{"id":4106,"date":"2023-07-13T13:24:27","date_gmt":"2023-07-13T13:24:27","guid":{"rendered":"https:\/\/statorials.org\/ko\/%e1%84%8e%e1%85%a6%e1%84%8b%e1%85%b5%e1%86%ab%e1%84%87%e1%85%a7%e1%86%af%e1%84%85%e1%85%a9-%e1%84%8c%e1%85%a5%e1%86%bc%e1%84%85%e1%85%a7%e1%86%af%e1%84%83%e1%85%ac%e1%86%ab-%e1%84%91%e1%85%a2%e1%86%ab\/"},"modified":"2023-07-13T13:24:27","modified_gmt":"2023-07-13T13:24:27","slug":"%e1%84%8e%e1%85%a6%e1%84%8b%e1%85%b5%e1%86%ab%e1%84%87%e1%85%a7%e1%86%af%e1%84%85%e1%85%a9-%e1%84%8c%e1%85%a5%e1%86%bc%e1%84%85%e1%85%a7%e1%86%af%e1%84%83%e1%85%ac%e1%86%ab-%e1%84%91%e1%85%a2%e1%86%ab","status":"publish","type":"post","link":"https:\/\/statorials.org\/ko\/%e1%84%8e%e1%85%a6%e1%84%8b%e1%85%b5%e1%86%ab%e1%84%87%e1%85%a7%e1%86%af%e1%84%85%e1%85%a9-%e1%84%8c%e1%85%a5%e1%86%bc%e1%84%85%e1%85%a7%e1%86%af%e1%84%83%e1%85%ac%e1%86%ab-%e1%84%91%e1%85%a2%e1%86%ab\/","title":{"rendered":"Pandas: \ubb38\uc790\uc5f4 \uc5f4\uc744 \uae30\uc900\uc73c\ub85c dataframe\uc744 \uc815\ub82c\ud558\ub294 \ubc29\ubc95"},"content":{"rendered":"

<\/p>\n

\n

\ub2e4\uc74c \ubc29\ubc95\uc744 \uc0ac\uc6a9\ud558\uc5ec \ud2b9\uc815 \ubb38\uc790\uc5f4 \uc5f4\uc758 \uac12\uc744 \uae30\ubc18\uc73c\ub85c pandas DataFrame\uc758 \ud589\uc744 \uc815\ub82c\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n

\ubc29\ubc95 1: \ubb38\uc790\uc5f4 \uc5f4\ub85c \uc815\ub82c(\uc5f4\uc5d0 \ubb38\uc790\ub9cc \ud3ec\ud568\ub41c \uacbd\uc6b0)<\/strong><\/span><\/p>\n

 df = df. sort_values<\/span> (' my_string_column<\/span> ')\n<\/strong><\/pre>\n
 \ubc29\ubc95 2: \ubb38\uc790\uc5f4 \uc5f4 \uae30\uc900\uc73c\ub85c \uc815\ub82c(\uc5f4\uc5d0 \ubb38\uc790 \uc640<\/em> \uc22b\uc790\uac00 \ud3ec\ud568\ub41c \uacbd\uc6b0)<\/strong><\/span><\/p>\n
 #create 'sort' column that contains digits from 'my_string_column'\n<\/span>df[' sort<\/span> '] = df[' my_string_column<\/span> ']. str<\/span> . extract<\/span> (' (\\d+)<\/span> ', expand= False<\/span> ). astype<\/span> (int)\n<\/span>\n#sort rows based on digits in 'sort' column\n<\/span>df = df. sort_values<\/span> (' sort<\/span> ')\n<\/strong><\/pre>\n
 \ub2e4\uc74c \uc608\uc5d0\uc11c\ub294 \uac01 \ubc29\ubc95\uc744 \uc2e4\uc81c\ub85c \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n
 \uc608 1: \ubb38\uc790\uc5f4 \uc5f4\uc744 \uae30\uc900\uc73c\ub85c \uc815\ub82c(\uc5f4\uc5d0 \ubb38\uc790\ub9cc \ud3ec\ud568\ub41c \uacbd\uc6b0)<\/strong><\/span><\/h2>\n
