README.md
In csgbloom/NOAAearthquake: NOAA Earthquake Analysis

NOAA Earthquake Analysis

This package has been developed as part of the capstone module for Coursera’s Mastering Software Development in R Specialization. This package allows you to load earthquake data from the US National Centers for Environmental Information. These data contains information on destructive earthquakes from 2150 B.C. to the present that meet at least one of the following criteria:

Moderate damage (approximately $1 million or more),
10 or more deaths,
Magnitude 7.5 or greater,
Modified Mercalli Intensity X or greater, or the earthquake generated a tsunami.

You can install the released version of the NOAA earthquake package by:

library(devtools)
#> Loading required package: usethis
install_github("csgbloom/NOAAearthquake")
#> Downloading GitHub repo csgbloom/NOAAearthquake@HEAD
#> 
#>      checking for file ‘/tmp/RtmpZSqsvw/remotes344176f32fa0/csgbloom-NOAAearthquake-b0e910d/DESCRIPTION’ ...  ✓  checking for file ‘/tmp/RtmpZSqsvw/remotes344176f32fa0/csgbloom-NOAAearthquake-b0e910d/DESCRIPTION’
#>   ─  preparing ‘NOAAearthquake’:
#>      checking DESCRIPTION meta-information ...  ✓  checking DESCRIPTION meta-information
#>   ─  checking for LF line-endings in source and make files and shell scripts
#>   ─  checking for empty or unneeded directories
#>   ─  building ‘NOAAearthquake_0.1.0.tar.gz’
#>      
#> 
#> Installing package into '/home/murray/R/x86_64-pc-linux-gnu-library/3.6'
#> (as 'lib' is unspecified)
library(NOAAearthquake)

The function eq_clean_data():

loads the data file
creates a single Date field from the original Year, Mo and Dy fields, adding 01-01 where no month or day in original data

df1 <- eq_clean_data(system.file("extdata", "earthquakes.tsv", package = "NOAAearthquake"))
head(df1$Date)
#> [1] "-2150-01-01" "-2000-01-01" "-2000-01-01" "-1610-01-01" "-1566-01-01"
#> [6] "-1450-01-01"

The function eq_location_clean():

splits and reformats the orginal Location Name field into Location Name and Country

df2 <- eq_location_clean(df1)
head(df2$Country)
#> [1] "Jordan"       "Syria"        "Turkmenistan" "Greece"       "Israel"      
#> [6] "Italy"

The function geom_timeline():

generates a basic ggplot2 visualisation of the timeline of earth quakes for a given year range and country
the size of the marker is proportional to the magnitude of the earthquake
the colour of the marker is scaled according to the the total number of deaths caused by the earthquake

library(tidyverse)
#> ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.0 ──
#> ✓ ggplot2 3.3.3     ✓ purrr   0.3.4
#> ✓ tibble  3.1.0     ✓ dplyr   1.0.5
#> ✓ tidyr   1.1.3     ✓ stringr 1.4.0
#> ✓ readr   1.4.0     ✓ forcats 0.5.1
#> ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
#> x dplyr::filter() masks stats::filter()
#> x dplyr::lag()    masks stats::lag()
df2 %>% 
   dplyr::filter(Country %in% c("Mexico", "Turkey"), lubridate::year(Date) > 2000) %>% 
   ggplot2::ggplot(aes(x = Date, y = Country, color = `Total Deaths`, size = Mag)) +
   geom_timeline() +
   ggplot2::labs(size = "Richter scale value", col = "# Deaths")

The function theme_timeline():

applies a specified ggplot2 theme to the plot generated by geom_timeline()

df2 %>% 
   dplyr::filter(Country %in% c("Mexico", "Turkey"), lubridate::year(Date) > 2000) %>% 
   ggplot2::ggplot(aes(x = Date, y = Country, color = `Total Deaths`, size = Mag)) +
   geom_timeline() +
   theme_timeline() +
   ggplot2::labs(size = "Richter scale value", col = "# Deaths")

The function geom_timeline_label():

applies Location Name labels to the earthquakes of the highest magnitude for that year range
the number of highest magnitude earthquakes to be labelled is specified n_max

df2 %>% 
   dplyr::filter(Country %in% c("Mexico", "Turkey"), lubridate::year(Date) > 2000) %>% 
   ggplot2::ggplot(aes(x = Date, y = Country, color = `Total Deaths`, size = Mag)) +
   geom_timeline() +
   geom_timeline_label(aes(label = `Location Name`), n_max = 3) +
   theme_timeline() +
   ggplot2::labs(size = "Richter scale value", col = "# Deaths")
#> Warning: `group_by_()` was deprecated in dplyr 0.7.0.
#> Please use `group_by()` instead.
#> See vignette('programming') for more help

The function eq_map():

generates a Leaflet map plotting the earthquakes for a specified country and year range
marker popup labels are date (YYYY-MM-DD)

df2 %>% 
   dplyr::filter(Country == "Turkey", lubridate::year(Date) >= 2010) %>%  
   eq_map(annot_col = "Date")

Map with basic date label

The function eq_create_label():

generates popup labels with Location, Magintude and Total Deaths fields

df2 %>% 
   dplyr::filter(Country == "Turkey", lubridate::year(Date) >= 2010) %>%  
   dplyr::mutate(popup_text = eq_create_label(.)) %>%
   eq_map(annot_col = "popup_text")

Map with more detailed label