{"id":1602,"date":"2023-07-25T16:51:45","date_gmt":"2023-07-25T16:51:45","guid":{"rendered":"https:\/\/statorials.org\/ko\/%e1%84%83%e1%85%ae-%e1%84%8b%e1%85%a7%e1%86%af-%e1%84%89%e1%85%a1%e1%84%8b%e1%85%b5%e1%84%8b%e1%85%b4-%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5-%e1%84%8e%e1%85%a1%e1%84%8b%e1%85%b5\/"},"modified":"2023-07-25T16:51:45","modified_gmt":"2023-07-25T16:51:45","slug":"%e1%84%83%e1%85%ae-%e1%84%8b%e1%85%a7%e1%86%af-%e1%84%89%e1%85%a1%e1%84%8b%e1%85%b5%e1%84%8b%e1%85%b4-%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5-%e1%84%8e%e1%85%a1%e1%84%8b%e1%85%b5","status":"publish","type":"post","link":"https:\/\/statorials.org\/ko\/%e1%84%83%e1%85%ae-%e1%84%8b%e1%85%a7%e1%86%af-%e1%84%89%e1%85%a1%e1%84%8b%e1%85%b5%e1%84%8b%e1%85%b4-%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5-%e1%84%8e%e1%85%a1%e1%84%8b%e1%85%b5\/","title":{"rendered":"Pandas: \ub450 \uc5f4\uc758 \ucc28\uc774\uc810\uc744 \ucc3e\ub294 \ubc29\ubc95"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">Pandas DataFrame\uc5d0\uc11c \ub450 \uc5f4 \uac04\uc758 \ucc28\uc774\uc810\uc744 \ucc3e\uc73c\ub824\uba74 \ub2e4\uc74c \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>df[' <span style=\"color: #ff0000;\">difference<\/span> '] = df[' <span style=\"color: #ff0000;\">column1<\/span> '] - df[' <span style=\"color: #ff0000;\">column2<\/span> ']\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \uc608\uc5d0\uc11c\ub294 \uc774 \uad6c\ubb38\uc744 \uc2e4\uc81c\ub85c \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>\uc608 1: \ub450 \uc5f4 \uac04\uc758 \ucc28\uc774 \ucc3e\uae30<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">8\uac1c\uc758 \uc5f0\uc18d \ud310\ub9e4 \uae30\uac04 \ub3d9\uc548 \ub450 \uc9c0\uc5ed(A \ubc0f B)\uc758 \ucd1d \ub9e4\ucd9c\uc744 \ud45c\uc2dc\ud558\ub294 \ub2e4\uc74c\uacfc \uac19\uc740 pandas 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. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">period<\/span> ': [1, 2, 3, 4, 5, 6, 7, 8],\n                   ' <span style=\"color: #ff0000;\">A_sales<\/span> ': [12, 14, 15, 13, 18, 20, 19, 24],\n                   ' <span style=\"color: #ff0000;\">B_sales<\/span> ': [14, 19, 20, 22, 24, 20, 17, 23]})\n\n<span style=\"color: #008080;\">#view DataFrame\n<\/span>df\n\nperiod A_sales B_sales\n0 1 12 14\n1 2 14 19\n2 3 15 20\n3 4 13 22\n4 5 18 24\n5 6 20 20\n6 7 19 17\n7 8 24 23<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \ucf54\ub4dc\ub294 \uac01 \ud310\ub9e4 \uae30\uac04\uc5d0 \ub300\ud574 B \uc9c0\uc5ed\uacfc A \uc9c0\uc5ed\uc758 \ub9e4\ucd9c \ucc28\uc774\ub97c \uacc4\uc0b0\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#add new column to represent difference between B sales and A sales<\/span>\ndf[' <span style=\"color: #ff0000;\">diff<\/span> '] = df[' <span style=\"color: #ff0000;\">B_sales<\/span> '] - df[' <span style=\"color: #ff0000;\">A_sales<\/span> ']\n\n<span style=\"color: #008080;\">#view DataFrame\n<\/span>df\n\n        period A_sales B_sales diff\n0 1 12 14 2\n1 2 14 19 5\n2 3 15 20 5\n3 4 13 22 9\n4 5 18 24 6\n5 6 20 20 0\n6 7 19 17 -2\n7 8 24 23 -1\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\"><strong>pandas.Series.abs()<\/strong> \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\uc5ec \ub9e4\ucd9c\uc758 \uc808\ub300 \ucc28\uc774\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: #008080;\">#add new column to represent absolute difference between B sales and A sales<\/span>\ndf[' <span style=\"color: #ff0000;\">diff<\/span> '] = pd. <span style=\"color: #3366ff;\">Series<\/span> . <span style=\"color: #3366ff;\">abs<\/span> (df[' <span style=\"color: #ff0000;\">B_sales<\/span> '] - df[' <span style=\"color: #ff0000;\">A_sales<\/span> '])\n\n<span style=\"color: #008080;\">#view DataFrame\n<\/span>df\n\n\tperiod A_sales B_sales diff\n0 1 12 14 2\n1 2 14 19 5\n2 3 15 20 5\n3 4 13 22 9\n4 5 18 24 6\n5 6 20 20 0\n6 7 19 17 2\n7 8 24 23 1\n<\/strong><\/pre>\n<h3> <span style=\"color: #000000;\"><strong>\uc608\uc2dc 2: \uc870\uac74\uc5d0 \ub530\ub77c \uc5f4 \uac04\uc758 \ucc28\uc774 \ucc3e\uae30<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\ub610\ud55c DataFrame\uc744 \ud544\ud130\ub9c1\ud558\uc5ec \uc5f4 \uac04\uc758 \ucc28\uc774\uac00 \ud2b9\uc815 \uac12\ubcf4\ub2e4 \uc791\uac70\ub098 \ud070 \ud589\ub9cc \ud45c\uc2dc\ud560 \uc218\ub3c4 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uc608\ub97c \ub4e4\uc5b4, \ub2e4\uc74c \ucf54\ub4dc\ub294 A \uc9c0\uc5ed\uc758 \ub9e4\ucd9c\uc774 B \uc9c0\uc5ed\uc758 \ub9e4\ucd9c\ubcf4\ub2e4 <strong>\ud070<\/strong> \ud589\ub9cc \ubc18\ud658\ud569\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#add new column to represent difference between B sales and A sales<\/span>\ndf[' <span style=\"color: #ff0000;\">diff<\/span> '] = df[' <span style=\"color: #ff0000;\">B_sales<\/span> '] - df[' <span style=\"color: #ff0000;\">A_sales<\/span> ']\n\n<span style=\"color: #008080;\">#display rows where sales in region A is greater than sales in region B\n<span style=\"color: #000000;\">df[df[' <span style=\"color: #ff0000;\">diff<\/span> ']&lt; <span style=\"color: #008000;\">0<\/span> ]\n\n\n        period A_sales B_sales diff\n6 7 19 17 -2\n7 8 24 23 -1\n<\/span><\/span><\/strong><\/pre>\n<h3> <span style=\"color: #000000;\"><strong>\ucd94\uac00 \ub9ac\uc18c\uc2a4<\/strong><\/span><\/h3>\n<p> <a href=\"https:\/\/statorials.org\/ko\/\u1112\u1162\u11bc-\u1109\u1161\u110b\u1175\u110b\u1174-\u1111\u1162\u11ab\u1103\u1165-\u110e\u1161\u110b\u1175\/\" target=\"_blank\" rel=\"noopener\">Pandas: \ub450 \uc904\uc758 \ucc28\uc774\uc810\uc744 \ucc3e\ub294 \ubc29\ubc95<\/a><br \/> <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\">Pandas: \uc5ec\ub7ec \uc5f4\uc744 \uadf8\ub8f9\ud654\ud558\uace0 \uc9d1\uacc4\ud558\ub294 \ubc29\ubc95<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Pandas DataFrame\uc5d0\uc11c \ub450 \uc5f4 \uac04\uc758 \ucc28\uc774\uc810\uc744 \ucc3e\uc73c\ub824\uba74 \ub2e4\uc74c \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. df[&#8216; difference &#8216;] = df[&#8216; column1 &#8216;] &#8211; df[&#8216; column2 &#8216;] \ub2e4\uc74c \uc608\uc5d0\uc11c\ub294 \uc774 \uad6c\ubb38\uc744 \uc2e4\uc81c\ub85c \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4. \uc608 1: \ub450 \uc5f4 \uac04\uc758 \ucc28\uc774 \ucc3e\uae30 8\uac1c\uc758 \uc5f0\uc18d \ud310\ub9e4 \uae30\uac04 \ub3d9\uc548 \ub450 \uc9c0\uc5ed(A \ubc0f B)\uc758 \ucd1d \ub9e4\ucd9c\uc744 \ud45c\uc2dc\ud558\ub294 \ub2e4\uc74c\uacfc \uac19\uc740 pandas DataFrame\uc774 \uc788\ub2e4\uace0 [&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-1602","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: \ub450 \uc5f4\uc758 \ucc28\uc774\uc810\uc744 \ucc3e\ub294 \ubc29\ubc95<\/title>\n<meta name=\"description\" content=\"\uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 \uba87 \uac00\uc9c0 \uc608\ub97c \ud1b5\ud574 Pandas DataFrame\uc5d0\uc11c \ub450 \uc5f4 \uc0ac\uc774\uc758 \ucc28\uc774\uc810\uc744 \ucc3e\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\" 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