{"id":1601,"date":"2023-07-25T16:56:36","date_gmt":"2023-07-25T16:56:36","guid":{"rendered":"https:\/\/statorials.org\/ko\/%e1%84%92%e1%85%a2%e1%86%bc-%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":"2023-07-25T16:56:36","modified_gmt":"2023-07-25T16:56:36","slug":"%e1%84%92%e1%85%a2%e1%86%bc-%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%92%e1%85%a2%e1%86%bc-%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 \uc904\uc758 \ucc28\uc774\uc810\uc744 \ucc3e\ub294 \ubc29\ubc95"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\"><strong>DataFrame.diff()<\/strong> \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\uc5ec Pandas DataFrame\uc5d0 \uc788\ub294 \ub450 \ud589 \uac04\uc758 \ucc28\uc774\ub97c \ucc3e\uc744 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uc774 \ud568\uc218\ub294 \ub2e4\uc74c \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud569\ub2c8\ub2e4.<\/span><\/p>\n<p> <strong><span style=\"color: #000000;\">DataFrame.diff(\uae30\uac04=1, \ucd95=0)<\/span><\/strong><\/p>\n<p> <span style=\"color: #000000;\">\uae08:<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>\ub9c8\uce68\ud45c:<\/strong> \ucc28\uc774\ub97c \uacc4\uc0b0\ud558\uae30 \uc704\ud55c \uc774\uc804 \uc904 \uc218\uc785\ub2c8\ub2e4.<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>\ucd95:<\/strong> \ud589(0) \ub610\ub294 \uc5f4(1)\uc5d0\uc11c \ucc28\uc774\uc810\uc744 \ucc3e\uc2b5\ub2c8\ub2e4.<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \uc608\uc5d0\uc11c\ub294 \uc774 \uae30\ub2a5\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: \uc774\uc804 \uac01 \ud589 \uac04\uc758 \ucc28\uc774\uc810 \ucc3e\uae30<\/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. <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;\">sales<\/span> ': [12, 14, 15, 15, 18, 20, 19, 24],\n                   ' <span style=\"color: #ff0000;\">returns<\/span> ': [2, 2, 3, 3, 5, 4, 4, 6]})\n\n<span style=\"color: #008080;\">#view DataFrame\n<\/span>df\n\n\tperiod sales returns\n0 1 12 2\n1 2 14 2\n2 3 15 3\n3 4 15 3\n4 5 18 5\n5 6 20 4\n6 7 19 4\n7 8 24 6<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \ucf54\ub4dc\ub294 DataFrame\uc758 \uac01 \ud604\uc7ac \ud589\uacfc \uc774\uc804 \ud589 \uac04\uc758 \ucc28\uc774\ub97c \ucc3e\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 sales differences between each row<\/span>\ndf[' <span style=\"color: #ff0000;\">sales_diff<\/span> '] = df[' <span style=\"color: #ff0000;\">sales<\/span> ']. <span style=\"color: #3366ff;\">diff<\/span> ()\n\n<span style=\"color: #008080;\">#view DataFrame\n<\/span>df\n\n        period sales returns sales_diff\n0 1 12 2 NaN\n1 2 14 2 2.0\n2 3 15 3 1.0\n3 4 15 3 0.0\n4 5 18 5 3.0\n5 6 20 4 2.0\n6 7 19 4 -1.0\n7 8 24 6 5.0\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\uc774\uc804 \uc5ec\ub7ec \uc904\uc758 \ucc28\uc774\uc810\ub3c4 \ucc3e\uc744 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc608\ub97c \ub4e4\uc5b4, \ub2e4\uc74c \ucf54\ub4dc\ub294 \ud604\uc7ac \uac01 \ud589\uacfc \uc138 \ud589 \uc774\uc804\uc5d0 \ud45c\uc2dc\ub41c \ud589 \uac04\uc758 \ucc28\uc774\ub97c \ucc3e\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 sales differences between current row and 3 rows earlier<\/span>\ndf[' <span style=\"color: #ff0000;\">sales_diff<\/span> '] = df[' <span style=\"color: #ff0000;\">sales<\/span> ']. <span style=\"color: #3366ff;\">diff<\/span> (periods= <span style=\"color: #008000;\">3<\/span> )\n\n<span style=\"color: #008080;\">#view DataFrame\n<\/span>df\n\n        period sales