#' @title process metadata for a given data file
#'
#' @description Generates the following metadata, including:
#' 1) Period of record
#' 2) Number of days with missing data for each parameter
#' 3) Number of days with data flagged as suspect for each parameter
#' 4) Number of days with data flagged as fail for each parameter
#'
#' @details The input is output file of the QC operation in ContDataQC(). That
#' is, a file with Date.Time, and parameters (matching formats in config.R).
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
#' @param fun.myFile Filename (no directory) of data file. Must be CSV file.
#' @param fun.myDir.import Directory for import data.
#' Default is current working directory.
#' @param fun.myDir.export Directory for export data.
#' Default is current working directory.
#' @param fun.myParam.Name Column name in myFile to perform summary statistics.
#' One or two parameters can be specified.
#' @param fun.myDate.Name Column name in myFile for date.
#' Default = "Date.Time".
#' @param fun.myDate.Format Format of DateTime field.
#' Default = \%Y-\%m-\%d.
#' @param fun.myThreshold Value to draw line on plot. For example, a regulatory
#' limit. Default = NA
#' @param fun.myConfig Configuration file to use for this data analysis.
#' The default is always loaded first so only "new" values need to be included.
#' This is the easiest way to control date and time formats.
#' @param df.input a date frame as input if not providing a csv file
#' @return Returns a data frame
#' @examples
#' #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
#' # Save example files from Package to use for example
#' ## This step not needed for users working on their own files
#' df.x <- DATA_period_test2_Aw_20130101_20141231
#' write.csv(df.x,"DATA_period_test2_Aw_20130101_20141231.csv")
#' myFile <- "config.ExcludeFailsFalse.R"
#' file.copy(file.path(path.package("ContDataQC"), "extdata", myFile)
#' , file.path(getwd(), myFile))
#' #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
#'
#' # Load File to use for PeriodStats
#' myDir <- tempdir()
#' myFile <- "DATA_period_test2_AW_20130101_20141231.csv"
#' df.x <- read.csv(file.path(myDir, myFile))
#'
#' # function inputs
#' myFile <- "DATA_period_test2_Aw_20130101_20141231.csv"
#' myDir.import <- tempdir()
#' myParam.Name <- "Water.Temp.C"
#' myDateTime.Name <- "Date.Time"
#' myDateTime.Format <- "%Y-%m-%d %H:%M:%S"
#' myThreshold <- 20
#' myConfig <- ""
#' # Custom Config
#' myConfig.Fail.Include <- "config.ExcludeFailsFalse.R"
#'
#' # Run Function
#' ## Example 1. default report format (html)
#' SumStats.updated(myFile
#' , myDir.import
#' , myParam.Name
#' , myDateTime.Name
#' , myDateTime.Format
#' , myThreshold
#' , myConfig
#' , df.input)
#'
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
#' @export
ReportMetaData <- function(fun.myFile
, fun.myDir.import = getwd()
, fun.myParam.Name
, fun.myDateTime.Name = "Date.Time"
, fun.myDateTime.Format = NA
, fun.myThreshold = NA
, fun.myConfig = ""
, df.input = NULL
)
{##FUN.fun.Stats.START
# 00. Debugging Variables####
boo_DEBUG <- FALSE
if(boo_DEBUG==TRUE) {##IF.boo_DEBUG.START
fun.myFile <- "DATA_test2_Aw_20130101_20141231.csv"
fun.myDir.import <- file.path(".","data-raw")
fun.myParam.Name <- c("Water.Temp.C", "Sensor.Depth.ft")
fun.myDateTime.Name <- "Date.Time"
fun.myDateTime.Format <- NA
fun.myThreshold <- 20
fun.myConfig <- ""
df.input <- NULL
# Load environment
#ContData.env <- new.env(parent = emptyenv()) # in config.R
source(file.path(getwd(),"R","config.R"), local=TRUE)
# might have to load manually
}##IF.boo_DEBUG.END
# 0a.0. Load environment
# config file load, 20170517
if (fun.myConfig!="") {##IF.fun.myConfig.START
config.load(fun.myConfig)
}##IF.fun.myConfig.START
# change the default settings in Environment if needed
# ContData.env$myName.Flag <- "Flag" # flag prefix
# ContData.env$myStats.Fails.Exclude <- TRUE #FALSE #TRUE
# ContData.env$myFlagVal.Fail <- "F"
# 0b.2. Format, DateTime
if (is.na(fun.myDateTime.Format)) {##IF.fun.myConfig.START
fun.myDateTime.Format <- ContData.env$myFormat.DateTime
}
# 2.0. Load File
# load data (data.frame or from CSV)
# if no data frame then import file.
if (!is.null(df.input)) {##IF.START
df.load <- df.input
} else {
# 2.1. Error Checking, make sure file exists
if(fun.myFile %in% list.files(path=fun.myDir.import)==FALSE) {##IF.file.START
#
myMsg <- paste0("Provided file ("
,fun.myFile
,") does not exist in the provided import directory ("
,fun.myDir.import
,").")
