{"id":1016918,"date":"2024-12-27T12:20:40","date_gmt":"2024-12-27T04:20:40","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1016918.html"},"modified":"2024-12-27T12:20:42","modified_gmt":"2024-12-27T04:20:42","slug":"python-plot%e5%a6%82%e4%bd%95%e7%94%bb%e5%87%bd%e6%95%b0","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1016918.html","title":{"rendered":"python plot\u5982\u4f55\u753b\u51fd\u6570"},"content":{"rendered":"

\"python<\/p>\n

\u5728Python\u4e2d\u7ed8\u5236\u51fd\u6570\u56fe\u50cf\u53ef\u4ee5\u901a\u8fc7\u4f7f\u7528matplotlib\u5e93\u3001numpy\u5e93\u3001seaborn\u5e93\uff0c\u8fd9\u4e9b\u5de5\u5177\u63d0\u4f9b\u5f3a\u5927\u7684\u53ef\u89c6\u5316\u529f\u80fd\u3001\u53ef\u4ee5\u7ed8\u5236\u5404\u79cd\u7c7b\u578b\u7684\u56fe\u50cf\u3001\u8f7b\u677e\u81ea\u5b9a\u4e49\u56fe\u5f62\u5916\u89c2\u3002\u4e0b\u9762\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528\u8fd9\u4e9b\u5e93\u7ed8\u5236\u51fd\u6570\u56fe\u50cf\u3002<\/strong><\/p>\n<\/p>\n

\u7ed8\u5236\u51fd\u6570\u56fe\u50cf\u662f\u6570\u636e\u5206\u6790\u548c\u79d1\u5b66\u8ba1\u7b97\u4e2d\u7684\u57fa\u672c\u4efb\u52a1\u4e4b\u4e00\u3002\u5728Python\u4e2d\uff0cmatplotlib\u662f\u6700\u5e38\u7528\u7684\u7ed8\u56fe\u5e93\u4e4b\u4e00\uff0c\u7ed3\u5408numpy\u5e93\u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u8f7b\u677e\u7ed8\u5236\u6570\u5b66\u51fd\u6570\u3002\u9996\u5148\uff0c\u6211\u4eec\u9700\u8981\u5b89\u88c5\u8fd9\u4e24\u4e2a\u5e93\u3002\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u547d\u4ee4\u5b89\u88c5\uff1a<\/p>\n<\/p>\n

pip install matplotlib numpy<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e00\u3001\u4f7f\u7528MATPLOTLIB\u7ed8\u5236\u51fd\u6570<\/h3>\n<\/p>\n
Matplotlib<\/strong>\u662fPython\u4e2d\u6700\u5e38\u7528\u7684\u7ed8\u56fe\u5e93\u4e4b\u4e00\uff0c\u5b83\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u7ed8\u56fe\u529f\u80fd\u548c\u7075\u6d3b\u7684\u63a5\u53e3\u3002\u8981\u7ed8\u5236\u51fd\u6570\u56fe\u50cf\uff0c\u9996\u5148\u9700\u8981\u5bfc\u5165\u5fc5\u8981\u7684\u5e93\uff1a<\/p>\n<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
import numpy as np<\/p>\n
<\/code><\/pre>\n<\/p>\n
1. \u57fa\u672c\u7ed8\u56fe\u6b65\u9aa4<\/h4>\n<\/p>\n
\u9996\u5148\uff0c\u5b9a\u4e49\u4e00\u4e2a\u51fd\u6570\uff0c\u4f8b\u5982\u4e00\u4e2a\u7b80\u5355\u7684\u4e8c\u6b21\u51fd\u6570\uff1a<\/p>\n<\/p>\n
def f(x):<\/p>\n
    return x2<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u7136\u540e\uff0c\u521b\u5efax\u8f74\u4e0a\u7684\u6570\u636e\u70b9\uff0c\u5e76\u8ba1\u7b97\u76f8\u5e94\u7684y\u503c\uff1a<\/p>\n<\/p>\n
