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Author: seankross

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+.DS_Store

README.md

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-# Developing_Data_Products
+# Developing Data Products
+
 Developing Data Products Course from the Johns Hopkins Data Science Lab
+
+Course Site: http://datasciencespecialization.github.io/Developing_Data_Products
+
+### Contributors
+
+* Brian Caffo
+* Jeff Leek
+* Roger Peng
+* Sean Kross
+
+### License
+
+<a rel="license" href="http://creativecommons.org/licenses/by-nc-sa/4.0/"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by-nc-sa/4.0/88x31.png" /></a><br />This work is licensed under a <a rel="license" href="http://creativecommons.org/licenses/by-nc-sa/4.0/">Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License</a>.
+
+### Building this Site
+
+1. `cd` to this repository.
+2. `Rscript build.R`
+
+`Rscript build.R clean` to start from scratch.

RPackages/example.R

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+#' Building a Model with Top Ten Features
+#' 
+#' This function develops a prediction algorithm based on the top 10 features
+#' in 'x' that are most predictive of 'y'.
+#' 
+#' @param x a n x p matrix of n observations and p predictors
+#' @param y a vector of length n representing the response
+#' @return a 'lm' object representing the linear model with the top 10 predictors
+#' @author Roger Peng
+#' @details
+#' This function runs a univariate regression of y on each predictor in x and
+#' calculates the p-value indicating the significance of the association. The
+#' final set of 10 predictors is the taken from the 10 smallest p-values.
+#' @seealso \code{lm}
+#' @import stats
+#' @export
+
+topten <- function(x, y) {
+        p <- ncol(x)
+        if(p < 10)
+                stop("there are less than 10 predictors")
+        pvalues <- numeric(p)
+        for(i in seq_len(p)) {
+                fit <- lm(y ~ x[, i])
+                summ <- summary(fit)
+                pvalues[i] <- summ$coefficients[2, 4]
+        }
+        ord <- order(pvalues)
+        x10 <- x[, ord]
+        fit <- lm(y ~ x10)
+        coef(fit)
+}
+
+#' Prediction with Top Ten Features
+#' 
+#' This function takes a set coefficients produced by the \code{topten}
+#' function and makes a prediction for each of the values provided in the
+#' input 'X' matrix.
+#' 
+#' @param X a n x 10 matrix containing n observations
+#' @param b a vector of coefficients obtained from the \code{topten} function
+#' @return a numeric vector containing the predicted values
+
+predict10 <- function(X, b) {
+        X <- cbind(1, X)
+        drop(X %*% b)
+}

