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Apr 21 • 10 tweets • 8 min read Twitter logo

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1/ 📚 Advanced R Package Development: Best Practices and Tips 🛠️ Explore the process of creating, documenting, and testing your own R packages like a pro! #rstats #AdvancedR #PackageDevelopment #DataScience

2/ 🏗️ Package Structure: Organize your package effectively by:

⚫️Using usethis::create_package() to set up the structure
⚫️Organizing functions in R/ directory
⚫️Placing data in data/ or extdata/ directories
⚫️Adding vignettes and README for documentation
#rstats #datascience

3/ 📝 Documentation: Make your package user-friendly by:

⚫️Writing clear, concise function descriptions
⚫️Using roxygen2 for function documentation
⚫️Creating package-level documentation with pkgdown
⚫️Writing vignettes to demonstrate usage
#rstats #datascience #AdvancedR

4/ 🧪 Testing: Ensure the reliability of your package by:

⚫️Writing unit tests with testthat
⚫️Using usethis::use_test() to set up tests
⚫️Adding test data in tests/testthat/ directory
⚫️Running tests with devtools::test()
#rstats #datascience #AdvancedR

5/ 📊 Continuous Integration: Automate your testing process with:

⚫️GitHub Actions for R package checks and tests
⚫️Using usethis::use_github_action_check_standard() to set up the workflow
⚫️Monitoring build status with badges in README
#rstats #datascience #AdvancedR

6/ 🛡️ Version Control: Keep track of your package's development with:

⚫️Git for version control
⚫️GitHub, GitLab, or Bitbucket for remote repositories
⚫️Following a clear branching and merging strategy
#rstats #datascience #AdvancedR

7/ 🔄 Dependency Management: Manage your package's dependencies by:

⚫️Listing them in the DESCRIPTION file
⚫️Using renv for project-specific library management
⚫️Keeping dependencies minimal to improve portability
#rstats #datascience #AdvancedR

8/ 🚀 Deployment: Share your package with the world by:

⚫️Submitting to CRAN for wide distribution
⚫️Using devtools::release() for CRAN submission
⚫️Hosting on GitHub for easy installation with remotes or devtools
#rstats #datascience #AdvancedR

9/ 📚 Resources: Learn more about advanced R package development with these books and articles:

"R Packages" by Hadley Wickham
"Advanced R" by Hadley Wickham
"Efficient R programming" by Matt Dowle
#rstats #datascience #AdvancedR

10/ 🎉 In conclusion, mastering advanced R package development techniques will help you create professional, robust, and user-friendly packages. Keep exploring these best practices to elevate your package development skills! #rstats #AdvancedR #datascience

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Twitter author

Apr 23

1/🧵✨Occam's razor is a principle that states that the simplest explanation is often the best one. But did you know that it can also be applied to statistics? Let's dive into how Occam's razor helps us make better decisions in data analysis. #OccamsRazor #Statistics #DataScience

2/ 📏 Occam's razor is based on the idea of "parsimony" - the preference for simpler solutions. In statistics, this means choosing models that are less complex but still accurate in predicting outcomes. #Simplicity #DataScience

3/ 📊 Overfitting is a common problem in statistics, where a model becomes too complex and captures noise rather than the underlying trend. Occam's razor helps us avoid overfitting by prioritizing simpler models with fewer parameters. #Overfitting #ModelSelection #DataScience

Read 6 tweets

Twitter author

Apr 22

🧵1/10 - Law of Large Numbers (LLN) in R 📈

Hello #Rstats community! Today, we're going to explore the Law of Large Numbers (LLN), a fundamental concept in probability theory, and how to demonstrate it using R. Get ready for some code! 🚀

#Probability #Statistics #DataScience

🧵2/10 - What is LLN? 🧐

LLN states that as the number of trials (n) in a random experiment increases, the average of the outcomes converges to the expected value. In other words, the more we repeat an experiment, the closer we get to the true probability.

#RStats #DataScience

🧵3/10 - Coin Flip Example 🪙

Imagine flipping a fair coin. The probability of getting heads (H) is 0.5. As we increase the number of flips, the proportion of H should approach 0.5. Let's see this in action with R!

#RStats #DataScience

Read 11 tweets

Twitter author

Apr 22

1/🧵 Welcome to this thread on the Central Limit Theorem (CLT), a key concept in statistics! We'll cover what the CLT is, why it's essential, and how to demonstrate it using R. Grab a cup of coffee and let's dive in! ☕️ #statistics #datascience #rstats

2/📚 The Central Limit Theorem states that the distribution of sample means approaches a normal distribution as the sample size (n) increases, given that the population has a finite mean and variance. It's a cornerstone of inferential statistics! #CLT #DataScience #RStats

3/🔑 Why is the CLT important? It allows us to make inferences about population parameters using sample data. Since many statistical tests assume normality, CLT gives us the foundation to apply those tests even when the underlying population is not normally distributed. #RStats

Read 12 tweets

Twitter author

Apr 22

[1/11] 🚀 Level Up Your R Machine Learning Skills with These Lesser-Known #RPackages! In this thread, we'll explore 10 hidden gems that can help you optimize your #MachineLearning workflows in R. Let's dive in! 🌊 #rstats #datascience

[2/11] 📊 caretEnsemble: Model ensembling with caret - Combine multiple models with ease and boost your model performance using this powerful package. #rstats #datascience #machinelearning
🔗 cran.r-project.org/web/packages/c…

[3/11] 📈 finalfit: Create regression model tables - Quickly generate publication-ready tables for regression models with #finalfit. Simplify reporting and communication of your results! #rstats #datascience #machinelearning
🔗 cran.r-project.org/web/packages/f…

Read 12 tweets

Twitter author

Apr 22

1/ 💼 R in Production: Deploying and Maintaining R Applications 🏭 Learn how to deploy, monitor, and maintain R applications in production environments for robust, real-world solutions. #rstats #AdvancedR #DataScience

2/ 🌐 Web Apps: Deploy interactive web applications with Shiny:
•Shiny Server or Shiny Server Pro for self-hosted solutions
•RStudio Connect for an integrated platform
•shinyapps.io for hosting on RStudio's servers
#rstats #AdvancedR #DataScience

3/ 📦 R APIs: Create and deploy RESTful APIs using R with:
•plumber for building, testing, and deploying APIs
•OpenCPU for creating scalable, stateless APIs
•RStudio Connect for hosting and managing your APIs
#rstats #AdvancedR #DataScience

Read 10 tweets

Twitter author

Apr 22

1/ 🌐 Web Scraping and Text Mining in R: Unlocking Insights 🔍 Learn advanced web scraping techniques and text mining tools to extract valuable insights from online data. #rstats #AdvancedR #TextMining #DataScience

2/ 🕸️ Web Scraping: Extract data from websites using powerful R tools:
•rvest for HTML scraping and parsing
•httr for managing HTTP requests
•xml2 for handling XML and XPath queries
•RSelenium for scraping dynamic web content
#rstats #datascience #AdvancedR

3/🧪 Advanced Web Scraping Techniques: Go beyond basic scraping with:
•Setting up custom headers and cookies with httr
•Handling pagination and infinite scrolling
•Throttling requests to avoid getting blocked
•Using proxy servers to bypass restrictions
#rstats #AdvancedR

Read 10 tweets

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