library(palmerpenguins)
names(penguins)
names(penguins_raw)
library(palmerpenguins)
names(penguins_raw)
names(penguins)
peng_raw_field <- penguins_raw %>%
select(Species, Island, `Culmen Length (mm)`, `Culmen Depth (mm)`,
`Flipper Length (mm)`, `Body Mass (g)`, Sex)
### Load the necessary libraries #####
library(dplyr)
library(tidyplots)
library(ggplot2)
peng_raw_field <- penguins_raw %>%
select(Species, Island, `Culmen Length (mm)`, `Culmen Depth (mm)`,
`Flipper Length (mm)`, `Body Mass (g)`, Sex)
peng_raw_field <- penguins_raw %>%
select(Species, Island, `Culmen Length (mm)`, `Culmen Depth (mm)`,
`Flipper Length (mm)`, `Body Mass (g)`, Sex) %>%
mutate(year = penguins$year)
peng_raw_field
names(peng_raw_field) <- names(penguins)
peng_raw_field == penguins
peng_raw_field
peng_raw_field <- penguins
peng_raw_field
penguins_raw %>%
peng_raw_field_lab <-
penguins_raw %>%
peng_raw_field_lab <-
penguins_raw %>%
peng_raw_field_lab <-
penguins_raw %>%
peng_raw_field_lab <-
penguins_raw %>%
peng_raw_field_lab <-
penguins_raw %>%
peng_raw_field_lab <-
penguins_raw %>%
peng_raw_field_lab <-
penguins_raw %>%
peng_raw_field_lab <-
penguins_raw
penguins_raw
View(penguins_raw)
peng_raw_field <-
penguins %>%
mutate(ID = penguins_raw$`Individual ID`)
peng_raw_field_lab <-
penguins_raw %>%
mutate(ID = penguins_raw$`Individual ID`,
delta15N = `Delta 15 N (o/oo)`,
delta13C = `Delta 13 C (o/oo)`)
peng_raw_field_lab
peng_raw_field_lab <-
penguins_raw %>%
mutate(ID = penguins_raw$`Individual ID`,
delta15N = `Delta 15 N (o/oo)`,
delta13C = `Delta 13 C (o/oo)`) %>%
select(ID, delta15N, delta13C)
peng_raw_field_lab
peng_raw_field
peng_raw_field <-
penguins %>%
mutate(ID = penguins_raw$`Individual ID`)
peng_raw_field
peng_raw_field <-
penguins %>%
mutate(ID = penguins_raw$`Individual ID`) %>%
relocate(ID)
peng_raw_field
peng_raw_field_lab <-
penguins_raw %>%
mutate(ID = penguins_raw$`Individual ID`,
delta15N = `Delta 15 N (o/oo)`,
delta13C = `Delta 13 C (o/oo)`) %>%
select(ID, delta15N, delta13C)
peng_raw_field_lab
library(readr)
write_csv(peng_raw_field, "data/palmerpenguins_fielddata.csv")
write_csv(peng_raw_field_lab, "data/palmerpenguins_labdata.csv")
data_lab <- read_csv("data/palmerpenguins_labdata.csv")
### Join the data ####
data_penguins <- full_join(data_field, data_lab)
#------------------------------------------------------------------------------#
### Penguin Analyses Skript: Data Import and Wrangling, Vis & Stats.        ####
#------------------------------------------------------------------------------#
### Load the necessary libraries #####
library(dplyr)
library(tidyplots)
library(ggplot2)
library(readr)
### Import the data ####
data_field <- read_csv("data/palmerpenguins_fielddata.csv")
data_lab <- read_csv("data/palmerpenguins_labdata.csv")
### Join the data ####
data_penguins <- full_join(data_field, data_lab)
View(data_penguins)
### Compute the descriptives ####
data_penguins %>%
group_by(species, sex) %>%
summarize(mean15N = mean(delta15N, na.rm = T),
sd15N = sd(delta15N, na.rm = T),
mean13C = mean(delta13C, na.rm = T),
sd13C = sd(delta13C, na.rm = T))
### Plot the descriptives ####
data_penguins %>%
tidyplot(x = sex, y = delta15N, color = species) %>%
add_mean_dot() %>%
add_data_points_jitter()
### Plot the descriptives ####
data_penguins %>%
tidyplot(x = sex, y = delta15N, color = species) %>%
add_mean_bar(saturation = .5) %>%
add_data_points_jitter()
### Plot the descriptives ####
data_penguins %>%
tidyplot(x = sex, y = delta15N, color = species) %>%
#add_mean_bar(saturation = .5) %>%
add_data_points_jitter(saturation = .1)
data_penguins %>%
tidyplot(x = sex, y = delta13C, color = species) %>%
#add_mean_bar(saturation = .5) %>%
add_data_points_jitter(saturation = .1)
### Plot the descriptives ####
data_penguins %>%
tidyplot(x = sex, y = delta15N, color = sex) %>%
add_data_points_jitter(saturation = .1) %>%
split_plot(species)
data_penguins %>%
tidyplot(x = sex, y = delta13C, color = species) %>%
add_data_points_jitter(saturation = .1) %>%
split_plot(species)
data_penguins %>%
tidyplot(x = sex, y = delta13C, color = sex) %>%
add_data_points_jitter(saturation = .1) %>%
split_plot(species)
### Load the necessary libraries #####
library(dplyr)
library(tidyplots)
library(ggplot2)
library(readr)
### Import the data ####
data_field <- read_csv("data/palmerpenguins_fielddata.csv")
