通过源码解析实现可视化数据分析

import matplotlib.pyplot as plt

# 示例数据

data = [25, 30, 35, 40, 45]

labels = ['A', 'B', 'C', 'D', 'E']

# 绘制柱状图

plt.bar(labels, data)

plt.title('Simple Bar Chart')

plt.xlabel('Categories')

plt.ylabel('Values')

plt.show()

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# 假设我们已经克隆了Matplotlib的源码仓库

from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas

from matplotlib.figure import Figure

# 创建一个Figure对象

fig = Figure()

# 获取画布

canvas = FigureCanvas(fig)

# 添加子图

ax = fig.add_subplot(111)

# 绘制数据

ax.bar(labels, data)

# 渲染图像

canvas.draw()

# 获取图像数据

image = np.frombuffer(canvas.buffer_rgba(), dtype=np.uint8)

image = image.reshape(canvas.get_width_height()[::-1] + (4,))

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import tkinter as tk

from PIL import Image, ImageDraw

# 创建窗口

root = tk.Tk()

canvas = tk.Canvas(root, width=400, height=400)

canvas.pack()

# 在画布上绘制矩形

draw = ImageDraw.Draw(canvas)

draw.rectangle([(50, 50), (350, 350)], outline="red", width=2)

# 运行主循环

root.mainloop()

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