x = np.linspace(-10, 10, 400)<\/p>\n
y = f(x)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u6700\u540e\uff0c\u4f7f\u7528matplotlib\u7ed8\u5236\u56fe\u50cf\uff1a<\/p>\n<\/p>\n
plt.plot(x, y, label='y = x^2')<\/p>\n
plt.xlabel('x')<\/p>\n
plt.ylabel('y')<\/p>\n
plt.title('Plot of y = x^2')<\/p>\n
plt.legend()<\/p>\n
plt.grid(True)<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4ee5\u4e0a\u4ee3\u7801\u5c06\u7ed8\u5236\u51fay=x^2\u7684\u56fe\u50cf\uff0c\u5e76\u4e3a\u56fe\u50cf\u6dfb\u52a0\u6807\u7b7e\u3001\u6807\u9898\u548c\u7f51\u683c\u3002<\/p>\n<\/p>\n
2. \u7ed8\u5236\u591a\u4e2a\u51fd\u6570<\/h4>\n<\/p>\n
\u6709\u65f6\u6211\u4eec\u9700\u8981\u5728\u540c\u4e00\u4e2a\u5750\u6807\u7cfb\u4e2d\u7ed8\u5236\u591a\u4e2a\u51fd\u6570\u3002\u4f8b\u5982\uff0c\u7ed8\u5236y=x^2\u548cy=x^3\uff1a<\/p>\n<\/p>\n
def g(x):<\/p>\n
    return x3<\/p>\n
y1 = f(x)<\/p>\n
y2 = g(x)<\/p>\n
plt.plot(x, y1, label='y = x^2')<\/p>\n
plt.plot(x, y2, label='y = x^3')<\/p>\n
plt.xlabel('x')<\/p>\n
plt.ylabel('y')<\/p>\n
plt.title('Plot of y = x^2 and y = x^3')<\/p>\n
plt.legend()<\/p>\n
plt.grid(True)<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4f7f\u7528\u4e0d\u540c\u989c\u8272\u548c\u7ebf\u578b\u53ef\u4ee5\u5e2e\u52a9\u533a\u5206\u4e0d\u540c\u7684\u66f2\u7ebf\u3002<\/p>\n<\/p>\n
\u4e8c\u3001\u4f7f\u7528NUMPY\u751f\u6210\u6570\u636e<\/h3>\n<\/p>\n
Numpy<\/strong>\u662f\u4e00\u4e2a\u5f3a\u5927\u7684\u6570\u503c\u8ba1\u7b97\u5e93\uff0c\u5b83\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u6570\u5b66\u51fd\u6570\u548c\u65b9\u4fbf\u7684\u6570\u7ec4\u64cd\u4f5c\u3002\u901a\u8fc7numpy\uff0c\u6211\u4eec\u53ef\u4ee5\u8f7b\u677e\u751f\u6210\u51fd\u6570\u7684\u8f93\u5165\u6570\u636e\u3002<\/p>\n<\/p>\n
1. \u751f\u6210\u7b49\u95f4\u8ddd\u6570\u636e<\/h4>\n<\/p>\n
\u4f7f\u7528numpy\u7684linspace\u51fd\u6570\u751f\u6210\u7b49\u95f4\u8ddd\u7684\u6570\u636e\u70b9\uff1a<\/p>\n<\/p>\n
x = np.linspace(-10, 10, 400)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8fd9\u6bb5\u4ee3\u7801\u751f\u6210\u4e86\u4ece-10\u523010\u4e4b\u95f4\u7684400\u4e2a\u7b49\u95f4\u8ddd\u7684\u6570\u636e\u70b9\u3002<\/p>\n<\/p>\n
2. \u4f7f\u7528numpy\u51fd\u6570\u8ba1\u7b97y\u503c<\/h4>\n<\/p>\n
Numpy\u63d0\u4f9b\u4e86\u8bb8\u591a\u6570\u5b66\u51fd\u6570\uff0c\u4f8b\u5982sin\u3001cos\u3001exp\u7b49\uff0c\u53ef\u4ee5\u76f4\u63a5\u4f5c\u7528\u4e8e\u6570\u7ec4\uff1a<\/p>\n<\/p>\n
