Skip to main content
TrustRadius
Jupyter Notebook

Jupyter Notebook

Overview

What is Jupyter Notebook?

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…

Read more
Recent Reviews

TrustRadius Insights

Jupyter Notebook has found a wide range of use cases across various industries and roles. Data analysts, scientists, and engineers have …
Continue reading

A Notebook for All

10 out of 10
October 24, 2021
Incentivized
Jupyter Notebook is a coffee to me, a daily dose of it makes my day. I have been using Jupyter Notebook for various purposes from …
Continue reading
Read all reviews

Awards

Products that are considered exceptional by their customers based on a variety of criteria win TrustRadius awards. Learn more about the types of TrustRadius awards to make the best purchase decision. More about TrustRadius Awards

Popular Features

View all 16 features
  • Interactive Data Analysis (21)
    9.6
    96%
  • Visualization (21)
    9.6
    96%
  • Connect to Multiple Data Sources (21)
    9.0
    90%
  • Data Transformations (21)
    8.9
    89%
Return to navigation

Pricing

View all pricing
N/A
Unavailable

What is Jupyter Notebook?

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…

Entry-level set up fee?

  • No setup fee
For the latest information on pricing, visithttps://www.trustradius.com/buyer…

Offerings

  • Free Trial
  • Free/Freemium Version
  • Premium Consulting/Integration Services

Would you like us to let the vendor know that you want pricing?

29 people also want pricing

Alternatives Pricing

What is Rational BI?

Rational BI provides analytics, data science and business intelligence in an analytical platform that connects to databases, data files and cloud drives including AWS and Azure data sources, enabling users to explore and visualize data. Users can build real-time notebook-style reports directly in a…

Return to navigation

Product Demos

H2O TensorFlow Deep Learning Demo

YouTube

EXPORT JUPYTER to EXCEL | nb2xls | Demo & My Thoughts | Jupyter Notebook to Excel Spreadsheet

YouTube

Jupyter Notebook using Docker for Data Science (Demo)

YouTube

Lecture 11, Python Demo for Distribution

YouTube
Return to navigation

Features

Platform Connectivity

Ability to connect to a wide variety of data sources

8.5
Avg 8.5

Data Exploration

Ability to explore data and develop insights

9.6
Avg 8.4

Data Preparation

Ability to prepare data for analysis

9
Avg 8.2

Platform Data Modeling

Building predictive data models

8.9
Avg 8.5

Model Deployment

Tools for deploying models into production

8.8
Avg 8.6
Return to navigation

Product Details

What is Jupyter Notebook?

Jupyter Notebook Video

How to install and use Jupyter Notebooks, a step by step tutorial. Learn to when to use Jupyter Notebooks, and how to write and run code and markdown.

Jupyter Notebook Technical Details

Operating SystemsUnspecified
Mobile ApplicationNo

Frequently Asked Questions

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 Jupyter notebooks, code, and data, with a configurable user interface that supports a wide range of workflows in data science, scientific computing, and machine learning.

Reviewers rate Visualization and Interactive Data Analysis highest, with a score of 9.6.

The most common users of Jupyter Notebook are from Enterprises (1,001+ employees).
Return to navigation

Comparisons

View all alternatives
Return to navigation

Reviews and Ratings

(124)

Community Insights

TrustRadius Insights are summaries of user sentiment data from TrustRadius reviews and, when necessary, 3rd-party data sources. Have feedback on this content? Let us know!

Jupyter Notebook has found a wide range of use cases across various industries and roles. Data analysts, scientists, and engineers have utilized Jupyter Notebook to handle different types of data, including csv, excel, and json files for efficient data analysis in banking and e-learning industries. The flexibility of the notebook allows users to organize workflows into manageable chunks, making them easier to replicate for future projects. Additionally, it has been widely adopted by Science and Analytics departments for tasks such as data wrangling, graph visualization, machine learning model creation, and suite of analyses to understand business landscapes. Jupyter Notebook has also been instrumental in training and fine-tuning machine learning models efficiently, as well as automating tasks like scraping data from PDFs. With its ability to integrate with cloud desktops and production systems, Jupyter Notebook is widely used by data scientists in organizations. Furthermore, it serves as a platform for collaboration and code sharing among teams, making it valuable for project management. Overall, Jupyter Notebook's interactive environment and flexibility have made it a versatile tool recommended for data analysts, managers, engineers, and data scientists seeking to explore, analyze, visualize, and deploy Python code efficiently.

