What users are saying about

Anaconda

Top Rated
33 Ratings

Anaconda

Top Rated
33 Ratings
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Score 8.8 out of 101

Enthought Canopy

2 Ratings
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Score 6 out of 101

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Likelihood to Recommend

Anaconda

Anaconda is great for academic and private organizations that cannot afford more expensive Python/R package managers. Also, it is more appropriate for intermediate to advanced Python users--Anaconda can be somewhat frustrating for beginners, as it takes some practice to get comfortable with the workflow. I find it particularly useful for working in teams, because if everyone uses the same package manager, it is easier to troubleshoot issues and makes for reproducible research. For wealthier organizations, a premium package management system (with tech support) would be ideal. Anaconda is also great for people working independently on code development.
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Enthought Canopy

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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Pros

  • Anaconda has iPython- Notebook that facilitates code writing in Python
  • It's very easy to install tour preferred the Python version
  • The risk of messing up the libraries is completely eliminated
Mauricio Quiroga-Pascal Ortega profile photo
  • 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
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Cons

  • It's hard to get security updates when you leave the system packages
  • There're some PyPI packages that Anaconda doesn't have. This obligates the user to package it by herself or using pip
  • Anaconda isn't as fast as PyPI publications
Mauricio Quiroga-Pascal Ortega profile photo
  • 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.
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Alternatives Considered

Anaconda is way easier to set-up. On Anaconda we have users working on Machine Learning in minutes, where on PyCharm is takes a lot longer to set-up and often involves getting help from IT. PyCharm is easier to integrate with Code repositories (such as GitHub), so if that's very important to you, you might want to take a look at PyCharm
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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 in one space. It definitely makes work life easier and effective.
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Return on Investment

  • Centralized repository for all notebooks and analysis projects.
  • Solved for some security concerns from IT.
  • Saves money by avoiding ad-hoc computer resources for analysts.
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  • 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.
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Pricing Details

Anaconda

General
Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No
Additional Pricing Details

Enthought Canopy

General
Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No
Additional Pricing Details