{"id":4082,"date":"2023-07-13T17:34:00","date_gmt":"2023-07-13T17:34:00","guid":{"rendered":"https:\/\/statorials.org\/id\/panda-membaca-csv-dtype\/"},"modified":"2023-07-13T17:34:00","modified_gmt":"2023-07-13T17:34:00","slug":"panda-membaca-csv-dtype","status":"publish","type":"post","link":"https:\/\/statorials.org\/id\/panda-membaca-csv-dtype\/","title":{"rendered":"Pandas: cara menentukan tipe saat mengimpor file csv"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">Anda dapat menggunakan sintaks dasar berikut untuk menentukan tipe setiap kolom dalam DataFrame saat mengimpor file CSV ke pandas:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>df = pd. <span style=\"color: #3366ff;\">read_csv<\/span> (' <span style=\"color: #ff0000;\">my_data.csv<\/span> ',\n                 dtype = {' <span style=\"color: #ff0000;\">col1<\/span> ': <span style=\"color: #008000;\">str<\/span> , ' <span style=\"color: #ff0000;\">col2<\/span> ': <span style=\"color: #008000;\">float<\/span> , ' <span style=\"color: #ff0000;\">col3<\/span> ': <span style=\"color: #008000;\">int<\/span> })\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">Argumen <b>dtype<\/b> menentukan tipe data yang harus dimiliki setiap kolom saat mengimpor file CSV ke dalam pandas DataFrame.<\/span><\/p>\n<p> <span style=\"color: #000000;\">Contoh berikut menunjukkan cara menggunakan sintaksis ini dalam praktiknya.<\/span><\/p>\n<h2> <span style=\"color: #000000;\"><strong>Contoh: Tentukan jenis saat mengimpor file CSV ke Pandas<\/strong><\/span><\/h2>\n<p> <span style=\"color: #000000;\">Katakanlah kita memiliki file CSV berikut bernama <strong>basket_data.csv<\/strong> :<\/span> <\/p>\n<p><img decoding=\"async\" loading=\"lazy\" class=\" wp-image-28596 aligncenter\" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/sauter1-1.jpg\" alt=\"\" width=\"435\" height=\"318\" srcset=\"\" sizes=\"\"><\/p>\n<p> <span style=\"color: #000000;\">Jika kita mengimpor file CSV menggunakan fungsi <strong>read_csv()<\/strong> , panda akan mencoba mengidentifikasi tipe data untuk setiap kolom secara otomatis:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <b><span style=\"color: #008000;\">import<\/span> pandas <span style=\"color: #008000;\">as<\/span> pd\n\n<span style=\"color: #000000;\"><strong><span style=\"color: #008080;\">#import CSV file\n<\/span>df = pd. <span style=\"color: #3366ff;\">read_csv<\/span> (' <span style=\"color: #ff0000;\">basketball_data.csv<\/span> ')\n\n<span style=\"color: #008080;\">#view resulting DataFrame\n<\/span><span style=\"color: #008000;\">print<\/span> (df)\n\n   At 22 10\n0 B 14 9\n1 C 29 6\n2 D 30 2\n3 E 22 9\n4 F 31 10\n\n<span style=\"color: #008080;\">#view data type of each column\n<\/span><span style=\"color: #008000;\">print<\/span> ( <span style=\"color: #3366ff;\">df.dtypes<\/span> )\n\nteam object\nint64 dots\nrebounds int64\ndtype:object\n<\/strong><\/span><\/b><\/pre>\n<p> <span style=\"color: #000000;\">Dari hasilnya, kita dapat melihat bahwa kolom DataFrame memiliki tipe data berikut:<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>tim<\/strong> :objek<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>poin<\/strong> : int64<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>memantul<\/strong> : int64<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">Namun, kita bisa menggunakan argumen <b>dtype<\/b> dalam fungsi <strong>read_csv()<\/strong> untuk menentukan tipe data yang harus dimiliki setiap kolom:<\/span><b> <\/b><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"><b><span style=\"color: #008000;\">import<\/span> pandas <span style=\"color: #008000;\">as<\/span> pd\n\n<span style=\"color: #000000;\"><strong><span style=\"color: #008080;\">#import CSV file and specify dtype of each column\n<\/span>df = pd. <span style=\"color: #3366ff;\">read_csv<\/span> (' <span style=\"color: #ff0000;\">basketball_data.csv<\/span> ',\n                 dtype = {' <span style=\"color: #ff0000;\">team<\/span> ': <span style=\"color: #008000;\">str<\/span> , ' <span style=\"color: #ff0000;\">points<\/span> ': <span style=\"color: #008000;\">float<\/span> , ' <span style=\"color: #ff0000;\">rebounds<\/span> ': <span style=\"color: #008000;\">int<\/span> }))\n\n<span style=\"color: #008080;\">#view resulting DataFrame\n<\/span><span style=\"color: #008000;\">print<\/span> (df)\n\n   At 22 10\n0 B 14 9\n1 C 29 6\n2 D 30 2\n3 E 22 9\n4 F 31 10\n\n<span style=\"color: #008080;\">#view data type of each column\n<\/span><span style=\"color: #008000;\">print<\/span> ( <span style=\"color: #3366ff;\">df.dtypes<\/span> )\n\nteam object\nfloat64 points\nrebounds int32\ndtype:object<\/strong><\/span><\/b><\/pre>\n<p><span style=\"color: #000000;\">Dari hasilnya, kita dapat melihat bahwa kolom DataFrame memiliki tipe data berikut:<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>tim<\/strong> :objek<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>poin<\/strong> : float64<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>memantul<\/strong> : int32<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">Tipe data ini sesuai dengan yang kami tentukan menggunakan argumen <strong>dtype<\/strong> .