{"id":3698,"date":"2023-07-16T01:36:44","date_gmt":"2023-07-16T01:36:44","guid":{"rendered":"https:\/\/statorials.org\/ko\/%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5%e1%84%82%e1%85%b3%e1%86%ab-%e1%84%83%e1%85%ae-%e1%84%80%e1%85%a2%e1%84%8b%e1%85%b4-%e1%84%83%e1%85%a6%e1%84%8b%e1%85%b5%e1%84%90%e1%85%a5-%e1%84%91-2\/"},"modified":"2023-07-16T01:36:44","modified_gmt":"2023-07-16T01:36:44","slug":"%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5%e1%84%82%e1%85%b3%e1%86%ab-%e1%84%83%e1%85%ae-%e1%84%80%e1%85%a2%e1%84%8b%e1%85%b4-%e1%84%83%e1%85%a6%e1%84%8b%e1%85%b5%e1%84%90%e1%85%a5-%e1%84%91-2","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%82%e1%85%b3%e1%86%ab-%e1%84%83%e1%85%ae-%e1%84%80%e1%85%a2%e1%84%8b%e1%85%b4-%e1%84%83%e1%85%a6%e1%84%8b%e1%85%b5%e1%84%90%e1%85%a5-%e1%84%91-2\/","title":{"rendered":"Pandas: \ub450 \uac1c\uc758 dataframe\uc744 \ube7c\ub294 \ubc29\ubc95"},"content":{"rendered":"

<\/p>\n

\n

\ub2e4\uc74c \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\uc5ec \ud55c \ud32c\ub354 DataFrame\uc744 \ub2e4\ub978 \ud32c\ub354 DataFrame\uc5d0\uc11c \ube84 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n

 df1. subtract<\/span> (df2)\n<\/strong><\/pre>\n
 \uac01 DataFrame\uc5d0 \ubb38\uc790 \uc5f4\uc774 \uc788\ub294 \uacbd\uc6b0 \uba3c\uc800 \uc774\ub97c \uac01 DataFrame\uc758 \uc778\ub371\uc2a4 \uc5f4\ub85c \uc774\ub3d9\ud574\uc57c \ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 df1. set_index<\/span> (' char_column<\/span> '). subtract<\/span> ( df2.set_index<\/span> (' char_column<\/span> '))<\/strong><\/pre>\n
 \ub2e4\uc74c \uc608\uc5d0\uc11c\ub294 \uc2e4\uc81c\ub85c \uac01 \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n
 \uc608 1: \ub450 \uac1c\uc758 Pandas DataFrame \ube7c\uae30(\uc22b\uc790 \uc5f4\ub9cc \ud574\ub2f9)<\/strong><\/span><\/h2>\n
 \uc22b\uc790 \uc5f4\ub9cc \uc788\ub294 \ub2e4\uc74c \ub450 \uac1c\uc758 \ud32c\ub354 DataFrame\uc774 \uc788\ub2e4\uace0 \uac00\uc815\ud574 \ubcf4\uaca0\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#create first DataFrame\n<\/span>df1 = pd. DataFrame<\/span> ({' points<\/span> ': [5, 17, 7, 19, 12, 13, 9, 24],\n                    ' assists<\/span> ': [4, 7, 7, 6, 8, 7, 10, 11]})\n\nprint<\/span> (df1)\n\n   assist points\n0 5 4\n1 17 7\n2 7 7\n3 19 6\n4 12 8\n5 13 7\n6 9 10\n7 24 11\n\n#create second DataFrame\n<\/span>df2 = pd. DataFrame<\/span> ({' points<\/span> ': [4, 22, 10, 3, 7, 8, 12, 10],\n                    ' assists<\/span> ': [3, 5, 5, 4, 7, 14, 9, 5]})\n\nprint<\/span> (df2)\n\n   assist points\n0 4 3\n1 22 5\n2 10 5\n3 3 4\n4 7 7\n5 8 14\n6 12 9\n7 10 5\n<\/span><\/span><\/span><\/strong><\/pre>\n
