R/SummarizeByMonth.R

In coopermj/SummarizeByMonth: Summarize DataFrame by Month

#' Summarize data frame by Month
#' This function summarizes all columns by week and returns a dataframe with summarized data and month dates
#' @param df Dataframe on which to operate. Must have column DateStamp
#' @param summarizationMethod String that indicates mean or sum
#' @param flipNA TRUE or FALSE to convert NAs to 0
#' @param dateCol Column that contains the date values. Defaults to DateStamp
#' @keywords summarize month monthly
#' @export
#' @examples
#' SummarizeByMonth(df, "mean", TRUE)

SummarizeByMonth <- function(df, summarizationMethod, flipNA, dateCol) {

  library(plyr)
  library(dplyr)
  library(data.table)

  browser()

  if (missing(dateCol)) {
    dateCol = 'DateStamp'
  } else {
    setnames(df, dateCol, 'DateStamp')
  }

  # Find the beginning/end of the range
  mindate <- min(df$DateStamp)
  maxdate <- max(df$DateStamp)
  # Create a data frame with all the dates
  ts <- seq.POSIXt(as.POSIXct(mindate), as.POSIXct(maxdate), by = "day")
  ts <- format.POSIXct(ts,'%Y-%m-%d')
  dfr <- data.frame(DateStamp = ts)
  # Merge the two dataframes to fill in missing dates
  data_with_missing_times <- full_join(dfr,df)
  # shortening to make typing (and copying examples) easiers
  df <- data_with_missing_times
  # create timestamp to make it easier to convert to week
  df$timestamp <- as.numeric(as.POSIXct(df$DateStamp))
  # convert to week

  df$month <- format(as.Date(df$DateStamp), "%Y-%m")

  # Because we're looping, we need a tempoary dataframe to hold our results
  # We start with just a dataframe of the months (made unique)
  tempdf <- data.frame(month = unique(df$month))


  for (columnName in names(df)) {
    # columnName <- i # switch i to columnName to make it
    if (columnName == "DateStamp") next # skip the DateStamp column
    if (columnName == "timestamp") next # skip the DateStamp column
    if (columnName == "month") next # skip the DateStamp column
    if (columnName == dateCol) next # skip variable DateStamp column

    # Make a dataframe that is a simplified with just what we need
    data <- data.frame()

    data <- df[columnName]
    data$month <- df$month
    data$DateStamp <- df$DateStamp
    # from http://stackoverflow.com/questions/7531868/how-to-rename-a-single-column-in-a-data-frame-in-r
    names(data)[names(data) == columnName] <- 'values'


    # Take any NA and make it 0
    if (flipNA)
      data$values[is.na(data$values)] <- 0

    # Take the column name and create two column names
    meanColumnName <- paste0(columnName,"Mn")
    sdColumnName <- paste0(columnName,"Sd")

    # Create dfs for mean and stddev
    if (summarizationMethod == "mean") {
      workingDF <- ddply(data, .(month), summarise, ValuesMn = mean(values))
      colnames(workingDF)[2] <- meanColumnName
      sdDF <- ddply(data, .(month), summarise, ValuesSD = sd(values))
      colnames(sdDF)[2] <- sdColumnName
      jnDF <- full_join(tempdf, workingDF)
      tempdf <- full_join(jnDF, sdDF)
    } else if (summarizationMethod == "sum") {
      workingDF <- ddply(data, .(month), summarise, ValuesMn = sum(values))
      colnames(workingDF)[2] <- meanColumnName
      jnDF <- full_join(tempdf, workingDF)
      tempdf <- jnDF
    } else {
      print("uhoh")
    }
  }

  return(tempdf)
}