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R User Group Philippines Turns 10

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The R User Group-Philippines (RUGPH) celebrated its 10th anniversary on the 16th of August. The group marked the occasion with its first physical event since the pandemic, and it highlighted the group’s progress over the past decade. 

The RUG-PH hosted 115 events in the past decade, making it one of the most persistent RUGs. During the pandemic, many RUGs struggled to remain active; however, RUG-PH continued with online events.  

Joe Brillantes and Michelle Alarcon are the two faces behind the group’s success and brilliant track record. The R Consortium recently talked to Joe and Michelle regarding the group’s evolution. They shared their journey with R in their work and their experience keeping the group up and running for a decade. They have also witnessed a growing acceptance of R in the Philippines and the industry. 

Please share about your background and involvement with the RUGS group

Michelle: My name is Michelle Alarcon, and I have been an analytics practitioner since 1999. I used commercially available software at university and brought it with me to the jobs I had. Open source tools were a minor part of my toolkit in practice. In 2013, I founded my analytics consulting firm, Z-Lift Solutions. As a consultant, I aimed to avoid being bound to software vendors that clients might have purchased, such as SAS or SPSS. So, I began searching for a versatile tool that would allow us to offer consultation without being locked into any particular vendor.

That’s when I discovered R, which was unpopular in the Philippines back then. However, R was gaining popularity among practitioners striving to learn analytics without heavy investments. I asked a former classmate from my old school, the University of the Philippines School of Statistics, for advice when I started my consultancy. I wanted to know the tools used by the new generation of statisticians. To my surprise, the curriculum remained largely unchanged over two decades. This realization led me to explore alternatives.

My efforts to ensure a consistent talent pool for consultancy drove me to get connected with Edward Santos, a key figure in the history of the R Users Group. I also connected with Joselito Magadia, a university professor who played a crucial role in the Philippines’ CRAN network. Through Edward and Joselito, I got introduced to the R Users Group. Our annual R Users Group anniversary celebrations often include Edward.

Joe: I’m Joe Brillantes, and I first encountered R in 2007 during my studies in the US. My mathematical statistics instructor introduced me to it. While I initially leaned towards software like MATLAB or Maple, my perspective shifted when I returned to the Philippines. Because of a tight budget, I had to create a portfolio optimization model for a shipping company without using expensive software. R emerged as a more feasible solution.

When I started using R, there wasn’t a community of R Users in the Philippines. Since I was new to it, I asked many questions, mainly to my classmates or other R users in the US. And then, someone started a Google group on R users specific to the Philippines, and that’s when I joined it. It seemed very appealing to me, as I no longer needed to ask people in the US and then wait for them to respond because of the different time zones. 

We did not start the Philippines R Users Group (RUGS); credit goes to Edward Santos. However, I co-organized the group alongside Michelle for the past decade. My commitment to R persisted throughout my career, replacing MATLAB and other software in my toolkit.

Can you share what the R community is like in the Philippines?

Michelle: In the past decade, I’ve witnessed an increasing acceptance of open source programming tools in the Philippines. In 2013, awareness of open source options was scarce. AWS was pivotal in promoting open source use, joined by Java‘s long-standing presence. However, the acquisition of Revolution Analytics by Microsoft was a turning point. Microsoft, on our request, provided us space for hosting our meetups, which were happening at coffee shops before that. Microsoft’s support showcased a shift toward open source.

A decade later, R has gained acceptance as a staple tool for data scientists and analysts, often mentioned alongside Python. Our user group collaborates with other tech communities, like AWS and Python. Interest in R has increased over the years. However, our meetup attendance has plateaued, maintaining a consistent level of participants even during the pandemic when we held virtual events. 

Joe: Today, data science and analytics practitioners in the Philippines typically gravitate toward Python or R. Both languages are considered essential tools. The open source nature of R fosters acceptance within organizations. If an employee is proficient in R, they typically approve its usage due to familiarity. However, an area for further growth is in deploying models. The deployment of predictive and prescriptive analytics models in production remains limited. R is commonly used in data science but not widely in production environments.

You had a Meetup RUG_PH 10th Anniversary. Can you share some details of this event?

