{"id":2338,"date":"2023-07-22T17:02:44","date_gmt":"2023-07-22T17:02:44","guid":{"rendered":"https:\/\/statorials.org\/ko\/%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5-%e1%84%85%e1%85%a9%e1%86%af%e1%84%85%e1%85%b5%e1%86%bc-%e1%84%8c%e1%85%ae%e1%86%bc%e1%84%8b%e1%85%a1%e1%86%bc%e1%84%80%e1%85%a1%e1%86%b9\/"},"modified":"2023-07-22T17:02:44","modified_gmt":"2023-07-22T17:02:44","slug":"%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5-%e1%84%85%e1%85%a9%e1%86%af%e1%84%85%e1%85%b5%e1%86%bc-%e1%84%8c%e1%85%ae%e1%86%bc%e1%84%8b%e1%85%a1%e1%86%bc%e1%84%80%e1%85%a1%e1%86%b9","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%85%e1%85%a9%e1%86%af%e1%84%85%e1%85%b5%e1%86%bc-%e1%84%8c%e1%85%ae%e1%86%bc%e1%84%8b%e1%85%a1%e1%86%bc%e1%84%80%e1%85%a1%e1%86%b9\/","title":{"rendered":"Pandas\uc5d0\uc11c \uc774\ub3d9 \uc911\uc559\uac12\uc744 \uacc4\uc0b0\ud558\ub294 \ubc29\ubc95: \uc608 \ud3ec\ud568"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\"><strong>\ub864\ub9c1 \uc911\uc559\uac12\uc740<\/strong> \uc2dc\uacc4\uc5f4\uc5d0\uc11c \uc774\uc804 \uae30\uac04 \uc218\uc758 \uc911\uc559\uac12\uc785\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">Pandas DataFrame\uc5d0\uc11c \uc5f4\uc758 \uc774\ub3d9 \uc911\uc559\uac12\uc744 \uacc4\uc0b0\ud558\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><span style=\"color: #008080;\">#calculate rolling median of previous 3 periods<\/span>\ndf[' <span style=\"color: #ff0000;\">column_name<\/span> ']. <span style=\"color: #3366ff;\">rolling<\/span> (3). <span style=\"color: #3366ff;\">median<\/span> ()\n<\/strong><\/pre>\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: \uc5f4\uc758 \uc774\ub3d9 \uc911\uc559\uac12 \uacc4\uc0b0<\/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: #008000;\">import<\/span> pandas <span style=\"color: #008000;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#createDataFrame\n<\/span><span style=\"color: #000000;\">df = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">month<\/span> ': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12],\n                   ' <span style=\"color: #ff0000;\">leads<\/span> ': [13, 15, 16, 15, 17, 20, 22, 24, 25, 26, 23, 24],\n                   ' <span style=\"color: #ff0000;\">sales<\/span> ': [22, 24, 23, 27, 26, 26, 27, 30, 33, 32, 27, 25]})\n\n<span style=\"color: #008080;\">#view DataFrame\n<\/span>df\n\n\tmonth sales leads\n0 1 13 22\n1 2 15 24\n2 3 16 23\n3 4 15 27\n4 5 17 26\n5 6 20 26\n6 7 22 27\n7 8 24 30\n8 9 25 33\n9 10 26 32\n10 11 23 27\n11 12 24 25\n<\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\uc5ec \uc774\uc804 3\uac1c \uae30\uac04\uc5d0 \ub300\ud55c &#8220;\ud310\ub9e4\uc561&#8221;\uc758 \uc774\ub3d9 \uc911\uc559\uac12\uc744 \ud3ec\ud568\ud558\ub294 \uc0c8 \uc5f4\uc744 \ub9cc\ub4e4 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#calculate 3-month rolling median\n<\/span>df[' <span style=\"color: #ff0000;\">sales_rolling3<\/span> '] = df[' <span style=\"color: #ff0000;\">sales<\/span> ']. <span style=\"color: #3366ff;\">rolling<\/span> (3). <span style=\"color: #3366ff;\">median<\/span> ()\n\n<span style=\"color: #008080;\">#view updated data frame\n<\/span>df\n\n\tmonth leads sales sales_rolling3\n0 1 13 22 NaN\n1 2 15 24 NaN\n2 3 16 23 23.0\n3 4 15 27 24.0\n4 5 17 26 26.0\n5 6 20 26 26.0\n6 7 22 27 26.0\n7 8 24 30 27.0\n8 9 25 33 30.0\n9 10 26 32 32.0\n10 11 23 27 32.0\n11 12 24 25 27.0<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">3\uac1c\uc6d4 \ub3d9\uc548 \ud45c\uc2dc\ub41c \ub864\ub9c1 \uc911\uc559\uac12 \ub9e4\ucd9c\uc774 \uc774\uc804 3\uac1c\uc6d4\uc758 \uc911\uc559\uac12\uc778\uc9c0 \uc218\ub3d9\uc73c\ub85c \ud655\uc778\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\">22, 24, 23\uc758 \uc911\uc559\uac12 = <strong>23.0<\/strong><\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">\ub9c8\ucc2c\uac00\uc9c0\ub85c 4\uac1c\uc6d4\ucc28\uc758 \ub864\ub9c1 \uc911\uc559\uac12 \ud310\ub9e4\ub7c9\uc744 \ud655\uc778\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\">24, 23, 27\uc758 \uc911\uc559\uac12 = <strong>24.0<\/strong><\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">\ube44\uc2b7\ud55c \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\uc5ec 6\uac1c\uc6d4 \uc774\ub3d9 \uc911\uc559\uac12\uc744 \uacc4\uc0b0\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#calculate 6-month rolling median\n<span style=\"color: #000000;\">df['<\/span> <span style=\"color: #ff0000;\">sales_rolling6<\/span> <span style=\"color: #000000;\">'] = df['<\/span> <span style=\"color: #ff0000;\">sales<\/span> <span style=\"color: #000000;\">'].<\/span> <span style=\"color: #3366ff;\">rolling<\/span> <span style=\"color: #000000;\">(6).<\/span> <span style=\"color: #3366ff;\">median<\/span> <span style=\"color: #000000;\">()<\/span><\/span>\n\n<span style=\"color: #008080;\">#view updated data frame\n<\/span>df\n\nmonth leads sales sales_rolling3 sales_rolling6\n0 1 13 22 NaN NaN\n1 2 15 24 NaN NaN\n2 3 16 23 23.0 NaN\n3 4 15 27 24.0 NaN\n4 5 17 26 26.0 NaN\n5 6 20 26 26.0 25.0\n6 7 22 27 26.0 26.0\n7 8 24 30 27.0 26.5\n8 9 25 33 30.0 27.0\n9 10 26 32 32.0 28.5\n10 11 23 27 32.0 28.5\n11 12 24 25 27.0 28.5\n<\/strong><\/pre>\n<h3> <span style=\"color: #000000;\"><strong>\ucd94\uac00 \ub9ac\uc18c\uc2a4<\/strong><\/span><\/h3>\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\/\u1109\u1161\u110b\u1161\u11a8\u1112\u1161\u11ab-\u1105\u1169\u11af\u1105\u1175\u11bc-\u1111\u1162\u11ab\u1103\u1165\/\" target=\"_blank\" rel=\"noopener\">Pandas\uc5d0\uc11c \uc774\ub3d9 \ud3c9\uade0\uc744 \uacc4\uc0b0\ud558\ub294 \ubc29\ubc95<\/a><br \/> <a href=\"https:\/\/statorials.org\/ko\/\u1111\u1162\u11ab\u1103\u1165-\u1109\u1161\u11bc\u1100\u116a\u11ab-\u1100\u116a\u11ab\u1100\u1168-\u1107\u1166\u110b\u1165\u1105\u1175\u11bc\/\" target=\"_blank\" rel=\"noopener\">\ud32c\ub354\uc5d0\uc11c \uc2ac\ub77c\uc774\ub529 \uc0c1\uad00 \uad00\uacc4\ub97c \uacc4\uc0b0\ud558\ub294 \ubc29\ubc95<\/a><br \/> <a href=\"https:\/\/statorials.org\/ko\/\u1111\u1162\u11ab\u1103\u1165\u110b\u1174-\u1107\u1162\u11a8\u1107\u116e\u11ab\u110b\u1172\u11af-\u1107\u1167\u11ab\u1112\u116a\/\" target=\"_blank\" rel=\"noopener\">\ud32c\ub354\uc758 \ubcc0\ud654\uc728\uc744 \uacc4\uc0b0\ud558\ub294 \ubc29\ubc95<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\ub864\ub9c1 \uc911\uc559\uac12\uc740 \uc2dc\uacc4\uc5f4\uc5d0\uc11c \uc774\uc804 \uae30\uac04 \uc218\uc758 \uc911\uc559\uac12\uc785\ub2c8\ub2e4. Pandas DataFrame\uc5d0\uc11c \uc5f4\uc758 \uc774\ub3d9 \uc911\uc559\uac12\uc744 \uacc4\uc0b0\ud558\ub824\uba74 \ub2e4\uc74c \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. #calculate rolling median of previous 3 periods df[&#8216; column_name &#8216;]. rolling (3). median () \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: \uc5f4\uc758 \uc774\ub3d9 \uc911\uc559\uac12 \uacc4\uc0b0 \ub2e4\uc74c\uacfc \uac19\uc740 \ud32c\ub354 DataFrame\uc774 \uc788\ub2e4\uace0 \uac00\uc815\ud569\ub2c8\ub2e4. import pandas as pd [&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-2338","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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