Introduction to Tidyverse

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.title[
# Introduction to Tidyverse
]
.author[
### Athanasia Monika Mowinckel
]

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## Timeline

- **Introduction to [tidyverse](https://www.tidyverse.org/) concepts** (15 minutes)

- **Tidy data wrangling** - with translations to base-R (~ 2 hours) 
  - plotting data with [ggplot2](https://ggplot2.tidyverse.org/) (~25 min) 
  - sub-setting data with [dplyr](https://dplyr.tidyverse.org/) (~25 min)  
  - chaining commands with the pipe `|>` (~10 min)  
  - adding and altering variables with [dplyr](https://dplyr.tidyverse.org/)  (~25 min)

- **Lunch break** (30 min)

- **Tidy data reshaping & summaries** - avoiding loops (~ 1.5 hours)   
  - pivoting data with [tidyr](https://tidyr.tidyverse.org/) (~25 min) 
  - grouped summaries with [dplyr](https://dplyr.tidyverse.org/) (~25 min)  
  - working with nested data using [purrr](https://purrr.tidyverse.org/) (~25 min)

> All parts (except first intro) come with small exercises and breaks between.

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# What is the Tidyverse?

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## The packages
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|Package|Functions|
|------|--------|  
| dplyr | data manipulation - altering and adding variables in a dataset  |
| tidyr | data tidying - changing data shape and structure  |
| ggplot2 | data visualisation  |
| purrr | Enhancements on functional programming |
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## The packages
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### Covered here

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### Not covered

|Package|Functions|
|------|--------|  
| readr | easy and fast importing of data |
| tibble | variations on the R data.frame |
| forcats | working with factors/categorical data |
| stringr | working with strings/characters |
]

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## What's so special about them?

- **made to work with data sets (tibbles / data.frames)**  
    - geared towards data-scientists and folks working with rectangular data   
    
--

- **made to work together**  
    - naming and argument conventions

- **use function names similar to spoken language**  
    - verbs and adverb function names

- **arguments can be chained (piped) together**  
    - avoids saving intermediary objects
    - input always as first argument

- **packages are actively developed and maintained by RStudio**
    - functions will not abruptly or without warning and careful thought change behaviour