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x = sage.all.r('c(1,2,3)')
type(x)
v = x.sage(); print(v)
print(type(v))
<class 'sage.interfaces.r.RElement'> [1, 2, 3] <type 'list'> 
# Also get a string if you want (no copy/paste)
str(x)
'[1] 1 2 3' 
# The global variable "r" in a Sage worksheet is just a Jupyter kernel, and it has
# no useful "magic" regarding interfacing with the sage session. Use sage.all.r,
# which is a pexpect interface to R and is very powerful for this.  Alternatively,
# if your data is HUGE, then use rpy2.
r??

   File: /cocalc/lib/python2.7/site-packages/smc_sagews/sage_salvus.py
   Source:
   def r(code=None, **kwargs):
    r"""
    Run R code in a sage worksheet.

    INPUT:

    - ``code`` -- a string containing code

    Use as a decorator. For example, put this in a cell and evaluate it to see a scatter plot
    of built-in mtcars dataframe variables `mpg` vs `wt`::

        %r
        with(mtcars,plot(wt,mpg))

    .. note::

        SMC %r mode uses the jupyter `ir` kernel.
    """
    if r.jupyter_kernel is None:
        r.jupyter_kernel = jupyter("ir")
        r.jupyter_kernel('options(repr.plot.res = 240)')
        r.jupyter_kernel.smc_image_scaling = .5
    return r.jupyter_kernel(code, **kwargs)


%sage.all.r
v <- c(1,2,3)
[1] 1 2 3 
sage.all.r('v').sage()
[1, 2, 3]