In jyjek/jyjekNOAA: Plot for Analysis NOAA dataset

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

Package Info

The jyjekNOAA package is R-package for prepare and plot and map vizualizate for NOAA Significant Earthquake Database. This package was build for Coursera Mastering Softfawe Development in R specialization

Package Installing

For install jyjekNOAA package, you must have installed devtools package.

if(!("devtools" %in% installed.packages())){install.packages("devtools")}
devtools::install_github("jyjek/jyjekNOAA")
library(jyjekNOAA)

The package has dependices. For correct work also must be installed next packages:

library(jyjekNOAA) 
library(dplyr)
library(ggplot2)
library(lubridate)
library(purrr)
library(glue)
library(stringr)

Loading data

You can load NOAA Significant Earthquake Database:

NOAA_quakes<-jyjekNOAA::NOAA_quakes

For more information about dataset:

?jyjekNOAA::NOAA_quakes

Clean data

After laoding dataset you can clean data to the tidy format. Function eq_clean_data() transform dataset to the correct Date format and Location Name.

    NOAA_quakes%>%
    eq_clean_data()%>%
    head()

Plot Timeline of Data

One of the main target of this package is building Timeline geom geom_timeline using ggplot2 package. This function plot timeline for choosed Country and Time values of significant earthquakes with points colored and sized by number of deaths and Richter scale strength. X-axis is Year of accidente, and choosed Countrys on Y-axis.

Second ggplot2 geom is geom_timeline_label. It's similar to the geom_timeline but with label of top_n earthquakes for each choosed Country by mangnitude.

Function NOAA_thm add theme for ggplot2. This function make plot more pretty.
For example geom_timeline:

 NOAA_quakes%>%
  eq_clean_data()%>%
  dplyr::filter(COUNTRY %in% c('CHINA','MEXICO')) %>%
  dplyr::filter(DATE > '2010-01-01') %>%
  ggplot2::ggplot() +
  geom_timeline(aes(x = DATE, y = COUNTRY, size = as.numeric(EQ_PRIMARY),
                    color = as.numeric(TOTAL_DEATHS))) +
  guides(size = guide_legend(order=1))+
  scale_color_continuous(name = '# deaths') +
  scale_size_continuous(name = 'Richter scale value')+ NOAA_thm()

For example geom_timeline:

 NOAA_quakes%>%
  eq_clean_data()%>%
   dplyr::filter(COUNTRY %in% c('USA', 'JAPAN')) %>%
       dplyr::filter(DATE > '2000-01-01') %>%
       ggplot() +
       geom_timeline(aes(x = DATE, y = COUNTRY, color = as.numeric(TOTAL_DEATHS),
                         size = as.numeric(EQ_PRIMARY))) +
       geom_timeline_label(aes(x = DATE, y = COUNTRY, magnitude = as.numeric(EQ_PRIMARY),
                              label = LOCATION_NAME, n_max = 5)) +  guides(size = guide_legend(order=1))+
       scale_size_continuous(name = 'Richter scale value') +
       scale_color_continuous(name = '# of deaths') +
      NOAA_thm()

Map Plot

Call the function eq_map with eq_clean_data() for visualization leaflet Map with choosed Country and Dates.

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