tor (to-R) helps you to import multiple files at once. For example:
list_rds() to import all .csv files from your working directory into a list.load_csv() to import all .csv files from your working directory into your global environment.Install tor from CRAN with:
Or install the development version from GitHub with:
# install.packages("devtools")
devtools::install_github("maurolepore/tor")
library(tor) withr::local_options(readr.show_col_types = FALSE)
list_*(): Import multiple files from a directory into a list
All functions default to importing files from the working directory.
dir() #> [1] "_pkgdown.yml" "codecov.yml" "cran-comments.md" "csv1.csv" #> [5] "csv2.csv" "DESCRIPTION" "inst" "LICENSE.md" #> [9] "man" "NAMESPACE" "NEWS.md" "R" #> [13] "README.md" "README.Rmd" "tests" "tor.Rproj" #> [17] "vignettes" list_csv() #> $csv1 #> # A tibble: 2 × 1 #> x #> <dbl> #> 1 1 #> 2 2 #> #> $csv2 #> # A tibble: 2 × 1 #> y #> <chr> #> 1 a #> 2 b
Often you will specify a path to read from.
# Helpes create paths to examples
tor_example()
#> [1] "csv" "mixed" "rdata" "rds" "tsv"
(path_rds <- tor_example("rds"))
#> [1] "/usr/local/lib/R/site-library/tor/extdata/rds"
dir(path_rds)
#> [1] "rds1.rds" "rds2.rds"
list_rds(path_rds)
#> $rds1
#> # A tibble: 2 × 1
#> x
#> <dbl>
#> 1 1
#> 2 2
#>
#> $rds2
#> # A tibble: 2 × 1
#> y
#> <chr>
#> 1 a
#> 2 b
You may read all files with a particular extension.
path_mixed <- tor_example("mixed")
dir(path_mixed)
#> [1] "csv.csv" "lower_rdata.rdata" "rda.rda"
#> [4] "upper_rdata.RData"
list_rdata(path_mixed)
#> $lower_rdata
#> # A tibble: 2 × 1
#> y
#> <chr>
#> 1 a
#> 2 b
#>
#> $rda
#> # A tibble: 2 × 1
#> y
#> <chr>
#> 1 a
#> 2 b
#>
#> $upper_rdata
#> # A tibble: 2 × 1
#> y
#> <chr>
#> 1 a
#> 2 b
Or you may read specific files matching a pattern.
list_rdata(path_mixed, regexp = "[.]RData", ignore.case = FALSE) #> $upper_rdata #> # A tibble: 2 × 1 #> y #> <chr> #> 1 a #> 2 b
list_any() is the most flexible function. You supply the function to read with.
(path_csv <- tor_example("csv"))
#> [1] "/usr/local/lib/R/site-library/tor/extdata/csv"
dir(path_csv)
#> [1] "csv1.csv" "csv2.csv"
list_any(path_csv, read.csv)
#> $csv1
#> # A tibble: 2 × 1
#> x
#> <int>
#> 1 1
#> 2 2
#>
#> $csv2
#> # A tibble: 2 × 1
#> y
#> <chr>
#> 1 a
#> 2 b
It understands lambda functions and formulas (powered by rlang).
# Use the pipe (%>%)
library(magrittr)
(path_rdata <- tor_example("rdata"))
#> [1] "/usr/local/lib/R/site-library/tor/extdata/rdata"
dir(path_rdata)
#> [1] "rdata1.rdata" "rdata2.rdata"
path_rdata %>%
list_any(function(x) get(load(x)))
#> $rdata1
#> # A tibble: 2 × 1
#> x
#> <dbl>
#> 1 1
#> 2 2
#>
#> $rdata2
#> # A tibble: 2 × 1
#> y
#> <chr>
#> 1 a
#> 2 b
# Same
path_rdata %>%
list_any(~ get(load(.x)))
#> $rdata1
#> # A tibble: 2 × 1
#> x
#> <dbl>
#> 1 1
#> 2 2
#>
#> $rdata2
#> # A tibble: 2 × 1
#> y
#> <chr>
#> 1 a
#> 2 b
Pass additional arguments via ... or inside the lambda function.
