Keeps a handful of id columns plus every column sharing a prefix – the
select(id, starts_with("demo_")) idiom – in one tidy call.
Arguments
- data
A data frame. If omitted, the session default (
use_dataset()) is used.- prefix
One or more column-name prefixes to keep (e.g.
"demo_", orc("demo_", "ratings_")).- keep
Optional character vector of additional column names to retain in front of the prefixed block (e.g. an id column).
Details
Survey questionnaires are usually organised by prefix (demo_, ratings_,
partner_, ...), so this is a quick way to grab one block plus a couple of id
columns without naming every variable. Order is keep first, then the
prefix-matching columns in their original order.
See also
read_folder(), calc_percentage_multi().
Other import:
parse_filename(),
read_folder(),
select_suffix()
Examples
select_prefix(podracing_survey, "demo_", keep = "respondent_id")
#> # A tibble: 1,000 × 7
#> respondent_id demo_age demo_gender demo_edu demo_country demo_job demo_sector
#> <chr> <int> <chr> <chr> <chr> <chr> <chr>
#> 1 R00001 35 Male Bachelo… Sweden Student Arts and e…
#> 2 R00002 29 Male Bachelo… United King… Student Education
#> 3 R00003 16 Male Upper s… Brazil Employe… Informatio…
#> 4 R00004 16 Male Upper s… Australia Employe… Human heal…
#> 5 R00005 16 Male Bachelo… France Student Education
#> 6 R00006 36 Male Short-c… Canada Student Other serv…
#> 7 R00007 30 Male Master … Mexico Employe… Human heal…
#> 8 R00008 23 Female Short-c… France Employe… Human heal…
#> 9 R00009 23 Female Upper s… United Stat… Employe… Manufactur…
#> 10 R00010 39 Male Upper s… United King… Employe… Manufactur…
#> # ℹ 990 more rows
select_prefix(podracing_survey, c("ratings_", "partner_"))
#> # A tibble: 1,000 × 12
#> ratings_atmosphere ratings_commentary ratings_safety ratings_speed
#> <chr> <chr> <chr> <chr>
#> 1 Very good Ok Ok Very good
#> 2 Bad Very bad Bad Bad
#> 3 Very good Good Very good Very good
#> 4 Very good Bad Good Good
#> 5 Very good Bad Very bad Good
#> 6 Very good Ok Good Ok
#> 7 Very good Good Good Very good
#> 8 Ok Bad Good Good
#> 9 Very good Very good Very good Very good
#> 10 Good Bad Bad Good
#> # ℹ 990 more rows
#> # ℹ 8 more variables: ratings_value <chr>, ratings_venue <chr>,
#> # partner_recall_PodTech <chr>, partner_likeability_PodTech <chr>,
#> # partner_recall_BanthaBrew <chr>, partner_likeability_BanthaBrew <chr>,
#> # partner_recall_JawaJuice <chr>, partner_likeability_JawaJuice <chr>