What users are saying about
Top Rated
41 Ratings
Top Rated
41 Ratings
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Score 8.7 out of 101
2 Ratings
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Score 6 out of 101

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Likelihood to Recommend

Anaconda

Anaconda shines if you need to set up a data analysis or data science lab in no time. Newcomers to Python or Jupiter can be up and running in minutes and playing with the most popular packages. I think the Anaconda Cloud package could benefit from some UX improvements to clarify the migration process. Integration with external data sources could be improved as well.
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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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Feature Rating Comparison

Data Exploration

Anaconda
7.5
Enthought Canopy
Visualization
Anaconda
7.0
Enthought Canopy
Interactive Data Analysis
Anaconda
8.0
Enthought Canopy

Data Preparation

Anaconda
7.0
Enthought Canopy
Interactive Data Cleaning and Enrichment
Anaconda
7.0
Enthought Canopy
Data Transformations
Anaconda
8.0
Enthought Canopy
Data Encryption
Anaconda
6.0
Enthought Canopy
Built-in Processors
Anaconda
7.0
Enthought Canopy

Platform Data Modeling

Anaconda
5.7
Enthought Canopy
Automated Machine Learning
Anaconda
4.0
Enthought Canopy
Single platform for multiple model development
Anaconda
7.0
Enthought Canopy
Self-Service Model Delivery
Anaconda
6.0
Enthought Canopy

Model Deployment

Anaconda
4.5
Enthought Canopy
Flexible Model Publishing Options
Anaconda
5.0
Enthought Canopy
Security, Governance, and Cost Controls
Anaconda
4.0
Enthought Canopy

Pros

  • Integration of the most popular and useful Python packages
  • Managing multiple execution environments
  • Management of package dependencies
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  • 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

  • User Interface could be a little bit more clearer.
  • Error messaging can definitely be improved
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  • 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

  • We save a lot of programming time, since all the add-ons are in the same environment.
  • Being multiplatform, Anaconda is perfect for work teams with many people, since it supports all operating systems.
  • The only negative thing that can happen is that at first, the way of working in Anaconda can be a bit confusing. Once passed the learning period, its daily use is very comfortable.
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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