{"id":25841,"date":"2021-12-16T09:19:35","date_gmt":"2021-12-16T03:49:35","guid":{"rendered":"https:\/\/python-programs.com\/?p=25841"},"modified":"2021-12-16T09:19:35","modified_gmt":"2021-12-16T03:49:35","slug":"python-nltk-program-to-implement-n-grams","status":"publish","type":"post","link":"https:\/\/python-programs.com\/python-nltk-program-to-implement-n-grams\/","title":{"rendered":"Python NLTK Program to Implement N-Grams"},"content":{"rendered":"<p>Natural language processing and text mining both make extensive use of text n-grams. It&#8217;s basically a string of words that all appear in the same window at the same time.<\/p>\n<p>When computing n-grams, you usually advance one word at a time (although in more complex scenarios you can move n-words). N-grams can be used for a variety of things.<\/p>\n<p><strong>N = 1:<\/strong> Welcome to Python Programs<\/p>\n<p>The <strong>Unigrams<\/strong> of this sentence is:\u00a0 welcome, to, Python, Programs<\/p>\n<p><strong>N = 2:\u00a0<\/strong>Welcome to Python Programs<\/p>\n<p><strong>bigrams:<\/strong><\/p>\n<p>Welcome to,<\/p>\n<p>to Python<\/p>\n<p>Python Programs<\/p>\n<p><strong>N=3:<\/strong> <strong>trigrams: <\/strong>Welcome to Python, to Python Programs<\/p>\n<p>For example, when developing language models, n-grams are used to generate not only unigram models but also bigrams and trigrams.<\/p>\n<p><strong>Examples:<\/strong><\/p>\n<p><strong>Example1:<\/strong><\/p>\n<p><strong>Input:<\/strong><\/p>\n<pre>Given String = \"Hello\u00a0Welcome\u00a0to\u00a0Python\u00a0Programs\"\r\nGiven n value = 2<\/pre>\n<p><strong>Output:<\/strong><\/p>\n<pre>('Hello', 'Welcome')\r\n('Welcome', 'to')\r\n('to', 'Python') \r\n('Python', 'Programs')<\/pre>\n<p><strong>Example2:<\/strong><\/p>\n<p><strong>Input:<\/strong><\/p>\n<pre>Given String = \"good morning all this is python programs\"\r\nGiven n value = 3<\/pre>\n<p><strong>Output:<\/strong><\/p>\n<pre>('good', 'morning', 'all')\r\n('morning', 'all', 'this')\r\n('all', 'this', 'is') \r\n('this', 'is', 'python')\r\n('is', 'python', 'programs')<\/pre>\n<h2>NLTK Program to Implement N-Grams<\/h2>\n<p>&nbsp;<\/p>\n<h3 id=\"Using_Built-in_Functions_(Static_Input)\">Method #1: Using NLTK Module (Static Input)<\/h3>\n<p><strong>Approach:<\/strong><\/p>\n<ul>\n<li>Import ngrams from the nltk module using the import keyword.<\/li>\n<li>Give the string as static input and store it in a variable.<\/li>\n<li>Give the n value as static input and store it in another variable.<\/li>\n<li>Split the given string into a list of words using the split() function.<\/li>\n<li>Pass the above split list and the given n value as the arguments to the ngrams()\u00a0function and store it in another variable.<\/li>\n<li>Loop in the above result obtained using the for loop.<\/li>\n<li>Inside the loop, print the iterator value.<\/li>\n<li>The Exit of the Program.<\/li>\n<\/ul>\n<p><strong>Below is the implementation:<\/strong><\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"python\"># Import ngrams from the nltk module using the import keyword\r\nfrom nltk import ngrams\r\n# Give the string as static input and store it in a variable.\r\ngvn_str = \"Hello Welcome to Python Programs\"\r\n# Give the n value as static input and store it in another variable.\r\ngvn_n_val = 2\r\n# Split the given string into list of words using the split() function\r\nsplt_lst = gvn_str.split()\r\n# Pass the above split list and the given n value as the arguments to the ngrams()\r\n# function and store it in another variable.\r\nrslt_n_grms = ngrams(splt_lst, gvn_n_val)\r\n# Loop in the above result obtained using the for loop\r\nfor itr in rslt_n_grms:\r\n    # Inside the loop, print the iterator value.\r\n    print(itr)\r\n<\/pre>\n<p><strong>Output:<\/strong><\/p>\n<pre>('Hello', 'Welcome')\r\n('Welcome', 'to')\r\n('to', 'Python') \r\n('Python', 'Programs')<\/pre>\n<h3 id=\"Using_Built-in_Functions_(User_Input)\">Method #2: Using NLTK Module (User Input)<\/h3>\n<p><strong>Approach:<\/strong><\/p>\n<ul>\n<li>Import ngrams from the nltk module using the import keyword.<\/li>\n<li>Give the string as user input using the input() function and store it in a variable.<\/li>\n<li>Give the n value as user input using the int(input()) function and store it in another variable.<\/li>\n<li>Split the given string into a list of words using the split() function.<\/li>\n<li>Pass the above split list and the given n value as the arguments to the ngrams()\u00a0function and store it in another variable.<\/li>\n<li>Loop in the above result obtained using the for loop.<\/li>\n<li>Inside the loop, print the iterator value.<\/li>\n<li>The Exit of the Program.<\/li>\n<\/ul>\n<p><strong>Below is the implementation:<\/strong><\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"python\"># Import ngrams from the nltk module using the import keyword\r\nfrom nltk import ngrams\r\n# Give the string as user input using the input() function and store it in a variable.\r\ngvn_str = input(\"Enter some random string = \")\r\n# Give the n value as user input using the int(input()) function and store it in another variable.\r\ngvn_n_val = int(input(\"Enter some random number(n) = \"))\r\n# Split the given string into list of words using the split() function\r\nsplt_lst = gvn_str.split()\r\n# Pass the above split list and the given n value as the arguments to the ngrams()\r\n# function and store it in another variable.\r\nrslt_n_grms = ngrams(splt_lst, gvn_n_val)\r\n# Loop in the above result obtained using the for loop\r\nfor itr in rslt_n_grms:\r\n    # Inside the loop, print the iterator value.\r\n    print(itr)\r\n<\/pre>\n<p><strong>Output:<\/strong><\/p>\n<pre>Enter some random string = good morning all this is python programs \r\nEnter some random number(n) = 3 \r\n('good', 'morning', 'all')\r\n('morning', 'all', 'this')\r\n('all', 'this', 'is')\r\n('this', 'is', 'python') \r\n('is', 'python', 'programs')<\/pre>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Natural language processing and text mining both make extensive use of text n-grams. It&#8217;s basically a string of words that all appear in the same window at the same time. When computing n-grams, you usually advance one word at a time (although in more complex scenarios you can move n-words). N-grams can be used for &hellip;<\/p>\n<p class=\"read-more\"> <a class=\"\" href=\"https:\/\/python-programs.com\/python-nltk-program-to-implement-n-grams\/\"> <span class=\"screen-reader-text\">Python NLTK Program to Implement N-Grams<\/span> Read More &raquo;<\/a><\/p>\n","protected":false},"author":7,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"spay_email":"","jetpack_publicize_message":"","jetpack_is_tweetstorm":false,"jetpack_publicize_feature_enabled":true},"categories":[5],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v18.9 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Python NLTK Program to Implement N-Grams - Python Programs<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/python-programs.com\/python-nltk-program-to-implement-n-grams\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Python NLTK Program to Implement N-Grams - Python Programs\" \/>\n<meta property=\"og:description\" content=\"Natural language processing and text mining both make extensive use of text n-grams. 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