0.5,                    hspace=0.3,                    left=0.125,                     right=0.9,                     top=0.9,                     bottom=0.1)fig.tight_layout() # 设置画布的子图布局

ax1.spines['top'].set_visible(False) # 隐藏顶部坐标轴线ax1.spines['bottom'].set_position(('outward',10)) # 设置底部边线的位置为outward

#保存画布plt.savefig('foo.png')# 保存透明画布plt.savefig('foo.png', transparent=True)

plt.show()

plt.cla() # 清除坐标轴plt.clf() #  清除画布plt.close() # 关闭窗口