Don't mention iris dataset in documentation

DESCRIPTION

@@ -50,4 +50,4 @@ Config/testthat/edition: 3
 Encoding: UTF-8
 Note: libxls v1.6.2 (patched) 45abe77
 Roxygen: list(markdown = TRUE)
-RoxygenNote: 7.2.3
+RoxygenNote: 7.3.2

R/read_excel.R

@@ -57,13 +57,17 @@ NULL
 #' read_excel(datasets, "mtcars")
 #'
 #' # Skip rows and use default column names
-#' read_excel(datasets, skip = 148, col_names = FALSE)
+#' read_excel(datasets, skip = 10, col_names = FALSE)
 #'
 #' # Recycle a single column type
 #' read_excel(datasets, col_types = "text")
 #'
 #' # Specify some col_types and guess others
-#' read_excel(datasets, col_types = c("text", "guess", "numeric", "guess", "guess"))
+#' read_excel(
+#'   readxl_example("deaths.xlsx"),
+#'   skip = 4, n_max = 10, col_names = TRUE,
+#'   col_types = c("text", "text", "guess", "guess", "guess", "guess")
+#' )
 #'
 #' # Accomodate a column with disparate types via col_type = "list"
 #' df <- read_excel(readxl_example("clippy.xlsx"), col_types = c("text", "list"))

README.Rmd

@@ -93,7 +93,7 @@ Specify a worksheet by name or number.
 
 ```{r}
 read_excel(xlsx_example, sheet = "chickwts")
-read_excel(xls_example, sheet = 4)
+read_excel(xls_example, sheet = 3)
 ```
 
 There are various ways to control which cells are read. You can even specify the sheet here, if providing an Excel-style cell range.
@@ -109,7 +109,7 @@ read_excel(xlsx_example, range = "mtcars!B1:D5")
 If `NA`s are represented by something other than blank cells, set the `na` argument.
 
 ```{r}
-read_excel(xlsx_example, na = "setosa")
+read_excel(xlsx_example, na = "0")
 ```
 
 If you are new to the tidyverse conventions for data import, you may want to consult the [data import chapter](https://r4ds.had.co.nz/data-import.html) in R for Data Science. readxl will become increasingly consistent with other packages, such as [readr](https://readr.tidyverse.org/).
@@ -149,7 +149,7 @@ Here are some other packages with functionality that is complementary to readxl
 __Writing Excel files__: The example files `datasets.xlsx` and `datasets.xls` were created with the help of [openxlsx](https://CRAN.R-project.org/package=openxlsx) (and Excel). openxlsx provides "a high level interface to writing, styling and editing worksheets".
 
 ```{r eval = FALSE}
-l <- list(iris = iris, mtcars = mtcars, chickwts = chickwts, quakes = quakes)
+l <- list(mtcars = mtcars, chickwts = chickwts, quakes = quakes)
 openxlsx::write.xlsx(l, file = "inst/extdata/datasets.xlsx")
 ```
 

README.md

@@ -75,7 +75,7 @@ readxl_example()
 #>  [5] "deaths.xls"    "deaths.xlsx"   "geometry.xls"  "geometry.xlsx"
 #>  [9] "type-me.xls"   "type-me.xlsx"
 readxl_example("clippy.xls")
-#> [1] "/private/tmp/RtmpM1GkLC/temp_libpatha8e46f7f62bf/readxl/extdata/clippy.xls"
+#> [1] "/Users/fontikar/Library/R/arm64/4.4/library/readxl/extdata/clippy.xls"
 ```
 
 `read_excel()` reads both xls and xlsx files and detects the format from
@@ -84,30 +84,30 @@ the extension.
 ``` r
 xlsx_example <- readxl_example("datasets.xlsx")
 read_excel(xlsx_example)
-#> # A tibble: 150 × 5
-#>   Sepal.Length Sepal.Width Petal.Length Petal.Width Species
-#>          <dbl>       <dbl>        <dbl>       <dbl> <chr>  
-#> 1          5.1         3.5          1.4         0.2 setosa 
-#> 2          4.9         3            1.4         0.2 setosa 
-#> 3          4.7         3.2          1.3         0.2 setosa 
-#> # ℹ 147 more rows
+#> # A tibble: 32 × 11
+#>     mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
+#>   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
+#> 1  21       6   160   110  3.9   2.62  16.5     0     1     4     4
+#> 2  21       6   160   110  3.9   2.88  17.0     0     1     4     4
+#> 3  22.8     4   108    93  3.85  2.32  18.6     1     1     4     1
+#> # ℹ 29 more rows
 
