『Python』matplotlib（二）

时间：2020-05-11 16:30:18 阅读：64 评论：0 收藏：0 [点我收藏+]

1. 绘制图表组成元素的主要函数

1.1 plot()——展现量的变化趋势

import numpy as np
import matplotlib.pyplot as plt
import matplotlib
matplotlib.use(‘Qt5Agg‘) 

x = np.linspace(0.05, 10, 1000)
y = np.cos(x)

plt.plot(x, y, ls="-", lw=2, label="plot figure")
plt.legend()
plt.show()

1.2 scatter()——寻找变量之间的关系

import numpy as np
import matplotlib.pyplot as plt
import matplotlib
matplotlib.use(‘Qt5Agg‘) 

x = np.linspace(0.05, 10, 1000)
y = np.random.rand(1000)

plt.scatter(x, y, label="scatter figure")
plt.legend()
plt.show()

1.3 xlim()——设置x轴的数值显示范围

import numpy as np
import matplotlib.pyplot as plt
import matplotlib
matplotlib.use(‘Qt5Agg‘) 

x = np.linspace(0.05, 10, 1000)
y = np.random.rand(1000)

plt.scatter(x, y, label="scatter figure")
plt.legend()
plt.xlim(0.05, 10)
plt.ylim(0, 1)
plt.show()

1.4 xlabel()——设置x轴的标签文本

import numpy as np
import matplotlib.pyplot as plt
import matplotlib
matplotlib.use(‘Qt5Agg‘) 

x = np.linspace(0.05, 10, 1000)
y = np.sin(x)

plt.plot(x, y, ls="--", lw=2, c="c", label="plot figure")
plt.legend()
plt.xlabel("x-axis")
plt.ylabel("y-axis")
plt.show()

1.5 grid()——绘制刻度线的网格线

import numpy as np
import matplotlib.pyplot as plt
import matplotlib

matplotlib.use(‘Qt5Agg‘)

x = np.linspace(0.05, 10, 1000)
y = np.sin(x)

plt.plot(x, y, ls="-.", lw=2, c="c", label="plot figure")
plt.legend()
plt.grid(linestyle=":", color="r")
plt.show()

1.6 axhline()——绘制平行于x轴的水平参考线

import numpy as np
import matplotlib.pyplot as plt
import matplotlib

matplotlib.use(‘Qt5Agg‘)

x = np.linspace(0.05, 10, 1000)
y = np.sin(x)

plt.plot(x, y, ls="-.", lw=2, c="c", label="plot figure")
plt.legend()
plt.axhline(y=0.0, c="r", ls="--", lw=2)
plt.axvline(x=4.0, c="r", ls="--", lw=2)
plt.show()

1.7 axvspan()——绘制垂直于x轴的参考区域

import numpy as np
import matplotlib.pyplot as plt
import matplotlib

matplotlib.use(‘Qt5Agg‘)

x = np.linspace(0.05, 10, 1000)
y = np.sin(x)

plt.plot(x, y, ls="-.", lw=2, c="c", label="plot figure")
plt.legend()
plt.axvspan(xmin=4.0, xmax=6.0, facecolor="y", alpha=0.3)
plt.axhspan(ymin=0.0, ymax=0.5, facecolor="y", alpha=0.3)
plt.show()

1.8 annotate()——添加图形内容细节的指向型注释文本

import numpy as np
import matplotlib.pyplot as plt
import matplotlib

matplotlib.use(‘Qt5Agg‘)

x = np.linspace(0.05, 10, 1000)
y = np.sin(x)

plt.plot(x, y, ls="-.", lw=2, c="c", label="plot figure")
plt.legend()
plt.annotate(s="maximum",
             xy=(np.pi / 2, 1.0),
             xytext=((np.pi / 2) + 1.0, 0.8),
             weight="bold",
             color="b",
             arrowprops=dict(arrowstyle="->", connectionstyle="arc3", color="b")
             )
plt.show()

xy：被注释图形内容的位置坐标

xytext：注释文本的位置坐标

weight：注释文本的字体粗细风格

color：注释文本的字体颜色

arrowprops：指示被注释内容的箭头的属性字典

1.9 text()——添加图形内容细节的无指向型注释文本

import numpy as np
import matplotlib.pyplot as plt
import matplotlib

matplotlib.use(‘Qt5Agg‘)

x = np.linspace(0.05, 10, 1000)
y = np.sin(x)

plt.plot(x, y, ls="-.", lw=2, c="c", label="plot figure")
plt.legend()
plt.text(x=3.10, y=0.09, s="y=sin(x)", weight="bold", color="b")
plt.show()

1.10 title()——添加图形内容的标题

import numpy as np
import matplotlib.pyplot as plt
import matplotlib

matplotlib.use(‘Qt5Agg‘)

x = np.linspace(0.05, 10, 1000)
y = np.sin(x)

plt.plot(x, y, ls="-.", lw=2, c="c", label="plot figure")
plt.legend()
plt.title("y=sin(x)")
plt.show()

1.11 legend()——表示不同图形的文本标签图例

import numpy as np
import matplotlib.pyplot as plt
import matplotlib

matplotlib.use(‘Qt5Agg‘)

x = np.linspace(0.05, 10, 1000)
y = np.sin(x)

plt.plot(x, y, ls="-.", lw=2, c="c", label="plot figure")
plt.legend()
plt.title("y=sin(x)")
plt.show()

loc参数：

best

upper right

upper left

lower left

lower right

right

center left

center right

lower center

upper center

center