{"id":188022,"date":"2024-05-09T16:32:00","date_gmt":"2024-05-09T08:32:00","guid":{"rendered":""},"modified":"2024-05-09T16:32:06","modified_gmt":"2024-05-09T08:32:06","slug":"python%e5%9c%a8%e5%81%9a%e6%9c%ba%e5%99%a8%e5%ad%a6%e4%b9%a0%e6%96%b9%e9%9d%a2%e6%af%94%e5%85%b6%e4%bb%96%e8%af%ad%e8%a8%80%e6%9c%89%e5%8a%bf%e6%98%af%e4%bb%80%e4%b9%88","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/188022.html","title":{"rendered":"python\u5728\u505a\u673a\u5668\u5b66\u4e60\u65b9\u9762\u6bd4\u5176\u4ed6\u8bed\u8a00\u6709\u52bf\u662f\u4ec0\u4e48"},"content":{"rendered":"<p style=\"text-align:center\"><img decoding=\"async\" src=\"https:\/\/cdn-kb.worktile.com\/kb\/wp-content\/uploads\/2024\/04\/26094237\/0cdcd76b-a168-4817-9015-2d69c03f4972.webp\" alt=\"python\u5728\u505a\u673a\u5668\u5b66\u4e60\u65b9\u9762\u6bd4\u5176\u4ed6\u8bed\u8a00\u6709\u52bf\u662f\u4ec0\u4e48\" \/><\/p>\n<p><p>Python\u5728<a href=\"https:\/\/docs.pingcode.com\/ask\/59192.html\" target=\"_blank\">\u673a\u5668\u5b66\u4e60<\/a>\u9886\u57df\u6bd4\u5176\u4ed6\u8bed\u8a00\u62e5\u6709\u7684\u4f18\u52bf\u4e3b\u8981\u5305\u62ec\uff1a<strong>\u5e7f\u6cdb\u7684\u5e93\u652f\u6301\u3001\u6613\u4e8e\u5b66\u4e60\u4e0e\u4f7f\u7528\u3001\u5f3a\u5927\u7684\u793e\u533a\u652f\u6301\u3001\u4e30\u5bcc\u7684\u6570\u636e\u5904\u7406\u80fd\u529b<\/strong>\u3002\u5176\u4e2d\uff0c<strong>\u5e7f\u6cdb\u7684\u5e93\u652f\u6301<\/strong>\u662fPython\u6210\u4e3a\u673a\u5668\u5b66\u4e60\u9996\u9009\u8bed\u8a00\u7684\u5173\u952e\u56e0\u7d20\u3002Python\u63d0\u4f9b\u4e86\u5927\u91cf\u4e14\u9ad8\u6548\u7684\u673a\u5668\u5b66\u4e60\u5e93\uff0c\u5982TensorFlow\u3001Keras\u3001PyTorch\u3001Scikit-learn\u7b49\uff0c\u8fd9\u4e9b\u5e93\u51e0\u4e4e\u6db5\u76d6\u4e86\u673a\u5668\u5b66\u4e60\u9879\u76ee\u6240\u9700\u7684\u6240\u6709\u529f\u80fd\uff0c\u5305\u62ec\u6570\u636e\u9884\u5904\u7406\u3001\u7b97\u6cd5\u5b9e\u73b0\u3001\u6a21\u578b\u8bad\u7ec3\u4e0e\u8bc4\u4f30\u7b49\u3002\u8fd9\u610f\u5473\u7740\u4f7f\u7528Python\u8fdb\u884c\u673a\u5668\u5b66\u4e60\u9879\u76ee\uff0c\u5f00\u53d1\u8005\u53ef\u4ee5\u5728\u5e9e\u5927\u7684\u8d44\u6e90\u5e93\u4e2d\u627e\u5230\u51e0\u4e4e\u6240\u6709\u4ed6\u4eec\u9700\u8981\u7684\u5de5\u5177\u548c\u7b97\u6cd5\uff0c\u5927\u5927\u52a0\u5feb\u4e86\u5f00\u53d1\u901f\u5ea6\u548c\u6548\u7387\u3002<\/p>\n<\/p>\n<p><h3>\u4e00\u3001\u5e7f\u6cdb\u7684\u5e93\u652f\u6301<\/h3>\n<\/p>\n<p><p>Python\u51ed\u501f\u5176\u5e7f\u6cdb\u7684\u5e93\u652f\u6301\uff0c\u5728\u673a\u5668\u5b66\u4e60\u9886\u57df\u5360\u636e\u4e86\u91cd\u8981\u5730\u4f4d\u3002\u4f8b\u5982\uff0cScikit-learn\u63d0\u4f9b\u4e86\u5927\u91cf\u7b80\u5355\u6613\u7528\u7684\u5de5\u5177\uff0c\u9002\u7528\u4e8e\u6570\u636e\u6316\u6398\u548c\u6570\u636e\u5206\u6790\u3002\u5b83\u5185\u5efa\u591a\u79cd\u5206\u7c7b\u3001\u56de\u5f52\u3001\u805a\u7c7b\u7b97\u6cd5\uff0c\u5e76\u652f\u6301\u4e0ePython\u6570\u503c\u548c\u79d1\u5b66\u5e93Numpy\u53caScipy\u7684\u9ad8\u6548\u96c6\u6210\u3002\u53e6\u4e00\u65b9\u9762\uff0cTensorFlow\u548cPyTorch\u7b49\u6846\u67b6\u5219\