R Users Group-Philippines 10th Anniversary Event

Joe:  We recently celebrated the R Users Group – Philippines’ 10th anniversary. We wanted it to be special, so it was also the first time we organized an in-person meetup since the pandemic ended. There were around 20 people who attended, half of whom had attended numerous meetups in the past, while the remaining were first-timers. We were pleasantly surprised that a substantial portion of attendees were first-timers because that indicated that R usage and user groups still have significant growth potential in the Philippines.

Because it’s an anniversary, the primary topic was to review how we’ve grown and changed over the years. Our event venues changed from cafes to company offices to online. Our participants became more diverse in terms of backgrounds and moved from predominantly analysts to a mix of data engineers, data scientists, software engineers, and managers. Participants come from Metro Manila to other areas in the Philippines and even abroad. We had dinner, an icebreaker, a raffle, and networking at the event.

Some participants also volunteered to discuss data visualization for scientific publication and causal inference in future meetups. We will promote these meetups to the community for future events through our Meetup page, Slack workspace, and Facebook page. We’re always happy to see familiar faces and to meet new R users.

Any techniques you recommend using for planning for or during the event? (Github, zoom, other) Can these techniques be used to make your group more inclusive to people that are unable to attend physical events in the future?   

Joe: We encourage presenters to share their materials soon after the meetup. They usually share them through GitHub or shared drives like Google Drive, OneDrive, or Dropbox. We started recording the meetups and plan to share them on our Facebook page. We do these to help attendees continue learning, reach those who couldn’t make it, and encourage future attendance.

We’re still exploring the best way to do hybrid meetups. People attending online usually feel left out in hybrid meetings because of low-quality equipment and lousy internet. Speakers usually select the in-person format as it requires less time and effort than preparing for a hybrid setup. We’re still figuring out the best way to have hybrid meetups that do not isolate online attendees. In the meantime, we ask presenters their preferred format: in-person, online, or hybrid. The voted-out meetup setup would likely be because the presenters are the best people to decide how their content can be best communicated.

I would also like to take this opportunity to reach out to RUGs around the globe. We at the RUG-PH are excited to be part of the global R community through the R Consortium. We look forward to collaborating with other RUGs and welcoming participants from around the globe. 

How do I Join?

R Consortium’s R User Group and Small Conference Support Program (RUGS) provides grants to help R groups around the world organize, share information and support each other. We have given grants over the past four years, encompassing over 65,000 members in 35 countries. We would like to include you! Cash grants and meetup.com accounts are awarded based on the intended use of the funds and the amount of money available to distribute. We are now accepting applications!

First Publicly Available R-Based Submission Package Submitted to FDA (Pilot 3)

By Announcement, Blog

The R Consortium is pleased to announce that on August 28, 2023, the R Submissions Working Group successfully submitted an R-based test submission pilot 3 package through the FDA eCTD gateway! The FDA CDER staff are now able to begin their evaluation process. All submission materials can be found at: https://github.com/RConsortium/submissions-pilot3-adam-to-fda 

The pilot 3 test submission is an example of an all R submission package following eCTD specifications. These include the installation and loading of the proprietary {pilot3} R package and other open-source R packages, R scripts for the analysis data model (ADaM) datasets from pilot 3 and tables, listings, figures (TLFs) from pilot 1, analysis data reviewer’s guide (adrg), and other required eCTD components. To our knowledge, this is the first publicly available R-based FDA submission package, which includes R scripts to generate ADaM datasets and TLFs. We hope this submission package and our learnings can serve as a good reference for future R-based regulatory submissions from different sponsors. Additional agency feedback will be shared in future communications.  For any future questions, you may contact the pilot 3 team here: https://rconsortium.github.io/submissions-pilot3-adam/main/index.html.

The working group also began working on a pilot 4 project to explore the use of novel technologies such as Linux containers and WebAssembly software to bundle a Shiny application into a self-contained package in order to facilitate a smoother process for transferring and executing the application. Stay tuned for more about pilot 4 in the future.

For past announcements on pilot 1 and pilot 2, see below.

Announcement of the R Consortium R submission pilot 1:

Announcement of the R Consortium R submission pilot 2, an R based test submission with a shiny component:

https://www.r-consortium.org/blog/2022/12/07/update-successful-r-based-package-submission-with-shiny-component-to-fda

About the R consortium R submission working group

The R Consortium R Submissions Working Group is focused on improving practices for R-based clinical trial regulatory submissions.

To bring an experimental clinical product to market, electronic submission of data, computer programs, and relevant documentation is required by health authority agencies from different countries. In the past, submissions have been mainly based on the SAS language. 

