This document captures current best practices for R development, emphasizing modern tidyverse patterns, performance, and style. Last updated: August 2025
| library(ggplot2) | |
| library(dplyr) | |
| library(tidyr) | |
| library(stringr) | |
| library(scales) | |
| library(gridExtra) | |
| library(grid) | |
| # use the NPR story data file --------------------------------------------- | |
| # and be kind to NPR's bandwidth budget |
We start with the imports:
import dicom
import os
import numpy
The
pydicompackage can be installed throughpipand can be found in https://pypi.python.org/pypi/pydicom/
| library("RSiteCatalyst") | |
| library("d3Network") | |
| #### Authentication | |
| SCAuth("key", "secret") | |
| #### Get Pathing data: Single page, then ::anything:: pattern | |
| pathpattern <- c("http://randyzwitch.com/big-data-hadoop-amazon-ec2-cloudera-part-1", "::anything::") | |
| next_page <- QueuePathing("zwitchdev", | |
| "2014-01-01", |
| library(MCMCpack) | |
| ## Coping with polls: the more recent, the better they are. | |
| ##http://en.wikipedia.org/wiki/Opinion_polling_for_the_Scottish_independence_referendum,_2014 | |
| polls = NULL | |
| polls <- data.frame( rbind( | |
| Survation = c(37, 50, 1010), | |
| YouGov = c(35, 55, 1142), | |
| TNSBMRB = c(32, 45, 1003), | |
| IpsosMORI = c(40, 54, 1006), |
| require(ipeds) | |
| require(ggplot2) | |
| require(reshape2) | |
| require(scales) | |
| data(surveys) | |
| View(surveys) | |
| # Directory | |
| ipedsHelp('HD', 2012) |
| library(plyr) | |
| library(ggplot2) | |
| library(ggmap) | |
| libraries = read.csv("ontario_library_stats_2010.csv") | |
| libraries$isFN = ifelse(libraries$Library.Service.Type == "First Nations Library",1,0) | |
| # Here we create the 'proportionate' versions of all the variables | |
| libraries[,143:265] = sapply(libraries[,20:142], function (x) x/libraries[,13]) | |
| names(libraries)[143:265] = paste(names(libraries)[20:142], "P",sep=".") |
| options(PlosApiKey = "<insert your API key here!>") | |
| #install_github("rplos", "ropensci") | |
| library("rplos") | |
| library("ggplot2") | |
| require("dplyr") | |
| # Convert author strings to counts | |
| countAuths <- function(cell) | |
| length(unlist(strsplit(cell, ";"))) |
