IBM SPSS Modeler vs. Python IDLE

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
IBM SPSS Modeler
Score 7.8 out of 10
N/A
IBM SPSS Modeler is a visual data science and machine learning (ML) solution designed to help enterprises accelerate time to value by speeding up operational tasks for data scientists. Organizations can use it for data preparation and discovery, predictive analytics, model management and deployment, and ML to monetize data assets.
$499
per month
Python IDLE
Score 8.7 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.
$0
Pricing
IBM SPSS ModelerPython IDLE
Editions & Modules
IBM SPSS Modeler Personal
4,670
per year
IBM SPSS Modeler Professional
7,000
per year
IBM SPSS Modeler Premium
11,600
per year
IBM SPSS Modeler Gold
contact IBM
per year
No answers on this topic
Offerings
Pricing Offerings
IBM SPSS ModelerPython IDLE
Free Trial
YesNo
Free/Freemium Version
NoYes
Premium Consulting/Integration Services
YesNo
Entry-level Setup FeeOptionalNo setup fee
Additional DetailsIBM SPSS Modeler Personal enables users to design and build predictive models right from the desktop. IBM SPSS Modeler Professional extends SPSS Modeler Personal with enterprise-scale in-database mining, SQL pushback, collaboration and deployment, champion/challenger, A/B testing, and more. IBM SPSS Modeler Premium extends SPSS Modeler Professional by including unstructured data analysis with integrated, natural language text and entity and social network analytics. IBM SPSS Modeler Gold extends SPSS Modeler Premium with the ability to build and deploy predictive models directly into the business process to aid in decision making. This is achieved with Decision Management which combines predictive analytics with rules, scoring, and optimization to deliver recommended actions at the point of impact.—
More Pricing Information
Community Pulse
IBM SPSS ModelerPython IDLE
Considered Both Products
IBM SPSS Modeler
Chose IBM SPSS Modeler
IBM SPSS Modeler is considerably easier to use. It allows for very rapid development and the ability to get to a goal quickly. There is no need to learn a new programming language so the analyst has the ability to focus on the problem rather than the pedantics of managing …
Python IDLE

No answer on this topic

Top Pros
Top Cons
Best Alternatives
IBM SPSS ModelerPython IDLE
Small Businesses
Saturn Cloud
Saturn Cloud
Score 9.1 out of 10
PyCharm
PyCharm
Score 9.3 out of 10
Medium-sized Companies
Mathematica
Mathematica
Score 8.3 out of 10
PyCharm
PyCharm
Score 9.3 out of 10
Enterprises
Dataiku
Dataiku
Score 7.9 out of 10
PyCharm
PyCharm
Score 9.3 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
IBM SPSS ModelerPython IDLE
Likelihood to Recommend
10.0
(6 ratings)
2.1
(6 ratings)
Usability
-
(0 ratings)
10.0
(1 ratings)
Support Rating
10.0
(1 ratings)
8.0
(1 ratings)
User Testimonials
IBM SPSS ModelerPython IDLE
Likelihood to Recommend
IBM
Fast NLP analytics are very easy in SPSS Modeler because there is a built-in interface for classifying concepts and themes and several pre-built models to match the incoming text source. The visualizations all match and help present NLP information without substantial coding, typically required for word clouds and such. SPSS Modeler is good at attaining results faster in general, and the visual nature of the code makes a good tool to have in the data science team's repository. For younger data scientists, and those just interested, it is a good tool to allow for exploring data science techniques.
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Python Software Foundation
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
IBM
  • Combine text and data
  • Provide facilities for all phases of the data mining process.
  • Use a node and stream paradigm to easily and quickly create models.
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Python Software Foundation
  • Firstly, I would say Python IDLE interface is user friendly.
  • Easy to learn for the beginners.
  • Syntax highlighting is nice features.
  • Smart indent helps a lot.
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Cons
IBM
  • Has very old style graphs, with lots of limitations.
  • Some advanced statistical functions cannot be done through the menu.
  • The data connectivity is not that extensive.
  • It's an expensive tool.
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Python Software Foundation
  • 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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Usability
IBM
No answers on this topic
Python Software Foundation
The IDE Python IDLE is a good place to start as it helps you become familiar with the way Python works and understand its syntax.
This IDE allows you to configure the environment, font, size, colors, .....
It also looks like any simple text editor for any operating system, I work with Windows or Linux interchangeably, and you don't have to learn to use the IDE before programming.
Once the IDE is executed you can start programming directly in it.
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Support Rating
IBM
The online support board is helpful and the free add ons are incredibly appreciated.
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Python Software Foundation
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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Alternatives Considered
IBM
When it comes to investigation and descriptive we have found SPSS Statistics to be the tool of choice, but when it comes to projects with large and several datasets SPSS Modeler has been picked from our customers.
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Python Software Foundation
It's easy to set up and run quick analysis in Python IDLE on my local machine. The output is direct and easy to read. But sometimes I prefer Jupyter Notebook when the datasets are large, since it would take too long to run on my local machine. It is easier to run Jupyter Notebook on my cloud desktop
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Return on Investment
IBM
  • Positive - Ease of decision making and reduction in product life cycle time.
  • Positive - Gives entirely new perspective with the help of right team. Helps expanding the portfolio.
  • Negative - Needs to have good understanding about mathematical modelling, of which talent is rare and expensive. Hence, increase the costs for R&D and manpower.
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Python Software Foundation
  • 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

IBM SPSS Modeler Screenshots

Screenshot of Use a single run to test multiple modeling methods, compare results and select which model to deploy. Quickly choose the best performing algorithm based on model performance.Screenshot of Explore geographic data, such as latitude and longitude, postal codes and addresses. Combine it with current and historical data for better insights and predictive accuracy.Screenshot of Capture key concepts, themes, sentiments and trends by analyzing unstructured text data. Uncover insights in web activity, blog content, customer feedback, emails and social media comments.Screenshot of Use R, Python, Spark, Hadoop and other open source technologies to amplify the power of your analytics. Extend and complement these technologies for more advanced analytics while you keep control.