In recent years, the use of open source languages, especially the R language, has become very popular in the pharmaceutical industry and research institutions. Although the health authorities accept submissions based on open source programming languages, sponsors may be hesitant to conduct submissions using open source languages due to a lack of working examples.

Therefore, the R Consortium R Submissions Working Group aims at providing R-based submission examples and identifying potential gaps during submission of these example packages. All materials, including submission examples and communications, are publicly available on the R consortium Github page: https://github.com/RConsortium.

The R consortium R submission working group includes members from more than 10 pharmaceutical companies, as well as regulatory agencies. More details of the working group can be found at: https://rconsortium.github.io/submissions-wg/.

The R consortium R submission working group is open to anyone who is interested in joining. If interested, please contact Joseph Rickert at joseph.rickert@gmail.com

R Validation Hub’s {riskassessment} Application – Mini Series Part 2

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The R Validation Hub – a working group established within the R Consortium to support the adoption of R within a biopharmaceutical regulatory setting – held a two-part mini-series about their {riskmetric} package and {riskassessment} application. 

The full talk is available here. Part 1 is available here.

In the second part of the mini-series, the team explained in depth how the {riskassessment} application helps those making “package inclusion” requests for GxP environments, which means the application empowers users to assess package risks themselves before making an IT request. It arms them with the criteria they need to show a package meets (or fails to meet) their organization’s unique set of requirements. 

The highlight of the talk was covering upgrades and improvements made to the application. 

Here’s a breakdown of what’s new:

  • Valuable Enhancements: Aesthetic & functional enhancements were made to the ‘Report Builder’ and ‘Database Viewer.’
  • In-depth Analysis: The app now boasts enhanced support for analyzing package dependencies.
  • Tailored Customizations: More organizational-level adjustments, including a configuration file for a bespoke experience.
  • Admin Capabilities: Admin users now have the power to modify roles and privileges. This ensures a seamless workflow by determining who should partake in the review processes.
  • Explore with Ease: A new feature allows users to delve into the source contents of a package through a file browser, making exploration straightforward and comprehensive.

The R Validation Hub team also shared a sneak peek of some exhilarating features, such as {riskscore}; there’s also more in store for package exploration within the app.

A Special Note on GSK’s Contributions

GSK Collaborators have generously contributed code that enhances the user experience. This new feature will enable users to delve deeper into exported functions. Imagine perusing function-level source code, documentation, and tests in one unified and easily navigable user interface. Thanks to GSK, this will soon be a reality!

R Validation Hub’s Risk Metric Application and Risk Score – Mini Series Part 1

By Blog

The R Validation Hub – a working group established within the R Consortium to support the adoption of R within a biopharmaceutical regulatory setting – held a two-part mini-series about their {riskmetric} package and {riskassessment} application. 

The full talk is available here. Part 2 is available here.

In Part 1, the R Validation team talked about defining risk in software quality. Equally important is understanding the intended use of the software. The {riskmetric} package fulfills the crucial need to assess the quality of R packages, ensuring they adhere to the highest standards.

{riskmetric} isn’t just a tool; it’s a comprehensive system. For users, it provides a well-defined workflow and offers insights into the package’s internals, aiding in understanding its functioning better.

Mapping the Future – Roadmap:

The {riskmetric} package is being actively worked on and improved. The major features in the upcoming roadmap include:

  • Ease of Use: The focus is on enhancing user experience. A more intuitive interface coupled with informative messages and functions to generate straightforward reports is on the horizon.
  • Metric Completion: The goal is to provide many metrics from various package metadata sources.
  • Optional Third-party Metric Inclusion: An API that supports metrics reliant on additional packages, giving users a choice to use them.
  • Cohorts: Evaluating the risk associated with a group of packages, treating them as a unified entity.

Metrics aren’t just about numbers; they’re about quality and relevance. In the talk, the team shed light on the guidelines and best practices for proposing or designing package metrics, complemented with examples for clarity.

Introduction of {riskscore} 

The team introduced {riskscore}, a repository that stores the results of riskmetric runs on CRAN. It is envisioned as a community resource with multiple aims:

  • Contextual Scoring: Helping users decipher scores, distinguishing between what’s deemed “good” or “bad.”
  • Benchmarking: Enabling development teams to benchmark scoring weight algorithms with historical results.
  • Trend Analysis: create an interesting dataset for package quality/risks analysis. 