 \ub2e4\uc74c \ucf54\ub4dc\ub294 \ub450 DataFrame \uc0ac\uc774\uc5d0\uc11c \ud574\ub2f9 \uac12\uc744 \ube7c\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n
 #subtract corresponding values between the two DataFrames<\/span>\ndf1. subtract<\/span> (df2)\n\n\tassist points\n0 1 1\n1 -5 2\n2 -3 2\n3 16 2\n4 5 1\n5 5 -7\n6 -3 1\n7 14 6\n<\/strong><\/span><\/pre>\n
 \uc608 2: \ub450 \uac1c\uc758 Pandas DataFrame \ube7c\uae30(\ubb38\uc790 \uc5f4\uacfc \uc22b\uc790 \uc5f4\uc758 \ud63c\ud569)<\/strong><\/span><\/h2>\n
 \uac01\uac01 team<\/strong> \uc774\ub77c\ub294 \ubb38\uc790 \uc5f4\uc774 \uc788\ub294 \ub2e4\uc74c \ub450 \uac1c\uc758 \ud32c\ub354 DataFrame\uc774 \uc788\ub2e4\uace0 \uac00\uc815\ud574 \ubcf4\uaca0\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#create first DataFrame\n<\/span>df1 = pd. DataFrame<\/span> ({' team<\/span> ': ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'],\n                    ' points<\/span> ': [5, 17, 7, 19, 12, 13, 9, 24],\n                    ' assists<\/span> ': [4, 7, 7, 6, 8, 7, 10, 11]})\n\nprint<\/span> (df1)\n\n  team points assists\n0 to 5 4\n1 B 17 7\n2 C 7 7\n3 D 19 6\n4 E 12 8\n5 F 13 7\n6 G 9 10\n7:24 a.m. 11\n\n#create second DataFrame\n<\/span>df2 = pd. DataFrame<\/span> ({' team<\/span> ': ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'],\n                    ' points<\/span> ': [4, 22, 10, 3, 7, 8, 12, 10],\n                    ' assists<\/span> ': [3, 5, 5, 4, 7, 14, 9, 3]})\n\nprint<\/span> (df2)\n\n  team points assists\n0 to 4 3\n1 B 22 5\n2 C 10 5\n3 D 3 4\n4 E 7 7\n5 F 8 14\n6 G 12 9\n7:10 a.m. 3<\/span><\/strong><\/pre>\n
 \ub2e4\uc74c \ucf54\ub4dc\ub294 \ud300<\/strong> \uc5f4\uc744 \uac01 DataFrame\uc758 \uc778\ub371\uc2a4 \uc5f4\ub85c \uc774\ub3d9\ud55c \ud6c4 \ub450 DataFrame \uc0ac\uc774\uc5d0\uc11c \ud574\ub2f9 \uac12\uc744 \ube7c\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n
 #move 'team' column to index of each DataFrame and subtract corresponding values\n<\/span>df1. set_index<\/span> (' team<\/span> '). subtract<\/span> ( df2.set_index<\/span> (' team<\/span> '))\n\n\tassist points\nteam\t\t\nAt 1 1\nB-52\nC -3 2\nD 16 2\nE 5 1\nF 5 -7\nG -3 1\nH 14 8\n<\/span><\/strong><\/pre>\n
 \ucd94\uac00 \ub9ac\uc18c\uc2a4<\/strong><\/span><\/h2>\n
 \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
 Pandas: \ub450 \uc5f4\uc758 \ucc28\uc774\uc810\uc744 \ucc3e\ub294 \ubc29\ubc95<\/a>
 Pandas: \ub450 \uc904\uc758 \ucc28\uc774\uc810\uc744 \ucc3e\ub294 \ubc29\ubc95<\/a>
 \ud32c\ub354:\ub450 \uc5f4\uc744 \ube7c\ub294 \ubc29\ubc95<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
