spec() to retrieve the full column specification for this data.
read_csv(readr_example("mtcars.csv")) %>% spec()
The result will be
It shows the column specification of the tibble.
What Flm wrote. And I'd add it's useful because you can copy-paste it into the
col_types argument of
read_csv(), and then:
1/ if the data changes one day and does not match the specification anymore, you can get a helpful error (instead of doing wrong computations without noticing)
2/ once the
col_types is written, you can tweak it, for example reading a column as an integer or factor, and specifying levels etc.
col_type argument is useful, but when you have many columns it's painful to type a description of each one,
spec() gives you a first version.