Spatial Data Science Using R in Berlin, Germany

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The Berlin R User Group fosters a diverse and vibrant R community in Berlin. Rafael Camargo shared some insights from his experience regarding the potential of R and some anecdotes for organizers of RUGs. The Berlin RUG is currently looking for sponsors to host their physical events, and companies interested in hosting the group can contact Rafael. 

The group is hosting a physical event using R for spatial data analysis on September 26, 2023.

Rafael is a Spatial Data Scientist working at Quantis as a Sustainability Expert. He has a Bachelor’s in Environmental Studies and a Master’s in Environmental planning.

Please share your background and involvement with the RUGS group.

I was first introduced to R during my Master’s studies in 2016. A Ph.D. student encouraged me to use R for data analysis, and I grew fond of it.

Later, during my Master’s thesis, I used it as well. After completing my Master’s degree, I used to work for WWF, a nature conservation organization. My responsibilities included maintaining a web tool and conducting spatial analysis.

In my job, I noticed repetitive tasks which I found tedious. I started automating tasks and report generation using R Markdown and, later, Quarto to reduce repetition. I am one of the early adopters of Quarto and heavily use it for my work. I work for a consultancy firm, and again, with a strong focus on automating processes. I use Notebooks in my work for documentation and reproducibility. 

Can you share what the R community is like in Berlin? 

The R community in Berlin is very welcoming and has this spirit of helping each other.  I joined the Berlin RUG around the same time I started using R. ‌The group hosted monthly meetings with talks on a diverse range of topics by speakers from industry, academia, and freelancers. Some speakers offered courses in R and used this opportunity to market their courses while giving back to the community. 

Just before COVID hit, there was a shift towards machine learning topics. I think this shift mirrored the industry’s growing interest in machine learning applications. There are more speakers keen to give machine learning-related talks. The audience also grew, and we saw more people joining our meetups who were new to R but eager to learn about machine learning.

Within our group, we see members from diverse backgrounds. For example, small financial institutions use R to optimize interest rates through bank APIs, professionals in biomedicine doing statistics, health insurance exploring spatial analysis, and experts in real estate using R for house price prediction.

Overall, it’s a pleasant mix of academia and applied industry. Companies using machine learning are considering R for industry applications.

You have a Meetup on Spatial Data Science with R: {sf}, {stars}, and other packages. Can you share more on the topic covered? Why this topic? 

I’m particularly excited about our upcoming meetup on Spatial Data Science with R. I’ve been advocating for this topic. We’re fortunate to have Edzer Pebesma, a prominent developer and maintainer of various R packages for spatial analysis. He’ll deliver a talk at the end of September, covering material from his latest book, “Spatial Data Science using R,” and the latest advancements in the field. And, of course, leveraging the packages he has developed over the years.

Any tips you would like to share with other R Users Group Organizers that can be helpful for hosting successful events?   

I can share a few insights from my experience as a RUG organizer. When I joined as a participant, our meetups were hosted at a company-sponsored venue with a dedicated room accommodating up to 50 people. They also generously provided drinks and snacks for the participants. 

After joining the organizing committee, I learned about the company’s flexibility and willingness to accommodate our event requests. We were somewhat reactive,  with potential speakers approaching us with proposed dates, and we coordinated with the company to find a suitable date. I would negotiate with the speaker to ensure the talks were concise, with enough time for discussion. 

Fortunately, the company managed the event logistics, including venue and refreshments, so my role was minimal. However, they stepped down as sponsors last year after COVID-19, and we are actively seeking new sponsors. This has been particularly difficult due to our busy schedules. So, I would recommend organizers be more proactive in reaching out to sponsors and not rely on only one sponsor.

Additionally, I would like to take this opportunity to reach out to any companies in Berlin who can offer us space to host our events. 

Would you like to add anything else for the readers?

In the past 5 years, engaging with several global organizations and multinational corporations, I realized that many organizations outside the research, software development, e-commerce, or marketing domains also rely heavily on data-driven solutions.  However, ‌I see a lack of awareness among organizations about the true potential of R. Many people are surprised to know that R can be used for domains beyond statistics when I talk about my work with R. Many global organizations still rely on manual work using Excel, which is much prone to errors. They are unaware of R’s capabilities and recent developments. I wish more people knew about the user-friendly functionalities of Tidyverse, Posit Connect, and other tools available in R.

