Many of us have faced this dilemma: it’s the night before a big presentation and you want to make sure you are prepared. However, as you are going through the slides, you notice there is an error in your analyses and you need to update the results on ALL of your slides.
Updating CVs/resumes can be a frustrating process, especially when there are multiple versions you may have across time that you need to draw from during the update. In my case, if I want to include an experience on my new CV/resume from when I was in undergrad, I sometimes end up wasting a lot of time just trying to figure out which of the versions of my resume had that information!
Understanding how outcomes vary based on membership to different groups is useful across many contexts. For instance, it is important to know how the proportion of people who check social media or buy cigarettes at least once a day varies across gender and socioeconomic status.
Regular expressions can be used to speed up data cleaning because they automate process of finding a pattern within strings. This can be a huge time saver, especially with larger datasets.