One last useful function

sessionInfo()

## R version 3.6.1 (2019-07-05)
## Platform: x86_64-w64-mingw32/x64 (64-bit)
## Running under: Windows 10 x64 (build 18362)
## 
## Matrix products: default
## 
## locale:
## [1] LC_COLLATE=English_United States.1252 
## [2] LC_CTYPE=English_United States.1252   
## [3] LC_MONETARY=English_United States.1252
## [4] LC_NUMERIC=C                          
## [5] LC_TIME=English_United States.1252    
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## loaded via a namespace (and not attached):
##  [1] compiler_3.6.1  magrittr_1.5    tools_3.6.1     htmltools_0.3.6
##  [5] xaringan_0.12   yaml_2.2.0      Rcpp_1.0.1      stringi_1.4.3  
##  [9] rmarkdown_2.0   knitr_1.23      stringr_1.4.0   xfun_0.8       
## [13] digest_0.6.20   evaluate_0.14

Data Science Cycle

Image from Grolemund, G., & Wickham, H. (2018). R for data science (CC BY-NC-ND 3.0).

gganimate for Animated ggplots
patchwork for displaying multiple ggplots
ggtext for adding text to ggplot
shiny for web apps
xaringan for being a Presentation Ninja with .Rmd
stringr for dealing with strings
rticles for LaTeX journal article templates
naniar for summarizing missing data
kableExtra for beautiful HTML tables
blogdownfor creating websites
github for version control

After the Workshop

• Join the conversation on Twitter with #rstats #tidyverse tags. It is a welcoming community.
• Find your local R meetups on meetup.com.
• Join RStudio Community.
• Try Out Tidy Tuesday.
• Join R for Data Science Learning Community.
• Use RStudio resources: webinars, conference talks etc.

Schedule for the Day

08:45 - 09:00 Introduction
09:00 - 09:15 Getting to Know the Basics
09:15 - 10:15 Data Visualization
10:15 - 10:30 Break
10:30 - 12:00 Data Wrangling
12:00 - 01:00 Lunch
01:00 - 01:30 Working Locally With R
01:30 - 02:00 Dealing with Datasets
02:00 - 02:30 Case Study
02:30 - 02:45 Break
02:45 - 03:30 Modeling
03:30 - 04:00 Everything I did not have time to cover