adding crew column to titanic data

Author: vpnagraj

R/data.R

@@ -7,6 +7,7 @@
 #' @format A data frame with 2201 rows and 4 variables:
 #'
 #' - **Class**: Passenger class ("1st", "2nd", "3rd") or crew status ("Crew")
+#' - **Crew**: Boolean as to whether or not a crew member (TRUE) or not (FALSE)
 #' - **Sex**: Sex of individual ("Male" or "Female")
 #' - **Age**: Categorized age ("Adult" or "Child")
 #' - **Survived**: Whether or not individual survived ("Yes" or "No")

README.Rmd

@@ -57,7 +57,6 @@ Next create a object with S3 class `twoxtwo`. For this example, use the `twoxtwo
 ```{r}
 crew_2x2 <-
   titanic %>%
-  mutate(Crew = ifelse(Class == "Crew", TRUE, FALSE)) %>%
   twoxtwo(.data = ., exposure = Crew, outcome = Survived)
 
 crew_2x2
@@ -73,19 +72,16 @@ Each effect measure can also be calculated without first creating the `twoxtwo`
 
 ```{r}
 titanic %>%
-  mutate(Crew = ifelse(Class == "Crew", TRUE, FALSE)) %>%
   odds_ratio(.data = ., exposure = Crew, outcome = Survived)
 ```
 
 ```{r}
 titanic %>%
-  mutate(Crew = ifelse(Class == "Crew", TRUE, FALSE)) %>%
   risk_ratio(.data = ., exposure = Crew, outcome = Survived)
 ```
 
 ```{r}
 titanic %>%
-  mutate(Crew = ifelse(Class == "Crew", TRUE, FALSE)) %>%
   risk_diff(.data = ., exposure = Crew, outcome = Survived)
 ```
 

README.md

@@ -53,7 +53,6 @@ must each be binary variables:
 ``` r
 crew_2x2 <-
   titanic %>%
-  mutate(Crew = ifelse(Class == "Crew", TRUE, FALSE)) %>%
   twoxtwo(.data = ., exposure = Crew, outcome = Survived)
 
 crew_2x2
@@ -97,7 +96,6 @@ Each effect measure can also be calculated without first creating the
 
 ``` r
 titanic %>%
-  mutate(Crew = ifelse(Class == "Crew", TRUE, FALSE)) %>%
   odds_ratio(.data = ., exposure = Crew, outcome = Survived)
 # # A tibble: 1 x 6
 #   measure    estimate ci_lower ci_upper exposure         outcome         
@@ -107,7 +105,6 @@ titanic %>%
 
 ``` r
 titanic %>%
-  mutate(Crew = ifelse(Class == "Crew", TRUE, FALSE)) %>%
   risk_ratio(.data = ., exposure = Crew, outcome = Survived)
 # # A tibble: 1 x 6
 #   measure    estimate ci_lower ci_upper exposure         outcome         
@@ -117,7 +114,6 @@ titanic %>%
 
 ``` r
 titanic %>%
-  mutate(Crew = ifelse(Class == "Crew", TRUE, FALSE)) %>%
   risk_diff(.data = ., exposure = Crew, outcome = Survived)
 # # A tibble: 1 x 6
 #   measure         estimate ci_lower ci_upper exposure         outcome         

data-raw/datasets.R

@@ -5,6 +5,8 @@ titanic <-
   ## convert to tibble
   dplyr::as_tibble() %>%
   ## expand counts
-  tidyr::uncount(n)
+  tidyr::uncount(n) %>%
+  ## create crew variable
+  dplyr::mutate(Crew = ifelse(Class == "Crew", TRUE, FALSE), .after = "Class")
 
 usethis::use_data(titanic, overwrite = TRUE)