library(palmerpenguins)
library(tidyverse)
RStudio Workbook
This is my RStudio Workbook
Warning
ctrl+alt+i is a very useful shortcut
Penguins database
penguins
# A tibble: 344 × 8
species island bill_length_mm bill_depth_mm flipper_length_mm body_mass_g
<fct> <fct> <dbl> <dbl> <int> <int>
1 Adelie Torgersen 39.1 18.7 181 3750
2 Adelie Torgersen 39.5 17.4 186 3800
3 Adelie Torgersen 40.3 18 195 3250
4 Adelie Torgersen NA NA NA NA
5 Adelie Torgersen 36.7 19.3 193 3450
6 Adelie Torgersen 39.3 20.6 190 3650
7 Adelie Torgersen 38.9 17.8 181 3625
8 Adelie Torgersen 39.2 19.6 195 4675
9 Adelie Torgersen 34.1 18.1 193 3475
10 Adelie Torgersen 42 20.2 190 4250
# ℹ 334 more rows
# ℹ 2 more variables: sex <fct>, year <int>
1) A different angle of the data (variables and measurements)
%>% # This symbol " %>% " can be inserted via pressing "ctrl + shift + m"
penguins glimpse
Rows: 344
Columns: 8
$ species <fct> Adelie, Adelie, Adelie, Adelie, Adelie, Adelie, Adel…
$ island <fct> Torgersen, Torgersen, Torgersen, Torgersen, Torgerse…
$ bill_length_mm <dbl> 39.1, 39.5, 40.3, NA, 36.7, 39.3, 38.9, 39.2, 34.1, …
$ bill_depth_mm <dbl> 18.7, 17.4, 18.0, NA, 19.3, 20.6, 17.8, 19.6, 18.1, …
$ flipper_length_mm <int> 181, 186, 195, NA, 193, 190, 181, 195, 193, 190, 186…
$ body_mass_g <int> 3750, 3800, 3250, NA, 3450, 3650, 3625, 4675, 3475, …
$ sex <fct> male, female, female, NA, female, male, female, male…
$ year <int> 2007, 2007, 2007, 2007, 2007, 2007, 2007, 2007, 2007…
2) Inserting an image in to a Quarto workbook
Task 3 - embed a video (How Quarto works; via RStudio)
Body Mass Histogram
library(tidyverse)
library(palmerpenguins)
#| label: vizualising data
#| echo: true
#| include: true
#| output: truedata("penguins")
%>%
penguins group_by(species) %>%
ggplot(aes(x=body_mass_g, colour=species, fill=species))+
geom_histogram()
`stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
Warning: Removed 2 rows containing non-finite values (`stat_bin()`).
Bill Length vs Bill depth vs Species scatterplot
%>%
penguins ggplot(aes(x=bill_length_mm,
y = bill_depth_mm,
color=species,
fill=species))+
geom_point()+
theme(axis.text=element_text(size=16),
axis.title=element_text(size=16))
Warning: Removed 2 rows containing missing values (`geom_point()`).
BMI vs Bill Length
%>%
penguins na.omit() %>%
ggplot(aes(x=bill_length_mm,
y = body_mass_g,
color=species,
fill=species))+
geom_boxplot(alpha=0.7)+
theme(axis.text=element_text(size=16),
axis.title=element_text(size=16))
Sex vs Flipper Length
%>%
penguins ggplot(aes(x=sex,
y = flipper_length_mm,
color=species,
fill=species))+
geom_point()+
theme(axis.text=element_text(size=16),
axis.title=element_text(size=16))
Warning: Removed 2 rows containing missing values (`geom_point()`).