Austin based Enthought offers their flagship scientific Python distribution, Canopy. The Canopy Geoscience (or Canopy Geo) variant of the product is a data analysis, exploration and visualization package optimized for geologists & geophysicists, and researchers in petroleum science.
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I was using Sublime Text Editor initially to edit and write most of my Python scripts, but a colleague recommended Enthought Canopy and I have been using it ever since then, because of its integrated packages for data analysis, its easier to execute and write relevant scripts …
Before Canopy with its python we were working with Matlab. We decided for Canopy against Matlab for two reasons: First, we believe that python together with NumPy or SciPy can achieve the objectives with less code and therefore less training, and second the prizes are much …
Enthought Canopy is best suites for scripting data analytical concepts. It has a wide range of data analytical libraries and also is good for data visualization. I would not recommend using Enthought Canopy only as an IDE, there may be better options available. If you're looking for a good data simulation & visualization package, Canopy it is.
Providing scientific libraries, both open source and Enthought's own libraries which are excellent.
Training. They provide several courses in python for general use and for data analysis.
Debugging tools. Several IDEs provides tools for debugging, but I think they are insufficient or too general. Canopy has a special debugging tool, specially design for python.
Before Canopy with its python we were working with Matlab. We decided for Canopy against Matlab for two reasons: First, we believe that python together with NumPy or SciPy can achieve the objectives with less code and therefore less training, and second the prizes are much lower than matlab which is most robust, expensive and less intuitive. It's clear we are making the comparison with python and it has nothing to with canopy. But with Canopy you feel you have all those tools close together without the problem of configuration, besides a lot of personalized libraries that complements a typical python environment.