#### Overview of this book

There are many algorithms for data analysis and it’s not always possible to quickly choose the best one for each case. Implementation of the algorithms takes a lot of time. With the help of Mathematica, you can quickly get a result from the use of a particular method, because this system contains almost all the known algorithms for data analysis. If you are not a programmer but you need to analyze data, this book will show you the capabilities of Mathematica when just few strings of intelligible code help to solve huge tasks from statistical issues to pattern recognition. If you're a programmer, with the help of this book, you will learn how to use the library of algorithms implemented in Mathematica in your programs, as well as how to write algorithm testing procedure. With each chapter, you'll be more immersed in the special world of Mathematica. Along with intuitive queries for data processing, we will highlight the nuances and features of this system, allowing you to build effective analysis systems. With the help of this book, you will learn how to optimize the computations by combining your libraries with the Mathematica kernel.
Mathematica Data Analysis
Credits
www.PacktPub.com
Preface
Free Chapter
First Steps in Data Analysis
Creating an Interface for an External Program
Analyzing Data with the Help of Mathematica
Discovering the Advanced Capabilities of Time Series
Statistical Hypothesis Testing in Two Clicks
Predicting the Dataset Behavior
Rock-Paper-Scissors – Intelligent Processing of Datasets
Index

## Permissible data format for import

Mathematica allows the importing of hundreds of data formats, but we only need some of them: those that are amenable to mathematical processing and analysis.

The main data formats can be divided into the following groups:

• Tabular Text Formats: This includes general text format data (`*.dat`), comma-separated (`*.csv`), or tab-separated (`*.tsv`)

• Spreadsheet Formats: This includes office programs data working with documents, such as Excel (`*.xls` and `*.xlsx`), Open Office (`*.odc`, and `*.sxc`), and even the first spreadsheet VisiCalc data (`*.di` `f`)

• Data Interchange Formats: This includes the JSON format

• Database Formats: This includes MS Access (`*.mdb`) and dBase (`*.dbf`)

• Compression and Archive Formats: This includes the files created by archivers, such as Windows ZIP (`*.zip`), Unix GZIP (`*.gz`), Unix TAR (`*.tar`), and BZIP2 (`*.bz2`)

• XML/HTML Formats: This includes extensions such as `.xml`, `.xhtml`, `.html`, and `.rss`

### Note

Here, you may find the complete list of all the data formats...