{"id":945,"date":"2023-07-28T05:49:15","date_gmt":"2023-07-28T05:49:15","guid":{"rendered":"https:\/\/statorials.org\/id\/menyaring-baris-r\/"},"modified":"2023-07-28T05:49:15","modified_gmt":"2023-07-28T05:49:15","slug":"menyaring-baris-r","status":"publish","type":"post","link":"https:\/\/statorials.org\/id\/menyaring-baris-r\/","title":{"rendered":"Cara memfilter baris di r"},"content":{"rendered":"

<\/p>\n

\n

Seringkali Anda mungkin tertarik pada subset bingkai data berdasarkan kondisi tertentu di R. Untungnya, hal ini mudah dilakukan menggunakan fungsi filter()<\/a> dari paket dplyr<\/a> .<\/span><\/p>\n

 library(dplyr)<\/strong><\/pre>\n
 Tutorial ini menjelaskan beberapa contoh cara praktis menggunakan fitur ini menggunakan dataset dplyr bawaan yang disebut starwars<\/strong> :<\/span><\/p>\n
 #view first six rows of starwars dataset<\/span>\nhead(starwars)\n\n# A tibble: 6 x 13\n  name height mass hair_color skin_color eye_color birth_year gender homeworld\n                                   \n1 Luke~ 172 77 blond fair blue 19 male Tatooine \n2 C-3PO 167 75 <NA> gold yellow 112 <NA> Tatooine \n3 R2-D2 96 32 <NA> white, bl~ red 33 <NA> Naboo    \n4 Dart~ 202 136 none white yellow 41.9 male Tatooine \n5 Leia~ 150 49 brown light brown 19 female Alderaan \n6 Owen~ 178 120 brown, gr~ light blue 52 male Tatooine \n# ... with 4 more variables: species , films , vehicles ,\n# starships \n<\/strong><\/pre>\n
 Contoh 1: Filter baris yang sama dengan nilai tertentu<\/span><\/strong><\/h3>\n
 Kode berikut menunjukkan cara memfilter kumpulan data untuk baris yang variabel “spesies” sama dengan Droid.<\/span><\/p>\n
 starwars %>% filter(species == ' Droid<\/span> ')\n\n# A tibble: 5 x 13\n  name height mass hair_color skin_color eye_color birth_year gender homeworld\n                                   \n1 C-3PO 167 75 gold yellow 112 Tatooine \n2 R2-D2 96 32 white, bl~ red 33 Naboo    \n3 R5-D4 97 32 white, red red NA Tatooine \n4 IG-88 200 140 none metal red 15 none        \n5 BB8 NA NA none none black NA none        \n# ... with 4 more variables: species , films , vehicles ,\n# starships \n<\/strong><\/pre>\n
 Kita dapat melihat bahwa 5 baris dataset memenuhi kondisi ini, seperti yang ditunjukkan oleh #A tibble: 5 x 13<\/em> .<\/span><\/p>\n
 Contoh 2: Filter Baris Menggunakan \u201cDan\u201d<\/span><\/strong><\/h3>\n
 Kita juga dapat memfilter baris yang spesiesnya adalah Droid dan<\/strong> warna matanya merah:<\/span><\/p>\n
 starwars %>% filter(species == ' Droid<\/span> ' &<\/span> eye_color == ' red<\/span> ')\n\n# A tibble: 3 x 13\n  name height mass hair_color skin_color eye_color birth_year gender homeworld\n                                   \n1 R2-D2 96 32 <NA> white, bl~ red 33 <NA> Naboo    \n2 R5-D4 97 32 <NA> white, red red NA <NA> Tatooine \n3 IG-88 200 140 none metal red 15 none <NA>      \n# ... with 4 more variables: species , films , vehicles ,\n# starships \n<\/strong><\/pre>\n
 Kita dapat melihat bahwa 3 baris dalam dataset memenuhi kondisi ini.<\/span><\/p>\n
 Contoh 3: Filter Baris Menggunakan \u201cAtau\u201d<\/span><\/strong><\/h3>\n
 Kita juga dapat memfilter baris yang spesiesnya Droid atau<\/strong> warna matanya merah:<\/span><\/p>\n
 starwars %>% filter(species == ' Droid<\/span> ' |<\/span> eye_color == ' red<\/span> ')\n\n# A tibble: 7 x 13\n  name height mass hair_color skin_color eye_color birth_year gender homeworld\n                                   \n1 C-3PO 167 75 <NA> gold yellow 112 <NA> Tatooine \n2 R2-D2 96 32 <NA> white, bl~ red 33 <NA> Naboo    \n3 R5-D4 97 32 <NA> white, red red NA <NA> Tatooine \n4 IG-88 200 140 none metal red 15 none <NA>     \n5 Bossk 190 113 none green red 53 male Trandosha\n6 Nute~ 191 90 none mottled g~ red NA male Cato Nei~\n7 BB8 NA NA none none black NA none <NA>     \n# ... with 4 more variables: species , films , vehicles ,\n# starships  \n<\/strong><\/pre>\n