stop(myMsg)
#
}##IF.file.END
df.load <- utils::read.csv(file.path(fun.myDir.import, fun.myFile)
,as.is=TRUE,na.strings=c("","NA"))
}##IF.END
# 2.3. Error Checking, data field names
param.len <- length(fun.myParam.Name)
myNames2Match <- c(fun.myParam.Name, fun.myDateTime.Name)
#myNames2Match %in% names(df.load)
if(sum(myNames2Match %in% names(df.load))!= (param.len + 1)){##IF.match.START
# find non match
Names.NonMatch <- myNames2Match[is.na(match(myNames2Match, names(df.load)))]
myMsg <- paste0("Provided data file ("
,fun.myFile
,") does not contain the column name ("
,Names.NonMatch,").")
stop(myMsg)
}##IF.match.END
# 2.4. Error Checking, DateTime format
#df.load[,fun.myDateTime.Name] <- as.Date()
# 2.5. Number of Parameters
# Check for 1 vs. 2 parameters
param.len <- length(fun.myParam.Name)
# Loop, Stats ####
if(boo_DEBUG==TRUE) {##IF.boo_DEBUG.START
i <- fun.myParam.Name[1]
}##IF.boo_DEBUG.END
# 20181114, added for 2nd parameter
df.list <- list()
for (i in fun.myParam.Name){##FOR.i.START
#
i.num <- match(i, fun.myParam.Name)
print(paste0("WORKING on parameter (", i.num,"/",param.len,"); ", i))
utils::flush.console()
myCol <- c(fun.myDateTime.Name, i)
# check NA for each parameter
# Subset Fields
df.param <- df.load[,myCol]
# 3.2. Add "Date" field
fd01 <- ContData.env$myFormat.Date
myDate.Name <- "Date"
df.param[,myDate.Name] <- as.Date(df.param[,fun.myDateTime.Name], fd01)
# 3.3. Data column to numeric
df.param[,i] <- suppressWarnings(as.numeric(df.param[,i]))
df.toCheck <- df.param[,c(myDate.Name,i)]
df.summaryNA <- df.toCheck %>% group_by(Date) %>% summarise(sumNA=sum(is.na(!!rlang::sym(i))))
# check if flag field is in data
# if yes, summarise the fail and suspect data points
# Default values from config.R
# ContData.env$myFlagVal.Fail <- "F"
# ContData.env$myFlagVal.Suspect <- "S"
# ContData.env$myName.Flag <- "Flag" # flag prefix
## If flag parameter names is different from config then it won't be found
myParam.Name.Flag <- paste(ContData.env$myName.Flag, i, sep=".")
# Modify columns to keep based on presence of "flag" field
if (myParam.Name.Flag %in% names(df.load)) {##IF.flagINnames.START
# Flag field present in data
myCol <- c(fun.myDateTime.Name, myParam.Name.Flag)
df.param.flag <- df.load[,myCol]
df.param.flag[,myDate.Name] <- as.Date(df.param.flag[,fun.myDateTime.Name], fd01)
df.toCheck.flag <- df.param.flag[,c(myDate.Name,myParam.Name.Flag)]
# summarise the fail and suspect data points
df.summaryFlag <- df.toCheck.flag %>% group_by(Date) %>% summarise(sumFail=sum(!!rlang::sym(myParam.Name.Flag)==ContData.env$myFlagVal.Fail),
sumSuspect=sum(!!rlang::sym(myParam.Name.Flag)==ContData.env$myFlagVal.Suspect),
sumNoFlagData=sum(!!rlang::sym(myParam.Name.Flag)==ContData.env$myFlagVal.NoData))
} else {
# No Flag column
df.summaryFlag <- data.frame()
myMsg <- "No QC Flag field was found so no summary on flags"
cat(paste0(myMsg, "\n"))
}##IF.flagINnames.END
if (length(df.summaryFlag)>0){
df.summary <- merge(df.summaryNA,df.summaryFlag,by="Date")
}else{
df.summary <- df.summaryNA
}
new.list <- list(df=df.summary)
names(new.list) <- i
df.list <- c(df.list,new.list)
}##FOR.i.END
return(df.list)
}##FUNCTION.END
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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