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What Is Pandas?
Pandas is the most popular Python library for data manipulation. It's the tool for working with tabular data like spreadsheets, CSV files, and database tables.
Later in this course we'll look at Polars, a newer alternative to Pandas that's quickly gaining popularity. But today, Pandas is still the dominant library.
Wes McKinney created Pandas in 2008 while working at a hedge fund to solve real-world data problems:
- Loading datasets from CSV, Excel, relational databases, APIs
- Filtering rows by conditions
- Creating new columns
- Grouping and aggregating
- Handling missing data
- Merging multiple datasets
Tasks that take many lines of code in Python become one-liners with Pandas. They also tend to be much faster, because Pandas relies on optimized, compiled array operations under the hood.
If you're considering a career in data analytics, Pandas is non-negotiable. Data scientists, analysts, and even some backend engineers use it regularly.