Isabella Velásquez

Isabella is an R enthusiast, first learning the programming language during her MSc in Analytics. Previously, Isabella conducted data analysis and research, developed infrastructure to support use of data, and created resources and trainings to engage technical and non-technical audiences. Her work on the RStudio Marketing team draws on these experiences to create content that supports and strengthens data science teams.


Tips for Getting Started With the NFL Big Data Bowl From the 2022 Winners

October 13, 2022

The NFL Big Data Bowl is an annual competition that explores statistical innovations in football. The 2022 champions share how to get started with a winning submission.


6 Productivity Hacks for Quarto

October 3, 2022

With Quarto, you can render plain text and mixed formats into different types of content. We highlight six productivity hacks that may be useful to you.


Designing Online Data Science Training for the Modern Age

September 21, 2022

Academy takes what we've learned from teaching over many years to provide the most effective way to learn data skills online.


R Markdown Lesser-Known Tips & Tricks #4: Looks Better, Works Better

September 14, 2022

In this series, we walk through lesser-known tips and tricks to help you work more effectively and efficiently in R Markdown. The final post focuses on making your document look and work better.


Update Your Machine Learning Pipeline With vetiver and Quarto

September 13, 2022

With the vetiver package, data scientists have a streamlined, consistent way to maintain machine learning pipelines. We recently updated our Bike Share prediction application using vetiver and Quarto.


Four announcements from rstudio::conf(2022)

August 8, 2022

rstudio::conf was an eventful four days! This post details some of the bigger announcements from RStudio.


RStudio Recap From the Appsilon Shiny Conference

July 5, 2022

The Appsilon Shiny Conference was an exciting event for Shiny developers worldwide. Speakers from RStudio showcased recent advancements in Shiny technology and answered questions from the community.


Automated Survey Reporting With googlesheets4, pins, and R Markdown

June 15, 2022

In this post, we walk through the tools and functionality we used to automate survey results reporting.


R Markdown Lesser-Known Tips & Tricks #3: Time-Savers & Trouble-Shooters

May 18, 2022

In this series, we walk through lesser-known tips and tricks to help you work more effectively and efficiently in R Markdown. This third post focuses on features that save you time and trouble.


Software Development Resources for Data Scientists

May 16, 2022

Many tools used routinely by software developers can also be useful to data scientists.


Exploring RStudio's Visual Markdown Editor

May 11, 2022

The RStudio IDE includes a visual markdown editor that displays changes in real-time and provides support for technical writing. This post walks through several features of visual editing mode.


Successfully Putting Shiny in Production

April 21, 2022

In this post, we explore possible challenges to putting Shiny in production and how to overcome them.


Track Shiny App User Activity With the RStudio Connect Server API

March 30, 2022

With the RStudio Connect Server API, you can access advanced usage metrics to focus your data science work.


Creating APIs for Data Science With plumber

March 22, 2022

APIs increase the impact of your data science work. With the plumber package, you can turn your R code into API endpoints so that others can use your function or model.


Curating Your Data Science Content on RStudio Connect

March 15, 2022

With RStudio Connect, you can curate data science content to deliver a great experience to your audience.


Working With Databases and SQL in RStudio

February 17, 2022

RStudio has several options for connecting with databases and querying data using SQL.


Build and Share Jupyter Notebooks on RStudio Team

February 3, 2022

With RStudio Team, data scientists can build and share their work within an integrated architecture.


Three Videos to Supercharge Your R Skills

January 18, 2022

In this blog post, we highlight three speakers from the RStudio Enterprise Community Meetup who share packages and tools to supercharge your R skills.


Sharing Secure and Scalable Shiny Apps on RStudio Connect

January 13, 2022

RStudio Connect allows you to easily share your Shiny apps with push-button publishing, while maintaining enterprise-level security and tuning resources to meet the demands of your application.


R Markdown Lesser-Known Tips & Tricks #2: Cleaning Up Your Code

January 6, 2022

In this series, we show you lesser-known tips and tricks to help you work more effectively and efficiently in R Markdown. This second post focuses on cleaning up your R Markdown code.


2021 at RStudio: A Year in Review

January 4, 2022

Happy New Year! In this blog post, we round up some of the many announcements and product releases from RStudio in 2021.


Integrating Dynamic R and Python Models in Tableau Using plumbertableau

December 20, 2021

The plumbertableau and fastapitableau packages allow you to integrate dynamic R and Python models in Tableau, enhancing your organization’s preferred dashboard tool.


Sharing Data With the pins Package

December 15, 2021

The pins package publishes R objects, such as data sets and predictive models, on a virtual corkboard so that you can share and reuse them easily and safely.


Using Keras for Deep Learning With R

December 8, 2021

We are excited to announce new developments in Keras for R. Data scientists can use the most popular and powerful deep learning frameworks to guide data-driven decisions, all within R.


Three Ways to Program in Python With RStudio

December 6, 2021

RStudio has many tools for both R and Python programmers. In this blog post, we’ll showcase various ways that you can program in Python with RStudio tools.


R Markdown Lesser-Known Tips & Tricks #1: Working in the RStudio IDE

November 22, 2021

In this series, we walk through lesser-known tips and tricks to help you work more effectively and efficiently in R Markdown. This first post focuses on working with R Markdown in the RStudio IDE.


Announcing the RStudio Blog’s New Vision and Design

November 17, 2021

Welcome to! We are excited to announce updates to the RStudio blog and can’t wait to share what’s possible with great data science tools.


How the "Clusterbuster" Shiny App Helps Hundreds of Doctors and Epidemiologists Battle COVID-19 in the Netherlands

November 2, 2021

In this post, we explore the creation and evolution of the Clusterbuster, a Shiny app developed by the Dutch National Institute for Public Health and the Environment. Hundreds of doctors and epidemiologists use the Clusterbuster to gain insight into COVID-19 clusters in the Netherlands.


RStudio at R/Pharma 2021

October 27, 2021

Join our RStudio colleagues at R/Pharma 2021, where they are presenting on a variety of tools and topics that support open source in the pharmaceutical field.


Announcing the RStudio 2021 Communications Survey

October 27, 2021

We are announcing the RStudio 2021 Communications Survey! This survey will help us understand your interaction with RStudio communications so that we can provide you information in your desired formats and channels.


How Data Scientists and Security Teams Can Effectively Work Together

October 26, 2021

At a recent RStudio Enterprise Meetup, Gordon Shotwell from Socure shared advice on resolving common tensions between data science and security teams. Through continuous conversation, closed systems for data, and streamlined tools, organizations can set up the relationships and systems needed to be successful.


Embedding Shiny Apps in Tableau Dashboards Using shinytableau

October 21, 2021

This post introduces and walks through shinytableau, a package that allows you to create dashboard extensions that embed Shiny apps in Tableau. Users can take advantage of R's powerful visualization and reporting capabilities when working in Tableau dashboards.


Why Your Data Science Team Might Need a Shiny Deployment Engineer

October 14, 2021

We interviewed Vergil Weatherford from Guidehouse to learn why they are planning to hire a Senior Shiny Deployment Engineer. Weatherford believes data science teams can benefit from someone who can apply software development best practices to support the deployment of high-quality R and Python applications into production.


Teaching a Biomedical Data Science Course Using RStudio Cloud

October 6, 2021

When developing his Data Science for Medical Decision Making course, Professor Chirag Patel discovered that RStudio Cloud is a solution that supports his students through efficient onboarding and reproducible analysis.