Enthought Canopy Geoscience (or Canopy Geo) variant of the product was a data analysis, exploration and visualization package optimized for geologists & geophysicists, and researchers in petroleum science. The product is discontinued.
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Enthought Canopy (discontinued)
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Enthought Canopy (discontinued)
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Chose Enthought Canopy (discontinued)
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 …
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Ayudante Académico Nivel II at Universidad Simón Bolívar (Higher Education, 1001-5000 employees)
Chose Enthought Canopy (discontinued)
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 …
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
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.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
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.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
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.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
