fix: print data frames and vectors

_freeze/posts/2023-10-08_rename-columns-lookup/index/execute-results/html.json

@@ -1,7 +1,7 @@
 {
-  "hash": "2c1b7cd21ed9922aade253ecf8ae1982",
+  "hash": "e011a619a786acecc6faf99647157127",
   "result": {
-    "markdown": "---\ntitle: \"Rename variables in a data frame using an external lookup table\"\nauthor: \"Layal C. Lettry\"\ndate: \"2023-10-08\"\ncategories: [unquote-splice, tidy evaluation, rename, any_of]\nimage: \"image.jpg\"\n---\n\n\n# Rename variables in a data frame using an external lookup table\n\nSuppose that a data frame is present with certain columns that possess the appropriate names, however, the remaining columns require renaming. An existing lookup table is ready to be used for setting new names to these specific columns. \n\nI found the solution by using tidy evaluation tools, namely the unquote-splice `!!!`, and by reading the [article written by Tim Tiefenbach](https://tim-tiefenbach.de/post/2022-rename-columns/#dplyr-tidyverse). \n\n\n::: {.cell}\n\n```{.r .cell-code}\nlibrary(tidyverse)\n```\n:::\n\n\nHere is the data frame with 3 variables, namely `var1`, `var2` and `var4`.\n\n\n::: {.cell}\n\n```{.r .cell-code}\ntest_tib <- tribble(\n  ~var1,      ~var2,   ~var4,\n  \"x\",        \"a\",     1L,\n  \"y\",        \"b\",     2L,\n  \"z\",        \"c\",     3L\n)\n```\n:::\n\n\nDefine the lookup table with the new names. Transform this lookup table into a named vector using `deframe()`. Do not forget that the first argument of `deframe()` should be the new names of the variable and the second one should have the actual names.\n\n\n::: {.cell}\n\n```{.r .cell-code}\nnew_names <- tribble(\n  ~names_var, ~new_names_var,\n  \"var1\",     \"Variable 1\",\n  \"var2\",     \"Variable 2\",\n  \"var3\",     \"Variable 3\",\n  \"var4\",     \"Variable 4\"\n)\n\nnew_names_vec <- deframe(select(new_names, new_names_var, names_var))\n```\n:::\n\n\n# Solution using tidy evaluation and base R\n\nOur goal is to unpack the vector of column name pairs that are actually in our data frame. We could achieve this by using unquote-splice `!!!` which will splice the list of names into the dynamic dots `...` of `rename()`.\n\nHowever, the column `var3` is not found. An error appears.\n\n\n::: {.cell}\n\n```{.r .cell-code}\ntest_tib |>\n  rename(!!!new_names_vec)\n```\n\n::: {.cell-output .cell-output-error}\n```\nError in `rename()`:\n! Can't rename columns that don't exist.\n✖ Column `var3` doesn't exist.\n```\n:::\n:::\n\n\nSelect only the variables which are in the named vector `new_names_vec`.\n\n\n::: {.cell}\n\n```{.r .cell-code}\ntest_tib |>\n  rename(!!!new_names_vec[new_names_vec %in% names(test_tib)])\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n# A tibble: 3 × 3\n  `Variable 1` `Variable 2` `Variable 4`\n  <chr>        <chr>               <int>\n1 x            a                       1\n2 y            b                       2\n3 z            c                       3\n```\n:::\n:::\n\n\n# Solution using dplyr\n\nInstead of selecting the common variables, you can use `any_of()` which does this selection automatically.\n\n\n::: {.cell}\n\n```{.r .cell-code}\ntest_tib |>\n  rename(any_of(new_names_vec))\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n# A tibble: 3 × 3\n  `Variable 1` `Variable 2` `Variable 4`\n  <chr>        <chr>               <int>\n1 x            a                       1\n2 y            b                       2\n3 z            c                       3\n```\n:::\n:::\n\n\n\n# Sources\n\nThese examples are inspired by:\n\n- [Article written by Tim Tiefenbach](https://tim-tiefenbach.de/post/2022-rename-columns/#dplyr-tidyverse)\n\n- [https://dcl-prog.stanford.edu/tidy-eval-detailed.html](https://dcl-prog.stanford.edu/tidy-eval-detailed.html)\n\n- [https://adv-r.hadley.nz/quasiquotation.html#unquoting-many-arguments](https://adv-r.hadley.nz/quasiquotation.html#unquoting-many-arguments)\n\n- [https://rlang.r-lib.org/reference/topic-inject.html#splicing-with--1](https://rlang.r-lib.org/reference/topic-inject.html#splicing-with--1)\n\n- [https://rlang.r-lib.org/reference/dyn-dots.html](https://rlang.r-lib.org/reference/dyn-dots.html)\n",
