plot_improvements.rmd

---
title: "Plot Improvements"
output: html_document
date: "2022-09-08"
---

# Take A Sad Plot and Make it Better 

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

## Load libraries 

```{r}
library(tidyverse)
library(scales)
library(palmerpenguins)
library(ggbeeswarm)
```

## Dataset 

```{r}
finalfit::missing_glimpse(penguins)
penguins = penguins %>% 
  drop_na(species, sex, body_mass_g)
```

## Sad Plot

```{r}
penguins %>% 
  ggplot(aes(x = species, y = body_mass_g)) + 
  geom_boxplot() +
  facet_grid(.~island)
```


## Sad Plot + raw data

```{r}
penguins %>% 
  ggplot(aes(x = species, y = body_mass_g)) + 
  geom_boxplot(outlier.shape = NA) +
  geom_jitter(alpha = 0.2) +
  facet_grid(.~island)

# Checkout geom_boxplot2
## https://stackoverflow.com/questions/5677885/ignore-outliers-in-ggplot2-boxplot
```
## Sad Plot + raw data + remove grey background

```{r}
penguins %>% 
  ggplot(aes(x = species, y = body_mass_g)) + 
  geom_boxplot(outlier.shape = NA) +
  geom_jitter(alpha = 0.2) +
  facet_grid(.~island) + 
  theme_bw()
```

## Sad Plot + raw data + remove grey background + axis labels

```{r}
library(ggtext)
penguins %>% 
  ggplot(aes(x = species, y = body_mass_g)) + 
  geom_boxplot(outlier.shape = NA) +
  geom_jitter(alpha = 0.2) +
  # labs(x = "Species", y = "Body mass (g)") +
  labs(x = "Species", y = "Body mass (g^(2))") +
  facet_grid(. ~ island) +
  theme_bw() +
  theme(axis.title.y = element_markdown())
```



## Sad Plot + raw data + remove grey background + axis labels + remove empty factor levels

```{r}
forcats::fct_drop
penguins %>% 
  ggplot(aes(x = species, y = body_mass_g)) + 
  geom_boxplot(outlier.shape = NA) +
  geom_jitter(alpha = 0.2) +
  labs(x = "Species", y = "Body mass (g^(2))") +
  facet_grid(. ~ island, scales = "free_x") +
  theme_bw() +
  theme(axis.title.y = element_markdown())
```

# Sad plot + change whisker length

```{r}
penguins %>% 
  ggplot(aes(x = species, y = body_mass_g)) + 
  geom_boxplot(coef = 2) +
  facet_grid(.~island)
```

## Hints 

* Add the raw data - colour per species - change colour palatte
* Remove the outliers
* Remove the grey background
* Fix the axes lables - remove legend
* Add the mean

```{r}
penguins %>% 
  ggplot(aes(x = species, y = body_mass_g))  +
  geom_boxplot(fill = NA, outlier.shape = NA, alpha = 0.2) +                                  # remove outliers
  facet_grid(.~island, scales = "free_x", space = "free_x") +                                 # free x axis          
  geom_jitter(aes(colour = species), alpha = 0.5, width = 0.1, size = 3) +                    # jitter 
  labs(y = "Body Mass (g)", x = "Penguin Species", caption = "Source: Palmerpenguins") +      # Axis captions
  stat_summary(fun = mean, 
               geom = "point", shape = 20, size = 5, color = "black", fill = "black") +       # Add mean
  scale_colour_viridis_d() +                                                                  # Change colour scheme 
  theme_bw() +                                                                                # Remove grey background  
  theme(legend.position = "none")                                                             # Remove legend - note: setting the theme should be done after removing background theme
```