This is the first one of a 3-posts-series, where I go from fetching Twitter users and preparing the data to visualizing it (If I wanted to show everything I’ve done in a single post, it would be almost as long as my first one! And believe me: nobody wants that ???? ):

1. How to fetch Twitter users with R: this one, the title is kind of self explanatory…
2. How to deal with ggplotly huge maps: where I go through the details of why I chose not to use ggplotly and use plot_geo instead to generate the HTML.
3. How to plot animated maps with gganimate: again, pretty obvious subject.

Finally I present my favourite visualization here.

I should warn you that there are a lot of emojis in this series, courtesy of the emo package Hadley recently released and I fanatically adopted ????

Let’s get started!

Getting Twitter users

I had to learn how to retrieve data from the Twitter API, and I chose to use the rtweet package, which is super easy to use! Since I only use public data I don’t have to worry about getting my Twitter personal access token.

Every R-Ladies’ chapter uses a standard handle, with the RLadiesLocation format (thankfully they are very compliant with this!). I use the rtweet::search_users function, setting the query to be searched with q = 'RLadies' and the number of users to retrieve with n = 1000, that being the maximum from a single search. As I want a dataframe as a result, I set the parse parameter to TRUE. This way I get 1,000 rows of users, with 36 variables regarding them. I’m only showing the variables I’m going to use, but there is a lot of extra information there.

library(rtweet)

users <- search_users(q = 'RLadies',
                      n = 1000,
                      parse = TRUE)

Let’s see what it returns:

library(DT)
datatable(users[, c(2:5)], rownames = FALSE,
          options = list(pageLength = 5))