@MeghanMHall

now a

vintage

sticker!

**this 2015MacBookAir is why Ilearned R**

you *can*

use R for your entire

data analysis workflow!

you *don’t have to*

use R for your entire

data analysis workflow!

**Struggles**

**Struggles**

do as much in R as possible

focus on what’s realistic, not ideal

**Struggles**

do as much in R as possible

focus on what’s realistic, not ideal

- can’t access data through R

**Struggles**

do as much in R as possible

focus on what’s realistic, not ideal

`00-setup.R`

`01-prep.R`

`02-analysis.R`

`03-dashboard.R`

**Struggles**

do as much in R as possible

focus on what’s realistic, not ideal

`00-setup.R`

`01-prep.R`

`02-analysis.R`

`03-dashboard.R`

- document
*all*report decisions: name, location, filters, run date, effective date - save data prep work for R

**Struggles**

**Struggles**

do as much in R as possible

focus on what’s realistic, not ideal

- can’t access data through R

- need to dashboard elsewhere

**Struggles**

do as much in R as possible

focus on what’s realistic, not ideal

`00-setup.R`

`01-prep.R`

`02-analysis.R`

`03-dashboard.R`

- handle relational data, aggregations, calculations, etc. in R
- save all data files in a specific folder

**Struggles**

**Struggles**

do as much in R as possible

focus on what’s realistic, not ideal

- can’t access data through R

- need to dashboard elsewhere

- no git/version control

**Struggles**

do as much in R as possible

focus on what’s realistic, not ideal

`00-setup.R`

`01-prep.R`

`02-analysis.R`

`03-dashboard.R`

- collaborate with yourself: use dated comments for major decisions
- link to supporting documentation

**Struggles**

do as much in R as possible

**focus on what’s realistic, not ideal**

`00-setup.R`

`01-prep.R`

`02-analysis.R`

`03-dashboard.R`

- collaborate with yourself: use dated comments for major decisions
- link to supporting documentation

**Big Wins**

**Big Wins**

ease the burden of repeated reporting

transfer institutional knowledge

**Big Wins**

ease the burden of repeated reporting

transfer institutional knowledge

- develop internal packages

- have easy access to common data sets used across multiple projects
- document data definitions and calculations
- track common analysis functions (and ggplot themes!)

**Big Wins**

**Big Wins**

ease the burden of repeated reporting

transfer institutional knowledge

- develop internal packages

- leverage parameterized reporting with R Markdown/Quarto

- many output formats!
- useful when you have code + text + updating data + varying parameters

**Big Wins**

less time reproducing

your own analysis

=

more time for the

work you find important

**Thank you!**

**MEGHAN HALL**

@MeghanMHall

meghall06

meghan.rbind.io

meghanhall6 AT gmail

slides made with Quarto 🎉