{"id":985676,"date":"2024-12-27T07:38:39","date_gmt":"2024-12-26T23:38:39","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/985676.html"},"modified":"2024-12-27T07:38:42","modified_gmt":"2024-12-26T23:38:42","slug":"python%e5%a6%82%e4%bd%95%e5%88%86%e6%9e%90%e6%95%b0%e6%8d%ae%e6%8c%96%e6%8e%98","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/985676.html","title":{"rendered":"python\u5982\u4f55\u5206\u6790\u6570\u636e\u6316\u6398"},"content":{"rendered":"

\"python\u5982\u4f55\u5206\u6790\u6570\u636e\u6316\u6398\"<\/p>\n

Python\u5728\u6570\u636e\u6316\u6398\u4e2d\u5177\u6709\u5f3a\u5927\u7684\u80fd\u529b\u3001\u4e30\u5bcc\u7684\u5e93\u652f\u6301\u3001\u793e\u533a\u6d3b\u8dc3\u3001\u6613\u4e8e\u5b66\u4e60\u548c\u4f7f\u7528\u3001\u5e7f\u6cdb\u7684\u5e94\u7528\u9886\u57df\u3002<\/strong>Python\u662f\u4e00\u79cd\u7075\u6d3b\u3001\u6613\u4e8e\u5b66\u4e60\u548c\u4f7f\u7528\u7684\u7f16\u7a0b\u8bed\u8a00\uff0c\u5b83\u5728\u6570\u636e\u6316\u6398\u9886\u57df\u4e2d\u626e\u6f14\u7740\u91cd\u8981\u89d2\u8272\u3002Python\u62e5\u6709\u4e30\u5bcc\u7684\u5e93\u652f\u6301\uff0c\u5982Pandas\u3001NumPy\u3001Scikit-learn\u3001Matplotlib\u548cSeaborn\u7b49\uff0c\u4f7f\u5f97\u6570\u636e\u51c6\u5907\u3001\u6e05\u6d17\u3001\u5206\u6790\u548c\u53ef\u89c6\u5316\u53d8\u5f97\u66f4\u52a0\u5bb9\u6613\u3002Python\u7684\u793e\u533a\u975e\u5e38\u6d3b\u8dc3\uff0c\u63d0\u4f9b\u4e86\u5927\u91cf\u7684\u8d44\u6e90\u548c\u652f\u6301\uff0c\u4f7f\u5f97\u5b66\u4e60\u548c\u4f7f\u7528Python\u8fdb\u884c\u6570\u636e\u6316\u6398\u66f4\u52a0\u7b80\u5355\u3002\u6b64\u5916\uff0cPython\u5728\u5404\u4e2a\u884c\u4e1a\u4e2d\u90fd\u6709\u5e7f\u6cdb\u7684\u5e94\u7528\uff0c\u4ece\u91d1\u878d\u3001\u533b\u7597\u5230\u793e\u4ea4\u5a92\u4f53\u5206\u6790\u7b49\u3002\u63a5\u4e0b\u6765\u5c06\u8be6\u7ec6\u4ecb\u7ecdPython\u5982\u4f55\u5728\u6570\u636e\u6316\u6398\u4e2d\u53d1\u6325\u4f5c\u7528\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u6570\u636e\u51c6\u5907\u4e0e\u6e05\u6d17<\/p>\n<\/p>\n

\u6570\u636e\u51c6\u5907\u548c\u6e05\u6d17\u662f\u6570\u636e\u6316\u6398\u4e2d\u81f3\u5173\u91cd\u8981\u7684\u4e00\u6b65\u3002Python\u7684Pandas\u5e93\u662f\u5904\u7406\u6570\u636e\u7684\u5229\u5668\u3002Pandas\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u6570\u636e\u7ed3\u6784\u548c\u6570\u636e\u5206\u6790\u5de5\u5177\uff0c\u53ef\u4ee5\u8f7b\u677e\u5730\u8fdb\u884c\u6570\u636e\u6e05\u6d17\u3001\u8f6c\u6362\u3001\u5408\u5e76\u548c\u805a\u5408\u7b49\u64cd\u4f5c\u3002<\/p>\n<\/p>\n

