R/get_rainfall.R

In Helson-Gomes/BReco: R Package to Download and Clean Brazilian Environmental Data

get_rainfall <- function(level = 'municipality', panel = FALSE){
  # The code below help to avoid the note "no visible binding for global variable [variable name]"
  CD_GEOCMU <- cod.state <- sigla.state <- country <- v1 <- rainfall <- NULL
  temp <- tempfile()
  if(level == "municipality"){
    message("Please, wait for the data to download!")
    dt <- openxlsx::read.xlsx("https://trello-attachments.s3.amazonaws.com/5ea83f462064047eed09f846/5ea83fc7d5707865983b4f14/2fe3829d60a70197d0b44337440348a2/PEECIPITACAO_1901_2019.xlsx")
  }
  if(level == 'state'){
    message('Please, wait for the data to download!')
    dt <- openxlsx::read.xlsx("https://trello-attachments.s3.amazonaws.com/5ea83f462064047eed09f846/5ea83fc7d5707865983b4f14/2fe3829d60a70197d0b44337440348a2/PEECIPITACAO_1901_2019.xlsx")
    dt <- dplyr::mutate(dt, cod.state = substr(CD_GEOCMU, 1, 2),
                        sigla.state = ifelse(cod.state == '11', 'RO' , 'DF'),
                        sigla.state = ifelse(cod.state == '12', 'AC' , sigla.state), sigla.state = ifelse(cod.state == '13', 'AM' , sigla.state),
                        sigla.state = ifelse(cod.state == '14', 'RR' , sigla.state), sigla.state = ifelse(cod.state == '15', 'PA' , sigla.state),
                        sigla.state = ifelse(cod.state == '16', 'AP' , sigla.state), sigla.state = ifelse(cod.state == '17', 'TO' , sigla.state),
                        sigla.state = ifelse(cod.state == '21', 'MA' , sigla.state), sigla.state = ifelse(cod.state == '22', 'PI' , sigla.state),
                        sigla.state = ifelse(cod.state == '23', 'CE' , sigla.state), sigla.state = ifelse(cod.state == '24', 'RN' , sigla.state),
                        sigla.state = ifelse(cod.state == '25', 'PB' , sigla.state), sigla.state = ifelse(cod.state == '26', 'PE' , sigla.state),
                        sigla.state = ifelse(cod.state == '27', 'AL' , sigla.state), sigla.state = ifelse(cod.state == '28', 'SE' , sigla.state),
                        sigla.state = ifelse(cod.state == '29', 'BA' , sigla.state), sigla.state = ifelse(cod.state == '31', 'MG' , sigla.state),
                        sigla.state = ifelse(cod.state == '32', 'ES' , sigla.state), sigla.state = ifelse(cod.state == '33', 'RJ' , sigla.state),
                        sigla.state = ifelse(cod.state == '35', 'SP' , sigla.state), sigla.state = ifelse(cod.state == '41', 'PR' , sigla.state),
                        sigla.state = ifelse(cod.state == '42', 'SC' , sigla.state), sigla.state = ifelse(cod.state == '43', 'RS' , sigla.state),
                        sigla.state = ifelse(cod.state == '50', 'MS' , sigla.state), sigla.state = ifelse(cod.state == '51', 'MT' , sigla.state),
                        sigla.state = ifelse(cod.state == '52', 'GO' , sigla.state))
    dt <- dplyr::group_by(dt, sigla.state, cod.state)
    dt <- dplyr::summarise_at(dt, 5:123, mean)
  }
  if(level == 'country'){
    message('Please, wait for the data to download!')
    dt <- openxlsx::read.xlsx("https://trello-attachments.s3.amazonaws.com/5ea83f462064047eed09f846/5ea83fc7d5707865983b4f14/2fe3829d60a70197d0b44337440348a2/PEECIPITACAO_1901_2019.xlsx")
    dt <- dplyr::mutate(dt, country = 'Brazil')
    dt <- dplyr::group_by(dt, country)
    dt <- dplyr::summarise_at(dt, 5:123, mean)
  }
  if(panel == TRUE){
    dt <- tidyr::gather(dt, v1, rainfall, 'PREC_1901':'PREC_2019')
    dt <- dplyr::mutate(dt, year = substr(v1, 6,9))
    dt <- dplyr::select(dt, -v1)
  }
  if(level %in% c('municipality', 'state', 'country') == FALSE | panel %in% c(T, F) == FALSE){
    stop('\n
    -------------------------------------------------------- \n
    Please, enter a valid value to level or panel parameter! \n
    -------------------------------------------------------- \n')
  }
  warning('\n
  -------------------------------------------------- \n
  Please, cite https://www.globalclimatemonitor.org/ \n
  and \n
  CAMARILLO-NARANJO, Juan Mariano et al. The global \n
  climate monitor system: from climate data-handling \n
  to knowledge dissemination. International journal \n
  of digital earth, v. 12, n. 4, p. 394-414, 2019.
  -------------------------------------------------- ')
  return(dt)
}