I'm a beginner programmer with a full-time job, how can I start using Python for data analysis without overwhelming myself?

I totally get it, learning a new skill can feel overwhelming, especially when there are so many libraries and tools available. To be honest, the key is to start simple and build your way up. I'd recommend starting with the basics of Python, and then moving on to popular libraries like Pandas and NumPy. You can't go wrong with the official Python documentation and tutorials on the official website, but if you're looking for something a bit more beginner-friendly, I've heard great things about Codecademy's Python course and the DataCamp Python courses.

Also, I think it's really important to focus on practical projects rather than just following tutorials. You can start by practicing with some public datasets, like those available on Kaggle or UCI Machine Learning Repository. Try to focus on a specific use case, like data cleaning or visualization, and work on building projects that demonstrate your skills in those areas. That way, you'll be able to build a portfolio of work that you can show off to potential employers.

One project idea to get you started is to practice data cleaning and manipulation with the 'tips' dataset from Seaborn. It's a simple dataset that you can use to practice working with Pandas and cleaning data. You can find the code for loading the dataset here: import seaborn as sns; tips = sns.load_dataset('tips') From there, try to clean and manipulate the data, and then visualize the results with Matplotlib or Seaborn.

Lastly, don't be afraid to ask for help or join online communities, like the r/learnpython or r/dataanalysis subreddits, where you can connect with other learners and get feedback on your work. Good luck, and have fun learning!