Jupyter Notebook

Overview
Product	Rating	Most Used By	Product Summary	Starting Price
Jupyter Notebook	Score 8.9 out of 10	N/A	Jupyter Notebook is an open-source web application that allows users to create and share documents containing live code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, and machine learning. It supports over 40 programming languages, and notebooks can be shared with others using email, Dropbox, GitHub and the Jupyter Notebook Viewer. It is used with JupyterLab, a web-based IDE for…	N/A

Pricing

Jupyter Notebook

Editions & Modules

No answers on this topic

Offerings

Pricing Offerings
Jupyter Notebook
Free Trial
No
Free/Freemium Version
No
Premium Consulting/Integration Services
No

Entry-level Setup Fee

No setup fee

Additional Details

—

More Pricing Information

Community Pulse
	Jupyter Notebook
Considered Both Products	Jupyter Notebook Verified User Engineer Chose Jupyter Notebook Jupyter is very easy to understand and easy to use. And can also be used by a student, freelancer, small industries, big industries. Jupyter also provides you a tool to work with machine learning and artificial intelligence. Helpful? Verified User Team Lead Chose Jupyter Notebook Negligible or no cost, Highly efficient, effective, scalable , hasslefree Incentivized Helpful? Shivam Rai Senior Implementation Services Assistant Chose Jupyter Notebook Jupyter Notebook is very attractive platform for new developers to code and to learn programming and perform tasks as compared to other IDE. It has very well and easy visualization, interactive programming and sharing the live code and slideshow is very easy as compare to … Helpful? RL Rita Lo Analyst Chose Jupyter Notebook Jupyter is still the most well known and widely used platform I've seen. Using it over other competition like Zeppelin simply because of its availability, and my familiarity with its functionality. Incentivized Helpful? Lindsay Veazey Senior Data Scientist Chose Jupyter Notebook Jupyter Notebook is unique in that it offers a flexible, lightweight, easy-to-replicate way of organizing your code in a visually intuitive fashion that can be exported in a number of formats. I've found that the broad functionalities available within the notebooks suit a lot … Incentivized Helpful? Ejaz Hussain Senior Analyst Chose Jupyter Notebook Well, so far Jupyter Notebook has been the better tool for me. It gives us more freedom & has more ability to train ML models & do the data visualization more efficiently. It's easier to operate & has a very simple-to-understand UI & with the support for taking data from … Incentivized Helpful? RV Rounak Verma Data Analyst Chose Jupyter Notebook I have used PyCharm as well as Jupyter Notebook and for me, Jupyter wins almost every time. I really like its user-friend interface for someone who is new to python programming. The ability to run a big chunk of code part by part is a big game-changer for me. One thing I would … Incentivized Helpful? Hemant Jajoo Machine Learning Intern Chose Jupyter Notebook It should have cleaner support for multi-environment setup and should also increase the amount of features. Moreover, more support should be present for other programming languages. It should also have the option to set a specific location that opens up whenever I run command … Incentivized Helpful? AJ Ayushi Jain Technical Specialist Chose Jupyter Notebook Jupyter is easier to handle and user friendly. We have free access to it and its cell by cell executing feature is amazing. Incentivized Helpful? Verified User Engineer Chose Jupyter Notebook Jupyter Notebook has a nicer interface than RStudio in our opinion and since most of our group is familiar with Jupyter Notebook it has made it a default choice. Overall the interactive programming as well as the easy visualizations, model deployment, and markdown made Jupyter … Incentivized Helpful? Verified User Professional Chose Jupyter Notebook Jupyter Notebook is the core feature extended on by many commercial alternatives. The commercial alternatives have more feature integration with the rest of their portfolio. RStudio is another competitor for interactive and literate programming. Incentivized Helpful? Arpit Ranka Graduate Student Chose Jupyter Notebook haven't actually explored as I decided to use it on a friend 's recommendation. Incentivized Helpful? Verified User Employee Chose Jupyter Notebook An interesting thing is that Jupyter Notebook is run on browser environments which may or may not be a positive feature according to cases. VS Code on [the] other hand doesn't use any interface and can run Jupyter Notebooks too. Sometimes my browser consumes too much RAM due to … Incentivized Helpful? Irene Rodríguez Alegre Data Scientist - HF Radar Chose Jupyter Notebook It was great to import and export data and plots using Jupyter Incentivized Helpful? RK Rahul Kapoor Software Engineer Chose Jupyter Notebook With Jupyter Notebook besides doing data analysis and performing complex visualizations you can also write machine learning algorithms with a long list of libraries that it supports. You can make better predictions, observations etc. with it which can help you achieve better … Incentivized Helpful? JJ Jewon Ju Data Analyst Chose Jupyter Notebook I like Jupyter Notebook over the other two because it keeps my work more organized. It helps me to structure my workflow and the ability to run commands in chunks keeps me from being confused when coming back to the work after some time. Incentivized Helpful? YX Yaxian Xie BIE Chose Jupyter Notebook I selected Jupyter Notebook because this is better integrated with the existing production systems than optional tools (for example, R). It is also commonly used tool within the scientist community. Incentivized Helpful? Verified User Program Manager Chose Jupyter Notebook When I tried Zeppelin in 2017, it was still in initial versions, Jupyter was way ahead as of then. Zeppelin had limitations and I wasn't confident of it making progress as much as Jupyter. Incentivized Helpful?
Top Pros	Pro Easy to use Pro Data analysis Pro Easy navigation
Top Cons	Minus Version control systems Minus No code Minus Version control

