Spelling errors

ChangeLog

@@ -1,5 +1,5 @@
 2017-11-06  George G. Vega Yon <[email protected]>
-	* Solving CRAN comments.
+	* Solving CRAN comments. And a bunch of misspelled words.
 
 
 2017-11-05  George G. Vega Yon <[email protected]>

NEWS.md

@@ -46,7 +46,7 @@
 
 *   The encoding issue is definetly solved (on utf8).
 
-*   Avoiding unnecesary warings while assigning geo:location attributes.
+*   Avoiding unnecessary warings while assigning geo:location attributes.
 
 *   Fixing some bugs when checking for duplicated concepts
 

R/dspl.r

@@ -34,17 +34,17 @@
 #' bundle with a more complete concepts definition including description, url,
 #' etc..
 #' 
-#' If there isn't any output defiend (\code{NA}) the function returns a
+#' If there isn't any output defined (\code{NA}) the function returns a
 #' dataframe containing concepts as observations. Using this, the user may add
-#' more descripting info about concepts. In turn it writes a tab file with the
+#' more descriptive info about concepts. In turn it writes a tab file with the
 #' dataframe described above. The user may recycle this file writing ``append''
 #' in the \code{action} argument.
 #' 
 #' @param path String. Path to the folder where the tables are saved.
-#' @param encoding The enconding of the files to be parsed.
+#' @param encoding The encoding of the files to be parsed.
 #' @param sep The separation character of the tables in the 'path' folder.
 #' Currently supports introducing the following arguments: ``,'' or ``;'' (for
-#' .csv files), ``\\t'' (for .tab files) and ``xls'' or ``xlsx'' (for microsofts
+#' .csv files), ``\\t'' (for .tab files) and ``xls'' or ``xlsx'' (for Microsoft's
 #' excel files).
 #' @param output If defined, the place where to save the dataframe as tab file.
 #' Otherwise it returns a data frame object.
@@ -54,11 +54,11 @@
 #' @return If no \code{output} defined, \code{genMoreInfo} returns a dataframe
 #' with the following columns.  \item{id}{XML id of the concept
 #' (autogenerated)} \item{label}{The label of the concept (autogenerated)}
-#' \item{description}{A breif description of the concept} \item{topic}{The
+#' \item{description}{A brief description of the concept} \item{topic}{The
 #' topic of the concept} \item{url}{A URL for the concept where, for example,
-#' to get more info} \item{totalName}{A total name as specified by DSPL languge
-#' (works for dimentional concepts)} \item{pluralName}{A total name as
-#' specified by DSPL language (works for dimentional concepts)}
+#' to get more info} \item{totalName}{A total name as specified by DSPL language
+#' (works for dimensional concepts)} \item{pluralName}{A total name as
+#' specified by DSPL language (works for dimensional concepts)}
 #' @author George G. Vega Yon 
 #' @references Google Public Data Explorer: \url{http://publicdata.google.com}
 #' @keywords IO
@@ -572,7 +572,7 @@ seekTables <- function(files, encoding, sep, output = NA, replace = T, dec) {
 #' If there isn't any output defined the function returns a list of class
 #' \code{dspl} that among its contents has a xml object (DSPL file); otherwise,
 #' if an output is defined, the results consists on two things, an already ZIP
-#' file containing a all the necesary to be uploaded at
+#' file containing a all the necessary to be uploaded at
 #' \url{publicdata.google.com} (a collection of csv files and the XML DSPL
 #' written file) and a message (character object).
 #' 
@@ -582,19 +582,19 @@ seekTables <- function(files, encoding, sep, output = NA, replace = T, dec) {
 #' \item Generating each column corresponding id, 
 #' \item Identifying the data types, 
 #' \item Building concepts, 
-#' \item Identifying dimentional concepts and distinguishing between categorical,
-#' geographical and time dimentions, and
+#' \item Identifying dimensional concepts and distinguishing between categorical,
+#' geographical and time dimensions, and
 #' \item Executing internal checks.
 #' }
 #' 
 #' In order to properly load the zip file (DSPL file plus CSV data files), the
 #' function executes a series of internal checks upon the data structure. The
 #' detailed list:
 #' \itemize{
-#' \item \strong{Slices with the same dimentions}: DSPL
-#' requires that each slice represents one dimentional cut, this is, there
-#' shouldn't be more than one data table with the same dimensions.
-#' \item \strong{Duplicated concetps}: As a result of multiple data types, e.g a single
+#' \item \strong{Slices with the same dimensions}: DSPL
+#' requires that each slice represents one dimensional cut, this is, there
+#' should not be more than one data table with the same dimensions.
+#' \item \strong{Duplicated concepts}: As a result of multiple data types, e.g a single
 #' concept (statistic) as integer in one table and float in other, \code{dspl}
 #' may get confused, so during the parsing process, if there is a chance, it
 #' collapses duplicated concepts into only one concept and assigns it the
@@ -627,11 +627,11 @@ seekTables <- function(files, encoding, sep, output = NA, replace = T, dec) {
 #' @param providerURL List of strings. The data provider website url.
 #' @param sep The separation character of the tables in the 'path' folder.
 #' Currently supports introducing the following arguments: ``,'' or ``;'' (for
-#' .csv files), ``\\t'' (for .tab files) and ``xls'' or ``xlsx'' (for microsofts
+#' .csv files), ``\\t'' (for .tab files) and ``xls'' or ``xlsx'' (for Microsoft's
 #' excel files).
 #' @param dec String. Decimal point.
 #' @param encoding The char encoding of the input tables. Currently ignored for
-#' microsoft excel files.
+#' Microsoft excel files.
 #' @param moreinfo A special tab file generated by the function
 #' \code{\link{genMoreInfo}} that contains a dataframe of the dataset concepts
 #' with more specifications such as description, topic, url, etc.
@@ -642,10 +642,10 @@ seekTables <- function(files, encoding, sep, output = NA, replace = T, dec) {
 #' \item{dspl}{A character string containing the DSPL XML document as defined
 #' by the \code{\link[XML:saveXML]{saveXML}} function.} 
 #' \item{concepts.by.table}{A data frame object of concepts stored by table.} 
-#' \item{dimtabs}{A data frame containing dimentional tables.} 
+#' \item{dimtabs}{A data frame containing dimensional tables.} 
 #' \item{slices}{A data frame of slices.} 
 #' \item{concepts}{A data frame of concepts (all of them).}
-#' \item{dimentions}{A data frame of dimentional concepts.}
+#' \item{dimensions}{A data frame of dimensional concepts.}
 #' \item{statistics}{A matrix of statistics.}
 #' 
 #' otherwise the function will build a ZIP file as specified in the output
@@ -858,7 +858,7 @@ dspl <- function(
       NROW(.dims)
     ), ncol=3)
 
