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You're reading from Practical Data Analysis For small businesses, analyzing the information contained in their data using open source technology could be game-changing. All you need is some basic programming and mathematical skills to do just that.

Product type Paperback

Published in Oct 2013

Publisher Packt

ISBN-13 9781783280995

Length 360 pages

Edition 1st Edition

Languages

Python

Tools

NLTK

Concepts

Data Analysis

Author (1):

Hector Cuesta

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Table of Contents (24) Chapters

Practical Data Analysis

Credits

Foreword

About the Author

Acknowledgments

About the Reviewers

www.PacktPub.com

Preface

1. Getting Started FREE CHAPTER

2. Working with Data

3. Data Visualization

4. Text Classification

5. Similarity-based Image Retrieval

6. Simulation of Stock Prices

7. Predicting Gold Prices

8. Working with Support Vector Machines

9. Modeling Infectious Disease with Cellular Automata

10. Working with Social Graphs

11. Sentiment Analysis of Twitter Data

12. Data Processing and Aggregation with MongoDB

13. Working with MapReduce

14. Online Data Analysis with IPython and Wakari

Setting Up the Infrastructure

Index

Getting started with Pandas

Pandas is a great library for data manipulation and analysis, written by Wes McKinney. Pandas provide us with optimized data structures such as Series and DataFrame , which are well suited for descriptive statistics, indexing, and aggregation. Pandas is already installed in the Anaconda distribution used in Wakari. In this section, we will present the basic operations with Pandas for time series and multivariate data. We may find more information about Pandas at http://pandas.pydata.org/.

Working with time series

Time series helps us to understand the change in a variable through time. Pandas include specific functionality in order to work with time series transparently. For this section, we need to upload the Gold.csv file used in Chapter 7, Predicting Gold Prices. The first five rows in the file will look as follows:

date,price
1/31/2003,367.5
2/28/2003,347.5
3/31/2003,334.9
4/30/2003,336.8
5/30/2003,361.4
. . .

We will load the Gold.csv file with the read_csv...

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You're reading from Practical Data Analysis For small businesses, analyzing the information contained in their data using open source technology could be game-changing. All you need is some basic programming and mathematical skills to do just that.

Table of Contents (24) Chapters

Getting started with Pandas

Working with time series

Authors (1)

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You're reading from Practical Data Analysis For small businesses, analyzing the information contained in their data using open source technology could be game-changing. All you need is some basic programming and mathematical skills to do just that.

Table of Contents (24) Chapters

Getting started with Pandas

Working with time series

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Authors (1)

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