When starting any project, you first want to understand ‘why’ you’re doing it, the end goal and what questions you want to answer.
In data analysis, you can either have questions you need the data to answer or let the data speak for itself. With that foundation, let’s examine this dataset.
Analyzing VISA-Free Countries
Data source: https://www.kaggle.com/datasets/bhadramohit/visa-free-countries-dataset2024/data
This data tells us about accessibility to different countries based on a ranking order. Since we don’t have any specific questions, we give the data a chance to speak for itself. This is called Exploratory Data Analysis (EDA).
But-
Before the data does any talking, accessing its quality is key to ensuring the effectiveness of our analysis. Here are important things I have done to ensure the use of quality data:
Remove duplicates
Ensure consistency in data types across columns.
Check for missing rows
This is an overview of the data we’re working with. We have the country name, it’s global ranking, and the number of countries a country is entitled to VISA-Free access.
The map here shows most countries in the top 5 ranks are from Europe, with Singapore, Japan and South Korea being the only Asian countries.
Here’s a close-up view of the top 10 countries with VISA-Free Access. A Singapore passport guarantees your entry into any country in the world.
On the contrary, these countries have the least VISA-Free access, with Afghanistan having access to 26 countries with Syria following closely.
In conclusion, we saw global rankings of passports and how much VISA-Free access is ascribed to them by possessing them. We’ve also seen countries that wouldn’t have as much VISA-Free access to other countries for various reasons ranging from security to economic considerations or even diplomatic relations.