{"id":1122437,"date":"2025-01-08T19:20:37","date_gmt":"2025-01-08T11:20:37","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1122437.html"},"modified":"2025-01-08T19:20:41","modified_gmt":"2025-01-08T11:20:41","slug":"python%e5%a6%82%e4%bd%95%e6%8c%87%e5%ae%9a%e5%9d%90%e6%a0%87%e8%bd%b4%e5%8f%aa%e6%98%be%e7%a4%ba%e9%83%a8%e5%88%86","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1122437.html","title":{"rendered":"python\u5982\u4f55\u6307\u5b9a\u5750\u6807\u8f74\u53ea\u663e\u793a\u90e8\u5206"},"content":{"rendered":"

\"python\u5982\u4f55\u6307\u5b9a\u5750\u6807\u8f74\u53ea\u663e\u793a\u90e8\u5206\"<\/p>\n

Python\u5982\u4f55\u6307\u5b9a\u5750\u6807\u8f74\u53ea\u663e\u793a\u90e8\u5206\uff1a\u4f7f\u7528Matplotlib\u7684set_xlim<\/code>\u548cset_ylim<\/code>\u65b9\u6cd5\u3001\u8bbe\u7f6e\u523b\u5ea6\u8303\u56f4\u3001\u9690\u85cf\u4e0d\u9700\u8981\u7684\u523b\u5ea6\u6807\u7b7e<\/strong>\u3002\u5176\u4e2d\uff0c\u4f7f\u7528Matplotlib\u7684set_xlim<\/code>\u548cset_ylim<\/code>\u65b9\u6cd5\u662f\u6700\u5e38\u89c1\u7684\u65b9\u5f0f\uff0c\u80fd\u591f\u8f7b\u677e\u5730\u8bbe\u5b9aX\u8f74\u548cY\u8f74\u663e\u793a\u7684\u8303\u56f4\u3002<\/p>\n<\/p>\n

\u4f7f\u7528Matplotlib\u7684set_xlim<\/code>\u548cset_ylim<\/code>\u65b9\u6cd5<\/strong>\u53ef\u4ee5\u8ba9\u4f60\u81ea\u7531\u5730\u8bbe\u5b9a\u5750\u6807\u8f74\u7684\u663e\u793a\u8303\u56f4\u3002\u4f8b\u5982\uff0c\u5982\u679c\u4f60\u53ea\u60f3\u663e\u793aX\u8f74\u4ece0\u523010\u7684\u90e8\u5206\uff0c\u53ef\u4ee5\u4f7f\u7528plt.xlim(0, 10)<\/code>\u6765\u5b9e\u73b0\u3002\u540c\u6837\u5730\uff0c\u4f60\u53ef\u4ee5\u4f7f\u7528plt.ylim<\/code>\u6765\u8bbe\u5b9aY\u8f74\u7684\u8303\u56f4\u3002\u8fd9\u79cd\u65b9\u6cd5\u975e\u5e38\u76f4\u89c2\u4e14\u6613\u4e8e\u5b9e\u73b0\u3002\u9664\u6b64\u4e4b\u5916\uff0c\u4f60\u8fd8\u53ef\u4ee5\u901a\u8fc7\u8bbe\u7f6e\u523b\u5ea6\u8303\u56f4\u548c\u9690\u85cf\u4e0d\u9700\u8981\u7684\u523b\u5ea6\u6807\u7b7e\u6765\u8fdb\u4e00\u6b65\u4f18\u5316\u5750\u6807\u8f74\u7684\u663e\u793a\u6548\u679c\u3002<\/p>\n<\/p>\n

\u4e00\u3001Matplotlib\u7b80\u4ecb<\/h3>\n<\/p>\n

Matplotlib\u662f\u4e00\u4e2aPython\u76842D\u7ed8\u56fe\u5e93\uff0c\u80fd\u591f\u751f\u6210\u51fa\u7248\u8d28\u91cf\u7684\u56fe\u5f62\uff0c\u4e14\u652f\u6301\u591a\u79cd\u8f93\u51fa\u683c\u5f0f\u3002\u5b83\u901a\u5e38\u4e0eNumPy\u4e00\u8d77\u4f7f\u7528\uff0c\u80fd\u591f\u8f7b\u677e\u7ed8\u5236\u51fa\u5404\u79cd\u590d\u6742\u7684\u56fe\u5f62\u3002Matplotlib\u5728\u6570\u636e\u79d1\u5b66\u3001\u673a\u5668\u5b66\u4e60<\/a>\u3001\u5de5\u7a0b\u7b49\u9886\u57df\u90fd\u6709\u5e7f\u6cdb\u7684\u5e94\u7528\u3002<\/p>\n<\/p>\n

