{"id":3422,"date":"2023-07-17T13:40:39","date_gmt":"2023-07-17T13:40:39","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%a1%e1%84%8b%e1%85%b3%e1%86%b7%e1%84%8b%e1%85%b3%e1%84%85%e1%85%a9-%e1%84%89%e1%85%b5%e1%84%8c%e1%85%a1%e1%86%a8\/"},"modified":"2023-07-17T13:40:39","modified_gmt":"2023-07-17T13:40:39","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%a1%e1%84%8b%e1%85%b3%e1%86%b7%e1%84%8b%e1%85%b3%e1%84%85%e1%85%a9-%e1%84%89%e1%85%b5%e1%84%8c%e1%85%a1%e1%86%a8","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%a1%e1%84%8b%e1%85%b3%e1%86%b7%e1%84%8b%e1%85%b3%e1%84%85%e1%85%a9-%e1%84%89%e1%85%b5%e1%84%8c%e1%85%a1%e1%86%a8\/","title":{"rendered":"Pandas: \ubb38\uc790\uc5f4\ub85c \uc2dc\uc791\ud558\uc9c0 \uc54a\ub294 \uc904\uc744 \uc120\ud0dd\ud558\ub294 \ubc29\ubc95"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">\ub2e4\uc74c \uae30\ubcf8 \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\uc5ec Pandas DataFrame\uc5d0\uc11c \ud2b9\uc815 \ubb38\uc790\uc5f4\ub85c \uc2dc\uc791\ud558\uc9c0 \uc54a\ub294 \ud589\uc744 \uc120\ud0dd\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>df[~df. <span style=\"color: #3366ff;\">my_column<\/span> . <span style=\"color: #3366ff;\">str<\/span> . <span style=\"color: #3366ff;\">startswith<\/span> ((' <span style=\"color: #ff0000;\">this<\/span> ', ' <span style=\"color: #ff0000;\">that<\/span> '))]\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\uc774 \ud2b9\uc815 \uacf5\uc2dd\uc740 <strong>my_column<\/strong> \uc774\ub77c\ub294 \uc5f4\uc774 <strong>this<\/strong> \ub610\ub294 <strong>that<\/strong> \ubb38\uc790\uc5f4\ub85c \uc2dc\uc791\ud558\uc9c0 \uc54a\ub294 DataFrame\uc758 \ubaa8\ub4e0 \ud589\uc744 \uc120\ud0dd\ud569\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: Pandas\uc5d0\uc11c \ubb38\uc790\uc5f4\ub85c \uc2dc\uc791\ud558\uc9c0 \uc54a\ub294 \uc904 \uc120\ud0dd<\/strong><\/span><\/h2>\n<p> <span style=\"color: #000000;\">\ub2e4\uc591\ud55c \ub9e4\uc7a5\uc758 \ud310\ub9e4 \uc815\ubcf4\uac00 \ud3ec\ud568\ub41c \ub2e4\uc74c\uacfc \uac19\uc740 pandas DataFrame\uc774 \uc788\ub2e4\uace0 \uac00\uc815\ud574 \ubcf4\uaca0\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\n<span style=\"color: #008080;\">#createDataFrame<\/span>\ndf = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">store<\/span> ': ['Upper East', 'Upper West', 'Lower East', 'West', 'CTR'],\n                   ' <span style=\"color: #ff0000;\">sales<\/span> ': [150, 224, 250, 198, 177]})\n\n<span style=\"color: #008080;\">#view DataFrame\n<\/span><span style=\"color: #008000;\">print<\/span> (df)\n\n        blind sales\n0 Upper East 150\n1 Upper West 224\n2 Lower East 250\n3 West 198\n4 CTR 177     \n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\uc5ec <strong>Store<\/strong> \uc5f4\uc5d0\uc11c &#8220;Upper&#8221; \ub610\ub294 &#8220;Lower&#8221; \ubb38\uc790\uc5f4\ub85c \uc2dc\uc791\ud558\uc9c0 \uc54a\ub294 DataFrame\uc758 \ubaa8\ub4e0 \ud589\uc744 \uc120\ud0dd\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <span style=\"color: #000000;\"><strong><span style=\"color: #008080;\">#select all rows where store does not start with 'Upper' or 'Lower'\n<span style=\"color: #000000;\">df[~df. <span style=\"color: #3366ff;\">blind<\/span> . <span style=\"color: #3366ff;\">str<\/span> . <span style=\"color: #3366ff;\">startswith<\/span> ((' <span style=\"color: #ff0000;\">Upper<\/span> ',' <span style=\"color: #ff0000;\">Lower<\/span> '))]\n\n\tblind sales\n3 West 198\n4 CTR 177<\/span><\/span><\/strong><\/span><\/pre>\n<p> <span style=\"color: #000000;\">\ubc18\ud658\ub418\ub294 \uc720\uc77c\ud55c \ud589\uc740 <strong>\uc0c1\uc810<\/strong> \uc5f4\uc774 &#8220;Upper&#8221; \ub610\ub294 &#8220;Lower&#8221;\ub85c \uc2dc\uc791\ud558\uc9c0 \uc54a\ub294 \ud589\uc785\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uc6d0\ud55c\ub2e4\uba74, <strong>Startingswith()<\/strong> \ud568\uc218 \uc678\ubd80\uc5d0\uc11c \ubb38\uc790\uc5f4 \ud29c\ud50c\uc744 \uc815\uc758\ud560 \uc218\ub3c4 \uc788\uc2b5\ub2c8\ub2e4:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <span style=\"color: #000000;\"><strong><span style=\"color: #008080;\">#define tuple of strings\n<span style=\"color: #000000;\">some_strings = (' <span style=\"color: #ff0000;\">Upper<\/span> ', ' <span style=\"color: #ff0000;\">Lower<\/span> ')\n<\/span>\n#select all rows where store does not start with strings in tuple\n<span style=\"color: #000000;\">df[~df. <span style=\"color: #3366ff;\">blind<\/span> . <span style=\"color: #3366ff;\">str<\/span> . <span style=\"color: #3366ff;\">startswith<\/span> (some_strings)]\n\n\tblind sales\n3 West 198\n4 CTR 177<\/span><\/span><\/strong><\/span><\/pre>\n<p> <span style=\"color: #000000;\">\uc774\ub294 \uc774\uc804 \ubc29\ubc95\uacfc \ub3d9\uc77c\ud55c \uacb0\uacfc\ub97c \uc0dd\uc131\ud569\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>\ucc38\uace0<\/strong> : <a href=\"https:\/\/pandas.pydata.org\/docs\/reference\/api\/pandas.Series.str.startswith.html\" target=\"_blank\" rel=\"noopener\">\uc5ec\uae30\uc5d0\uc11c<\/a> pandas\uc758 <b>startwith<\/b> \ud568\uc218\uc5d0 \ub300\ud55c \uc804\uccb4 \ubb38\uc11c\ub97c \ucc3e\uc744 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/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\/pandas\u1102\u1173\u11ab-\u1106\u116e\u11ab\u110c\u1161\u110b\u1167\u11af-\u1100\u1175\u11af\u110b\u1175\u1105\u1169-\u1105\u1161\u110b\u1175\u11ab\u110b\u1173\u11af-\u1111\u1175\u11af\u1110\u1165\u1105\u1175\u11bc\u1112\u1161\u11b8\u1102\u1175\u1103\u1161.\/\" target=\"_blank\" rel=\"noopener\">Pandas: \ubb38\uc790\uc5f4 \uae38\uc774\ub97c \uae30\uc900\uc73c\ub85c \ud589\uc744 \ud544\ud130\ub9c1\ud558\ub294 \ubc29\ubc95<\/a><br \/> <a href=\"https:\/\/statorials.org\/ko\/pandas\u1102\u1173\u11ab-\u110b\u1167\u11af\u110b\u1166-\u1106\u116e\u11ab\u110c\u1161\u110b\u1167\u11af\u110b\u1175-\u1111\u1169\u1112\u1161\u11b7\u1103\u116c\u110b\u1165-\u110b\u1175\u11bb\u1102\u1173\u11ab\u110c\u1175-\u1112\u116a\u11a8\u110b\u1175\u11ab\u1112\u1161\u11b8\u1102\u1175\u1103\u1161.