{"id":1083055,"date":"2025-01-08T12:54:31","date_gmt":"2025-01-08T04:54:31","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1083055.html"},"modified":"2025-01-08T12:54:33","modified_gmt":"2025-01-08T04:54:33","slug":"python%e5%a6%82%e4%bd%95%e7%94%bb%e4%b8%80%e7%bb%b4%e6%95%b0%e7%bb%84%e7%9a%84%e5%9b%be-2","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1083055.html","title":{"rendered":"python\u5982\u4f55\u753b\u4e00\u7ef4\u6570\u7ec4\u7684\u56fe"},"content":{"rendered":"

\"python\u5982\u4f55\u753b\u4e00\u7ef4\u6570\u7ec4\u7684\u56fe\"<\/p>\n

\u4f7f\u7528Python\u7ed8\u5236\u4e00\u7ef4\u6570\u7ec4\u7684\u56fe\u7684\u6838\u5fc3\u65b9\u6cd5\u5305\u62ec\uff1a\u4f7f\u7528Matplotlib\u5e93\u3001\u4f7f\u7528Seaborn\u5e93\u3001\u4f7f\u7528Pandas\u5e93\u3002<\/strong>\u4e0b\u9762\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5176\u4e2d\u4e00\u79cd\u65b9\u6cd5\uff0c\u5373\u4f7f\u7528Matplotlib\u5e93\uff0c\u6765\u7ed8\u5236\u4e00\u7ef4\u6570\u7ec4\u7684\u56fe\u3002<\/p>\n<\/p>\n

\u4f7f\u7528Matplotlib\u5e93\u7ed8\u5236\u4e00\u7ef4\u6570\u7ec4\u7684\u56fe\u662f\u4e00\u79cd\u975e\u5e38\u5e38\u89c1\u4e14\u7b80\u5355\u7684\u65b9\u6cd5\u3002Matplotlib\u662f\u4e00\u4e2a\u7528\u4e8e\u521b\u5efa\u9759\u6001\u3001\u52a8\u753b\u548c\u4ea4\u4e92\u5f0f\u53ef\u89c6\u5316\u7684Python\u5e93\u3002\u5b83\u63d0\u4f9b\u4e86\u4e00\u4e2a\u9762\u5411\u5bf9\u8c61\u7684API\uff0c\u4ee5\u5d4c\u5165\u5404\u79cd\u56fe\u8868\u5230\u5e94\u7528\u7a0b\u5e8f\u4e2d\uff0c\u5e76\u4e14\u652f\u6301\u591a\u79cd\u7c7b\u578b\u7684\u56fe\u8868\uff0c\u5982\u6298\u7ebf\u56fe\u3001\u6563\u70b9\u56fe\u3001\u67f1\u72b6\u56fe\u7b49\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u4f7f\u7528Matplotlib\u5e93\u7ed8\u5236\u4e00\u7ef4\u6570\u7ec4\u7684\u56fe<\/p>\n<\/p>\n

1\u3001\u5b89\u88c5Matplotlib\u5e93<\/p>\n<\/p>\n

\u5728\u4f7f\u7528Matplotlib\u5e93\u4e4b\u524d\uff0c\u9996\u5148\u9700\u8981\u786e\u4fdd\u5df2\u7ecf\u5b89\u88c5\u4e86\u8be5\u5e93\u3002\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\u3001\u5bfc\u5165Matplotlib\u5e93<\/p>\n<\/p>\n
\u5728\u5b89\u88c5\u5b8c\u6210\u540e\uff0c\u53ef\u4ee5\u5728Python\u811a\u672c\u4e2d\u5bfc\u5165Matplotlib\u5e93\uff1a<\/p>\n<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
<\/code><\/pre>\n<\/p>\n
3\u3001\u521b\u5efa\u4e00\u7ef4\u6570\u7ec4<\/p>\n<\/p>\n
\u63a5\u4e0b\u6765\uff0c\u9700\u8981\u521b\u5efa\u4e00\u4e2a\u4e00\u7ef4\u6570\u7ec4\u3002\u53ef\u4ee5\u4f7f\u7528Python\u5185\u7f6e\u7684\u5217\u8868\u6765\u521b\u5efa\u4e00\u7ef4\u6570\u7ec4\uff0c\u4f8b\u5982\uff1a<\/p>\n<\/p>\n
data = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]<\/p>\n
<\/code><\/pre>\n<\/p>\n
4\u3001\u7ed8\u5236\u56fe\u8868<\/p>\n<\/p>\n
\u4f7f\u7528Matplotlib\u5e93\u63d0\u4f9b\u7684\u5404\u79cd\u51fd\u6570\uff0c\u53ef\u4ee5\u7ed8\u5236\u4e0d\u540c\u7c7b\u578b\u7684\u56fe\u8868\u3002\u4f8b\u5982\uff0c\u4f7f\u7528plt.plot()<\/code>\u51fd\u6570\u53ef\u4ee5\u7ed8\u5236\u6298\u7ebf\u56fe\uff1a<\/p>\n<\/p>\n