Matplotlib\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u529f\u80fd\u6765\u5b9a\u5236\u56fe\u5f62\uff0c\u5305\u62ec\u4f46\u4e0d\u9650\u4e8e\u8bbe\u7f6e\u5750\u6807\u8f74\u3001\u56fe\u4f8b\u3001\u6807\u9898\u3001\u6807\u7b7e\u7b49\u3002\u5176\u7075\u6d3b\u6027\u548c\u5f3a\u5927\u7684\u529f\u80fd\u4f7f\u5176\u6210\u4e3aPython\u4e2d\u6700\u5e38\u7528\u7684\u7ed8\u56fe\u5e93\u4e4b\u4e00\u3002<\/p>\n<\/p>\n

\u4e8c\u3001\u4f7f\u7528set_xlim<\/code>\u548cset_ylim<\/code><\/h3>\n<\/p>\n

1. \u57fa\u672c\u4f7f\u7528\u65b9\u6cd5<\/h4>\n<\/p>\n

\u8981\u6307\u5b9a\u5750\u6807\u8f74\u53ea\u663e\u793a\u90e8\u5206\uff0c\u53ef\u4ee5\u4f7f\u7528set_xlim<\/code>\u548cset_ylim<\/code>\u65b9\u6cd5\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u793a\u4f8b\uff1a<\/p>\n<\/p>\n