y = np.sin(x)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u7136\u540e\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528matplotlib\u7ed8\u5236\u8fd9\u4e9b\u6570\u636e\uff1a<\/p>\n<\/p>\n
plt.plot(x, y, label='y = sin(x)')<\/p>\n
plt.xlabel('x')<\/p>\n
plt.ylabel('y')<\/p>\n
plt.title('Plot of y = sin(x)')<\/p>\n
plt.legend()<\/p>\n
plt.grid(True)<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e09\u3001\u4f7f\u7528SEABORN\u8fdb\u884c\u9ad8\u7ea7\u53ef\u89c6\u5316<\/h3>\n<\/p>\n
Seaborn<\/strong>\u662f\u57fa\u4e8ematplotlib\u7684\u9ad8\u7ea7\u53ef\u89c6\u5316\u5e93\uff0c\u63d0\u4f9b\u4e86\u66f4\u4e3a\u7f8e\u89c2\u548c\u590d\u6742\u7684\u56fe\u5f62\u6837\u5f0f\u3002\u867d\u7136seaborn\u4e3b\u8981\u7528\u4e8e\u7edf\u8ba1\u6570\u636e\u7684\u53ef\u89c6\u5316\uff0c\u4f46\u5b83\u4e5f\u53ef\u4ee5\u7528\u4e8e\u51fd\u6570\u56fe\u50cf\u7684\u7ed8\u5236\u3002<\/p>\n<\/p>\n
1. \u5b89\u88c5\u548c\u5bfc\u5165Seaborn<\/h4>\n<\/p>\n
\u9996\u5148\uff0c\u786e\u4fdd\u5b89\u88c5\u4e86seaborn\u5e93\uff1a<\/p>\n<\/p>\n
pip install seaborn<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u7136\u540e\uff0c\u5bfc\u5165seaborn\u5e76\u4f7f\u7528\u5b83\u6765\u7ed8\u5236\u51fd\u6570\uff1a<\/p>\n<\/p>\n
import seaborn as sns<\/p>\n
sns.set(style="darkgrid")<\/p>\n
x = np.linspace(-10, 10, 400)<\/p>\n
y = np.sin(x)<\/p>\n
plt.figure(figsize=(10, 6))<\/p>\n
sns.lineplot(x, y, label='y = sin(x)')<\/p>\n
plt.xlabel('x')<\/p>\n
plt.ylabel('y')<\/p>\n
plt.title('Seaborn Plot of y = sin(x)')<\/p>\n
plt.legend()<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56db\u3001\u5b9a\u5236\u56fe\u50cf\u5916\u89c2<\/h3>\n<\/p>\n
1. \u66f4\u6539\u7ebf\u578b\u548c\u989c\u8272<\/h4>\n<\/p>\n
\u53ef\u4ee5\u901a\u8fc7\u5728plot\u51fd\u6570\u4e2d\u6307\u5b9a\u53c2\u6570\u6765\u66f4\u6539\u7ebf\u578b\u548c\u989c\u8272\uff1a<\/p>\n<\/p>\n
plt.plot(x, y, 'r--', label='y = sin(x)')  # \u7ea2\u8272\u865a\u7ebf<\/p>\n
<\/code><\/pre>\n<\/p>\n
2. \u6dfb\u52a0\u7f51\u683c\u548c\u56fe\u4f8b<\/h4>\n<\/p>\n
\u901a\u8fc7grid<\/code>\u548clegend<\/code>\u51fd\u6570\u53ef\u4ee5\u6dfb\u52a0\u7f51\u683c\u548c\u56fe\u4f8b\uff0c\u4f7f\u56fe\u50cf\u66f4\u5177\u53ef\u8bfb\u6027\uff1a<\/p>\n<\/p>\n
plt.grid(True)<\/p>\n
plt.legend()<\/p>\n
<\/code><\/pre>\n<\/p>\n
3. \u8c03\u6574\u56fe\u50cf\u5c3a\u5bf8<\/h4>\n<\/p>\n
\u901a\u8fc7figure<\/code>\u51fd\u6570\u8bbe\u7f6e\u56fe\u50cf\u7684\u5927\u5c0f\uff1a<\/p>\n<\/p>\n
plt.figure(figsize=(10, 6))<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e94\u3001\u4fdd\u5b58\u56fe\u50cf<\/h3>\n<\/p>\n