 \uc2dd\ub8cc\ud488\uc810\uc758 \ub2e4\uc591\ud55c \uc81c\ud488 \ud310\ub9e4\uc5d0 \ub300\ud55c \uc815\ubcf4\uac00 \ud3ec\ud568\ub41c \ub2e4\uc74c\uacfc \uac19\uc740 pandas DataFrame\uc774 \uc788\ub2e4\uace0 \uac00\uc815\ud569\ub2c8\ub2e4.<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#createDataFrame\n<\/span>df = pd. DataFrame<\/span> ({' product<\/span> ': ['Apples', 'Oranges', 'Bananas', 'Lettuce', 'Beans'],\n                   ' sales<\/span> ': [18, 22, 19, 14, 29]})\n\n#view DataFrame\n<\/span>print<\/span> (df)\n\n   product sales\n0 Apples 18\n1 Oranges 22\n2 Bananas 19\n3 Lettuce 14\n4 Beans 29<\/strong><\/pre>\n
 \ub2e4\uc74c \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\uc5ec \uc81c\ud488<\/strong> \uc5f4\uc758 \ubb38\uc790\uc5f4\uc744 \uae30\ubc18\uc73c\ub85c DataFrame\uc758 \ud589\uc744 \uc815\ub82c\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 #sort rows from A to Z based on string in 'product' column\n<\/span>df = df. sort_values<\/span> (' product<\/span> ')\n\n#view updated DataFrame\n<\/span>print<\/span> (df)\n\n   product sales\n0 Apples 18\n2 Bananas 19\n4 Beans 29\n3 Lettuce 14\n1 Oranges 22<\/span><\/span><\/strong><\/pre>\n
 \uc774\uc81c \ud589\uc740 Product<\/strong> \uc5f4\uc758 \ubb38\uc790\uc5f4\uc744 \uae30\uc900\uc73c\ub85c A\ubd80\ud130 Z\uae4c\uc9c0 \uc815\ub82c\ub429\ub2c8\ub2e4.<\/span><\/p>\n
 \ub300\uc2e0\uc5d0 Z\uc5d0\uc11c A\ub85c \uc815\ub82c\ud558\ub824\uba74, \uac04\ub2e8\ud788 ascending=False<\/strong> \uc778\uc218\ub97c \ucd94\uac00\ud558\uba74 \ub429\ub2c8\ub2e4:<\/span><\/p>\n
 #sort rows from Z to A based on string in 'product' column\n<\/span>df = df. sort_values<\/span> (' product<\/span> ', ascending= False<\/span> )\n\n#view updated DataFrame\n<\/span>print<\/span> (df)\n\n   product sales\n1 Oranges 22\n3 Lettuce 14\n4 Beans 29\n2 Bananas 19\n0 Apples 18\n<\/span><\/span><\/strong><\/pre>\n
 \uc774\uc81c \ud589\uc740 Product<\/strong> \uc5f4\uc758 \ubb38\uc790\uc5f4\uc744 \uae30\uc900\uc73c\ub85c Z\uc5d0\uc11c A\ub85c \uc815\ub82c\ub429\ub2c8\ub2e4.<\/span><\/p>\n
 \uc608\uc2dc 2: \ubb38\uc790\uc5f4 \uc5f4 \uae30\uc900 \uc815\ub82c(\uc5f4\uc5d0 \ubb38\uc790 \uc640<\/em> \uc22b\uc790\uac00 \ud3ec\ud568\ub41c \uacbd\uc6b0)<\/strong><\/span><\/h2>\n
