In kfull/noaa: Visualize NOAA Earthquake Data

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

options(warn=-1)

library(noaa)
library(readr)
library(dplyr)
library(tidyr)
library(stringr)
library(chron)
library(ggplot2)
library(grid)
library(scales)
library(utils)
library(leaflet)

setwd(system.file("extdata", package = "noaa"))

This vignette gives an overview on the functionality of the NOAA package. The package is designed to visualize earthquake data from the National Oceanic and Atmospheric Administration (NOAA).

The package provides a set of functions for visualizing earthquake data from NOAA:

eq_clean_data(data)
eq_location_clean(data)
geom_timeline(mapping, data, stat, position, ..., na.rm, show.legend, inherit.aes)
geom_timeline_label(mapping, data, stat, position, ..., na.rm, show.legend, inherit.aes)
eq_map(data, annot_col)
eq_create_label(data, location, magnitude, total_deaths)

In the following, these functions are discussed in more detail. The data used for demonstrating the usage of the functions are stored in the package folder inst/extdata.

Cleaning NOAA Earthquake Data

Before visualizing earthquake data from NOAA, the data has to be cleaned. For that purpose, the function eq_clean_data(data) can be used. The function adds a date column to the given NOAA data frame, converts the latitude and longitude columns to numeric, and uses the function eq_location_clean(data) to strip out the country name of the location column and covert the location column to title case.

The following example shows how to clean earthquake data:

# set working directory
setwd(system.file("extdata", package = "noaa"))
# read and clean NOAA data
data <- read_delim("signif.txt", "\t") %>%
  eq_clean_data()

The following examples can be used in order to only clean the location name instead of the whole earthquake data:

# set working directory
setwd(system.file("extdata", package = "noaa"))
# read and clean NOAA data
data <- read_delim("signif.txt", "\t") %>%
  eq_location_clean()

Plotting NOAA Earthquake Data

For the purpose of plotting earthquake data from NOAA, two function are available in the package. The function geom_timeline(mapping, data, stat, position, ..., na.rm, show.legend, inherit.aes) plots one or multiple timelines of earthquakes. The function geom_timeline_label(mapping, data, stat, position, ..., na.rm, show.legend, inherit.aes) adds labels to the timelines.

With the following example, timelines of earthquakes are plotted and labelled:

# set working directory
setwd(system.file("extdata", package = "noaa"))
# read and clean NOAA data
data <- read_delim("signif.txt", "\t") %>%
  eq_clean_data() %>%
  dplyr::filter(COUNTRY %in% c("USA", "CHINA"), YEAR > 2000)
# plot NOAA data
ggplot2::ggplot(data, ggplot2::aes(DATE,
                                   colour = as.numeric(TOTAL_DEATHS),
                                   y = COUNTRY,
                                   size = as.numeric(EQ_PRIMARY))) +
 geom_timeline() +
 geom_timeline_label(ggplot2::aes(label = data$LOCATION_NAME)) +
 ggplot2::guides(size = ggplot2::guide_legend(title = "Richter Scale")) +
 ggplot2::scale_colour_continuous(name = "Number of Deaths") +
 ggplot2::theme_classic()

Mapping NOAA Earthquake Data

In addition to cleaning and plotting earthquake data from NOAA, the package provides functions for mapping earthquake data. The function eq_map(data, annot_col) maps the epicenters of earthquakes and annotates them within pop up windows. The function eq_create_label(data, location, magnitude, total_deaths) creates HTML labels for earthquakes that can be used as annotations within the pop up windows.

With the following example, earthquake data are mapped and annotated:

# set working directory
setwd(system.file("extdata", package = "noaa"))
# read and clean NOAA data
data <- readr::read_delim("signif.txt", "\t") %>%
  eq_clean_data() %>%
  dplyr::filter(COUNTRY == "MEXICO", YEAR > 2000)
# create HTML labels
data <- data %>%
  dplyr::mutate(html_label = eq_create_label(.))
# map and annotate NOAA data
eq_map(data, annot_col = "html_label")