{"id":903,"date":"2023-07-28T09:10:08","date_gmt":"2023-07-28T09:10:08","guid":{"rendered":"https:\/\/statorials.org\/id\/mendigitalkan-numpy\/"},"modified":"2023-07-28T09:10:08","modified_gmt":"2023-07-28T09:10:08","slug":"mendigitalkan-numpy","status":"publish","type":"post","link":"https:\/\/statorials.org\/id\/mendigitalkan-numpy\/","title":{"rendered":"Cara mengelompokkan variabel dengan python menggunakan numpy.digitize()"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">Seringkali Anda mungkin tertarik untuk memasukkan nilai suatu variabel ke dalam &#8220;bins&#8221; dengan Python.<\/span><\/p>\n<p> <span style=\"color: #000000;\">Untungnya, hal ini mudah dilakukan menggunakan fungsi <a href=\"https:\/\/numpy.org\/doc\/stable\/reference\/generated\/numpy.digitize.html\" target=\"_blank\" rel=\"noopener\">numpy.digitize()<\/a> , yang menggunakan sintaks berikut:<br \/><\/span><\/p>\n<p> <strong><span style=\"color: #000000;\">numpy.digitize(x, bins, kanan=False)<\/span><\/strong><\/p>\n<p> <span style=\"color: #000000;\">Emas:<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>x:<\/strong> array ke grup.<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>tempat sampah:<\/strong> susunan tempat sampah.<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>kanan:<\/strong> Menunjukkan apakah interval mencakup tepi kanan atau kiri nampan. Secara default, interval tidak menyertakan tepi kanan.<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">Tutorial ini menunjukkan beberapa contoh penggunaan praktis fungsi ini.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>Contoh 1: Tempatkan semua nilai dalam dua nampan<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">Kode berikut menunjukkan cara menempatkan nilai array ke dalam dua nampan:<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>0<\/strong> jika x &lt; 20<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>1<\/strong> jika x \u2265 20<\/span><\/li>\n<\/ul>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #107d3f;\">import<\/span> numpy <span style=\"color: #107d3f;\">as<\/span> np\n\n<span style=\"color: #008080;\">#create data<\/span>\ndata = [2, 4, 4, 7, 12, 14, 19, 20, 24, 31, 34]\n\n<span style=\"color: #008080;\">#place values into bins\n<span style=\"color: #000000;\">n.p. <span style=\"color: #3366ff;\">digitize<\/span> (data, bins=[20])\n\narray([0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1])\n<\/span><\/span><\/strong><\/pre>\n<h3> <span style=\"color: #000000;\"><strong>Contoh 2: Tempatkan semua nilai dalam tiga wadah<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">Kode berikut menunjukkan cara menempatkan nilai array ke dalam tiga nampan:<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>0<\/strong> jika x &lt; 10<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>1<\/strong> jika 10 \u2264 x &lt; 20<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>2<\/strong> jika x \u2265 20<\/span><\/li>\n<\/ul>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #107d3f;\">import<\/span> numpy <span style=\"color: #107d3f;\">as<\/span> np\n\n<span style=\"color: #008080;\">#create data<\/span>\ndata = [2, 4, 4, 7, 12, 14, 20, 22, 24, 31, 34]\n\n<span style=\"color: #008080;\">#place values into bins\n<span style=\"color: #000000;\">n.p. <span style=\"color: #3366ff;\">digitize<\/span> (data, bins=[10, 20])\n\narray([0, 0, 0, 0, 1, 1, 2, 2, 2, 2, 2])<\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">Perhatikan bahwa jika kita menentukan right= <strong>True<\/strong> maka nilainya akan ditempatkan di tempat sampah berikut:<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>0<\/strong> jika x \u2264 10<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>1<\/strong> jika 10 &lt; x \u2264 20<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>2<\/strong> jika x &gt; 20<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">Setiap interval akan mencakup tepi kanan wadah. Ini adalah tampilannya:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #107d3f;\">import<\/span> numpy <span style=\"color: #107d3f;\">as<\/span> np\n\n<span style=\"color: #008080;\">#createdata<\/span>\ndata = [2, 4, 4, 7, 12, 14, 20, 22, 24, 31, 34]\n\n<span style=\"color: #008080;\">#place values into bins\n<span style=\"color: #000000;\">n.p. <span style=\"color: #3366ff;\">digitize<\/span> (data, bins=[10, 20], right= <span style=\"color: #008000;\">True<\/span> )\n\narray([0, 0, 0, 0, 1, 1, 1, 2, 2, 2, 2])<\/span><\/span><\/strong><\/pre>\n<h3> <span style=\"color: #000000;\"><strong>Contoh 3: Tempatkan semua nilai dalam empat nampan<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">Kode berikut menunjukkan cara menempatkan nilai array ke dalam tiga nampan:<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>0<\/strong> jika x &lt; 10<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>1<\/strong> jika 10 \u2264 x &lt; 20<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>2<\/strong> jika 20 \u2264 x &lt; 30<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>3<\/strong> jika x \u2265 