Last updated: 2022-09-07
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File | Version | Author | Date | Message |
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Rmd | af276fa | Dave Tang | 2022-09-07 | Backticks in R |
The only times I used backticks in R was when a file was imported
into R and the column names had spaces (as a side note, please don’t use
spaces in your column or file names but use an underscore,
i.e. _
). For example, you can access col a
by
using backticks.
my_df <- data.frame(
"col a" = 1:5,
"col b" = letters[1:5],
check.names = FALSE)
my_df$`col a`
[1] 1 2 3 4 5
However, I have seen backticks used in combination with symbols, especially with the square bracket. The following code let’s you subset (fourth item) each list item.
my_list <- list(
l = letters[1:5],
u = LETTERS[1:5]
)
lapply(my_list, `[`, 4)
$l
[1] "d"
$u
[1] "D"
It turns out that the use of backticks in the examples above are
consistent, despite two very different applications: the backtick lets
you refer to functions or variables that have otherwise reserved or
illegal names. The first example with my_df
shows the use
of backticks to refer to an illegal column name and the second example
with my_list
shows the use of backticks to refer to a
reserved function name. The square bracket is a function!
You can look up the help pages on the [
function, by
typing ?"["
and the manual will indicate that
[
is used to extract or replace parts of vectors, matrices,
or arrays. In R a function is invoked using parentheses, so to use
[
like a typical function call, we can perform the
following to get the first five heights in the dataset:
`[`(women, 1:5, 1)
[1] 58 59 60 61 62
The code above is actually the same as how you would usually subset a data frame, and is probably the syntax that most people are familiar with.
women[1:5, 1]
[1] 58 59 60 61 62
But it turns out you do not have to use backticks and single- or double-quotes works the same. Despite this, I have seen backticks used more often, which could be due to the fact that in Bash (and Perl!) backticks are used to indicate that the text between the backticks should be executed as a command.
'['(women, 1:5, 1)
[1] 58 59 60 61 62
"["(women, 1:5, 1)
[1] 58 59 60 61 62
It also turns out that (
is a function as well, which
was what I surmised in my
previous post. I can run the first example of my previous post with
backticks.
`(`(v_log <- c(TRUE, FALSE, FALSE, TRUE))
[1] TRUE FALSE FALSE TRUE
In closing, I’ll end with the following quote, which I found while researching this post, that helped me understand backticks in R.
“To understand computations in R, two slogans are helpful:
- Everything that exists is an object.
- Everything that happens is a function call.”
–John Chambers
sessionInfo()
R version 4.2.0 (2022-04-22)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 20.04.4 LTS
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/liblapack.so.3
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] forcats_0.5.1 stringr_1.4.0 dplyr_1.0.9 purrr_0.3.4
[5] readr_2.1.2 tidyr_1.2.0 tibble_3.1.8 ggplot2_3.3.6
[9] tidyverse_1.3.1 workflowr_1.7.0
loaded via a namespace (and not attached):
[1] Rcpp_1.0.8.3 lubridate_1.8.0 getPass_0.2-2 ps_1.7.0
[5] assertthat_0.2.1 rprojroot_2.0.3 digest_0.6.29 utf8_1.2.2
[9] R6_2.5.1 cellranger_1.1.0 backports_1.4.1 reprex_2.0.1
[13] evaluate_0.15 httr_1.4.3 pillar_1.8.1 rlang_1.0.4
[17] readxl_1.4.0 rstudioapi_0.13 whisker_0.4 callr_3.7.0
[21] jquerylib_0.1.4 rmarkdown_2.14 munsell_0.5.0 broom_0.8.0
[25] compiler_4.2.0 httpuv_1.6.5 modelr_0.1.8 xfun_0.31
[29] pkgconfig_2.0.3 htmltools_0.5.2 tidyselect_1.1.2 fansi_1.0.3
[33] crayon_1.5.1 tzdb_0.3.0 dbplyr_2.1.1 withr_2.5.0
[37] later_1.3.0 grid_4.2.0 jsonlite_1.8.0 gtable_0.3.0
[41] lifecycle_1.0.1 DBI_1.1.2 git2r_0.30.1 magrittr_2.0.3
[45] scales_1.2.0 cli_3.3.0 stringi_1.7.6 fs_1.5.2
[49] promises_1.2.0.1 xml2_1.3.3 bslib_0.3.1 ellipsis_0.3.2
[53] generics_0.1.3 vctrs_0.4.1 tools_4.2.0 glue_1.6.2
[57] hms_1.1.2 processx_3.5.3 fastmap_1.1.0 yaml_2.3.5
[61] colorspace_2.0-3 rvest_1.0.2 knitr_1.39 haven_2.5.0
[65] sass_0.4.1