 Kita dapat melihat bahwa 7 baris dalam dataset memenuhi kondisi ini.<\/span><\/p>\n
 Contoh 4: Filter baris dengan nilai dalam daftar<\/span><\/strong><\/h3>\n
 Kita juga dapat memfilter baris tempat warna mata muncul dalam daftar warna:<\/span><\/p>\n
 starwars %>% filter(eye_color %in%<\/span> c(' blue<\/span> ', ' yellow<\/span> ', ' red<\/span> '))\n\n# A tibble: 35 x 13\n   name height mass hair_color skin_color eye_color birth_year gender\n                               \n 1 Luke~ 172 77 blond fair blue 19 male  \n 2 C-3PO 167 75 <NA> gold yellow 112 <NA> \n 3 R2-D2 96 32 <NA> white, bl~ red 33 <NA>  \n 4 Dart~ 202 136 none white yellow 41.9 male  \n 5 Owen~ 178 120 brown, gr~ light blue 52 male  \n 6 Beru~ 165 75 brown light blue 47 female\n 7 R5-D4 97 32 <NA> white, red red NA <NA> \n 8 Anak~ 188 84 blond fair blue 41.9 male  \n 9 Wilh~ 180 NA auburn, g~ fair blue 64 male  \n10 Chew~ 228 112 brown unknown blue 200 male  \n# ... with 25 more rows, and 5 more variables: homeworld, species,\n# films, vehicles, starships  \n<\/strong><\/pre>\n
 Kita dapat melihat bahwa 35 baris dalam dataset memiliki warna mata biru, kuning, atau merah.<\/span><\/p>\n
 Terkait:<\/span><\/strong> Cara Menggunakan Operator %in% di R (Dengan Contoh)<\/a><\/p>\n
 Contoh 5: Filter baris menggunakan kurang dari atau lebih besar dari<\/span><\/strong><\/h3>\n
 Kita juga dapat memfilter baris menggunakan operasi yang lebih kecil dari atau lebih besar dari pada variabel numerik:<\/span><\/p>\n
 #find rows where height is greater than 250<\/span>\nstarwars %>% filter(height ><\/span> 250)\n\n# A tibble: 1 x 13\n  name height mass hair_color skin_color eye_color birth_year gender homeworld\n                                   \n1 Yara~ 264 NA none white yellow NA male Quermia  \n# ... with 4 more variables: species , films , vehicles ,\n# starships   \n\n#find rows where height is between 200 and 220<\/span>\nstarwars %>% filter(height ><\/span> 200 &<\/span> height <<\/span> 220)\n\n# A tibble: 5 x 13\n  name height mass hair_color skin_color eye_color birth_year gender homeworld\n                                   \n1 Dart~ 202 136 none white yellow 41.9 male Tatooine \n2 Rugo~ 206 NA none green orange NA male Naboo    \n3 Taun~ 213 NA none gray black NA female Kamino   \n4 Grie~ 216 159 none brown, wh~ green, y~ NA male Kalee    \n5 Tion~ 206 80 none gray black NA male Utapau   \n# ... with 4 more variables: species , films , vehicles ,\n# starships \n\n#find rows where height is above the average height\nstarwars %>% filter(height ><\/span> mean<\/span> (height, na.rm = TRUE<\/span> ))\n\n# A tibble: 51 x 13\n   name height mass hair_color skin_color eye_color birth_year gender\n                               \n 1 Dart~ 202 136 none white yellow 41.9 male  \n 2 Owen~ 178 120 brown, gr~ light blue 52 male  \n 3 Bigg~ 183 84 black light brown 24 male  \n 4 Obi-~ 182 77 auburn, w~ fair blue-gray 57 male  \n 5 Anak~ 188 84 blond fair blue 41.9 male  \n 6 Wilh~ 180 NA auburn, g~ fair blue 64 male  \n 7 Chew~ 228 112 brown unknown blue 200 male  \n 8 Han ~ 180 80 brown fair brown 29 male  \n 9 Jabb~ 175 1358 <NA> green-tan~ orange 600 herma~\n10 Jek ~ 180 110 brown fair blue NA male  \n# ... with 41 more rows, and 5 more variables: homeworld, species,\n# films, vehicles, starships<\/span><\/span>\n<\/strong><\/pre>\n