Features

Jupyter Notebook

Platform Connectivity

Comparison of Platform Connectivity features of Product A and Product B
	Jupyter Notebook 8.5 21 Ratings 1% above category average
Connect to Multiple Data Sources	9.021 Ratings
Extend Existing Data Sources	9.220 Ratings
Automatic Data Format Detection	8.514 Ratings
MDM Integration	7.415 Ratings

Data Exploration

Comparison of Data Exploration features of Product A and Product B
	Jupyter Notebook 9.6 21 Ratings 13% above category average
Visualization	9.621 Ratings
Interactive Data Analysis	9.621 Ratings

Data Preparation

Comparison of Data Preparation features of Product A and Product B
	Jupyter Notebook 9.0 21 Ratings 9% above category average
Interactive Data Cleaning and Enrichment	9.320 Ratings
Data Transformations	8.921 Ratings
Data Encryption	8.514 Ratings
Built-in Processors	9.314 Ratings

Platform Data Modeling

Comparison of Platform Data Modeling features of Product A and Product B
	Jupyter Notebook 8.9 21 Ratings 5% above category average
Multiple Model Development Languages and Tools	9.020 Ratings
Automated Machine Learning	9.218 Ratings
Single platform for multiple model development	9.221 Ratings
Self-Service Model Delivery	8.020 Ratings

Model Deployment

Comparison of Model Deployment features of Product A and Product B
	Jupyter Notebook 8.8 19 Ratings 3% above category average
Flexible Model Publishing Options	8.819 Ratings
Security, Governance, and Cost Controls	8.718 Ratings

Best Alternatives
	Jupyter Notebook
Small Businesses	IBM SPSS Modeler Score 7.8 out of 10
Medium-sized Companies	Mathematica Score 8.2 out of 10
Enterprises	IBM SPSS Modeler Score 7.8 out of 10
All Alternatives	View all alternatives

User Ratings
	Jupyter Notebook
Likelihood to Recommend	8.4 (22 ratings)
Usability	10.0 (1 ratings)
Support Rating	9.0 (1 ratings)

User Testimonials
	Jupyter Notebook
Likelihood to Recommend	Open Source I've created a number of daisy chain notebooks for different workflows, and every time, I create my workflows with other users in mind. Jupiter Notebook makes it very easy for me to outline my thought process in as granular a way as I want without using innumerable small. inline comments. Incentivized Lindsay Veazey Senior Data Scientist Read full review
Pros	Open Source Simple and elegant code writing ability. Easier to understand the code that way. The ability to see the output after each step. The ability to use ton of library functions in Python. Easy-user friendly interface. Incentivized RV Rounak Verma Data Analyst Read full review
Cons	Open Source Need more Hotkeys for creating a beautiful notebook. Sometimes we need to download other plugins which messes [with] its default settings. Not as powerful as IDE, which sometimes makes [the] job difficult and allows duplicate code as it get confusing when the number of lines increases. Need a feature where [an] error comes if duplicate code is found or [if a] developer tries the same function name. Incentivized Verified User Anonymous Read full review
Usability	Open Source Jupyter is highly simplistic. It took me about 5 mins to install and create my first "hello world" without having to look for help. The UI has minimalist options and is quite intuitive for anyone to become a pro in no time. The lightweight nature makes it even more likeable. Incentivized Verified User Anonymous Read full review
Support Rating	Open Source I haven't had a need to contact support. However, all required help is out there in public forums. Incentivized Verified User Anonymous Read full review
Alternatives Considered	Open Source With Jupyter Notebook besides doing data analysis and performing complex visualizations you can also write machine learning algorithms with a long list of libraries that it supports. You can make better predictions, observations etc. with it which can help you achieve better business decisions and save cost to the company. It stacks up better as we know Python is more widely used than R in the industry and can be learnt easily. Unlike PyCharm jupyter notebooks can be used to make documentations and exported in a variety of formats. Incentivized RK Rahul Kapoor Software Engineer Read full review
Return on Investment	Open Source Positive impact: flexible implementation on any OS, for many common software languages Positive impact: straightforward duplication for adaptation of workflows for other projects Negative impact: sometimes encourages pigeonholing of data science work into notebooks versus extending code capability into software integration Incentivized Lindsay Veazey Senior Data Scientist Read full review
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