Recent & Upcoming Events

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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!


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.


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!


Recent Blog Posts

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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:


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.


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.


Code of conduct

The leadership, mentoring & teaching roles within this Community are held exclusively by minority genders (majority gender speakers may be allowed/invited as one-off guests in exceptional circumstances at the leadership team’s discretion). Due to unexpected demand, we have opened learning participation to all genders, dependent on initial and on-going vetting by the leadership team. However, the stated priority of the R-Ladies communities is the development & support specifically of those identifying as a minority gender, and we, therefore, reserve the right to guard this interest through whatever measures the leadership team deems appropriate. Anyone involved with R-Ladies Baltimore is expected to fully respect each other, the mandate of this community, and the goodwill on which R-Ladies is founded, or face expulsion/a penalty of any form, at the discretion of the leadership team.

Full community guidelines are found here: rladies/starter-kit/wiki.

Photos, Films and all other media/recordings:

Photos, Films, and all other media/recordings: photographs and/or video/other media will be taken at events held by this community. By taking part in an R-Ladies Baltimore event you grant the community organizers full rights to use the images resulting from the photography/video filming/media, and any reproductions or adaptations of the images for publicity, fundraising or other purposes to help achieve the community’s aims. This might include (but is not limited to), the right to use them in their printed and online publicity, social media, press releases and funding applications. If you do not wish to be recorded in these media please inform a community organizer.


Meet our leadership team

Stephanie Hicks

Stephanie is an Assistant Professor at Johns Hopkins Bloomberg School of Public Health and a faculty member of the Johns Hopkins Data Science Lab in Baltimore, MD. Previously, she was a postdoctoral research fellow at Dana-Farber Cancer Institute and Harvard T.H. Chan School of Public Health in Boston, MA. She is all about data science education, genomics and statistics using R! Her vision for R-Ladies Baltimore is to create a community for individuals to learn and contribute to the R community, while increasing gender diversity. She holds a Bachelor’s degree in Mathematics from Louisiana State University and a M.A. and Ph.D. in Statistics from Rice University.

Margaret Taub

Margaret is an Assistant Scientist in the Biostatistics Department at Johns Hopkins Bloomberg School of Public Health . Previously, she was a Postdoctoral Fellow in the same department. She received her BA in Mathematics from Harvard University and her PhD in Statistics from the University of California, Berkeley. Her research interests are mainly in statistical genetics and genomics and she also teaches a large undergraduate course in Biostatistics. She tries to convert new users to R whenever possible and loves teaching brand new programmers how powerful a programming language like R can be.

Rachel Workman

Rachel received her BS in Biology from WV State, with a thesis project focusing on parasite systematics, and her MS from Portland State, studying invasive plant ecology and plant-fungal interactions. She is currently a PhD student in the Biochemistry, Cellular and Molecular Biology program at Johns Hopkins School of Medicine. When not doing research or homework she is probably playing with her dogs.

Gabriela de Queiroz

Gabriela is the founder of the global organization R-Ladies. She is a Senior Developer Advocate at IBM where she democratizes AI by building tools, launching new open source projects, and improving existing core open source frameworks. She likes to mentor and shares her knowledge through mentorship programs, tutorials and talks. She holds 2 Master’s: one in Epidemiology and one in Statistics.