 \uc2dd\ub8cc\ud488\uc810\uc758 \ub2e4\uc591\ud55c \uc81c\ud488 \ud310\ub9e4\uc5d0 \ub300\ud55c \uc815\ubcf4\uac00 \ud3ec\ud568\ub41c \ub2e4\uc74c\uacfc \uac19\uc740 pandas DataFrame\uc774 \uc788\ub2e4\uace0 \uac00\uc815\ud569\ub2c8\ub2e4.<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#createDataFrame\n<\/span>df = pd. DataFrame<\/span> ({' product<\/span> ': ['A3', 'A5', 'A22', 'A50', 'A2', 'A7', 'A9', 'A13'],\n                   ' sales<\/span> ': [18, 22, 19, 14, 14, 11, 20, 28]})\n\n#view DataFrame\n<\/span>print<\/span> (df)\n\n  product sales\n0 A3 18\n1 A5 22\n2 A22 19\n3 A50 14\n4 A2 14\n5 A7 11\n6 A9 20\n7 A13 28\n<\/strong><\/pre>\n
 \uc81c\ud488<\/strong> \uc5f4\uc758 \ubb38\uc790\uc5f4\uc5d0\ub294 \ubb38\uc790\uc640 \uc22b\uc790\uac00 \ubaa8\ub450 \ud3ec\ud568\ub418\uc5b4 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 \uc81c\ud488<\/strong> \uc5f4\uc758 \uac12\uc744 \uc0ac\uc6a9\ud558\uc5ec DataFrame\uc758 \ud589\uc744 \uc815\ub82c\ud558\ub824\uace0 \ud558\uba74 \ubb38\uc790\uc5f4\uc774 \uc22b\uc790\ub97c \uae30\uc900\uc73c\ub85c \uc62c\ubc14\ub978 \uc21c\uc11c\ub85c \uc815\ub82c\ub418\uc9c0 \uc54a\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#sort rows based on strings in 'product' column\n<\/span>df = df. sort_values<\/span> (' product<\/span> ')\n\n#view updated DataFrame\n<\/span>print<\/span> (df)\n\n  product sales\n7 A13 28\n4 A2 14\n2 A22 19\n0 A3 18\n1 A5 22\n3 A50 14\n5 A7 11\n6 A9 20\n<\/strong><\/pre>\n
 \ub300\uc2e0 \uc81c\ud488 \uc5f4\uc758 \uc22b\uc790\ub9cc \ud3ec\ud568\ud558\ub294 sort<\/strong> \ub77c\ub294 \uc0c8 \uc784\uc2dc \uc5f4\uc744 \ub9cc\ub4e0 \ub2e4\uc74c \uc815\ub82c<\/strong> \uc5f4\uc758 \uac12\uc744 \uae30\uc900\uc73c\ub85c \uc815\ub82c\ud55c \ub2e4\uc74c \uc5f4\uc744 \uc644\uc804\ud788 \uc0ad\uc81c\ud574\uc57c \ud569\ub2c8\ub2e4.<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#create new 'sort' column that contains digits from 'product' column\n<\/span>df[' sort<\/span> '] = df[' product<\/span> ']. str<\/span> . extract<\/span> (' (\\d+)<\/span> ', expand= False<\/span> ). astype<\/span> (int)\n\n#sort rows based on digits in 'sort' column\n<\/span>df = df. sort_values<\/span> (' sort<\/span> ')\n\n#drop 'sort' column\n<\/span>df = df. drop<\/span> (' sort<\/span> ', axis= 1<\/span> )\n\n#view updated DataFrame\n<\/span>print<\/span> (df)\n\n  product sales\n4 A2 14\n0 A3 18\n1 A5 22\n5 A7 11\n6 A9 20\n7 A13 28\n2 A22 19\n3 A50 14<\/strong><\/pre>\n
 \uc774\uc81c \ud589\uc740 \uc81c\ud488<\/strong> \uc5f4\uc758 \ubb38\uc790\uc5f4\uc744 \uae30\uc900\uc73c\ub85c \uc815\ub82c\ub418\uace0 \uc22b\uc790\ub294 \uc62c\ubc14\ub978 \uc21c\uc11c\ub85c \uc815\ub82c\ub429\ub2c8\ub2e4.<\/span><\/p>\n