30<\/span><\/li>\n<\/ul>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #107d3f;\">import<\/span> numpy <span style=\"color: #107d3f;\">as<\/span> np\n\n<span style=\"color: #008080;\">#createdata<\/span>\ndata = [2, 4, 4, 7, 12, 14, 20, 22, 24, 31, 34]\n\n<span style=\"color: #008080;\">#place values into bins\n<span style=\"color: #000000;\">n.p. <span style=\"color: #3366ff;\">digitize<\/span> (data, bins=[10, 20, 30])\n\narray([0, 0, 0, 0, 1, 1, 2, 2, 2, 3, 3])\n<\/span><\/span><\/strong><\/pre>\n<h3> <span style=\"color: #000000;\"><strong>Contoh 4: Hitung frekuensi setiap bin<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">Fungsi NumPy lain yang berguna yang melengkapi fungsi numpy.digitize() adalah fungsi <a href=\"https:\/\/numpy.org\/doc\/stable\/reference\/generated\/numpy.bincount.html#numpy.bincount\" target=\"_blank\" rel=\"noopener\">numpy.bincount()<\/a> , yang menghitung frekuensi setiap bin.<\/span><\/p>\n<p> <span style=\"color: #000000;\">Kode berikut menunjukkan cara menempatkan nilai suatu array ke dalam tiga kelompok, lalu menghitung frekuensi masing-masing kelompok:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #107d3f;\">import<\/span> numpy <span style=\"color: #107d3f;\">as<\/span> np\n\n<span style=\"color: #008080;\">#createdata<\/span>\ndata = [2, 4, 4, 7, 12, 14, 20, 22, 24, 31, 34]\n\n<span style=\"color: #008080;\">#place values into bins\n<span style=\"color: #000000;\">bin_data = np. <span style=\"color: #3366ff;\">digitize<\/span> (data, bins=[10, 20])\n\n<span style=\"color: #008080;\">#view binned data<\/span>\nbin_data\n\narray([0, 0, 0, 0, 1, 1, 2, 2, 2, 2, 2])\n\n<span style=\"color: #008080;\">#count frequency of each bin\n<span style=\"color: #000000;\">n.p. <span style=\"color: #3366ff;\">bincount<\/span> (bin_data)\n\narray([4, 2, 5])\n<\/span><\/span><\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">Outputnya memberitahu kita bahwa:<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\">Bin \u201c0\u201d berisi <strong>4<\/strong> nilai data.<\/span><\/li>\n<li> <span style=\"color: #000000;\">Bin \u201c1\u201d berisi <strong>2<\/strong> nilai data.<\/span><\/li>\n<li> <span style=\"color: #000000;\">Bin \u201c2\u201d berisi <strong>5<\/strong> nilai data.<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\"><em><span style=\"color: #000000;\">Temukan tutorial Python lainnya di sini .<\/span><\/em><\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Seringkali Anda mungkin tertarik untuk memasukkan nilai suatu variabel ke dalam &#8220;bins&#8221; dengan Python. Untungnya, hal ini mudah dilakukan menggunakan fungsi numpy.digitize() , yang menggunakan sintaks berikut: numpy.digitize(x, bins, kanan=False) Emas: x: array ke grup. tempat sampah: susunan tempat sampah. kanan: Menunjukkan apakah interval mencakup tepi kanan atau kiri nampan. Secara default, interval tidak menyertakan [&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>Cara mengelompokkan variabel dengan Python menggunakan numpy.digitize() - Statorials<\/title>\n<meta name=\"description\" content=\"Penjelasan sederhana tentang cara mengelompokkan variabel dengan Python menggunakan fungsi numpy.digitize().\" \/>\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\/mendigitalkan-numpy\/\" \/>\n<meta property=\"og:locale\" content=\"id_ID\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Cara mengelompokkan variabel dengan Python menggunakan numpy.digitize() - Statorials\" \/>\n<meta property=\"og:description\" content=\"Penjelasan sederhana tentang cara mengelompokkan variabel dengan Python menggunakan fungsi numpy.digitize().\" \/>\n<meta property=\"og:url\" content=\"https:\/\/statorials.org\/id\/mendigitalkan-numpy\/\" \/>\n<meta property=\"og:site_name\" content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-28T09:10:08+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\/mendigitalkan-numpy\/\",\"url\":\"https:\/\/statorials.org\/id\/mendigitalkan-numpy\/\",\"name\":\"Cara mengelompokkan variabel dengan Python menggunakan numpy.digitize() - Statorials\",\"isPartOf\":{\"@id\":\"https:\/\/statorials.org\/id\/#website\"},\"datePublished\":\"2023-07-28T09:10:08+00:00\",\"dateModified\":\"2023-07-28T09:10:08+00:00\",\"author\":{\"@id\":\"https:\/\/statorials.org\/id\/#\/schema\/person\/3d17a1160dd2d052b7c78e502cb9ec81\"},\"description\":\"Penjelasan sederhana tentang cara mengelompokkan variabel dengan Python menggunakan fungsi numpy.digitize().\",\"breadcrumb\":{\"@id\":\"https:\/\/statorials.org\/id\/mendigitalkan-numpy\/#breadcrumb\"},\"inLanguage\":\"id\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/statorials.org\/id\/mendigitalkan-numpy\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/statorials.org\/id\/mendigitalkan-numpy\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\/\/statorials.org\/id\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Cara mengelompokkan variabel dengan python menggunakan numpy.digitize()\"}]},{\"@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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