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I am currently working on the argument project. I've been attempting

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all of the labs.
For the pokemon labe, as stated in that commit message, I understood the concepts and
knew what I wanted to do with the code, but wasnt always successful in writing it correctly.

I'm worried about the same thing in the arguement project. I'm limiting my dataset to the first 15 rows to make it more
managable for me.
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Heather
2025-10-27 20:07:52 -04:00
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@@ -10,30 +10,53 @@ argument.
*This should be the big picture question that you ask; use at least 5 *This should be the big picture question that you ask; use at least 5
sentences to describe why you are interested in it.* sentences to describe why you are interested in it.*
My overarching question is whether it is possible to find a healthy option at a fast food place.
By healthy, I will look at how many of the calories are made up of fat. I'm interested in exploring this because I generally
do not eat at fast food places, but, on the rare occasion that I do, I usually just opt for a burger or chicken sandwich.
When I was scrolling through looking for data this caught my eye. The dataset focuses on 6 of the largest and most popular fast food places. I will focus on the first 15 rows to mak it more managable for me.
### What specific research questions will you investigate? ### What specific research questions will you investigate?
*List 2-4 specific research questions. Each should be answerable *List 2-4 specific research questions. Each should be answerable
using your data set.* using your data set.*
Question 1 - For the first 15 rows, which food item has the most/least calories
Question 2 - From the first 15 rows, which food has the most/least fat
Question 3- which has the most/least sodium
## Data source ## Data source
Kaggle.com
### What data set will you use to answer your overarching question? ### What data set will you use to answer your overarching question?
My dataset is from Kaggle.com and is title nutritional-fast-food-dataset
https://www.kaggle.com/datasets/tan5577/nutritonal-fast-food-dataset/data
*Give the title of your data set and provide a link to your data.* *Give the title of your data set and provide a link to your data.*
### Where is this data from? ### Where is this data from?
Data on fast food nutrition was collected from restaurant menus, official nutritional labels, and verified food databases. The information includes calories, macronutrients (carbohydrates, proteins, fats), and micronutrients. Reliable sources and standardized measurement methods were used to ensure accuracy.
*Describe the source of the data set--not just where you downloaded it, but *Describe the source of the data set--not just where you downloaded it, but
the person or organization who gathered the data. Explain why you trust them.* the person or organization who gathered the data. Explain why you trust them.*
### What is this data about? ### What is this data about?
I'm focusing on the first 15 rows and columns dealing with total fat, sodium and calories
*Describe the nature of the data in the dataset, including the number of rows *Describe the nature of the data in the dataset, including the number of rows
and some of the columns which will be important to you.* and some of the columns which will be important to you.*
## Methods ## Methods
I will use the analysis in the dataset to compare and contrast the amount of fat, sodium and calories.
### How will you use your data set to answer your quantitative questions? ### How will you use your data set to answer your quantitative questions?
For question 1 and 2 I plan on using a chart to help visually compare (in question1 ) which food has the most/least calories and (question 2) which food has the most/ least amount of fat
Question 3 will use a table to help visually compare which foods have th emost/ least sodium
*For each research question, explain what you will do with the data set *For each research question, explain what you will do with the data set
to answer the question, and how you will present your answer (e.g. a chart or a table).* to answer the question, and how you will present your answer (e.g. a chart or a table).*