u4e3b\u8981\u7528\u4e8e\u6df1\u5ea6\u5b66\u4e60\u4efb\u52a1\uff0c\u63d0\u4f9b\u4e86\u7075\u6d3b\u4e14\u5f3a\u5927\u7684\u8ba1\u7b97\u56fe\u8868\u53ca\u9ad8\u7ea7\u795e\u7ecf\u7f51\u7edc\u7b49\u529f\u80fd\uff0c\u4f7f\u5f97\u590d\u6742\u7684\u6a21\u578b\u53ef\u4ee5\u66f4\u4e3a\u7b80\u6613\u5730\u6784\u5efa\u4e0e\u8bad\u7ec3\u3002<\/p>\n<\/p>\n<p><h4>\u6570\u636e\u9884\u5904\u7406<\/h4>\n<\/p>\n<p><p>\u5728\u673a\u5668\u5b66\u4e60\u9879\u76ee\u4e2d\uff0c\u6570\u636e\u9884\u5904\u7406\u662f\u4e00\u4e2a\u4e0d\u53ef\u5ffd\u89c6\u7684\u6b65\u9aa4\u3002Python\u901a\u8fc7Pandas\u7b49\u5e93\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u6570\u636e\u5904\u7406\u548c\u5206\u6790\u80fd\u529b\uff0c\u80fd\u591f\u9ad8\u6548\u5730\u5904\u7406\u548c\u5206\u6790\u5404\u79cd\u7ed3\u6784\u7684\u6570\u636e\u3002Pandas\u63d0\u4f9b\u7684DataFrame\u7ed3\u6784\u975e\u5e38\u9002\u5408\u5904\u7406\u65f6\u95f4\u5e8f\u5217\u6570\u636e\u3001\u975e\u65f6\u95f4\u5e8f\u5217\u6570\u636e\u8868\u683c\u6570\u636e\u7b49\u3002\u6b64\u5916\uff0cMatplotlib\u548cSeaborn\u7b49\u5e93\u80fd\u591f\u63d0\u4f9b\u4e30\u5bcc\u7684\u6570\u636e\u53ef\u89c6\u5316\u65b9\u6cd5\uff0c\u5e2e\u52a9\u5f00\u53d1\u8005\u66f4\u597d\u5730\u7406\u89e3\u6570\u636e\u548c\u5206\u6790\u6a21\u578b\u7684\u6027\u80fd\u3002<\/p>\n<\/p>\n<p><h3>\u4e8c\u3001\u6613\u4e8e\u5b66\u4e60\u4e0e\u4f7f\u7528<\/h3>\n<\/p>\n<p><p>Python\u8bed\u8a00\u7b80\u6d01\u660e\u4e86\uff0c\u8bed\u6cd5\u63a5\u8fd1\u81ea\u7136\u8bed\u8a00\uff0c\u8fd9\u4f7f\u5f97\u5176\u6210\u4e3a\u521d\u5b66\u8005\u53cb\u597d\u7684\u7f16\u7a0b\u8bed\u8a00\u3002\u76f8\u8f83\u4e8eC++\u6216Java\uff0cPython\u7684\u5b66\u4e60\u66f2\u7ebf\u66f4\u4e3a\u5e73\u7f13\uff0c\u65b0\u624b\u4e5f\u80fd\u5728\u8f83\u77ed\u65f6\u95f4\u5185\u638c\u63e1\u3002\u8fd9\u4e00\u7279\u70b9\u4f7f\u5f97\u66f4\u591a\u975e\u4e13\u4e1a\u80cc\u666f\u7684\u4eba\u58eb\u80fd\u591f\u8fdb\u5165\u673a\u5668\u5b66\u4e60\u9886\u57df\uff0c\u62d3\u5bbd\u4e86\u673a\u5668\u5b66\u4e60\u7684\u5e94\u7528\u8303\u56f4\u3002<\/p>\n<\/p>\n<p><h4>\u6559\u80b2\u8d44\u6e90\u4e30\u5bcc<\/h4>\n<\/p>\n<p><p>\u968f\u7740Python\u5728\u673a\u5668\u5b66\u4e60\u9886\u57df\u7684\u666e\u53ca\uff0c\u4e92\u8054\u7f51\u4e0a\u51fa\u73b0\u4e86\u5927\u91cf\u7684\u5b66\u4e60\u8d44\u6e90\uff0c\u5305\u62ec\u5728\u7ebf\u8bfe\u7a0b\u3001\u6559\u7a0b\u3001\u4e66\u7c4d\u3001\u8bba\u575b\u7b49\u3002\u8fd9\u4e9b\u8d44\u6e90\u5927\u5927\u964d\u4f4e\u4e86\u5b66\u4e60\u95e8\u69db\uff0c\u4f7f\u5f97\u5373\u4f7f\u662f\u673a\u5668\u5b66\u4e60\u9886\u57df\u7684\u65b0\u624b\u4e5f\u80fd\u5feb\u901f\u5165\u95e8\u5e76\u9010\u6e10\u6df1\u5165\u3002\u66f4\u91cd\u8981\u7684\u662f\uff0cPython\u793e\u533a\u6d3b\u8dc3\uff0c\u9047\u5230\u95ee\u9898\u65f6\u5f80\u5f80\u80fd\u5728\u7f51\u7edc\u4e0a\u627e\u5230\u89e3\u7b54\u6216\u83b7\u5f97\u793e\u533a\u6210\u5458\u7684\u76f4\u63a5\u5e2e\u52a9\u3002<\/p>\n<\/p>\n<p><h3>\u4e09\u3001\u5f3a\u5927\u7684\u793e\u533a\u652f\u6301<\/h3>\n<\/p>\n<p><p>Python\u6709\u7740\u5f3a\u592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