.large[Robust data analysis]

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# .large[Robust data analysis]
## An introduction to R
### Sina Rüeger & Allie Burns
### 2019-09-05

---

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# Who we are

.pull-left-large[
## Sina

- **Background** in Data Science and Biostatistics
- Works with genomic & clinical **data**

<i class="fab  fa-twitter "></i> <small>@sinarueeger</small><br />
<i class="fab  fa-github "></i> <small>@sinarueeger</small><br />

]

.pull-right-small[
## Allie

- **Background** in Biology and Bioinformatics
- Works with genomic & experimental **data**

<i class="fab  fa-twitter "></i> <small>@imallieburns</small><br />
<i class="fab  fa-github "></i> <small>@allie-burns</small><br />

]

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## Slides
### &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; http://bit.ly/rds-slides

## Handbook
### &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; http://bit.ly/rds-handbook

## RStudio Cloud
### &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; http://bit.ly/rds-rstudio

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<div class="figure">
<img src="https://raw.githubusercontent.com/allisonhorst/stats-illustrations/master/openscapes/starwars-rey-rstats.png" width="600" alt="Cover image" />
<p class="caption">Artwork by <a href="https://github.com/allisonhorst/stats-illustrations">@allison_horst</a> for <a href="https://www.openscapes.org/">openscapes</a></p>
</div>

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## 1. [Data Analysis](#part-1-data-analysis)

## 2. [Introducing R](#part-2-r)

## 3. [Workshop](#part-3-workshop)

## 4. [Beyond the Basics](#part-4-beyond-the-basics)

## 5. [Learning R](#part-5-learning-r)

---
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# Part 1
# <a name="part-1-data-analysis"></a>Data Analysis

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# Data Analysis Workflow

<div class="figure">
<img src="img/workflow/workflow.001.jpeg" width="800" alt="R 4 DS image" />
<caption>Adapted from <a href="https://r4ds.had.co.nz/introduction.html">R for Data Science by Grolemund & Wickham, 2017.</a></caption>
</div>

---
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# Emojification of Data Analysis Workflow

### 🤔 <i class="fas  fa-arrow-right " style="color:gray;"></i> <i class="fas  fa-table " style="color:black;"></i> <i class="fas  fa-arrow-right " style="color:gray;"></i> <i class="fas  fa-laptop " style="color:#377eb8;"></i> <i class="fas  fa-arrows-alt " style="color:gray;"></i> <i class="fab  fa-r-project " style="color:#377eb8;"></i> <i class="fas  fa-arrow-right " style="color:gray;"></i> <i class="fas  fa-chart-line " style="color:#f03b20;"></i> <i class="fas  fa-arrow-right " style="color:gray;"></i> <i class="fas  fa-lightbulb " style="color:#31a354;"></i> <i class="fas  fa-arrow-right " style="color:gray;"></i> <i class="fas  fa-map-signs " style="color:#d95f0e;"></i>

---
exclude: true

<div class="figure">
<img src="https://github.com/allisonhorst/stats-illustrations/raw/master/openscapes/environmental-data-science-r4ds.png" width="700" alt="Cover image" />
<p class="caption">Artwork by <a href="https://github.com/allisonhorst/stats-illustrations">@allison_horst</a> for <a href="https://www.openscapes.org/">openscapes</a></p>
</div>

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# Principles

- Tidy data
- Distinct "modules""
- Module dependency
- Flow: Entrance → Iteration → Exit 
- Communication & sharing of results
- Isolated box

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# In reality

???

_Revisiting modules many many times: robust DA when this works at easy_.

_Draw figure on whiteboard_.

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# Role of Excel

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# Role of Excel

- Use Excel for _data entry & storage_

- Organise data for humans and computer programs

- [Data Organization in Spreadsheets](https://www.tandfonline.com/doi/full/10.1080/00031305.2017.1375989) by Broman & Woo (2018)

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# Requirements to Software

- Translation of modules to scripts (high-level language)
- Easy updating of modules
- Sharing ready results + scripts

- Used by others
- Continuously developed & improved

---
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# Thought experiment

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## Q1: 
### What is the most annoying & repetitive task at work? 
## Q2: 
### How could you automate it?

