visualizeNOAA

Introduction

This vignette provides an overview of the visualizeNOAA package functionalities for cleaning and visualizing earthquake data from NOAA.

Installation

You can install the package from GitHub using the following command:

#devtools::install_github("apd/visualizeNOAA")

Loading the Package

Once installed, load the package into your R session:

library(visualizeNOAA)
library(tidyverse)
library(leaflet)

Cleaning NOAA Earthquake Data

The eq_clean_data() function cleans the raw NOAA earthquake data. It reads the data from a tab-delimited file, creates a date column, and converts latitude and longitude to numeric class.

cleaned_data <- eq_clean_data("inst/extdata/earthquakes.tsv")
cleaned_data %>%
  head()
#> # A tibble: 6 × 6
#>   date       latitude longitude Location.Name                   magnitude no_deaths
#>   <date>        <dbl>     <dbl> <chr>                               <dbl>     <dbl>
#> 1 0480-09-29     37.9      23.5 GREECE:  SARONIC GULF                  NA        NA
#> 2 0186-02-22     33.8     106.  CHINA:  GANSU PROVINCE                  7       760
#> 3 0070-06-01     36.3     119   CHINA:  SHANDONG PROVINCE               7      6000
#> 4 0047-04-17     34.9     105.  CHINA:  GANSU PROVINCE:  LONGXI        NA        NA
#> 5 0031-09-02     32        35.5 ISRAEL:  QUMRAN,ARIHA (JERICHO)         7        NA
#> 6 0037-04-09     36.1      36.1 TURKEY:  ANTAKYA (ANTIOCH)             NA        NA

Cleaning Earthquake Location Names

The eq_location_clean() function cleans the LOCATION_NAME column by stripping out the country name and converting names to title case.

cleaned_location <- eq_location_clean(cleaned_data)
cleaned_location %>% 
  head()
#> # A tibble: 6 × 8
#>   date       latitude longitude Location.Name                         country         location               magnitude no_deaths
#>   <date>        <dbl>     <dbl> <chr>                                 <chr>           <chr>                      <dbl>     <dbl>
#> 1 2024-01-22    41.3       78.6 CHINA: XINJIANG PROVINCE;  KAZAKHSTAN CHINA           Xinjiang Province;  K…       7           3
#> 2 2024-01-01    37.5      137.  JAPAN: HONSHU: ISHIKAWA               JAPAN           Honshu: Ishikawa             7.5       241
#> 3 2023-12-18    35.7      103.  CHINA:  GANSU PROVINCE: JISHISHAN     CHINA           Gansu Province: Jishi…       5.9       151
#> 4 2023-12-07   -20.7      169.  VANUATU:  TANNA ISLAND                VANUATU         Tanna Island                 7.1        NA
#> 5 2023-12-02     8.53     126.  PHILIPPINES:  MINDANAO:  E            PHILIPPINES     Mindanao:  E                 7.6         3
#> 6 2023-11-22   -15.0      168.  VANUATU ISLANDS: MAEWO                VANUATU ISLANDS Maewo                        6.7        NA

Visualizing Earthquake Data

Timeline of Earthquakes

The geom_timeline() function plots a timeline of earthquakes.

df_visualize <- bind_rows(
  cleaned_location %>%
    head(10),
  data.frame(country="", location ="")) %>% 
  mutate(country=factor(country, levels = unique(country))) 
ggplot(data = df_visualize) +
  geom_timeline(aes(date,size = magnitude,  color = no_deaths)) +
  theme_minimal() +
  theme(
    axis.line.x = element_line(linewidth = 0.75),
    axis.title.y = element_blank(),
    panel.grid.major.x = element_blank(),
    panel.grid.minor.x = element_blank(),
    legend.position = "bottom"
  )
#> Warning: Removed 1 rows containing missing values (`geom_timeline()`).

Timeline of Earthquakes

The geom_timelinelabel() function includes label as well.

ggplot(data = df_visualize) +
  geom_timeline(aes(date,size = magnitude,  color = no_deaths))  +
  geom_timelinelabel(aes(date,label = location), n_max = 5) +
  theme_minimal() +
  theme(
    axis.line.x = element_line(linewidth = 0.75),
    axis.title.y = element_blank(),
    panel.grid.major.x = element_blank(),
    panel.grid.minor.x = element_blank(),
    legend.position = "bottom"
  )
#> Warning: Removed 1 rows containing missing values (`geom_timeline()`).
#> Warning: Removed 1 rows containing missing values (`geom_timeline_label()`).

ggplot(data = df_visualize) +
  geom_timeline(aes(date,country, size = magnitude,  color = no_deaths))  +
  geom_timelinelabel(aes(date,country,label = location), n_max = 5) +
  theme_minimal() +
  theme(
    axis.line.x = element_line(linewidth = 0.75),
    axis.title.y = element_blank(),
    panel.grid.major.x = element_blank(),
    panel.grid.minor.x = element_blank(),
    legend.position = "bottom"
  )
#> Warning: Removed 1 rows containing missing values (`geom_timeline()`).
#> Warning: Removed 1 rows containing missing values (`geom_timeline_label()`).

Visualize Earthquakes in Mexico Since 2000

This function filters the cleaned earthquake data to include only earthquakes in Mexico since the year 2000 and visualizes them on a leaflet map. Each earthquake is represented by a circle on the map, with the circle’s radius proportional to the earthquake’s magnitude. The pop-up for each circle displays the date of the earthquake.

eq_clean_data("../inst/extdata/earthquakes.tsv") %>%
  eq_location_clean() %>%
  filter(country=="MEXICO" & lubridate::year(date) >= 2000) %>%
  eq_map(annot_col = "date")

Visualize Earthquakes in Mexico Since 2000 with Custom Annotations

This function filters the cleaned earthquake data to include only earthquakes in Mexico since the year 2000. It then creates custom annotations for each earthquake, including information about the location, magnitude, and total deaths. These annotations are added to the leaflet map, providing more detailed information when a user interacts with the map.

eq_clean_data("../inst/extdata/earthquakes.tsv") %>%
  eq_location_clean() %>%
  filter(country=="MEXICO" & lubridate::year(date) >= 2000) %>%
  mutate(popup_text =  eq_create_label(.)) %>%
  eq_map(annot_col = "popup_text")