RPackages/rpackages.Rmd

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+---
+title       : Building R Packages
+author      : Roger D. Peng, Professor of Biostatistics
+output:
+  ioslides_presentation:
+    logo: ../../img/bloomberg_shield.png
+  beamer_presentation: default
+always_allow_html: yes
+---
+
+## What is an R Package?
+
+- A mechanism for extending the basic functionality of R
+- A collection of R functions, or other (data) objects
+- Organized in a systematic fashion to provide a minimal amount of consistency
+- Written by users/developers everywhere
+
+
+
+## Where are These R Packages?
+
+- Primarily available from CRAN and Bioconductor
+
+- Also available from GitHub, Bitbucket, Gitorious, etc. (and elsewhere)
+
+- Packages from CRAN/Bioconductor can be installed with `install.packages()`
+
+- Packages from GitHub can be installed using `install_github()` from
+  the <b>devtools</b> package
+
+You do not have to put a package on a central repository, but doing so
+makes it easier for others to install your package.
+
+
+
+## What's the Point?
+
+- "Why not just make some code available?"
+- Documentation / vignettes
+- Centralized resources like CRAN
+- Minimal standards for reliability and robustness
+- Maintainability / extension
+- Interface definition / clear API
+- Users know that it will at least load properly
+
+
+
+## Package Development Process
+
+- Write some code in an R script file (.R)
+- Want to make code available to others
+- Incorporate R script file into R package structure
+- Write documentation for user functions
+- Include some other material (examples, demos, datasets, tutorials)
+- Package it up!
+
+
+
+## Package Development Process
+
+- Submit package to CRAN or Bioconductor
+- Push source code repository to GitHub or other source code sharing web site
+- People find all kinds of problems with your code
+  - Scenario #1: They tell you about those problems and expect you to fix it
+  - Scenario #2: They fix the problem for you and show you the changes
+- You incorporate the changes and release a new version
+
+
+
+## R Package Essentials
+
+- An R package is started by creating a directory with the name of the R package
+- A DESCRIPTION file which has info about the package
+- R code! (in the R/ sub-directory)
+- Documentation (in the man/ sub-directory)
+- NAMESPACE
+- Full requirements in Writing R Extensions
+
+
+
+## The DESCRIPTION File
+
+- <b>Package</b>: Name of package (e.g. library(name))
+- <b>Title</b>: Full name of package
+- <b>Description</b>: Longer description of package in one sentence (usually)
+- <b>Version</b>: Version number (usually M.m-p format)
+- <b>Author</b>, <b>Authors@R</b>: Name of the original author(s)
+- <b>Maintainer</b>: Name + email of person who fixes problems
+- <b>License</b>: License for the source code
+
+
+
+## The DESCRIPTION File
+
+These fields are optional but commonly used
+
+- <b>Depends</b>: R packages that your package depends on
+- <b>Suggests</b>: Optional R packages that users may want to have installed
+- <b>Date</b>: Release date in YYYY-MM-DD format
+- <b>URL</b>: Package home page
+- <b>Other</b> fields can be added
+
+
+
+## DESCRIPTION File: `gpclib`
+
+<b>Package</b>:  gpclib<br />
+<b>Title</b>:  General Polygon Clipping Library for R<br />
+<b>Description</b>:  General polygon clipping routines for R based on Alan Murta's C library.<br />
+<b>Version</b>:  1.5-5<br />
+<b>Author</b>:  Roger D. Peng <[email protected]> with contributions from Duncan Murdoch and Barry Rowlingson; GPC library by Alan Murta<br />
+<b>Maintainer</b>:  Roger D. Peng <[email protected]><br />
+<b>License</b>:  file LICENSE<br />
+<b>Depends</b>:  R (>= 2.14.0), methods<br />
+<b>Imports</b>:  graphics<br />
+<b>Date</b>:  2013-04-01<br />
+<b>URL</b>:  http://www.cs.man.ac.uk/~toby/gpc/, http://github.com/rdpeng/gpclib
+
+
+
+## R Code
+
+- Copy R code into the R/ sub-directory
+- There can be any number of files in this directory
+- Usually separate out files into logical groups
+- Code for all functions should be included here and not anywhere else in the package
+
+
+
+## The NAMESPACE File
+
+- Used to indicate which functions are <b>exported</b>
+- Exported functions can be called by the user and are considered the public API
+- Non-exported functions cannot be called directly by the user (but the code can be viewed)
+- Hides implementation details from users and makes a cleaner package interface
+
+
+
+## The NAMESPACE File
+
+- You can also indicate what functions you <b>import</b> from other packages
+- This allows for your package to use other packages without making other packages visible to the user
+- Importing a function loads the package but does not attach it to the search list
+
+
+
+## The NAMESPACE File
+
+Key directives
+
+- export("\<function>") 
+- import("\<package>")
+- importFrom("\<package>", "\<function>")
+
+Also important
+
+- exportClasses("\<class>")
+- exportMethods("\<generic>")
+
+
+
+## NAMESPACE File: `mvtsplot` package
+
+```r
+export("mvtsplot")
+import(splines)
+import(RColorBrewer)
+importFrom("grDevices", "colorRampPalette", "gray")
+importFrom("graphics", "abline", "axis", "box", "image", 
+           "layout", "lines", "par", "plot", "points", 
+           "segments", "strwidth", "text", "Axis")
+importFrom("stats", "complete.cases", "lm", "na.exclude", 
+           "predict", "quantile")
+```
+
+
+
+## NAMESPACE File: `gpclib` package
+
+```r
+export("read.polyfile", "write.polyfile")
+
+importFrom(graphics, plot)
+
+exportClasses("gpc.poly", "gpc.poly.nohole")
+
+exportMethods("show", "get.bbox", "plot", "intersect", "union", 
+              "setdiff", "[", "append.poly", "scale.poly", 
+              "area.poly", "get.pts", "coerce", "tristrip", 
+              "triangulate")
+```
+
+
+
+## Documentation
+
+- Documentation files (.Rd) placed in man/ sub-directory
+- Written in a specific markup language
+- Required for every exported function
+  - Another reason to limit exported functions
+- You can document other things like concepts, package overview
+
+
+
+## Help File Example: `line` Function
+
+```
+\name{line}
+\alias{line}
+\alias{residuals.tukeyline}
+\title{Robust Line Fitting}
+\description{
+  Fit a line robustly as recommended in \emph{Exploratory Data Analysis}.
+}
+```
+
+
+
+## Help File Example: `line` Function
+
+```
+\usage{
+line(x, y)
+}
+\arguments{
+  \item{x, y}{the arguments can be any way of specifying x-y pairs.  See
+    \code{\link{xy.coords}}.}
+}
+```
+
+
+
+## Help File Example: `line` Function
+
+```
+\details{
+  Cases with missing values are omitted.
+
+  Long vectors are not supported.
+}
+\value{
+  An object of class \code{"tukeyline"}.
+
+  Methods are available for the generic functions \code{coef},
+  \code{residuals}, \code{fitted}, and \code{print}.
+}
+```
+
+
+
+## Help File Example: `line` Function
+
+```
+\references{
+  Tukey, J. W. (1977).
+  \emph{Exploratory Data Analysis},
+  Reading Massachusetts: Addison-Wesley.
+}
+```
+
+
+
+## Building and Checking
+
+- R CMD build is a command-line program that creates a package archive
+  file (`.tar.gz`)
+
+- R CMD check runs a battery of tests on the package
+
+- You can run R CMD build or R CMD check from the command-line using a
+  terminal or command-shell application
+
+- You can also run them from R using the system() function
+
+```r
+system("R CMD build newpackage")
+system("R CMD check newpackage")
+```
+
+
+
+## Checking
+
+- R CMD check runs a battery tests
+- Documentation exists
+- Code can be loaded, no major coding problems or errors
+- Run examples in documentation
+- Check docs match code
+- All tests must pass to put package on CRAN
+
+
+
+
+## Getting Started
+
+- The `package.skeleton()` function in the utils package creates a "skeleton" R package
+- Directory structure (R/, man/), DESCRIPTION file, NAMESPACE file, documentation files
+- If there are functions visible in your workspace, it writes R code files to the R/ directory
+- Documentation stubs are created in man/
+- You need to fill in the rest!
+
+
+
+## Summary
+
+- R packages provide a systematic way to make R code available to others
+- Standards ensure that packages have a minimal amount of documentation and robustness
+- Obtained from CRAN, Bioconductor, Github, etc.
+
+
+
+## Summary
+
+- Create a new directory with R/ and man/ sub-directories (or just use package.skeleton())
+- Write a DESCRIPTION file
+- Copy R code into the R/ sub-directory
+- Write documentation files in man/ sub-directory
+- Write a NAMESPACE file with exports/imports
+- Build and check
+