https://github.com/2kabhishek/pyramen
Data Analysis for Ramen 🍜💹
https://github.com/2kabhishek/pyramen
csv data data-analysis fun python report
Last synced: 14 days ago
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Data Analysis for Ramen 🍜💹
- Host: GitHub
- URL: https://github.com/2kabhishek/pyramen
- Owner: 2KAbhishek
- License: gpl-3.0
- Created: 2022-03-07T17:59:14.000Z (over 4 years ago)
- Default Branch: main
- Last Pushed: 2023-02-16T07:42:22.000Z (over 3 years ago)
- Last Synced: 2025-10-26T19:37:36.879Z (9 months ago)
- Topics: csv, data, data-analysis, fun, python, report
- Language: Python
- Size: 664 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
## What is this
PyRamen is a data analysis project that solves a very real problem for an imaginary ramen shop.
## Inspiration
Wanted to try out Azure notebooks, came across this dataset and boom!
### Imaginary problem statement
Welcome to 2KRamen!
Opening a ramen shop has always been my dream, and now it's finally been realized – I'm closing out on my second year of sales!
I need to analyze my business's financial performance by cross-referencing my sales data with my internal menu data to figure out revenues and costs for the year.
I also want to analyze how well my business did on a per-product basis in order to better understand which products may need to be removed or changed.
## Prerequisites
Before you begin, ensure you have met the following requirements:
- You have installed the latest version of `python`
## Getting PyRamen
To get PyRamen, follow these steps:
```bash
git clone https://github.com/2kabhishek/pyramen
cd pyramen
```
## Using PyRamen
```bash
python pyramen.py # This will run the program, and will produce a report
```
The report will be saved to the `gen/report.md` file. Try exploring the `data` and report folders to see what else you can do with the data.
## How it was built
pyramen was built using `python` and the `csv` module.
## Challenges faced
Hunting for the data, and coming up with an imaginative problem statement :)
## What I learned
- Didn't use pandas, opted for csv module, which was sufficient for this problem.
- Followed python best practices as much as possible.
Hit the ⭐ button if you found this useful.
## More Info
