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Turn messy R scripts into
clean
interactive
reproducible
online
reports

An interactive mini course helping R developers be So. Much. More. efficient at data analysis.

YHTaught by Yan Holtz

The struggle is real

For the 10th time you open your script called my_analysis_final2.R.

You're ready for a last run, creating a few graphs that you will have to copy paste to your report, together with some crucial statistical test results.

๐Ÿ˜ฑ Bummer!

Did you really write this? It is barely readable. There are no comments. Some lines are so long you can't see their ends. It basically looks like a labyrinth of duplication, making even the smallest changes an agonizing ordeal.

But wait ๐Ÿค”. Where is the awesome piece of code you wrote the other day? Perhaps in another version of the script...

Nevermind, let's email those results to the team, it is not too bad already. At least you did not lose your script like last time.

Wait.. No!

You run the analysis on data_clean.csv instead of data_final.csv. Results are all wrong! ๐Ÿ™ˆ

There is an easier way!

I remember those good old days so well.

But some tools can make your life 100x easier ๐ŸŽ‰

Quarto transforms your code in a stunning report. HTML widgets integrate interactive charts in it. Git tracks all your changes.Github hosts your work and transforms it in a website for free.

In this mini course, I provide you with an efficient pipeline for your daily data analysis work with R. An elixir of the best tools, tips and tricks.

I promise there won't be any coming back.

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๐Ÿ”ฅ Let's build a

Productive R Workflow

Get a Clean, Interactive, Reproducible, Online report

Reproducible

Fork the project. Click 1 button. โ†’ Everything runs again.

Clean

Use the theme provided by the course. Plus some web dev tips.

Online

Code and report are available for free on the web. For free.

Interactive

Include tabs, interactive charts, links, maps, and more.

โค๏ธ What people are sayingโ€ฆ โค๏ธ

Yan's recent talk showcased his R programming course, brilliantly tailored for beginners.

Leveraging his deep expertise in the R ecosystem and common challenges, the course is a perfect launchpad to boost productivity in R.

A picture of a testimonial
Marylene Henry ๐Ÿ‡ซ๐Ÿ‡ท

Project Leader, French National Institute of Statistics

R is a fantastic but permissive language; it's hard not to make errors in reproducibility.

What I loved about Yan's talk is his way of simply presenting the best R practices that can be game-changing for your statistical work even if you are a beginner!

A picture of a testimonial
Frida Kronquist ๐Ÿ‡ฉ๐Ÿ‡ฐ

Associate Risk Consultant, Marsh Advisory Nordics

I only finished module 2 lesson 3 so far, but already feel like I have got value for my money.

The course is informative, yet easy to follow. Yan and the welcoming community on Discord help me when I need it. I look forward to learning even more from Yan as I progress through the course.

A picture of a testimonial
Vinรญcius Ferreira ๐Ÿ‡ง๐Ÿ‡ท

Revenue Growth Specialist, Adevinta

R resources are abundant online, but Yan's project truly enhanced my skills.

Thanks to it, I transitioned from simple R knowledge to mastering speed, reliability, and clarity in my storytelling.

This is the most changing game I've been to in terms of dataviz and comprehension .

A picture of a testimonial
Wim van Saase ๐Ÿ‡ณ๐Ÿ‡ฑ

Finance consultant, Eiffel

The course provides concrete tools to convert the analyses you do in R into more readable and shareable reports. You get an A to Z method of creating a reproducible project!

The focus is on R, but the creative mind can also apply this elsewhere.

The whole thing is brought into small directly applicable modules, which immediately have a big impact on your workflow.

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Bertha Rohenkohl ๐Ÿ‡ฌ๐Ÿ‡ง

Postdoctoral economist, Institute for the Future of Work

This is such an amazing course that will help you streamline those R projects and develop good data practices!

So happy to have joined the first group, it made my life so much easier!

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Yann Say ๐Ÿ‡จ๐Ÿ‡ญ

R and Data specialist, IMPACT Initiatives

Productive R workflow is very focus and straight to the point. It gives practical tips that can be immediately applied.

Format is friendly whether you have 10 minutes or an hour to learn. I recommend it to anyone who is starting his/her data journey to boost their productivity!

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David Lefebvre ๐Ÿ‡จ๐Ÿ‡ฆ

Postdoctoral Fellow, University of British Columbia

Productive R Workflow has revolutionized the way I manage my scripts.

My scripts are now organized and easier to share and maintain. Thanks to this course, I now have a structured system in place that enhances collaboration and ensures efficiency in my R projects.

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Julian Busch ๐Ÿ‡จ๐Ÿ‡ญ

Portfolio Manager Multi Asset Solutions, Fisch Asset Management AG

A very much to the point, bite-sized course that will provide you and your employees with a best-practice workflow for your R projects.

It uses one of Rstat's classic datasets to explain all concepts clearly and consistently.

If you are working with R in practice, this course is essential!