Seringkali Anda mungkin tertarik pada subset bingkai data berdasarkan kondisi tertentu di R. Untungnya, hal ini mudah dilakukan menggunakan fungsi filter() dari paket dplyr . library(dplyr) Tutorial ini menjelaskan beberapa contoh cara praktis menggunakan fitur ini menggunakan dataset dplyr bawaan yang disebut starwars : #view first six rows of starwars dataset head(starwars) # A tibble: […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11],"tags":[],"yoast_head":"\nCara memfilter baris di R \u2013 Statorials<\/title>\n<meta name=\"description\" content=\"Penjelasan sederhana tentang cara memfilter data di R menggunakan fungsi filter() dari paket dplyr.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/statorials.org\/id\/menyaring-baris-r\/\" \/>\n<meta property=\"og:locale\" content=\"id_ID\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Cara memfilter baris di R \u2013 Statorials\" \/>\n<meta property=\"og:description\" content=\"Penjelasan sederhana tentang cara memfilter data di R menggunakan fungsi filter() dari paket dplyr.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/statorials.org\/id\/menyaring-baris-r\/\" \/>\n<meta property=\"og:site_name\" content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-28T05:49:15+00:00\" \/>\n<meta name=\"author\" content=\"Benjamin anderson\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Ditulis oleh\" \/>\n\t<meta name=\"twitter:data1\" content=\"Benjamin anderson\" \/>\n\t<meta name=\"twitter:label2\" content=\"Estimasi waktu membaca\" \/>\n\t<meta name=\"twitter:data2\" content=\"4 menit\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/statorials.org\/id\/menyaring-baris-r\/\",\"url\":\"https:\/\/statorials.org\/id\/menyaring-baris-r\/\",\"name\":\"Cara memfilter baris di R \u2013 Statorials\",\"isPartOf\":{\"@id\":\"https:\/\/statorials.org\/id\/#website\"},\"datePublished\":\"2023-07-28T05:49:15+00:00\",\"dateModified\":\"2023-07-28T05:49:15+00:00\",\"author\":{\"@id\":\"https:\/\/statorials.org\/id\/#\/schema\/person\/3d17a1160dd2d052b7c78e502cb9ec81\"},\"description\":\"Penjelasan sederhana tentang cara memfilter data di R menggunakan fungsi filter() dari paket dplyr.\",\"breadcrumb\":{\"@id\":\"https:\/\/statorials.org\/id\/menyaring-baris-r\/#breadcrumb\"},\"inLanguage\":\"id\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/statorials.org\/id\/menyaring-baris-r\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/statorials.org\/id\/menyaring-baris-r\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\/\/statorials.org\/id\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Cara memfilter baris di r\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/statorials.org\/id\/#website\",\"url\":\"https:\/\/statorials.org\/id\/\",\"name\":\"Statorials\",\"description\":\"Panduan anda untuk kompetensi statistik!\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/statorials.org\/id\/?s={search_term_string}\"},\"query-input\":\"required name=search_term_string\"}],\"inLanguage\":\"id\"},{\"@type\":\"Person\",\"@id\":\"https:\/\/statorials.org\/id\/#\/schema\/person\/3d17a1160dd2d052b7c78e502cb9ec81\",\"name\":\"Benjamin anderson\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"id\",\"@id\":\"https:\/\/statorials.org\/id\/#\/schema\/person\/image\/\",\"url\":\"http:\/\/statorials.org\/id\/wp-content\/uploads\/2023\/10\/Dr.-Benjamin-Anderson-96x96.jpg\",\"contentUrl\":\"http:\/\/statorials.org\/id\/wp-content\/uploads\/2023\/10\/Dr.-Benjamin-Anderson-96x96.jpg\",\"caption\":\"Benjamin anderson\"},\"description\":\"Halo, saya Benjamin, pensiunan profesor statistika yang menjadi guru Statorial yang berdedikasi. 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 Anda dapat menemukan dokumentasi lengkap untuk fungsi filter()<\/strong> di sini<\/a> .<\/em><\/span><\/p>\n","protected":false},"excerpt":{"rendered":"