---
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# Automation

Programming is essentially an automation of a process
- for common tasks
- scalable
- complicated tasks
- where precision is needed 
- to reuse frameworks
- to redo something from the past

Side effect: reproducibility.

---
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# Part 2
# <a name="part-2-r"></a>R

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> <p><small>As developers, “tidyevaluations” help us make sure the user does as little typing as possible and can express really rich ideas [for analysis]. This is what underlies ggplot2 and some of our other libraries.</p></small> The idea is to get things out of your head and on to the computer as quickly as possible.

[_Interview with Hadley Wickham, Quartz, 2019_](https://qz.com/1661487/hadley-wickham-on-the-future-of-r-python-and-the-tidyverse/)

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# R

- is "a programming language for statistical computing"
- is free
- has a webpage: [r-project.org/](https://www.r-project.org/)
- just celebrated its [25 year anniversary](https://rss.onlinelibrary.wiley.com/doi/10.1111/j.1740-9713.2018.01169.x)
- comes with *basic*/*default* packages, but there are over 13'000 R-packages that can be by users.

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# What is R used for?

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# Quite a few things

Data science, data analysis & stats stuff

???

_sdflkjfdksjdf_.

---
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# Capabilities of R

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## Communication of results
- through literate programming
- through a web application

## Data visualisation

## Accessing other tools or data sources
through APIs

???

_Beyond being a calculator and being able to estimate statistical models, R can help us to organise the data analysis workflow better. _

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# R is constantly evolving & improving

???

_Other biologists_

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# Some terms

- Function

- Object

- Package

- Script

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## Object

- A "physical" object.

- For example, a dataset or a number.

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## Function

- A pre-written [recipe](https://twitter.com/IsabellaGhement/status/1070691303485128704).

- Functions can be applied to objects.

- For example, `mean()` is a function in R.

- Function = action = verb, applied to object = noun.

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## Script

- Chain of functions + objects create a _programming script_.

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## Package

- Aackage is a **collection of functions**.

- Anyone can contribute a package.

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# R vs RStudio

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# Programming language vs. natural language

- Similar to natural languages: tool to communicate with others.

- Programming: communication with computer (+colleagues).

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# Hierarchy of best practices

1. documentation (`lintr`)
1. run all script (`usethis`)
1. version control (`gitr`)
1. unit tests and sanity checks (`testthat`, `assertr`)
1. write functions, package them and tell everyone (`devtools`, `blogdown`)
1. continuous integration (`devtools`, `blogdown`)
1. makefile (caching) (`drake`)
1. binder (`holepunch`)

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# Part 3
# <a name="part-3-workshop"></a>Workshop

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# Goal

1. Make a data visualisation.
2. Import data into R.
3. Make the data analysis-ready.
4. Create a report that gives insights into meteorite falls around the world.

???

_two steps: make changes + add things_.

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# Get started

1. Go to RStudio Cloud: http://bit.ly/rds-rstudio.

2. Log in (this might take a while).

3. Once logged in, RStudio Cloud will tell you that you have been added to a workspace.

4. Click on `Project`.

5. Choose `Workshop`

6. Click `Make a permanent copy`.

---
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# Part 4 
# <a name="part-4-beyond-the-basics"></a>Beyond the Basics

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<div class="figure">
<img src="https://raw.githubusercontent.com/allisonhorst/stats-illustrations/master/rstats-artwork/r_first_then.png" height="500" alt="Cover image" />
<p class="caption">Artwork by <a href="https://github.com/allisonhorst/stats-illustrations">@allison_horst</a></p>
</div>

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<div class="figure">
<img src="https://happygitwithr.com/img/watch-me-diff-watch-me-rebase-smaller.png
" width="700" alt="Cover image" />
<p class="caption">Source: <a href="https://happygitwithr.com/">Happy Git with R by Jenny Bryan</a></p>
</div>

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# Git & R

--
1. Use git. 
--

2. Read [*Happy Git with R*](https://happygitwithr.com/). 
--

3. Use the handy *git interface* in RStudio. 
--

4. 🎉
--

Tipp: Use [gist.github.com](https://gist.github.com/) to share & store code snippets, notes, thoughts and blogposts.

