{"id":3201,"date":"2023-07-18T17:14:14","date_gmt":"2023-07-18T17:14:14","guid":{"rendered":"https:\/\/statorials.org\/ko\/numpy-%e1%84%85%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5%e1%86%b7-%e1%84%92%e1%85%a2%e1%86%bc%e1%84%85%e1%85%a7%e1%86%af\/"},"modified":"2023-07-18T17:14:14","modified_gmt":"2023-07-18T17:14:14","slug":"numpy-%e1%84%85%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5%e1%86%b7-%e1%84%92%e1%85%a2%e1%86%bc%e1%84%85%e1%85%a7%e1%86%af","status":"publish","type":"post","link":"https:\/\/statorials.org\/ko\/numpy-%e1%84%85%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5%e1%86%b7-%e1%84%92%e1%85%a2%e1%86%bc%e1%84%85%e1%85%a7%e1%86%af\/","title":{"rendered":"\ub09c\uc218\ub85c numpy \ud589\ub82c\uc744 \ub9cc\ub4dc\ub294 \ubc29\ubc95"},"content":{"rendered":"

<\/p>\n

\n

\ub2e4\uc74c \ubc29\ubc95\uc744 \uc0ac\uc6a9\ud558\uc5ec \ub09c\uc218\ub85c NumPy \ud589\ub82c\uc744 \ub9cc\ub4e4 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n

\ubc29\ubc95 1: \uc784\uc758\uc758 \uc815\uc218\ub85c \uad6c\uc131\ub41c NumPy \ud589\ub82c \ub9cc\ub4e4\uae30<\/strong><\/span><\/p>\n

