R may still have an advantage when it comes to plotting simplicity.
On the Python side, matplotlib is still a bit of a pain, but has improved.
Also look at ggplot.py (alpha-ish?) and Bokeh from ContinuumIO
On the Python side, matplotlib is still a bit of a pain, but has improved.
Also look at ggplot.py (alpha-ish?) and Bokeh from ContinuumIO
and Vincent: https://github.com/wrobstory/vincent
Also the code examples given on AstroML to work well for figuring out how to make publication quality figures in Matplotlib: http://www.astroml.org/book_figures/
x = arange(0, 2*pi, 1e-2)
plot(x, sin(x)) set xrange [0:2*pi]
plot sin(x)
R may still have an advantage when it comes to plotting simplicity
But this about perspective. Coming from a Python background, I would rather stay in Python and work with matplotlib, seaborn, or even ggplot.py, than try to work my data management code into the R model.