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