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https://github.com/pablobernabeu/CarpentryCon-2020-workshop-Open-Data-Reproducibility

This workshop provides a stepping stone into a suite of interrelated tools—R Markdown, data dashboards and Binder environments—, which are all underlain by reproducible workflows and open-source software.
https://github.com/pablobernabeu/CarpentryCon-2020-workshop-Open-Data-Reproducibility

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This workshop provides a stepping stone into a suite of interrelated tools—R Markdown, data dashboards and Binder environments—, which are all underlain by reproducible workflows and open-source software.

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README 

        

# Workshop *Open data and reproducibility v2.1*

## An introduction to R Markdown, dashboards and Binder

### :round_pushpin: [CarpentryCon@Home 2020](https://2020.carpentrycon.org/schedule/)



### Pablo Bernabeu and [Florencia D'Andrea](https://github.com/flor14)

[email protected]    |    [email protected] 







## :movie_camera:   [Watch the workshop](https://www.youtube.com/watch?v=wZsPD7CgJC0)







## Introduction



This workshop provides a stepping stone into a suite of interrelated tools—R Markdown, data dashboards and Binder environments—, which are all underlain by reproducible workflows and open-source software. 



### Prior information 



Real data and code of varying complexity will be used. Basic and advanced R users are welcome.

Please sign up to RStudio Cloud (https://rstudio.cloud/), which may become useful if you encounter any issues in your local R. 



 Also suggested: 

 installing or updating R (https://www.r-project.org/) and RStudio  (https://rstudio.com/products/rstudio/download/); 

 perusing the links here; 

 having some of your own data and R code ready, preferably in a Github repository. 



 The resources in the programme and a video recording of the workshop will remain available afterwards. 

 

 We have two RStudio Cloud projects, one corresponding up to the Flexdashboard section (including), and one for the Shiny section: 

 

 - R Markdown and Flexdashboard: https://rstudio.cloud/project/1520963

 - Shiny: https://rstudio.cloud/project/1514617







## R Markdown



 RStudio Cloud project (not required if local RStudio fine): https://rstudio.cloud/project/1520963  



 Keep your input and output in check using R Markdown (https://rmarkdown.rstudio.com/). 

 

 Examples: https://bookdown.org/yihui/rmarkdown/journals.html,  http://rpubs.com/  



### Markdown

- background: https://rmarkdown.rstudio.com/authoring_pandoc_markdown.html 

- examples: https://rmarkdown.rstudio.com/gallery.html 

- code demo: https://hackmd.io/@pablobernabeu/S1rnZkseP 



### HTML, CSS

- background: https://html.com/ 

- example and code demo: https://github.com/pablobernabeu/UKCLC2020-workshop-Open-data-and-reproducibility/tree/master/R%20Markdown 



### Running code and cross-referencing

- background: https://rmarkdown.rstudio.com/lesson-4.html, https://rmarkdown.rstudio.com/lesson-3.html 

https://bookdown.org/yihui/rmarkdown-cookbook/cross-ref.html

- examples: https://bookdown.org/yihui/rmarkdown/journals.html,  http://rpubs.com/ 

- code demo: https://rpubs.com/pcbernabeu/R-Markdown-Madison-parks 







 ## Data dashboards / web applications



 RStudio Cloud project (same as above): https://rstudio.cloud/project/1520963  



On a further step in reproducible, open data, we will learn how to publish dashboards online presenting data in the form of plots and tables. These all-reproducible dashboards are displayed as websites; thus, they can include hyperlinks and downloadable files. Some of the R packages used are rmarkdown, knitr, ggplot, plotly, flexdashboard, and shiny. The aim is to practise with different forms of dashboards (Flexdashboard, Shiny, Flexdashboard-Shiny) and the suitable hosting platforms (personal website, RPubs, Binder, Shinyapps, and custom servers).



### Flexdashboard

- background: https://rmarkdown.rstudio.com/flexdashboard/ 

- examples: https://rmarkdown.rstudio.com/flexdashboard/examples.html 

- code demo: https://rpubs.com/pcbernabeu/Butterfly-species-richness-in-LA 



### Flexdashboard + Shiny

- background: https://rmarkdown.rstudio.com/flexdashboard/shiny.html 

- examples: https://rmarkdown.rstudio.com/flexdashboard/shiny.html 

- code demo: https://pablo-bernabeu.shinyapps.io/experimental-data-simulation 



### Tasks



RStudio Cloud project (same as above): https://rstudio.cloud/project/1520963  



#### Materials 



 1.  R Markdown doc: https://rpubs.com/pcbernabeu/R-Markdown-Madison-parks 

 Code: https://github.com/pablobernabeu/Data-is-present/blob/master/examples-documents-dashboards/R%20Markdown/R-Markdown-amidst-Madison-parks.Rmd



 2.  Flexdashboard: https://rpubs.com/pcbernabeu/Butterfly-species-richness-in-LA 

 Code: https://github.com/pablobernabeu/Data-is-present/blob/master/examples-documents-dashboards/Dashboards/Flexdashboard/Butterfly-species-richness-in-LA.Rmd 



 3.  Your own data, or any other data, if you like. 



 N.B. Flexdashboard is actually a type of R Markdown document, even if we're referring to them separately here. 