Pandas\u53ef\u4ee5\u8bfb\u53d6\u591a\u79cd\u683c\u5f0f\u7684\u6570\u636e\u6587\u4ef6\uff0c\u5982CSV\u3001Excel\u3001SQL\u6570\u636e\u5e93\u7b49\uff0c\u5e76\u5c06\u5176\u8f6c\u6362\u4e3aDataFrame\u683c\u5f0f\uff0c\u65b9\u4fbf\u8fdb\u884c\u540e\u7eed\u64cd\u4f5c\u3002\u5728\u6570\u636e\u6e05\u6d17\u8fc7\u7a0b\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528Pandas\u8fdb\u884c\u7f3a\u5931\u503c\u5904\u7406\u3001\u91cd\u590d\u6570\u636e\u5220\u9664\u3001\u6570\u636e\u7c7b\u578b\u8f6c\u6362\u7b49\u64cd\u4f5c\u3002NumPy\u5e93\u5219\u63d0\u4f9b\u4e86\u9ad8\u6548\u7684\u6570\u7ec4\u64cd\u4f5c\u548c\u6570\u503c\u8ba1\u7b97\u529f\u80fd\uff0c\u53ef\u4ee5\u7528\u4e8e\u6570\u636e\u7684\u6570\u5b66\u8fd0\u7b97\u548c\u7edf\u8ba1\u5206\u6790\u3002<\/p>\n<\/p>\n

\u4e8c\u3001\u7279\u5f81\u5de5\u7a0b<\/p>\n<\/p>\n

\u7279\u5f81\u5de5\u7a0b\u662f\u6570\u636e\u6316\u6398\u4e2d\u63d0\u5347\u6a21\u578b\u6027\u80fd\u7684\u91cd\u8981\u6b65\u9aa4\u3002Python\u63d0\u4f9b\u4e86\u591a\u79cd\u5e93\u548c\u5de5\u5177\uff0c\u5e2e\u52a9\u5b9e\u73b0\u7279\u5f81\u9009\u62e9\u3001\u7279\u5f81\u63d0\u53d6\u548c\u7279\u5f81\u8f6c\u6362\u7b49\u4efb\u52a1\u3002<\/p>\n<\/p>\n

Scikit-learn\u5e93\u63d0\u4f9b\u4e86\u591a\u79cd\u7279\u5f81\u9009\u62e9\u65b9\u6cd5\uff0c\u5982\u9012\u5f52\u7279\u5f81\u6d88\u9664\uff08RFE\uff09\u3001\u4e3b\u6210\u5206\u5206\u6790\uff08PCA\uff09\u7b49\uff0c\u53ef\u4ee5\u5e2e\u52a9\u9009\u62e9\u6700\u5177\u4fe1\u606f\u91cf\u7684\u7279\u5f81\u3002\u6b64\u5916\uff0cScikit-learn\u8fd8\u63d0\u4f9b\u4e86\u7279\u5f81\u6807\u51c6\u5316\u3001\u5f52\u4e00\u5316\u3001\u7f16\u7801\u7b49\u529f\u80fd\uff0c\u5e2e\u52a9\u5bf9\u6570\u636e\u8fdb\u884c\u9884\u5904\u7406\u3002\u4f7f\u7528Python\u53ef\u4ee5\u8f7b\u677e\u5b9e\u73b0\u7279\u5f81\u5de5\u7a0b\uff0c\u63d0\u9ad8\u6a21\u578b\u7684\u9884\u6d4b\u6027\u80fd\u3002<\/p>\n<\/p>\n

\u4e09\u3001\u6570\u636e\u5efa\u6a21\u4e0e\u8bc4\u4f30<\/p>\n<\/p>\n

Python\u5728\u6570\u636e\u5efa\u6a21\u548c\u8bc4\u4f30\u65b9\u9762\u4e5f\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u5de5\u5177\u548c\u5e93\u3002Scikit-learn\u662fPython\u4e2d\u6700\u6d41\u884c\u7684\u673a\u5668\u5b66\u4e60<\/a>\u5e93\u4e4b\u4e00\uff0c\u5b83\u63d0\u4f9b\u4e86\u591a\u79cd\u673a\u5668\u5b66\u4e60\u7b97\u6cd5\uff0c\u5305\u62ec\u7ebf\u6027\u56de\u5f52\u3001\u51b3\u7b56\u6811\u3001\u968f\u673a\u68ee\u6797\u3001\u652f\u6301\u5411\u91cf\u673a\u7b49\u3002<\/p>\n<\/p>\n

