{"id":4027,"date":"2023-07-14T02:31:52","date_gmt":"2023-07-14T02:31:52","guid":{"rendered":"https:\/\/statorials.org\/cn\/%e6%9c%80%e5%b8%b8%e8%a7%81%e7%9a%84%e5%80%bc-numpy\/"},"modified":"2023-07-14T02:31:52","modified_gmt":"2023-07-14T02:31:52","slug":"%e6%9c%80%e5%b8%b8%e8%a7%81%e7%9a%84%e5%80%bc-numpy","status":"publish","type":"post","link":"https:\/\/statorials.org\/cn\/%e6%9c%80%e5%b8%b8%e8%a7%81%e7%9a%84%e5%80%bc-numpy\/","title":{"rendered":"\u5982\u4f55\u67e5\u627e numpy \u6570\u7ec4\u4e2d\u6700\u5e38\u89c1\u7684\u503c\uff08\u9644\u793a\u4f8b\uff09"},"content":{"rendered":"

<\/p>\n

\n

\u60a8\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u65b9\u6cd5\u67e5\u627e NumPy \u6570\u7ec4\u4e2d\u51fa\u73b0\u9891\u7387\u6700\u9ad8\u7684\u503c\uff1a<\/span><\/p>\n

\u65b9\u6cd5 1\uff1a\u67e5\u627e\u51fa\u73b0\u6b21\u6570\u6700\u591a\u7684\u503c<\/strong><\/span><\/p>\n