plt.plot(data)<\/p>\n
plt.title('Line Plot of 1D Array')<\/p>\n
plt.xlabel('Index')<\/p>\n
plt.ylabel('Value')<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8fd9\u6bb5\u4ee3\u7801\u5c06\u7ed8\u5236\u4e00\u4e2a\u6298\u7ebf\u56fe\uff0c\u5176\u4e2dx\u8f74\u8868\u793a\u6570\u7ec4\u7684\u7d22\u5f15\uff0cy\u8f74\u8868\u793a\u6570\u7ec4\u7684\u503c\u3002<\/p>\n<\/p>\n
\u4e8c\u3001\u4f7f\u7528Seaborn\u5e93\u7ed8\u5236\u4e00\u7ef4\u6570\u7ec4\u7684\u56fe<\/p>\n<\/p>\n
Seaborn\u662f\u4e00\u4e2a\u57fa\u4e8eMatplotlib\u7684Python\u6570\u636e\u53ef\u89c6\u5316\u5e93\u3002\u5b83\u63d0\u4f9b\u4e86\u66f4\u9ad8\u7ea7\u7684\u63a5\u53e3\u548c\u66f4\u7b80\u6d01\u7684\u8bed\u6cd5\uff0c\u4f7f\u5f97\u7ed8\u5236\u590d\u6742\u7684\u7edf\u8ba1\u56fe\u8868\u66f4\u52a0\u5bb9\u6613\u3002Seaborn\u4e5f\u53ef\u4ee5\u7528\u6765\u7ed8\u5236\u4e00\u7ef4\u6570\u7ec4\u7684\u56fe\u3002<\/p>\n<\/p>\n
1\u3001\u5b89\u88c5Seaborn\u5e93<\/p>\n<\/p>\n
\u9996\u5148\uff0c\u9700\u8981\u5b89\u88c5Seaborn\u5e93\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\uff1a<\/p>\n<\/p>\n
pip install seaborn<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u5bfc\u5165Seaborn\u5e93<\/p>\n<\/p>\n
\u5728\u5b89\u88c5\u5b8c\u6210\u540e\uff0c\u53ef\u4ee5\u5728Python\u811a\u672c\u4e2d\u5bfc\u5165Seaborn\u5e93\uff1a<\/p>\n<\/p>\n
import seaborn as sns<\/p>\n
<\/code><\/pre>\n<\/p>\n
3\u3001\u7ed8\u5236\u56fe\u8868<\/p>\n<\/p>\n
\u4f7f\u7528Seaborn\u5e93\uff0c\u53ef\u4ee5\u7ed8\u5236\u591a\u79cd\u7c7b\u578b\u7684\u7edf\u8ba1\u56fe\u8868\u3002\u4f8b\u5982\uff0c\u53ef\u4ee5\u4f7f\u7528sns.lineplot()<\/code>\u51fd\u6570\u7ed8\u5236\u6298\u7ebf\u56fe\uff1a<\/p>\n<\/p>\n
sns.lineplot(x=range(len(data)), y=data)<\/p>\n
plt.title('Line Plot of 1D Array using Seaborn')<\/p>\n
plt.xlabel('Index')<\/p>\n
plt.ylabel('Value')<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8fd9\u6bb5\u4ee3\u7801\u5c06\u7ed8\u5236\u4e00\u4e2a\u6298\u7ebf\u56fe\uff0c\u5176\u4e2dx\u8f74\u8868\u793a\u6570\u7ec4\u7684\u7d22\u5f15\uff0cy\u8f74\u8868\u793a\u6570\u7ec4\u7684\u503c\u3002<\/p>\n<\/p>\n
\u4e09\u3001\u4f7f\u7528Pandas\u5e93\u7ed8\u5236\u4e00\u7ef4\u6570\u7ec4\u7684\u56fe<\/p>\n<\/p>\n
Pandas\u662f\u4e00\u4e2a\u6570\u636e\u5206\u6790\u548c\u64cd\u4f5c\u5e93\uff0c\u63d0\u4f9b\u4e86\u9ad8\u6548\u7684\u6570\u636e\u7ed3\u6784\u548c\u6570\u636e\u5206\u6790\u5de5\u5177\u3002Pandas\u4e5f\u63d0\u4f9b\u4e86\u4e0eMatplotlib\u96c6\u6210\u7684\u7ed8\u56fe\u529f\u80fd\uff0c\u53ef\u4ee5\u7528\u6765\u7ed8\u5236\u4e00\u7ef4\u6570\u7ec4\u7684\u56fe\u3002<\/p>\n<\/p>\n
1\u3001\u5b89\u88c5Pandas\u5e93<\/p>\n<\/p>\n
\u9996\u5148\uff0c\u9700\u8981\u5b89\u88c5Pandas\u5e93\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\uff1a<\/p>\n<\/p>\n
pip install pandas<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u5bfc\u5165Pandas\u5e93<\/p>\n<\/p>\n