\u4f7f\u7528Scikit-learn\uff0c\u53ef\u4ee5\u8f7b\u677e\u5730\u6784\u5efa\u548c\u8bad\u7ec3\u673a\u5668\u5b66\u4e60\u6a21\u578b\uff0c\u5e76\u8fdb\u884c\u6a21\u578b\u8bc4\u4f30\u3002Scikit-learn\u63d0\u4f9b\u4e86\u591a\u79cd\u8bc4\u4f30\u6307\u6807\uff0c\u5982\u51c6\u786e\u7387\u3001\u7cbe\u786e\u7387\u3001\u53ec\u56de\u7387\u3001F1\u5f97\u5206\u7b49\uff0c\u5e2e\u52a9\u8bc4\u4f30\u6a21\u578b\u7684\u6027\u80fd\u3002\u6b64\u5916\uff0cScikit-learn\u8fd8\u652f\u6301\u4ea4\u53c9\u9a8c\u8bc1\u3001\u7f51\u683c\u641c\u7d22\u7b49\u6a21\u578b\u4f18\u5316\u6280\u672f\uff0c\u5e2e\u52a9\u9009\u62e9\u6700\u4f73\u7684\u6a21\u578b\u53c2\u6570\u3002<\/p>\n<\/p>\n

\u56db\u3001\u6570\u636e\u53ef\u89c6\u5316<\/p>\n<\/p>\n

\u6570\u636e\u53ef\u89c6\u5316\u662f\u6570\u636e\u6316\u6398\u4e2d\u4e0d\u53ef\u6216\u7f3a\u7684\u4e00\u90e8\u5206\u3002Python\u63d0\u4f9b\u4e86\u591a\u79cd\u53ef\u89c6\u5316\u5e93\uff0c\u5982Matplotlib\u3001Seaborn\u3001Plotly\u7b49\uff0c\u53ef\u4ee5\u5e2e\u52a9\u521b\u5efa\u5404\u79cd\u7c7b\u578b\u7684\u56fe\u8868\u548c\u53ef\u89c6\u5316\u3002<\/p>\n<\/p>\n

Matplotlib\u662fPython\u4e2d\u6700\u57fa\u7840\u7684\u53ef\u89c6\u5316\u5e93\uff0c\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u7ed8\u56fe\u529f\u80fd\uff0c\u53ef\u4ee5\u521b\u5efa\u6298\u7ebf\u56fe\u3001\u67f1\u72b6\u56fe\u3001\u6563\u70b9\u56fe\u3001\u997c\u56fe\u7b49\u591a\u79cd\u56fe\u8868\u3002Seaborn\u662f\u5728Matplotlib\u57fa\u7840\u4e0a\u6784\u5efa\u7684\u9ad8\u7ea7\u53ef\u89c6\u5316\u5e93\uff0c\u63d0\u4f9b\u4e86\u66f4\u7b80\u6d01\u7684\u63a5\u53e3\u548c\u66f4\u7f8e\u89c2\u7684\u56fe\u5f62\u6837\u5f0f\u3002\u4f7f\u7528Seaborn\uff0c\u53ef\u4ee5\u8f7b\u677e\u521b\u5efa\u70ed\u529b\u56fe\u3001\u7bb1\u7ebf\u56fe\u3001\u5206\u5e03\u56fe\u7b49\u9ad8\u7ea7\u56fe\u8868\u3002\u6b64\u5916\uff0cPlotly\u662f\u4e00\u4e2a\u4ea4\u4e92\u5f0f\u53ef\u89c6\u5316\u5e93\uff0c\u53ef\u4ee5\u521b\u5efa\u52a8\u6001\u7684\u3001\u4ea4\u4e92\u5f0f\u7684\u56fe\u8868\uff0c\u9002\u7528\u4e8e\u5c55\u793a\u590d\u6742\u7684\u6570\u636e\u5173\u7cfb\u3002<\/p>\n<\/p>\n

