{"id":1112928,"date":"2025-01-08T17:43:03","date_gmt":"2025-01-08T09:43:03","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1112928.html"},"modified":"2025-01-08T17:43:06","modified_gmt":"2025-01-08T09:43:06","slug":"%e5%a6%82%e4%bd%95%e7%94%a8python%e6%8a%8a%e8%ae%ad%e7%bb%83%e6%95%b0%e6%8d%ae%e5%ae%9e%e6%97%b6%e6%98%be%e7%a4%ba","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1112928.html","title":{"rendered":"\u5982\u4f55\u7528python\u628a\u8bad\u7ec3\u6570\u636e\u5b9e\u65f6\u663e\u793a"},"content":{"rendered":"

\"\u5982\u4f55\u7528python\u628a\u8bad\u7ec3\u6570\u636e\u5b9e\u65f6\u663e\u793a\"<\/p>\n

\u8981\u5b9e\u73b0\u7528Python\u628a\u8bad\u7ec3\u6570\u636e\u5b9e\u65f6\u663e\u793a\uff0c\u53ef\u4ee5\u4f7f\u7528\u53ef\u89c6\u5316\u5de5\u5177\u5982Matplotlib\u3001Seaborn\u3001Plotly\u7b49\uff0c\u5229\u7528\u8fd9\u4e9b\u5de5\u5177\u63d0\u4f9b\u7684\u52a8\u6001\u7ed8\u56fe\u529f\u80fd\uff0c\u5b9e\u65f6\u5c55\u793a\u8bad\u7ec3\u8fc7\u7a0b\u4e2d\u7684\u6570\u636e\u53d8\u5316\u3002<\/strong> \u5728\u672c\u6587\u4e2d\uff0c\u6211\u4eec\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528Matplotlib\u548cPlotly\u6765\u5b9e\u73b0\u8fd9\u4e00\u76ee\u6807\uff0c\u5e76\u6df1\u5165\u63a2\u8ba8\u5982\u4f55\u4f18\u5316\u53ef\u89c6\u5316\u6548\u679c\u548c\u4ee3\u7801\u6027\u80fd\u3002<\/p>\n<\/p>\n

\u4e00\u3001MATPLOTLIB\u5b9e\u73b0\u5b9e\u65f6\u6570\u636e\u5c55\u793a<\/strong><\/p>\n<\/p>\n

Matplotlib\u662fPython\u4e2d\u6700\u5e38\u7528\u7684\u7ed8\u56fe\u5e93\u4e4b\u4e00\uff0c\u652f\u6301\u9759\u6001\u3001\u52a8\u6001\u548c\u4ea4\u4e92\u5f0f\u7ed8\u56fe\u3002\u5229\u7528Matplotlib\uff0c\u6211\u4eec\u53ef\u4ee5\u5b9e\u73b0\u5b9e\u65f6\u6570\u636e\u5c55\u793a\u3002<\/p>\n<\/p>\n

1. \u5b89\u88c5Matplotlib<\/h3>\n<\/p>\n

\u9996\u5148\uff0c\u786e\u4fdd\u4f60\u5df2\u7ecf\u5b89\u88c5\u4e86Matplotlib\u5e93\u3002\u5982\u679c\u6ca1\u6709\u5b89\u88c5\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n

pip install matplotlib<\/p>\n
<\/code><\/pre>\n<\/p>\n
2. \u5b9e\u73b0\u5b9e\u65f6\u6570\u636e\u5c55\u793a<\/h3>\n<\/p>\n
\u4e0b\u9762\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u793a\u4f8b\uff0c\u5c55\u793a\u5982\u4f55\u4f7f\u7528Matplotlib\u5b9e\u73b0\u5b9e\u65f6\u6570\u636e\u5c55\u793a\uff1a<\/p>\n<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
import numpy as np<\/p>\n
import time<\/p>\n
\u521b\u5efa\u4e00\u4e2a\u7ed8\u56fe\u7a97\u53e3<\/strong><\/h2>\n
plt.ion()  # \u5f00\u542f\u4ea4\u4e92\u6a21\u5f0f<\/p>\n
fig, ax = plt.subplots()<\/p>\n
x_data = []<\/p>\n
y_data = []<\/p>\n
line, = ax.plot(x_data, y_data)<\/p>\n
\u6a21\u62df\u6570\u636e\u751f\u6210\u8fc7\u7a0b<\/strong><\/h2>\n
for i in range(100):<\/p>\n
    x_data.append(i)<\/p>\n
    y_data.append(np.sin(i * 0.1))<\/p>\n
    line.set_xdata(x_data)<\/p>\n
    line.set_ydata(y_data)<\/p>\n
    ax.relim()<\/p>\n
    ax.autoscale_view()<\/p>\n
    fig.canvas.draw()<\/p>\n
    fig.canvas.flush_events()<\/p>\n
    time.sleep(0.1)  # \u6a21\u62df\u6570\u636e\u751f\u6210\u7684\u65f6\u95f4\u95f4\u9694<\/p>\n
plt.ioff()  # \u5173\u95ed\u4ea4\u4e92\u6a21\u5f0f<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u4e0a\u8ff0\u4ee3\u7801\u4e2d\uff0c\u901a\u8fc7plt.ion()<\/code>\u5f00\u542f\u4ea4\u4e92\u6a21\u5f0f\uff0c\u4f7f\u5f97\u7ed8\u56fe\u7a97\u53e3\u80fd\u591f\u5b9e\u65f6\u66f4\u65b0\u3002\u7136\u540e\uff0c\u901a\u8fc7\u5faa\u73af\u4e0d\u65ad\u751f\u6210\u6570\u636e\uff0c\u5e76\u66f4\u65b0\u7ed8\u56fe\u5185\u5bb9\u3002\u6700\u540e\uff0c\u901a\u8fc7plt.ioff()<\/code>\u5173\u95ed\u4ea4\u4e92\u6a21\u5f0f\uff0c\u5e76\u663e\u793a\u6700\u7ec8\u7684\u7ed8\u56fe\u7ed3\u679c\u3002<\/p>\n<\/p>\n
3. \u4f18\u5316\u5b9e\u65f6\u663e\u793a\u6027\u80fd<\/h3>\n<\/p>\n
\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\uff0c\u5982\u679c\u6570\u636e\u91cf\u8f83\u5927\uff0c\u7ed8\u56fe\u6027\u80fd\u53ef\u80fd\u4f1a\u6210\u4e3a\u74f6\u9888\u3002\u4e3a\u4e86\u4f18\u5316\u6027\u80fd\uff0c\u53ef\u4ee5\u8003\u8651\u4ee5\u4e0b\u51e0\u70b9\uff1a<\/p>\n<\/p>\n