\u6709\u65f6\u6211\u4eec\u9700\u8981\u5c06\u7ed8\u5236\u7684\u56fe\u50cf\u4fdd\u5b58\u4e3a\u6587\u4ef6\uff0c\u53ef\u4ee5\u4f7f\u7528savefig<\/code>\u51fd\u6570\uff1a<\/p>\n<\/p>\n
plt.savefig('plot.png')<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u516d\u3001\u603b\u7ed3<\/h3>\n<\/p>\n
\u5728Python\u4e2d\uff0c\u4f7f\u7528matplotlib\u548cnumpy\u5e93\u53ef\u4ee5\u8f7b\u677e\u5b9e\u73b0\u51fd\u6570\u7684\u7ed8\u5236\u3002\u901a\u8fc7\u8fd9\u4e9b\u5de5\u5177\uff0c\u60a8\u53ef\u4ee5\u5feb\u901f\u751f\u6210\u5404\u79cd\u7c7b\u578b\u7684\u56fe\u50cf\uff0c\u5e76\u81ea\u5b9a\u4e49\u56fe\u5f62\u7684\u5916\u89c2\u4ee5\u6ee1\u8db3\u7279\u5b9a\u9700\u6c42\u3002\u6b64\u5916\uff0cseaborn\u5e93\u8fd8\u53ef\u4ee5\u63d0\u4f9b\u66f4\u4e3a\u7f8e\u89c2\u7684\u56fe\u50cf\u6837\u5f0f\u3002\u638c\u63e1\u8fd9\u4e9b\u5de5\u5177\uff0c\u60a8\u5c06\u80fd\u591f\u5728\u6570\u636e\u5206\u6790\u548c\u79d1\u5b66\u8ba1\u7b97\u4e2d\u8fdb\u884c\u6709\u6548\u7684\u53ef\u89c6\u5316\u5de5\u4f5c\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
 \u5982\u4f55\u5728Python\u4e2d\u4f7f\u7528Matplotlib\u7ed8\u5236\u6570\u5b66\u51fd\u6570\uff1f<\/strong>
\u5728Python\u4e2d\uff0c\u4f7f\u7528Matplotlib\u5e93\u7ed8\u5236\u6570\u5b66\u51fd\u6570\u975e\u5e38\u7b80\u5355\u3002\u9996\u5148\uff0c\u786e\u4fdd\u5df2\u5b89\u88c5Matplotlib\u548cNumPy\u5e93\u3002\u4f60\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\u5bfc\u5165\u6240\u9700\u7684\u5e93\u5e76\u7ed8\u5236\u4e00\u4e2a\u7b80\u5355\u7684\u51fd\u6570\uff0c\u4f8b\u5982y = x^2\uff1a<\/p>\n
import numpy as np\nimport matplotlib.pyplot as plt\n\nx = np.linspace(-10, 10, 400)  # \u521b\u5efa\u4ece-10\u523010\u7684400\u4e2a\u70b9\ny = x**2  # \u5b9a\u4e49\u51fd\u6570\n\nplt.plot(x, y)  # \u7ed8\u5236\u51fd\u6570\nplt.title('y = x^2')  # \u6dfb\u52a0\u6807\u9898\nplt.xlabel('x')  # \u6dfb\u52a0x\u8f74\u6807\u7b7e\nplt.ylabel('y')  # \u6dfb\u52a0y\u8f74\u6807\u7b7e\nplt.grid()  # \u6dfb\u52a0\u7f51\u683c\nplt.show()  # \u663e\u793a\u56fe\u5f62\n<\/code><\/pre>\n
\u53ef\u4ee5\u4f7f\u7528\u54ea\u4e9b\u51fd\u6570\u6765\u7ed8\u5236\u4e0d\u540c\u7c7b\u578b\u7684\u56fe\u5f62\uff1f<\/strong>
\u9664\u4e86\u7b80\u5355\u7684\u7ebf\u6027\u548c\u591a\u9879\u5f0f\u51fd\u6570\u5916\uff0cMatplotlib\u652f\u6301\u591a\u79cd\u7c7b\u578b\u7684\u56fe\u5f62\uff0c\u4f8b\u5982\u4e09\u89d2\u51fd\u6570\u3001\u6307\u6570\u51fd\u6570\u548c\u5bf9\u6570\u51fd\u6570\u3002\u4f60\u53ef\u4ee5\u4f7f\u7528NumPy\u5e93\u4e2d\u7684\u5404\u79cd\u51fd\u6570\uff08\u5982np.sin(), np.exp(), np.log()\u7b49\uff09\u6765\u5b9a\u4e49\u4e0d\u540c\u7684y\u503c\uff0c\u5e76\u5229\u7528\u76f8\u540c\u7684plot\u51fd\u6570\u7ed8\u5236\u3002\u793a\u4f8b\u4ee3\u7801\u5982\u4e0b\uff1a<\/p>\n
