What programming language should I learn for a career in data analysis?

Welcome to the world of programming and data analysis. It's great that you have a background in statistics and mathematics, as this will definitely help you in your journey. Now, let's talk about the programming languages you're considering - Python and R. Both are excellent choices, but they do have different strengths and weaknesses.

Python is a versatile language that can be used for a wide range of applications, from web development to machine learning. It has a large community of developers and a vast number of libraries and frameworks that make it easy to work with. For data analysis, Python has popular libraries like pandas, numpy, and matplotlib that make it easy to work with data. On the other hand, R is a language that's specifically designed for statistical computing and has a wide range of built-in functions for statistical modeling and data visualization. It's also a great language for data analysis, and has libraries like dplyr and ggplot2 that make it easy to work with data.

So, which language should you start with? Well, if you're new to programming, I'd recommend starting with Python. It's a bit more forgiving than R, and has a wider range of applications beyond just data analysis. Plus, it's easy to learn and has a large community of developers who can help you out. That being said, if you're specifically interested in statistical modeling and data visualization, R might be the better choice. It's also worth noting that you don't have to choose just one language - you can definitely learn both Python and R, and use them for different projects.

If you're just starting out, I'd recommend checking out some online resources like Codecademy or