{"id":4243,"date":"2023-07-12T13:59:04","date_gmt":"2023-07-12T13:59:04","guid":{"rendered":"https:\/\/statorials.org\/ko\/%e1%84%80%e1%85%b5%e1%86%af%e1%84%8b%e1%85%b5%e1%84%80%e1%85%a1-%e1%84%83%e1%85%a1%e1%84%85%e1%85%b3%e1%86%ab-dict%e1%84%8b%e1%85%b4-%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5-%e1%84%83%e1%85%a6\/"},"modified":"2023-07-12T13:59:04","modified_gmt":"2023-07-12T13:59:04","slug":"%e1%84%80%e1%85%b5%e1%86%af%e1%84%8b%e1%85%b5%e1%84%80%e1%85%a1-%e1%84%83%e1%85%a1%e1%84%85%e1%85%b3%e1%86%ab-dict%e1%84%8b%e1%85%b4-%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5-%e1%84%83%e1%85%a6","status":"publish","type":"post","link":"https:\/\/statorials.org\/ko\/%e1%84%80%e1%85%b5%e1%86%af%e1%84%8b%e1%85%b5%e1%84%80%e1%85%a1-%e1%84%83%e1%85%a1%e1%84%85%e1%85%b3%e1%86%ab-dict%e1%84%8b%e1%85%b4-%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5-%e1%84%83%e1%85%a6\/","title":{"rendered":"Pandas: \uae38\uc774\uac00 \ub2e4\ub978 dict\uc5d0\uc11c dataframe \ub9cc\ub4e4\uae30"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">\ub2e4\uc74c \uae30\ubcf8 \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\uc5ec \ud56d\ubaa9 \uae38\uc774\uac00 \ub2e4\ub978 \uc0ac\uc804\uc5d0\uc11c pandas DataFrame\uc744 \ub9cc\ub4e4 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008000;\">import<\/span> pandas <span style=\"color: #008000;\">as<\/span> pd\n\ndf = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> (dict([(key, pd. <span style=\"color: #3366ff;\">Series<\/span> (value)) <span style=\"color: #008000;\">for<\/span> key, value <span style=\"color: #008000;\">in<\/span> some_dict. <span style=\"color: #3366ff;\">items<\/span> ()]))\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\uc774 \uad6c\ubb38\uc740 \uc0ac\uc804 \ubc30\uc5f4 \ubaa9\ub85d\uc744 Pandas \uc2dc\ub9ac\uc988 \ubaa9\ub85d\uc73c\ub85c \ubcc0\ud658\ud569\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uc774\ub97c \ud1b5\ud574 \uc6b0\ub9ac\ub294 pandas DataFrame\uc744 \uc0dd\uc131\ud558\uace0 NaN \uac12\uc744 \uc785\ub825\ud558\uc5ec \uacb0\uacfc DataFrame\uc758 \uac01 \uc5f4\uc774 \ub3d9\uc77c\ud55c \uae38\uc774\uc778\uc9c0 \ud655\uc778\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \uc608\uc5d0\uc11c\ub294 \uc2e4\uc81c\ub85c \uc774 \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n<h2> <span style=\"color: #000000;\"><strong>\uc608: \uae38\uc774\uac00 \ub2e4\ub978 \uc0ac\uc804\uc5d0\uc11c Pandas DataFrame \ub9cc\ub4e4\uae30<\/strong><\/span><\/h2>\n<p> <span style=\"color: #000000;\">\uc11c\ub85c \ub2e4\ub978 \uae38\uc774\uc758 \ud56d\ubaa9\uc744 \ud3ec\ud568\ud558\ub294 \ub2e4\uc74c \uc0ac\uc804\uc774 \uc788\ub2e4\uace0 \uac00\uc815\ud569\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#create dictionary whose entries have different lengths\n<\/span>some_dict = dict(A=[2, 5, 5, 7, 8], B=[9, 3], C=[4, 4, 2])\n\n<span style=\"color: #008080;\">#view