In ankit2219/masteringr: NOAA Significant Earthquakes Dataset Mapping

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

The noaar package has been built for cleaning and mapping NOAA's Significant Earthquake data.

Installation

In order to install the noaar package, you must first install the devtools package and then use the following commands:

devtools::install_github("AnoushiravanR/noaar")
library(noaar)

Required packages

For codes in noaar package to work the following packages are required:

library(noaar)
library(dplyr)
library(tidyr)
library(ggplot2)
library(stringr)
library(lubridate)
library(purrr)
library(rlang)
library(grid)
library(leaflet)
library(tibble)

Load and clean package data

For loading the NOAA_data you can use noaar::NOAA_data, then you can call eq_clean_data and eq_location_clean to do some modifications on a number of variables. After that the data can be used for geom functions.

NOAA_data <- noaar::NOAA_data
NOAA_data <- NOAA_data %>%
  eq_clean_data() %>%
  eq_location_clean()
NOAA_data %>%
  dplyr::select(1:10)

A brief description of the variables that are used for data analysis are presented in the table bellow:

knitr::kable(tibble::tribble(~ Variable, ~ Class, ~ Description,
                             "Date", "Date", "The date in which the earthquake occurred",
                             "Country", "Character", "The Country in which the earthquake occurred",
                             "Location", "Character", "The place(normally city) in which the earthquake occurred",
                             "Longitude", "Numeric", "The longitude of the location",
                             "Latitude", "Numeric", "The latitude of the location", 
                             "Mag", "Numeric", "The magnitude of earthquake based on the Richter scale",
                             "Deaths", "Numeric", "The number of casualties(deaths)"), 
             caption = "The Principal Variables Required for Visualization")

Geoms

geom_timeline

You can use the following code to make a time line geom of a single or multiple countries within a specific time intervals:

NOAA_data %>%
  dplyr::filter(Country %in% c("MEXICO", "IRAN") &
           Date %within% lubridate::interval(ymd(20000103), ymd(20180104))) %>%
  dplyr::mutate(Country = factor(Country, levels = unique(Country))) %>%
  ggplot2::ggplot() +
  geom_timeline(aes(x = Date, y = Country, size = Mag, colour = Deaths)) +
  ggplot2::scale_colour_continuous(name = "# deaths") +
  ggplot2::scale_size_continuous(name = "Richter scale value") +
  ggplot2::theme(legend.position = "bottom") +
  ggplot2::ylab("")

geom_timeline_label

This geom function also enables you to map a time line of a single or multiple countries within a specific time interval, additionally, it has a new aesthetic n_max which you can adjust for labeling the n biggest earthquakes.

NOAA_data %>%
  dplyr::filter(Country %in% c("MEXICO", "IRAN") &
           Date %within% lubridate::interval(ymd(20000103), ymd(20180104))) %>%
  dplyr::mutate(Country = factor(Country, levels = unique(Country))) %>%
  ggplot2::ggplot() +
  geom_timeline(aes(x = Date, y = Country, size = Mag, colour = Deaths)) +
  geom_timeline_label(aes(x = Date, y = Country, label = Location,
                          magnitude = Mag, colour = Deaths, n_max = 5), alpha = 0.5) +
  ggplot2::scale_colour_continuous(name = "# deaths") +
  ggplot2::theme(legend.position = "bottom") +
  ggplot2::ylab("")

Note that you can combine these two geoms or use them seperately.

Plot Map

Using a column for annotation

You can create an interactive leaflet map with eq_map function. You can also annotate the locations by using annot_col argument and adjusting a column to it. It should be noted that annot_col requires a character vector.

NOAA_data %>%
  dplyr::filter(Country == "MEXICO" & lubridate::year(Date) >= 2000) %>%
  eq_map(annot_col = "Date")

Using a more interesting and informative annotation

For more customized and informative labels you can create a new variable in the data set using some HTML-formatting to create character string for the annot_col parameter.

NOAA_data %>%
  dplyr::filter(Country %in% c("HONDURAS", "MEXICO") & year(Date) >= 2000) %>%
  dplyr::mutate(popup_text = eq_create_label(.)) %>%
  eq_map(annot_col = "popup_text")