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The goal of tibblify is to provide an easy way to convert a nested list into a tibble.
Install the released version of tibblify from CRAN:
install.packages("tibblify")Install the development version of tibblify from GitHub:
# install.packages("pak")
pak::pak("wranglezone/tibblify")To illustrate how tibblify() works, we’ll start with a
list containing information about four GitHub users.
library(tibblify)
library(repurrrsive)
gh_users_small <- purrr::map(
repurrrsive::gh_users,
~ .x[c("followers", "login", "url", "name", "location", "email", "public_gists")]
)
names(gh_users_small[[1]])
#> [1] "followers" "login" "url" "name" "location"
#> [6] "email" "public_gists"We can rectangle gh_users_small automatically with
tibblify():
tibblify(gh_users_small)
#> # A tibble: 6 × 7
#> followers login url name location email public_gists
#> <int> <chr> <chr> <chr> <chr> <chr> <int>
#> 1 303 gaborcsardi https://api.github.co… Gábo… Chippen… csar… 6
#> 2 780 jennybc https://api.github.co… Jenn… Vancouv… <NA> 54
#> 3 3958 jtleek https://api.github.co… Jeff… Baltimo… <NA> 12
#> 4 115 juliasilge https://api.github.co… Juli… Salt La… <NA> 4
#> 5 213 leeper https://api.github.co… Thom… London,… <NA> 46
#> 6 34 masalmon https://api.github.co… Maël… Barcelo… <NA> 0We can avoid the note about the unspecified field by formally
providing a spec starting with guess_tspec():
spec <- guess_tspec(gh_users_small, inform_unspecified = FALSE)
# Drop the unused email specification.
spec$fields$email <- NULL
tibblify(gh_users_small, spec = spec)
#> # A tibble: 6 × 6
#> followers login url name location public_gists
#> <int> <chr> <chr> <chr> <chr> <int>
#> 1 303 gaborcsardi https://api.github.com/user… Gábo… Chippen… 6
#> 2 780 jennybc https://api.github.com/user… Jenn… Vancouv… 54
#> 3 3958 jtleek https://api.github.com/user… Jeff… Baltimo… 12
#> 4 115 juliasilge https://api.github.com/user… Juli… Salt La… 4
#> 5 213 leeper https://api.github.com/user… Thom… London,… 46
#> 6 34 masalmon https://api.github.com/user… Maël… Barcelo… 0Learn more in vignette("tibblify").
jsonlite::fromJSON() is excellent for parsing JSON, but
tibblify allows for strict specifications and can be faster
for complex nested lists.tidyr::hoist() and tidyr::unnest_longer()
allow for step-by-step rectangling. tibblify aims to
rectangle the data in a single step based on a schema.Please note that the tibblify project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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