R/importLimeSurveyData.R

Defines functions importLimeSurveyData

Documented in importLimeSurveyData

#' importLimeSurveyData
#' 
#' This function can be used to import files exported by LimeSurvey, a powerful
#' Open Source online survey application that can be used for, for example,
#' psychological experiments and other research.
#' 
#' This function was intended to make importing data from LimeSurvey a bit
#' easier. The default settings used by LimeSurvey are not always convenient,
#' and this function provides a bit more control.
#' 
#' @param datafile The path and filename of the file containing the data (comma
#' separated values).
#' @param dataPath,datafileRegEx Path containing datafiles: this can be used to
#' read multiple datafiles, if the data is split between those. This is useful
#' when downloading the entire datafile isn't possible because of server
#' restrictions, for example when the processing time for the script in
#' LimeSurvey that generates the datafiles is limited. In that case, the data
#' can be downloaded in portions, and specifying a path here enables reading
#' all datafiles in one go. Use the regular expression to indicate which files
#' in the path should be read.
#' @param scriptfile The path and filename of the file containing the R script
#' to import the data.
#' @param limeSurveyRegEx.varNames The regular expression used to extract the
#' variable names from the script file. The first regex expression (i.e. the
#' first expression between parentheses) will be extracted as variable name.
#' @param limeSurveyRegEx.toChar The regular expression to detect the lines in
#' the import script where variables are converted to the character type.
#' @param limeSurveyRegEx.varLabels The regular expression used to detect the
#' lines in the import script where variable labels are set.
#' @param limeSurveyRegEx.toFactor The regular expression used to detect the
#' lines in the import script where vectors are converted to factors.
#' @param limeSurveyRegEx.varNameSanitizing A list of regular expression
#' patterns and their replacements to sanitize the variable names (e.g. replace
#' hashes/pound signs ('#') by something that is not considered the comment
#' symbol by R).
#' @param setVarNames,setLabels,convertToCharacter,convertToFactor Whether to
#' set variable names or labels, or convert to character or factor, using the
#' code isolated using the specified regular expression.
#' @param categoricalQuestions Which variables (specified using LimeSurvey
#' variable names) are considered categorical questions; for these, the script
#' to convert the variables to factors, as extracted from the LimeSurvey import
#' file, is applied.
#' @param massConvertToNumeric Whether to convert all variables to numeric
#' using \code{\link{massConvertToNumeric}}.
#' @param dataHasVarNames Whether the variable names are included as header
#' (first line) in the comma separated values file (data file).
#' @param encoding,dataEncoding,scriptEncoding The encoding of the files;
#' \code{encoding} overrides \code{dataEncoding} and \code{scriptEncoding}, and
#' so can be used to specify the same encoding for both.
#' @return The dataframe.
#' @author Gjalt-Jorn Peters
#' 
#' Maintainer: Gjalt-Jorn Peters <[email protected]@userfriendlyscience.com>
#' @seealso \code{\link{getData}}
#' @keywords utility
#' @examples
#' 
#' \dontrun{
#' ### Of course, you need valid LimeSurvey files. This is an example of
#' ### what you'd do if you have them, assuming you specified that path
#' ### containing the data in 'dataPath', the name of the datafile in
#' ### 'dataFileName', the name of the script file in 'dataLoadScriptName',
#' ### and that you only want variables 'informedConsent', 'gender', 'hasJob',
#' ### 'currentEducation', 'prevEducation', and 'country' to be converted to
#' ### factors.
#' dat <- importLimeSurveyData(datafile = file.path(dataPath, dataFileName),
#'                             scriptfile = file.path(dataPath, dataLoadScriptName),
#'                             categoricalQuestions = c('informedConsent',
#'                                                      'gender',
#'                                                      'hasJob',
#'                                                      'currentEducation',
#'                                                      'prevEducation',
#'                                                      'country'));
#' }
#' 
#' @export importLimeSurveyData
importLimeSurveyData <- function(datafile = NULL,
                                 dataPath = NULL,
                                 datafileRegEx = NULL,
                                 scriptfile = NULL,
                                 limeSurveyRegEx.varNames =
                                   "names\\(data\\)\\[\\d*\\] <- ",
                                 limeSurveyRegEx.toChar =
                                   "data\\[, \\d*\\] <- as.character\\(data\\[, \\d*\\]\\)",
                                 limeSurveyRegEx.varLabels =
                                   "attributes\\(data\\)\\$variable.labels\\[\\d*\\] <- \".*\"",
                                 limeSurveyRegEx.toFactor =
                                   paste0("data\\[, \\d*\\] <- factor\\(data\\[, \\d*\\], ",
                                          "levels=c\\(.*\\),.*labels=c\\(.*\\)\\)"),
                                 limeSurveyRegEx.varNameSanitizing =
                                   list(list(pattern = "#", replacement = "."),
                                        list(pattern = "\\$", replacement = ".")),
                                 setVarNames = TRUE,
                                 setLabels = TRUE,
                                 convertToCharacter = FALSE,
                                 convertToFactor = FALSE,
                                 categoricalQuestions = NULL,
                                 massConvertToNumeric = TRUE,
                                 dataHasVarNames = TRUE,
                                 encoding=NULL,
                                 dataEncoding='unknown', #'UTF-8',
                                 scriptEncoding='ASCII') {
  
