Motivation In this tutorial, you are going to create your own package using the usethis workflow R package. For our purposes, we are using the code provide on the usethis website and the blog from Emil Hvitfeldt.
This package is great because it automates repetitive tasks that arise during project setup and development, both for R packages and non-package projects.
Getting started with the usethis package Installation Install the released version of usethis from CRAN:
Come out to our third event in 2019 on May 22nd from 5:30-7pm!
WHO is this for?
If you are new to R & are short-budgeted on time! If you have R code that you want to convert into an R package, but don’t know how! If you want to learn about how others create R packages! If any/all of this is true, this event might be for you!
Motivation: Global Health and Economic Data Throughout this section we will be analyzing global health and economic data. We will be exploring one question:
Is there a relationship between life expectancy and GDP per capita? We will use the data that has been organized and delivered in the gapminder package available in an R package from Jenny Bryan.
To install the gapminder data set
library(devtools) install_github("jennybc/gapminder") Loading data into R library(gapminder) Meet the gapminder data frame or “tibble” By loading the gapminder package, we now have access to a data frame by the same name.
Come out to our second event in 2019 on March 13 from 12-1:20pm!
WHO is this for?
If you are new to R & are short-budgeted on time! If you’d like to start working with data in R without learning all the programming details first!! If you have a neat data set you’d like to explore and visualize! If you are a current R user but only familiar w/ base R!
Come out to our first event in 2019 on January 23 from 5:30-7pm!
We will discuss really useful R packages that can be used to scrape data from the web by walking through some vignettes and tutorials. We plan to focus on rvest. From the CRAN website it says “rvest helps you scrape information from web pages. It is designed to work with magrittr to make it easy to express common web scraping tasks, inspired by libraries like beautifulsoup.
With the holiday season coming up, we want our first R-Ladies Baltimore coding project in R to be get into small groups and create holiday designs in R. Here are a few examples:
Happy Holidays from Rafael Irizarry The main part of the code looks like this:
N <- 120 par(bg="black") h <- rep(c(2:4,7),N/3) h[sample(N,N/5)] <- 0 plot((-2)^as.complex(seq(1,49,len=100)^0.5), pch=21,bg=h,xlab="", ylab="", xaxt="n",yaxt="n", cex=1.5) text(-25,50,"Happy Holidays!",cex=2,col=ifelse(h%%2,"white","black")) Make a Christmas Tree in R with random ornaments/presents # Make the canvas plot(1:10,1:10,xlim=c(-5,5),ylim=c(0,10),type="n",xlab="",ylab="",xaxt="n",yaxt="n") # Make the branches rect(-1,0,1,2,col="tan3",border="tan4",lwd=3) polygon(c(-5,0,5),c(2,4,2),col="palegreen3",border="palegreen4",lwd=3) polygon(c(-4,0,4),c(3.
Come out to our November 14th event to create your own holiday design in R to send to your friends and families this holiday season to hear a great talk!
This meeting will include a group coding event (we’re making holiday cards! :D ) and a presentation from a Christine Zhang (slides available here) who works as a Data Journalist at the Baltimore Sun and Baltimore Sun Data Visualization team to discuss how she uses R in her jobs and examples of projects she works on!