path_csv %>% list_any(readr::read_csv, skip = 1) #> $csv1 #> # A tibble: 1 × 1 #> `1` #> <dbl> #> 1 2 #> #> $csv2 #> # A tibble: 1 × 1 #> a #> <chr> #> 1 b path_csv %>% list_any(~ read.csv(., stringsAsFactors = FALSE)) #> $csv1 #> # A tibble: 2 × 1 #> x #> <int> #> 1 1 #> 2 2 #> #> $csv2 #> # A tibble: 2 × 1 #> y #> <chr> #> 1 a #> 2 b
It also provides the arguments regexp, ignore.case, and invert to pick specific files in a directory (powered by fs).
path_mixed <- tor_example("mixed")
dir(path_mixed)
#> [1] "csv.csv" "lower_rdata.rdata" "rda.rda"
#> [4] "upper_rdata.RData"
path_mixed %>%
list_any(~ get(load(.)), "[.]Rdata$", ignore.case = TRUE)
#> $lower_rdata
#> # A tibble: 2 × 1
#> y
#> <chr>
#> 1 a
#> 2 b
#>
#> $upper_rdata
#> # A tibble: 2 × 1
#> y
#> <chr>
#> 1 a
#> 2 b
path_mixed %>%
list_any(~ get(load(.)), regexp = "[.]csv$", invert = TRUE)
#> $lower_rdata
#> # A tibble: 2 × 1
#> y
#> <chr>
#> 1 a
#> 2 b
#>
#> $rda
#> # A tibble: 2 × 1
#> y
#> <chr>
#> 1 a
#> 2 b
#>
#> $upper_rdata
#> # A tibble: 2 × 1
#> y
#> <chr>
#> 1 a
#> 2 bload_*(): Load multiple files from a directory into an environment
All functions default to importing files from the working directory and into the global environment.
# The working directory contains .csv files dir() #> [1] "_pkgdown.yml" "codecov.yml" "cran-comments.md" "csv1.csv" #> [5] "csv2.csv" "DESCRIPTION" "inst" "LICENSE.md" #> [9] "man" "NAMESPACE" "NEWS.md" "R" #> [13] "README.md" "README.Rmd" "tests" "tor.Rproj" #> [17] "vignettes" load_csv() # Each file is now available as a dataframe in the global environment csv1 #> # A tibble: 2 × 1 #> x #> <dbl> #> 1 1 #> 2 2 csv2 #> # A tibble: 2 × 1 #> y #> <chr> #> 1 a #> 2 b rm(list = ls())
You may import files from a specific path.
(path_mixed <- tor_example("mixed"))
#> [1] "/usr/local/lib/R/site-library/tor/extdata/mixed"
dir(path_mixed)
#> [1] "csv.csv" "lower_rdata.rdata" "rda.rda"
#> [4] "upper_rdata.RData"
load_rdata(path_mixed)
ls()
#> [1] "lower_rdata" "path_mixed" "rda" "upper_rdata"
rda
#> # A tibble: 2 × 1
#> y
#> <chr>
#> 1 a
#> 2 b
You may import files into a specific environment.
e <- new.env() ls(e) #> character(0) load_rdata(path_mixed, envir = e) ls(e) #> [1] "lower_rdata" "rda" "upper_rdata"
For more flexibility use load_any() with a function able to read one file of the format you want to import.
dir()
#> [1] "_pkgdown.yml" "codecov.yml" "cran-comments.md" "csv1.csv"
#> [5] "csv2.csv" "DESCRIPTION" "inst" "LICENSE.md"
#> [9] "man" "NAMESPACE" "NEWS.md" "R"
#> [13] "README.md" "README.Rmd" "tests" "tor.Rproj"
#> [17] "vignettes"
load_any(".", .f = readr::read_csv, regexp = "[.]csv$")
# The data is now available in the global environment
csv1
#> # A tibble: 2 × 1
#> x
#> <dbl>
#> 1 1
#> 2 2
csv2
#> # A tibble: 2 × 1
#> y
#> <chr>
#> 1 a
#> 2 b
Two great packages to read and write data are rio and io.
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