\u5728\u5b89\u88c5\u5b8c\u6210\u540e\uff0c\u53ef\u4ee5\u5728Python\u811a\u672c\u4e2d\u5bfc\u5165Pandas\u5e93\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
<\/code><\/pre>\n<\/p>\n
3\u3001\u521b\u5efa\u4e00\u7ef4\u6570\u7ec4<\/p>\n<\/p>\n
\u53ef\u4ee5\u4f7f\u7528Pandas\u7684Series<\/code>\u5bf9\u8c61\u6765\u521b\u5efa\u4e00\u7ef4\u6570\u7ec4\uff0c\u4f8b\u5982\uff1a<\/p>\n<\/p>\n
data = pd.Series([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])<\/p>\n
<\/code><\/pre>\n<\/p>\n
4\u3001\u7ed8\u5236\u56fe\u8868<\/p>\n<\/p>\n
\u4f7f\u7528Pandas\u7684plot<\/code>\u65b9\u6cd5\uff0c\u53ef\u4ee5\u7ed8\u5236\u4e0d\u540c\u7c7b\u578b\u7684\u56fe\u8868\u3002\u4f8b\u5982\uff0c\u4f7f\u7528data.plot()<\/code>\u65b9\u6cd5\u53ef\u4ee5\u7ed8\u5236\u6298\u7ebf\u56fe\uff1a<\/p>\n<\/p>\n
data.plot()<\/p>\n
plt.title('Line Plot of 1D Array using Pandas')<\/p>\n
plt.xlabel('Index')<\/p>\n
plt.ylabel('Value')<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8fd9\u6bb5\u4ee3\u7801\u5c06\u7ed8\u5236\u4e00\u4e2a\u6298\u7ebf\u56fe\uff0c\u5176\u4e2dx\u8f74\u8868\u793a\u6570\u7ec4\u7684\u7d22\u5f15\uff0cy\u8f74\u8868\u793a\u6570\u7ec4\u7684\u503c\u3002<\/p>\n<\/p>\n
\u56db\u3001\u603b\u7ed3<\/p>\n<\/p>\n
\u4f7f\u7528Python\u7ed8\u5236\u4e00\u7ef4\u6570\u7ec4\u7684\u56fe\u53ef\u4ee5\u901a\u8fc7\u591a\u79cd\u65b9\u6cd5\u5b9e\u73b0\uff0c\u5176\u4e2d\u6700\u5e38\u7528\u7684\u65b9\u6cd5\u5305\u62ec\u4f7f\u7528Matplotlib\u5e93\u3001\u4f7f\u7528Seaborn\u5e93\u548c\u4f7f\u7528Pandas\u5e93\u3002\u6bcf\u79cd\u65b9\u6cd5\u90fd\u6709\u5176\u72ec\u7279\u7684\u4f18\u52bf\u548c\u9002\u7528\u573a\u666f\u3002\u5bf9\u4e8e\u7b80\u5355\u7684\u56fe\u8868\u7ed8\u5236\uff0cMatplotlib\u5e93\u662f\u4e00\u4e2a\u975e\u5e38\u597d\u7684\u9009\u62e9\uff1b\u5bf9\u4e8e\u590d\u6742\u7684\u7edf\u8ba1\u56fe\u8868\uff0cSeaborn\u5e93\u63d0\u4f9b\u4e86\u66f4\u9ad8\u7ea7\u7684\u63a5\u53e3\u548c\u66f4\u7b80\u6d01\u7684\u8bed\u6cd5\uff1b\u5bf9\u4e8e\u6570\u636e\u5206\u6790\u548c\u64cd\u4f5c\uff0cPandas\u5e93\u63d0\u4f9b\u4e86\u9ad8\u6548\u7684\u6570\u636e\u7ed3\u6784\u548c\u6570\u636e\u5206\u6790\u5de5\u5177\u3002\u6839\u636e\u5177\u4f53\u7684\u9700\u6c42\u9009\u62e9\u5408\u9002\u7684\u5de5\u5177\uff0c\u53ef\u4ee5\u66f4\u9ad8\u6548\u5730\u5b8c\u6210\u6570\u636e\u53ef\u89c6\u5316\u4efb\u52a1\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
 \u5982\u4f55\u5728Python\u4e2d\u7ed8\u5236\u4e00\u7ef4\u6570\u7ec4\u7684\u56fe\u5f62\uff1f<\/strong>
\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528\u591a\u79cd\u5e93\u6765\u7ed8\u5236\u4e00\u7ef4\u6570\u7ec4\u7684\u56fe\u5f62\u3002\u6700\u5e38\u7528\u7684\u5e93\u662fMatplotlib\u3002\u60a8\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u6b65\u9aa4\u5b9e\u73b0\uff1a\u9996\u5148\uff0c\u5b89\u88c5Matplotlib\u5e93\u3002\u63a5\u7740\uff0c\u4f7f\u7528plt.plot()<\/code>\u51fd\u6570\u5c06\u4e00\u7ef4\u6570\u7ec4\u4f5c\u4e3a\u8f93\u5165\uff0c\u6700\u540e\u4f7f\u7528plt.show()<\/code>\u6765\u663e\u793a\u56fe\u5f62\u3002\u4ee3\u7801\u793a\u4f8b\uff1a  <\/p>\n