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# R in the wild

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## Research compendium

<div class="figure">
<a href="https://github.com/seabbs/DirectEffBCGPolicyChange">
<img border="0" alt="mouse" src="img/bcg.png" width="600">
</a>
<p class="caption">Source: <a href="https://github.com/seabbs/DirectEffBCGPolicyChange">Effect of BCG policy change in England.</a></p>
</div>

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## Blogpost

<div class="figure">
<a href="https://notstatschat.rbind.io/2019/06/16/analysing-the-mouse-autism-data/">
<img border="0" alt="mouse" src="img/mouse.png" width="400">
</a>
<p class="caption">Source: <a href="https://notstatschat.rbind.io/2019/06/16/analysing-the-mouse-autism-data/">Analysing mouse autism data</a></p>
</div>

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## Data journalism

<div class="figure">
<a href="https://www.srf.ch/static/srf-data/data/2018/federer/#/en">
<img border="0" alt="SRF" src="img/datajournalism.png" width="700">
</a>
<p class="caption">Source: <a href="https://www.srf.ch/static/srf-data/data/2018/federer/#/en">SRF</a></p>
</div>

---

## Data journalism

<div class="figure">
<a href="https://srfdata.github.io/2018-01-roger-federer/#load_data">
<img border="0" alt="SRF" src="img/datajournalism_code.png" width="800">
</a>
<p class="caption">Source: <a href="https://www.srf.ch/static/srf-data/data/2018/federer/#/en">SRF</a></p>
</div>

---

## Web application with Shiny

<div class="figure">
<a href="https://kevinrue.shinyapps.io/isee-shiny-contest/">
<img border="0" alt="SRF" src="https://d33wubrfki0l68.cloudfront.net/8e0d1f45ed43ea538143b4b3cc7ea1cd7ad17e69/33284/images/2019-04-05-isee.png" width="800">
</a>
<p class="caption">Source: <a href="https://blog.rstudio.com/2019/04/05/first-shiny-contest-winners/">Winner of the Shiny Contest 2019</a></p>
</div>

---

## Animations

<div class="figure">
<a href="https://raw.githubusercontent.com/gadenbuie/tidy-animated-verbs/master/images/anti-join.gif">
<img src="https://raw.githubusercontent.com/gadenbuie/tidy-animated-verbs/master/images/anti-join.gif" width="400">
</a>
<p class="caption">Source: <a href="https://github.com/gadenbuie/tidy-animated-verbs#tidy-animated-verbs">Animated verbs by @gadenbuie</a></p>
</div>

---

## Fun things: Memes

<div class="figure">
<a href="http://djnavarro.net/post/2018-05-03-valid-social-commentary/">
<img src="http://djnavarro.net/post/2018-05-03-valid-social-commentary_files/figure-html/unnamed-chunk-2-1.png" width="500">
</a>
<p class="caption">Source: <a href="http://djnavarro.net/post/2018-05-03-valid-social-commentary/">Danielle Navaro</a></p>
</div>

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# Neat packages & functions

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## Data import

- [`data.table`](https://cran.r-project.org/web/packages/data.table/vignettes/datatable-intro.html): (Fast) alternative to `readr`.

- [`datapasta`](https://twitter.com/dataandme/status/1148548556850114561): Copy + paste unconventional tables.

- [`fabricatr`](https://rviews.rstudio.com/2019/07/01/imagine-your-data-before-you-collect-it/): Imagine your data before you collect it.

- Practical recommendations for organizing spreadsheet data in a way that both humans and computer programs can read: [Data Organization in Spreadsheets](https://www.tandfonline.com/doi/full/10.1080/00031305.2017.1375989) by Broman & Woo (2018).

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## Data manipulation

- [`data.table`](https://cran.r-project.org/web/packages/data.table/vignettes/datatable-intro.html): (Fast) alternative to `dplyr`.

- [`janitor`](http://sfirke.github.io/janitor/): data cleaning.

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## Data visualisation

- [`esquisse`](https://github.com/dreamRs/esquisse) to interactively create a plot.

