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IntroR.R
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# Title: Introduction to R - SMALL GROUP CHALLENGE VERSION
# Author: LLK
# Date: 2022-10-19
# Description: DSF Intro to R Session - This file represents changes during the 10/19/22 small group challenge
# Setup required packages
# Penguins dataset
install.packages("palmerpenguins", dependencies = TRUE)
# HTML tables
install.packages("formattable")
# Load all required packages
library(palmerpenguins)
library(formattable)
library(tidyverse)
# Load and examine data
data("penguins")
# First 6 rows
head(penguins)
# First and last 6 rows HTML table
formattable(head(penguins))
formattable(tail(penguins))
# Summary statistics
summary(penguins)
# Tidyverse
# %>% Tidyverse pipe
# |> Base R Pipe
penguins |>
group_by(species) |>
select(bill_length_mm) |>
filter(bill_length_mm > 39.23) |>
arrange(desc(bill_length_mm)) |>
head()
# Plotting in ggplot()
# Boxplot
penguins |>
ggplot(aes(x = species, y = bill_length_mm, fill = species)) +
geom_boxplot() +
theme_minimal(base_size = 16) +
xlab(NULL) +
ylab("Bill length (mm)") +
theme(legend.position = "none") +
ggtitle("Penguin species bill lengths")
# Regression plot
penguins |>
ggplot(aes(x = bill_length_mm, y = bill_depth_mm, color = species)) +
geom_smooth(method = "lm", se = FALSE) +
geom_point() +
theme_minimal(base_size = 16) +
xlab("Bill length (mm)") +
ylab("Bill depth (mm)") +
ggtitle("Relationship between bill length and depth")
# Write .csv
# Log transform a dataset
penguins_bill_length <- penguins |>
group_by(species) |>
select(bill_length_mm) |>
filter(bill_length_mm > 39.23) |>
arrange(desc(bill_length_mm)) |>
rename(Species = species) |>
mutate(Log_bill_length = log(bill_length_mm))
# Write a new .csv
write.csv(penguins_bill_length, "penguins_bill_length.csv", row.names = FALSE)
# Read in a .csv
penguins_bill_length1 <- read.csv("penguins_bill_length.csv")
#View dataset
View(penguins)
#Grouping the dataset by species and sex
penguins |>
group_by(species) |>
group_by(sex) |>
select(bill_length_mm) |>
filter(bill_length_mm > 39.23) |>
arrange(desc(bill_length_mm)) |>
head()
# Plotting Bill length in ggplot() grouped by species AND sex
# Boxplot
penguins |>
group_by(species) |>
select(bill_length_mm , sex)|>
na.omit(sex) |>
ggplot(aes(x = species, y = bill_length_mm, fill = sex)) +
geom_boxplot() +
# geom_dotplot(binaxis='y', stackdir='center', dotsize=0.5)
theme_minimal(base_size = 16) +
xlab(NULL) +
ylab("Bill length (mm)") +
ggtitle("Penguin species bill lengths")
theme(plot.title = element_text(hjust = 0.5))
#Violin plot
penguins |>
group_by(species) |>
select(bill_length_mm , sex)|>
na.omit(sex) |>
ggplot(aes(x = species, y = bill_length_mm, fill = sex)) +
geom_violin() +
# geom_dotplot(binaxis='y', stackdir='center', dotsize=0.5)
theme_minimal(base_size = 16) +
xlab(NULL) +
ylab("Bill length (mm)") +
ggtitle("Penguin species bill lengths")
theme(plot.title = element_text(hjust = 0.5))
# Plotting flipper length in ggplot() grouped by species AND sex
# Boxplot
penguins |>
group_by(species) |>
select(flipper_length_mm , sex)|>
na.omit(sex) |>
ggplot(aes(x = species, y = flipper_length_mm, fill = sex)) +
geom_boxplot() +
# geom_dotplot(binaxis='y', stackdir='center', dotsize=0.5)
theme_minimal(base_size = 16) +
xlab(NULL) +
ylab("Flipper length (mm)") +
ggtitle("Penguin species flipper lengths")
#Violin plot
penguins |>
group_by(species) |>
select(flipper_length_mm , sex)|>
na.omit(sex) |>
ggplot(aes(x = species, y = flipper_length_mm, fill = sex)) +
geom_violin() +
# geom_dotplot(binaxis='y', stackdir='center', dotsize=0.5)
theme_minimal(base_size = 16) +
xlab(NULL) +
