Python for Data Analysis, 3rd Edition (Second Early Release) by Wes Mckinney 9781098103989 109810398X

Python for Data Analysis, 3rd Edition (Second Early Release) Wes Mckinney – Ebook Instant Download/Delivery ISBN(s): 9781098104023, 1098104021, 9781098103989, 109810398X

Product details:

• ISBN 10:  109810398X
• ISBN 13: 9781098103989
• Author: Wes Mckinney

Get the definitive handbook for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.10 and pandas 1.4, the third edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You’ll learn the latest versions of pandas, NumPy, and Jupyter in the process. Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It’s ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub. Use the Jupyter notebook and IPython shell for exploratory computing Learn basic and advanced features in NumPy Get started with data analysis tools in the pandas library Use flexible tools to load, clean, transform, merge, and reshape data Create informative visualizations with matplotlib Apply the pandas groupby facility to slice, dice, and summarize datasets Analyze and manipulate regular and irregular time series data Learn how to solve real-world data analysis problems with thorough, detailed examples

Table contents:

1. Preliminaries
2. Python Language Basics, IPython, and Jupyter Notebooks
3. Built-In Data Structures, Functions, and Files
4. NumPy Basics: Arrays and Vectorized Computation
5. Getting Started with pandas
6. Data Loading, Storage, and File Formats
7. Data Cleaning and Preparation
8. Data Wrangling: Join, Combine, and Reshape
9. Plotting and Visualization
10. Data Aggregation and Group Operations
11. Time Series
12. Introduction to Modeling Libraries in Python
13. Data Analysis Examples

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