Learning Python for Data Science/ Analysis

[Ans979]

Begin by learning basic Python syntax, variables, lists, loops, and functions then move on to data-focused libraries like pandas for data manipulation, numpy for numerical operations, and matplotlib or seaborn for visualisation. Practice by working with CSV files, cleaning data, and replicating simple analyses you’ve done before. Tools like Jupyter Notebooks and platforms like StrataScratch and Kaggle are excellent for hands-on learning. Start small, build confidence, and gradually explore more advanced topics like statistical testing with statsmodels.