R/timeseries.R

In USGS-R/AWUDS: wateRuse data analysis functions

#' time_series_data
#'
#' time_series_data
#' 
#' @param data.elements character name of data element within available categories by year for state
#' @param years vector of integers specifying all years available for state. Defaults to NA which shows all years in dataset.
#' @param w.use is a subset of the datafile wUseSample that includes all areas in all data elements for state
#' @param areas is a geographical area as defined in your datafile such as county, HUC, or aquifer
#' @param area.column character that defines which column to use to specify area
#' @param y.scale allows R to set the y-axis scale given available data range. Defaults to NA which lets R set the scale based on dataset values.
#' @param log = TRUE or FALSE allows user to set log scale, default is FALSE
#' @param plot.points is a logical function to show counties as points or clustered bar graph
#' @param legend is a logical function to include list of counties in a legend if manageable, default is TRUE
#' @param c.palette color palette to use for points or bars
#' 
#' @export
#' @import ggplot2
#' @importFrom tidyr gather_
#' @importFrom grDevices colorRampPalette
#' 
#' @examples 
#' df <- wUseSample
#' areas <- c("Kent County","Sussex County")
#' area.column = "COUNTYNAME"
#' data.elements <- c("PS.GWPop","TP.TotPop")
#' w.use <- subset_wuse(df, data.elements,area.column,areas)
#' year1 <- 2005
#' year2 <- 2010
#' years <- c(year1, year2)
#' time_series_data(w.use, data.elements, area.column = area.column,areas = areas)
#' time_series_data(w.use, data.elements, plot.points = FALSE,
#'        area.column = area.column,areas = areas)
#' time_series_data(w.use, data.elements, plot.points = FALSE,
#'        area.column = area.column,areas = areas, legend=FALSE)
#' time_series_data(w.use, data.elements, area.column)
#' time_series_data(w.use, data.elements, area.column, y.scale = c(0,1000))
#' time_series_data(w.use, data.elements, area.column, 
#'        y.scale = c(0,100),years = c(1990,2005))
time_series_data <- function(w.use, data.elements, area.column, plot.points = TRUE,
                             years= NA, areas= NA, y.scale=NA, log= FALSE, legend= TRUE,
                             c.palette = c("#999999", "#E69F00", "#56B4E9", "#009E73", "#F0E442", "#0072B2", "#D55E00", "#CC79A7")){

  w.use.sub <- subset_wuse(w.use, data.elements, area.column, areas)
  
  if(!any(is.na(years))){
    w.use.sub <-  w.use.sub[w.use.sub$YEAR %in% years,]
    w.use.sub$YEAR <- as.factor(w.use.sub$YEAR)
    levels(w.use.sub$YEAR) <- as.character(years)
  }
  
  df <- w.use.sub[,c("YEAR",area.column,data.elements)]
  
  df <- gather_(df, "dataElement", "value", c(data.elements))
  
  fix.labs <- gsub("\\,","\\,\n",dataelement$NAME)
  names(fix.labs) <- dataelement$DATAELEMENT
  
  df$dataElement <- fix.labs[gsub(pattern = "\\.", replacement = "-", x = df$dataElement)]
  
  if(length(unique(df[[area.column]])) > length(c.palette)){
    c.palette.ramp <- colorRampPalette(c.palette)
    c.palette <- c.palette.ramp(length(unique(df[[area.column]])))
  }
  
  ts.object <- ggplot(data = df) 
  
  if(plot.points){
    ts.object <- ts.object + geom_point(aes_string(x = "YEAR", y = "value", color = area.column)) +
      scale_colour_manual(values=c.palette)
  } else {
    ts.object <- ts.object + geom_bar(aes_string(x = "YEAR", y = "value", 
                                                 fill = area.column), 
                                      position = "dodge",stat="identity")+
      scale_fill_manual(values=c.palette)
  }

  ts.object <- ts.object + facet_grid(dataElement ~ ., scales = "free") +
    ylab("") +
    theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1))
  
  if(!all(is.na(y.scale))){
    ts.object <- ts.object + scale_y_continuous(limits=y.scale)
  }

  if(log){
    ts.object <- ts.object + scale_y_log10()
  }
  
  if(!legend){
    ts.object <- ts.object + theme(legend.position = "none")
  }
  
  ts.object
  
  return(ts.object)
}