Intuitive Organization: Users have found Jupyter Notebook's visually intuitive organization of code to be beneficial for understanding and navigating through different sections. This seamless workflow has increased productivity for many reviewers.

Static but Changeable Display: The static but changeable display of function outputs in Jupyter Notebook has been highly valued by users, allowing them to easily replicate notebooks or convert them into PDFs for documentation and sharing purposes. This feature provides a convenient way to showcase analysis results and collaborate with others.

Step-by-Step Output Viewing: Many users appreciate the ability to see the output after each step in Jupyter Notebook, enabling a step-by-step approach to data analysis and visualization. This functionality helps users identify and rectify errors or inconsistencies in their code efficiently.

Limited Features: Some users have expressed that Jupyter Notebook lacks certain features and functionality, such as limited markdown styling and the inability to handle multiple kernels. They feel that these limitations restrict their ability to fully utilize the software for their needs.

Difficult Code Styling and Navigation: A common concern among users is the difficulty in styling Python code within Jupyter Notebook and navigating through long notebooks. Several reviewers have suggested the addition of bookmarks or easier ways to navigate, as they find it time-consuming and cumbersome to work with large amounts of code.

Absence of Dark Mode Option: The absence of a dark mode option has been mentioned by several users as a helpful feature that could improve the user experience. They believe that having a dark mode would reduce eye strain during prolonged usage sessions and enhance overall readability.

Attribute Ratings

Reviews

(1-1 of 1)
Companies can't remove reviews or game the system. Here's why
October 22, 2020

Jupyter or nothing

Score 10 out of 10
Vetted Review
Verified User
Incentivized
I started using Jupyter to solve my everyday problems and to do things faster. I'm aware that there a few users already across the organization. I have been recommended to use it and I have also recommended this fantastic tool. With Jupyter, it's really easy to break the problem into small pieces and develop larger, more productive code. It's also easy to enhance without breaking the remaining part of code. I develop working code as and when time permits, integrate with different tools (through API, DB calls, etc), and even plot beautiful graphs all in one notebook. The best thing is that the results are saved when I reopen the notebook.
  • Saves the results until next time the notebook is reopened
  • Provides so many libraries
  • Allows to code on multiple platforms
  • Automatically creates checkpoints
  • Really lightweight
  • Would like to see syntax errors highlighted while coding
  • PDF integration should get better to print notebook results
Juypter suits developers the most, who want to write small pieces of code and create larger modules. Jupyter is also suited when creating smaller integration scenarios. Jupyter enables creating neat graphical charts for analysts very quickly. It is particularly easy to create and share notebooks to who so ever. For Enterprise-grade scenarios and large scale implementations, Jupyter may not be the best fit.
Platform Connectivity (4)
85%
8.5
Connect to Multiple Data Sources
90%
9.0
Extend Existing Data Sources
90%
9.0
Automatic Data Format Detection
90%
9.0
MDM Integration
70%
7.0
Data Exploration (2)
100%
10.0
Visualization
100%
10.0
Interactive Data Analysis
100%
10.0
Data Preparation (4)
55%
5.5
Interactive Data Cleaning and Enrichment
40%
4.0
Data Transformations
50%
5.0
Data Encryption
40%
4.0
Built-in Processors
90%
9.0
Platform Data Modeling (3)
86.66666666666666%
8.7
Multiple Model Development Languages and Tools
100%
10.0
Automated Machine Learning
80%
8.0
Single platform for multiple model development
80%
8.0
Model Deployment (2)
45%
4.5
Flexible Model Publishing Options
80%
8.0
Security, Governance, and Cost Controls
10%
1.0
  • Saves Time
  • Easy to develop
  • Very easy to setup and adapt
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.
I haven't had a need to contact support. However, all required help is out there in public forums.
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.
Return to navigation