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Restu Restuadi ๐Ÿด๓ ง๓ ข๓ ฅ๓ ฎ๓ ง๓ ฟ

R: search Associate in Computational Biology, Imperial College London

The course is both visually appealing and incredibly interactive โ€“ a winning combination! The lessons flow seamlessly, mirroring the real-world way I use R in my work.

There's no shortage of great R programming courses, but this one fills a crucial gap.

It teaches you how to manage and maximise productivity with R. As a bioinformatician and consulting-statistician juggling multiple research projects, this course has been an absolute lifesaver.

What I liked the most about the course was the alert rhythm of quickly covering a vast amount of content.

It increases the appetite for trying out new things based on this foundation alone. Thank you, Yan!

This is exactly what I needed.

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Benjamin David ๐Ÿ‡ซ๐Ÿ‡ท

Market Risk Analyst, Arkรฉa Investment Services

Very neat course! It's very well structured and helps you adopt good coding practices quickly.

The UX with a signifiant part of gamification is absolutely perfect thanks to the website developed by Yan himself.

This helps me stay motivated and follow the course from A to Z!

Productive R Workflow is a quintessential component of the learning journey for beginners, as well as intermediate users who want to start applying best data and coding practices.

This course empowers you to create shareable, reproducible, and debuggable code. Plus, itโ€™s an excellent stepping stone if you havenโ€™t used Quarto or GitHub yet!

It feels so nice when the ideas click in your mind, and you realize, โ€œthis is how it should be done.โ€ ๐Ÿš€

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Ivan Osinnii ๐Ÿ‡จ๐Ÿ‡ญ

Postdoc, University of Basel

Yan Holtz's new course offers an accessible guide to streamlining R data analyses using the evolving tideverse, R-markdown, and Quarto tools.

The course is beautifully sequential, breaking down complex concepts into bite-size tips and tools rather than overwhelming learners with grandiose ideas.

You can track your progress in short, manageable intervals and enjoy frequent pauses without losing your train of thought.

Perfect for learning at your own pace and seeing visible improvements every 15-30 minutes.

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Luke Arundel ๐Ÿด๓ ง๓ ข๓ ฅ๓ ฎ๓ ง๓ ฟ

Research officer, Centre for Transforming Access and Student Outcomes in Higher Education

Yan's course is incredibly valuable and maps out โ€” unlike any other resource I've come across โ€” how to work more efficiently in R.

I can only imagine the time I would have saved if I'd had all these lessons compiled in one place when I first started using R.

The module on cleaning code alone would add a huge amount of value to the workflow of almost everyone I know who uses or is looking to learn R.

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Giandomenico Bisaccia ๐Ÿ‡ฎ๐Ÿ‡น

Health Economics Student, London School of Economics

This course makes it easy to grasp various concepts about Quarto reporting which are not easily found in the official documentation or elsewhere.

What I found particularly useful was being guided through each and every step. The course offers something to be learned for both beginners and intermediate users.

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Cedric Vidonne ๐Ÿ‡จ๐Ÿ‡ญ

Health Economics Student, London School of Economics

While I already had a grasp on basic R concepts, the course taught me invaluable skills in organizing my work and ensuring reproducibility.

It's a must for anyone looking to optimize their R projects.

Looking forward for the future Quarto tips and more advanced bonus sections!

๐ŸŽฎ Interactive learning experience ๐ŸŽฎ

This course is not a book or a set of boring videos! I tried to make learning fun and interactive. For instance, check your R knowledge with this quizz! ๐Ÿ˜€.

What is the primary use of ggplot2?

Perform statistical computations.
Create publication-quality visualizations.
Manage and manipulate data frames.
Interface with databases.

What is the purpose of StyleR?

It adds additional styling options to ggplot2 graphs.
It is used for creating styled R Markdown documents.
It automatically styles R code according to specified guidelines.
It is a package for theming Shiny applications.

In a Quarto document, how do you create an executable R code chunk?

```{r} ... ```
```[r] ... ```
<r> ... </r>
<code lang='r'> ... </code>

In R, what is the correct syntax to define a function named calculateSum that takes two arguments and returns their sum?

function calculateSum(x, y) { return x + y; }
def calculateSum(x, y): return x + y
calculateSum <- function(x, y) { return(x + y) }
function calculateSum(x, y) = x + y

What is the Tidyverse?

An R package for statistical analysis.
A collection of R packages designed for data science that share common philosophies.
A new programming language based on R.
A graphical user interface for R.

Name three core principles that the Tidyverse packages adhere to.

Consistency, readability, and usability.
Complexity, dependency, and variety.
Speed, automation, and scalability.
Randomness, flexibility, and modularity.

