matplotlib draws histograms, pie charts, scatter plots , bubble charts, box plots, radar charts http://t.csdn.cn/ZeXim

Parameter configuration of matplotlib: http://t.csdn.cn/TiI79

1. Set the labels of the x-axis and y-axis

xlabel(xlabel,fontdict=None,labelpad=None)
ylabel(ylabel,fontdict=None,labelpad=None)

• xlabel/ylabel: Indicates the label text of the x-axis (y-axis).

• fontdict: Represents a dictionary that controls the text style of the label.

• labelpad: Indicates the distance between the label and the axis frame (including scale and scale label).

Sample code:

# 标签
import numpy as np
import matplotlib.pyplot as plt
# 支持中文
plt.rcParams['font.sans-serif'] = ['SimHei']  # 用来正常显示中文标签
plt.rcParams['axes.unicode_minus'] = False  # 用来正常显示负号
x=np.linspace(-np.pi,np.pi,256,endpoint=True)
y1,y2=np.sin(x),np.cos(x)
plt.plot(x,y1,x,y2)
# 设置标签
plt.xlabel("this is x 轴",size=20)
plt.ylabel("this is y 轴",size=20)
plt.show()

2. Set the scale range

Use the xlim, ylim functions to set the range of the x-axis and y-axis

xlim(left=None,right=None,emit=True,auto=False,xmin=None,xmax=None)
ylim(left=None,right=None,emit=True,auto=False,ymin=None,ymax=None)

• Use xmin(ymin) and xmax(ymax) to set

# 标签
import numpy as np
import matplotlib.pyplot as plt
# 支持中文
plt.rcParams['font.sans-serif'] = ['SimHei']  # 用来正常显示中文标签
plt.rcParams['axes.unicode_minus'] = False  # 用来正常显示负号
x=np.linspace(-np.pi,np.pi,256,endpoint=True)
y1,y2=np.sin(x),np.cos(x)
plt.plot(x,y1,x,y2)
# 设置标签
plt.xlabel("this is x 轴",size=20)
plt.ylabel("this is y 轴",size=20)
# 刻度标签
plt.xlim(-4,4)
plt.ylim(-1,1)
plt.show()

3. Add title and legend

title

title(label,fontdict=None,loc="center",pad=None)

Mainly here this loc

• loc: Indicates the alignment style of the title, including left, right, center
• pad: Indicates the distance between the title and the top of the chart, the default is None

legend

legend(handles,labels,loc)

• loc: The position of the legend can be selected here as upper right, upper left, lowerleft, lowright ... It is recommended to choose loc='best'

# 标签
import numpy as np
import matplotlib.pyplot as plt
# 支持中文
plt.rcParams['font.sans-serif'] = ['SimHei']  # 用来正常显示中文标签
plt.rcParams['axes.unicode_minus'] = False  # 用来正常显示负号
x=np.linspace(-np.pi,np.pi,256,endpoint=True)
y1,y2=np.sin(x),np.cos(x)
pic=plt.plot(x,y1,x,y2)
# 设置标签
plt.xlabel("this is x 轴",size=20)
plt.ylabel("this is y 轴",size=20)
# 刻度标签
plt.xlim(-4,4)
plt.ylim(-1,1)
# 添加标题
plt.title("正弦曲线和余弦曲线",loc="left")
# 添加图例
plt.legend(pic,["sinx","cosx"],shadow=True,fancybox="blue")
plt.show()

4. Display grid

This is simple, plt.grid()just fine, but there are still some parameters in it

grid(b=True,axis="both",which='major')

• which: display the type of grid, support major, minor, both defaults to major

• axis: Indicates which direction to display the grid, there are three options x, y, and both

• linewidth or lw: the width of the line

  Default :

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

# 支持中文
plt.rcParams['font.sans-serif'] = ['SimHei']  # 用来正常显示中文标签
plt.rcParams['axes.unicode_minus'] = False  # 用来正常显示负号
x = np.linspace(-np.pi, np.pi, 256, endpoint=True)
y1, y2 = np.sin(x), np.cos(x)
pic = plt.plot(x, y1, x, y2)
# 设置标签
plt.xlabel("this is x 轴", size=20)
plt.ylabel("this is y 轴", size=20)
# 添加标题
plt.title("正弦曲线和余弦曲线", loc="left")
# 添加图例
plt.legend(pic, ["sinx", "cosx"], shadow=True, fancybox="blue")
# 网格
plt.grid()
plt.show()

Select the grid to add the y axis, modify lw to 0.3

plt.grid(lw=1, axis="y")

5. Add horizontal guides and reference areas

1. Use axhline to add horizontal guide lines

axhline(y=0,xmin=0,xmax-1,linestyle="-")

• y: Indicates the coordinates of the horizontal reference line

• xmin: Indicates the starting position of the horizontal reference line, the default is 0

• xmax: the end position of the horizontal reference line, the default is 1

• linstyle: Indicates the type of horizontal reference line, the default is solid line

  Other types of linstyle: http://t.csdn.cn/Ufbvt

2. Use axvline to draw vertical guide lines

The syntax of axvline is similar to that of axhline, only need to modify x and y

Example: Adding two reference lines to the image above:

