Data visualisation, reporting, and processing with R

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# Data visualisation, reporting, and processing with R
## Closing remarks
### Kirill Müller
### 2017-10-20

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# More transformations

- Grouped `mutate()` and `filter()`, see r4ds 5.7.1
- Scoped functions, see `?scoped`
- `complete()` and `fill()`
- `extract()`

## Same syntax for working with databases

- *dbplyr* package
- Transformation operations are translated to SQL

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# Nested data frames

r4ds, chapter 25

```r
flights %>%
  nest(-month) %>% 
  arrange(month)
```

```
## # A tibble: 12 x 2
##    month data                  
##    <int> <list>                
##  1     1 <tibble [27,004 × 18]>
##  2     2 <tibble [24,951 × 18]>
##  3     3 <tibble [28,834 × 18]>
##  4     4 <tibble [28,330 × 18]>
##  5     5 <tibble [28,796 × 18]>
##  6     6 <tibble [28,243 × 18]>
##  7     7 <tibble [29,425 × 18]>
##  8     8 <tibble [29,327 × 18]>
##  9     9 <tibble [27,574 × 18]>
## 10    10 <tibble [28,889 × 18]>
## 11    11 <tibble [27,268 × 18]>
## 12    12 <tibble [28,135 × 18]>
```

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# Pointers

Working directory hell:
- https://www.tidyverse.org/articles/2017/12/workflow-vs-script/

Symbolic link to data directory:
- Linux and OS X: `file.symlink()`
- Windows: `Sys.junction()`

R markdown: http://rmarkdown.rstudio.com/gallery.html

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# Pointers 2

Literature:

- Quick-R [http://www.statmethods.net](http://www.statmethods.net)
- Advanced R [http://adv-r.had.co.nz](http://adv-r.had.co.nz)
- Packages suggested by RStudio [https://github.com/rstudio/RStartHere](https://github.com/rstudio/RStartHere)