How do you install a package from GitHub in R?

install.packages(github: 'username/repository')
install_github('username/repository')
github_install('username/repository')
get_github('username/repository')

Which package in the Tidyverse is primarily used for data manipulation?

ggplot2
readr
dplyr
forcats

In a Quarto document, how do you link to an external CSS file?

use_css('path/to/style.css')
<link rel='stylesheet' href='path/to/style.css'>
css: 'path/to/style.css'
style: 'path/to/style.css'

How do you update your local repository to match the remote repository in Git?

git update remote
git refresh
git pull
git download

What shortcut is used to run a line of R code in RStudio?

Ctrl + Enter
Alt + R
Shift + Enter
Ctrl + R

How do you write text in bold in Markdown?

Using <b>...</b> tags
Enclosing text in *asterisks*
Enclosing text in **double asterisks**
Using the :bold: syntax

Is Shiny required to create a document with interactive graphs?

Yes, Shiny is always required.
No, there are other options like ggiraph or plotly.
Only if the graphs are complex.
Shiny is not compatible with interactive graphs.

Do you need to pay to share your data analysis report via GitHub?

Yes, GitHub charges for hosting data reports.
No, GitHub offers free repositories for data sharing.
Only for private repositories.
Sharing data reports is not allowed on GitHub.

Is it possible to read an xlsx file in R without converting it to CSV format?

No, conversion to CSV is mandatory.
Yes, using packages like readxl or openxlsx.
Only with special software outside of R.
Reading xlsx files is not supported in R.

Is building an interactive graph in R typically a complex task requiring at least 100 lines of code?

Yes, it always requires extensive coding.
No, it can be achieved with fewer lines using specific packages.
Interactive graphs cannot be created in R.
It depends on the complexity of the graph.

Should an R script always begin with the setwd() function?

Yes, it's a mandatory practice.
No, it's not recommended to use setwd() in scripts.
Only if the script is run on multiple machines.
setwd() is not a function in R.

What role does CSS play in relation to Quarto documents?

CSS is used for data analysis in Quarto.
CSS enhances the visual appearance of Quarto documents.
CSS is irrelevant to Quarto.
CSS is used to write R code in Quarto.

What is GitHub Desktop?

A cloud storage service provided by GitHub.
A graphical interface for managing Git repositories.
A text editor developed by GitHub.
An operating system based on GitHub.

Is RStudio required to use Quarto?

Yes, RStudio is necessary for Quarto.
No, Quarto can be used independently of RStudio.
Quarto only works with RStudio Cloud.
Quarto and RStudio are the same thing.

๐Ÿ‘‹ Hi! I'm Yan Holtz.

Senior Software Engineer in โค๏ธ with educational content.

A picture of Yan Holtz

With over a decade of hands-on experience in data analysis and software engineering, I've had the privilege of working in various tech companies and research labs globally.

You might recognize me from my widely-visited educational platforms like the R, Python, D3.js, and React Graph Galleries, as well as my award-winning projects Data-to-Viz.com and Dataviz-Inspiration.com.

Frequently, people approach me seeking guidance on their R journey. This course is my comprehensive, well-structured response, born from a broad and deep understanding of the field.

Spend just a few hours of your time with me! I guarantee that the productivity gains will quickly offset the initial investment ๐Ÿ”ฅ.

A picture of a testimonial

Yan's recent talk showcased his R programming course, brilliantly tailored for beginners.

Leveraging his deep expertise in the R ecosystem and common challenges, the course is a perfect launchpad to boost productivity in R.

Vincent Guyader ๐Ÿ‡ซ๐Ÿ‡ท

CTO of ThinkR

A picture of a testimonial

I only finished module 2 lesson 3 so far, but already feel like I have got value for my money.

The course is informative, yet easy to follow. Yan and the welcoming community on Discord help me when I need it. I look forward to learning even more from Yan as I progress through the course.

Frida Kronquist ๐Ÿ‡ฉ๐Ÿ‡ฐ

Associate Risk Consultant, Marsh Advisory Nordics

๐Ÿ”ฅ Pricing

The course was released in March 2024 and over 300 people have enrolled already. An updated version is coming soon with a significant price increase. Enroll now to secure the current rate!

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149$

299$

Early Access

Price will double soon


Lifetime Access
Discord community
Interactive learning experience
30+ lessons
Certificate of completion
Personalized feedback on Discord

๐Ÿ’ธ Discounts

A picture of a testimonial

R is a fantastic but permissive language; it's hard not to make errors in reproducibility.

What I loved about Yan's talk is his way of simply presenting the best R practices that can be game-changing for your statistical work even if you are a beginner!

Marylene Henry ๐Ÿ‡ซ๐Ÿ‡ท

Project Leader, French National Institute of Statistics

A picture of a testimonial

R resources are abundant online, but Yan's project truly enhanced my skills.

Thanks to it, I transitioned from simple R knowledge to mastering speed, reliability, and clarity in my storytelling.

This is the most changing game I've been to in terms of dataviz and comprehension .

Vinรญcius Ferreira ๐Ÿ‡ง๐Ÿ‡ท

Revenue Growth Specialist, Adevinta

Frequently asked questions