Python 数据科学 Matplotlib图库详解

import matplotlib.pyplot as plt
x = [1,2,3,4] # step1
y = [10,20,25,30]
fig = plt.figure() # step2
ax = fig.add_subplot(111) # step3
ax.plot(x, y, color='lightblue', linewidth=3) # step3\4
ax.scatter([2,4,6], 
            [5,15,25], 
            color='darkgreen', 
            marker='^')
ax.set_xlim(1, 6.5)
plt.savefig('foo.png') # step5
plt.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 + Y
V = 1 + X - Y**2
from matplotlib.cbook import get_sample_data
img = 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-num
ax3 = 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 imgplt
img = 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1
ax.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