R/eq_clean_data.R

In raggichr/earthquakes: MSDR Capstone: Build an R Package for Earthquakes Data

#' @title Cleans the raw NOAA earthquake dataset.
#'
#' @description The dataset is obtained from the U.S. National Oceanographic and Atmospheric Administration (NOAA)
#' on significant earthquakes around the world. This dataset contains information about 5,933 earthquakes over an
#' approximately 4,000 year time span.
#'
#' The \code{eq_clean_data()} function takes the raw NOAA data frame and
#' returns a clean data frame. The clean data frame should have the following:
#' \enumerate{
#'   \item A date column created by uniting the year, month, day and converting it to the Date class.
#'   \item LATITUDE and LONGITUDE columns converted to numeric class.
#'   \item In addition, a LOCATION_NAME column by stripping out the country name (including the colon)
#'   and converts names to title case (as opposed to all caps). This will be needed later for annotating visualizations.
#' }
#'
#' @param eq_raw the raw NOAA earthquake dataset as a data frame that contains location names written in upper case.
#'
#' @return returns a clean data frame of the NOAA earthquake dataset.
#'
#' @examples
#' \dontrun{
#' filename <- system.file("extdata", "signif.txt", package = "earthquakes")
#' library(readr)
#' eq_data_raw <- readr::read_delim(file = filename, delim = "\t")
#' eq_data <- eq_clean_data(eq_raw = eq_data_raw)
#' head(eq_data_raw$LOCATION_NAME)
#' head(eq_data$LOCATION_NAME)
#' }
#'
#' @export
eq_clean_data <- function(eq_raw){

    YEAR <- NULL
    MONTH <- NULL
    DAY <- NULL
    HOUR <- NULL

    LATITUDE <- NULL
    LONGITUDE <- NULL
    EQ_PRIMARY <- NULL
    DEATHS <- NULL
    TOTAL_DEATHS <- NULL

    LOCATION_NAME <- NULL

    # 1. A date column created by uniting the year, month, day and converting it to the Date class
    # 2. LATITUDE and LONGITUDE columns converted to numeric class
    eq_raw %>%
        dplyr::mutate(DATE = lubridate::ymd_h(paste(eq_raw$YEAR,
                                             eq_raw$MONTH,
                                             eq_raw$DAY,
                                             eq_raw$HOUR, sep = ""))) %>%
        dplyr::mutate_at(.vars = (c("LATITUDE",
                                    "LONGITUDE",
                                    "EQ_PRIMARY",
                                    "DEATHS",
                                    "TOTAL_DEATHS")), .funs = ~as.numeric(.)) -> eq_clean

    # 3. cleans the LOCATION_NAME column by stripping out the country name (including the colon) and converts names to title case
    eq_clean <- eq_location_clean(eq_datf = eq_clean)

    return(eq_clean)
}