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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.https://dudodiprj2sv7.cloudfront.net/product-logos/yy/dK/8NGFE6B0T5HO.pngCanopy is highly recommended for data analystsI currently use Enthought Canopy as my IDE for writing, editing and running Python scripts. It helps me keep track of all my Python programs and projects in one space. Canopy is good for data analysis and playing around with data to achieve a specific purpose. Currently I am the only one using Enthought Canopy at my team.,Canopy's editor has an integrated environment of having an editor and a Python shell attached to it The Documentation Browser is useful The analytic Python package distribution is definitely a plus,Canopy does not support Python 3 There were times the Python shell crashed, and I would have to restart it Some Python libraries are slow.,6,Its easier to define KPI's with Enthought It is good for reiteration and building on top of existing scripts Its dedicated Python console makes it easier to execute projects.,Sublime,SaltStack, Google Cloud StorageData analysis and scientific applications with python integrated in a beautifully designed environment.Enthought Canopy is the programming platform of choice by myself for python 2.7, and is the tool I'm currently using for my project. We are keeping track of a bunch of data and making a lot of analysis on them. I chose Canopy for its ease of use, and because they provide several libraries which are perfect for our purpose, specially for data analysis. Besides that Canopy offers several training courses which are very helpful. Canopy facilitates the incorporation of scientific libraries it works locally and provides its own compiler, that's why configuring a common environment for all the developers stop being a problem.,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.,Lack of python 3 support. I hope this will chance in the near future. Canopy is perfect for scientific application, but it would be even more perfect if they include more general purpose libraries.,9,Canopy increased our efficiency in processing , analyzing and plotting our data. Canopy reduced the cost of developing several libraries.,
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Enthought Canopy
2 Ratings
Score 6.0 out of 101
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Enthought Canopy Reviews

Enthought Canopy
2 Ratings
Score 6.0 out of 101
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March 28, 2018

Enthought Canopy Review: "Canopy is highly recommended for data analysts"

Score 6 out of 10
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Verified User
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I currently use Enthought Canopy as my IDE for writing, editing and running Python scripts. It helps me keep track of all my Python programs and projects in one space. Canopy is good for data analysis and playing around with data to achieve a specific purpose. Currently I am the only one using Enthought Canopy at my team.
  • Canopy's editor has an integrated environment of having an editor and a Python shell attached to it
  • The Documentation Browser is useful
  • The analytic Python package distribution is definitely a plus
  • Canopy does not support Python 3
  • There were times the Python shell crashed, and I would have to restart it
  • Some Python libraries are slow.
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.
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Jesús Aponte profile photo
February 11, 2016

Enthought Canopy: "Data analysis and scientific applications with python integrated in a beautifully designed environment."

Score 9 out of 10
Vetted Review
Verified User
Review Source
Enthought Canopy is the programming platform of choice by myself for python 2.7, and is the tool I'm currently using for my project. We are keeping track of a bunch of data and making a lot of analysis on them. I chose Canopy for its ease of use, and because they provide several libraries which are perfect for our purpose, specially for data analysis. Besides that Canopy offers several training courses which are very helpful. Canopy facilitates the incorporation of scientific libraries it works locally and provides its own compiler, that's why configuring a common environment for all the developers stop being a problem.
  • 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.
  • Lack of python 3 support. I hope this will chance in the near future.
  • Canopy is perfect for scientific application, but it would be even more perfect if they include more general purpose libraries.
Canopy is perfect for data analysis in general. If you are a programmer for general purpose commercial application perhaps Canopy is not the best choice. But if you are just beginning programming or making simulation with python I recommend using Canopy and its training platform, they have excellent teachers with impressive curriculum.
Read Jesús Aponte's full review

Enthought Canopy Scorecard Summary

About Enthought Canopy

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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