\u4e94\u3001\u5e94\u7528\u9886\u57df<\/p>\n<\/p>\n

Python\u5728\u6570\u636e\u6316\u6398\u4e2d\u7684\u5e94\u7528\u9886\u57df\u975e\u5e38\u5e7f\u6cdb\uff0c\u51e0\u4e4e\u6db5\u76d6\u4e86\u5404\u4e2a\u884c\u4e1a\u548c\u9886\u57df\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u5e38\u89c1\u7684\u5e94\u7528\u9886\u57df\uff1a<\/p>\n<\/p>\n

    \n
  1. \n

    \u91d1\u878d\u5206\u6790<\/strong>\uff1aPython\u53ef\u4ee5\u7528\u4e8e\u91d1\u878d\u6570\u636e\u5206\u6790\u3001\u80a1\u7968\u9884\u6d4b\u3001\u98ce\u9669\u7ba1\u7406\u7b49\u3002\u901a\u8fc7\u4f7f\u7528Python\u7684\u673a\u5668\u5b66\u4e60\u7b97\u6cd5\uff0c\u53ef\u4ee5\u5b9e\u73b0\u5bf9\u91d1\u878d\u5e02\u573a\u7684\u9884\u6d4b\u548c\u5206\u6790\u3002<\/p>\n<\/p>\n<\/li>\n

  2. \n

    \u533b\u7597\u6570\u636e\u5206\u6790<\/strong>\uff1aPython\u53ef\u4ee5\u7528\u4e8e\u533b\u7597\u6570\u636e\u5206\u6790\u3001\u75be\u75c5\u9884\u6d4b\u3001\u57fa\u56e0\u7ec4\u5206\u6790\u7b49\u3002\u5728\u533b\u7597\u9886\u57df\uff0cPython\u53ef\u4ee5\u5e2e\u52a9\u5206\u6790\u5927\u91cf\u7684\u533b\u7597\u6570\u636e\uff0c\u63d0\u4f9b\u6709\u4ef7\u503c\u7684\u8bca\u65ad\u548c\u6cbb\u7597\u5efa\u8bae\u3002<\/p>\n<\/p>\n<\/li>\n

  3. \n

    \u793e\u4ea4\u5a92\u4f53\u5206\u6790<\/strong>\uff1aPython\u53ef\u4ee5\u7528\u4e8e\u793e\u4ea4\u5a92\u4f53\u6570\u636e\u5206\u6790\u3001\u60c5\u611f\u5206\u6790\u3001\u7528\u6237\u884c\u4e3a\u5206\u6790\u7b49\u3002\u901a\u8fc7\u5206\u6790\u793e\u4ea4\u5a92\u4f53\u6570\u636e\uff0c\u53ef\u4ee5\u4e86\u89e3\u7528\u6237\u7684\u60c5\u611f\u503e\u5411\u3001\u70ed\u70b9\u8bdd\u9898\u7b49\u3002<\/p>\n<\/p>\n<\/li>\n

  4. \n

    \u5e02\u573a\u8425\u9500<\/strong>\uff1aPython\u53ef\u4ee5\u7528\u4e8e\u5e02\u573a\u5206\u6790\u3001\u5ba2\u6237\u7ec6\u5206\u3001\u4ea7\u54c1\u63a8\u8350\u7b49\u3002\u5728\u5e02\u573a\u8425\u9500\u4e2d\uff0cPython\u53ef\u4ee5\u5e2e\u52a9\u5206\u6790\u5ba2\u6237\u6570\u636e\uff0c\u63d0\u4f9b\u4e2a\u6027\u5316\u7684\u4ea7\u54c1\u548c\u670d\u52a1\u63a8\u8350\u3002<\/p>\n<\/p>\n<\/li>\n