import matplotlib.pyplot as plt<\/p>\n
import numpy as np<\/p>\n
x = np.linspace(-10, 10, 100)<\/p>\n
y = np.sin(x)<\/p>\n
plt.plot(x, y)<\/p>\n
plt.xlim(0, 10)  # \u8bbe\u7f6eX\u8f74\u8303\u56f4<\/p>\n
plt.ylim(-1, 1)  # \u8bbe\u7f6eY\u8f74\u8303\u56f4<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0c\u6211\u4eec\u901a\u8fc7plt.xlim(0, 10)<\/code>\u8bbe\u7f6e\u4e86X\u8f74\u7684\u8303\u56f4\u4e3a0\u523010\uff0c\u800c\u901a\u8fc7plt.ylim(-1, 1)<\/code>\u8bbe\u7f6e\u4e86Y\u8f74\u7684\u8303\u56f4\u4e3a-1\u52301\u3002<\/p>\n<\/p>\n
2. \u9ad8\u7ea7\u7528\u6cd5<\/h4>\n<\/p>\n
\u9664\u4e86\u57fa\u672c\u7684set_xlim<\/code>\u548cset_ylim<\/code>\u65b9\u6cd5\uff0cMatplotlib\u8fd8\u63d0\u4f9b\u4e86\u4e00\u4e9b\u9ad8\u7ea7\u7528\u6cd5\u3002\u4f8b\u5982\uff0c\u4f60\u53ef\u4ee5\u901a\u8fc7\u8bbe\u7f6eauto<\/code>\u53c2\u6570\u81ea\u52a8\u8c03\u6574\u5750\u6807\u8f74\u8303\u56f4\uff1a<\/p>\n<\/p>\n
plt.plot(x, y)<\/p>\n
plt.xlim(auto=True)  # \u81ea\u52a8\u8c03\u6574X\u8f74\u8303\u56f4<\/p>\n
plt.ylim(auto=True)  # \u81ea\u52a8\u8c03\u6574Y\u8f74\u8303\u56f4<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8fd9\u79cd\u65b9\u6cd5\u9002\u7528\u4e8e\u6570\u636e\u8303\u56f4\u672a\u77e5\u7684\u60c5\u51b5\uff0c\u80fd\u591f\u81ea\u52a8\u6839\u636e\u6570\u636e\u8c03\u6574\u5750\u6807\u8f74\u7684\u663e\u793a\u8303\u56f4\u3002<\/p>\n<\/p>\n
\u4e09\u3001\u8bbe\u7f6e\u523b\u5ea6\u8303\u56f4<\/h3>\n<\/p>\n
1. \u4f7f\u7528set_xticks<\/code>\u548cset_yticks<\/code><\/h4>\n<\/p>\n
\u9664\u4e86\u4f7f\u7528set_xlim<\/code>\u548cset_ylim<\/code>\u65b9\u6cd5\uff0c\u4f60\u8fd8\u53ef\u4ee5\u901a\u8fc7\u8bbe\u7f6e\u523b\u5ea6\u8303\u56f4\u6765\u5b9e\u73b0\u90e8\u5206\u663e\u793a\u5750\u6807\u8f74\u3002\u4f8b\u5982\uff0c\u4f7f\u7528set_xticks<\/code>\u548cset_yticks<\/code>\u65b9\u6cd5\u53ef\u4ee5\u81ea\u5b9a\u4e49\u523b\u5ea6\uff1a<\/p>\n<\/p>\n
plt.plot(x, y)<\/p>\n
plt.xticks(np.arange(0, 11, step=1))  # \u8bbe\u7f6eX\u8f74\u523b\u5ea6<\/p>\n
plt.yticks(np.arange(-1, 1.1, step=0.5))  # \u8bbe\u7f6eY\u8f74\u523b\u5ea6<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0c\u6211\u4eec\u901a\u8fc7plt.xticks<\/code>\u65b9\u6cd5\u8bbe\u7f6e\u4e86X\u8f74\u7684\u523b\u5ea6\u8303\u56f4\u4e3a0\u523010\uff0c\u6b65\u957f\u4e3a1\uff1b\u901a\u8fc7plt.yticks<\/code>\u65b9\u6cd5\u8bbe\u7f6e\u4e86Y\u8f74\u7684\u523b\u5ea6\u8303\u56f4\u4e3a-1\u52301\uff0c\u6b65\u957f\u4e3a0.5\u3002<\/p>\n<\/p>\n
2. \u9690\u85cf\u4e0d\u9700\u8981\u7684\u523b\u5ea6\u6807\u7b7e<\/h4>\n<\/p>\n
\u6709\u65f6\u5019\uff0c\u4f60\u53ef\u80fd\u53ea\u60f3\u663e\u793a\u90e8\u5206\u523b\u5ea6\u6807\u7b7e\uff0c\u53ef\u4ee5\u901a\u8fc7\u9690\u85cf\u4e0d\u9700\u8981\u7684\u523b\u5ea6\u6807\u7b7e\u6765\u5b9e\u73b0\uff1a<\/p>\n<\/p>\n
plt.plot(x, y)<\/p>\n
plt.xticks([0, 5, 10])  # \u53ea\u663e\u793a0, 5, 10\u4e09\u4e2a\u523b\u5ea6<\/p>\n
