{"id":1114,"date":"2023-07-27T14:58:19","date_gmt":"2023-07-27T14:58:19","guid":{"rendered":"https:\/\/statorials.org\/ko\/%e1%84%8b%e1%85%b2%e1%84%8f%e1%85%b3%e1%86%af%e1%84%85%e1%85%b5%e1%84%83%e1%85%b3-%e1%84%80%e1%85%a5%e1%84%85%e1%85%b5-%e1%84%91%e1%85%a1%e1%84%8b%e1%85%b5%e1%84%8a%e1%85%a5%e1%86%ab\/"},"modified":"2023-07-27T14:58:19","modified_gmt":"2023-07-27T14:58:19","slug":"%e1%84%8b%e1%85%b2%e1%84%8f%e1%85%b3%e1%86%af%e1%84%85%e1%85%b5%e1%84%83%e1%85%b3-%e1%84%80%e1%85%a5%e1%84%85%e1%85%b5-%e1%84%91%e1%85%a1%e1%84%8b%e1%85%b5%e1%84%8a%e1%85%a5%e1%86%ab","status":"publish","type":"post","link":"https:\/\/statorials.org\/ko\/%e1%84%8b%e1%85%b2%e1%84%8f%e1%85%b3%e1%86%af%e1%84%85%e1%85%b5%e1%84%83%e1%85%b3-%e1%84%80%e1%85%a5%e1%84%85%e1%85%b5-%e1%84%91%e1%85%a1%e1%84%8b%e1%85%b5%e1%84%8a%e1%85%a5%e1%86%ab\/","title":{"rendered":"Python\uc5d0\uc11c \uc720\ud074\ub9ac\ub4dc \uac70\ub9ac\ub97c \uacc4\uc0b0\ud558\ub294 \ubc29\ubc95(\uc608\uc81c \ud3ec\ud568)"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">\ub450 \ubca1\ud130 A\uc640 B \uc0ac\uc774\uc758 <strong>\uc720\ud074\ub9ac\ub4dc \uac70\ub9ac\ub294<\/strong> \ub2e4\uc74c\uacfc \uac19\uc774 \uacc4\uc0b0\ub429\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>\uc720\ud074\ub9ac\ub4dc \uac70\ub9ac = \u221a <span style=\"border-top: 1px solid black;\">\u03a3(A <sub>i<\/sub> -B <sub>i<\/sub> ) <sup>2<\/sup><\/span><\/strong><\/span><\/p>\n<p> <span style=\"color: #000000;\">Python\uc5d0\uc11c \ub450 \ubca1\ud130 \uc0ac\uc774\uc758 \uc720\ud074\ub9ac\ub4dc \uac70\ub9ac\ub97c \uacc4\uc0b0\ud558\ub824\uba74 <strong>numpy.linalg.norm<\/strong> \ud568\uc218\ub97c \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008000;\"><span style=\"color: #008080;\">#import functions<\/span>\nimport <span style=\"color: #000000;\">numpy<\/span> as <span style=\"color: #000000;\">np<\/span>\nfrom<\/span> numpy. <span style=\"color: #008000;\"><span style=\"color: #3366ff;\">linalg<\/span> import<\/span> norm\n\n<span style=\"color: #008080;\">#define two vectors\n<\/span>a = np.array([2, 6, 7, 7, 5, 13, 14, 17, 11, 8])\nb = np.array([3, 5, 5, 3, 7, 12, 13, 19, 22, 7])\n\n<span style=\"color: #008080;\">#calculate Euclidean distance between the two vectors<\/span> \nnorm(ab)\n\n12.409673645990857<\/strong>\n<\/pre>\n<p> <span style=\"color: #000000;\">\ub450 \ubca1\ud130 \uc0ac\uc774\uc758 \uc720\ud074\ub9ac\ub4dc \uac70\ub9ac\ub294 <strong>12.40967<\/strong> \uc785\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\ub450 \ubca1\ud130\uc758 \uae38\uc774\uac00 \uac19\uc9c0 \uc54a\uc73c\uba74 \uc774 \ud568\uc218\ub294 \uacbd\uace0 \uba54\uc2dc\uc9c0\ub97c \uc0dd\uc131\ud569\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008000;\"><span style=\"color: #008080;\">#import functions<\/span>\nimport <span style=\"color: #000000;\">numpy<\/span> as <span style=\"color: #000000;\">np<\/span>\nfrom<\/span> numpy. <span style=\"color: #008000;\"><span style=\"color: #3366ff;\">linalg<\/span> import<\/span> norm\n\n<span style=\"color: #008080;\">#define two vectors\n<\/span>a = np.array([2, 6, 7, 7, 5, 13, 14])\nb = np.array([3, 5, 5, 3, 7, 12, 13, 19, 22, 7])\n\n<span style=\"color: #008080;\">#calculate Euclidean distance between the two vectors<\/span> \nnorm(ab)\n\n<span style=\"color: #993300;\">ValueError<\/span> : operands could not be broadcast together with shapes (7,) (10,) \n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\uc774 \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\uc5ec Pandas DataFrame\uc758 \ub450 \uc5f4 \uc0ac\uc774\uc758 \uc720\ud074\ub9ac\ub4dc \uac70\ub9ac\ub97c \uacc4\uc0b0\ud560 \uc218\ub3c4 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008000;\"><span style=\"color: #008080;\">#import functions\n<\/span>import <span style=\"color: #000000;\">pandas<\/span> as <span style=\"color: #000000;\">pd<\/span> \nimport <span style=\"color: #000000;\">numpy<\/span> as <span style=\"color: #000000;\">np<\/span>\nfrom<\/span> numpy. <span style=\"color: #008000;\"><span style=\"color: #3366ff;\">linalg<\/span> import<\/span> norm\n\n<span style=\"color: #008080;\">#define DataFrame with three columns\n<\/span>df = pd.DataFrame({'points': [25, 12, 15, 14, 19, 23, 25, 29],\n                   'assists': [5, 7, 7, 9, 12, 9, 9, 4],\n                   'rebounds': [11, 8, 10, 6, 6, 5, 9, 12]})\n\n<span style=\"color: #008080;\">#calculate Euclidean distance between 'points' and 'assists'<\/span> \nnorm(df[' <span style=\"color: #008000;\">points<\/span> '] - df[' <span style=\"color: #008000;\">assists<\/span> '])\n\n40.496913462633174\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\ub450 \uc5f4 \uc0ac\uc774\uc758 \uc720\ud074\ub9ac\ub4dc \uac70\ub9ac\ub294 <strong>40.49691<\/strong> \uc785\ub2c8\ub2e4.<\/span><\/p>\n<h3> <strong><span style=\"color: #000000;\">\ucf54\uba58\ud2b8<\/span><\/strong><\/h3>\n<p> <span style=\"color: #000000;\"><strong>1.<\/strong> Python\uc5d0\uc11c \uc720\ud074\ub9ac\ub4dc \uac70\ub9ac\ub97c \uacc4\uc0b0\ud558\ub294 \ubc29\ubc95\uc740 \uc5ec\ub7ec \uac00\uc9c0\uac00 \uc788\uc9c0\ub9cc <a href=\"https:\/\/stackoverflow.com\/questions\/1401712\/how-can-the-euclidean-distance-be-calculated-with-numpy\" target=\"_blank\" rel=\"noopener noreferrer\">\uc774 Stack Overflow \uc2a4\ub808\ub4dc\uc5d0\uc11c \uc124\uba85\ud558\ub294<\/a> \uac83\ucc98\ub7fc \uc5ec\uae30\uc5d0 \uc124\uba85\ub41c \ubc29\ubc95\uc774 \uac00\uc7a5 \ube60\ub978 \uac83\uc73c\ub85c \ub098\ud0c0\ub0ac\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>2.<\/strong> <a href=\"https:\/\/numpy.org\/doc\/stable\/reference\/generated\/numpy.linalg.norm.html\" target=\"_blank\" rel=\"noopener noreferrer\">\uc5ec\uae30\uc5d0\uc11c<\/a> <strong>numpy.linalg.norm<\/strong> \ud568\uc218\uc5d0 \ub300\ud55c \uc804\uccb4 \ubb38\uc11c\ub97c \ucc3e\uc744 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> 3. \uc720\ud074\ub9ac\ub4dc \uac70\ub9ac\uc5d0 \ub300\ud574 \uc790\uc138\ud788 \uc54c\uc544\ubcf4\ub824\uba74 <a href=\"https:\/\/en.wikipedia.org\/wiki\/Euclidean_distance\" target=\"_blank\" rel=\"noopener noreferrer\">\uc774 Wikipedia \ud398\uc774\uc9c0\ub97c<\/a> <span style=\"color: #000000;\"><strong>\ucc38\uc870<\/strong> \ud558\uc138\uc694<\/span> <span style=\"color: #000000;\">.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\ub450 \ubca1\ud130 A\uc640 B \uc0ac\uc774\uc758 \uc720\ud074\ub9ac\ub4dc \uac70\ub9ac\ub294 \ub2e4\uc74c\uacfc \uac19\uc774 \uacc4\uc0b0\ub429\ub2c8\ub2e4. \uc720\ud074\ub9ac\ub4dc \uac70\ub9ac = \u221a \u03a3(A i -B i ) 2 Python\uc5d0\uc11c \ub450 \ubca1\ud130 \uc0ac\uc774\uc758 \uc720\ud074\ub9ac\ub4dc \uac70\ub9ac\ub97c \uacc4\uc0b0\ud558\ub824\uba74 numpy.linalg.norm \ud568\uc218\ub97c \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. #import functions import numpy as np from numpy. linalg import norm #define two vectors a = np.array([2, 6, 7, 7, 5, 13, 14, [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[20],"tags":[],"class_list":["post-1114","post","type-post","status-publish","format-standard","hentry","category-20"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - 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