{"id":33238,"date":"2025-03-29T04:27:33","date_gmt":"2025-03-29T03:27:33","guid":{"rendered":"https:\/\/www.graviton.at\/letterswaplibrary\/need-urgent-help-merging-mimic-iv-csv-files-for-ml-project\/"},"modified":"2025-03-29T04:27:33","modified_gmt":"2025-03-29T03:27:33","slug":"need-urgent-help-merging-mimic-iv-csv-files-for-ml-project","status":"publish","type":"post","link":"https:\/\/www.graviton.at\/letterswaplibrary\/need-urgent-help-merging-mimic-iv-csv-files-for-ml-project\/","title":{"rendered":"Need Urgent Help Merging MIMIC-IV CSV Files For ML Project"},"content":{"rendered":"<p><!-- SC_OFF --><\/p>\n<div class=\"md\">\n<p>Hi everyone,<\/p>\n<p>We\u2019re working on a machine learning project using the MIMIC-IV dataset, but we\u2019re struggling to merge the CSV files into a single dataset. The issue is that the zip file is 9GB, and we don\u2019t have enough processing power to efficiently join the tables.<\/p>\n<p>Since MIMIC-IV follows a relational structure, we\u2019re unsure about the best way to merge tables like patients, admissions, diagnoses, procedures, etc. while keeping relationships intact.<\/p>\n<p>Has anyone successfully processed MIMIC-IV under similar constraints? Would SQLite, Dask, or any cloud-based solution be a good alternative? Any sample queries, scripts, or lightweight processing strategies would be a huge help.<\/p>\n<p>We need this urgently, so any quick guidance would be amazing. Thanks in advance!<\/p>\n<\/div>\n<p><!-- SC_ON -->   submitted by   <a href=\"https:\/\/www.reddit.com\/user\/bindumalavika24\"> \/u\/bindumalavika24 <\/a> <br \/> <span><a href=\"https:\/\/www.reddit.com\/r\/datasets\/comments\/1jmcja5\/need_urgent_help_merging_mimiciv_csv_files_for_ml\/\">[link]<\/a><\/span>   <span><a href=\"https:\/\/www.reddit.com\/r\/datasets\/comments\/1jmcja5\/need_urgent_help_merging_mimiciv_csv_files_for_ml\/\">[comments]<\/a><\/span><\/p><div class='watch-action'><div class='watch-position align-right'><div class='action-like'><a class='lbg-style1 like-33238 jlk' href='javascript:void(0)' data-task='like' data-post_id='33238' data-nonce='614a020375' rel='nofollow'><img class='wti-pixel' src='https:\/\/www.graviton.at\/letterswaplibrary\/wp-content\/plugins\/wti-like-post\/images\/pixel.gif' title='Like' \/><span class='lc-33238 lc'>0<\/span><\/a><\/div><\/div> <div class='status-33238 status align-right'><\/div><\/div><div class='wti-clear'><\/div>","protected":false},"excerpt":{"rendered":"<p>Hi everyone, We\u2019re working on a machine learning project using the MIMIC-IV dataset, but we\u2019re struggling to&#8230;<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[85],"tags":[],"class_list":["post-33238","post","type-post","status-publish","format-standard","hentry","category-datatards","wpcat-85-id"],"_links":{"self":[{"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/posts\/33238","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/comments?post=33238"}],"version-history":[{"count":0,"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/posts\/33238\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/media?parent=33238"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/categories?post=33238"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/tags?post=33238"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}