import matplotlib.pyplot as plt\n\ndata = [1, 2, 3, 4, 5]  # \u4e00\u7ef4\u6570\u7ec4\nplt.plot(data)\nplt.title("\u4e00\u7ef4\u6570\u7ec4\u56fe")\nplt.xlabel("\u7d22\u5f15")\nplt.ylabel("\u503c")\nplt.show()\n<\/code><\/pre>\n
\u5728\u4e00\u7ef4\u6570\u7ec4\u4e2d\u5982\u4f55\u6807\u8bb0\u7279\u5b9a\u7684\u6570\u636e\u70b9\uff1f<\/strong>
\u8981\u6807\u8bb0\u4e00\u7ef4\u6570\u7ec4\u4e2d\u7684\u7279\u5b9a\u6570\u636e\u70b9\uff0c\u53ef\u4ee5\u4f7f\u7528Matplotlib\u7684plt.scatter()<\/code>\u51fd\u6570\u3002\u5728\u7ed8\u5236\u56fe\u5f62\u65f6\uff0c\u60a8\u53ef\u4ee5\u5728\u76f8\u5e94\u7684\u4f4d\u7f6e\u6dfb\u52a0\u6563\u70b9\u6765\u7a81\u51fa\u663e\u793a\u7279\u5b9a\u7684\u6570\u503c\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u793a\u4f8b\uff1a  <\/p>\n
import matplotlib.pyplot as plt\n\ndata = [1, 3, 2, 5, 4]\nplt.plot(data)\nplt.scatter([1, 3], [data[1], data[3]], color='red')  # \u6807\u8bb0\u7279\u5b9a\u6570\u636e\u70b9\nplt.title("\u5e26\u6807\u8bb0\u7684\u4e00\u7ef4\u6570\u7ec4\u56fe")\nplt.xlabel("\u7d22\u5f15")\nplt.ylabel("\u503c")\nplt.show()\n<\/code><\/pre>\n
\u53ef\u4ee5\u4f7f\u7528\u54ea\u4e9b\u5176\u4ed6\u5e93\u6765\u7ed8\u5236\u4e00\u7ef4\u6570\u7ec4\u7684\u56fe\u5f62\uff1f<\/strong>
\u9664\u4e86Matplotlib\uff0c\u60a8\u8fd8\u53ef\u4ee5\u4f7f\u7528Seaborn\u548cPlotly\u7b49\u5e93\u6765\u7ed8\u5236\u4e00\u7ef4\u6570\u7ec4\u7684\u56fe\u5f62\u3002Seaborn\u5728\u5904\u7406\u7edf\u8ba1\u6570\u636e\u65f6\u975e\u5e38\u6709\u6548\uff0c\u800cPlotly\u63d0\u4f9b\u4e86\u4ea4\u4e92\u5f0f\u56fe\u5f62\uff0c\u4f7f\u7528\u6237\u80fd\u591f\u66f4\u76f4\u89c2\u5730\u63a2\u7d22\u6570\u636e\u3002\u6839\u636e\u9700\u6c42\u9009\u62e9\u5408\u9002\u7684\u5e93\uff0c\u53ef\u4ee5\u63d0\u5347\u6570\u636e\u53ef\u89c6\u5316\u7684\u6548\u679c\u548c\u4f53\u9a8c\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u4f7f\u7528Python\u7ed8\u5236\u4e00\u7ef4\u6570\u7ec4\u7684\u56fe\u7684\u6838\u5fc3\u65b9\u6cd5\u5305\u62ec\uff1a\u4f7f\u7528Matplotlib\u5e93\u3001\u4f7f\u7528Seaborn\u5e93\u3001\u4f7f\u7528Pand […]","protected":false},"author":3,"featured_media":1083062,"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\/1083055"}],"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=1083055"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1083055\/revisions"}],"predecessor-version":[{"id":1083063,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1083055\/revisions\/1083063"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1083062"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1083055"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1083055"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1083055"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}