#### 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
Advanced Indexing and Array Concepts
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

## Loading data as pandas objects from statsmodels

Statsmodels has quite a lot of sample datasets in its distributions. The complete list can be found at https://github.com/statsmodels/statsmodels/tree/master/statsmodels/datasets .

In this tutorial, we will concentrate on the copper dataset, which contains information about copper prices, world consumption, and other parameters.

Before we start, we might need to install patsy. It is easy enough to see if this is necessary just run the code. If you get errors related to patsy, you will need to execute any one of the following two commands:

```sudo easy_install patsy
pip install --upgrade patsy
```

### How to do it...

In this section, we will see how we can load a dataset from statsmodels as a Pandas `DataFrame` or `Series` object.

The function we need to call is `load_pandas`. Load the data as follows:
`data = statsmodels.api.datasets.copper.load_pandas()`
This loads the data in a `DataSet` object, which contains `pandas` objects.