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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

Python Profiling
Measuring where Python code spends time and memory to identify performance bottlenecks and optimization opportunities.
FastAPI
A modern, high-performance Python web framework for building APIs with automatic OpenAPI documentation and type validation.
Pip Requirements File
A text file listing Python package dependencies with version specifications for reproducible project installations.
NumPy
A fundamental library for numerical computing in Python, providing efficient multi-dimensional arrays and mathematical operations.
Comprehension
A concise syntax pattern for creating collections by transforming and filtering items from iterables.
Python ABC Module
The Abstract Base Classes module that enables defining interfaces and abstract methods that subclasses must implement.
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