\/\" target=\"_blank\" rel=\"noopener\">Pandas:\uc5f4\uc5d0 \ubb38\uc790\uc5f4\uc774 \ud3ec\ud568\ub418\uc5b4 \uc788\ub294\uc9c0 \ud655\uc778\ud558\ub294 \ubc29\ubc95<\/a><br \/> <a href=\"https:\/\/statorials.org\/ko\/pandas-groupby-\u1106\u116e\u11ab\u110c\u1161\u110b\u1167\u11af-\u110b\u1167\u11ab\u1100\u1167\u11af\/\" target=\"_blank\" rel=\"noopener\">Pandas: GroupBy\ub97c \uc0ac\uc6a9\ud558\uc5ec \ubb38\uc790\uc5f4\uc744 \uc5f0\uacb0\ud558\ub294 \ubc29\ubc95<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\ub2e4\uc74c \uae30\ubcf8 \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\uc5ec Pandas DataFrame\uc5d0\uc11c \ud2b9\uc815 \ubb38\uc790\uc5f4\ub85c \uc2dc\uc791\ud558\uc9c0 \uc54a\ub294 \ud589\uc744 \uc120\ud0dd\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. df[~df. my_column . str . startswith ((&#8216; this &#8216;, &#8216; that &#8216;))] \uc774 \ud2b9\uc815 \uacf5\uc2dd\uc740 my_column \uc774\ub77c\ub294 \uc5f4\uc774 this \ub610\ub294 that \ubb38\uc790\uc5f4\ub85c \uc2dc\uc791\ud558\uc9c0 \uc54a\ub294 DataFrame\uc758 \ubaa8\ub4e0 \ud589\uc744 \uc120\ud0dd\ud569\ub2c8\ub2e4. \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. \uc608: Pandas\uc5d0\uc11c \ubb38\uc790\uc5f4\ub85c \uc2dc\uc791\ud558\uc9c0 \uc54a\ub294 [&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-3422","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: \ubb38\uc790\uc5f4\ub85c \uc2dc\uc791\ud558\uc9c0 \uc54a\ub294 \uc904\uc744 \uc120\ud0dd\ud558\ub294 \ubc29\ubc95 \u2013 Statorials<\/title>\n<meta name=\"description\" content=\"\uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 \uc608\uc81c\ub97c \ud3ec\ud568\ud558\uc5ec \ud2b9\uc815 \ubb38\uc790\uc5f4\ub85c \uc2dc\uc791\ud558\uc9c0 \uc54a\ub294 pandas DataFrame\uc758 \ubaa8\ub4e0 \ud589\uc744 \uc120\ud0dd\ud558\ub294 \ubc29\ubc95\uc744 \uc124\uba85\ud569\ub2c8\ub2e4.\" \/>\n<meta name=\"robots\" content=\"index, follow, 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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%a1%e1%84%8b%e1%85%b3%e1%86%b7%e1%84%8b%e1%85%b3%e1%84%85%e1%85%a9-%e1%84%89%e1%85%b5%e1%84%8c%e1%85%a1%e1%86%a8\/\",\"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%a1%e1%84%8b%e1%85%b3%e1%86%b7%e1%84%8b%e1%85%b3%e1%84%85%e1%85%a9-%e1%84%89%e1%85%b5%e1%84%8c%e1%85%a1%e1%86%a8\/\",\"name\":\"Pandas: \ubb38\uc790\uc5f4\ub85c \uc2dc\uc791\ud558\uc9c0 \uc54a\ub294 \uc904\uc744 \uc120\ud0dd\ud558\ub294 \ubc29\ubc95 \u2013 Statorials\",\"isPartOf\":{\"@id\":\"https:\/\/statorials.org\/ko\/#website\"},\"datePublished\":\"2023-07-17T13:40:39+00:00\",\"dateModified\":\"2023-07-17T13:40:39+00:00\",\"author\":{\"@id\":\"https:\/\/statorials.org\/ko\/#\/schema\/person\/600556789b7d79cbaa9d9f0c721b74f4\"},\"description\":\"\uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 \uc608\uc81c\ub97c \ud3ec\ud568\ud558\uc5ec \ud2b9\uc815 \ubb38\uc790\uc5f4\ub85c \uc2dc\uc791\ud558\uc9c0 \uc54a\ub294 pandas DataFrame\uc758 \ubaa8\ub4e0 \ud589\uc744 \uc120\ud0dd\ud558\ub294 \ubc29\ubc95\uc744 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