{"version":"1.0","provider_url":"https:\/\/warpwire.duke.edu","provider_name":"Warpwire","is_public":true,"duration":6260.18,"has_caption":true,"links":{"caption":[{"label":"English","url":"https:\/\/warpwire.duke.edu\/api\/caption\/DYMHAA\/292157\/vtt\/?nonce=b8a149c0a43d02c9a7ace2c8e7e93e2f&expiration=1782378000&signature=e648d5c43a1bd6bd1782f852dee252931f3b77ad8fb7d645c6c48a51c7c99941"}]},"views":0,"upload_date":"2023-02-15T19:16:48+00:00","description":"In this intermediate workshop, following on Pandas 101, we learn about using Python to melt wide tabular data into a tidy form, visualize with Seaborn, and JOIN multiple tables together with merge.","author_name":"Eric Monson","html":"\u003Ciframe width=\"640\" height=\"360\" src=\"https:\/\/warpwire.duke.edu\/w\/DYMHAA\/\" frameborder=\"0\" allow=\"autoplay; encrypted-media; camera; microphone; picture-in-picture\" allowfullscreen\u003E\u003C\/iframe\u003E","height":360,"width":640,"thumbnail_height":360,"thumbnail_width":640,"url":"https:\/\/warpwire.duke.edu\/w\/DYMHAA\/","type":"video","title":"Pandas102: Tidy data (melt) & JOIN (merge)","thumbnail_url":"https:\/\/warpwire.duke.edu\/img\/99270955-B8B2-479C-AAD7-F22DE7908EEA\/84B39BF2-BD29-4B34-98E8-E46A0EAF55ED\/large\/"}