{"id":2477,"date":"2023-07-22T02:43:48","date_gmt":"2023-07-22T02:43:48","guid":{"rendered":"https:\/\/statorials.org\/id\/pandas-memperhitungkan-nilai-yang-hilang\/"},"modified":"2023-07-22T02:43:48","modified_gmt":"2023-07-22T02:43:48","slug":"pandas-memperhitungkan-nilai-yang-hilang","status":"publish","type":"post","link":"https:\/\/statorials.org\/id\/pandas-memperhitungkan-nilai-yang-hilang\/","title":{"rendered":"Cara memperhitungkan nilai yang hilang di panda (termasuk contoh)"},"content":{"rendered":"

<\/p>\n

\n

Anda dapat menggunakan sintaks dasar berikut untuk memperhitungkan nilai yang hilang dalam pandas DataFrame:<\/span><\/p>\n

 df[' column_name<\/span> '] = df[' column_name<\/span> ']. interpolate<\/span> ()\n<\/strong><\/pre>\n
 Contoh berikut menunjukkan cara menggunakan sintaksis ini dalam praktiknya.<\/span><\/p>\n
 Contoh: Interpolasi Nilai yang Hilang di Pandas<\/strong><\/span><\/h3>\n
 Katakanlah kita memiliki panda DataFrame berikut yang menunjukkan total penjualan yang dilakukan oleh sebuah toko selama 15 hari berturut-turut:<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\nimport<\/span> numpy as<\/span> np\n\n#createDataFrame\n<\/span>df = pd. DataFrame<\/span> ({' day<\/span> ': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15],\n                   ' sales<\/span> ': [3, 6, 8, 10, 14, 17, 20, np.nan, np.nan, np.nan,\n                             np.nan, 35, 39, 44, 49]})\n\n#view DataFrame\n<\/span>print<\/span> (df)\n\n    day sales\n0 1 3.0\n1 2 6.0\n2 3 8.0\n3 4 10.0\n4 5 14.0\n5 6 17.0\n6 7 20.0\n7 8 NaN\n8 9 NaN\n9 10 NaN\n10 11 NaN\n11 12 35.0\n12 13 39.0\n13 14 44.0\n14 15 49.0<\/strong><\/pre>\n
 Perhatikan bahwa kami kehilangan angka penjualan selama empat hari dalam kerangka data.<\/span><\/p>\n
 Jika kita membuat diagram garis sederhana untuk memvisualisasikan penjualan dari waktu ke waktu, tampilannya akan seperti ini:<\/span> <\/p>\n
 #create line chart to visualize sales\n<\/span>df[' sales<\/span> ']. plot<\/span> ()\n<\/strong><\/pre>\n
\"menyalahkan<\/p>\n
 Untuk mengisi nilai yang hilang, kita dapat menggunakan fungsi interpolate()<\/strong> sebagai berikut:<\/span><\/p>\n
 #interpolate missing values in 'sales' column\n<\/span>df[' sales<\/span> '] = df[' sales<\/span> ']. interpolate<\/span> ()\n\n#view DataFrame\n<\/span>print<\/span> (df)\n\n    day sales\n0 1 3.0\n1 2 6.0\n2 3 8.0\n3 4 10.0\n4 5 14.0\n5 6 17.0\n6 7 20.0\n7 8 23.0\n8 9 26.0\n9 10 29.0\n10 11 32.0\n11 12 35.0\n12 13 39.0\n13 14 44.0\n14 15 49.0<\/strong><\/pre>\n
 Perhatikan bahwa setiap nilai yang hilang telah diganti.<\/span><\/p>\n
 Jika kita membuat diagram garis lain untuk memvisualisasikan bingkai data yang diperbarui, tampilannya akan seperti ini:<\/span> <\/p>\n
 #create line chart to visualize sales\n<\/span>df[' sales<\/span> ']. plot<\/span> ()\n<\/strong><\/pre>\n
\"\"<\/p>\n
 Perhatikan bahwa nilai yang dipilih oleh fungsi interpolate()<\/strong> tampaknya cukup cocok dengan tren data.<\/span><\/p>\n
 Catatan<\/strong> : Anda dapat menemukan dokumentasi lengkap untuk fungsi interpolate()<\/strong> di sini<\/a> .<\/span><\/p>\n
 Sumber daya tambahan<\/strong><\/span><\/h3>\n
 Tutorial berikut memberikan informasi tambahan tentang cara menangani nilai yang hilang di panda:<\/span><\/p>\n
 Cara menghitung nilai yang hilang di panda<\/a>
 Bagaimana cara mengganti nilai NaN dengan string di Pandas<\/a>
 Bagaimana cara mengganti nilai NaN dengan nol di Pandas<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
Anda dapat menggunakan sintaks dasar berikut untuk memperhitungkan nilai yang hilang dalam pandas DataFrame: df[‘ column_name ‘] = df[‘ column_name ‘]. interpolate () Contoh berikut menunjukkan cara menggunakan sintaksis ini dalam praktiknya. Contoh: Interpolasi Nilai yang Hilang di Pandas Katakanlah kita memiliki panda DataFrame berikut yang menunjukkan total penjualan yang dilakukan oleh sebuah toko selama […]<\/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 memperhitungkan nilai yang hilang di panda (termasuk contoh) - Statorials<\/title>\n<meta name=\"description\" content=\"Tutorial ini menjelaskan cara memperhitungkan nilai yang hilang di pandas DataFrame, dengan sebuah contoh.\" \/>\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\/pandas-memperhitungkan-nilai-yang-hilang\/\" \/>\n<meta property=\"og:locale\" content=\"id_ID\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Cara memperhitungkan nilai yang hilang di panda (termasuk contoh) - Statorials\" \/>\n<meta property=\"og:description\" content=\"Tutorial ini menjelaskan cara memperhitungkan nilai yang hilang di pandas DataFrame, dengan sebuah contoh.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/statorials.org\/id\/pandas-memperhitungkan-nilai-yang-hilang\/\" \/>\n<meta property=\"og:site_name\" content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-22T02:43:48+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/imputerpandas1.png\" \/>\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=\"1 menit\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/statorials.org\/id\/pandas-memperhitungkan-nilai-yang-hilang\/\",\"url\":\"https:\/\/statorials.org\/id\/pandas-memperhitungkan-nilai-yang-hilang\/\",\"name\":\"Cara memperhitungkan nilai yang hilang di panda (termasuk contoh) - Statorials\",\"isPartOf\":{\"@id\":\"https:\/\/statorials.org\/id\/#website\"},\"datePublished\":\"2023-07-22T02:43:48+00:00\",\"dateModified\":\"2023-07-22T02:43:48+00:00\",\"author\":{\"@id\":\"https:\/\/statorials.org\/id\/#\/schema\/person\/3d17a1160dd2d052b7c78e502cb9ec81\"},\"description\":\"Tutorial ini menjelaskan cara memperhitungkan nilai yang hilang di pandas DataFrame, dengan sebuah contoh.\",\"breadcrumb\":{\"@id\":\"https:\/\/statorials.org\/id\/pandas-memperhitungkan-nilai-yang-hilang\/#breadcrumb\"},\"inLanguage\":\"id\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/statorials.org\/id\/pandas-memperhitungkan-nilai-yang-hilang\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/statorials.org\/id\/pandas-memperhitungkan-nilai-yang-hilang\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\/\/statorials.org\/id\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Cara memperhitungkan nilai yang hilang di panda (termasuk contoh)\"}]},{\"@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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