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Journey Through R Programming: Week 1

 


Journey Through R Programming: Week 1






Introduction

Welcome to my blog! As part of my Open Source R course with Professor Alon Friedman at the University of South Florida, I’m excited to document my weekly progress in learning R programming.

A bit about me: I’m currently pursuing a Master’s in Bioinformatics & Computational Biology, following an undergrad in Biotechnology. My programming journey began with Python through the “100 Days of Code: The Complete Python Pro Bootcamp” on Udemy, which included around 8 mini projects. This experience has made transitioning to R a bit smoother, as many concepts overlap.

To support my learning, I’m using the book The Art of R Programming and the edX course Data Science: R Basics from Harvard University. These resources have been invaluable in deepening my understanding of R.


Summary


1. Function Creation

Objective:

Create a function to count the number of odd numbers in a vector.

Code:






What I Learned:

  • The modulus operator (%%) helps identify odd numbers.
  • Using loops in R allows you to process each element in a vector.

2. String Operations

Objective:

Manipulate and split strings in R.

Code:

What I Learned:

  • paste() joins multiple strings into one.
  • strsplit() splits a string based on a delimiter.


3. Matrix Manipulation

Objective:
Create and access elements in matrices.

Code:




What I Learned:

  • cbind() combines vectors into a matrix.
  • Such indexing allows for easy retrieval of specific elements.


4. Exploring Data with dslabs

Objective:

Analyze the murders dataset from the dslabs package.

Code:





What I Learned:

  • summary() provides a quick overview of the dataset.
  • Functions like str() and head()/tail() help understand data structure and content.


5. Data Visualization

Objective:
Create various plots to visualize data.

Code:

                                       

What I Learned:

  • Scatterplots, histograms, and boxplots are useful for visualizing different aspects of the data, with each function serving the data in a new way.


Additional Resources

For more detailed notes from my R programming journey, check out my comprehensive notes here. Additionally, you can explore my GitHub repository with all my work and projects here.


Conclusion

The first week of exploring R has been both informative and engaging. With the help of The Art of R Programming and the edX course Data Science: R Basics, I’m excited to continue deepening my understanding and skills. Stay tuned for more updates as I progress through the course!



Location: 14601 Gilligan's Way, Tampa, FL 33613, USA

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