{"id":2048,"date":"2021-06-28T18:18:04","date_gmt":"2021-06-28T18:18:04","guid":{"rendered":"http:\/\/optimumsportsperformance.com\/blog\/?p=2048"},"modified":"2021-06-28T18:18:04","modified_gmt":"2021-06-28T18:18:04","slug":"tidyx-65-cleaning-ugly-excel-data-part-2","status":"publish","type":"post","link":"https:\/\/optimumsportsperformance.com\/blog\/tidyx-65-cleaning-ugly-excel-data-part-2\/","title":{"rendered":"TidyX 65: Cleaning ugly excel data, Part 2"},"content":{"rendered":"<p>In the <strong><span style=\"color: #0000ff;\"><a style=\"color: #0000ff;\" href=\"https:\/\/optimumsportsperformance.com\/blog\/tidyx-64-cleaning-ugly-excel-data-part-1\/\">last episode<\/a><\/span><\/strong>, I took my crack at cleaning some messy excel data. This week, it is <strong><span style=\"color: #0000ff;\"><a style=\"color: #0000ff;\" href=\"https:\/\/twitter.com\/ellis_hughes\">Ellis&#8217;<\/a><\/span><\/strong> turn!<\/p>\n<p>While we took two different approaches to clean the data, we end up with the same result &#8212; a data frame of data that can be analyzed.<\/p>\n<p>The key take-a-ways from this two part series are:<\/p>\n<ol>\n<li>There are more than one ways to scale the mountain in R.<\/li>\n<li>We both take a\u00a0<em>chunking<\/em> approach,\u00a0 where we work with a single excel sheet first and try to wrap our head around the problem and develop an approach to solve it.<\/li>\n<li>Once we&#8217;ve setup an approach that we think will be useful, we both built functions that could parse all of the sheets in the excel file, returning our cleaned data frame.<\/li>\n<\/ol>\n<p>To watch our screen cast, <strong><span style=\"color: #0000ff;\"><a style=\"color: #0000ff;\" href=\"https:\/\/www.youtube.com\/watch?v=BilpJribZ-M\">CLICK HERE<\/a><\/span><\/strong>.<\/p>\n<p>To access our code, <strong><span style=\"color: #0000ff;\"><a style=\"color: #0000ff;\" href=\"https:\/\/github.com\/thebioengineer\/TidyX\/tree\/master\/TidyTuesday_Explained\/065-Data_Cleaning_Excel_Files_2\">CLICK HERE<\/a><\/span><\/strong>.<\/p>\n<p>Happy cleaning!<\/p>\n","protected":false},"excerpt":{"rendered":"<p>In the last episode, I took my crack at cleaning some messy excel data. This week, it is Ellis&#8217; turn! While we took two different approaches to clean the data, we end up with the same result &#8212; a data frame of data that can be analyzed. The key take-a-ways from this two part series [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[44],"tags":[],"class_list":["post-2048","post","type-post","status-publish","format-standard","hentry","category-tidyx-screen-cast"],"_links":{"self":[{"href":"https:\/\/optimumsportsperformance.com\/blog\/wp-json\/wp\/v2\/posts\/2048","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/optimumsportsperformance.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/optimumsportsperformance.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/optimumsportsperformance.com\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/optimumsportsperformance.com\/blog\/wp-json\/wp\/v2\/comments?post=2048"}],"version-history":[{"count":1,"href":"https:\/\/optimumsportsperformance.com\/blog\/wp-json\/wp\/v2\/posts\/2048\/revisions"}],"predecessor-version":[{"id":2049,"href":"https:\/\/optimumsportsperformance.com\/blog\/wp-json\/wp\/v2\/posts\/2048\/revisions\/2049"}],"wp:attachment":[{"href":"https:\/\/optimumsportsperformance.com\/blog\/wp-json\/wp\/v2\/media?parent=2048"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/optimumsportsperformance.com\/blog\/wp-json\/wp\/v2\/categories?post=2048"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/optimumsportsperformance.com\/blog\/wp-json\/wp\/v2\/tags?post=2048"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}