Python for Data Analysis Book

The “Python for Data Analysis Book” delves into leveraging Python for analyzing and manipulating data effectively. It covers essential topics like data cleaning, transformation, and visualization using Python libraries like Pandas and Matplotlib. The book aims to equip readers with the skills needed to work with real-world data sets, perform statistical analysis, and extract valuable insights. By exploring practical examples and hands-on exercises, it provides a comprehensive guide for individuals looking to enhance their data analysis capabilities using Python.

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Built-In Data Structures, Functions, and Files

This chapter discusses capabilities built into the Python language that will be used ubiquitously throughout the book. While add-on libraries like pandas and NumPy add advanced computational functiona...

Preface

Python for Data Analysis Book

The first edition of this book was published in 2012, during a time when open source data analysis libraries for Python, especially pandas, were very new and developing rapidly. When the time came to ...

Time Series

Python for Data Analysis Book

Time series data is an important form of structured data in many different fields, such as finance, economics, ecology, neuroscience, and physics. Anything that is recorded repeatedly at many points i...

Python Language Basics, IPython, and Jupyter Notebooks

Python for Data Analysis Book

When I wrote the first edition of this book in 2011 and 2012, there were fewer resources available for learning about doing data analysis in Python. This was partially a chicken-and-egg problem; many ...

Data Loading, Storage, and File Formats

Python for Data Analysis Book

Reading data and making it accessible (often called data loading ) is a necessary first step for using most of the tools in this book. The term parsing is also sometimes used to describe loading text ...

Preliminaries

Python for Data Analysis Book

1.1 What Is This Book About? This book is concerned with the nuts and bolts of manipulating, processing, cleaning, and crunching data in Python. My goal is to offer a guide to the parts of the Python ...

Python for Data Analysis Book

About the Open Edition The 3rd edition of Python for Data Analysis is now available as an “Open Access” HTML version on this site https://wesmckinney.com/book in addition to the usual print and e-book...

Data Aggregation and Group Operations

Python for Data Analysis Book

Categorizing a dataset and applying a function to each group, whether an aggregation or transformation, can be a critical component of a data analysis workflow. After loading, merging, and preparing a...

Plotting and Visualization

Python for Data Analysis Book

Making informative visualizations (sometimes called plots ) is one of the most important tasks in data analysis. It may be a part of the exploratory process—for example, to help identify outliers or n...

Getting Started with pandas

Python for Data Analysis Book

pandas will be a major tool of interest throughout much of the rest of the book. It contains data structures and data manipulation tools designed to make data cleaning and analysis fast and convenient...

Data Cleaning and Preparation

Python for Data Analysis Book

During the course of doing data analysis and modeling, a significant amount of time is spent on data preparation: loading, cleaning, transforming, and rearranging. Such tasks are often reported to tak...

NumPy Basics: Arrays and Vectorized Computation

Python for Data Analysis Book

NumPy, short for Numerical Python, is one of the most important foundational packages for numerical computing in Python. Many computational packages providing scientific functionality use NumPy's arra...