dictionary\n<\/span><span style=\"color: #008000;\">print<\/span> (some_dict)\n\n{'A': [2, 5, 5, 7, 8], 'B': [9, 3], 'C': [4, 4, 2]}\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\"><strong>from_dict()<\/strong> \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\uc5ec \uc774 \uc0ac\uc804\uc744 pandas DataFrame\uc73c\ub85c \ubcc0\ud658\ud558\ub824\uace0 \ud558\uba74 \uc624\ub958\uac00 \ubc1c\uc0dd\ud569\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\"><span style=\"color: #000000;\"><span style=\"color: #008000;\">import<\/span> pandas <span style=\"color: #008000;\">as<\/span> pd<\/span>\n\n#attempt to create pandas DataFrame from dictionary<\/span>\ndf = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> . <span style=\"color: #3366ff;\">from_dict<\/span> (some_dict)\n\n<span style=\"color: #ff0000;\">ValueError<\/span> : All arrays must be of the same length\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\uc0ac\uc804\uc758 \ubaa8\ub4e0 \ubc30\uc5f4\uc740 \uae38\uc774\uac00 \ub3d9\uc77c\ud574\uc57c \ud55c\ub2e4\ub294 \uc624\ub958\uac00 \ubc1c\uc0dd\ud569\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uc774 \uc624\ub958\ub97c \ud574\uacb0\ud558\ub824\uba74 \ub2e4\uc74c \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\uc5ec Dictionary\ub97c DataFrame\uc73c\ub85c \ubcc0\ud658\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\"><span style=\"color: #000000;\"><span style=\"color: #008000;\">import<\/span> pandas <span style=\"color: #008000;\">as<\/span> pd<\/span>\n\n#create pandas DataFrame from dictionary<\/span>\ndf = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> (dict([(key, pd. <span style=\"color: #3366ff;\">Series<\/span> (value)) <span style=\"color: #008000;\">for<\/span> key, value <span style=\"color: #008000;\">in<\/span> some_dict. <span style=\"color: #3366ff;\">items<\/span> ()]))\n\n<span style=\"color: #008080;\">#view DataFrame<\/span>\n<span style=\"color: #008000;\">print<\/span> (df)\n\n   ABC\n0 2 9.0 4.0\n1 5 3.0 4.0\n2 5 NaN 2.0\n3 7 NaN NaN\n4 8 NaN NaN\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">pandas DataFrame\uc744 \uc131\uacf5\uc801\uc73c\ub85c \uc0dd\uc131\ud560 \uc218 \uc788\uc73c\uba70 \uac01 \uc5f4\uc758 \uae38\uc774\uac00 \ub3d9\uc77c\ud558\ub3c4\ub85d NaN \uac12\uc774 \ucc44\uc6cc\uc9d1\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uc774\ub7ec\ud55c NaN \uac12\uc744 \ub2e4\ub978 \uac12(\uc608: 0)\uc73c\ub85c \ubc14\uafb8\ub824\uba74 \ub2e4\uc74c\uacfc \uac19\uc774 <strong>replacement()<\/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: #008080;\">#replace all NaNs with zeros\n<span style=\"color: #000000;\">df. <span style=\"color: #3366ff;\">replace<\/span> (np. <span style=\"color: #3366ff;\">nan<\/span> , 0, inplace= <span style=\"color: #008000;\">True<\/span> )\n<\/span>\n#view updated DataFrame\n<span style=\"color: #000000;\"><span style=\"color: #008000;\">print<\/span> (df)\n\n   ABC\n0 2 9.0 4.0\n1 5 3.0 4.0\n2 5 0.0 2.0\n3 7 0.0 0.0\n4 8 0.0 0.0\n<\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\uac01 NaN \uac12\uc740 0\uc73c\ub85c \ub300\uccb4\ub418\uc5c8\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">NaN \uac12\uc744 \uc6d0\ud558\ub294 \uac12\uc73c\ub85c \ubc14\uafb8\ub824\uba74 \uc790\uc720\ub86d\uac8c <strong>replacement()<\/strong> \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\uc138\uc694.<\/span><\/p>\n<h2> <span style=\"color: #000000;\"><strong>\ucd94\uac00 \ub9ac\uc18c\uc2a4<\/strong><\/span><\/h2>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 Pandas\uc5d0\uc11c \ub2e4\ub978 \uc77c\ubc18\uc801\uc778 \uc791\uc5c5\uc744 \uc218\ud589\ud558\ub294 \ubc29\ubc95\uc744 \uc124\uba85\ud569\ub2c8\ub2e4.<\/span><\/p>\n<p> <a href=\"https:\/\/statorials.org\/ko\/\u1111\u1162\u11ab\u1103\u1165-\u1103\u1166\u110b\u1175\u1110\u1165-\u1111\u1173\u1105\u1166\u110b\u1175\u11b7\u110b\u1173\u11af-\u1109\u1161\u110c\u1165\u11ab\u110b\u1173\u1105\u1169\/\" target=\"_blank\" rel=\"noopener\">Pandas: DataFrame\uc744 \uc0ac\uc804\uc73c\ub85c \ubcc0\ud658\ud558\ub294 \ubc29\ubc95<\/a><br \/> <a href=\"https:\/\/statorials.org\/ko\/\u1111\u1162\u11ab\u1103\u1165\u1102\u1173\u11ab-\u1109\u1161\u110c\u1165\u11ab\u110b\u1173\u1105\u1169-\u110b\u1167\u11af-\u110b\u1175\u1105\u1173\u11b7\u110b\u1173\u11af-\u1107\u1161\u1101\u116e\u11b8\u1102\u1175\u1103\u1161.\/\" target=\"_blank\" rel=\"noopener\">Pandas: \uc0ac\uc804\uc744 \uc0ac\uc6a9\ud558\uc5ec \uc5f4 \uc774\ub984\uc744 \ubc14\uafb8\ub294 \ubc29\ubc95<\/a><br \/> <a href=\"https:\/\/statorials.org\/ko\/\u1111\u1162\u11ab\u1103\u1165-\u1111\u1175\u11af\u1102\u1161-\u1109\u1161\u110c\u1165\u11ab\/\" target=\"_blank\" rel=\"noopener\">Pandas: \uc0ac\uc804\uc744 \uc0ac\uc6a9\ud558\uc5ec NaN \uac12\uc744 \ucc44\uc6b0\ub294 \ubc29\ubc95<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\ub2e4\uc74c \uae30\ubcf8 \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\uc5ec \ud56d\ubaa9 \uae38\uc774\uac00 \ub2e4\ub978 \uc0ac\uc804\uc5d0\uc11c pandas DataFrame\uc744 \ub9cc\ub4e4 \uc218 \uc788\uc2b5\ub2c8\ub2e4. import pandas as pd df = pd. DataFrame (dict([(key, pd. Series (value)) for key, value in some_dict. items ()])) \uc774 \uad6c\ubb38\uc740 \uc0ac\uc804 \ubc30\uc5f4 \ubaa9\ub85d\uc744 Pandas \uc2dc\ub9ac\uc988 \ubaa9\ub85d\uc73c\ub85c \ubcc0\ud658\ud569\ub2c8\ub2e4. \uc774\ub97c \ud1b5\ud574 \uc6b0\ub9ac\ub294 pandas DataFrame\uc744 \uc0dd\uc131\ud558\uace0 NaN \uac12\uc744 \uc785\ub825\ud558\uc5ec \uacb0\uacfc DataFrame\uc758 \uac01 \uc5f4\uc774 \ub3d9\uc77c\ud55c [&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-4243","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: \uae38\uc774\uac00 \ub2e4\ub978 dict\uc5d0\uc11c DataFrame \uc0dd\uc131 \u2013 Statorials<\/title>\n<meta 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