- Publication ready plots with [`cowplot`](https://github.com/wilkelab/cowplot) and [`ggpubr`](https://github.com/kassambara/ggpubr).

- Pick a chart type with [R Graph Gallery](https://www.r-graph-gallery.com/).

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## ggpubr

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## holepunch

Make your package binder-ready with [holepunch](https://github.com/karthik/holepunch).

<div class="figure">
<img src="https://camo.githubusercontent.com/fd4274e8efa5ef6e2e096176bf75465c4746c667/68747470733a2f2f692e696d6775722e636f6d2f6f71576c3531322e706e67" width="600" alt="Cover image" />
<p class="caption">Source: <a href="https://github.com/karthik/holepunch">github/holepunch</a></p>
</div>

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# Part 5
# <a name="part-5-learning-r"></a>Learning R

???

_Any ideas?_.

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# Learning strategies

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## 1. Learn with isolated & digestible examples

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## 2. Look for a steady stream of data or exercises

[TidyTuesday](https://github.com/rfordatascience/tidytuesday)!

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## 3. Watch recordings

- Screencasts
- New York R conference [recordings](https://www.rstats.nyc/2019/nyr/)
- R conference [recordings](https://www.youtube.com/channel/UC_R5smHVXRYGhZYDJsnXTwg)
- RStudio conference [recordings](https://resources.rstudio.com/rstudio-conf-2019)
- rOpenSci community call [archive](https://ropensci.org/commcalls/)

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## 4. Read blogposts

![](https://camo.githubusercontent.com/42ba3f035a08ef82195b24b4f39452b63ecbb469/68747470733a2f2f727765656b6c792e6f72672f696d616765732f69636f6e732f69636f6e2d323536783235362e706e67)

Weekly supply of blogposts by [rweekly.org/](https://rweekly.org/).

---
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# Embrace imperfection

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### Programming is an iterative process

### 1 Problem → 1+ solutions

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## Exploit imperfection

- Look at & review each others code

- Rewrite your code

- Look at open source code

---
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# How to ask for help

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## 1. Check if question has been ask before

- [Stack Overflow](https://stackoverflow.com/) (SO)
- [RStudio Community](https://community.rstudio.com/)

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<div class="figure">
<img src="https://raw.githubusercontent.com/allisonhorst/stats-illustrations/master/rstats-artwork/reprex.png" height="500" alt="Cover image" />
<p class="caption">Artwork by <a href="https://github.com/allisonhorst/stats-illustrations">@allison_horst</a></p>
</div>

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## 2. Create a reproducible example

1. create a reproducible example using a small R available dataset (e.g. iris)
1. `install.packages("reprex")`
1. select code and run [reprex](https://reprex.tidyverse.org/)

---
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## 3. Ask your question

- Ask within an online community
- [RStudio community](https://community.rstudio.com/) 
- [Stack Overflow](https://stackoverflow.com/)
- Twitter using the `#rstats` hashtag

<!-------
More: https://masalmon.eu/2018/07/22/wheretogethelp/
- If its a bug: file an issue on github

Why not writing directly to the maintainer? Because online helps
----->

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# Become part of the community

<div class="figure">
<img src="https://raw.githubusercontent.com/allisonhorst/stats-illustrations/master/rstats-artwork/welcome_to_rstats_twitter.png" height="400" alt="Cover image" />
<p class="caption">Artwork by <a href="https://github.com/allisonhorst/stats-illustrations">@allison_horst</a></p>
</div>

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## [R-Ladies](https://rladies.org/)

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### 47 countries, 167 chapters

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.pull-left[
<div class="figure">
<img src="https://secure.meetupstatic.com/photos/event/5/3/a/8/600_480981416.jpeg" width="600" alt="Cover image" />
</div>

]

.pull-right[
<div class="figure">
<img src="https://pbs.twimg.com/media/DbUq6zqU0AE2_Ls.jpg" width="600" alt="Cover image" />
</div>

]

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### R-Ladies at useR!2019

---
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### What does R-Ladies do?

R-Ladies has a [Code of Conduct](https://rladies.org/code-of-conduct/).