Grants For R Language Infrastructure Projects Available Now!

By Announcement, Blog

Round two is here! The R Consortium Infrastructure Steering Committee (ISC) orchestrates two rounds of proposal calls and grant awards per year to fortify the R ecosystem’s technical infrastructure. We have one key goal: to make meaningful infrastructure improvements that serve the R community. 

ISC’s Call for Proposals opens on September 1, 2023. Send in your submission! https://www.r-consortium.org/all-projects/call-for-proposals 

We’re reaching out to the extended R community to tap into your expertise and insights. What areas do you think need attention to extend R’s capabilities? Do you see emerging domains where R could significantly impact? Whether in Climate Science, Engineering, Finance, Medicine, or any other discipline, your ideas could spark innovations that advance the field and broaden the R community. 

Technical Infrastructure projects that have been funded include:

  • R-hub is a centralized tool for checking R packages
  • Testing DBI and improving key open-source database backends.
  • Improvements in packages such as mapview and sf 
  • Improving Translations in R
  • Ongoing infrastructural development for R on Windows and macOS

Social Infrastructure projects include:

  • SatuRDays bootstrapping a system for local R conferences.
  • Data-Driven Discovery and Tracking of R Consortium Activities

The ISC is interested in projects that:

  • Are likely to have a broad impact on the R community.
  • Have a focused scope (a good example is the Simple Features for R project). If you have a larger project, consider breaking it into smaller chunks (a good example is with the DBI/DBItest project submission, where multiple proposals came in overtime to address the various needs).
  • Have a low-to-medium risk with a low-to-medium reward. The ISC tends not to fund high-risk, high-reward projects.

Key Dates for 2023

Second Grant Cycle: September 1 to October 1, acceptance by November 1, contract by December 1.

Review Process

The Chair of the ISC and committee members will review all proposals. Results will be announced as per the schedule above, and all funded projects will feature on the R Consortium blog.

Final Thoughts

Let’s enrich the R landscape, amplifying its utility across various sectors. The time is ripe, and your ideas could be the seeds of transformation. We look forward to your active participation.

Apply now and be part of shaping the future of R! You can read more about ISC Grant Proposal application process here.

Use of R for Pharma in Rosario, Argentina

By Blog

Ivan Millanes from the R en Rosario recently talked to the R-Consortium. He shared the group’s vision to create an inclusive knowledge-sharing platform for a diverse R community in Rosario. In Argentina, the group welcomes participants and speakers at all experience levels. Ivan also uses R at work and builds Shiny applications for the pharmaceutical industry. 

Ivan co-organizes R en Rosario and is one of the group’s founding members. He completed his Bachelor’s in Statistics at the National University of Rosario. Not to mention, Ivan has achieved multiple certifications in Machine Learning. Currently, he works as a R/Shiny developer at Appsilon. 

R en Rosario First Anniversary Celebrations


Please share your background and involvement with the RUGS group.


My educational background is in Mathematics and Statistics. I first used R around six years ago during my studies and have since gained experience in R through different jobs. I have worked in various industries like marketing, healthcare, and insurance. I am currently working in the Pharmaceutical industry. 

R en Rosario Founding Members

We started the R en Rosario User Group a couple of years ago, Argentina’s first R User Group. Later, other cities also started their R Users Groups, e.g., Buenos Aires. We hosted a few virtual meetings during the pandemic but stopped after a few months. Now that everything is returning to normal, we plan to resume our meetings. We would like to host speakers from different industries who use R for their work. A networking session would follow these talks. 

R en Rosario First Meeting

What industry are you currently in? How do you use R in your work?

I currently work in Pharma, where we develop Shiny applications using R.

The applications we develop have a similar workflow: we connect to SQL databases and produce some outputs the business needs in the form of PDFs or Word documents based on user choices for different parameters.

We use the Rhino package from Appsilon to develop the applications, as it provides a great framework for developing high-quality applications. We also use:

One application we developed generates annual reports of different incidents in the laboratory. Before we developed the application, this process was manual and took time. With this app, they have a relatively simple interface where they can select the data they want to see in the report. They can download the reports and also get it sent to their system.

Why do industry professionals come to your user group? What is the benefit for attending?

People from a diverse range of backgrounds attend our meetups. Some government officials use R to analyze traffic data for public services. Some people from the farming industry use R to interpret satellite images to understand crops. 

