---
title: Data Analysis (Pandas, NumPy)
description: This topic covers data manipulation using Python's foundational libraries, Pandas and NumPy. You will understand how to manipulate multi-dimensional arrays, perform vectorized operations, clean tabular data, and execute complex aggregations efficiently.
category: programming-tech
subcategory: data-science
difficulty: beginner, intermediate, advanced
url: /subject/data-analysis-pandas-numpy
---

# Data Analysis (Pandas, NumPy)

This topic covers data manipulation using Python's foundational libraries, Pandas and NumPy. You will understand how to manipulate multi-dimensional arrays, perform vectorized operations, clean tabular data, and execute complex aggregations efficiently.

## Available Resources

1 Books • 1 Websites

## Youtubes

### 1. Corey Schafer - Pandas Tutorials

Corey Schafer's YouTube channel offers excellent, clear, and concise tutorials on various Python topics, including a dedicated series on Pandas. His videos are highly recommended by the community for their practical examples and easy-to-follow explanations.

**Difficulty:** Beginner | **Language:** English | **Price:** Free

**Link:** https://www.youtube.com/playlist?list=PLSLQ7uyfNIItZf404-TviaeM01pnebr5K

**Tags:** pandas, python, dataframes, data-cleaning, data-analysis

## Websites

### 1. NumPy Official Documentation

Similar to Pandas, the NumPy documentation provides extensive information on numerical operations, array manipulation, and linear algebra. It's essential for anyone working with numerical data in Python.

**Difficulty:** Intermediate | **Language:** English | **Price:** Free

**Link:** https://numpy.org/doc/stable/

**Tags:** numpy, python, arrays, numerical-computing, documentation

## Books

### 1. Python Data Science Handbook by Jake VanderPlas

**Author:** Jake VanderPlas

This book provides a comprehensive overview of essential tools for data science in Python, with a strong focus on NumPy for numerical computation and Pandas for data manipulation. It's widely considered a foundational text and is excellent for both beginners and those looking to deepen their understanding.

**Difficulty:** Intermediate | **Language:** English | **Price:** Free

**Link:** https://jakevdp.github.io/PythonDataScienceHandbook/

**Tags:** python, numpy, pandas, matplotlib, scikit-learn, data-science

---

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