#### Overview of this book

Today's world of science and technology is all about speed and flexibility. When it comes to scientific computing, NumPy is on the top of the list. NumPy will give you both speed and high productivity. "NumPy Cookbook" will teach you all about NumPy, a leading scientific computing library. NumPy replaces a lot of the functionality of Matlab and Mathematica, but in contrast to those products, it is free and open source. "Numpy Cookbook" will teach you to write readable, efficient, and fast code that is as close to the language of Mathematics as much as possible with the cutting edge open source NumPy software library. You will learn about installing and using NumPy and related concepts. At the end of the book, we will explore related scientific computing projects. This book will give you a solid foundation in NumPy arrays and universal functions. You will also learn about plotting with Matplotlib and the related SciPy project through examples. "NumPy Cookbook" will help you to be productive with NumPy and write clean and fast code.
NumPy Cookbook
Credits
www.PacktPub.com
Preface
Free Chapter
Winding Along with IPython
Get to Grips with Commonly Used Functions
Connecting NumPy with the Rest of the World
Audio and Image Processing
Special Arrays and Universal Functions
Profiling and Debugging
Quality Assurance
Speed Up Code with Cython
Index

## Creating a scores table with recarray

The `recarray` class is a subclass of `ndarray`. They can hold records like in a database, with different data types. For instance, we can store records about employees, containing numerical data such as salary, and strings such as the employee name.

Modern economic theory tells us that an investing boils down to optimizing risk and reward. Risk is represented by the standard deviation of log returns (for more information on Arithmetic and logarithmic return visit http://en.wikipedia.org/wiki/Rate_of_return#Arithmetic_and_logarithmic_return). Reward on the other hand, is represented by the average of log returns. We can come up with a relative score, where a high score means low risk and high reward. We will calculate the scores for several stocks and store them together with the stock symbol using a table format in a NumPy `recarray` function.

### How to do it...

We will start by creating the record array.

1. Create the record array.

Create a record array with for...