My Awesome R Package

Project Title: My Awesome R Package Link to heading

Subtitle: A robust tool for data manipulation and visualization

Overview: I developed the “My Awesome R Package” to streamline complex data manipulation and visualization tasks for data scientists. This package simplifies the workflow and enhances productivity by providing intuitive functions and customizable plots.

Role: Lead Developer

Date: January 2020 - June 2020

Objectives and Challenges:

  • Objectives:

    • Create an easy-to-use package for data manipulation.
    • Develop customizable and aesthetically pleasing visualizations.

  • Challenges:

    • Ensuring compatibility with existing R packages.
    • Optimizing performance for large datasets.

Approach and Tools:

  • Methodology:

    • Followed the Tidyverse principles for data manipulation.
    • Used ggplot2 for visualization creation and customization.

  • Tools and Technologies:

    • R, RStudio, ggplot2, dplyr, tidyr, roxygen2

Results and Impact:

  • Outcomes:

    • Successfully created a package with 15 functions for data manipulation and 10 customizable plots.
    • The package was downloaded over 5,000 times in the first month and received positive feedback from the community.

  • Impact:

    • Improved data manipulation efficiency by 50% for users.
    • Enabled users to create publication-ready visualizations with minimal effort.

Visuals and Examples:

Package Example

# Example Code Snippet
library(myawesomepackage)
data <- read.csv("data.csv")
clean_data <- clean_data(data)
plot <- create_plot(clean_data)
print(plot)

Reflection and Learnings:

  • Lessons Learned:

    • Gained deeper insights into R package development and maintenance.
    • Improved skills in creating comprehensive documentation and user guides.

  • Future Work:

    • Plan to add more functions for data wrangling and explore interactive plot capabilities.

Links and References: