keithmcnulty

penguins_wide <- penguins_long %>% 
  tidyr::pivot_wider(names_from = c("part", "measure", "unit"), # pivot these columns
                     values_from = "value", # take the values from here
                     names_sep = "_") # combine col names using an underscore

penguins_wide

# A tibble: 344 x 9
# Groups:   species, island, sex, year [35]
   species island    sex     year penguinid bill_length_mm bill_depth_mm flipper_length_mm body_mass_g

keithmcnulty

penguins_long <- penguins_id %>% 
  tidyr::pivot_longer(contains("_"), # break out the measurement cols
                      names_to = c("part", "measure", "unit"), # break them into these three columns
                      names_sep = "_") #  use the underscore to separate

penguins_long

# A tibble: 1,376 x 9
# Groups:   species, island, sex, year [35]
   species island    sex     year penguinid part    measure unit   value

keithmcnulty

penguins_id <- penguins %>% 
  dplyr::group_by(species, island, sex, year) %>% 
  dplyr::mutate(penguinid = row_number(), .before = contains("_"))

penguins_id

# A tibble: 344 x 9
# Groups:   species, island, sex, year [35]
   species island    sex     year penguinid bill_length_mm bill_depth_mm flipper_length_mm body_mass_g
   <fct>   <fct>     <fct>  <int>     <int>          <dbl>         <dbl>             <int>       <int>

keithmcnulty

penguins <- penguins %>% 
  dplyr::relocate(contains("_"), .after = year)

penguins

# A tibble: 344 x 8
   species island    sex     year bill_length_mm bill_depth_mm flipper_length_mm body_mass_g
   <fct>   <fct>     <fct>  <int>          <dbl>         <dbl>             <int>       <int>
 1 Adelie  Torgersen male    2007           39.1          18.7               181        3750
 2 Adelie  Torgersen female  2007           39.5          17.4               186        3800

keithmcnulty

penguins %>% 
  dplyr::select(!contains("_"), starts_with("bill"))
  
# A tibble: 344 x 6
   species island    sex     year bill_length_mm bill_depth_mm
   <fct>   <fct>     <fct>  <int>          <dbl>         <dbl>
 1 Adelie  Torgersen male    2007           39.1          18.7
 2 Adelie  Torgersen female  2007           39.5          17.4
 3 Adelie  Torgersen female  2007           40.3          18  
 4 Adelie  Torgersen NA      2007           NA            NA  

keithmcnulty

library(tidyverse)
library(palmerpenguins)

penguins

# A tibble: 344 x 8
   species island    bill_length_mm bill_depth_mm flipper_length_mm body_mass_g sex     year
   <fct>   <fct>              <dbl>         <dbl>             <int>       <int> <fct>  <int>
 1 Adelie  Torgersen           39.1          18.7               181        3750 male    2007
 2 Adelie  Torgersen           39.5          17.4               186        3800 female  2007

keithmcnulty

library(tidyverse)
library(palmerpenguins)

penguins

# A tibble: 344 x 8
   species island    bill_length_mm bill_depth_mm flipper_length_mm body_mass_g sex     year
   <fct>   <fct>              <dbl>         <dbl>             <int>       <int> <fct>  <int>
 1 Adelie  Torgersen           39.1          18.7               181        3750 male    2007
 2 Adelie  Torgersen           39.5          17.4               186        3800 female  2007

keithmcnulty

Package: isawesome
Type: Package
Title: Tells people they are awesome
Version: 0.1.0
Author: c(
  person(given = "Jiena",
         family = "McLellan",
         role = c("aut", "cre"),
         email = "jienagu90@gmail.com")
  person(given = "Keith",

keithmcnulty

(plots$plotcol[1]$scatter | plots$plotcol[2]$scatter | plots$plotcol[3]$scatter) /
(plots$boxcol[1]$box | plots$boxcol[2]$box | plots$boxcol[3]$box)

keithmcnulty

library(patchwork)

scatter_plot <- function(df, xvar, yvar) {
  ggplot(df) +
  geom_point(aes(x = {{xvar}}, y = {{yvar}}))
}

box_plot <- function(df, xvar, yvar, groupvar) {
  ggplot(df) + 
  geom_boxplot(aes(x = {{xvar}}, y = {{yvar}}, group = {{groupvar}}))