{"id":33,"date":"2020-12-17T15:15:47","date_gmt":"2020-12-17T15:15:47","guid":{"rendered":"http:\/\/gats.me\/?p=33"},"modified":"2020-12-19T06:02:59","modified_gmt":"2020-12-19T06:02:59","slug":"a-little-book-of-python-for-multivariate-analysis","status":"publish","type":"post","link":"https:\/\/gats.me\/?p=33","title":{"rendered":"A Little Book of Python for Multivariate Analysis"},"content":{"rendered":"\n<p>An excellent resource on multivariate analysis that I stumbled upon was called <a href=\"https:\/\/little-book-of-r-for-multivariate-analysis.readthedocs.org\/en\/latest\/\">&#8220;A little book of R for multivariate analysis&#8221;<\/a> by Avril Coghlan.<\/p>\n\n\n\n<p>I liked it for its clarity and its good use of examples in explaining how to use and interpret <a href=\"https:\/\/en.wikipedia.org\/wiki\/Principal_component_analysis\">PCA<\/a> and <a href=\"https:\/\/en.wikipedia.org\/wiki\/Linear_discriminant_analysis\">LDA<\/a>, as well as how to perform some typical and basic preliminary data analysis. As the title suggests, it is targeted to R.<\/p>\n\n\n\n<p>With Python becoming a popular choice for data science, I thought it would be useful to show how this same analysis could be done in Python, and add some further links related to Python and data science.<\/p>\n\n\n\n<p>You can find it hosted in <a href=\"http:\/\/python-for-multivariate-analysis.readthedocs.org\">Read the Docs<\/a>, which allows to read it online or download a <a href=\"http:\/\/readthedocs.org\/projects\/python-for-multivariate-analysis\/downloads\/pdf\/latest\/\">PDF version<\/a> of it, among other available formats. For those that want to get their hands dirty, there is the corresponding <a href=\"https:\/\/github.com\/yianni\/a_little_book_of_python_for_multivariate_analysis\">Jupyter notebook on github<\/a>.<\/p>\n\n\n\n<p>Hope you enjoy it and feel free to leave a message or contact me for any comments.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>An excellent resource on multivariate analysis that I stumbled upon was called &#8220;A little book of R for multivariate analysis&#8221; by Avril Coghlan. I liked it for its clarity and its good use of examples in explaining how to use and interpret PCA and LDA, as well as how to<span class=\"more-link\"><a href=\"https:\/\/gats.me\/?p=33\">Continue Reading<\/a><\/span><\/p>\n","protected":false},"author":1,"featured_media":34,"comment_status":"open","ping_status":"open","sticky":true,"template":"","format":"standard","meta":{"spay_email":"","footnotes":""},"categories":[2],"tags":[6,14],"class_list":["entry","author-gatsoulisgmail-com","post-33","post","type-post","status-publish","format-standard","has-post-thumbnail","category-data-science","tag-python","tag-statistics"],"jetpack_featured_media_url":"https:\/\/gats.me\/wp-content\/uploads\/2020\/12\/screenshot-2016-03-14-14-31-17.png","_links":{"self":[{"href":"https:\/\/gats.me\/index.php?rest_route=\/wp\/v2\/posts\/33","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/gats.me\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/gats.me\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/gats.me\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/gats.me\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=33"}],"version-history":[{"count":1,"href":"https:\/\/gats.me\/index.php?rest_route=\/wp\/v2\/posts\/33\/revisions"}],"predecessor-version":[{"id":35,"href":"https:\/\/gats.me\/index.php?rest_route=\/wp\/v2\/posts\/33\/revisions\/35"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/gats.me\/index.php?rest_route=\/wp\/v2\/media\/34"}],"wp:attachment":[{"href":"https:\/\/gats.me\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=33"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/gats.me\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=33"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/gats.me\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=33"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}