 Options (several possibilities, subject to preference and experience) 



 Tasks are ordered from easier to more difficult below. Please choose freely (or even create your own task, if you prefer). Feel free to ask the presenter any questions. 

 

#### Task 1



In any of the code chunks, set the chunk options `warning` and `message` both to TRUE. What's the result? 

 

#### Task 2



Change the labels of the code chunks (e.g., largest-parks) as well as the calls to them in the cross-references (e.g., /@ref(tab:largest-parks)). You can replace the labels with any other word or words you like. 



#### Task 3



In the R Markdown document, please look at the cross-reference in the last code chunk. Modify the options of that chunk in these ways: 



 1. Change the cross-reference (\@...) to that of the figure ('park-types'), instead of the table as it is now. 

 2. Change the options to display the plot but not the code. 



#### Task 4



What changes in the R Markdown doc if you delete the argument shown below this line from the plot code? Hint: notice that the plot is an interactive plotly plot. 



```

 , tooltip = 'text' 

```



#### Task 5



Insert an image into an R Markdown of Flexdashboard document, using either Markdown (https://guides.github.com/features/mastering-markdown/) or HTML (https://www.w3schools.com/tags/tag_img.asp) code. 



#### Task 6



In the code for the table, remove the `%>% head(20)` bit to display the entire data. Then use the DT package to present the table nicely, and to allow the download of the data (https://rstudio.github.io/DT/). 



#### Task 7



Create an R Markdown template or a Flexdashboard template, and apply some of the options we've viewed. For this purpose, you may use some of the classic built-in data in R (http://www.sthda.com/english/wiki/r-built-in-data-sets). 



#### Task 8



Create an R Markdown or Flexdashboard document presenting some of your own data. 



#### Task 9



Transform the R Markdown document into a Flexdashboard; then, vice versa, transform the Flexdashboard into an R Markdown document. For this purpose, please draw on the background links, and of course, the two documents themselves which serve as templates. This exercise is largely a matter of transposing code across templates. 



#### Task 10



Add Shiny user inputs to a Flexdashboard  (https://rmarkdown.rstudio.com/flexdashboard/shiny.html). Find out about Shiny and user inputs in the following section! 







## Shiny



#### Books: 

- https://mastering-shiny.org

- https://engineering-shiny.org/



#### Examples of Shiny apps 

- https://shiny.rstudio.com/gallery 

- https://pablobernabeu.shinyapps.io/ERP-waveform-visualization_CMS-experiment/

- https://mybinder.org/v2/gh/flor14/shinyssd/binder?urlpath=shiny/shinyssd/inst/shiny/ (https://github.com/flor14/shinyssd ) 



### Tasks



RStudio Cloud (different from the one above): https://rstudio.cloud/project/1514617



I have prepared different kind of exercises. Are you new to Shiny? This is a good exercise to start:



Allow the user the option of changing the y axis too, adding a new set of radiobuttons. Let the user to select among the options petal length and sepal length. 

      Hint: Remember to check how the variable names in the iris dataset are written.



RStudio Cloud -> iris folder



If you have some experience or you finish quickly the first task:

I have 3 examples of this same app that are not working. Could you fix the apps? 

The apps are in the folders called 



RStudio cloud ->

shiny_ex1

shiny_ex2

shiny_ex3







## Binder



Did you know that you can enable public access to your data and analysis code in RStudio, on a simple internet browser? There are various options for this, and one of the most accessible ones is Binder (https://mybinder.org). We’ll look at Binder’s requirements and possibilities. 



RStudio environment example: http://mybinder.org/v2/gh/binder-examples/r/master?urlpath=rstudio

Dashboard environment example: https://mybinder.org/v2/gh/pablobernabeu/Modality-switch-effects-emerge-early-and-increase-throughout-conceptual-processing/eab65b392a8817454824f11c4efacea2e8a927f3?urlpath=shiny/Shiny-app/ 



#### Git: https://happygitwithr.com/



#### Binder

- https://the-turing-way.netlify.app/welcome

- https://github.com/binder-examples/r



Example of Shiny app in GitHub repo

https://github.com/flor14/shiny_carpentrycon.git



#### Binder URLs



Shiny: https://mybinder.org/v2/gh///?urlpath=shiny//

RStudio IDE: https://mybinder.org/v2/gh///?urlpath=rstudio



#### Binder URLs for the example 



Shiny: https://mybinder.org/v2/gh/flor14/shiny_carpentrycon/master?urlpath=shiny/iris/

RStudio IDE: https://mybinder.org/v2/gh/flor14/shiny_carpentrycon/master?urlpath=rstudio