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Python Intermediate

What is Pandas?

A powerful data analysis and manipulation library providing DataFrames and tools for working with structured data.

Pandas is the cornerstone of data analysis in Python. DataFrames organize data into rows and columns (like spreadsheets). Key operations include reading CSV/Excel/SQL data, filtering, grouping, merging, pivoting, and statistical analysis.

Built on NumPy, Pandas handles missing data, time series, and large datasets efficiently. Common methods include .head(), .describe(), .groupby(), .merge(), .apply(), and .to_csv(). It is essential for data science, analytics, and machine learning workflows.

Related Terms

Generator
A function that yields values one at a time using the yield keyword, enabling memory-efficient iteration over large datasets.
Class
A blueprint for creating objects that bundles data (attributes) and behavior (methods) together.
Python Coroutine
A function defined with async def that can be paused and resumed, enabling concurrent execution without threads.
Slots
A class mechanism that restricts attribute creation and reduces memory usage by using a fixed set of instance variables.
ABC (Abstract Base Class)
A class that defines a common interface for subclasses by declaring abstract methods that must be implemented.
Python Typing Module
A standard library module providing type hints for function signatures and variables, enabling static analysis without runtime enforcement.
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