 xls_example <- readxl_example("datasets.xls")
 read_excel(xls_example)
-#> # A tibble: 150 × 5
-#>   Sepal.Length Sepal.Width Petal.Length Petal.Width Species
-#>          <dbl>       <dbl>        <dbl>       <dbl> <chr>  
-#> 1          5.1         3.5          1.4         0.2 setosa 
-#> 2          4.9         3            1.4         0.2 setosa 
-#> 3          4.7         3.2          1.3         0.2 setosa 
-#> # ℹ 147 more rows
+#> # A tibble: 32 × 11
+#>     mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
+#>   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
+#> 1  21       6   160   110  3.9   2.62  16.5     0     1     4     4
+#> 2  21       6   160   110  3.9   2.88  17.0     0     1     4     4
+#> 3  22.8     4   108    93  3.85  2.32  18.6     1     1     4     1
+#> # ℹ 29 more rows
 ```
 
 List the sheet names with `excel_sheets()`.
 
 ``` r
 excel_sheets(xlsx_example)
-#> [1] "iris"     "mtcars"   "chickwts" "quakes"
+#> [1] "mtcars"   "chickwts" "quakes"
 ```
 
 Specify a worksheet by name or number.
@@ -121,7 +121,7 @@ read_excel(xlsx_example, sheet = "chickwts")
 #> 2    160 horsebean
 #> 3    136 horsebean
 #> # ℹ 68 more rows
-read_excel(xls_example, sheet = 4)
+read_excel(xls_example, sheet = 3)
 #> # A tibble: 1,000 × 5
 #>     lat  long depth   mag stations
 #>   <dbl> <dbl> <dbl> <dbl>    <dbl>
@@ -136,34 +136,34 @@ specify the sheet here, if providing an Excel-style cell range.
 
 ``` r
 read_excel(xlsx_example, n_max = 3)
-#> # A tibble: 3 × 5
-#>   Sepal.Length Sepal.Width Petal.Length Petal.Width Species
-#>          <dbl>       <dbl>        <dbl>       <dbl> <chr>  
-#> 1          5.1         3.5          1.4         0.2 setosa 
-#> 2          4.9         3            1.4         0.2 setosa 
-#> 3          4.7         3.2          1.3         0.2 setosa
+#> # A tibble: 3 × 11
+#>     mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
+#>   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
+#> 1  21       6   160   110  3.9   2.62  16.5     0     1     4     4
+#> 2  21       6   160   110  3.9   2.88  17.0     0     1     4     4
+#> 3  22.8     4   108    93  3.85  2.32  18.6     1     1     4     1
 read_excel(xlsx_example, range = "C1:E4")
 #> # A tibble: 3 × 3
-#>   Petal.Length Petal.Width Species
-#>          <dbl>       <dbl> <chr>  
-#> 1          1.4         0.2 setosa 
-#> 2          1.4         0.2 setosa 
-#> 3          1.3         0.2 setosa
+#>    disp    hp  drat
+#>   <dbl> <dbl> <dbl>
+#> 1   160   110  3.9 
+#> 2   160   110  3.9 
+#> 3   108    93  3.85
 read_excel(xlsx_example, range = cell_rows(1:4))
-#> # A tibble: 3 × 5
-#>   Sepal.Length Sepal.Width Petal.Length Petal.Width Species
-#>          <dbl>       <dbl>        <dbl>       <dbl> <chr>  
-#> 1          5.1         3.5          1.4         0.2 setosa 
-#> 2          4.9         3            1.4         0.2 setosa 
-#> 3          4.7         3.2          1.3         0.2 setosa
+#> # A tibble: 3 × 11
+#>     mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
+#>   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
+#> 1  21       6   160   110  3.9   2.62  16.5     0     1     4     4
+#> 2  21       6   160   110  3.9   2.88  17.0     0     1     4     4
+#> 3  22.8     4   108    93  3.85  2.32  18.6     1     1     4     1
 read_excel(xlsx_example, range = cell_cols("B:D"))
-#> # A tibble: 150 × 3
-#>   Sepal.Width Petal.Length Petal.Width
-#>         <dbl>        <dbl>       <dbl>
-#> 1         3.5          1.4         0.2
-#> 2         3            1.4         0.2
-#> 3         3.2          1.3         0.2
-#> # ℹ 147 more rows
+#> # A tibble: 32 × 3
+#>     cyl  disp    hp
+#>   <dbl> <dbl> <dbl>
+#> 1     6   160   110
+#> 2     6   160   110
+#> 3     4   108    93
+#> # ℹ 29 more rows
 read_excel(xlsx_example, range = "mtcars!B1:D5")
 #> # A tibble: 4 × 3
 #>     cyl  disp    hp
@@ -178,14 +178,14 @@ If `NA`s are represented by something other than blank cells, set the
 `na` argument.
 
 ``` r
-read_excel(xlsx_example, na = "setosa")
-#> # A tibble: 150 × 5
-#>   Sepal.Length Sepal.Width Petal.Length Petal.Width Species
-#>          <dbl>       <dbl>        <dbl>       <dbl> <chr>  
-#> 1          5.1         3.5          1.4         0.2 <NA>   
-#> 2          4.9         3            1.4         0.2 <NA>   
-#> 3          4.7         3.2          1.3         0.2 <NA>   
-#> # ℹ 147 more rows
+read_excel(xlsx_example, na = "0")
+#> # A tibble: 32 × 11
+#>     mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
+#>   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
+#> 1  21       6   160   110  3.9   2.62  16.5    NA     1     4     4
+#> 2  21       6   160   110  3.9   2.88  17.0    NA     1     4     4
+#> 3  22.8     4   108    93  3.85  2.32  18.6     1     1     4     1
+#> # ℹ 29 more rows
 ```
 