  5. \n

    \u81ea\u7136\u8bed\u8a00\u5904\u7406<\/strong>\uff1aPython\u53ef\u4ee5\u7528\u4e8e\u6587\u672c\u5206\u6790\u3001\u60c5\u611f\u5206\u6790\u3001\u673a\u5668\u7ffb\u8bd1\u7b49\u3002\u5728\u81ea\u7136\u8bed\u8a00\u5904\u7406\u9886\u57df\uff0cPython\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u5de5\u5177\u548c\u5e93\uff0c\u5982NLTK\u3001spaCy\u3001TextBlob\u7b49\uff0c\u53ef\u4ee5\u5e2e\u52a9\u5b9e\u73b0\u5404\u79cd\u81ea\u7136\u8bed\u8a00\u5904\u7406\u4efb\u52a1\u3002<\/p>\n<\/p>\n<\/li>\n<\/ol>\n

    \u516d\u3001Python\u5728\u6570\u636e\u6316\u6398\u4e2d\u7684\u4f18\u52bf<\/p>\n<\/p>\n

    Python\u5728\u6570\u636e\u6316\u6398\u4e2d\u5177\u6709\u591a\u65b9\u9762\u7684\u4f18\u52bf\uff0c\u4f7f\u5176\u6210\u4e3a\u6570\u636e\u5206\u6790\u5e08\u548c\u79d1\u5b66\u5bb6\u7684\u9996\u9009\u5de5\u5177\u3002<\/p>\n<\/p>\n

      \n
    1. \n

      \u6613\u4e8e\u5b66\u4e60\u548c\u4f7f\u7528<\/strong>\uff1aPython\u7684\u8bed\u6cd5\u7b80\u6d01\u660e\u4e86\uff0c\u975e\u5e38\u9002\u5408\u521d\u5b66\u8005\u5165\u95e8\u3002Python\u7684\u4ee3\u7801\u53ef\u8bfb\u6027\u5f3a\uff0c\u4f7f\u5f97\u56e2\u961f\u5408\u4f5c\u66f4\u52a0\u9ad8\u6548\u3002<\/p>\n<\/p>\n<\/li>\n

    2. \n

      \u4e30\u5bcc\u7684\u5e93\u652f\u6301<\/strong>\uff1aPython\u62e5\u6709\u4e30\u5bcc\u7684\u5e93\u652f\u6301\uff0c\u5982Pandas\u3001NumPy\u3001Scikit-learn\u3001Matplotlib\u7b49\uff0c\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u6570\u636e\u5904\u7406\u3001\u5206\u6790\u548c\u53ef\u89c6\u5316\u529f\u80fd\u3002<\/p>\n<\/p>\n<\/li>\n

    3. \n

      \u793e\u533a\u6d3b\u8dc3<\/strong>\uff1aPython\u7684\u793e\u533a\u975e\u5e38\u6d3b\u8dc3\uff0c\u63d0\u4f9b\u4e86\u5927\u91cf\u7684\u8d44\u6e90\u548c\u652f\u6301\u3002\u65e0\u8bba\u662f\u5728\u5b66\u4e60\u8fc7\u7a0b\u4e2d\u9047\u5230\u95ee\u9898\uff0c\u8fd8\u662f\u5728\u9879\u76ee\u5f00\u53d1\u4e2d\u9700\u8981\u5e2e\u52a9\uff0c\u90fd\u53ef\u4ee5\u5728\u793e\u533a\u4e2d\u627e\u5230\u7b54\u6848\u3002<\/p>\n<\/p>\n<\/li>\n

    4. \n

      \u8de8\u5e73\u53f0\u517c\u5bb9<\/strong>\uff1aPython\u662f\u8de8\u5e73\u53f0\u7684\u7f16\u7a0b\u8bed\u8a00\uff0c\u53ef\u4ee5\u5728Windows\u3001Linux\u3001Mac\u7b49\u591a\u4e2a\u5e73\u53f0\u4e0a\u8fd0\u884c\uff0c\u4f7f\u5f97\u5f00\u53d1\u548c\u90e8\u7f72\u66f4\u52a0\u7075\u6d3b\u3002<\/p>\n<\/p>\n<\/li>\n

