This is part one of a two-part series on building effective visualizations. In this post, we take a shallow dive into evaluating existing visualizations. In the next post, we’ll dive a little deeper as we explore techniques on how to improve them.
If you aspire to be a data scientist, you’re really aspiring to be a data wrangler. You see, 80% of your working hours will be spent wrangling the data. That’s on average. On some projects, you will spend more than 100% of your “working” hours with your lasso. I hope you enjoy that sort of thing.