Python 高级绘图：探索数据可视化

import matplotlib.pyplot as plt
import numpy as np

# 生成示例数据
x = np.linspace(0, 2 * np.pi, 100)
y = np.sin(x)

# 绘制折线图
plt.plot(x, y, label='Sin Curve')
plt.xlabel('X')
plt.ylabel('Y')
plt.title('Sine Wave')
plt.legend()
plt.show()

import seaborn as sns
import pandas as pd

# 生成示例数据
data = {'X': np.random.randn(100), 'Y': np.random.randn(100)}
df = pd.DataFrame(data)

# 绘制散点图
sns.scatterplot(data=df, x='X', y='Y')
plt.title('Scatter Plot')
plt.show()

from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import numpy as np

# 生成示例数据
x = np.linspace(-2, 2, 100)
y = np.linspace(-2, 2, 100)
X, Y = np.meshgrid(x, y)
Z = np.sin(np.sqrt(X ** 2 + Y ** 2))

# 绘制 3D 曲面图
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
ax.plot_surface(X, Y, Z)
plt.title('3D Surface Plot')
plt.show()

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

# 初始化图形
plt.ion()  # 开启交互模式
fig, ax = plt.subplots()

# 模拟数据更新
for i in range(100):
    x = np.linspace(0, 2 * np.pi, 100)
    y = np.sin(x + i * 0.1)
    ax.clear()  # 清除之前的图形
    ax.plot(x, y)
    plt.draw()  # 重新绘制图形
    plt.pause(0.1)  # 暂停一段时间