- NumPy Cookbook
- Table of Contents
- 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
- Introduction
- Using the buffer protocol
- Using the array interface
- Exchanging data with MATLAB and Octave
- Installing RPy2
- Interfacing with R
- Installing JPype
- Sending a NumPy array to JPype
- Installing Google App Engine
- Deploying NumPy code in the Google cloud
- Running NumPy code in a Python Anywhere web console
- Setting up PiCloud
- 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
- Introduction
- Installing scikits-learn
- Loading an example dataset
- Clustering Dow Jones stocks with scikits-learn
- Installing scikits-statsmodels
- Performing a normality test with scikits-statsmodels
- Installing scikits-image
- Detecting corners
- Detecting edges
- Installing Pandas
- Estimating stock returns correlation with Pandas
- Loading data as pandas objects from statsmodels
- Resampling time series data
- Index
R is a popular scripting language used for statistics and data analysis. RPy2 is an interface between R and Python. We will install RPy2 in this recipe.
If you want to install RPy2, choose one of the following options:
- Installing with
piporeasy_install.RPy2 is available on PYPI, so we can install it with either of the following two commands:
easy_install rpy2or
sudo pip install rpy2 - Installing from source.
We can install RPy2 from the source
tar.gz:tar -xzf <rpy2_package>.tar.gz cd <rpy2_package> python setup.py build install
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