{"id":25475,"date":"2021-11-16T08:39:38","date_gmt":"2021-11-16T03:09:38","guid":{"rendered":"https:\/\/python-programs.com\/?p=25475"},"modified":"2021-11-16T08:39:38","modified_gmt":"2021-11-16T03:09:38","slug":"python-statistics-pvariance-method-with-examples","status":"publish","type":"post","link":"https:\/\/python-programs.com\/python-statistics-pvariance-method-with-examples\/","title":{"rendered":"Python statistics.pvariance() Method with Examples"},"content":{"rendered":"<p><strong>statistics.pvariance() Method in Python:<\/strong><\/p>\n<p>The statistics.pvariance() method computes the variance of a whole population.<\/p>\n<p>A high variance indicates that the data is dispersed, whereas a low variance indicates that the data is tightly clustered around the mean.<\/p>\n<p>Examine the statistics.variance() method to determine the variance from a sample of data.<\/p>\n<p><strong>Syntax:<\/strong><\/p>\n<pre>statistics.pvariance(data, xbar)<\/pre>\n<p><strong>Parameters<\/strong><\/p>\n<p><strong>data:<\/strong> This is Required. It is the data values that will be used (it can be any sequence, list, or iterator).<\/p>\n<p><strong>xbar:<\/strong> This is Optional. The arithmetic mean of the given data (can also be a second moment around a point that is not the mean). If omitted (or set to None), the mean is calculated automatically.<\/p>\n<p><strong>Note:<\/strong> It is important to note that if the data is empty, it returns a StatisticsError.<\/p>\n<p><strong>Return Value:<\/strong><\/p>\n<p>Returns a \u00a0float value representing the given data&#8217;s population variance.<\/p>\n<p><strong>Examples:<\/strong><\/p>\n<p><strong>Example1:<\/strong><\/p>\n<p><strong>Input:<\/strong><\/p>\n<pre>Given list = [10, 20, 40, 15, 30]<\/pre>\n<p><strong>Output:<\/strong><\/p>\n<pre id=\"codeOutputPre\">The variance of the given list items [10, 20, 40, 15, 30] =  116<\/pre>\n<p><strong>Example2:<\/strong><\/p>\n<p><strong>Input:<\/strong><\/p>\n<pre>Given list = [1, 6, 9, 7]<\/pre>\n<p><strong>Output:<\/strong><\/p>\n<pre id=\"codeOutputPre\">The variance of the given list items [1, 6, 9, 7] = 8.6875<\/pre>\n<p><span style=\"font-size: 1.7em; font-weight: bold;\">statistics.pvariance() Method with Examples in Python<\/span><\/p>\n<ul>\n<li><a href=\"#Using_Built-in_Functions_(Static_Input)\">Using Built-in Functions (Static Input)<\/a><\/li>\n<li><a href=\"#Using_Built-in_Functions_(User_Input)\">Using Built-in Functions (User Input)<\/a><\/li>\n<\/ul>\n<h3 id=\"Using_Built-in_Functions_(Static_Input)\">Method #1: Using Built-in Functions (Static Input)<\/h3>\n<p><strong>Approach:<\/strong><\/p>\n<ul>\n<li>Import statistics module using the import keyword.<\/li>\n<li>Give the list as static input and store it in a variable.<\/li>\n<li>Pass the given list as an argument to the statistics.pvariance() method that computes the variance of a whole population.<\/li>\n<li>Store it in another variable.<\/li>\n<li>Print the variance of the given list items.<\/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 statistics module using the import keyword.\r\nimport statistics\r\n# Give the list as static input and store it in a variable.\r\ngvn_lst = [10, 20, 40, 15, 30]\r\n# Pass the given list as an argument to the statistics.pvariance() method that\r\n# computes the variance of a whole population.\r\n# Store it in another variable.\r\nrslt = statistics.pvariance(gvn_lst)\r\n# Print the variance of the given list items.\r\nprint(\"The variance of the given list items\", gvn_lst, \"= \", rslt)\r\n<\/pre>\n<p><strong>Output:<\/strong><\/p>\n<pre id=\"codeOutputPre\">The variance of the given list items [10, 20, 40, 15, 30] =  116<\/pre>\n<h3 id=\"Using_Built-in_Functions_(User_Input)\">Method #2: Using Built-in Functions (User Input)<\/h3>\n<p><strong>Approach:<\/strong><\/p>\n<ul>\n<li>Import statistics module using the import keyword.<\/li>\n<li>Give the list as user input using list(),map(),input(),and split() functions.<\/li>\n<li>Store it in another variable.<\/li>\n<li>Pass the given list as an argument to the statistics.pvariance() method that computes the variance of a whole population.<\/li>\n<li>Store it in another variable.<\/li>\n<li>Print the variance of the given list items.<\/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 statistics module using the import keyword.\r\nimport statistics\r\n# Give the list as user input using list(),map(),input(),and split() functions.\r\n# Store it in a variable.\r\ngvn_lst = list(map(int, input(\r\n    'Enter some random List Elements separated by spaces = ').split()))\r\n\r\n# Pass the given list as an argument to the statistics.pvariance() method that\r\n# computes the variance of a whole population.\r\n# Store it in another variable.\r\nrslt = statistics.pvariance(gvn_lst)\r\n# Print the variance of the given list items.\r\nprint(\"The variance of the given list items\", gvn_lst, \"= \", rslt)\r\n<\/pre>\n<p><strong>Output:<\/strong><\/p>\n<pre>Enter some random List Elements separated by spaces = 1 6 9 7\r\nThe variance of the given list items [1, 6, 9, 7] = 8.6875<\/pre>\n","protected":false},"excerpt":{"rendered":"<p>statistics.pvariance() Method in Python: The statistics.pvariance() method computes the variance of a whole population. A high variance indicates that the data is dispersed, whereas a low variance indicates that the data is tightly clustered around the mean. Examine the statistics.variance() method to determine the variance from a sample of data. Syntax: statistics.pvariance(data, xbar) Parameters data: &hellip;<\/p>\n<p class=\"read-more\"> <a class=\"\" href=\"https:\/\/python-programs.com\/python-statistics-pvariance-method-with-examples\/\"> <span class=\"screen-reader-text\">Python statistics.pvariance() Method with Examples<\/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 statistics.pvariance() Method with Examples - 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-statistics-pvariance-method-with-examples\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Python statistics.pvariance() Method with Examples - Python Programs\" \/>\n<meta property=\"og:description\" content=\"statistics.pvariance() Method in Python: The statistics.pvariance() method computes the variance of a whole population. 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