ylab("Flipper length (mm)") +
ggtitle("Penguin species flipper lengths")
# Title: Introduction to R - SMALL GROUP CHALLENGE VERSION
# Author: LLK
# Date: 2022-10-19
# Description: DSF Intro to R Session - This file represents changes during the 10/19/22 small group challenge
# Setup required packages
# Penguins dataset
install.packages("palmerpenguins", dependencies = TRUE)
# HTML tables
install.packages("formattable")
# Load all required packages
library(palmerpenguins)
library(formattable)
library(tidyverse)
# Load and examine data
data("penguins")
# First 6 rows
head(penguins)
# First and last 6 rows HTML table
formattable(head(penguins))
formattable(tail(penguins))
# Summary statistics
summary(penguins)
# Tidyverse
# %>% Tidyverse pipe
# |> Base R Pipe
penguins |>
group_by(species) |>
select(bill_length_mm) |>
filter(bill_length_mm > 39.23) |>
arrange(desc(bill_length_mm)) |>
head()
# Plotting in ggplot()
# Boxplot
penguins |>
ggplot(aes(x = species, y = bill_length_mm, fill = species)) +
geom_boxplot() +
theme_minimal(base_size = 16) +
xlab(NULL) +
ylab("Bill length (mm)") +
theme(legend.position = "none") +
ggtitle("Penguin species bill lengths")
# Regression plot
penguins |>
ggplot(aes(x = bill_length_mm, y = bill_depth_mm, color = species)) +
geom_smooth(method = "lm", se = FALSE) +
geom_point() +
theme_minimal(base_size = 16) +
xlab("Bill length (mm)") +
ylab("Bill depth (mm)") +
ggtitle("Relationship between bill length and depth")
# Write .csv
# Log transform a dataset
penguins_bill_length <- penguins |>
group_by(species) |>
select(bill_length_mm) |>
filter(bill_length_mm > 39.23) |>
arrange(desc(bill_length_mm)) |>
rename(Species = species) |>
mutate(Log_bill_length = log(bill_length_mm))
# Write a new .csv
write.csv(penguins_bill_length, "penguins_bill_length.csv", row.names = FALSE)
# Read in a .csv
penguins_bill_length1 <- read.csv("penguins_bill_length.csv")
#View dataset
View(penguins)
#Grouping the dataset by species and sex
penguins |>
group_by(species) |>
group_by(sex) |>
select(bill_length_mm) |>
filter(bill_length_mm > 39.23) |>
arrange(desc(bill_length_mm)) |>
head()
# Plotting Bill length in ggplot() grouped by species AND sex
# Boxplot
penguins |>
group_by(species) |>
select(bill_length_mm , sex)|>
na.omit(sex) |>
ggplot(aes(x = species, y = bill_length_mm, fill = sex)) +
geom_boxplot() +
# geom_dotplot(binaxis='y', stackdir='center', dotsize=0.5)
theme_minimal(base_size = 16) +
xlab(NULL) +
ylab("Bill length (mm)") +
ggtitle("Penguin species bill lengths")
theme(plot.title = element_text(hjust = 0.5))
#Violin plot
penguins |>
group_by(species) |>
select(bill_length_mm , sex)|>
na.omit(sex) |>
ggplot(aes(x = species, y = bill_length_mm, fill = sex)) +
geom_violin() +
# geom_dotplot(binaxis='y', stackdir='center', dotsize=0.5)
theme_minimal(base_size = 16) +
xlab(NULL) +
ylab("Bill length (mm)") +
ggtitle("Penguin species bill lengths")
theme(plot.title = element_text(hjust = 0.5))
# Plotting flipper length in ggplot() grouped by species AND sex
# Boxplot
penguins |>
group_by(species) |>
select(flipper_length_mm , sex)|>
na.omit(sex) |>
ggplot(aes(x = species, y = flipper_length_mm, fill = sex)) +
geom_boxplot() +
# geom_dotplot(binaxis='y', stackdir='center', dotsize=0.5)
theme_minimal(base_size = 16) +
xlab(NULL) +
ylab("Flipper length (mm)") +
ggtitle("Penguin species flipper lengths")
#Violin plot
penguins |>
group_by(species) |>
select(flipper_length_mm , sex)|>
na.omit(sex) |>
ggplot(aes(x = species, y = flipper_length_mm, fill = sex)) +
geom_violin() +
# geom_dotplot(binaxis='y', stackdir='center', dotsize=0.5)
theme_minimal(base_size = 16) +
xlab(NULL) +
ylab("Flipper length (mm)") +
ggtitle("Penguin species flipper lengths")