going to submit to CRAN

Author: tonyfischetti

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: assertr
 Type: Package
 Title: Assertive Programming for R Analysis Pipelines
-Version: 0.9.7
+Version: 1.0.0
 Authors@R: person("Tony", "Fischetti", email="tony.fischetti@gmail.com",
   role = c("aut", "cre"))
 Maintainer: Tony Fischetti <tony.fischetti@gmail.com>

NAMESPACE

@@ -1,4 +1,4 @@
-# Generated by roxygen2 (4.1.0): do not edit by hand
+# Generated by roxygen2 (4.1.1): do not edit by hand
 
 export(assert)
 export(assert_)

NEWS

@@ -1,3 +1,11 @@
+# assertr 1.0.0
+
+* added row reduction functions like mahalanobis distnace
+
+* added assert_rows and insist_rows assert verbs
+
+* bug fixes
+
 # assertr 0.5.7
 
 * added within_n_mads predicate generator

R/assertr.R

@@ -16,7 +16,7 @@
 #'   \item \code{\link{insist_rows}}
 #'   \item \code{\link{not_na}}
 #'   \item \code{\link{in_set}}
-#'   \item \code{\link{num_rows_NAs}}
+#'   \item \code{\link{num_row_NAs}}
 #'   \item \code{\link{maha_dist}}
 #'   \item \code{\link{within_bounds}}
 #'   \item \code{\link{within_n_sds}}
@@ -26,6 +26,7 @@
 #'
 #' @examples
 #' library(magrittr)     # for the piping operator
+#' library(dplyr)
 #'
 #' # this confirms that
 #'   # - that the dataset contains more than 10 observations

R/row-redux.R

@@ -6,12 +6,12 @@
 #' Computes mahalanobis distance for each row of data frame
 #'
 #' This function will return a vector, with the same length as the number
-#' of rows of the provided data frame, corresponding to the mahalanobis
-#' distances of each row.
+#' of rows of the provided data frame, corresponding to the average
+#' mahalanobis distances of each row from the whole data set.
 #'
-#' This is useful for finding anomalous row-wise observations.
+#' This is useful for finding anomalous observations, row-wise.
 #'
-#' It will convert strings into numerics.
+#' It will convert any categorical variables in the data frame into numerics.
 #'
 #' @param data A data frame
 #' @param keep.NA Ensure that every row with missing data remains NA in

README.md

@@ -12,7 +12,7 @@ The assertr package supplies a suite of functions designed to verify
 assumptions about data early in an analysis pipeline so that
 data errors are spotted early and can be addressed quickly.
 
-This package in no way needs to be used with the magrittr/dplyr piping
+This package does not need to be used with the magrittr/dplyr piping
 mechanism but the examples in this README use them for clarity.
 
 ### Installation
@@ -31,7 +31,7 @@ This package offers five assertion functions, `assert`, `verify`,
 `insist`, `assert_rows`, and `insist_rows`, that are designed to be used
 shortly after data-loading in an analysis pipeline...
 
-Let’s say, for example, that the R’s built-in car dataset, mtcars, was not 
+Let’s say, for example, that the R’s built-in car dataset, `mtcars`, was not 
 built-in but rather procured from an external source that was known for making
 errors in data entry or coding. Pretend we wanted to find the average
 miles per gallon for each number of engine cylinders. We might want to first,
@@ -44,7 +44,7 @@ that is outside 4 standard deviations from its mean, and
 respectively) contain 0s and 1s only
 - each row contains at most 2 NAs
 - each row's mahalanobis distance is within 10 median absolute deviations of
-all the distance (for outlier detection)
+all the distances (for outlier detection)
 
 
 This could be written (in order) using `assertr` like this:
@@ -102,7 +102,8 @@ missing values in each row. Internally, the `assert_rows` function uses
 `dplyr`'s`select` function to extract the columns to test the predicate
 function on.
 
-- `insist_rows` - takes a data frame, a row reduction function, a predicate
+- `insist_rows` - takes a data frame, a row reduction function, a
+predicate-generating
 function, and an arbitrary number of columns to apply the predicate function
 to. The row reduction function is applied to the data frame, and returns a value
 for each row. The predicate-generating function is then applied to the vector
@@ -136,7 +137,7 @@ and `insist_rows`:
 
 - `num_row_NAs` - counts number of missing values in each row
 - `maha_dist` - computes the mahalanobis distance of each row (for outlier
-detection)
+detection). It will coerce categorical variables into numerics if it needs to.
 
 Finally, each assertion function has a counterpart that using standard
 evaluation. The counterpart functions are postfixed by "_" (an underscore).

cran-comments.md

@@ -1,18 +1,19 @@
 ## Test environments
-* local OS X Yosemite 10.10.2 install, R 3.1.3
-* ubuntu (on travis-ci), R 3.1.2
+* local OS X Yosemite 10.10.2 install, R 3.2.1
+* ubuntu (on travis-ci), R 3.2.1
 * win-builder (devel and release)
 
 ## R CMD check results
 
-There were no ERRORs, WARNINGs or NOTEs
-when checked locally with --no-manual
+There were no ERRORs, WARNINGs but 1 NOTE
+when checked locally with --as-cran and --no-manual
 
-I got an email from Uwe.Ligges@R-project.org saying that assertr v0.4
-(which was just accepted into CRAN a few days ago) failed with the
-oldrelease (3.0.3). I was told to either fix or declare a proper version
-dependency.
+The NOTE said:
+    * checking CRAN incoming feasibility ... NOTE
+    Maintainer: 'Tony Fischetti <tony.fischetti@gmail.com>'
 
-I fixed it, slightly incremented the version number and I am submitting it
-here. This is the proper thing to do, right? Please excuse my ignorance, as
-this is my first package.
+    License components with restrictions and base license permitting such:
+      MIT + file LICENSE
+    File 'LICENSE':
+      YEAR: 2015
+      COPYRIGHT HOLDER: Tony Fischetti

inst/doc/assertr.R

@@ -20,3 +20,10 @@ not.empty.p <- function(x) if(x=="") return(FALSE)
 ## ------------------------------------------------------------------------
 seven.digit.p <- function(x) nchar(x)==7
 
+## ----perl=FALSE----------------------------------------------------------
+example.data <- data.frame(x=c(8, 9, 6, 5, 9, 5, 6, 7,
+                             8, 9, 6, 5, 5, 6, 7),
+                         y=c(82, 91, 61, 49, 40, 49, 57,
+                             74, 78, 90, 61, 49, 51, 62, 68))
+(example.data)
+