What This Visualization Shows

This data visualization displays "[OC] Price distribution comparison of gym single-entry passes vs. monthly memberships in Denmark and Hungary" and provides a clear visual representation of the underlying data patterns and trends. The visualization focuses on I scraped gym and climbing gym prices in Denmark and Hungary and found an interesting trend of having cheaper single entrance gym passes in Hungary over Denmark, and vice versa for the monthly memberships. I am unsure what economic or cultural trend could explain this.

You can find the used data, the scrapers, and the data source of the scrapers in my GitHub repository: [https://github.com/nlevi-dev/PriceCompass](https://github.com/nlevi-dev/PriceCompass).

The diagram was made with basic python and matplotlib.

Looking for help

The diagram above is just one interesting trend I accidentally discovered while working on my open source project called **Price Compass**, which is for scraping and comparing the prices of common commodities across different countries.

Regardless of some of the questions that this reversed trend sparked in me, this post is about the future of this project and asking for help. This project aims to collect comparable prices of common everyday commodities, across borders. For example a kg of dry spaghetti pasta should exist everywhere, and its price per kg should be comparable. The generic spirit of the project is radical transparency, such as making the data available about the dry spaghetti prices on a very granular level, of multiple datapoints from multiple retailers per country, resulting in 100+ price data points per item per country. From which you can derive your own statistics with your own aggregation methods, like taking the minimum cheapest product per item to compare between countries.

What has been implemented so far

The project in practice allows you to browse the scraped catalog of items, and define a custom "shopping basket" that represent your lifestyle, thus you can see how prices compare for you, instead of blindly relying on blackbox cost of living indicators published by governments.

The historical aspect of the data also allows to confirm and audit official inflation and other economic metrics.

You can find the project at its current state on my GitHub: [https://github.com/nlevi-dev/PriceCompass](https://github.com/nlevi-dev/PriceCompass), and the live pre-release with a few days of test data available at: [https://nlevi-dev.github.io/PriceCompass](https://nlevi-dev.github.io/PriceCompass).

The problem (and why I need help)

I love this concept and I really believe this would be a great way of giving back power into the hands of the people through data transparency. But this is a huge effort; I managed to get two countries (Denmark and Hungary) to a point of 70% being done with the scrapers after 2 long months. Following a 2 month burnout period, I came back to pick up the project, only to find that 1 data source had shut down entirely and 4 others had changed their interfaces.

And this is the problem with scraper based projects. There is no finish line, it will always require maintenance.

**BUT** if there is genuine community interest in this project, I am willing to pick this project back up and continue working on it.

Here is what I am looking to gauge before diving back in

* User Interest & Crowdfunding: Would you actually use a tool like this? If the interest is there, I'd consider setting up a community fund down the line to help cover general project costs. * Future Contributors: If you are a developer, data scientist, or open-source enthusiast, would you want to contribute? I'd love to connect with anyone who wants to help expand regional data or collaborate on building a more resilient data architecture.

The code is a bit of a mess right now, but if this gains enough traction, I will jump back in, clean and document everything, fix the currently broken scrapers and create a welcoming environment for community contributions.

Is a transparent, auditable cost-of-living tool something the community actually wants, or am I shouting into the void? Let me know your thoughts, critiques, or if you'd be down to help build this!, which allows us to understand complex relationships and insights within the data through visual storytelling.

Deep Dive into the Topic

This data visualization represents a sophisticated analysis of complex information patterns that provide valuable insights into underlying trends and relationships. Data visualization serves as a bridge between raw numerical data and human understanding, transforming abstract statistics into comprehensible visual narratives.

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Data Analysis and Insights

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