Python使用Matplotlib绘制散点趋势线的代码详解

import matplotlib.pyplot as plt
import numpy as np

x = np.random.rand(50)
y = np.random.rand(50)

plt.scatter(x, y)
plt.title("Basic Scatter Plot")
plt.xlabel("X-axis")
plt.ylabel("Y-axis")
plt.show()

# Calculate the best-fit line
z = np.polyfit(x, y, 1)
p = np.poly1d(z)

# Plot the scatter plot and the trend line
plt.scatter(x, y)
plt.plot(x, p(x), "r--")  # 'r--' is for a red dashed line
plt.title("Scatter Plot with Linear Trend Line")
plt.xlabel("X-axis")
plt.ylabel("Y-axis")
plt.show()

# Calculate the polynomial trend line (degree 2)
z = np.polyfit(x, y, 2)
p = np.poly1d(z)

# Plot the scatter plot and the polynomial trend line
plt.scatter(x, y)
plt.plot(x, p(x), "g-")  # 'g-' is for a green solid line
plt.title("Scatter Plot with Polynomial Trend Line")
plt.xlabel("X-axis")
plt.ylabel("Y-axis")
plt.show()

# Calculate the best-fit line
z = np.polyfit(x, y, 1)
p = np.poly1d(z)

# Plot the scatter plot and the customized trend line
plt.scatter(x, y)
plt.plot(x, p(x), color="purple", linewidth=2, linestyle="--")
plt.title("Scatter Plot with Customized Trend Line")
plt.xlabel("X-axis")
plt.ylabel("Y-axis")
plt.show()

# Generate random data
x = np.random.rand(50)
y = np.random.rand(50)

# Calculate the linear and polynomial trend lines
z1 = np.polyfit(x, y, 1)
p1 = np.poly1d(z1)
z2 = np.polyfit(x, y, 2)
p2 = np.poly1d(z2)

# Plot the scatter plot and both trend lines
plt.scatter(x, y)
plt.plot(x, p1(x), "r--", label="Linear Trend Line")
plt.plot(x, p2(x), "g-", label="Polynomial Trend Line")
plt.title("Scatter Plot with Multiple Trend Lines")
plt.xlabel("X-axis")
plt.ylabel("Y-axis")
plt.legend()
plt.show()