{"id":245613,"date":"2021-10-11T14:18:55","date_gmt":"2021-10-11T14:18:55","guid":{"rendered":"https:\/\/imarticus.org\/?p=245613"},"modified":"2026-05-15T14:28:43","modified_gmt":"2026-05-15T08:58:43","slug":"principal-component-analysis-in-python-and-its-most-common-applications","status":"publish","type":"post","link":"https:\/\/imarticus.org\/blog\/principal-component-analysis-in-python-and-its-most-common-applications\/","title":{"rendered":"Principal Component Analysis in Python \u2013 and its Most Common Applications!"},"content":{"rendered":"<p><span style=\"font-weight: 400;\">Principal Component Analysis is a widely used data analysis technique that can identify patterns in large datasets. It has been applied to fields as diverse as astronomy, psychology and even marketing!<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">PCA in Python: Explained<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">PCA is a statistical technique that can reduce the dimensionality of data sets by transforming them into new sets of orthogonal (uncorrelated) variables called principal components or eigenvectors. PCA is a data analysis technique that reduces the dimensionality of data to reveal patterns. It&#8217;s an essential method in many fields, including machine learning, bioinformatics and statistical computing.<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">When to use PCA?<\/span><\/h3>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Whenever you need to ensure that variables in data are independent of each other.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">When you need to reduce the number of variables in a data set with different variables in it.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">When you need to interpret variable &amp; data selection out of it.<\/span><\/li>\n<\/ul>\n<h3><span style=\"font-weight: 400;\">Some Common Applications of Principal Component Analysis (PCA)<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">Principal Component Analysis performs well in identifying various influencing factors affecting results in particular areas. It can correlate factors associated with a candidate who might be winning\/losing. In the election commission, the PCA technique is also used in many applications, different industries, &amp; multiple fields. Some are discussed below:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Image compression: PCA can be employed in image compression and can resize the image as per the requirements while determining different patterns.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Customer profiling: Principal Component Analysis helps in Customer profiling based on demographics &amp; their intellect in the purchase.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Research: PCA is a widely known technique widely used by researchers in different fields, especially food science.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Banking: It can also be used in banking for activities like filing applicants&#8217; names for loans, credit cards, etc.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Maintaining Customer Perception towards brands.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Finance: PCA is used diversely in the field of Finance to analyze stocks quantitatively, forecast portfolio returns, and interest rate implantation.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Medical and Healthcare: PCA is also used in the Healthcare sector and related areas like patient insurance data. There are multiple sources of data with a vast number of variables correlated to each other. Probable resources are hospitals, pharmacies, etc.<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">To make a career in profiles associated with all these functions, a person needs to have a thorough knowledge of IoT and cloud computing. The best way to gain insights is to enrol into professional <a href=\"https:\/\/imarticus.org\/certification-in-software-engineering-for-cloud-blockchain-iot-e-ict-iit-guwahati\/\">cloud DevOps engineering certification<\/a>.<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">Learn and Grow with Imarticus Learning:<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">Enrol on the best Cloud, Blockchain and <a href=\"https:\/\/imarticus.org\/certification-in-software-engineering-for-cloud-blockchain-iot-e-ict-iit-guwahati\/\">IoT Software Engineering Course<\/a> at Imarticus Learning. The Certification in Software Engineering for Cloud, Blockchain and IoT program has been designed by industry leaders to provide the best learning outcome to aspiring Software Engineers.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The extensive program helps students prepare for the new-age Software Engineer role specialising in Cloud, Blockchain and IoT. It is an opportunity to build a strong foundation of Software Engineering concepts &amp; industry experts who will help you learn the practical implementation of Cloud, Blockchain and IoT through real-world projects. The course goes a long way to help unlock lucrative career opportunities in the field of Software Engineering. <\/span><b>Here are some Course USPs of Certification in Software Engineering:<\/b><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Uniquely designed by E&amp;ICT Academy, IIT Guwahati &amp; other industry leaders<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Learn exactly what the job market demands.\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Get ready for the job roles you aspire.\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Learn Cloud, Blockchain and IoT application skills through multiple business projects.<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">Contact us through the Live Chat Support system or visit our training centres in Mumbai, Thane, Pune, Chennai, Bengaluru, Hyderabad, Delhi, Gurgaon, and Ahmedabad.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Principal Component Analysis is a widely used data analysis technique that can identify patterns in large datasets. It has been applied to fields as diverse as astronomy, psychology and even marketing! PCA in Python: Explained PCA is a statistical technique that can reduce the dimensionality of data sets by transforming them into new sets of [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":245145,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"om_disable_all_campaigns":false,"_lmt_disableupdate":"no","_lmt_disable":"","_monsterinsights_skip_tracking":false,"footnotes":""},"categories":[24],"tags":[],"class_list":["post-245613","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-technology"],"acf":{"youtube-url-id":"","publised_date":"","ls_key":"PG Analytics"},"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One SEO 5.0.1.1 - aioseo.com -->\n\t<meta name=\"description\" content=\"Principal Component Analysis is a widely used data analysis technique that can identify patterns in large datasets. 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