Even though statisticians founded this group, its purpose is to provide a platform for people from various backgrounds to learn R and use it for their work. We usually have around 20-30 people attending our meetups, and different companies provide space to host our meetups.

Networking is an important part of our meetups, allowing members to learn more about each other. 

We also do not have any limit on the topics for these talks, and anyone who feels like sharing their work in R with the audience can give a talk. So everyone, at any experience level, is more than welcome to give a speech. We are not experts and are not looking for only experts to give talks. The idea is for people from different backgrounds to come together and learn from each other. 

R en Rosario Meeting Hosted by a Company

New Executive Director Position Created at R Consortium

By Announcement, Blog

Motivated by the growth of the R Consortium over the past several years and the expansion of activities, the R Consortium Board of Directors has taken a step to ensure long-term, consistent oversight of day-to-day activities. 

The R Consortium is pleased to announce that Joseph Rickert has been appointed to the position of Executive Director reporting directly to the Board of Directors.

Joseph has been active in the R Community since he joined Revolution Analytics in 2009 and has held prominent, community-facing positions at both the R Consortium and RStudio (now renamed posit). He is deeply involved in multiple R Consortium technical working groups, is an organizer of the Bay Area useR Group (BARUG), and has been on the R/Medicine conference organizing committee since the first conference in 2018. Joseph served on the R Consortium Board of Directors from August 2016 to July 2023, serving as Chair from 2020.

Welcome, Joseph, to your new position!

R-Ladies Morelia, Mexico, hosts First Anniversary Event on July 31, 2023

By Blog, Events

R-Ladies Morelia is celebrating its first anniversary on the 31st of July 2023, and hosting a hybrid event to mark this occasion. In this event, they plan on providing the Center of Mathematical Science at UNAM with an analysis of their recruitment, graduation, and research data. 

Nelly Sélem, co-founder and organizer of the group also discussed the group’s rapid growth over the course of a year. She also shared how she uses R for her work as a bioinformatics researcher.

Please share about your background and involvement with the RUGS group.

I am a professor at the Center for Mathematical Sciences at UNAM in Morelia, Mexico. I earned a degree in Mathematics from the University of Guanajuato and a master’s degree from CIMAT. Then, I did a Ph.D. and a Post-doctorate in Integrative Biology at the Evolution of Metabolic Diversity lab at Langebio-Cinvestav. I care about teaching. I have taught at prestigious México Universities: UNAM, ITESM, IPN, and CINVESTAV. I contributed to the educational community by developing a metagenomics open-source lesson in “The Carpentries Incubator.” I’m a founder member of BetterLab, a biotechnology and software startup, and I’m also a member of the Mexican SARS-CoV-2 Genomic Surveillance Consortium.

As a scientist, I have proposed and developed bioinformatics solutions to biological problems of comparative genomics of microorganisms. I am interested in the genome evolution of Archaea, Bacteria, and Fungi. 

I founded the R Ladies Morelia chapter with Haydee and Claudia last year. We try to organize meetings every month more or less. And this year on our first anniversary we plan to hold a big annual meeting in which we will get to meet more people. 

Can you share what the R community is like in Mexico?

I can only talk about the R Ladies chapters in Mexico, as I am more familiar with them. We have several chapters in Mexico and each year there is an annual meeting for all cities. 

The Mexico City and Cuernavaca chapters are rather big. I would say, overall, there is a lot of interest on social media and members of R-Ladies chapters are inviting other girls to learn to code. 

Our chapter is also growing rapidly as we started with four members and now we have a stable community. On the best days, we have up to 90 people attending our events but on average we have between 12 to 20 attendees. 

Most of the R-Ladies chapters in Mexico are being run by people from academia and sponsored by universities. I do know that some of us work in the area of bioinformatics and Bioconductor. 

We are also close to the international R community because we are following the R Champions program. I think it’s for Latin America and we are trying to get connected with that program.

You have a Meetup on “Graphics for the Center of Mathematical Science,” can you share more on the topic covered? Why this topic? 

For this meetup, which is also our first anniversary, we plan on giving the Center of Mathematical Science, National University of Mexico an evaluation. It would include a comparison of the number of students being graduated each year and the quality standard of researchers against other universities from Mathematics in Mexico and Latin America. The center has sponsored us for the past year, and it is going through the process of becoming a bigger institute. 