 If you are new to the tidyverse conventions for data import, you may
@@ -249,7 +249,7 @@ openxlsx provides “a high level interface to writing, styling and
 editing worksheets”.
 
 ``` r
-l <- list(iris = iris, mtcars = mtcars, chickwts = chickwts, quakes = quakes)
+l <- list(mtcars = mtcars, chickwts = chickwts, quakes = quakes)
 openxlsx::write.xlsx(l, file = "inst/extdata/datasets.xlsx")
 ```
 

vignettes/articles/readxl-workflows.Rmd

@@ -47,32 +47,32 @@ Solution: cache a CSV snapshot of your raw data tables at the time of export. Ev
 Pipe the output of `read_excel()` directly into `readr::write_csv()` like so:
 
 ```{r}
-iris_xl <- readxl_example("datasets.xlsx") %>% 
-  read_excel(sheet = "iris") %>% 
-  write_csv("iris-raw.csv")
+mtcars_xl <- readxl_example("datasets.xlsx") %>% 
+  read_excel(sheet = "mtcars") %>% 
+  write_csv("mtcars-raw.csv")
 ```
 
 ```{r include = FALSE}
-delete_on_exit <- c(delete_on_exit, "iris-raw.csv")
+delete_on_exit <- c(delete_on_exit, "mtcars-raw.csv")
 ```
 
 Why does this work? `readr::write_csv()` is a well-mannered "write" function: it does its main job *and returns its input invisibly*. The above command reads the iris sheet from readxl's `datasets.xlsx` example workbook and caches a CSV version of the resulting data frame to file.
 
 Let's check. Did we still import the data? Did we write the CSV file?
 
 ```{r}
-iris_xl
-dir(pattern = "iris")
+mtcars_xl
+dir(pattern = "mtcars")
 ```
 
 Yes! Is the data written to CSV an exact copy of what we imported from Excel?
 
 ```{r}
-iris_alt <- read_csv("iris-raw.csv")
+mtcars_alt <- read_csv("mtcars-raw.csv")
 ## readr leaves a note-to-self in `spec` that records its column guessing,
 ## so we remove that attribute before the check
-attr(iris_alt, "spec") <- NULL
-identical(iris_xl, iris_alt)
+attr(mtcars_alt, "spec") <- NULL
+identical(mtcars_xl, mtcars_alt)
 ```
 
 Yes! If we needed to restart or troubleshoot this fictional analysis, `iris-raw.csv` is available as a second, highly accessible alternative to `datasets.xlsx`.
@@ -192,11 +192,11 @@ Rework examples from above but using base R only, other than readxl.
 ### Cache a CSV snapshot
 
 ```{r eval = FALSE}
-iris_xl <- read_excel(readxl_example("datasets.xlsx"), sheet = "iris")
-write.csv(iris_xl, "iris-raw.csv", row.names = FALSE, quote = FALSE)
-iris_alt <- read.csv("iris-raw.csv", stringsAsFactors = FALSE)
+mtcars_xl <- read_excel(readxl_example("datasets.xlsx"), sheet = "mtcars")
+write.csv(iris_xl, "mtcars-raw.csv", row.names = FALSE, quote = FALSE)
+mtcars_alt <- read.csv("mtcars-raw.csv", stringsAsFactors = FALSE)
 ## coerce iris_xl back to a data.frame
-identical(as.data.frame(iris_xl), iris_alt)
+identical(as.data.frame(mtcars_xl), mtcars_alt)
 ```
 
 ### Iterate over multiple worksheets in a workbook