JMP vs. Python IDLE

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
JMP
Score 9.2 out of 10
N/A
JMP® is statistical analysis software with capabilities that span from data access to advanced statistical techniques, with click of a button sharing. The software is interactive and visual, and statistically deep enough to allow users to see and explore data.
$1,320
per year per user
Python IDLE
Score 8.9 out of 10
N/A
Python's IDLE is the integrated development environment (IDE) and learning platform for Python, presented as a basic and simple IDE appropriate for learners in educational settings.N/A
Pricing
JMPPython IDLE
Editions & Modules
JMP
$1320
per year per user
No answers on this topic
Offerings
Pricing Offerings
JMPPython IDLE
Free Trial
YesNo
Free/Freemium Version
NoYes
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional DetailsBulk discounts available.
More Pricing Information
Community Pulse
JMPPython IDLE
Best Alternatives
JMPPython IDLE
Small Businesses
IBM SPSS Statistics
IBM SPSS Statistics
Score 7.8 out of 10
PyCharm
PyCharm
Score 9.2 out of 10
Medium-sized Companies
Alteryx Platform
Alteryx Platform
Score 8.9 out of 10
PyCharm
PyCharm
Score 9.2 out of 10
Enterprises
Dataiku
Dataiku
Score 7.6 out of 10
PyCharm
PyCharm
Score 9.2 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
JMPPython IDLE
Likelihood to Recommend
9.0
(0 ratings)
3.2
(0 ratings)
Likelihood to Renew
10.0
(0 ratings)
-
(0 ratings)
Usability
8.0
(0 ratings)
8.2
(0 ratings)
Availability
10.0
(0 ratings)
-
(0 ratings)
Performance
10.0
(0 ratings)
-
(0 ratings)
Support Rating
9.2
(0 ratings)
8.0
(0 ratings)
Online Training
7.9
(0 ratings)
-
(0 ratings)
Implementation Rating
9.6
(0 ratings)
-
(0 ratings)
Product Scalability
10.0
(0 ratings)
-
(0 ratings)
User Testimonials
JMPPython IDLE
Likelihood to Recommend
Many organizations have seen their analytical capabilities, and the results from them, plateau. Of these, we've observed, that most of them didn't appreciate that they could do (even) better. These companies should definitely consider JMP. Any company that is research-based can benefit from accelerating their research, learning more in less time, effort and cost, with JMP's tools. Basically, any organization that is hungry enough for improvement to seek out better ways is suitable for JMP. Those who are happy with their current performance are not likely to consider the changes, though they were not major impediments by our clients, required.
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IDLE is a good option to run small scripts directly on the console, and that's it. It is a good exit when you don't want or need to open a proper IDE like Pycharm.
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Pros
  • Graphs are more detail-oriented and contain statistical inferences.
  • Everything is drag and drop. Pretty much easy to use and handle and also to learn.
  • Importing and exporting the results are easy and they can be attached with any other tool for processing.
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  • The best thing is the debug that incorporates.
  • Friendly graphic environment.
  • Provide keyword auto-fill.
  • Color the command syntax automatically.
  • Very configurable.
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Cons
  • Loading a large amount of data is very tedious as it takes a lot of time and it crashes very frequently.
  • I dislike the limited options they have in terms of statistical models or analysis tools.
  • Variable value designation is a big problem in JMP, the software fails to recognize the type of data when it comes to the numeric value.
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  • Too simplistic
  • Could not find source revision management integration support
  • Only basic debugging is available
  • Does not have data-science-specific notebooks (but can be installed separately)
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Likelihood to Renew
I've mentioned this earlier, but the licensing agreements are very prohibitive. I work with a company where my role has become less and less doing my own analytics and more and more trying to help other people in that role. As we are bringing more people "up to speed" it's hard to justify licenses for 2-3 people when they aren't full time, Six Sigma black belts just looking at stats all day. A floating license option would make this a no-brainer, since these people could continue their other work and add JMP usage as they grow their skills, but this is not something JMP/SAS has offered.
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No answers on this topic
Usability
The GUI interface makes it easier to generate plots and find statistics without having to write code. The JSL scripting is a bit of a steep learning curve but does give you more ability to customize your analysis. Overall, I would recommend JMP as a good product for overall usability.
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1-Ease of use: python IDLE is relatively ease to use,especially for developers familiar with python. Its simple and intuitive interface makes it easy to navigate and find basic features 2- learnability:python IDLE is relatively easy to learn especially for developers with prior experience with python or other programming Languages 3- efficiency: Python IDLE efficiency is limited by its basic feature set and lack of advanced tools.while it’s great for rapid prototyping and small scale developers
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Support Rating
The helpful tips are great for new users. I am always able to find solutions to a tool I am working with through the hep section. And my area has a users group that meets each quarter to share ideas and view upcoming JMP revisions.
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Python IDLE support is what the community can give you. As it is free software, it does not have support provided by the manufacturer or by third-parties.
In any case, for most of the problems that normal users can find, the solution, or alternatives, can be found quickly online.
As this IDE is made in Python, the support is the same group of Python developers.
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Online Training
I have not used your online training. I use JMP manuals and SAS direct help.
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No answers on this topic
Alternatives Considered
We actually use both JMP and IBM SPSS, but I think JMP's complexity lends itself to more in-depth statistical analyses. SPSS is designed for that as well, but we tend to use it more for quicker analyses, and we have found that JMP is far more powerful.
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I chose python IDLE for its simplicity and ease of use, which made it ideal for rapid prototyping and small scale development future sets: while python IDLE offers a basic set of features, including syntax highlighting, auto completion and basic debugging tools Performance :python IDLE is relatively lightweight and doesn’t require significant system resources, making it an excellent choice for older machines or resources constrained environment
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Return on Investment
  • JMP has resulted in literally millions of dollars in ROI due to identification of correctable errors.
  • Use of JMP control charts JMP has greatly simplified and improved interpretation of Lean, FMEA, and PDSA type analyses.
  • Use of JMP has enable the testing and subsequent selection of 'best practices' saving uncounted hours in false starts based on 'collective experience'.
  • The down side is that JMP is not a 'magic box', one still has to take care in applying the tools properly. Moreover, time-consuming approaches using JMP may still be the 'order of the day', because the service (even power user) is unaware of significant shortcuts available for free on the JMP community website.
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  • In a short time, we were able to develop several ML models for various teams to make accurate decisions.
  • Beginners can easily understand and adapt to GUI.
  • We could automate several manual validation tasks and so could reduce human intervention.
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ScreenShots

JMP Screenshots

Screenshot of in JMP, how all graphical displays and the data table are linked.Screenshot of a few designed experiments, for more understanding and maximum impact. Users can understand cause and effect using statistically designed experiments — even with limited resources.Screenshot of an example of Predictive Modeling in JMP Pro's Prediction Profiler, used to build better models for more confident decision making.Screenshot of example outputs, built with tools designed for quality and reliability.