Pandas
What it is: Python's data manipulation library. DataFrames, groupby, merge, pivot. Foundation of Python data work.
What It Does Best
Excel in code. DataFrames work like spreadsheets. Familiar operations: filter, sort, pivot, merge.
Handle messy data. Missing values, duplicates, type conversions. Built-in functions for common data problems.
Fast vectorized operations. No loops needed. Operations on entire columns at once.
Pricing
Free. Open source, BSD license.
When to Use It
✅ Datasets that fit in memory (< few GB)
✅ Data wrangling and cleaning
✅ Exploratory analysis in Jupyter
✅ Preparing data for ML models
When NOT to Use It
❌ Very large data (use Dask, Spark, or databases)
❌ Real-time streaming (not designed for it)
❌ Complex SQL operations (just use SQL)
Bottom line: If you're doing data work in Python, you're using Pandas. Non-negotiable part of the Python data stack.