With this event, we are trying to give back to the center with data analysis of its basic statistics. The audience will learn to use dataframes and ggplot to visualize data. We will be working in teams to teach basic ggplot visualizations. And on the second day, we will be giving small workshops and sharing our work with each other. All our events are Hybrid so this one is also going to be Hybrid and people will attend both physically and virtually. 

We hope to grow our community through this event and also contribute to the annual report of the Center of Mathematical Sciences. 

Any techniques you recommend using for planning for or during the event? (Github, zoom, other) Can these techniques be used to make your group more inclusive to people that are unable to attend physical events in the future?   

Meetup has been very helpful for keeping everything organized, and we use Zoom for our virtual meetings. We also share code through our GitHub repo and people can go back to it after meetings. For communication between organizers, we mostly use WhatsApp chat. 

At the start of the semester, we plan events for that semester with dates, speakers, and topics to be covered. We work in teams, so we can help each other. Sometimes we go through chapters of a book, or we just go for an R package. We consider ourselves a community of practice. Even if people don’t know a lot, we do some data analysis and share the code on the meeting day.

Please share about a project you are currently working on or have worked on in the past using the R language. Goal/reason, result, anything interesting, especially related to the industry you work in?

I would like to mention MetaEvoMining, a project one of my undergrad students is working on for his thesis. We are trying to treat metagenomic data in order to look for some gene families that are going through expansions. And maybe these expansions conduce to recruitment into antibiotic gene producers. So we are looking for something different in gene families that may be recruited to new antibiotic gene families. This has been researched in genomes but not in metagenomes and there is a lot more data available in metagenomes. We want to develop an R package for this purpose. For the project, we are using Posit (RStudio). We are also using packages like ggplot and RString. We are also using tidyverse in general.

A Memorable Experience: Attending the NYC-R Conference and Key Takeaways

By Blog, Events

This is a guest post by Joseph Korszun, Senior Manager of Data Solutions at ProCogia. ProCogia is a member of the R Consortium. Joe is a data scientist with a background in mathematics and engineering. He is passionate about using statistical analysis to improve business decisions by developing scalable and flexible solutions that solve complex problems.

Introduction

New York City, known for its vibrant energy and thriving tech scene, became the epicenter of data and analytics during the recent NYC-R Conference. As an avid data enthusiast, I couldn’t resist the opportunity to immerse myself in this bustling conference and gain valuable insights into the world of R and Python programming.

I had the pleasure of representing ProCogia and the R-Consortium. The experts who stood before us showcased their deep knowledge and dedication to advancing data science. It was remarkable to see people so passionate about the R programming language and its applications in the field. Throughout the event, they engaged the audience with informative presentations and interactive workshops, sparking insightful discussions among attendees. The positive reception from the crowd highlighted the significance of collaboration and knowledge-sharing in the data science community. I was inspired by their expertise and left the conference with a renewed enthusiasm for data science and the possibilities it offers. The event provided a fantastic opportunity to connect with like-minded professionals and learn from the best in the industry. I am grateful for the experience and eagerly look forward to seeing more contributions in the future. In this blog post, I will share my experiences attending the NYC-R Conference and highlight some key takeaways that left a lasting impression.

Pre-Conference: Workshops at NYC-R

The NYC-R Conference’s workshops promise a thrilling exploration of diverse data science topics using the power of R programming. Attendees will embark on an immersive journey to delve into essential areas of data science, including time series forecasting, machine learning, Bayesian data analysis, and causal inference. Industry experts led these workshops offer a unique opportunity to expand data science expertise and harness the true potential of R in driving data-driven innovations. Some of the below workshops were provided in the first two days of the NYC-R Conference:

  • Tidy Time Series and Forecasting in R by Michell O’Hara-Wild
  • Machine Learning in R by Max Kuhn
  • Bayesian Data Analysis and STAN by Jonah Gabry
  • Causal Inference in R by Malcolm Barrett and Lucky D’Agostino McGowan

Day 1: An Exciting Kickoff

The conference commenced with an invigorating address, highlighting the growing significance of R in the industry and the importance of fostering its continued development. The vibrant atmosphere was infectious as I was surrounded by like-minded individuals who shared the same passion for data science.

The day was packed with informative sessions covering a various of topics, from advanced data visualization techniques to machine learning algorithms.

