When it comes to using tidyverse in non-American contexts it gets often a little bit tricky. The last time I encountered a problem was when I tried to show the Euro-sign (€) in a PDF created with quarto and the gt-package.

Using html as output format everything was fine, but when I tried to create a PDF the Euro-sign was replaced by EUR.

There’s already an open issue at github ([ https://github.com/rstudio/gt/issues/1345]). But it’s getting pushed further and further down on the list of expected release versions.

Sometimes I want to summarize some categories which don’t have much impact on my analysis. So the best way to do this is using some of the forcats::fct_lump*() functions. But I often struggle to find the way using the weights to order the categories. That’s because the main use case of fct_lump() is a vector of a factor containing several values and getting the most n and the rest combined as “other”.

When working with data provided by common APIs you will almost always get in contact with JSON formatted data. Using R’s rjson::fromJSON will transform JSON to R’s lists. So far so good. Converting those lists to tibble using tibble::as_tibble will fail when the JSON (and therefor the list) contains NULL values. So you havve to replace them before building the tibble.

Lately I tried to query BigQuery using bigrquery. Unfortunately I got an error: Error in strsplit(name, ".", fixed = TRUE) : non-character argument

Lately I wanted to play around with nflfastR. That’s a great package giving you access to NFL’s play-by-play data since 1999. It let’s you download all the data and store it in several different databases.

Unfortunately I ran into trouble when I tried to import the data to Google’s BigQuery.