Sure enough there are parts of matlab where matlab is without serious competitors. I think however that a majority of needs is available for Python, although I know that I do not represent everyone's needs.
I switched to Sci.Python at the point where I had difficulty treating time series data with Matlab. I know there is a toolboxy-thingy from mathworks but it either was not available or I did not find the documentation. Anyway, I quickly got started with Pandas. I had prior knowledge of Python and other mainstream programming languages before.
Spyder is a Matlab-ish IDE with a variable explorer, etc. Some like the Ipython Notebook which I think is great for demonstrations and teaching, but eventually does not scale when projects grow bigger.
Yeah, networkx is pretty good -- I actually meant that network analysis and text processing are the two areas where I'd be quite comfortable recommending Python over Matlab.
For time series data, I'd personally pick R though, or perhaps SAS if it's large enough -- at least if any statistical analysis is involved...
R design is somewhat like perl in the sense that usually there are a lot of ways of doing anything. This includes time series of course. That being said, last time I did time series, I've used xts and was quite happy with it.
Quick google search yielded: http://networkx.github.io/ do not know how it compares though.
I switched to Sci.Python at the point where I had difficulty treating time series data with Matlab. I know there is a toolboxy-thingy from mathworks but it either was not available or I did not find the documentation. Anyway, I quickly got started with Pandas. I had prior knowledge of Python and other mainstream programming languages before.
Spyder is a Matlab-ish IDE with a variable explorer, etc. Some like the Ipython Notebook which I think is great for demonstrations and teaching, but eventually does not scale when projects grow bigger.