Suggest openxlsx2 instead of openxlsx

DESCRIPTION

@@ -24,7 +24,7 @@ Imports:
     leaflet,
     maps,
     nycflights13,
-    openxlsx,
+    openxlsx2,
     palmerpenguins,
     repurrrsive (>= 1.1.0),
     tidymodels,

intro.qmd

@@ -207,7 +207,7 @@ For example, we'll use the following packages because they provide interesting d
 install.packages(
   c("arrow", "babynames", "curl", "duckdb", "gapminder", 
     "ggrepel", "ggridges", "ggthemes", "hexbin", "janitor", "Lahman", 
-    "leaflet", "maps", "nycflights13", "openxlsx", "palmerpenguins", 
+    "leaflet", "maps", "nycflights13", "openxlsx2", "palmerpenguins", 
     "repurrrsive", "tidymodels", "writexl")
   )
 ```

spreadsheets.qmd

@@ -376,11 +376,11 @@ read_excel("data/bake-sale.xlsx")
 
 ### Formatted output
 
-The writexl package is a light-weight solution for writing a simple Excel spreadsheet, but if you're interested in additional features like writing to sheets within a spreadsheet and styling, you will want to use the [openxlsx package](https://ycphs.github.io/openxlsx).
-We won't go into the details of using this package here, but we recommend reading <https://ycphs.github.io/openxlsx/articles/Formatting.html> for an extensive discussion on further formatting functionality for data written from R to Excel with openxlsx.
+The writexl package is a light-weight solution for writing a simple Excel spreadsheet, but if you're interested in additional features like writing to sheets within a spreadsheet and styling, you will want to use the [openxlsx2 package](https://janmarvin.github.io/openxlsx2/).
+We won't go into the details of using this package here, but we recommend reading <https://janmarvin.github.io/openxlsx2/articles/openxlsx2_style_manual.html> for an extensive discussion on further formatting functionality for data written from R to Excel with openxlsx2.
 
-Note that this package is not part of the tidyverse so the functions and workflows may feel unfamiliar.
-For example, function names are camelCase, multiple functions can't be composed in pipelines, and arguments are in a different order than they tend to be in the tidyverse.
+Note that this package is not part of the tidyverse.
+For example, arguments are in a different order than they tend to be in the tidyverse.
 However, this is ok.
 As your R learning and usage expands outside of this book you will encounter lots of different styles used in various R packages that you might use to accomplish specific goals in R.
 A good way of familiarizing yourself with the coding style used in a new package is to run the examples provided in function documentation to get a feel for the syntax and the output formats as well as reading any vignettes that might come with the package.
@@ -496,7 +496,7 @@ A good way of familiarizing yourself with the coding style used in a new package
       print(n = 7)
     ```
 
-4.  Recreate the `bake_sale` data frame, write it out to an Excel file using the `write.xlsx()` function from the openxlsx package.
+4.  Recreate the `bake_sale` data frame, write it out to an Excel file using the `write_xlsx()` function from the openxlsx2 package.
 
 5.  In @sec-data-import you learned about the `janitor::clean_names()` function to turn column names into snake case.
     Read the `students.xlsx` file that we introduced earlier in this section and use this function to "clean" the column names.