Day 1 of the NYC-R Conference featured diverse and insightful presentations, showcasing the remarkable potential of the R programming language in data science. Attendees explored various topics, including transitioning to Quarto for interactive data reports, building R packages with LLMs, and making impactful design decisions for statistical software visualizations. The presentations also delved into data-driven marketing channel attribution, the power of OpenAI’s Embeddings API, and the art of creating captivating presentations through Slidecraft. Experts from NFL Next Gen Stats revealed the many models powering sports analytics, underscoring the transformative role of data science in the sports industry. The conference left attendees inspired and equipped with valuable skills to drive data- driven innovation in their fields.

The Importance of Continuous Learning

Day 1 of the NYC-R Conference was a remarkable showcase of the importance of continued learning and the incredible potential of the R programming language. As data enthusiasts gathered, the conference provided a platform for exploring various facets of R and its impact on data-driven decision-making.

The NYC-R Conference became a hub of knowledge sharing and collaboration, where data professionals engaged in vibrant discussions and exchanged ideas. This collaborative environment emphasized the significance of staying updated with the latest trends in data science to remain at the forefront of innovation.

Day 2: Unlocking Data Insights through Advanced Analytics

Day 2 of the NYC-R Conference was a captivating journey into the forefront of data science. Attendees were treated to lectures and presentations that showcased the latest advancements in the field. The exploration of Bayesian Boosting revealed its potential for predictive modeling, offering a fresh perspective on data analysis techniques.

In an enlightening presentation, a renowned data science expert delved into the importance of democratizing data access in the session “An Ode to Permissionless Data Science.” This inspiring talk encouraged attendees to foster a more inclusive and collaborative data science community, empowering data professionals to drive innovation together.

Participants were enthralled by demonstrations of LLM use, equipping them with practical skills to build robust R packages. The “How to Make Decisions with Data” session, empowered attendees to derive meaningful insights, ensuring data-driven strategies and informed decision-making.

The day continued with captivating lectures that covered various data science aspects, concluding with a live episode of the SuperDataScience Podcast. The podcast provided invaluable industry insights and sparked engaging discussions, leaving attendees inspired and eager to apply their newfound knowledge in their data-driven endeavors. Day 2 at the NYC-R Conference left participants with a deeper understanding of data science’s evolving landscape, motivating them to make a lasting impact in the dynamic world of data-driven innovation.

Language Wars Still at Large

Wes McKinney, the brilliant mind behind pandas, addressed the ever-lingering “Language Wars” in the data science realm. With a focus on breaking down barriers and fostering interoperability, McKinney unveiled how Apache Arrow and the Python Polars library are revolutionizing the data stack. Attendees were enthralled by McKinney’s insights on harnessing the power of these cutting-edge tools to streamline data operations, improve performance, and enable seamless data exchange across programming languages. As the discussion unfolded, it became evident that the quest for data-driven excellence continues, and the open-source community remains at the forefront of bridging the gap between programming languages for the betterment of data science.

The Power of Community

The conference highlighted the power of community in the world of data science. Interacting with professionals from diverse backgrounds provided fresh perspectives and insights, fostering an environment of collaborative learning and growth. As a sponsor member of the R-Consortium, ProCogia extends its heartfelt gratitude for their invaluable support in making this event possible. Their commitment to advancing the R programming language and data science community has been instrumental in creating a vibrant platform for knowledge sharing and networking. The connections made during the NYC-R Conference are a testament to the strength of this community, forming the foundation for future collaborations and knowledge sharing that will undoubtedly drive data-driven innovations for years to come. ProCogia is proud to be part of this thriving community and looks forward to continuing its involvement in fostering growth and innovation within the R community.

Conclusion

Attending the NYC-R Conference was an exhilarating and enlightening experience. The conference reiterated the widespread adoption of R as a powerful tool in data science. Numerous presenters showcased their impressive projects and highlighted the versatility of R in data analysis, modeling, and visualization. It became evident that R is not just a programming language but an entire ecosystem that supports data-driven decision-making across various domains.

The conference showcased the immense potential of R in data science, emphasized the importance of continuous learning, and highlighted the value of community and collaboration. As I left the conference with a wealth of new knowledge and connections, I felt inspired to apply what I had learned in my own data-driven endeavors. The NYC-R Conference not only expanded my horizons but also reinforced my passion for the exciting world of data science.