meteorite-impacts.Rmd

---
title: "Meteorite Impacts"
author: "Dean Marchiori"
date: "6/18/2019"
output: html_document
editor_options: 
  chunk_output_type: console
---

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

##  Intro  

This week's dataset is a dataset all about meteorites, where they fell and when they fell! Data comes from the Meteoritical Society by way of NASA.   

https://github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-06-11  


## Loading packages and reading in data

```{r message=FALSE, warning=FALSE}
library(tidyverse)
library(maps)
library(cowplot)
library(ggrepel)

meteorites <- readr::read_csv("https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2019/2019-06-11/meteorites.csv")
```

# Preprocessing 

Here I limit the dataset to those records that fall within the bounding box of
Australia.  

To enable selective labelling I make use of `ifelse` to create a new column with
mostly `NA` values except the records I want to print as labels.  

```{r}
# Aus. Bounding Box
bbox <- c(113.338953078, -45.6345972634, 153.569469029, -10.6681857235)

meteorites_processed <- meteorites %>% 
  mutate(class = fct_lump(class, 5)) %>% 
  filter(long > bbox[1], long < bbox[3], 
         lat > bbox[2], lat < bbox[4],
         name_type != "Relict") %>% 
  mutate(met_name = ifelse(mass >= 2000000, name, NA))
```

## Making Plots  

The idea here is to creatre two plots and use the `cowplot` package to 
draw one as an inset.  

```{r}

map <- borders(database = "world", 
               regions = c("Australia"), 
               colour="gray50", 
               fill="gray50",
               ylim = c(bbox[2], bbox[4]), 
               xlim = c(bbox[1], bbox[3])) 

size_guide <- meteorites_processed %>% 
  top_n(5, mass)  %>% 
  mutate(name = fct_reorder(name, mass)) %>% 
  ggplot(aes(name, 1, size = mass)) + 
  geom_point(show.legend = F, alpha = 0.6, colour = "red") +
  scale_size(range = c(1, 20)) +
  geom_text(aes(name, 1, label = name), nudge_y = -0.15,  size = 2.5) +
  geom_text(aes(name, 1, label = year), nudge_y = -0.2,  size = 2.5) +
  geom_text(aes(name, 1, label = paste(mass/1000, "kg")), size = 2.5, nudge_y = -0.25) +
  scale_y_continuous(limits = c(0, 1.5))  +
  theme_void() 

ozmap <- ggplot() +
  map +
  theme_void() +
  geom_point(data = meteorites_processed, aes(long, lat, size = sqrt(mass), colour = class), alpha = 0.3, show.legend = T) +
  scale_size(range = c(0.1, 20), guide = FALSE) +
  scale_color_viridis_d(direction = -1) +
  geom_label_repel(data = meteorites_processed, aes(long, lat, label = met_name), size = 3, nudge_y = -3, nudge_x = 3) +
  labs(title = "Australian Meteorite Landings",
       subtitle = "All recorded meteorite landings by NASA",
       caption = "source: https://data.nasa.gov/Space-Science/Meteorite-Landings/gh4g-9sfh/data",
       colour = "Meteor \n Class")

ggdraw() +
  draw_plot(ozmap) +
  draw_plot(size_guide, x = 0.0, y = -0.3, width = 0.55, height = .75) 

```