plt.yticks([-1, 0, 1])  # \u53ea\u663e\u793a-1, 0, 1\u4e09\u4e2a\u523b\u5ea6<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8fd9\u79cd\u65b9\u6cd5\u80fd\u591f\u66f4\u52a0\u7cbe\u7ec6\u5730\u63a7\u5236\u5750\u6807\u8f74\u7684\u663e\u793a\u6548\u679c\uff0c\u9002\u7528\u4e8e\u9700\u8981\u7a81\u51fa\u663e\u793a\u7279\u5b9a\u523b\u5ea6\u7684\u60c5\u51b5\u3002<\/p>\n<\/p>\n
\u56db\u3001\u9690\u85cf\u4e0d\u9700\u8981\u7684\u523b\u5ea6\u6807\u7b7e<\/h3>\n<\/p>\n
\u6709\u65f6\u5019\uff0c\u663e\u793a\u6240\u6709\u7684\u523b\u5ea6\u6807\u7b7e\u53ef\u80fd\u4f1a\u4f7f\u56fe\u5f62\u663e\u5f97\u6742\u4e71\u65e0\u7ae0\u3002\u5728\u8fd9\u79cd\u60c5\u51b5\u4e0b\uff0c\u4f60\u53ef\u4ee5\u9009\u62e9\u9690\u85cf\u4e0d\u9700\u8981\u7684\u523b\u5ea6\u6807\u7b7e\u6765\u4f18\u5316\u56fe\u5f62\u7684\u663e\u793a\u6548\u679c\u3002<\/p>\n<\/p>\n
1. \u4f7f\u7528tick_params<\/code>\u65b9\u6cd5<\/h4>\n<\/p>\n
\u4f60\u53ef\u4ee5\u901a\u8fc7tick_params<\/code>\u65b9\u6cd5\u6765\u9690\u85cf\u4e0d\u9700\u8981\u7684\u523b\u5ea6\u6807\u7b7e\uff1a<\/p>\n<\/p>\n
plt.plot(x, y)<\/p>\n
plt.tick_params(axis='x', which='both', bottom=False, top=False, labelbottom=False)  # \u9690\u85cfX\u8f74\u523b\u5ea6<\/p>\n
plt.tick_params(axis='y', which='both', left=False, right=False, labelleft=False)  # \u9690\u85cfY\u8f74\u523b\u5ea6<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0c\u6211\u4eec\u901a\u8fc7plt.tick_params<\/code>\u65b9\u6cd5\u9690\u85cf\u4e86X\u8f74\u548cY\u8f74\u7684\u6240\u6709\u523b\u5ea6\u3002<\/p>\n<\/p>\n
2. \u4f7f\u7528set_visible<\/code>\u65b9\u6cd5<\/h4>\n<\/p>\n
\u4f60\u8fd8\u53ef\u4ee5\u901a\u8fc7set_visible<\/code>\u65b9\u6cd5\u6765\u9690\u85cf\u7279\u5b9a\u7684\u523b\u5ea6\u6807\u7b7e\uff1a<\/p>\n<\/p>\n
plt.plot(x, y)<\/p>\n
ax = plt.gca()<\/p>\n
ax.xaxis.set_visible(False)  # \u9690\u85cfX\u8f74\u523b\u5ea6<\/p>\n
ax.yaxis.set_visible(False)  # \u9690\u85cfY\u8f74\u523b\u5ea6<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8fd9\u79cd\u65b9\u6cd5\u80fd\u591f\u66f4\u52a0\u7075\u6d3b\u5730\u63a7\u5236\u5750\u6807\u8f74\u7684\u663e\u793a\u6548\u679c\uff0c\u9002\u7528\u4e8e\u9700\u8981\u90e8\u5206\u9690\u85cf\u523b\u5ea6\u7684\u60c5\u51b5\u3002<\/p>\n<\/p>\n
\u4e94\u3001\u5b9e\u9645\u6848\u4f8b\u5206\u6790<\/h3>\n<\/p>\n
1. \u6570\u636e\u53ef\u89c6\u5316\u4e2d\u7684\u5e94\u7528<\/h4>\n<\/p>\n
\u5728\u6570\u636e\u53ef\u89c6\u5316\u4e2d\uff0c\u6307\u5b9a\u5750\u6807\u8f74\u53ea\u663e\u793a\u90e8\u5206\u662f\u4e00\u4e2a\u5e38\u89c1\u7684\u9700\u6c42\u3002\u4f8b\u5982\uff0c\u5728\u80a1\u7968\u4ef7\u683c\u8d70\u52bf\u56fe\u4e2d\uff0c\u6211\u4eec\u53ef\u80fd\u53ea\u5173\u5fc3\u6700\u8fd1\u4e00\u6bb5\u65f6\u95f4\u7684\u4ef7\u683c\u53d8\u5316\uff0c\u8fd9\u65f6\u5019\u5c31\u9700\u8981\u901a\u8fc7\u8bbe\u5b9a\u5750\u6807\u8f74\u8303\u56f4\u6765\u5b9e\u73b0\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
