differences for PR #883

00-before-we-start.md

@@ -432,7 +432,7 @@ and help others to pinpoint where the issue might be. Try to...
 sessionInfo()
 ```
 
-```{.output}
+```output
 #> R version 4.3.3 (2024-02-29)
 #> Platform: x86_64-pc-linux-gnu (64-bit)
 #> Running under: Ubuntu 22.04.4 LTS
@@ -454,20 +454,20 @@ sessionInfo()
 #> [1] stats     graphics  grDevices utils     datasets  methods   base     
 #> 
 #> other attached packages:
-#>  [1] RSQLite_2.3.4   lubridate_1.9.3 forcats_1.0.0   stringr_1.5.1  
-#>  [5] dplyr_1.1.4     purrr_1.0.2     readr_2.1.4     tidyr_1.3.0    
-#>  [9] tibble_3.2.1    ggplot2_3.4.4   tidyverse_2.0.0 knitr_1.45     
+#>  [1] RSQLite_2.3.6   lubridate_1.9.3 forcats_1.0.0   stringr_1.5.1  
+#>  [5] dplyr_1.1.4     purrr_1.0.2     readr_2.1.5     tidyr_1.3.1    
+#>  [9] tibble_3.2.1    ggplot2_3.5.1   tidyverse_2.0.0 knitr_1.46     
 #> 
 #> loaded via a namespace (and not attached):
-#>  [1] bit_4.0.5        gtable_0.3.4     compiler_4.3.3   renv_1.0.5      
-#>  [5] highr_0.10       tidyselect_1.2.0 blob_1.2.4       scales_1.3.0    
+#>  [1] bit_4.0.5        gtable_0.3.5     compiler_4.3.3   renv_1.0.7      
+#>  [5] highr_0.10       tidyselect_1.2.1 blob_1.2.4       scales_1.3.0    
 #>  [9] fastmap_1.1.1    yaml_2.3.8       R6_2.5.1         generics_0.1.3  
-#> [13] munsell_0.5.0    DBI_1.2.0        pillar_1.9.0     tzdb_0.4.0      
-#> [17] rlang_1.1.2      utf8_1.2.4       cachem_1.0.8     stringi_1.8.3   
-#> [21] xfun_0.41        bit64_4.0.5      memoise_2.0.1    timechange_0.2.0
-#> [25] cli_3.6.2        withr_2.5.2      magrittr_2.0.3   grid_4.3.3      
+#> [13] munsell_0.5.1    DBI_1.2.2        pillar_1.9.0     tzdb_0.4.0      
+#> [17] rlang_1.1.3      utf8_1.2.4       cachem_1.0.8     stringi_1.8.4   
+#> [21] xfun_0.43        bit64_4.0.5      memoise_2.0.1    timechange_0.3.0
+#> [25] cli_3.6.2        withr_3.0.0      magrittr_2.0.3   grid_4.3.3      
 #> [29] hms_1.1.3        lifecycle_1.0.4  vctrs_0.6.5      evaluate_0.23   
-#> [33] glue_1.6.2       fansi_1.0.6      colorspace_2.1-0 tools_4.3.3     
+#> [33] glue_1.7.0       fansi_1.0.6      colorspace_2.1-0 tools_4.3.3     
 #> [37] pkgconfig_2.0.3
 ```
 

01-intro-to-r.md

@@ -222,7 +222,7 @@ Let's try a function that can take multiple arguments: `round()`.
 round(3.14159)
 ```
 
-```{.output}
+```output
 #> [1] 3
 ```
 
@@ -238,7 +238,7 @@ help for this function using `?round`.
 args(round)
 ```
 
-```{.output}
+```output
 #> function (x, digits = 0) 
 #> NULL
 ```
@@ -256,7 +256,7 @@ type `digits = 2` or however many we want.
 round(3.14159, digits = 2)
 ```
 
-```{.output}
+```output
 #> [1] 3.14
 ```
 
@@ -268,7 +268,7 @@ don't have to name them:
 round(3.14159, 2)
 ```
 
-```{.output}
+```output
 #> [1] 3.14
 ```
 
@@ -279,7 +279,7 @@ And if you do name the arguments, you can switch their order:
 round(digits = 2, x = 3.14159)
 ```
 
-```{.output}
+```output
 #> [1] 3.14
 ```
 
@@ -459,15 +459,15 @@ animals <- c("mouse", "rat", "dog", "cat")
 animals[2]
 ```
 
-```{.output}
+```output
 #> [1] "rat"
 ```
 
 ```r
 animals[c(3, 2)]
 ```
 
-```{.output}
+```output
 #> [1] "dog" "rat"
 ```
 
@@ -480,7 +480,7 @@ more_animals <- animals[c(1, 2, 3, 2, 1, 4)]
 more_animals
 ```
 
-```{.output}
+```output
 #> [1] "mouse" "rat"   "dog"   "rat"   "mouse" "cat"
 ```
 
@@ -500,7 +500,7 @@ weight_g <- c(21, 34, 39, 54, 55)
 weight_g[c(TRUE, FALSE, FALSE, TRUE, TRUE)]
 ```
 
-```{.output}
+```output
 #> [1] 21 54 55
 ```
 
@@ -513,7 +513,7 @@ values above 50:
 weight_g > 50    # will return logicals with TRUE for the indices that meet the condition
 ```
 
-```{.output}
+```output
 #> [1] FALSE FALSE FALSE  TRUE  TRUE
 ```
 
@@ -522,7 +522,7 @@ weight_g > 50    # will return logicals with TRUE for the indices that meet the
 weight_g[weight_g > 50]
 ```
 