<\/span><\/p>\n<p> <span style=\"color: #000000;\">Perhatikan bahwa dalam contoh ini kami telah menentukan tipe untuk setiap kolom di DataFrame.<\/span><\/p>\n<p> <span style=\"color: #000000;\">Namun, Anda dapat memilih untuk menentukan jenis kolom tertentu saja dan membiarkan panda menyimpulkan jenis kolom lainnya.<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>Catatan<\/strong> : Anda dapat menemukan dokumentasi lengkap fungsi pandas <strong>read_csv()<\/strong> <a href=\"https:\/\/pandas.pydata.org\/docs\/reference\/api\/pandas.read_csv.html\" target=\"_blank\" rel=\"noopener\">di sini<\/a> .<\/span><\/p>\n<h2> <span style=\"color: #000000;\"><strong>Sumber daya tambahan<\/strong><\/span><\/h2>\n<p> <span style=\"color: #000000;\">Tutorial berikut menjelaskan cara melakukan tugas umum lainnya di panda:<\/span><\/p>\n<p> <a href=\"https:\/\/statorials.org\/id\/panda-melompati-barisan\/\" target=\"_blank\" rel=\"noopener\">Pandas: Cara melewati baris saat membaca file CSV<\/a><br \/> <a href=\"https:\/\/statorials.org\/id\/pandas-memiliki-tambahan-csv\/\" target=\"_blank\" rel=\"noopener\">Pandas: Cara menambahkan data ke file CSV yang sudah ada<\/a><br \/> <a href=\"https:\/\/statorials.org\/id\/pandasa-membaca-csv-tanpa-header\/\" target=\"_blank\" rel=\"noopener\">Pandas: Cara membaca file CSV tanpa header<\/a><br \/> <a href=\"https:\/\/statorials.org\/id\/panda-membaca-kolom-nama-csv\/\" target=\"_blank\" rel=\"noopener\">Pandas: Cara mengatur nama kolom saat mengimpor file CSV<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Anda dapat menggunakan sintaks dasar berikut untuk menentukan tipe setiap kolom dalam DataFrame saat mengimpor file CSV ke pandas: df = pd. read_csv (&#8216; my_data.csv &#8216;, dtype = {&#8216; col1 &#8216;: str , &#8216; col2 &#8216;: float , &#8216; col3 &#8216;: int }) Argumen dtype menentukan tipe data yang harus dimiliki setiap kolom saat mengimpor [&hellip;]<\/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":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Pandas: Cara menentukan tipe saat mengimpor file CSV - Statorials<\/title>\n<meta name=\"description\" content=\"Tutorial ini menjelaskan cara menentukan tipe variabel saat mengimpor file CSV ke pandas DataFrame, termasuk contohnya.\" \/>\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\/panda-membaca-csv-dtype\/\" \/>\n<meta property=\"og:locale\" content=\"id_ID\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Pandas: Cara menentukan tipe saat mengimpor file CSV - Statorials\" \/>\n<meta property=\"og:description\" content=\"Tutorial ini menjelaskan cara menentukan tipe variabel saat mengimpor file CSV ke pandas DataFrame, termasuk contohnya.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/statorials.org\/id\/panda-membaca-csv-dtype\/\" \/>\n<meta property=\"og:site_name\" content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-13T17:34:00+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/sauter1-1.jpg\" \/>\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\/panda-membaca-csv-dtype\/\",\"url\":\"https:\/\/statorials.org\/id\/panda-membaca-csv-dtype\/\",\"name\":\"Pandas: Cara menentukan tipe saat mengimpor file CSV - Statorials\",\"isPartOf\":{\"@id\":\"https:\/\/statorials.org\/id\/#website\"},\"datePublished\":\"2023-07-13T17:34:00+00:00\",\"dateModified\":\"2023-07-13T17:34:00+00:00\",\"author\":{\"@id\":\"https:\/\/statorials.org\/id\/#\/schema\/person\/3d17a1160dd2d052b7c78e502cb9ec81\"},\"description\":\"Tutorial ini menjelaskan cara menentukan tipe variabel saat mengimpor file CSV ke pandas DataFrame, termasuk contohnya.\",\"breadcrumb\":{\"@id\":\"https:\/\/statorials.org\/id\/panda-membaca-csv-dtype\/#breadcrumb\"},\"inLanguage\":\"id\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/statorials.org\/id\/panda-membaca-csv-dtype\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/statorials.org\/id\/panda-membaca-csv-dtype\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\/\/statorials.org\/id\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Pandas: cara menentukan tipe saat mengimpor file csv\"}]},{\"@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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