Python for Data Analysis

( 2 )

Overview

Python for Data Analysis is concerned with the nuts and bolts of manipulating, processing, cleaning, and crunching data in Python. It is also a practical, modern introduction to scientific computing in Python, tailored for data-intensive applications. This is a book about the parts of the Python language and libraries you’ll need to effectively solve a broad set of data analysis problems. This book is not an exposition on analytical methods using Python as the implementation ...

See more details below
Paperback
$25.25
BN.com price
(Save 36%)$39.99 List Price

Pick Up In Store

Reserve and pick up in 60 minutes at your local store

Other sellers (Paperback)
  • All (11) from $22.06   
  • New (8) from $22.06   
  • Used (3) from $22.06   
Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython

Available on NOOK devices and apps  
  • NOOK Devices
  • NOOK HD/HD+ Tablet
  • NOOK
  • NOOK Color
  • NOOK Tablet
  • Tablet/Phone
  • NOOK for Windows 8 Tablet
  • NOOK for iOS
  • NOOK for Android
  • NOOK Kids for iPad
  • PC/Mac
  • NOOK for Windows 8
  • NOOK for PC
  • NOOK for Mac
  • NOOK Study
  • NOOK for Web

Want a NOOK? Explore Now

NOOK Book (eBook)
$17.99
BN.com price
(Save 43%)$31.99 List Price

Overview

Python for Data Analysis is concerned with the nuts and bolts of manipulating, processing, cleaning, and crunching data in Python. It is also a practical, modern introduction to scientific computing in Python, tailored for data-intensive applications. This is a book about the parts of the Python language and libraries you’ll need to effectively solve a broad set of data analysis problems. This book is not an exposition on analytical methods using Python as the implementation language.

Written by Wes McKinney, the main author of the pandas library, this hands-on book is packed with practical cases studies. It’s ideal for analysts new to Python and for Python programmers new to scientific computing.

  • Use the IPython interactive shell as your primary development environment
  • Learn basic and advanced NumPy (Numerical Python) features
  • Get started with data analysis tools in the pandas library
  • Use high-performance tools to load, clean, transform, merge, and reshape data
  • Create scatter plots and static or interactive visualizations with matplotlib
  • Apply the pandas groupby facility to slice, dice, and summarize datasets
  • Measure data by points in time, whether it’s specific instances, fixed periods, or intervals
  • Learn how to solve problems in web analytics, social sciences, finance, and economics, through detailed examples
Read More Show Less

Product Details

  • ISBN-13: 9781449319793
  • Publisher: O'Reilly Media, Incorporated
  • Publication date: 10/29/2012
  • Edition number: 1
  • Pages: 470
  • Sales rank: 141,501
  • Product dimensions: 7.00 (w) x 9.10 (h) x 0.90 (d)

Meet the Author

Wes McKinney is the main author of pandas, the popular open sourcePython library for data analysis. Wes is an active speaker andparticipant in the Python and open source communities. He worked as aquantitative analyst at AQR Capital Management and Python consultantbefore founding DataPad, a data analytics company, in 2013. Hegraduated from MIT with an S.B. in Mathematics.