-```{.output}
+```output
 #> [1] 54 55
 ```
 
@@ -534,23 +534,23 @@ You can combine multiple tests using `&` (both conditions are true, AND) or `|`
 weight_g[weight_g > 30 & weight_g < 50]
 ```
 
-```{.output}
+```output
 #> [1] 34 39
 ```
 
 ```r
 weight_g[weight_g <= 30 | weight_g == 55]
 ```
 
-```{.output}
+```output
 #> [1] 21 55
 ```
 
 ```r
 weight_g[weight_g >= 30 & weight_g == 21]
 ```
 
-```{.output}
+```output
 #> numeric(0)
 ```
 
@@ -573,7 +573,7 @@ animals <- c("mouse", "rat", "dog", "cat", "cat")
 animals[animals == "cat" | animals == "rat"]
 ```
 
-```{.output}
+```output
 #> [1] "rat" "cat" "cat"
 ```
 
@@ -583,7 +583,7 @@ animals[animals == "cat" | animals == "rat"]
 animals %in% c("rat", "cat", "dog", "duck", "goat", "bird", "fish")
 ```
 
-```{.output}
+```output
 #> [1] FALSE  TRUE  TRUE  TRUE  TRUE
 ```
 
@@ -593,7 +593,7 @@ animals %in% c("rat", "cat", "dog", "duck", "goat", "bird", "fish")
 animals[animals %in% c("rat", "cat", "dog", "duck", "goat", "bird", "fish")]
 ```
 
-```{.output}
+```output
 #> [1] "rat" "dog" "cat" "cat"
 ```
 

02-starting-with-data.md

@@ -122,7 +122,7 @@ about data frames later):
 surveys <- read_csv("data_raw/portal_data_joined.csv")
 ```
 
-```{.output}
+```output
 #> Rows: 34786 Columns: 13
 #> ── Column specification ────────────────────────────────────────────────────────
 #> Delimiter: ","
@@ -175,7 +175,7 @@ We can also extract the first few lines of this data using the function
 head(surveys)
 ```
 
-```{.output}
+```output
 #> # A tibble: 6 × 13
 #>   record_id month   day  year plot_id species_id sex   hindfoot_length weight
 #>       <dbl> <dbl> <dbl> <dbl>   <dbl> <chr>      <chr>           <dbl>  <dbl>
@@ -290,7 +290,7 @@ questions?
 str(surveys)
 ```
 
-```{.output}
+```output
 #> spc_tbl_ [34,786 × 13] (S3: spec_tbl_df/tbl_df/tbl/data.frame)
 #>  $ record_id      : num [1:34786] 1 72 224 266 349 363 435 506 588 661 ...
 #>  $ month          : num [1:34786] 7 8 9 10 11 11 12 1 2 3 ...
@@ -532,7 +532,7 @@ the `sex` vector would be:
 sex # current order
 ```
 
-```{.output}
+```output
 #> [1] male   female female male  
 #> Levels: female male
 ```
@@ -542,7 +542,7 @@ sex <- factor(sex, levels = c("male", "female"))
 sex # after re-ordering
 ```
 
-```{.output}
+```output
 #> [1] male   female female male  
 #> Levels: male female
 ```
@@ -650,7 +650,7 @@ sex <- surveys$sex
 levels(sex)
 ```
 
-```{.output}
+```output
 #> [1] "F" "M"
 ```
 
@@ -659,15 +659,15 @@ sex <- addNA(sex)
 levels(sex)
 ```
 
-```{.output}
+```output
 #> [1] "F" "M" NA
 ```
 
 ```r
 head(sex)
 ```
 
-```{.output}
+```output
 #> [1] M    M    <NA> <NA> <NA> <NA>
 #> Levels: F M <NA>
 ```
@@ -677,15 +677,15 @@ levels(sex)[3] <- "undetermined"
 levels(sex)
 ```
 
-```{.output}
+```output
 #> [1] "F"            "M"            "undetermined"
 ```
 
 ```r
 head(sex)
 ```
 
-```{.output}
+```output
 #> [1] M            M            undetermined undetermined undetermined
 #> [6] undetermined
 #> Levels: F M undetermined
@@ -844,7 +844,7 @@ This character vector can be used as the argument for `ymd()`:
 ymd(paste(surveys$year, surveys$month, surveys$day, sep = "-"))
 ```
 
-```{.warning}
+```warning
 #> Warning: 129 failed to parse.
 ```
 
@@ -859,7 +859,7 @@ vector to the `surveys` data frame as a new column called `date`:
 surveys$date <- ymd(paste(surveys$year, surveys$month, surveys$day, sep = "-"))
 ```
 
-```{.warning}
+```warning
 #> Warning: 129 failed to parse.
 ```
 
@@ -875,7 +875,7 @@ column is to use `summary()`:
 summary(surveys$date)
 ```
 
-```{.output}
+```output
 #>         Min.      1st Qu.       Median         Mean      3rd Qu.         Max. 
 #> "1977-07-16" "1984-03-12" "1990-07-22" "1990-12-15" "1997-07-29" "2002-12-31" 
 #>         NA's 
@@ -898,7 +898,7 @@ missing_dates <- surveys[is.na(surveys$date), c("year", "month", "day")]
 head(missing_dates)
 ```
 
-```{.output}
+```output
 #> # A tibble: 6 × 3
 #>    year month   day
 #>   <dbl> <dbl> <dbl>