{"id":54540,"date":"2024-04-16T00:11:55","date_gmt":"2024-04-16T00:11:55","guid":{"rendered":"https:\/\/exam.pscnotes.com\/mcq\/?p=54540"},"modified":"2024-04-16T00:11:55","modified_gmt":"2024-04-16T00:11:55","slug":"what-is-the-primary-purpose-of-the-melt-function-in-pandas-when-reshaping-data","status":"publish","type":"post","link":"https:\/\/exam.pscnotes.com\/mcq\/what-is-the-primary-purpose-of-the-melt-function-in-pandas-when-reshaping-data\/","title":{"rendered":"What is the primary purpose of the &#8220;melt&#8221; function in Pandas when reshaping data?"},"content":{"rendered":"<p>\r\n    <!-- Check if it's an AMP page -->\r\n            <!-- Non-AMP version -->\r\n        <div class=\"mcq-container\" data-quiz-id=\"quizState_6a97a229c3e3d\">\r\n                                            <div class=\"option\" data-option-key=\"option1\" data-is-correct=\"true\">\r\n                    Convert wide data to long format                <\/div>\r\n                                            <div class=\"option\" data-option-key=\"option2\" data-is-correct=\"false\">\r\n                    Sorting data                <\/div>\r\n                                            <div class=\"option\" data-option-key=\"option3\" data-is-correct=\"false\">\r\n                    Aggregating data                <\/div>\r\n                                            <div class=\"option\" data-option-key=\"option4\" data-is-correct=\"false\">\r\n                    Grouping data                <\/div>\r\n                            \r\n            <!-- Feedback messages for non-AMP -->\r\n            <div class=\"feedback\" data-feedback=\"wrong\">Answer is Right!<\/div>\r\n            <div class=\"feedback\" data-feedback=\"right\">Answer is Wrong!<\/div>\r\n        <\/div>\r\n\r\n        <script>\r\n        document.addEventListener('DOMContentLoaded', function () {\r\n            var containers = document.querySelectorAll('.mcq-container');\r\n\r\n            containers.forEach(function(container) {\r\n                var options = container.querySelectorAll('.option');\r\n                var feedbackSelect = container.querySelector('[data-feedback=\"select\"]');\r\n                var feedbackWrong = container.querySelector('[data-feedback=\"wrong\"]');\r\n                var feedbackRight = container.querySelector('[data-feedback=\"right\"]');\r\n\r\n                options.forEach(function(option) {\r\n                    option.addEventListener('click', function() {\r\n                        var selectedOption = option.getAttribute('data-option-key');\r\n                        var isCorrect = option.getAttribute('data-is-correct') === 'true';\r\n\r\n                        \/\/ Remove previous selections\r\n                        options.forEach(function(opt) {\r\n                            opt.classList.remove('correct', 'incorrect');\r\n                        });\r\n\r\n                        \/\/ Add the correct\/incorrect class\r\n                        if (isCorrect) {\r\n                            option.classList.add('correct');\r\n                            feedbackRight.hidden = false;\r\n                            feedbackWrong.hidden = true;\r\n                        } else {\r\n                            option.classList.add('incorrect');\r\n                            feedbackRight.hidden = true;\r\n                            feedbackWrong.hidden = false;\r\n                        }\r\n\r\n                        \/\/ Hide select feedback\r\n                        feedbackSelect.hidden = true;\r\n                    });\r\n                });\r\n            });\r\n        });\r\n        <\/script>\r\n    \r\n    <!--more--><\/p>\n<p>The correct answer is A. Convert wide data <div class=\"youtube-subscribe-container\">\r\n        <a href=\"https:\/\/www.youtube.com\/channel\/UCNHT8lW-JmLC68rjBfZhdkg?sub_confirmation=1\" target=\"_blank\" class=\"youtube-subscribe-button\">\r\n            <span class=\"youtube-icon\">\r\n                <svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 576 512\">\r\n                    <path d=\"M549.7 124.1c-6.3-23.7-24.8-42.3-48.3-48.6C458.8 64 288 64 288 64S117.2 64 74.6 75.5c-23.5 6.3-42 24.9-48.3 48.6-11.4 42.9-11.4 132.3-11.4 132.3s0 89.4 11.4 132.3c6.3 23.7 24.8 41.5 48.3 47.8C117.2 448 288 448 288 448s170.8 0 213.4-11.5c23.5-6.3 42-24.2 48.3-47.8 11.4-42.9 11.4-132.3 11.4-132.3s0-89.4-11.4-132.3zm-317.5 213.5V175.2l142.7 81.2-142.7 81.2z\"\/>\r\n                <\/svg>\r\n            <\/span>\r\n            Subscribe on YouTube\r\n        <\/a>\r\n    <\/div> to long format.<\/p>\n<p>The melt function in Pandas is used to convert wide data to long format. Wide data is a data structure where each row represents an observation and each column represents a variable. Long data is a data structure where each row represents a variable and each column represents an observation.<\/p>\n<p>The melt function takes two arguments: a DataFrame and a <div class=\"telegram-channel-container\">\r\n        <a href=\"https:\/\/t.me\/pscnotes2025\" target=\"_blank\" class=\"telegram-channel-button\">\r\n            <span class=\"telegram-icon\">\r\n                <svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 496 512\">\r\n                    <path fill=\"white\" d=\"M248,8C111,8,0,119,0,256s111,248,248,248s248-111,248-248S385,8,248,8z M362,177L320,367c-3,14-10,18-20,14l-56-41l-27,26 c-3,3-5,5-10,5l4-63L323,196c5-5-1-7-8-3l-98,62l-42-13c-9-3-10-9,2-14l162-63C351,160,365,164,362,177z\"\/>\r\n                <\/svg>\r\n            <\/span>\r\n            Join Our Telegram Channel\r\n        <\/a>\r\n    <\/div> column name. The DataFrame is the data that you want to convert to long format. The column name is the name of the column that you want to use as the index of the long data.<\/p>\n<p>The melt function returns a new DataFrame in long format. The new DataFrame will have one row for each variable and one column for each observation. The values in the new DataFrame will be the values from the original DataFrame, but they will be organized in a different way.<\/p>\n<p>Here is an example of how to use the melt function:<\/p>\n<p>&#8220;`<br \/>\nimport pandas as pd<\/p>\n<p>df = pd.DataFrame({&#8216;A&#8217;: [1, 2, 3], &#8216;B&#8217;: [4, 5, 6], &#8216;C&#8217;: [7, 8, 9]})<\/p>\n<p>melted_df = pd.melt(df, id_vars=[&#8216;A&#8217;], var_name=&#8217;B&#8217;, value_name=&#8217;C&#8217;)<\/p>\n<p>print(melted_df)<\/p>\n<p>A  B  C<br \/>\n0  1  4  7<br \/>\n1  2  5  8<br \/>\n2  3  6  9<br \/>\n&#8220;`<\/p>\n<p>The melted_df DataFrame has one row for each variable (A, B, and C) and one column for each observation (1, 2, and 3). The values in the melted_df DataFrame are the values from the original DataFrame, but they are organized in a different way.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Subscribe on YouTube<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[737],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v22.2 (Yoast SEO v23.3) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>What is the primary purpose of the &quot;melt&quot; function in Pandas when reshaping data?<\/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:\/\/exam.pscnotes.com\/mcq\/what-is-the-primary-purpose-of-the-melt-function-in-pandas-when-reshaping-data\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"What is the primary purpose of the &quot;melt&quot; 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