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    <p>As pointed out by @lgautier, there is already <a href="https://stackoverflow.com/q/5630441/1290420">another answer on this subject</a>. I leave my answer here as it adds the experience of approaching R as a novice, knowing Python first.</p> <hr> <p>I use both Python and R and sympathise with your need as a newcomer to R. </p> <p>Since any answer you get will be subjective, I summarise a few points from my experience:</p> <ul> <li>I use <a href="http://rpy.sourceforge.net/rpy2.html" rel="noreferrer">rpy2</a> as my interface and find it is 'Pythonic', stable, predictable, and effective enough for my needs. I have not used the other packages so this is not a comment on them, rather on the merits of rpy2 itself.</li> <li>BUT do not expect that there will be an easy way of using R in Python without learning both. I find that adding an interface between the two languages allows ease of coding when you know both, but a nightmare of debugging for someone who is deficient in one of the languages.</li> </ul> <p>My advice:</p> <ol> <li>For most applications, Python has packages that allow you to do most of the things that you want to do in R, from data wrangling to plotting. Check out <a href="http://www.scipy.org/" rel="noreferrer">SciPy</a>, <a href="http://www.numpy.org/" rel="noreferrer">NumPy</a>, <a href="http://pandas.pydata.org/" rel="noreferrer">pandas</a>, <a href="http://biopython.org/wiki/Biopython" rel="noreferrer">BioPython</a>, <a href="http://matplotlib.sourceforge.net/" rel="noreferrer">matplotlib</a> and other scientific packages, or even the full <a href="https://store.continuum.io/cshop/anaconda/" rel="noreferrer">Anaconda</a> or <a href="http://www.enthought.com/products/epd.php" rel="noreferrer">Enthought</a> python distributions. This allows you to stay within the Python environment and provides you most of the power that you need.</li> <li>At the same time, you will want R's vast range of specialised packages, so spend some time learning it in an interactive environment. I found it almost impossible to master even basic R on the command line, but <a href="http://rstudio.org/" rel="noreferrer">RStudio</a> and the tutorials at <a href="http://www.statmethods.net/" rel="noreferrer">Quick-R</a> and <a href="http://learnr.wordpress.com/" rel="noreferrer">Learn-R</a> got me going very fast.</li> </ol> <p>Once you know both, then you will do magic with <a href="http://rpy.sourceforge.net/rpy2.html" rel="noreferrer">rpy2</a> without the horrors of cross-language debugging.</p> <hr> <h2>New Resources</h2> <p><strong>Update on 29 Jan 2015</strong></p> <p>This answer has proved popular and so I thought it would be useful to point out two more recent resources:</p> <ul> <li>Ralph Heinkel gave a great talk on this subject at EuroPython 2014. The video on <a href="https://www.youtube.com/watch?v=ucJ2-5a2CAA" rel="noreferrer"><em>Combining the powerful worlds of Python and R</em></a> is available on the <a href="https://www.youtube.com/channel/UCadZ6_NWdCN6YolgQdfV8Pg" rel="noreferrer">EuroPython YouTube channel</a>. Quoting him:</li> </ul> <blockquote> <p>The triplet <a href="http://www.r-project.org" rel="noreferrer" title="R">R</a>, <a href="https://rforge.net/Rserve/" rel="noreferrer" title="Rserve">Rserve</a>, and <a href="https://pypi.python.org/pypi/pyRserve/" rel="noreferrer" title="pyRserve">pyRserve</a> allows the building up of a network bridge from Python to R: Now R-functions can be called from Python as if they were implemented in Python, and even complete R scripts can be executed through this connection.</p> </blockquote> <ul> <li>It is now possible to combine R and Python using <a href="http://rpy.sourceforge.net/rpy2/doc-2.4/html/interactive.html#module-rpy2.ipython.rmagic" rel="noreferrer"><code>rmagic</code> in <code>IPython/Jupyter</code></a> greatly easing the work of producing reproducible research and notebooks that combine both languages.</li> </ul>
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    1. COI found debugging R code from within Python quite hard. For example, `browser` statements where not picked up. What is you experience?
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    2. CO@PaulHiemstra: same here. I could never be sure whether something failed to work (a) because I had a bug in Python or R or (b) because rpy2 was not working or (c) a combination. Nowadays I code the bit I need in R directly and then execute the script from within Python if I need it.
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    3. CObrowser is currently not working from within rpy2 ( https://bitbucket.org/lgautier/rpy2/issue/66/segfault-when-using-browser-inside-rpy2). An error happening during the evaluation of R code will raise an RRuntimeError exception, which should tell where the point of failure was in R or Python.
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