Pandas / NumPy
The foundational Python libraries for data manipulation and numerical computing — required knowledge for any data role using Python.
Pandas provides DataFrame-based data manipulation in Python, enabling filtering, aggregation, reshaping, merging, and analysis of structured data. NumPy underpins it with efficient array operations and mathematical functions. Together they are the foundation of the Python data science stack and are expected knowledge for data analysts, data scientists, and data engineers. For larger datasets, Polars is an emerging high-performance alternative.
Typical time to job-readiness: ~4 weeks.