  if (!is.null(encoding)) {
    dataEncoding <- scriptEncoding <- encoding;
  }

  ### Set filename(s) to read
  if (!is.null(dataPath) && !is.null(datafileRegEx)) {
    files <- unique(list.files(path = dataPath,
                               pattern = datafileRegEx,
                               ignore.case = TRUE,
                               recursive=TRUE,
                               full.names=TRUE));
    
  } else if (!is.null(datafile)) {
    if (!file.exists(datafile)) {
      stop("File specified as datafile ('", datafile, "') does not exist!");
    } else {
      files <- datafile;
    }
  } else {
    stop("Please specify a datafile to read, or a datafileRegEx to read multiple datafiles!");
  }
  
  ### Load datafile(s)
  data <- NULL;
  for (currentDatafile in files) {
    if (dataHasVarNames) {
      currentData <- getData(currentDatafile, quote = "'\"", na.strings=c("", "\"\""),
                             stringsAsFactors=FALSE, encoding=dataEncoding, header=TRUE);
    } else {
      currentData <- getData(currentDatafile, quote = "'\"", na.strings=c("", "\"\""),
                             stringsAsFactors=FALSE, encoding=dataEncoding, header=FALSE);
    }
    if (is.null(data)) {
      data <- currentData;
    } else {
      data <- rbind(data, currentData);
    }
  }

  ### Load scriptfile
  if (!is.null(scriptfile)) {
    if (!file.exists(scriptfile)) {
      stop("File specified as scriptfile ('", scriptfile, "') does not exist!");
    }
    ### Use separate connection to make sure proper encoding is selected
    con <- file(scriptfile, encoding=scriptEncoding)
    datascript <- readLines(con);
    close(con);
    varNamesScript <- datascript[grepl(limeSurveyRegEx.varNames,
                                       datascript)];
    varLabelsScript <- datascript[grepl(limeSurveyRegEx.varLabels,
                                        datascript)];
    toCharScript <- datascript[grepl(limeSurveyRegEx.toChar,
                                     datascript)];
    toFactorScript <- datascript[grepl(limeSurveyRegEx.toFactor,
                                       datascript)];
    
    if (setVarNames) {
      eval(parse(text=varNamesScript));
    }
    if (setLabels) {
      eval(parse(text=varLabelsScript));
    }
    if (convertToCharacter) {
      eval(parse(text=toCharScript));
    }
    if (convertToFactor || (!is.null(categoricalQuestions))) {
      if (massConvertToNumeric) {
        data <- massConvertToNumeric(data);
      }
      if (!is.null(categoricalQuestions)) {
        if (setVarNames) {
          varNames <- names(data);
        } else {
          stop("You can't set setVarNames to FALSE and also set ",
               "categoricalQuestions to anything else than NULL, ",
               "because the content of categoricalQuestions should ",
               "be the LimeSurvey variables names!");
        }
        toFactorScript <- unlist(lapply(as.list(categoricalQuestions),
                                        function(x, string=toFactorScript,
                                                 varNms=varNames) {
                                          return(grep(paste0("data\\[, ",
                                                             which(varNms==x),
                                                             "\\] <-"),
                                                      string, value=TRUE));
                                        }));
      }
      eval(parse(text=toFactorScript));
    }
  } else {
    if (massConvertToNumeric) {
      data <- massConvertToNumeric(data);
    }
  }
  if (length(limeSurveyRegEx.varNameSanitizing)) {
    for (currentRegexPair in limeSurveyRegEx.varNameSanitizing) {
      names(data) <- gsub(currentRegexPair$pattern,
                          currentRegexPair$replacement,
                          names(data));
    }
  }

  return(data);
}

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userfriendlyscience documentation built on Sept. 25, 2018, 9:05 a.m.