Read More Show Less

Table of Contents

Preface;
Conventions Used in This Book;
Using Code Examples;
Safari® Books Online;
How to Contact Us;
Chapter 1: Preliminaries;
1.1 What Is This Book About?;
1.2 Why Python for Data Analysis?;
1.3 Essential Python Libraries;
1.4 Installation and Setup;
1.5 Community and Conferences;
1.6 Navigating This Book;
1.7 Acknowledgements;
Chapter 2: Introductory Examples;
2.1 1.usa.gov data from bit.ly;
2.2 MovieLens 1M Data Set;
2.3 US Baby Names 1880-2010;
2.4 Conclusions and The Path Ahead;
Chapter 3: IPython: An Interactive Computing and Development Environment;
3.1 IPython Basics;
3.2 Using the Command History;
3.3 Interacting with the Operating System;
3.4 Software Development Tools;
3.5 IPython HTML Notebook;
3.6 Tips for Productive Code Development Using IPython;
3.7 Advanced IPython Features;
3.8 Credits;
Chapter 4: NumPy Basics: Arrays and Vectorized Computation;
4.1 The NumPy ndarray: A Multidimensional Array Object;
4.2 Universal Functions: Fast Element-wise Array Functions;
4.3 Data Processing Using Arrays;
4.4 File Input and Output with Arrays;
4.5 Linear Algebra;
4.6 Random Number Generation;
4.7 Example: Random Walks;
Chapter 5: Getting Started with pandas;
5.1 Introduction to pandas Data Structures;
5.2 Essential Functionality;
5.3 Summarizing and Computing Descriptive Statistics;
5.4 Handling Missing Data;
5.5 Hierarchical Indexing;
5.6 Other pandas Topics;
Chapter 6: Data Loading, Storage, and File Formats;
6.1 Reading and Writing Data in Text Format;
6.2 Binary Data Formats;
6.3 Interacting with HTML and Web APIs;
6.4 Interacting with Databases;
Chapter 7: Data Wrangling: Clean, Transform, Merge, Reshape;
7.1 Combining and Merging Data Sets;
7.2 Reshaping and Pivoting;
7.3 Data Transformation;
7.4 String Manipulation;
7.5 Example: USDA Food Database;
Chapter 8: Plotting and Visualization;
8.1 A Brief matplotlib API Primer;
8.2 Plotting Functions in pandas;
8.3 Plotting Maps: Visualizing Haiti Earthquake Crisis Data;
8.4 Python Visualization Tool Ecosystem;
Chapter 9: Data Aggregation and Group Operations;
9.1 GroupBy Mechanics;
9.2 Data Aggregation;
9.3 Group-wise Operations and Transformations;
9.4 Pivot Tables and Cross-Tabulation;
9.5 Example: 2012 Federal Election Commission Database;
Chapter 10: Time Series;
10.1 Date and Time Data Types and Tools;
10.2 Time Series Basics;
10.3 Date Ranges, Frequencies, and Shifting;
10.4 Time Zone Handling;
10.5 Periods and Period Arithmetic;
10.6 Resampling and Frequency Conversion;
10.7 Time Series Plotting;
10.8 Moving Window Functions;
10.9 Performance and Memory Usage Notes;
Chapter 11: Financial and Economic Data Applications;
11.1 Data Munging Topics;
11.2 Group Transforms and Analysis;
11.3 More Example Applications;
Chapter 12: Advanced NumPy;
12.1 ndarray Object Internals;
12.2 Advanced Array Manipulation;
12.3 Broadcasting;
12.4 Advanced ufunc Usage;
12.5 Structured and Record Arrays;
12.6 More About Sorting;
12.7 NumPy Matrix Class;
12.8 Advanced Array Input and Output;
12.9 Performance Tips;
Python Language Essentials;
The Python Interpreter;
The Basics;
Data Structures and Sequences;
Functions;
Files and the operating system;
Colophon;

Read More Show Less

Customer Reviews

Average Rating 1.5
( 2 )
Rating Distribution

5 Star

(0)

4 Star

(0)

3 Star

(0)

2 Star

(1)

1 Star

(1)

Your Rating:

Your Name: Create a Pen Name or

Barnes & Noble.com Review Rules

Our reader reviews allow you to share your comments on titles you liked, or didn't, with others. By submitting an online review, you are representing to Barnes & Noble.com that all information contained in your review is original and accurate in all respects, and that the submission of such content by you and the posting of such content by Barnes & Noble.com does not and will not violate the rights of any third party. Please follow the rules below to help ensure that your review can be posted.

Reviews by Our Customers Under the Age of 13

We highly value and respect everyone's opinion concerning the titles we offer. However, we cannot allow persons under the age of 13 to have accounts at BN.com or to post customer reviews. Please see our Terms of Use for more details.

What to exclude from your review:

Please do not write about reviews, commentary, or information posted on the product page. If you see any errors in the information on the product page, please send us an email.

Reviews should not contain any of the following:

  • - HTML tags, profanity, obscenities, vulgarities, or comments that defame anyone
  • - Time-sensitive information such as tour dates, signings, lectures, etc.
  • - Single-word reviews. Other people will read your review to discover why you liked or didn't like the title. Be descriptive.
  • - Comments focusing on the author or that may ruin the ending for others
  • - Phone numbers, addresses, URLs
  • - Pricing and availability information or alternative ordering information
  • - Advertisements or commercial solicitation

Reminder:

  • - By submitting a review, you grant to Barnes & Noble.com and its sublicensees the royalty-free, perpetual, irrevocable right and license to use the review in accordance with the Barnes & Noble.com Terms of Use.
  • - Barnes & Noble.com reserves the right not to post any review -- particularly those that do not follow the terms and conditions of these Rules. Barnes & Noble.com also reserves the right to remove any review at any time without notice.
  • - See Terms of Use for other conditions and disclaimers.
Search for Products You'd Like to Recommend

Recommend other products that relate to your review. Just search for them below and share!

Create a Pen Name

Your Pen Name is your unique identity on BN.com. It will appear on the reviews you write and other website activities. Your Pen Name cannot be edited, changed or deleted once submitted.

 
Your Pen Name can be any combination of alphanumeric characters (plus - and _), and must be at least two characters long.

Continue Anonymously
Sort by: Showing all of 2 Customer Reviews
  • Anonymous

    Posted April 1, 2014

    No text was provided for this review.

  • Anonymous

    Posted January 21, 2013

    No text was provided for this review.

Sort by: Showing all of 2 Customer Reviews

If you find inappropriate content, please report it to Barnes & Noble
Why is this product inappropriate?
Comments (optional)