-  colnames(pde.statistics) <- c('slices','concepts','dimentions')
+  colnames(pde.statistics) <- c('slices','concepts','dimensions')
 
   result <- structure(
     .Data=
@@ -867,7 +867,7 @@ dspl <- function(
         .dims, pde.statistics
         ),
     .Names = c(
-      'dspl', 'concepts.by.table', 'dimtabs', 'slices', 'concepts', 'dimentions',
+      'dspl', 'concepts.by.table', 'dimtabs', 'slices', 'concepts', 'dimensions',
       'statistics'),
     class = "dspl"
     )

R/googlepublicdata.r

@@ -6,7 +6,7 @@ NULL
 #' World countries example data set
 #' 
 #' This data set is one used in the DSPL Tutorial. Specifically, it contains
-#' the basic columns used to define geographical dimentions, in this case,
+#' the basic columns used to define geographical dimensions, in this case,
 #' countries.
 #' 
 #' 
@@ -51,7 +51,7 @@ NULL
 #' @param path String. Output path where to save the XML DSPL file.
 #' @param replace Logical. If \code{path} exists, \code{TRUE} would replace the
 #' file.
-#' @param quiet Whether or not to print infor on the screen
+#' @param quiet Whether or not to print information on the screen
 #' @param \dots arguments passed on to \code{\link{cat}} (\code{print.dspl})
 #' @return \item{list("print.dspl")}{ None (invisible \code{NULL}).}
 #' 
@@ -103,7 +103,7 @@ NULL
 #' Genders example data set
 #' 
 #' This data set is one used in the DSPL Tutorial. Specifically, it contains
-#' the basic columns used to define a categorical dimentions such as gender.
+#' the basic columns used to define a categorical dimensions such as gender.
 #' 
 #' 
 #' @name genders
@@ -122,7 +122,7 @@ NULL
 #' 
 #' \code{googlePublicData} package provides a collection of functions to set up
 #' Google Public Data Explorer data visualization tool with your own data,
-#' building automaticaly the corresponding DSPL (XML) metadata file jointly
+#' building automatically the corresponding DSPL (XML) metadata file jointly
 #' with the CSV files. All zipped up and ready to be published at Public Data
 #' Explorer.
 #' 
@@ -182,8 +182,8 @@ NULL
 #' US states example data set
 #' 
 #' This data set is one used in the DSPL Tutorial. Specifically, it contains
-#' the basic columns used to define geographical dimentions, in this case, US
-#' Satates.
+#' the basic columns used to define geographical dimensions, in this case, US
+#' States.
 #' 
 #' 
 #' @name states

R/jodatimes.r

@@ -24,7 +24,7 @@ colnames(.joda.times) <- c('regex','format','example')
 #' DSPL language.
 #' 
 #' Public Data Explorer currently supports daily, monthly and yearly
-#' distributed data. Joda-time, the corresponding time format on wich DSPL
+#' distributed data. Joda-time, the corresponding time format on which DSPL
 #' times is based, allows declaring time formats using small case "d" (for
 #' days), capitalized "M" (for months) and small case "y" for years. Some
 #' examples: \tabular{ll}{ Format Specification \tab Data Example\cr "yyyy"

R/pdemethods.r

@@ -42,5 +42,5 @@ summary.dspl <- function(object, ...) {
   print(attributes(object))
   cat('Dataset contents\n')
   object[c('dimtabs', 'slices', 'concepts',
-            'dimentions','statistics')]
+            'dimensions','statistics')]
 }

inst/NEWS

@@ -63,7 +63,8 @@ DEVELOPMENT
 
 -   The encoding issue is definetly solved (on utf8).
 
--   Avoiding unnecesary warings while assigning geo:location attributes.
+-   Avoiding unnecessary warings while assigning
+    geo:location attributes.
 
 -   Fixing some bugs when checking for duplicated concepts
 

readme.md

@@ -9,13 +9,13 @@ Features:
 
 -   Reads tab, csv, xls and xlsx from a folder.
 
--   Identifies data types and distinguishes between dimentional and metric concepts.
+-   Identifies data types and distinguishes between dimensional and metric concepts.
 
--   Identifies dimentional data tabs.
+-   Identifies dimensional data tabs.
 
 -   Auto generates conceps id.
 
--   Auto data sorting on dimentional (no time) concepts.
+-   Auto data sorting on dimensional (no time) concepts.
 
 -   Prints XML and csv files to upload to Public Data Explorer.