{"id":4183,"date":"2023-07-13T00:49:45","date_gmt":"2023-07-13T00:49:45","guid":{"rendered":"https:\/\/statorials.org\/id\/filter-dplyr-simpan-na\/"},"modified":"2023-07-13T00:49:45","modified_gmt":"2023-07-13T00:49:45","slug":"filter-dplyr-simpan-na","status":"publish","type":"post","link":"https:\/\/statorials.org\/id\/filter-dplyr-simpan-na\/","title":{"rendered":"Cara memfilter bingkai data tanpa kehilangan garis na menggunakan dplyr"},"content":{"rendered":"

<\/p>\n

\n

Anda dapat menggunakan sintaks dasar berikut untuk memfilter bingkai data tanpa kehilangan baris yang berisi nilai NA menggunakan fungsi dalam paket dplyr<\/strong> dan Tidyr<\/strong> di R:<\/span><\/p>\n

 library<\/span> (dplyr)\nlibrary<\/span> (tidyr)\n\n<\/strong>#filter for rows where team is not equal to 'A' (and keep rows with NA)<\/strong><\/span>\ndf <- df %>% filter((team !=<\/span> ' A<\/span> ') %>% replace_na( TRUE<\/span> ))<\/strong><\/pre>\n
 Perhatikan bahwa rumus ini menggunakan fungsi replace_na()<\/strong> dari paket Tidyr<\/strong> untuk mengonversi nilai NA menjadi TRUE sehingga tidak terhapus dari bingkai data selama pemfilteran.<\/span><\/p>\n
 Contoh berikut menunjukkan cara menggunakan sintaksis ini dalam praktiknya.<\/span><\/p>\n
 Contoh: Filter bingkai data tanpa kehilangan baris NA menggunakan dplyr<\/strong><\/span><\/h2>\n
 Misalkan kita memiliki kerangka data berikut di R yang berisi informasi tentang berbagai pemain bola basket:<\/span><\/p>\n
 #create data frame\n<\/span>df <- data. frame<\/span> (team=c('A', NA, 'A', 'B', NA, 'C', 'C', 'C'),\n                 points=c(18, 13, 19, 14, 24, 21, 20, 28),\n                 assists=c(5, 7, 17, 9, 12, 9, 5, 12))\n\n#view data frame\n<\/span>df\n\n  team points assists\n1 to 18 5\n2 <NA> 13 7\n3 A 19 17\n4 B 14 9\n5 <NA> 24 12\n6 C 21 9\n7 C 20 5\n8 C 28 12\n<\/strong><\/pre>\n
 Sekarang misalkan kita menggunakan fungsi filter()<\/strong> dari paket dplyr<\/strong> untuk memfilter bingkai data agar hanya berisi baris-baris yang nilainya di kolom tim<\/strong> tidak sama dengan A:<\/span><\/span><\/p>\n
 library<\/span> (dplyr)<\/span>\n\n#filter for rows where team is not equal to 'A'<\/span>\ndf <- df %>% filter(team !=<\/span> ' A<\/span> ')\n\n#view updated data frame<\/span>\ndf\n\n  team points assists\n1 B 14 9\n2 C 21 9\n3 C 20 5\n4 C 28 12\n<\/strong><\/pre>\n
 Perhatikan bahwa setiap baris yang nilai di kolom tim<\/strong> sama dengan A telah difilter, termasuk baris yang nilai di kolom tim<\/strong> sama dengan NA.<\/span><\/p>\n
 Jika kita ingin memfilter baris dengan tim<\/strong> yang sama dengan A dan mempertahankan<\/em> baris dengan nilai NA, kita dapat menggunakan sintaks berikut:<\/span><\/p>\n
 library<\/span> (dplyr)\nlibrary<\/span> (tidyr)\n\n<\/strong>#filter for rows where team is not equal to 'A' (and keep rows with NA)<\/strong><\/span>\ndf <- df %>% filter((team !=<\/span> ' A<\/span> ') %>% replace_na( TRUE<\/span> ))\n\n#view updated data frame<\/span>\ndf\n\n  team points assists\n1 <NA> 13 7\n2 B 14 9\n3 <NA> 24 12\n4 C 21 9\n5 C 20 5\n6 C 28 12\n<\/strong><\/pre>\n
 Perhatikan bahwa setiap baris yang nilai di kolom tim<\/strong> sama dengan A telah difilter, namun kami tetap mempertahankan baris yang nilai di kolom tim<\/strong> sama dengan NA.<\/span><\/p>\n
