Data Wrangling Techniques in Julia - Part 2 | Tom Kwong

As a data scientist, it is super important to sharpen your skills and learn to use the tools effectively. This is the second part of the series. Part 1 can be found at https://www.youtube.com/watch?v=txme9o0EdLk This video demonstrates how to perform data wrangling tasks using two-sample data sets. It demonstrates various data wrangling techniques including: Read: skipping lines, reading compressed CSV files, specifying a missing string Clean: removing non-useful columns, removing rows with missing data Tidy: stacking and unstacking data frames Analyze: grouping and aggregating data Visualize: plotting line chart, bar chart, histogram, heatmap, etc. Quick links 01:12 GitHub repo for this video 02:07 Washington state youth suicide data set 29:10 TIPS yield curve and inflation compensation data set Related GitHub repo https://github.com/tk3369/data-wrangling-techniques-in-julia 00:00 Welcome! 00:10 Help us add time stamps or captions to this video! See the description for details. Want to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/JuliaCommunity/YouTubeVideoTimestamps Interested in improving the auto generated captions? Get involved here: https://github.com/JuliaCommunity/YouTubeVideoSubtitles