+    "markdown": "---\ntitle: \"Rename variables in a data frame using an external lookup table\"\nauthor: \"Layal C. Lettry\"\ndate: \"2023-10-08\"\ncategories: [unquote-splice, tidy evaluation, rename, any_of]\nimage: \"image.jpg\"\n---\n\n\n# Rename variables in a data frame using an external lookup table\n\nSuppose that a data frame is present with certain columns that possess the appropriate names, however, the remaining columns require renaming. An existing lookup table is ready to be used for setting new names to these specific columns.\n\nI found the solution by using tidy evaluation tools, namely the unquote-splice `!!!`, and by reading the [article written by Tim Tiefenbach](https://tim-tiefenbach.de/post/2022-rename-columns/#dplyr-tidyverse).\n\n\n::: {.cell}\n\n```{.r .cell-code}\nlibrary(tidyverse)\n```\n:::\n\n\nHere is the data frame with 3 variables, namely `var1`, `var2` and `var4`.\n\n\n::: {.cell}\n\n```{.r .cell-code}\ntest_tib <- tribble(\n  ~var1,      ~var2,   ~var4,\n  \"x\",        \"a\",     1L,\n  \"y\",        \"b\",     2L,\n  \"z\",        \"c\",     3L\n)\ntest_tib\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n# A tibble: 3 × 3\n  var1  var2   var4\n  <chr> <chr> <int>\n1 x     a         1\n2 y     b         2\n3 z     c         3\n```\n:::\n:::\n\n\nDefine the lookup table with the new names. Transform this lookup table into a named vector using `deframe()`. Do not forget that the first argument of `deframe()` should be the new names of the variable and the second one should have the actual names.\n\n\n::: {.cell}\n\n```{.r .cell-code}\nnew_names <- tribble(\n  ~names_var, ~new_names_var,\n  \"var1\",     \"Variable 1\",\n  \"var2\",     \"Variable 2\",\n  \"var3\",     \"Variable 3\",\n  \"var4\",     \"Variable 4\"\n)\nnew_names\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n# A tibble: 4 × 2\n  names_var new_names_var\n  <chr>     <chr>        \n1 var1      Variable 1   \n2 var2      Variable 2   \n3 var3      Variable 3   \n4 var4      Variable 4   \n```\n:::\n\n```{.r .cell-code}\nnew_names_vec <- deframe(select(new_names, new_names_var, names_var))\nnew_names_vec\n```\n\n::: {.cell-output .cell-output-stdout}\n```\nVariable 1 Variable 2 Variable 3 Variable 4 \n    \"var1\"     \"var2\"     \"var3\"     \"var4\" \n```\n:::\n:::\n\n\n# Solution using tidy evaluation and base R\n\nOur goal is to unpack the vector of column name pairs that are actually in our data frame. We could achieve this by using unquote-splice `!!!` which will splice the list of names into the dynamic dots `...` of `rename()`.\n\nHowever, the column `var3` is not found. An error appears.\n\n\n::: {.cell}\n\n```{.r .cell-code}\ntest_tib |>\n  rename(!!!new_names_vec)\n```\n\n::: {.cell-output .cell-output-error}\n```\nError in `rename()`:\n! Can't rename columns that don't exist.\n✖ Column `var3` doesn't exist.\n```\n:::\n:::\n\n\nSelect only the variables which are in the named vector `new_names_vec`.\n\n\n::: {.cell}\n\n```{.r .cell-code}\ntest_tib |>\n  rename(!!!new_names_vec[new_names_vec %in% names(test_tib)])\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n# A tibble: 3 × 3\n  `Variable 1` `Variable 2` `Variable 4`\n  <chr>        <chr>               <int>\n1 x            a                       1\n2 y            b                       2\n3 z            c                       3\n```\n:::\n:::\n\n\n# Solution using dplyr\n\nInstead of selecting the common variables, you can use `any_of()` which does this selection automatically.\n\n\n::: {.cell}\n\n```{.r .cell-code}\ntest_tib |>\n  rename(any_of(new_names_vec))\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n# A tibble: 3 × 3\n  `Variable 1` `Variable 2` `Variable 4`\n  <chr>        <chr>               <int>\n1 x            a                       1\n2 y            b                       2\n3 z            c                       3\n```\n:::\n:::\n\n\n# Sources\n\nThese examples are inspired by:\n\n-   [Article written by Tim Tiefenbach](https://tim-tiefenbach.de/post/2022-rename-columns/#dplyr-tidyverse)\n\n-   <https://dcl-prog.stanford.edu/tidy-eval-detailed.html>\n\n-   <https://adv-r.hadley.nz/quasiquotation.html#unquoting-many-arguments>\n\n-   [https://rlang.r-lib.org/reference/topic-inject.html#splicing-with--1](https://rlang.r-lib.org/reference/topic-inject.html#splicing-with--1)\n\n-   <https://rlang.r-lib.org/reference/dyn-dots.html>\n",
     "supporting": [],
     "filters": [
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posts/2023-10-08_rename-columns-lookup/index.qmd

