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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.

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A Python file containing definitions and statements that can be imported and reused in other Python programs.
Uvicorn
A lightning-fast ASGI server for Python, commonly used to serve FastAPI and other async web applications.
Python Iterator Protocol
The interface requiring __iter__() and __next__() methods, enabling objects to be used in for loops and other iteration contexts.
Magic Methods
Special double-underscore methods that define how Python objects behave with built-in operations and functions.
Scikit-learn
The most popular Python machine learning library providing simple and efficient tools for data analysis and modeling.
Django
A high-level web framework that follows the batteries-included philosophy, providing ORM, admin, auth, and more out of the box.
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