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NumPy Cookbook

You're reading from  NumPy Cookbook

Product type Book
Published in Oct 2012
Publisher Packt
ISBN-13 9781849518925
Pages 226 pages
Edition 1st Edition
Languages

Table of Contents (17) Chapters

NumPy Cookbook
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. Winding Along with IPython 2. Advanced Indexing and Array Concepts 3. Get to Grips with Commonly Used Functions 4. Connecting NumPy with the Rest of the World 5. Audio and Image Processing 6. Special Arrays and Universal Functions 7. Profiling and Debugging 8. Quality Assurance 9. Speed Up Code with Cython 10. Fun with Scikits Index

Interfacing with R


RPy2 can only be used to call R from Python, and not the other way around. We will import some sample R datasets, and plot the data of one of them.

Getting ready

Install RPy2 if necessary. See the previous recipe.

How to do it...

Let's start by loading a sample R dataset.

  1. Load a data set into an array.

    Load the datasets with the RPy2 importr function. This function can import R packages. In this example, we will import the datasets R package. Create a NumPy array from the mtcars dataset:

    datasets = importr('datasets')
    mtcars = numpy.array(datasets.mtcars)
  2. Plot the dataset.

    Plot the dataset with Matplotlib:

    matplotlib.pyplot.plot(mtcars)
    matplotlib.pyplot.show()

    The following image shows the data, which is a two dimensional array:

The complete code for this recipe is as follows:

from rpy2.robjects.packages import importr
import numpy
import matplotlib.pyplot

datasets = importr('datasets')
mtcars = numpy.array(datasets.mtcars)

matplotlib.pyplot.plot(mtcars)
matplotlib.pyplot.show...
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