presentation.md

The R User's Guide to Result Delivery Through Data Products

author: Kelly O'Briant date: PhUSE 2019 font-family: 'Helvetica' autosize: true

The R For Data Science Workflow

• Access
• Understand
• Communicate

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R is an open source programming language for statistical computing

RStudio provides open source and enterprise-ready professional software for data science

What are Data Products?

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• The artifacts through which you communicate, share and provide access to your ideas and analyses
• Reports, Visualizations, Applications, Services, Dashboards
• Data Storytelling Devices

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"It doesn't matter how great your analysis is unless you can explain it to others: you need to communicate your results."

- Wickham & Grolemund R for Data Science

Explore Common R Data Product Packages

R is supported by a rich ecosystem of open source packages

Why is using R for data products empowering?

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1. Opportunity to delight

2. Options for different communication styles and needs

3. Leverage code and version control for reproducibility

4. Justify worth: proof that you can contribute meaningful work

What does it mean to deliver delight?

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My goal is this:

• Work that I'm proud to show off
• Communication with excellent user experience

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Not this:

Should all my spreadsheets be Shiny apps?

Send a crucial weekly data update

library(ggplot2)

irisinfo <- ggplot(iris, aes_string(x = "Sepal.Length", fill = "Species")) +
  geom_histogram(data = iris[,-5], fill = "grey", alpha = .5) +
  geom_histogram(colour = "black") +
  facet_wrap(~ Species) +
  guides(fill = FALSE) +
  theme_bw()

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The latest in "Sepal Length" news

Interested in learning more?

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Resources:

• Community - rstd.io/community
• Twitter - rstd.io/twitter
• Webinars - resources.rstudio.com
• Solutions - solutions.rstudio.com

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RStudio Conference 2019

This data product is reproducible!

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GitHub: bit.ly/phuse-2019