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Hands-On Data Analysis with NumPy and pandas电子书

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47人正在读 | 0人评论 6.2

作       者:Curtis Miller

出  版  社:Packt Publishing

出版时间:2018-06-29

字       数:10.5万

所属分类: 进口书 > 外文原版书 > 电脑/网络

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Get to grips with the most popular Python packages that make data analysis possible About This Book ? Explore the tools you need to become a data analyst ? Discover practical examples to help you grasp data processing concepts ? Walk through hierarchical indexing and grouping for data analysis Who This Book Is For Hands-On Data Analysis with NumPy and Pandas is for you if you are a Python developer and want to take your first steps into the world of data analysis. No previous experience of data analysis is required to enjoy this book. What You Will Learn ? Understand how to install and manage Anaconda ? Read, sort, and map data using NumPy and pandas ? Find out how to create and slice data arrays using NumPy ? Discover how to subset your DataFrames using pandas ? Handle missing data in a pandas DataFrame ? Explore hierarchical indexing and plotting with pandas In Detail Python, a multi-paradigm programming language, has become the language of choice for data scientists for visualization, data analysis, and machine learning. Hands-On Data Analysis with NumPy and Pandas starts by guiding you in setting up the right environment for data analysis with Python, along with helping you install the correct Python distribution. In addition to this, you will work with the Jupyter notebook and set up a database. Once you have covered Jupyter, you will dig deep into Python’s NumPy package, a powerful extension with advanced mathematical functions. You will then move on to creating NumPy arrays and employing different array methods and functions. You will explore Python’s pandas extension which will help you get to grips with data mining and learn to subset your data. Last but not the least you will grasp how to manage your datasets by sorting and ranking them. By the end of this book, you will have learned to index and group your data for sophisticated data analysis and manipulation. Style and approach A step-by-step approach, taking you through the different concepts and features of Data Analysis using Python libraries and tools.
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Title Page

Copyright and Credits

Hands-On Data Analysis with NumPy and pandas

Packt Upsell

Why subscribe?

PacktPub.com

Contributors

About the author

Packt is searching for authors like you

Preface

Who this book is for

What this book covers

To get the most out of this book

Download the example code files

Conventions used

Get in touch

Reviews

Setting Up a Python Data Analysis Environment

What is Anaconda?

Installing Anaconda

Exploring Jupyter Notebooks

Exploring alternatives to Jupyter

Spyder

Rodeo

ptpython

Package management with Conda

What is Conda?

Conda environment management

Managing Python

Package management

Setting up a database

Installing MySQL

MySQL connectors

Creating a database

Summary

Diving into NumPY

NumPy arrays

Special numeric values

Creating NumPy arrays

Creating ndarray

Summary

Operations on NumPy Arrays

Selecting elements explicitly

Slicing arrays with colons

Advanced indexing

Expanding arrays

Arithmetic and linear algebra with arrays

Arithmetic with two equal-shaped arrays

Broadcasting

Linear algebra

Employing array methods and functions

Array methods

Vectorization with ufuncs

Custom ufuncs

Summary

pandas are Fun! What is pandas?

What does pandas do?

Exploring series and DataFrame objects

Creating series

Creating DataFrames

Adding data

Saving DataFrames

Subsetting your data

Subsetting a series

Indexing methods

Slicing a DataFrame

Summary

Arithmetic, Function Application, and Mapping with pandas

Arithmetic

Arithmetic with DataFrames

Vectorization with DataFrames

DataFrame function application

Handling missing data in a pandas DataFrame

Deleting missing information

Filling missing information

Summary

Managing, Indexing, and Plotting

Index sorting

Sorting by values

Hierarchical indexing

Slicing a series with a hierarchical index

Plotting with pandas

Plotting methods

Summary

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