    5. \n

      \u5e7f\u6cdb\u7684\u5e94\u7528\u9886\u57df<\/strong>\uff1aPython\u5728\u6570\u636e\u6316\u6398\u4e2d\u7684\u5e94\u7528\u9886\u57df\u975e\u5e38\u5e7f\u6cdb\uff0c\u51e0\u4e4e\u6db5\u76d6\u4e86\u5404\u4e2a\u884c\u4e1a\u548c\u9886\u57df\u3002\u4ece\u91d1\u878d\u3001\u533b\u7597\u5230\u5e02\u573a\u8425\u9500\u3001\u81ea\u7136\u8bed\u8a00\u5904\u7406\uff0cPython\u90fd\u80fd\u80dc\u4efb\u3002<\/p>\n<\/p>\n<\/li>\n<\/ol>\n

      \u4e03\u3001Python\u6570\u636e\u6316\u6398\u7684\u672a\u6765\u53d1\u5c55<\/p>\n<\/p>\n

      \u968f\u7740\u6570\u636e\u7684\u7206\u70b8\u5f0f\u589e\u957f\u548c\u4eba\u5de5\u667a\u80fd<\/a>\u6280\u672f\u7684\u5feb\u901f\u53d1\u5c55\uff0cPython\u5728\u6570\u636e\u6316\u6398\u4e2d\u7684\u5e94\u7528\u524d\u666f\u5e7f\u9614\u3002\u672a\u6765\uff0cPython\u5c06\u5728\u4ee5\u4e0b\u51e0\u4e2a\u65b9\u9762\u7ee7\u7eed\u53d1\u6325\u91cd\u8981\u4f5c\u7528\uff1a<\/p>\n<\/p>\n

        \n
      1. \n

        \u5927\u6570\u636e\u5904\u7406<\/strong>\uff1a\u968f\u7740\u5927\u6570\u636e\u6280\u672f\u7684\u53d1\u5c55\uff0cPython\u5c06\u7ee7\u7eed\u5728\u5927\u6570\u636e\u5904\u7406\u548c\u5206\u6790\u4e2d\u53d1\u6325\u4f5c\u7528\u3002Python\u7684\u5e93\u548c\u5de5\u5177\u5c06\u4e0d\u65ad\u5b8c\u5584\u548c\u4f18\u5316\uff0c\u4ee5\u5904\u7406\u66f4\u5927\u89c4\u6a21\u7684\u6570\u636e\u96c6\u3002<\/p>\n<\/p>\n<\/li>\n

      2. \n

        \u6df1\u5ea6\u5b66\u4e60<\/strong>\uff1a\u968f\u7740\u6df1\u5ea6\u5b66\u4e60\u6280\u672f\u7684\u5feb\u901f\u53d1\u5c55\uff0cPython\u5c06\u7ee7\u7eed\u5728\u6df1\u5ea6\u5b66\u4e60\u9886\u57df\u4e2d\u5360\u636e\u91cd\u8981\u5730\u4f4d\u3002Python\u7684\u6df1\u5ea6\u5b66\u4e60\u6846\u67b6\uff0c\u5982TensorFlow\u3001Keras\u3001PyTorch\u7b49\uff0c\u5c06\u4e0d\u65ad\u53d1\u5c55\u548c\u6f14\u8fdb\uff0c\u63d0\u4f9b\u66f4\u5f3a\u5927\u7684\u529f\u80fd\u548c\u66f4\u9ad8\u7684\u6027\u80fd\u3002<\/p>\n<\/p>\n<\/li>\n

      3. \n

        \u81ea\u52a8\u5316\u6570\u636e\u6316\u6398<\/strong>\uff1a\u968f\u7740\u81ea\u52a8\u5316\u6280\u672f\u7684\u53d1\u5c55\uff0cPython\u5c06\u5728\u81ea\u52a8\u5316\u6570\u636e\u6316\u6398\u4e2d\u53d1\u6325\u91cd\u8981\u4f5c\u7528\u3002Python\u7684\u5e93\u548c\u5de5\u5177\u5c06\u4e0d\u65ad\u53d1\u5c55\uff0c\u63d0\u4f9b\u66f4\u667a\u80fd\u7684\u81ea\u52a8\u5316\u6570\u636e\u6316\u6398\u89e3\u51b3\u65b9\u6848\u3002<\/p>\n<\/p>\n<\/li>\n

