Assignment #10: Building Your Own R Package

Assignment #10: Building Your Own R Package


Purpose

The Friedman package is designed to help students like me and researchers perform efficient exploratory data analysis in R. It provides tools for data cleaning, summarizing, and visualizing datasets, making common workflows faster and easier. The package is aimed at beginners and intermediate R users who want a consistent set of functions for analyzing data without having to write repetitive code.

Key Functions

Here are some planned functions:

  • clean_data(): Standardizes column names, handles missing values, and formats data frames for analysis.
  • summarize_data(): Provides summary statistics for numeric and categorical columns, including counts, means, medians, and standard deviations.
  • plot_distribution(): Generates histograms, density plots, and boxplots for selected variables.
  • compare_groups():  Performs group-wise comparisons and outputs summary tables and plots.

DESCRIPTION Choices

Dependencies (Imports): I included ggplot2 and dplyr because they are commonly used for plotting and data manipulation, which Friedman relies on.

License: CC0, to make the package freely available for educational use.

Authors: My name and email are listed as aut (author) and cre (creator). This makes me responsible for the package and credits me for development.

LazyData: Set to TRUE to allow inclusion of sample datasets for examples and testing



GitHub Link: https://github.com/ygraham-code/r-programming-assignments.git


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