{"id":983,"date":"2023-07-28T02:28:10","date_gmt":"2023-07-28T02:28:10","guid":{"rendered":"https:\/\/statorials.org\/ko\/%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5-%e1%84%83%e1%85%a6%e1%84%8b%e1%85%b5%e1%84%90%e1%85%a5-%e1%84%91%e1%85%b3%e1%84%85%e1%85%a6%e1%84%8b%e1%85%b5%e1%86%b7-%e1%84%8b%e1%85%a7%e1%86%af-2\/"},"modified":"2023-07-28T02:28:10","modified_gmt":"2023-07-28T02:28:10","slug":"%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5-%e1%84%83%e1%85%a6%e1%84%8b%e1%85%b5%e1%84%90%e1%85%a5-%e1%84%91%e1%85%b3%e1%84%85%e1%85%a6%e1%84%8b%e1%85%b5%e1%86%b7-%e1%84%8b%e1%85%a7%e1%86%af-2","status":"publish","type":"post","link":"https:\/\/statorials.org\/ko\/%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5-%e1%84%83%e1%85%a6%e1%84%8b%e1%85%b5%e1%84%90%e1%85%a5-%e1%84%91%e1%85%b3%e1%84%85%e1%85%a6%e1%84%8b%e1%85%b5%e1%86%b7-%e1%84%8b%e1%85%a7%e1%86%af-2\/","title":{"rendered":"Pandas dataframe\uc758 \uc5f4\uc744 \uc815\uaddc\ud654\ud558\ub294 \ubc29\ubc95"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">\uc885\uc885 Pandas DataFrame\uc5d0 \uc788\ub294 \ud558\ub098 \uc774\uc0c1\uc758 \uc5f4\uc758 \ub370\uc774\ud130 \uac12\uc744 <strong>\uc815\uaddc\ud654<\/strong> \ud558\ub824\ub294 \uacbd\uc6b0\uac00 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 \uc774\ub97c \uc218\ud589\ud558\ub294 \ub450 \uac00\uc9c0 \ubc29\ubc95\uc744 \uc124\uba85\ud569\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>1. \ucd5c\uc18c-\ucd5c\ub300 \uc815\uaddc\ud654<\/strong><\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><b>\ubaa9\uc801:<\/b> \uac01 \ub370\uc774\ud130 \uac12\uc744 0\uacfc 1 \uc0ac\uc774\uc758 \uac12\uc73c\ub85c \ubcc0\ud658\ud569\ub2c8\ub2e4.<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>\uacf5\uc2dd:<\/strong> \uc0c8 \uac12 = (\uac12 \u2013 \ucd5c\uc18c) \/ (\ucd5c\ub300 \u2013 \ucd5c\uc18c)<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\"><strong>2. \ud3c9\uade0 \uc815\uaddc\ud654<\/strong><\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><b>\ubaa9\uc801:<\/b> \ubaa8\ub4e0 \uac12\uc758 \ud3c9\uade0\uc774 0\uacfc std\uac00 \ub418\ub3c4\ub85d \uac12\uc744 \uc870\uc815\ud569\ub2c8\ub2e4. \uac1c\ubc1c\uc790 1\uc785\ub2c8\ub2e4.<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>\uacf5\uc2dd:<\/strong> \uc0c8 \uac12 = (\uac12 \u2013 \ud3c9\uade0) \/ (\ud45c\uc900 \ud3b8\ucc28)<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">Pandas DataFrame\uc5d0\uc11c \uac01 \uba54\uc11c\ub4dc\ub97c \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95\uc758 \uc608\ub97c \uc0b4\ud3b4\ubcf4\uaca0\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>\uc608\uc2dc 1: \ucd5c\uc18c-\ucd5c\ub300 \uc815\uaddc\ud654<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c\uacfc \uac19\uc740 \ud32c\ub354 DataFrame\uc774 \uc788\ub2e4\uace0 \uac00\uc815\ud569\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #107d3f;\">import<\/span> pandas <span style=\"color: #107d3f;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#createDataFrame<\/span>\ndf = pd.DataFrame({'points': [25, 12, 15, 14, 19],\n                   'assists': [5, 7, 7, 9, 12],\n                   'rebounds': [11, 8, 10, 6, 6]}) \n\n<span style=\"color: #008080;\">#view DataFrame\n<\/span><span style=\"color: #993300;\">print<\/span> (df)\n\n   points assists rebounds\n0 25 5 11\n1 12 7 8\n2 15 7 10\n3 14 9 6\n4 19 12 6\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \ucf54\ub4dc\ub97c \uc0ac\uc6a9\ud558\uc5ec DataFrame\uc758 \uac01 \uc5f4\uc5d0 \ucd5c\uc18c-\ucd5c\ub300 \uc815\uaddc\ud654\ub97c \uc801\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>(df-df. <span style=\"color: #3366ff;\">min<\/span> ())\/(df. <span style=\"color: #3366ff;\">max<\/span> ()-df. <span style=\"color: #3366ff;\">min<\/span> ())\n\n        points assists rebounds\n0 1.000000 0.000000 1.0\n1 0.000000 0.285714 0.4\n2 0.230769 0.285714 0.8\n3 0.153846 0.571429 0.0\n4 0.538462 1.000000 0.0\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\uc774\uc81c \uac01 \uc5f4\uc758 \ucd5c\ub300\uac12\uc740 <strong>1<\/strong> \uc774\uace0 \uac01 \uc5f4\uc758 \ucd5c\uc18c\uac12\uc740 <strong>0<\/strong> \uc774\uba70 \ub2e4\ub978 \ubaa8\ub4e0 \uac12\uc740 0\uacfc 1 \uc0ac\uc774\uc785\ub2c8\ub2e4.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>\uc608\uc2dc 2: \ud3c9\uade0 \uc815\uaddc\ud654<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c\uacfc \uac19\uc740 pandas DataFrame\uc774 \uc788\ub2e4\uace0 \ub2e4\uc2dc \uac00\uc815\ud574 \ubcf4\uaca0\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #107d3f;\">import<\/span> pandas <span style=\"color: #107d3f;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#createDataFrame<\/span>\ndf = pd.DataFrame({'points': [25, 12, 15, 14, 19],\n                   'assists': [5, 7, 7, 9, 12],\n                   'rebounds': [11, 8, 10, 6, 6]}) \n\n<span style=\"color: #008080;\">#view DataFrame\n<\/span><span style=\"color: #993300;\">print<\/span> (df)\n\n   points assists rebounds\n0 25 5 11\n1 12 7 8\n2 15 7 10\n3 14 9 6\n4 19 12 6\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \ucf54\ub4dc\ub97c \uc0ac\uc6a9\ud558\uc5ec DataFrame\uc758 \uac01 \uc5f4\uc5d0 \ud3c9\uade0 \uc815\uaddc\ud654\ub97c \uc801\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>(df- <span style=\"color: #3366ff;\">df.mean<\/span> ())\/df. <span style=\"color: #3366ff;\">std<\/span> ()\n\n        points assists rebounds\n0 1.554057 -1.133893 1.227881\n1 -0.971286 -0.377964 -0.087706\n2 -0.388514 -0.377964 0.789352\n3 -0.582772 0.377964 -0.964764\n4 0.388514 1.511858 -0.964764\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\uc774\uc81c \uac01 \uc5f4 \uac12\uc758 \ud3c9\uade0\uc774 0, \uac01 \uc5f4 \uac12\uc758 \ud45c\uc900\ud3b8\ucc28\uac00 1\uc774 \ub418\ub3c4\ub85d \uc815\uaddc\ud654\ub418\uc5c8\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\ud2b9\uc815 \ub370\uc774\ud130 \ud3ec\uc778\ud2b8\uc758 \uc815\uaddc\ud654\ub41c \uac12\uc774 0\ubcf4\ub2e4 \ud070 \uacbd\uc6b0 \uc774\ub294 \ud574\ub2f9 \ub370\uc774\ud130 \ud3ec\uc778\ud2b8\uac00 \ud574\ub2f9 \uc5f4\uc758 \ud3c9\uade0\ubcf4\ub2e4 \ud06c\ub2e4\ub294 \uac83\uc744 \ub098\ud0c0\ub0c5\ub2c8\ub2e4. \ubc18\ub300\ub85c, 0\ubcf4\ub2e4 \uc791\uc740 \uc815\uaddc\ud654\ub41c \uac12\uc740 \ub370\uc774\ud130 \ud3ec\uc778\ud2b8\uac00 \ud574\ub2f9 \uc5f4\uc758 \ud3c9\uade0\ubcf4\ub2e4 \uc544\ub798\uc5d0 \uc788\uc74c\uc744 \ub098\ud0c0\ub0c5\ub2c8\ub2e4.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>\ucd94\uac00 \ub9ac\uc18c\uc2a4<\/strong><\/span><\/h3>\n<p> <a href=\"https:\/\/statorials.org\/ko\/pandas-groupby\u1102\u1173\u11ab-\u110b\u1167\u1105\u1165-\u110b\u1167\u11af\u110b\u1173\u11af-\u110c\u1175\u11b8\u1100\u1168\u1112\u1161\u11b8\u1102\u1175\u1103\u1161.\/\" target=\"_blank\" rel=\"noopener noreferrer\">Pandas: \uc5ec\ub7ec \uc5f4\uc744 \uadf8\ub8f9\ud654\ud558\uace0 \uc9d1\uacc4\ud558\ub294 \ubc29\ubc95<\/a><br \/> <a href=\"https:\/\/statorials.org\/ko\/\u1111\u1162\u11ab\u1103\u1165\u1102\u1173\u11ab-\u110b\u1167\u1105\u1165-\u110c\u1169\u1100\u1165\u11ab\u110b\u1173\u11af-\u1111\u1175\u11af\u1110\u1165\u1105\u1175\u11bc\u1112\u1161\u11b8\u1102\u1175\u1103\u1161.\/\" target=\"_blank\" rel=\"noopener noreferrer\">\uc5ec\ub7ec \uc870\uac74\uc5d0\uc11c Pandas DataFrame\uc744 \ud544\ud130\ub9c1\ud558\ub294 \ubc29\ubc95<\/a><br \/> <a href=\"https:\/\/statorials.org\/ko\/\u1111\u1162\u11ab\u1103\u1165\u1102\u1173\u11ab-\u1102\u116e\u1105\u1161\u11a8\u1103\u116c\u11ab-\u1100\u1161\u11b9\u110b\u1173\u11af-\u1100\u1168\u1109\u1161\u11ab\u1112\u1161\u11b8\u1102\u1175\u1103\u1161\/\" target=\"_blank\" rel=\"noopener noreferrer\">Pandas DataFrame\uc5d0\uc11c \ub204\ub77d\ub41c \uac12\uc744 \uacc4\uc0b0\ud558\ub294 \ubc29\ubc95<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\uc885\uc885 Pandas DataFrame\uc5d0 \uc788\ub294 \ud558\ub098 \uc774\uc0c1\uc758 \uc5f4\uc758 \ub370\uc774\ud130 \uac12\uc744 \uc815\uaddc\ud654 \ud558\ub824\ub294 \uacbd\uc6b0\uac00 \uc788\uc2b5\ub2c8\ub2e4. \uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 \uc774\ub97c \uc218\ud589\ud558\ub294 \ub450 \uac00\uc9c0 \ubc29\ubc95\uc744 \uc124\uba85\ud569\ub2c8\ub2e4. 1. \ucd5c\uc18c-\ucd5c\ub300 \uc815\uaddc\ud654 \ubaa9\uc801: \uac01 \ub370\uc774\ud130 \uac12\uc744 0\uacfc 1 \uc0ac\uc774\uc758 \uac12\uc73c\ub85c \ubcc0\ud658\ud569\ub2c8\ub2e4. \uacf5\uc2dd: \uc0c8 \uac12 = (\uac12 \u2013 \ucd5c\uc18c) \/ (\ucd5c\ub300 \u2013 \ucd5c\uc18c) 2. \ud3c9\uade0 \uc815\uaddc\ud654 \ubaa9\uc801: \ubaa8\ub4e0 \uac12\uc758 \ud3c9\uade0\uc774 0\uacfc std\uac00 \ub418\ub3c4\ub85d \uac12\uc744 [&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-983","post","type-post","status-publish","format-standard","hentry","category-20"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Pandas DataFrame\uc758 \uc5f4\uc744 \uc815\uaddc\ud654\ud558\ub294 \ubc29\ubc95 \u2013 Statorials<\/title>\n<meta name=\"description\" content=\"\uc608\uc81c\ub97c \ud3ec\ud568\ud558\uc5ec Pandas DataFrame\uc758 \uc5f4\uc744 \uc815\uaddc\ud654\ud558\ub294 \ubc29\ubc95\uc5d0 \ub300\ud55c \uac04\ub2e8\ud55c 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