#### Overview of this book

Practical Data Analysis
Credits
Foreword
Acknowledgments
www.PacktPub.com
Preface
Free Chapter
Getting Started
Working with Data
Data Visualization
Text Classification
Similarity-based Image Retrieval
Simulation of Stock Prices
Predicting Gold Prices
Working with Support Vector Machines
Modeling Infectious Disease with Cellular Automata
Working with Social Graphs
Data Processing and Aggregation with MongoDB
Working with MapReduce
Online Data Analysis with IPython and Wakari
Setting Up the Infrastructure
Index

## Installing and running NumPy

According to the official website http://www.numpy.org/, NumPy is the fundamental package for scientific computing with Python. It contains amongst other things:

• A powerful N-dimensional array object

• Tools for integrating C/C++ and Fortran code

• Useful linear algebra, Fourier transform, and random number capabilities

Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of the generic data. Arbitrary datatypes can be defined. This allows NumPy to seamlessly and speedily integrate with a wide variety of datasets.

### Installing and running NumPy on Ubuntu

To install numpy, simply open a command prompt and run.

```\$ sudo apt-get install python3-numpy
```

To check whether everything is installed correctly, just execute the Python Shell shown as follows:

```\$ idle3
```

Then execute the following commands:

```>>> import numpy
>>> numpy.test()```

### Tip

We need to use the `nose` library (that extends the test loading and running features of unit test) when using `numpy.test()`.

In order to install it, we just need to open a command line and run the following command:

```\$ sudo apt-get install python3-nose
```

Or you can also execute:

```\$ pip install nose
```

For more information about the `nose` library, visit https://pypi.python.org/pypi/nose/1.1.2.

### Installing and running NumPy on Windows

The Windows version is provided as an `.exe` package. To install it manually, just double click on the `/numpy-1.7.0-win32-superpack-python3.2.exe` file.

To check whether everything is installed correctly, just navigate to Start | All Programs | Python 3.2 | IDLE (Python GUI).

Then execute the following commands:

```>>> import numpy
>>> numpy.test()```

### Tip

We need to use the `nose` library (that extends the test loading and running features of unit test) when using `numpy.test()`.

In order to install it, you just need to open a Windows command line (CMD) and run the following command:

```C:\> pip install nose
```

For more information about `nose`, visit https://pypi.python.org/pypi/nose/1.1.2.