 #find frequency of each value\n<\/span>values, counts = np. unique<\/span> (my_array, return_counts= True<\/span> )\n\n#display value with highest frequency\n<\/span>values[counts. argmax<\/span> ()]\n<\/strong><\/span><\/pre>\n
\u5982\u679c NumPy \u6570\u7ec4\u4e2d\u51fa\u73b0\u6700\u9891\u7e41\u7684\u591a\u4e2a\u503c\uff0c\u5219\u6b64\u65b9\u6cd5\u5c06\u4ec5\u8fd4\u56de\u7b2c\u4e00\u4e2a\u503c\u3002<\/span><\/p>\n
\u65b9\u6cd5 2\uff1a\u67e5\u627e\u6bcf\u4e2a\u6700\u9891\u7e41\u7684\u503c<\/strong><\/span><\/p>\n
 #find frequency of each value\n<\/span>values, counts = np. unique<\/span> (my_array, return_counts= True<\/span> )\n\n#display all values with highest frequencies\n<\/span>values[counts ==<\/span> counts. max<\/span> ()]\n<\/strong><\/span><\/pre>\n
\u5982\u679c NumPy \u6570\u7ec4\u4e2d\u51fa\u73b0\u6700\u9891\u7e41\u7684\u591a\u4e2a\u503c\uff0c\u6b64\u65b9\u6cd5\u5c06\u8fd4\u56de\u6bcf\u4e2a\u6700\u9891\u7e41\u7684\u503c\u3002<\/span><\/p>\n
\u4ee5\u4e0b\u793a\u4f8b\u5c55\u793a\u4e86\u5982\u4f55\u5728\u5b9e\u8df5\u4e2d\u4f7f\u7528\u6bcf\u79cd\u65b9\u6cd5\u3002<\/span><\/p>\n
\u793a\u4f8b 1\uff1a\u67e5\u627e NumPy \u6570\u7ec4\u4e2d\u51fa\u73b0\u6b21\u6570\u6700\u591a\u7684\u503c<\/span><\/strong><\/h2>\n
\u5047\u8bbe\u6211\u4eec\u6709\u4ee5\u4e0b NumPy \u6570\u7ec4\uff1a<\/span><\/p>\n
 import<\/span> numpy as<\/span> np\n\n#create NumPy array\n<\/span>my_array = np. array<\/span> ([1, 2, 4, 4, 4, 5, 6, 7, 12])\n<\/strong><\/span><\/pre>\n
\u8bf7\u6ce8\u610f\uff0c\u6b64\u8868\u4e2d\u53ea\u6709\u4e00\u4e2a\u51fa\u73b0\u9891\u7387\u6700\u9ad8\u7684\u503c\uff1a 4<\/strong> \u3002<\/span><\/span><\/p>\n
\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528argmax()<\/strong>\u51fd\u6570\u8fd4\u56de\u6570\u7ec4\u4e2d\u51fa\u73b0\u6b21\u6570\u6700\u591a\u7684\u503c\uff1a<\/span><\/p>\n
 #find frequency of each value\n<\/span>values, counts = np. unique<\/span> (my_array, return_counts= True<\/span> )\n\n#display value with highest frequency\n<\/span>values[counts. argmax<\/span> ()]\n\n4<\/strong><\/span><\/pre>\n
\u8be5\u51fd\u6570\u6b63\u786e\u8fd4\u56de\u503c4<\/strong> \u3002<\/span><\/span><\/p>\n
\u793a\u4f8b 2\uff1a\u67e5\u627e NumPy \u6570\u7ec4\u4e2d\u6bcf\u4e2a\u6700\u5e38\u89c1\u7684\u503c<\/span><\/strong><\/h2>\n
\u5047\u8bbe\u6211\u4eec\u6709\u4ee5\u4e0b NumPy \u6570\u7ec4\uff1a<\/span><\/p>\n
 import<\/span> numpy as<\/span> np\n\n#create NumPy array\n<\/span>my_array = np. array<\/span> ([1, 2, 4, 4, 4, 5, 6, 7, 12, 12, 12])\n<\/strong><\/span><\/pre>\n
\u8bf7\u6ce8\u610f\uff0c\u6b64\u8868\u4e2d\u51fa\u73b0\u6700\u9891\u7e41\u7684\u6709\u4e24\u4e2a\u503c\uff1a 4<\/strong>\u548c12<\/strong> \u3002<\/span><\/p>\n
\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528max()<\/strong>\u51fd\u6570\u8fd4\u56de\u6570\u7ec4\u4e2d\u51fa\u73b0\u6b21\u6570\u6700\u591a\u7684\u6bcf\u4e2a\u503c\uff1a<\/span><\/p>\n
 #find frequency of each value\n<\/span>values, counts = np. unique<\/span> (my_array, return_counts= True<\/span> )\n\n#display each value with highest frequency\n<\/span>values[counts ==<\/span> counts. max<\/span> ()]\n\narray([4,12])\n<\/strong><\/span><\/pre>\n
\u8be5\u51fd\u6570\u6b63\u786e\u8fd4\u56de\u503c4<\/strong>\u548c12<\/strong> \u3002<\/span><\/p>\n
\u6ce8\u610f<\/strong>\uff1a\u60a8\u53ef\u4ee5\u5728\u6b64\u5904<\/a>\u627e\u5230 NumPy unique()<\/strong>\u51fd\u6570\u7684\u5b8c\u6574\u6587\u6863\u3002<\/span><\/p>\n
\u5176\u4ed6\u8d44\u6e90<\/strong><\/span><\/h2>\n
\u4ee5\u4e0b\u6559\u7a0b\u89e3\u91ca\u4e86\u5982\u4f55\u5728 NumPy \u4e2d\u6267\u884c\u5176\u4ed6\u5e38\u89c1\u4efb\u52a1\uff1a<\/span><\/p>\n
\u5982\u4f55\u5220\u9664 NumPy \u6570\u7ec4\u4e2d\u7684\u91cd\u590d\u5143\u7d20<\/a>
\u5982\u4f55\u66ff\u6362 NumPy \u6570\u7ec4\u4e2d\u7684\u5143\u7d20<\/a>
\u5982\u4f55\u5bf9 NumPy \u6570\u7ec4\u4e2d\u7684\u5143\u7d20\u8fdb\u884c\u6392\u5e8f<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
\u60a8\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u65b9\u6cd5\u67e5\u627e NumPy \u6570\u7ec4\u4e2d\u51fa\u73b0\u9891\u7387\u6700\u9ad8\u7684\u503c\uff1a \u65b9\u6cd5 1\uff1a\u67e5\u627e\u51fa\u73b0\u6b21\u6570\u6700\u591a\u7684\u503c #find fr […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11],"tags":[],"class_list":["post-4027","post","type-post","status-publish","format-standard","hentry","category-11"],"yoast_head":"\n\u5982\u4f55\u67e5\u627e NumPy \u6570\u7ec4\u4e2d\u51fa\u73b0\u6b21\u6570\u6700\u591a\u7684\u503c\uff08\u9644\u793a\u4f8b\uff09 \u2013 Statorials<\/title>\n<meta name=\"description\" content=\"\u672c\u6559\u7a0b\u901a\u8fc7\u51e0\u4e2a\u793a\u4f8b\u89e3\u91ca\u4e86\u5982\u4f55\u67e5\u627e NumPy \u6570\u7ec4\u4e2d\u6700\u5e38\u89c1\u7684\u503c\u3002\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, 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