Building Your Own R Package


I would like to make a package that allows culinary students, chefs, or even just people cooking at home, to analyze and filter thousands of different recipes in a more simplified manner. It would allow them to find specific recipes based on ingredients, preparation time, type of meal, etc. It would also generate visualizations to easily compare different types of recipes based on their characteristics. This package will help them save time, explore new recipes, and view trends.

Key functions that I would include are finding a specific recipe (find_recipe), outputting a random recipe (random_recipe), filtering the recipes by ingredients you have (filter_ingredient), and creating graphs to compare recipes by different characteristics (plot_time). I will think of more after further exploring the dataset.

I hope this proposal meets the final project requirements. I was struggling to come up with an idea and realized I love to cook, but I often struggle with new things to make or what I could make with the ingredients I have on hand, so this project would help others who share the same struggle. If I should meet with you to workshop a better package idea, I can also do that.

My DESCRIPTION file for my package:

Package: Randall
Title: Analyzing Recipes and Their Characteristics
Version: 0.0.0.9000
Authors@R: 
    person("Destini", "Randall", "destinirandall@yahoo.com", role = c("aut", "cre"))
Description: This package provides a dataset of thousands of recipes and uses functions for filtering, comparing, and visualizing them. Users can search for specific recipes, generate random ones, and even filter them based on what ingredients they own or how much time they have. There is also a function allowing users to graph recipes and compare their characteristics. This package is intended for culinary students, chefs, and anyone interested in exploring recipe data.
Depends: R (>= 3.1.2)
Imports: ggplot2, dplyr, stringr
License: CC0
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.3
LazyData: true

Title, description, package, and author, I changed to represent me, and what my package is supposed to do regarding recipes. Some of these fields I kept the same, like version, depends, license, and encoding, because they were the recommended options. I chose ggplot2, dplyr, and stringr for imports since dplyr will be used when filtering, ggplot2 will be used to make the visualizations, and stringr helps search for ingredients by their string. LazyData is true because there will be the recipe dataset included in the package. 

GitHub Repo: https://github.com/Ultimaterock78/Friedman 

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