\u751f\u6210\u793a\u4f8b\u6570\u636e<\/strong><\/h2>\n
dates = pd.date_range('20230101', periods=100)<\/p>\n
prices = np.random.rand(100) * 100<\/p>\n
plt.plot(dates, prices)<\/p>\n
plt.xlim(dates[50], dates[99])  # \u53ea\u663e\u793a\u6700\u8fd150\u5929\u7684\u6570\u636e<\/p>\n
plt.ylim(0, 100)  # \u8bbe\u7f6eY\u8f74\u8303\u56f4<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0c\u6211\u4eec\u901a\u8fc7plt.xlim<\/code>\u65b9\u6cd5\u53ea\u663e\u793a\u4e86\u6700\u8fd150\u5929\u7684\u80a1\u7968\u4ef7\u683c\u53d8\u5316\u3002<\/p>\n<\/p>\n
2. \u79d1\u5b66\u7814\u7a76\u4e2d\u7684\u5e94\u7528<\/h4>\n<\/p>\n
\u5728\u79d1\u5b66\u7814\u7a76\u4e2d\uff0c\u6307\u5b9a\u5750\u6807\u8f74\u53ea\u663e\u793a\u90e8\u5206\u4e5f\u6709\u5e7f\u6cdb\u7684\u5e94\u7528\u3002\u4f8b\u5982\uff0c\u5728\u751f\u7269\u5b9e\u9a8c\u4e2d\uff0c\u6211\u4eec\u53ef\u80fd\u53ea\u5173\u5fc3\u67d0\u4e2a\u7279\u5b9a\u65f6\u95f4\u6bb5\u5185\u7684\u6570\u636e\u53d8\u5316\uff1a<\/p>\n<\/p>\n
# \u751f\u6210\u793a\u4f8b\u6570\u636e<\/p>\n
time = np.linspace(0, 100, 500)<\/p>\n
response = np.exp(-time \/ 20) * np.sin(time)<\/p>\n
plt.plot(time, response)<\/p>\n
plt.xlim(20, 80)  # \u53ea\u663e\u793a20\u523080\u65f6\u95f4\u6bb5\u7684\u6570\u636e<\/p>\n
plt.ylim(-1, 1)  # \u8bbe\u7f6eY\u8f74\u8303\u56f4<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0c\u6211\u4eec\u901a\u8fc7plt.xlim<\/code>\u65b9\u6cd5\u53ea\u663e\u793a\u4e8620\u523080\u65f6\u95f4\u6bb5\u5185\u7684\u5b9e\u9a8c\u6570\u636e\u53d8\u5316\u3002<\/p>\n<\/p>\n
\u516d\u3001\u603b\u7ed3<\/h3>\n<\/p>\n
\u901a\u8fc7\u672c\u6587\u7684\u4ecb\u7ecd\uff0c\u6211\u4eec\u8be6\u7ec6\u8ba8\u8bba\u4e86\u5728Python\u4e2d\u5982\u4f55\u6307\u5b9a\u5750\u6807\u8f74\u53ea\u663e\u793a\u90e8\u5206\u7684\u65b9\u6cd5\u3002\u4e3b\u8981\u5305\u62ec\u4f7f\u7528Matplotlib\u7684set_xlim<\/code>\u548cset_ylim<\/code>\u65b9\u6cd5\u3001\u8bbe\u7f6e\u523b\u5ea6\u8303\u56f4\u3001\u9690\u85cf\u4e0d\u9700\u8981\u7684\u523b\u5ea6\u6807\u7b7e\u7b49\u3002\u6bcf\u79cd\u65b9\u6cd5\u90fd\u6709\u5176\u7279\u5b9a\u7684\u5e94\u7528\u573a\u666f\uff0c\u80fd\u591f\u6ee1\u8db3\u4e0d\u540c\u7684\u9700\u6c42\u3002<\/p>\n<\/p>\n
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\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528Matplotlib\u5e93\u6765\u8bbe\u7f6e\u5750\u6807\u8f74\u7684\u663e\u793a\u8303\u56f4\u3002\u53ef\u4ee5\u901a\u8fc7plt.xlim()<\/code>\u548cplt.ylim()<\/code>\u51fd\u6570\u6765\u6307\u5b9ax\u8f74\u548cy\u8f74\u7684\u8303\u56f4\u3002\u4f8b\u5982\uff0cplt.xlim(0, 10)<\/code>\u5c06x\u8f74\u8303\u56f4\u8bbe\u7f6e\u4e3a0\u523010\uff0cplt.ylim(-5, 5)<\/code>\u5c06y\u8f74\u8303\u56f4\u8bbe\u7f6e\u4e3a-5\u52305\u3002\u8fd9\u79cd\u65b9\u6cd5\u53ef\u4ee5\u5e2e\u52a9\u7528\u6237\u66f4\u597d\u5730\u805a\u7126\u4e8e\u611f\u5174\u8da3\u7684\u6570\u636e\u533a\u57df\u3002<\/p>\n
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