For women and gender minorities R-Ladies offers:

- [Slack](https://rladies-community-slack.herokuapp.com/) 
- [Abstract / Scholarship review process](tinyurl.com/rladiesabstracts)
- [R-Ladies directory](http://rladies.org/directory/)

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### Want to start a chapter?

<blockquote class="twitter-tweet"><p lang="en" dir="ltr">Interested in starting an <a href="https://twitter.com/hashtag/RLadies?src=hash&amp;ref_src=twsrc%5Etfw">#RLadies</a> meetup in your city? We&#39;d love to help! Send us an email at info@rladies.org to get in touch. <a href="https://twitter.com/hashtag/rstats?src=hash&amp;ref_src=twsrc%5Etfw">#rstats</a></p>&mdash; R-Ladies Global (@RLadiesGlobal) <a href="https://twitter.com/RLadiesGlobal/status/770662914365808640?ref_src=twsrc%5Etfw">August 30, 2016</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>

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## Online Communities

- [R for Data Science](https://www.rfordatasci.com/) online learning community (e.g. [Slack](https://rfordatascience.slack.com/join/shared_invite/enQtMzA1Nzk1MjIzNDczLTY0OTVlMzM3ZTU5ZjA3NWE5ZDkxOGVmNjRjODQ2YmRjMzg4NWQxMDAxZTcwNzViZTczOThiNzBhYWJhZDM2ZTU), [TidyTuesday](https://github.com/rfordatascience/tidytuesday))

- French-speaking [r-grrr Slack](https://r-grrr.slack.com/join/shared_invite/enQtMzI4MzgwNTc4OTAxLWZlOGZiZTBiMWU0NDQ3OTYzOGE1YThiODgwZWNhNWEyYjI4ZDJiNmNhY2YyYWI5YzFiOTFkNDYxYzkwODUwNWM) (+ [online resources](https://github.com/frrrenchies/frrrenchies))

---
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## [rOpenSci](https://ropensci.org)

- Non-profit initiative founded in 2011.

- **Builds software** with a community of users and developers.

- **Educates scientists** about transparent research practices.

- Check [their handbook](https://devguide.ropensci.org/) on _Development, Maintenance, and Peer Review_.

- Attend or re-watch a community call ([archive](https://ropensci.org/commcalls/)).

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## Join an R meetup

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.pull-left[
### Switzerland 
- [R-Ladies Lausanne](https://www.meetup.com/rladies-lausanne/)
- [Geneve RUG](https://www.meetup.com/Geneve-R-User-Group)
- [R lunches](http://use-r-carlvogt.github.io/prochains-lunchs/)
- [adminR](https://www.meetup.com/adminR/)
- [Zurich RUG](https://www.meetup.com/Zurich-R-User-Group/)

]

.pull-right[

### [R Ladies Remote](https://twitter.com/RLadiesRemote) 
- Coffee chats
- Journal club
- For women & gender minorities

### Around the world
Full list of RUG's [here](https://jumpingrivers.github.io/meetingsR/r-user-groups.html) and for R-Ladies [here](https://gqueiroz.shinyapps.io/rshinylady/).

]

---
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## Write blogposts

- Start with [gist.github.com](https://gist.github.com/)

- Move to [`blogdown`](https://bookdown.org/yihui/blogdown/)

- Submit your post to [rweekly](https://rweekly.org/)!

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## Engage on Twitter

Lots of cool #rstats folks on twitter. For example:

- [Mara Averick: @dataandme](https://twitter.com/dataandme)

- [Maëlle Salmon: @ma_salmon](https://twitter.com/ma_salmon)

- [WeAreRLadies: @WeAreRLadies](https://twitter.com/WeAreRLadies)

- [R for the rest of us: @rfortherest](https://twitter.com/rfortherest)

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<div class="figure">
<img src="https://raw.githubusercontent.com/allisonhorst/stats-illustrations/master/openscapes/starwars-teamwork.png" width="600" alt="Cover image" />
<p class="caption">Artwork by <a href="https://github.com/allisonhorst/stats-illustrations">@allison_horst</a> for <a href="https://www.openscapes.org/">openscapes</a></p>
</div>

---
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# .large[Questions?]