 Catatan<\/strong> : Anda dapat menemukan dokumentasi lengkap untuk fungsi Tidyr replace_na()<\/strong> di sini<\/a> .<\/span><\/p>\n
 Sumber daya tambahan<\/strong><\/span><\/h2>\n
 Tutorial berikut menjelaskan cara menjalankan fungsi umum lainnya di dplyr:<\/span><\/p>\n
 Cara memfilter berdasarkan nomor baris menggunakan dplyr<\/a>
 Cara memfilter berdasarkan beberapa kondisi menggunakan dplyr
 Cara menggunakan filter “tidak termasuk” di dplyr<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
Anda dapat menggunakan sintaks dasar berikut untuk memfilter bingkai data tanpa kehilangan baris yang berisi nilai NA menggunakan fungsi dalam paket dplyr dan Tidyr di R: library (dplyr) library (tidyr) #filter for rows where team is not equal to ‘A’ (and keep rows with NA) df <- df %>% filter((team != ‘ A ‘) %>% […]<\/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 bingkai data tanpa kehilangan baris NA menggunakan dplyr - Statologi<\/title>\n<meta name=\"description\" content=\"Tutorial ini menjelaskan cara memfilter bingkai data tanpa kehilangan baris dengan nilai NA menggunakan paket dplyr di R.\" \/>\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\/filter-dplyr-simpan-na\/\" \/>\n<meta property=\"og:locale\" content=\"id_ID\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Cara memfilter bingkai data tanpa kehilangan baris NA menggunakan dplyr - Statologi\" \/>\n<meta property=\"og:description\" content=\"Tutorial ini menjelaskan cara memfilter bingkai data tanpa kehilangan baris dengan nilai NA menggunakan paket dplyr di R.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/statorials.org\/id\/filter-dplyr-simpan-na\/\" \/>\n<meta property=\"og:site_name\" content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-13T00:49:45+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=\"2 menit\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/statorials.org\/id\/filter-dplyr-simpan-na\/\",\"url\":\"https:\/\/statorials.org\/id\/filter-dplyr-simpan-na\/\",\"name\":\"Cara memfilter bingkai data tanpa kehilangan baris NA menggunakan dplyr - Statologi\",\"isPartOf\":{\"@id\":\"https:\/\/statorials.org\/id\/#website\"},\"datePublished\":\"2023-07-13T00:49:45+00:00\",\"dateModified\":\"2023-07-13T00:49:45+00:00\",\"author\":{\"@id\":\"https:\/\/statorials.org\/id\/#\/schema\/person\/3d17a1160dd2d052b7c78e502cb9ec81\"},\"description\":\"Tutorial ini menjelaskan cara memfilter bingkai data tanpa kehilangan baris dengan nilai NA menggunakan paket dplyr di R.\",\"breadcrumb\":{\"@id\":\"https:\/\/statorials.org\/id\/filter-dplyr-simpan-na\/#breadcrumb\"},\"inLanguage\":\"id\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/statorials.org\/id\/filter-dplyr-simpan-na\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/statorials.org\/id\/filter-dplyr-simpan-na\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\/\/statorials.org\/id\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Cara memfilter bingkai data tanpa kehilangan garis na menggunakan dplyr\"}]},{\"@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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