x = np.linspace(0, 2 * np.pi, 100)  # \u4ece0\u52302\u03c0\u751f\u6210100\u4e2a\u70b9\ny = np.sin(x)  # \u8ba1\u7b97y\u503c\u4e3asin(x)\n\nplt.plot(x, y)  # \u7ed8\u5236sin\u51fd\u6570\nplt.title('y = sin(x)')  # \u6dfb\u52a0\u6807\u9898\nplt.xlabel('x')  # \u6dfb\u52a0x\u8f74\u6807\u7b7e\nplt.ylabel('y')  # \u6dfb\u52a0y\u8f74\u6807\u7b7e\nplt.grid()  # \u6dfb\u52a0\u7f51\u683c\nplt.show()  # \u663e\u793a\u56fe\u5f62\n<\/code><\/pre>\n
\u5982\u4f55\u81ea\u5b9a\u4e49\u56fe\u5f62\u7684\u5916\u89c2\uff0c\u4f8b\u5982\u989c\u8272\u548c\u7ebf\u578b\uff1f<\/strong>
Matplotlib\u5141\u8bb8\u7528\u6237\u81ea\u5b9a\u4e49\u56fe\u5f62\u7684\u5916\u89c2\uff0c\u5305\u62ec\u989c\u8272\u3001\u7ebf\u578b\u548c\u6807\u8bb0\u3002\u53ef\u4ee5\u5728plot\u51fd\u6570\u4e2d\u4f20\u9012\u989d\u5916\u7684\u53c2\u6570\u6765\u5b9e\u73b0\u8fd9\u4e00\u70b9\u3002\u4f8b\u5982\uff0c\u4f60\u53ef\u4ee5\u4f7f\u7528'ro-'\u6765\u6307\u5b9a\u7ea2\u8272\u5706\u70b9\u7684\u7ebf\u578b\uff0c\u6216'–'\u6765\u7ed8\u5236\u865a\u7ebf\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u793a\u4f8b\uff1a<\/p>\n
plt.plot(x, y, 'ro-', label='y = sin(x)')  # \u7ea2\u8272\u5706\u70b9\uff0c\u5e26\u5b9e\u7ebf\nplt.legend()  # \u663e\u793a\u56fe\u4f8b\n<\/code><\/pre>\n
\u901a\u8fc7\u8fd9\u4e9b\u53c2\u6570\uff0c\u4f60\u53ef\u4ee5\u521b\u5efa\u66f4\u5177\u89c6\u89c9\u5438\u5f15\u529b\u548c\u4fe1\u606f\u6027\u7684\u56fe\u5f62\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u5728Python\u4e2d\u7ed8\u5236\u51fd\u6570\u56fe\u50cf\u53ef\u4ee5\u901a\u8fc7\u4f7f\u7528matplotlib\u5e93\u3001numpy\u5e93\u3001seaborn\u5e93\uff0c\u8fd9\u4e9b\u5de5\u5177\u63d0\u4f9b\u5f3a […]","protected":false},"author":3,"featured_media":1016927,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[37],"tags":[],"acf":[],"_links":{"self":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1016918"}],"collection":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/comments?post=1016918"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1016918\/revisions"}],"predecessor-version":[{"id":1016931,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1016918\/revisions\/1016931"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1016927"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1016918"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1016918"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1016918"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}