      4. \n

        \u7269\u8054\u7f51\u6570\u636e\u5206\u6790<\/strong>\uff1a\u968f\u7740\u7269\u8054\u7f51\u6280\u672f\u7684\u53d1\u5c55\uff0cPython\u5c06\u5728\u7269\u8054\u7f51\u6570\u636e\u5206\u6790\u4e2d\u53d1\u6325\u91cd\u8981\u4f5c\u7528\u3002Python\u7684\u5e93\u548c\u5de5\u5177\u5c06\u4e0d\u65ad\u53d1\u5c55\uff0c\u4ee5\u6ee1\u8db3\u7269\u8054\u7f51\u6570\u636e\u5206\u6790\u7684\u9700\u6c42\u3002<\/p>\n<\/p>\n<\/li>\n

      5. \n

        \u53ef\u89e3\u91ca\u6027\u548c\u900f\u660e\u6027<\/strong>\uff1a\u968f\u7740\u5bf9\u6a21\u578b\u53ef\u89e3\u91ca\u6027\u548c\u900f\u660e\u6027\u9700\u6c42\u7684\u589e\u52a0\uff0cPython\u5c06\u7ee7\u7eed\u5728\u8fd9\u4e00\u9886\u57df\u4e2d\u53d1\u6325\u4f5c\u7528\u3002Python\u7684\u5e93\u548c\u5de5\u5177\u5c06\u4e0d\u65ad\u53d1\u5c55\uff0c\u4ee5\u63d0\u4f9b\u66f4\u597d\u7684\u6a21\u578b\u53ef\u89e3\u91ca\u6027\u548c\u900f\u660e\u6027\u3002<\/p>\n<\/p>\n<\/li>\n<\/ol>\n

        \u603b\u7ed3\u800c\u8a00\uff0cPython\u5728\u6570\u636e\u6316\u6398\u4e2d\u7684\u5e94\u7528\u5df2\u7ecf\u76f8\u5f53\u6210\u719f\uff0c\u5e76\u5c06\u5728\u672a\u6765\u7ee7\u7eed\u53d1\u5c55\u3002\u51ed\u501f\u5176\u5f3a\u5927\u7684\u529f\u80fd\u3001\u6613\u7528\u7684\u7279\u6027\u548c\u5e7f\u6cdb\u7684\u5e94\u7528\u9886\u57df\uff0cPython\u5c06\u7ee7\u7eed\u5728\u6570\u636e\u6316\u6398\u9886\u57df\u4e2d\u5360\u636e\u91cd\u8981\u5730\u4f4d\u3002\u901a\u8fc7\u4e0d\u65ad\u5b66\u4e60\u548c\u5b9e\u8df5\uff0c\u6570\u636e\u5206\u6790\u5e08\u548c\u79d1\u5b66\u5bb6\u53ef\u4ee5\u5229\u7528Python\u5728\u6570\u636e\u6316\u6398\u4e2d\u5b9e\u73b0\u66f4\u591a\u7684\u521b\u65b0\u548c\u7a81\u7834\u3002<\/p>\n<\/p>\n

        \u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n

        Python\u6709\u54ea\u4e9b\u5e38\u7528\u7684\u6570\u636e\u6316\u6398\u5e93\uff1f<\/strong>
        Python\u63d0\u4f9b\u4e86\u591a\u79cd\u5f3a\u5927\u7684\u5e93\u6765\u652f\u6301\u6570\u636e\u6316\u6398\uff0c\u5305\u62ecPandas\u3001NumPy\u3001Scikit-learn\u548cMatplotlib\u7b49\u3002Pandas\u4e3b\u8981\u7528\u4e8e\u6570\u636e\u5904\u7406\u548c\u5206\u6790\uff0cNumPy\u7528\u4e8e\u6570\u503c\u8ba1\u7b97\uff0cScikit-learn\u63d0\u4f9b\u4e86\u4f17\u591a\u673a\u5668\u5b66\u4e60\u7b97\u6cd5\uff0c\u800cMatplotlib\u5219\u5e2e\u52a9\u53ef\u89c6\u5316\u6570\u636e\u3002\u8fd9\u4e9b\u5e93\u7ed3\u5408\u4f7f\u7528\u53ef\u4ee5\u9ad8\u6548\u5730\u8fdb\u884c\u6570\u636e\u6316\u6398\u3002<\/p>\n