@@ -8,9 +8,9 @@ image: "image.jpg"
 
 # Rename variables in a data frame using an external lookup table
 
-Suppose that a data frame is present with certain columns that possess the appropriate names, however, the remaining columns require renaming. An existing lookup table is ready to be used for setting new names to these specific columns. 
+Suppose that a data frame is present with certain columns that possess the appropriate names, however, the remaining columns require renaming. An existing lookup table is ready to be used for setting new names to these specific columns.
 
-I found the solution by using tidy evaluation tools, namely the unquote-splice `!!!`, and by reading the [article written by Tim Tiefenbach](https://tim-tiefenbach.de/post/2022-rename-columns/#dplyr-tidyverse). 
+I found the solution by using tidy evaluation tools, namely the unquote-splice `!!!`, and by reading the [article written by Tim Tiefenbach](https://tim-tiefenbach.de/post/2022-rename-columns/#dplyr-tidyverse).
 
 ```{r}
 #| label: load_libraries
@@ -32,6 +32,7 @@ test_tib <- tribble(
   "y",        "b",     2L,
   "z",        "c",     3L
 )
+test_tib
 ```
 
 Define the lookup table with the new names. Transform this lookup table into a named vector using `deframe()`. Do not forget that the first argument of `deframe()` should be the new names of the variable and the second one should have the actual names.
@@ -48,8 +49,10 @@ new_names <- tribble(
   "var3",     "Variable 3",
   "var4",     "Variable 4"
 )
+new_names
 
 new_names_vec <- deframe(select(new_names, new_names_var, names_var))
+new_names_vec
 ```
 
 # Solution using tidy evaluation and base R
@@ -90,17 +93,16 @@ test_tib |>
   rename(any_of(new_names_vec))
 ```
 
-
 # Sources
 
 These examples are inspired by:
 
-- [Article written by Tim Tiefenbach](https://tim-tiefenbach.de/post/2022-rename-columns/#dplyr-tidyverse)
+-   [Article written by Tim Tiefenbach](https://tim-tiefenbach.de/post/2022-rename-columns/#dplyr-tidyverse)
 
-- [https://dcl-prog.stanford.edu/tidy-eval-detailed.html](https://dcl-prog.stanford.edu/tidy-eval-detailed.html)
+-   <https://dcl-prog.stanford.edu/tidy-eval-detailed.html>
 
-- [https://adv-r.hadley.nz/quasiquotation.html#unquoting-many-arguments](https://adv-r.hadley.nz/quasiquotation.html#unquoting-many-arguments)
+-   <https://adv-r.hadley.nz/quasiquotation.html#unquoting-many-arguments>
 
-- [https://rlang.r-lib.org/reference/topic-inject.html#splicing-with--1](https://rlang.r-lib.org/reference/topic-inject.html#splicing-with--1)
+-   [https://rlang.r-lib.org/reference/topic-inject.html#splicing-with--1](https://rlang.r-lib.org/reference/topic-inject.html#splicing-with--1)
 
-- [https://rlang.r-lib.org/reference/dyn-dots.html](https://rlang.r-lib.org/reference/dyn-dots.html)
+-   <https://rlang.r-lib.org/reference/dyn-dots.html>