Canopy is highly recommended for data analysts
March 28, 2018

Canopy is highly recommended for data analysts

Anonymous | TrustRadius Reviewer
Score 6 out of 10
Vetted Review
Verified User

Overall Satisfaction with Enthought Canopy

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.
  • 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
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.
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.