In moralmar/earthquakesWithR:

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-"
)

earthquakesWithR

The goal of earthquakesWithR is to give a few handy visualization tools for the NOAA data set. It provides to the user of this package the following functions:
- geom_timeline() - which is a specific geom for the ggplot2 package
- geom_timeline_label() - which is an extension for the above geom
- eq_location_clean() - which is a helper function, cleaning the NOAA dataset
- eq_clean_data() - a function which loads and applies a few cleaning function to it
- eq_map() - a function creating a leaflet map and visualizing the earth quakes
- eq_create_label() - is a helper function, creating a nice pop-ups in the leaflet map

Installation

You can install earthquakesWithR from github with:

# install.packages("devtools")
devtools::install_github("moralmar/earthquakesWithR")

Data

The Significant Earthquake Database 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.
Feel free to browse through the code as follows:

# To load the earth quake data and have a look:
data("NOAAearthquakes")

# the following is a spatial polygon data frame, which merely gives a nice touch to the leaflet map
# hence, there is not much to see here
data("world")

Example - Timeline

Here are three simple examples, showing
- a single country without labels
- a single country with labels
- and showing multiple countries, also with lables

More complex examples can be found in the vignette and also on my RPubs.

require(earthquakesWithR)
require(magrittr) # for piping operator
require(dplyr) # for filter/subsetting functions
require(ggplot2) # should be obvious :)
require(ggthemes) # for the theme_classic()

eval=FALSE

# Load the data and filter it accordingly to your needs
quakes <- eq_clean_data()
quakes_filtered <- quakes %>%
        filter(COUNTRY %in% c("USA") & YEAR >= 1000)

# single country without labels
ggplot() +
        geom_timeline(data = quakes_filtered, aes(x = date, y = COUNTRY, color = TOTAL_DEATHS, size = EQ_PRIMARY)) +
        theme_classic()

# Load the data and filter it accordingly to your needs
quakes <- eq_clean_data()
quakes_filtered <- quakes %>%
        filter(COUNTRY %in% c("PERU") & YEAR >= 1960)

# single country without labels
ggplot() +
        geom_timeline(data = quakes_filtered, aes(x = date, y = COUNTRY, color = TOTAL_DEATHS, size = EQ_PRIMARY)) +
        geom_timeline_label(data = quakes_filtered, aes(x = date,
                                                 y = COUNTRY,
                                                 magnitude = EQ_PRIMARY,
                                                 label = LOCATION_NAME,
                                                 n_max = 6)) +
        theme_classic()

# Load the data and filter it accordingly to your needs
quakes <- eq_clean_data()
quakes_filtered <- quakes %>%
        filter(COUNTRY %in% c("ECUADOR", "PERU", "CHILE") & YEAR >= 1000)

# single country without labels
ggplot() +
        geom_timeline(data = quakes_filtered, aes(x = date, y = COUNTRY, color = TOTAL_DEATHS, size = EQ_PRIMARY)) +
        geom_timeline_label(data = quakes_filtered, aes(x = date,
                                                 y = COUNTRY,
                                                 magnitude = EQ_PRIMARY,
                                                 label = LOCATION_NAME,
                                                 n_max = 4)) +
        theme_classic()

Example - Leaflet Map

Besides the added timeline geom-functions, the package provides a few function which helps to easily create a leaflet map. What these functions do is shown below. Keep in mind that this is static maps, respectively a print screen of the leaflet map (because the README.rm is a static file format). It shows the two main functions in action:

eq_map() - the base function creating a leaflet map and visualizing the earth quakes
eq_create_label() - is a helper function, creating a nice pop-ups in the leaflet map

# in addition to the earthquakesWithR package, we need:
require(leaflet)

eq_clean_data() %>%
        dplyr::filter(COUNTRY == "MEXICO" & lubridate::year(date) >= 2000) %>%
        dplyr::mutate(popup_text = eq_create_label(.)) %>%
        eq_map(annot_col = "popup_text")