returns sales_diff\n0 1 12 2 NaN\n1 2 14 2 NaN\n2 3 15 3 NaN\n3 4 15 3 3.0\n4 5 18 5 4.0\n5 6 20 4 5.0\n6 7 19 4 4.0\n7 8 24 6 6.0<\/strong><\/pre>\n<h3> <span style=\"color: #000000;\"><strong>\uc608\uc2dc 2: \uc870\uac74\uc5d0 \ub530\ub978 \ucc28\uc774 \ucc3e\uae30<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\ub610\ud55c DataFrame\uc744 \ud544\ud130\ub9c1\ud558\uc5ec \ud604\uc7ac \ud589\uacfc \uc774\uc804 \ud589\uc758 \ucc28\uc774\uac00 \ud2b9\uc815 \uac12\ubcf4\ub2e4 \uc791\uac70\ub098 \ud070 \ud589\uc744 \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 \ud604\uc7ac \ud589 \uac12\uc774 \uc774\uc804 \ud589 \uac12 <strong>\ubcf4\ub2e4 \uc791\uc740<\/strong> \ud589\ub9cc \ubc18\ud658\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;\">sales<\/span> ': [12, 14, 15, 13, 18, 20, 19, 24],\n                   ' <span style=\"color: #ff0000;\">returns<\/span> ': [2, 2, 3, 3, 5, 4, 4, 6]})\n\n<span style=\"color: #008080;\">#find difference between each current row and the previous row\n<\/span>df[' <span style=\"color: #ff0000;\">sales_diff<\/span> '] = df[' <span style=\"color: #ff0000;\">sales<\/span> ']. <span style=\"color: #3366ff;\">diff<\/span> ()\n\n<span style=\"color: #008080;\">#filter for rows where difference is less than zero\n<\/span>df = df[df[' <span style=\"color: #ff0000;\">sales_diff<\/span> ']&lt; <span style=\"color: #008000;\">0<\/span> ]\n\n<span style=\"color: #008080;\">#view DataFrame\n<\/span>df\n\n        period sales returns sales_diff\n3 4 13 3 -2.0\n6 7 19 4 -1.0<\/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\/\u1103\u1161\u11ab\u110b\u1175\u11af-\u1111\u1162\u11ab\u1103\u1165-\u1103\u1161\u110c\u116e\u11bc-\u110b\u1167\u11af\/\" target=\"_blank\" rel=\"noopener\">Pandas\uc758 \uc5ec\ub7ec \uc5f4\uc5d0\uc11c \uace0\uc720\ud55c \uac12\uc744 \ucc3e\ub294 \ubc29\ubc95<\/a><br \/> \uc5f4 \uac12\uc73c\ub85c Pandas DataFrame\uc744 \ud544\ud130\ub9c1\ud558\ub294 \ubc29\ubc95<br \/> <a href=\"https:\/\/statorials.org\/ko\/\u1111\u1162\u11ab\u1103\u1165\u1102\u1173\u11ab-\u110b\u1175\u11ab\u1103\u1166\u11a8\u1109\u1173\u1105\u1169-\u1112\u1162\u11bc\u110b\u1173\u11af-\u1109\u1165\u11ab\u1110\u1162\u11a8\u1112\u1161\u11b8\u1102\u1175\u1103\u1161.\/\" target=\"_blank\" rel=\"noopener\">Pandas DataFrame\uc5d0\uc11c \uc778\ub371\uc2a4\ub85c \ud589\uc744 \uc120\ud0dd\ud558\ub294 \ubc29\ubc95<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>DataFrame.diff() \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\uc5ec Pandas DataFrame\uc5d0 \uc788\ub294 \ub450 \ud589 \uac04\uc758 \ucc28\uc774\ub97c \ucc3e\uc744 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc774 \ud568\uc218\ub294 \ub2e4\uc74c \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud569\ub2c8\ub2e4. DataFrame.diff(\uae30\uac04=1, \ucd95=0) \uae08: \ub9c8\uce68\ud45c: \ucc28\uc774\ub97c \uacc4\uc0b0\ud558\uae30 \uc704\ud55c \uc774\uc804 \uc904 \uc218\uc785\ub2c8\ub2e4. \ucd95: \ud589(0) \ub610\ub294 \uc5f4(1)\uc5d0\uc11c \ucc28\uc774\uc810\uc744 \ucc3e\uc2b5\ub2c8\ub2e4. \ub2e4\uc74c \uc608\uc5d0\uc11c\ub294 \uc774 \uae30\ub2a5\uc744 \uc2e4\uc81c\ub85c \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4. \uc608 1: \uc774\uc804 \uac01 \ud589 \uac04\uc758 \ucc28\uc774\uc810 \ucc3e\uae30 \ub2e4\uc74c\uacfc \uac19\uc740 \ud32c\ub354 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-1601","post","type-post","status-publish","format-standard","hentry","category-20"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - 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