The environment uses the environment created in the previous article. → Building Anaconda python environment on Windows 10 Please refer to the previous article for how to use numpy. → #Python basics (#Numpy 1/2) → #Python basics (#Numpy 2/2)

1. Matplotlib import

Graph drawing: Use pyplot module Draw on jupyter lab: % matplotlib inline

%matplotlib inline

import numpy as np
import matplotlib.pyplot as plt

import numpy as np

x = np.linspace(-5, 5, num=10)  # -Divide from 5 to 5 into 10
# x = np.linspace(-5, 5) #The default is 50 splits

print(x)
print(len(x))  #Number of elements of x

`Execution result`


[-5.         -3.88888889 -2.77777778 -1.66666667 -0.55555556  0.55555556
  1.66666667  2.77777778  3.88888889  5.        ]
10

2. Graph drawing

import numpy as np
import matplotlib.pyplot as plt

x = np.linspace(-5, 5)  # -From 5 to 5
y = 2 * x  #Multiply x by 2 to get the y coordinate

plt.plot(x, y)
plt.show()

3. Title, legend, line style

import numpy as np
import matplotlib.pyplot as plt

x = np.linspace(-100, 100, num=1000)
y_1 = x * x.T # x.T :1 row 1000 columns → Transposed to 1000 rows 1 column
y_2 = 10 * x

#Axis label
plt.xlabel("x val")
plt.ylabel("y val")

#Graph title
plt.title("Graph Name")

#Specify plot legend and line style
plt.plot(x, y_1, label="y1")
plt.plot(x, y_2, label="y2", linestyle="dashed")
plt.legend() #Show legend

plt.show()

4. Scatter plot

import numpy as np
import matplotlib.pyplot as plt

x = np.array([1.2, 2.4, 0.0, 1.4, 1.5])
y = np.array([2.4, 1.4, 1.0, 0.1, 1.7])

plt.scatter(x, y)  #Scatter plot plot
plt.show()

5. Image display

import numpy as np
import matplotlib.pyplot as plt

img = np.linspace(0, 100,num=100)  #Divide 0 to 100 into 100 equal parts
print(img)
img = img.reshape(10,10) # 10 *10 Transformed into a matrix
plt.imshow(img, "gray")  #Display in grayscale
plt.colorbar()   #Color bar display
plt.show()

#Python basics (#matplotlib)