​

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

# 支持中文
plt.rcParams['font.sans-serif'] = ['SimHei']  # 用来正常显示中文标签
plt.rcParams['axes.unicode_minus'] = False  # 用来正常显示负号
x = np.linspace(-np.pi, np.pi, 256, endpoint=True)
y1, y2 = np.sin(x), np.cos(x)
pic = plt.plot(x, y1, x, y2)
# 设置标签
plt.xlabel("this is x 轴", size=20)
plt.ylabel("this is y 轴", size=20)
# 添加标题
plt.title("正弦曲线和余弦曲线", loc="left")
# 添加图例
plt.legend(pic, ["sinx", "cosx"], shadow=True, fancybox="blue")
# 网格
plt.grid(lw=1, axis="y")
# 参考线
plt.axvline(x=0.5, linestyle=":", color="m")
plt.axhline(y=0.5, linestyle="--", color="y")
plt.show()

3. Use axhspan and axvspan to add reference areas

axhspan(ymin,ymax,xmin,xmax)
axvspan(ymin,ymax,xmin,xmax)

• ymin: Indicates the lower limit of the horizontal span
• ymax represents the upper limit of the horizontal span
• xmin: Indicates the lower limit of the vertical span
• xmax: Indicates the upper limit of the vertical span

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

# 支持中文
plt.rcParams['font.sans-serif'] = ['SimHei']  # 用来正常显示中文标签
plt.rcParams['axes.unicode_minus'] = False  # 用来正常显示负号
x = np.linspace(-np.pi, np.pi, 256, endpoint=True)
y1, y2 = np.sin(x), np.cos(x)
pic = plt.plot(x, y1, x, y2)
# 设置标签
plt.xlabel("this is x 轴", size=20)
plt.ylabel("this is y 轴", size=20)
# 添加标题
plt.title("正弦曲线和余弦曲线")
# 添加图例
plt.legend(pic, ["sinx", "cosx"], shadow=True, fancybox="blue")
# 网格
plt.grid(lw=1, axis="y")
# 参考线
plt.axvline(x=0.5, linestyle=":", color="m")
plt.axhline(y=0.5, linestyle="--", color="y")
# 参考区域
plt.axvspan(xmin=0.5, xmax=1, alpha=0.32)
plt.axhspan(ymin=0.2, ymax=0.5, alpha=0.32)

plt.show()

Six: Add comment text

1. Directional text

anootate(s,xy,xytext,xycoords,arrowprops,bbox)

• s: indicates the text content of the comment
• xy: the coordinate position of the point representing the annotation, accepting tuple (x, y)
• xytext: Indicates the coordinate position of the annotation text
• xycoords: Indicates the coordinate system of xy, which uses the same coordinate system as the polyline by default
• bbox: A dictionary of attributes representing the border of the annotation text
• arrowprops: a dictionary of properties representing knowledge arrows

The arrowprops parameters are as follows:

2. Non-directional text annotation text

text(x,y,s,fontdict=None,bbox)

• x, y: Indicates the position of the annotation text.

• s: Indicates the content of the annotation text.

• fontdict: A dictionary representing the control font.

• bbox: Indicates the border attribute bullet of the annotation text

For example:

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

# 支持中文
plt.rcParams['font.sans-serif'] = ['SimHei']  # 用来正常显示中文标签
plt.rcParams['axes.unicode_minus'] = False  # 用来正常显示负号
x = np.linspace(-np.pi, np.pi, 256, endpoint=True)
y1, y2 = np.sin(x), np.cos(x)
pic = plt.plot(x, y1, x, y2)
# 设置标签
plt.xlabel("x 轴", size=20)
plt.ylabel("y 轴", size=20)
# 添加标题
plt.title("正弦曲线和余弦曲线")
# 添加图例
plt.legend(pic, ["sinx", "cosx"], shadow=True, fancybox="blue")
# 网格
plt.grid()
plt.annotate("最小值", xy=(-np.pi / 2, -1.0), xytext=((-np.pi / 2), -0.5), arrowprops=dict(arrowstyle="->"))
plt.text(3.1, 0.1, "y=sin(x)", bbox=dict(alpha=0.2))
plt.show()

7. Add math formulas

Just use latetx or katex syntax

For example, r"$\sin x$"it will appear as$\sin x$

Modify the title here

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

    # 支持中文
    plt.rcParams['font.sans-serif'] = ['SimHei']  # 用来正常显示中文标签
    plt.rcParams['axes.unicode_minus'] = False  # 用来正常显示负号
    x = np.linspace(-np.pi, np.pi, 256, endpoint=True)
    y1, y2 = np.sin(x), np.cos(x)
    pic = plt.plot(x, y1, x, y2)
    # 设置标签
    plt.xlabel(" x 轴", size=15)
    plt.ylabel(" y 轴", size=15)
    # 添加标题
    plt.title(r'$\frac{\sin x}{2}$')
    # 添加图例
    plt.legend(pic, ["sinx", "cosx"], shadow=True, fancybox="blue")
    # 网格
    plt.grid()
    plt.annotate("最小值", xy=(-np.pi / 2, -1.0), xytext=((-np.pi / 2), -0.5), arrowprops=dict(arrowstyle="->"))
    plt.text(3.1, 0.1, "y=sin(x)", bbox=dict(alpha=0.2))
    plt.show()

Reference link: Matplotlib — Visualization with Python
Reference Book: Python Data Visualization%20 (Dark Horse Programmer)