Assignment #10: Building Your Own R Package

 # Proposal for My R Package: Friedman


For this project, I am proposing an R package called **Friedman**. The

purpose of this package is to provide beginner-friendly tools for simple

data analysis and visualization in R. Many students and new R users

struggle with repetitive tasks such as cleaning datasets, calculating

summary statistics, and creating clear visualizations. This package will

help make those tasks easier by grouping useful functions into one

simple package.


The main audience for this package is students, beginner analysts, and

anyone who wants a more straightforward way to explore data in R.

Instead of writing long code repeatedly, users will be able to call

functions from Friedman to quickly summarize and visualize their data.

This makes the package especially useful for class assignments, small

research projects, and practice with R programming.


Some of the key functions I plan to implement include:


- `clean_data()` – removes missing values or standardizes column names.

- `summary_stats()` – calculates mean, median, standard deviation,

  minimum, and maximum values.

- `plot_histogram()` – creates simple histograms for numeric variables.

- `plot_scatter()` – creates scatterplots for comparing two variables.

- `group_summary()` – summarizes a variable by category using grouped

  statistics.


When creating the DESCRIPTION file, I chose each field carefully. I used

`0.0.0.9000` for the version because the package is still under

development. In the `Authors@R` field, I listed myself as both the

author and creator so the metadata is machine-readable. For

dependencies, I kept `Depends` minimal by only including

`R (>= 3.1.2)`, which is recommended practice. I added `ggplot2` and

`dplyr` in `Imports` because they will support plotting and data

manipulation functions in the package. I selected the `CC0` license so

the package can be shared openly without restrictions. I also included

`LazyData: true` because I may include datasets in the package later.


This project will help me better understand how R packages are

structured, how metadata works in the DESCRIPTION file, and how to

organize code into a reusable format. It also gives me practice with

GitHub by publishing the package scaffold online and documenting the

project through my blog.


## GitHub Repository

Replace this with your real GitHub link after you upload the package:


`https://github.com/yourusername/Friedman`

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