 n.p. random<\/span> . randint<\/span> (low, high, (rows, columns))\n<\/strong><\/pre>\n
 \ubc29\ubc95 2: \ubb34\uc791\uc704 \ubd80\ub3d9 \uc18c\uc218\uc810\uc758 NumPy \ud589\ub82c \ub9cc\ub4e4\uae30<\/strong><\/span><\/p>\n
 n.p. random<\/span> . rand<\/span> (rows, columns)<\/strong><\/pre>\n
 \ub2e4\uc74c \uc608\uc5d0\uc11c\ub294 \uac01 \ubc29\ubc95\uc744 \uc2e4\uc81c\ub85c \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n
 \uc608\uc81c 1: \uc784\uc758\uc758 \uc815\uc218\ub85c \uad6c\uc131\ub41c NumPy \ud589\ub82c \ub9cc\ub4e4\uae30<\/strong><\/span><\/h3>\n
 \ub2e4\uc74c \ucf54\ub4dc\ub294 7\ud589<\/strong> 2\uc5f4<\/strong> \ubaa8\uc591\uc73c\ub85c 0<\/strong> \ubd80\ud130 20<\/strong> \uae4c\uc9c0\uc758 \uc784\uc758 \uac12\uc73c\ub85c \uad6c\uc131\ub41c NumPy \ud589\ub82c\uc744 \ub9cc\ub4dc\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n
 import<\/span> numpy as<\/span> np\n\n#create NumPy matrix of random integers\n<\/span>n.p. random<\/span> . randint<\/span> (0, 20, (7, 2))\n\narray([[ 3, 7],\n       [17, 10],\n       [0, 10],\n       [13, 16],\n       [6, 14],\n       [8, 7],\n       [9, 15]])<\/span><\/span><\/strong><\/pre>\n
 \ud589\ub82c\uc758 \uac01 \uac12\uc740 0\uc5d0\uc11c 20 \uc0ac\uc774\uc774\uba70 \ud589\ub82c\uc758 \ucd5c\uc885 \ud615\ud0dc\ub294 7\ud589 2\uc5f4\uc774\ub77c\ub294 \uc810\uc5d0 \uc720\uc758\ud558\uc138\uc694.<\/span><\/p>\n
 \uc608\uc81c 2:<\/strong><\/span> \ubb34\uc791\uc704 \ubd80\ub3d9 \uc18c\uc218\uc810\uc758 NumPy \ud589\ub82c \ub9cc\ub4e4\uae30<\/strong><\/h3>\n
 \ub2e4\uc74c \ucf54\ub4dc\ub294 0<\/strong> \uacfc 1<\/strong> \uc0ac\uc774\uc758 \uc784\uc758\uc758 \ubd80\ub3d9 \uc18c\uc218\uc810 \uac12\uacfc 7\uac1c\uc758<\/strong> \uc5f4\uacfc 2\uac1c\uc758<\/strong> \ud589\uc758 \ubaa8\uc591\uc744 \uac00\uc9c4 NumPy \ud589\ub82c\uc744 \ub9cc\ub4dc\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n
 import<\/span> numpy as<\/span> np\n\n#create NumPy matrix of random floats\n<\/span>n.p. random<\/span> . rand<\/span> (7, 2)\n\narray([[0.64987774, 0.60099292],\n       [0.13626106, 0.1859029 ],\n       [0.77007972, 0.65179164],\n       [0.33524707, 0.46201819],\n       [0.1683, 0.72960909],\n       [0.76117417, 0.37212974],\n       [0.18879731, 0.65723325]])\n<\/span><\/span><\/strong><\/pre>\n
 \uadf8 \uacb0\uacfc\ub294 7\ud589 2\uc5f4 \ud615\ud0dc\uc758 0\uacfc 1 \uc0ac\uc774\uc758 \uc784\uc758\uc758 \ubd80\ub3d9 \uc18c\uc218\uc810 \uac12\uc744 \ud3ec\ud568\ud558\ub294 NumPy \ud589\ub82c\uc785\ub2c8\ub2e4.<\/span><\/p>\n
 NumPy round()<\/strong> \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\uc5ec \uac01 \ubd80\ub3d9\uc18c\uc218\uc810\uc744 \ud2b9\uc815 \uc18c\uc218 \uc790\ub9bf\uc218\ub85c \ubc18\uc62c\ub9bc\ud560 \uc218\ub3c4 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 \uc608\ub97c \ub4e4\uc5b4, \ub2e4\uc74c \ucf54\ub4dc\ub294 \uac01\uac01 \uc18c\uc218\uc810 \uc774\ud558 2\uc790\ub9ac\ub85c \ubc18\uc62c\ub9bc\ub41c \uc784\uc758 \ubd80\ub3d9 \uc18c\uc218\uc810\uc758 NumPy \ud589\ub82c\uc744 \ub9cc\ub4dc\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n
 import<\/span> numpy as<\/span> np\n\n#create NumPy matrix of random floats rounded to 2 decimal places\n<\/span>n.p. round<\/span> (np. random<\/span> . rand<\/span> (5, 2), 2)\n\narray([[0.37, 0.63],\n       [0.51, 0.68],\n       [0.23, 0.98],\n       [0.62, 0.46],\n       [0.02, 0.94]])\n<\/span><\/span><\/strong><\/pre>\n
 \ucc38\uace0<\/strong> : NumPy rand()<\/strong> \ud568\uc218\uc5d0 \ub300\ud55c \uc804\uccb4 \ubb38\uc11c\ub294 \uc5ec\uae30\uc5d0\uc11c<\/a> \ucc3e\uc744 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 \ucd94\uac00 \ub9ac\uc18c\uc2a4<\/strong><\/span><\/h3>\n
 \ub2e4\uc74c \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 Python\uc5d0\uc11c \ub2e4\ub978 \uc77c\ubc18\uc801\uc778 \ubcc0\ud658\uc744 \uc218\ud589\ud558\ub294 \ubc29\ubc95\uc744 \uc124\uba85\ud569\ub2c8\ub2e4.<\/span><\/p>\n
 Pandas DataFrame \uc5f4\uc744 \ubb38\uc790\uc5f4\ub85c \ubcc0\ud658\ud558\ub294 \ubc29\ubc95<\/a>
 Pandas\uc5d0\uc11c \ud0c0\uc784\uc2a4\ud0ec\ud504\ub97c \ub0a0\uc9dc\/\uc2dc\uac04\uc73c\ub85c \ubcc0\ud658\ud558\ub294 \ubc29\ubc95<\/a>
 Pandas\uc5d0\uc11c DateTime\uc744 \ub0a0\uc9dc\ub85c \ubcc0\ud658\ud558\ub294 \ubc29\ubc95<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
\ub2e4\uc74c \ubc29\ubc95\uc744 \uc0ac\uc6a9\ud558\uc5ec \ub09c\uc218\ub85c NumPy \ud589\ub82c\uc744 \ub9cc\ub4e4 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ubc29\ubc95 1: \uc784\uc758\uc758 \uc815\uc218\ub85c \uad6c\uc131\ub41c NumPy \ud589\ub82c \ub9cc\ub4e4\uae30 n.p. random . randint (low, high, (rows, columns)) \ubc29\ubc95 2: \ubb34\uc791\uc704 \ubd80\ub3d9 \uc18c\uc218\uc810\uc758 NumPy \ud589\ub82c \ub9cc\ub4e4\uae30 n.p. random . rand (rows, columns) \ub2e4\uc74c \uc608\uc5d0\uc11c\ub294 \uac01 \ubc29\ubc95\uc744 \uc2e4\uc81c\ub85c \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4. \uc608\uc81c 1: \uc784\uc758\uc758 \uc815\uc218\ub85c \uad6c\uc131\ub41c NumPy \ud589\ub82c \ub9cc\ub4e4\uae30 […]<\/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-3201","post","type-post","status-publish","format-standard","hentry","category-20"],"yoast_head":"\n\ub09c\uc218\ub97c \uc0ac\uc6a9\ud558\uc5ec NumPy \ud589\ub82c\uc744 \ub9cc\ub4dc\ub294 \ubc29\ubc95 - \ud1b5\uacc4\ud559<\/title>\n<meta name=\"description\" content=\"\uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 NumPy\ub97c \uc0ac\uc6a9\ud558\uc5ec \ub09c\uc218\ub85c \ud589\ub82c\uc744 \ub9cc\ub4dc\ub294 \ubc29\ubc95\uc744 \uc608\uc81c\uc640 \ud568\uaed8 \uc124\uba85\ud569\ub2c8\ub2e4.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/statorials.org\/ko\/numpy-\u1105\u1162\u11ab\u1103\u1165\u11b7-\u1112\u1162\u11bc\u1105\u1167\u11af\/\" \/>\n<meta property=\"og:locale\" content=\"ko_KR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"\ub09c\uc218\ub97c \uc0ac\uc6a9\ud558\uc5ec NumPy \ud589\ub82c\uc744 \ub9cc\ub4dc\ub294 \ubc29\ubc95 - \ud1b5\uacc4\ud559\" \/>\n<meta property=\"og:description\" content=\"\uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 NumPy\ub97c \uc0ac\uc6a9\ud558\uc5ec \ub09c\uc218\ub85c \ud589\ub82c\uc744 \ub9cc\ub4dc\ub294 \ubc29\ubc95\uc744 \uc608\uc81c\uc640 \ud568\uaed8 \uc124\uba85\ud569\ub2c8\ub2e4.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/statorials.org\/ko\/numpy-\u1105\u1162\u11ab\u1103\u1165\u11b7-\u1112\u1162\u11bc\u1105\u1167\u11af\/\" \/>\n<meta property=\"og:site_name\" content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-18T17:14:14+00:00\" \/>\n<meta name=\"author\" content=\"\ubca4\uc790\ubbfc \uc564\ub354\uc2a8\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"\ubca4\uc790\ubbfc \uc564\ub354\uc2a8\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/statorials.org\/ko\/numpy-%e1%84%85%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5%e1%86%b7-%e1%84%92%e1%85%a2%e1%86%bc%e1%84%85%e1%85%a7%e1%86%af\/\",\"url\":\"https:\/\/statorials.org\/ko\/numpy-%e1%84%85%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5%e1%86%b7-%e1%84%92%e1%85%a2%e1%86%bc%e1%84%85%e1%85%a7%e1%86%af\/\",\"name\":\"\ub09c\uc218\ub97c \uc0ac\uc6a9\ud558\uc5ec NumPy \ud589\ub82c\uc744 \ub9cc\ub4dc\ub294 \ubc29\ubc95 - 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