 \ucc38\uace0<\/strong> : \uc5ec\uae30\uc5d0\uc11c<\/a> pandas sort_values()<\/strong> \ud568\uc218\uc5d0 \ub300\ud55c \uc804\uccb4 \ubb38\uc11c\ub97c \ucc3e\uc744 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\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
 \ud32c\ub354: \ub0a0\uc9dc\ubcc4\ub85c \uc815\ub82c\ud558\ub294 \ubc29\ubc95<\/a>
 Pandas: \uc774\ub984\ubcc4\ub85c \uc5f4\uc744 \uc815\ub82c\ud558\ub294 \ubc29\ubc95<\/a>
 Pandas: \uc778\ub371\uc2a4\uc640 \uc5f4\uc744 \ubaa8\ub450 \uae30\uc900\uc73c\ub85c \uc815\ub82c\ud558\ub294 \ubc29\ubc95<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
\ub2e4\uc74c \ubc29\ubc95\uc744 \uc0ac\uc6a9\ud558\uc5ec \ud2b9\uc815 \ubb38\uc790\uc5f4 \uc5f4\uc758 \uac12\uc744 \uae30\ubc18\uc73c\ub85c pandas DataFrame\uc758 \ud589\uc744 \uc815\ub82c\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ubc29\ubc95 1: \ubb38\uc790\uc5f4 \uc5f4\ub85c \uc815\ub82c(\uc5f4\uc5d0 \ubb38\uc790\ub9cc \ud3ec\ud568\ub41c \uacbd\uc6b0) df = df. sort_values (‘ my_string_column ‘) \ubc29\ubc95 2: \ubb38\uc790\uc5f4 \uc5f4 \uae30\uc900\uc73c\ub85c \uc815\ub82c(\uc5f4\uc5d0 \ubb38\uc790 \uc640 \uc22b\uc790\uac00 \ud3ec\ud568\ub41c \uacbd\uc6b0) #create ‘sort’ column that contains digits from ‘my_string_column’ df[‘ sort ‘] = df[‘ my_string_column ‘]. […]<\/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-4106","post","type-post","status-publish","format-standard","hentry","category-20"],"yoast_head":"\nPandas: \ubb38\uc790\uc5f4 \uc5f4\uc744 \uae30\ubc18\uc73c\ub85c DataFrame\uc744 \uc815\ub82c\ud558\ub294 \ubc29\ubc95 \u2013 Statorials<\/title>\n<meta name=\"description\" content=\"\uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 \ubb38\uc790\uc5f4 \uc5f4\uc758 \uac12\uc744 \uae30\uc900\uc73c\ub85c pandas DataFrame\uc758 \ud589\uc744 \uc815\ub82c\ud558\ub294 \ubc29\ubc95\uc744 \uc608\uc640 \ud568\uaed8 \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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Statorials\",\"isPartOf\":{\"@id\":\"https:\/\/statorials.org\/ko\/#website\"},\"datePublished\":\"2023-07-13T13:24:27+00:00\",\"dateModified\":\"2023-07-13T13:24:27+00:00\",\"author\":{\"@id\":\"https:\/\/statorials.org\/ko\/#\/schema\/person\/600556789b7d79cbaa9d9f0c721b74f4\"},\"description\":\"\uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 \ubb38\uc790\uc5f4 \uc5f4\uc758 \uac12\uc744 \uae30\uc900\uc73c\ub85c pandas DataFrame\uc758 \ud589\uc744 \uc815\ub82c\ud558\ub294 \ubc29\ubc95\uc744 \uc608\uc640 \ud568\uaed8 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