This book is an in-depth guide to the use of pandas for data analysis, for either the seasoned data analysis practitioner or the novice user. It provides a basic introduction to the pandas framework, and takes users through the installation of the library and the IPython interactive environment. Thereafter, you will learn basic as well as advanced features, such as MultiIndexing, modifying data structures, and sampling data, which provide powerful capabilities for data analysis.
Femi Anthony is a seasoned and knowledgeable software programmer, with over 15 years experience in a vast array of languages, including Perl, C, C++, Java, and Python. He has worked in both the Internet space and financial services space for many years and is now working for a well-known financial data company. He holds a bachelor's degree in mathematics with computer science from MIT and a master's degree from the University of Pennsylvania. His pet interests include data science, machine learning, and Python. Femi is working on a few side projects in these areas. His hobbies include reading, soccer, and road cycling. You can follow him at @dataphanatik, and for any queries, contact him at firstname.lastname@example.org.
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 IPython shell and Jupyter notebook for exploratory computingLearn basic and advanced features in NumPy (Numerical Python)Get started with data analysis tools in the pandas libraryUse flexible tools to load, clean, transform, merge, and reshape dataCreate informative visualizations with matplotlibApply the pandas groupby facility to slice, dice, and summarize datasetsAnalyze and manipulate regular and irregular time series dataLearn how to solve real-world data analysis problems with thorough, detailed examples
Almost anyone can learn to write working script and create high quality code but they might lack a structured understanding of what it means to be 'Pythonic'. If you are a Python programmer who wants to code efficiently by getting the syntax and usage of a few intricate Python techniques exactly right, this book is for you.What You Will LearnCreate a virtualenv and start a new projectUnderstand how and when to use the functional programming paradigmGet familiar with the different ways the decorators can be written inUnderstand the power of generators and coroutines without digressing into lambda calculusCreate metaclasses and how it makes working with Python far easierGenerate HTML documentation out of documents and code using SphinxLearn how to track and optimize application performance, both memory and cpuUse the multiprocessing library, not just locally but also across multiple machinesGet a basic understanding of packaging and creating your own libraries/applicationsIn Detail
Python is a dynamic programming language. It is known for its high readability and hence it is often the first language learned by new programmers. Python being multi-paradigm, it can be used to achieve the same thing in different ways and it is compatible across different platforms. Even if you find writing Python code easy, writing code that is efficient, easy to maintain, and reuse is not so straightforward.
This book is an authoritative guide that will help you learn new advanced methods in a clear and contextualised way. It starts off by creating a project-specific environment using venv, introducing you to different Pythonic syntax and common pitfalls before moving on to cover the functional features in Python. It covers how to create different decorators, generators, and metaclasses. It also introduces you to functools.wraps and coroutines and how they work. Later on you will learn to use asyncio module for asynchronous clients and servers. You will also get familiar with different testing systems such as py.test, doctest, and unittest, and debugging tools such as Python debugger and faulthandler. You will learn to optimize application performance so that it works efficiently across multiple machines and Python versions. Finally, it will teach you how to access C functions with a simple Python call. By the end of the book, you will be able to write more advanced scripts and take on bigger challenges.Style and Approach
This book is a comprehensive guide that covers advanced features of the Python language, and communicate them with an authoritative understanding of the underlying rationale for how, when, and why to use them.