\ub2e4\uc74c \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\uc5ec \ud55c \ud32c\ub354 DataFrame\uc744 \ub2e4\ub978 \ud32c\ub354 DataFrame\uc5d0\uc11c \ube84 \uc218 \uc788\uc2b5\ub2c8\ub2e4. df1. subtract (df2) \uac01 DataFrame\uc5d0 \ubb38\uc790 \uc5f4\uc774 \uc788\ub294 \uacbd\uc6b0 \uba3c\uc800 \uc774\ub97c \uac01 DataFrame\uc758 \uc778\ub371\uc2a4 \uc5f4\ub85c \uc774\ub3d9\ud574\uc57c \ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. df1. set_index (‘ char_column ‘). subtract ( df2.set_index (‘ char_column ‘)) \ub2e4\uc74c \uc608\uc5d0\uc11c\ub294 \uc2e4\uc81c\ub85c \uac01 \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4. \uc608 1: \ub450 \uac1c\uc758 Pandas […]<\/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-3698","post","type-post","status-publish","format-standard","hentry","category-20"],"yoast_head":"\nPandas: \ub450 \uac1c\uc758 DataFrame\uc744 \ube7c\ub294 \ubc29\ubc95 - Statorials<\/title>\n<meta name=\"description\" content=\"\uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 \uba87 \uac00\uc9c0 \uc608\ub97c \ud1b5\ud574 \ub450 \ud32c\ub354 DataFrame \uc0ac\uc774\uc5d0\uc11c \uac12\uc744 \ube7c\ub294 \ubc29\ubc95\uc744 \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\/\u1111\u1162\u11ab\u1103\u1165\u1102\u1173\u11ab-\u1103\u116e-\u1100\u1162\u110b\u1174-\u1103\u1166\u110b\u1175\u1110\u1165-\u1111-2\/\" \/>\n<meta property=\"og:locale\" content=\"ko_KR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Pandas: \ub450 \uac1c\uc758 DataFrame\uc744 \ube7c\ub294 \ubc29\ubc95 - Statorials\" \/>\n<meta property=\"og:description\" content=\"\uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 \uba87 \uac00\uc9c0 \uc608\ub97c \ud1b5\ud574 \ub450 \ud32c\ub354 DataFrame \uc0ac\uc774\uc5d0\uc11c \uac12\uc744 \ube7c\ub294 \ubc29\ubc95\uc744 \uc124\uba85\ud569\ub2c8\ub2e4.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/statorials.org\/ko\/\u1111\u1162\u11ab\u1103\u1165\u1102\u1173\u11ab-\u1103\u116e-\u1100\u1162\u110b\u1174-\u1103\u1166\u110b\u1175\u1110\u1165-\u1111-2\/\" \/>\n<meta property=\"og:site_name\" content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-16T01:36:44+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\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"1\ubd84\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/statorials.org\/ko\/%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5%e1%84%82%e1%85%b3%e1%86%ab-%e1%84%83%e1%85%ae-%e1%84%80%e1%85%a2%e1%84%8b%e1%85%b4-%e1%84%83%e1%85%a6%e1%84%8b%e1%85%b5%e1%84%90%e1%85%a5-%e1%84%91-2\/\",\"url\":\"https:\/\/statorials.org\/ko\/%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5%e1%84%82%e1%85%b3%e1%86%ab-%e1%84%83%e1%85%ae-%e1%84%80%e1%85%a2%e1%84%8b%e1%85%b4-%e1%84%83%e1%85%a6%e1%84%8b%e1%85%b5%e1%84%90%e1%85%a5-%e1%84%91-2\/\",\"name\":\"Pandas: \ub450 \uac1c\uc758 DataFrame\uc744 \ube7c\ub294 \ubc29\ubc95 - 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