        \u5728\u6570\u636e\u6316\u6398\u8fc7\u7a0b\u4e2d\uff0c\u5982\u4f55\u9009\u62e9\u5408\u9002\u7684\u7b97\u6cd5\uff1f<\/strong>
        \u9009\u62e9\u5408\u9002\u7684\u7b97\u6cd5\u901a\u5e38\u53d6\u51b3\u4e8e\u6570\u636e\u7684\u7279\u6027\u548c\u76ee\u6807\u3002\u4f8b\u5982\uff0c\u5206\u7c7b\u95ee\u9898\u53ef\u4ee5\u4f7f\u7528\u51b3\u7b56\u6811\u3001\u968f\u673a\u68ee\u6797\u6216\u652f\u6301\u5411\u91cf\u673a\u7b49\u7b97\u6cd5\uff0c\u800c\u805a\u7c7b\u95ee\u9898\u5219\u53ef\u4ee5\u8003\u8651K-means\u6216\u5c42\u6b21\u805a\u7c7b\u7b49\u65b9\u6cd5\u3002\u7406\u89e3\u6570\u636e\u7684\u7c7b\u578b\uff08\u5982\u7ed3\u6784\u5316\u6216\u975e\u7ed3\u6784\u5316\uff09\u548c\u6316\u6398\u76ee\u6807\uff08\u5982\u9884\u6d4b\u6216\u63cf\u8ff0\uff09\u6709\u52a9\u4e8e\u505a\u51fa\u66f4\u660e\u667a\u7684\u9009\u62e9\u3002<\/p>\n

        \u5982\u4f55\u8fdb\u884c\u6570\u636e\u9884\u5904\u7406\u4ee5\u63d0\u9ad8\u6316\u6398\u6548\u679c\uff1f<\/strong>
        \u6570\u636e\u9884\u5904\u7406\u662f\u6570\u636e\u6316\u6398\u7684\u91cd\u8981\u4e00\u6b65\uff0c\u901a\u5e38\u5305\u62ec\u6570\u636e\u6e05\u6d17\u3001\u7f3a\u5931\u503c\u5904\u7406\u3001\u6570\u636e\u8f6c\u6362\u548c\u6807\u51c6\u5316\u7b49\u8fc7\u7a0b\u3002\u6e05\u6d17\u6570\u636e\u53ef\u4ee5\u53bb\u9664\u566a\u58f0\u548c\u4e0d\u4e00\u81f4\uff0c\u7f3a\u5931\u503c\u5904\u7406\u53ef\u4ee5\u901a\u8fc7\u586b\u8865\u6216\u5220\u9664\u7f3a\u5931\u6570\u636e\u6765\u89e3\u51b3\uff0c\u800c\u6807\u51c6\u5316\u5219\u5e2e\u52a9\u63d0\u9ad8\u7b97\u6cd5\u7684\u6548\u7387\u548c\u51c6\u786e\u6027\u3002\u826f\u597d\u7684\u9884\u5904\u7406\u53ef\u4ee5\u663e\u8457\u63d0\u5347\u6316\u6398\u7ed3\u679c\u7684\u8d28\u91cf\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"Python\u5728\u6570\u636e\u6316\u6398\u4e2d\u5177\u6709\u5f3a\u5927\u7684\u80fd\u529b\u3001\u4e30\u5bcc\u7684\u5e93\u652f\u6301\u3001\u793e\u533a\u6d3b\u8dc3\u3001\u6613\u4e8e\u5b66\u4e60\u548c\u4f7f\u7528\u3001\u5e7f\u6cdb\u7684\u5e94\u7528\u9886\u57df\u3002Python\u662f […]","protected":false},"author":3,"featured_media":985681,"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\/985676"}],"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=985676"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/985676\/revisions"}],"predecessor-version":[{"id":985685,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/985676\/revisions\/985685"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/985681"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=985676"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=985676"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=985676"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}