The same is true if your personal or professional interests extend beyond data and into programming, development, or other computer science fields. If, on the other hand, you’re interested in becoming a data scientist and working with big data, artificial intelligence, and deep learning algorithms, Python would be the better fit. If you’re passionate about the statistical calculation and data visualization portions of data analysis, R could be a good fit for you. Think about how learning a programming language fits in with your longer term career goals. Its robust ecosystem of statistical packages Performing non-statistical tasks, like web scraping, saving to databases, and running workflows
Read more: What Is Python Used For? A Beginner’s Guide to Using PythonĬreating graphics and data visualizations You can use Python code for a wide variety of tasks, but three popular applications include: Python is a high-level, general-purpose programming language known for its intuitive syntax that mimics natural language. So which should you choose to learn (or learn first)?īefore we dig into the differences, here’s a broad overview of each language. Both can handle just about any data analysis task, and both are considered relatively easy languages to learn, especially for beginners. Python and R are both free, open-source languages that can run on Windows, macOS, and Linux.
Data analysts use SQL (Structured Query Language) to communicate with databases, but when it comes to cleaning, manipulating, analyzing, and visualizing data, you’re looking at either Python or R. One of the most important skills for a data analyst is proficiency in a programming language.
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