Using different IDEs (Anaconda, IDLE) for Python 2.7, 3.5 Respectively

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Discussion Overview

The discussion revolves around the use of different Integrated Development Environments (IDEs) for Python, specifically IDLE and Anaconda Navigator/Jupyter, in the context of Python versions 2.7 and 3.7. Participants explore challenges related to data analysis packages and seek recommendations for training resources.

Discussion Character

  • Exploratory, Technical explanation, Debate/contested

Main Points Raised

  • One participant expresses a desire to use IDLE and Anaconda for Python 2.7 and 3.7, respectively, while noting difficulties in finding data analysis packages for Python 3.x that are comparable to those available in Anaconda for 2.7.
  • Another participant shares their experience with Visual Studio Code and PyCharm, suggesting that PyCharm, especially in collaboration with Anaconda, could be beneficial for data science work.
  • A later reply introduces a question about machine learning with SQL Server 2017, indicating a potential interest in integrating SQL with Python for data science applications.
  • One participant mentions their lack of experience with machine learning but acknowledges the potential of SQL Server in production environments, while expressing concerns about the setup of a development environment.
  • There is a note about the relationship between JetBrains and PyCharm, suggesting that the independence of surveys regarding IDEs may be questionable.

Areas of Agreement / Disagreement

The discussion reflects a variety of experiences and preferences regarding IDEs for Python, with no clear consensus on the best approach or tools for data analysis. Participants have differing views on the usefulness of specific IDEs and the integration of machine learning with SQL Server.

Contextual Notes

Participants express uncertainty about the availability of data analysis packages in IDLE for Python 3.x and the implications of using SQL Server for machine learning, indicating a need for further exploration of these topics.

Who May Find This Useful

Individuals interested in using Python for data analysis, those exploring different IDEs for Python development, and participants looking to integrate machine learning with SQL Server may find this discussion relevant.

WWGD
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TL;DR
For complicated reasons it would be convenient for me to work with both IDEs. I can work with IDLE, but I get error messages when I try to work with Anaconda.
Hi,
I would like to be able to use both IDLE and Anaconda Navigator/Jupyter IDEs for Python 3.7 (64-bit), 2.7 respectfully. I can open up and work with IDLE. I understand Python 2.x is for legacy systems mostly but I spent a lot of time using data analysis packages in/with Anaconda for 2.7 and I am having trouble finding similar packages or just similar Data packs with IDLE for 3.x.

Alternatively, if someone knows of training for Data Science/Analysis using IDLE, Python 3.x , I would appreciate refs. I am just having trouble going through a maze of setups.
 
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I use Visual Studio Code, but then I don't do a lot of work in Python any more. When I did, I used PyCharm which I found excellent.

This may seem a bit off-topic, but I have recently noticed the headline "Anaconda and JetBrains Join Forces to Launch ‘PyCharm for Anaconda’" - if I was getting back into Python for data science I would definitely check this out.
 
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Thanks Pbuk,
Have you heard about doing ML with SQL Server 2017 (Bottom Option):

244388
 
No, I have no experience of ML. I just had a quick look at some of the MS stuff, it looks as though it could make sense in a production environment (where SQL Server is always at home) but I would hate to have to set up a development environment for it - in most SQL Server dev scenarios there is someone who is paid to do that for you!

You might be interested in this survey - note that JetBrains own PyCharm so it is not independent, and I would never use a survey for anything other than highlighting things I hadn't paid much attention to anyway.
 
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