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Jupyter Notebook

Score8.5 out of 10

137 Reviews and Ratings

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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 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.

Categories & Use Cases

Key Features

Learn about the best (and worst!) features Jupyter Notebook has to offer, as determined by TrustRadius' reviewers.
Based on 137 ratings of Jupyter Notebook's features
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Top Performing Features

  • Connect to Multiple Data Sources

    Ability to connect to a wide variety of data sources including data lakes or data warehouses for data ingestion

    Category average: 8.7

  • Extend Existing Data Sources

    Use R or Python to create custom connectors for any APIs or databases

    Category average: 8.9

  • Interactive Data Cleaning and Enrichment

    Access to visual processors for data wrangling

    Category average: 9

Areas for Improvement

  • Self-Service Model Delivery

    Multiple model delivery modes to comply with existing workflows

    Category average: 8.3

  • MDM Integration

    Integration with MDM and metadata dictionaries

    Category average: 7.8

  • Visualization

    The product’s support and tooling for analysis and visualization of data.

    Category average: 8.2

Reviews

What users are saying about Jupyter Notebook.
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Jupyter Notebook User Review

Incentivized
Verified User
Analyst in Sales (1001-5000 employees employees)

Use Cases and Deployment Scope

We usually write python code in it as its interface is simple and easy to use. To reduce time and to automate daily task we started using python and to write code we searched for multiple interfaces and finally opted Jupyter Notebook.

Pros

  • Language
  • Interface
  • Scalability

Cons

  • Modification in interface

Return on Investment

  • Reduce time
  • Reduce effort
  • Reduced errors

Usability

Alternatives Considered

Python IDLE and PyCharm

Other Software Used

Microsoft Power BI, Adobe Acrobat, Adobe Acrobat Reader, Symantec Advanced Threat Protection

Feedback - Jupyter Notebook

Shailesh PandeyView profile
Laboratory Technician at Regency Healthcare - Kanpur (1001-5000 employees employees)

Use Cases and Deployment Scope

I do all my python projects with it every day and the amount of convenience it provides is unmatchable. It's interface is very easy and self expressive which is why I recommend it the most. It comes with the code sharing feature which i use when I get stuck somewhere or having some bug or needed any advice from the team lead.

Pros

  • Great interface.
  • Segments for codes.
  • Markdown for code explanation.

Cons

  • Sometimes I have to restart it when I import any new python library.
  • Should be available for more languages.

Most Important Features

  • Code sharing feature.
  • Markdown.
  • Code segments.

Return on Investment

  • Open source.
  • Makes coding easier.

Flexible, lightweight, and visually intuitive organization of your workflows

Incentivized
Lindsay VeazeyView profile
Senior Data Scientist in Engineering at Very (201-500 employees employees)

Pros

  • Visually intuitive organization of code.
  • Static (but changeable) display of function outputs.
  • Easy replication of notebooks or into new notebooks, or into PDFs.

Cons

  • I'd like to see bookmarks made available for easier scrolling through long notebooks.
  • A dark mode option would be helpful, too.
  • I wish that the display of graphics would be a little bit more customizable as a native function of Jupyter.

Most Important Features

  • Lightweight installation
  • Flexibility with different software languages
  • Straightforward duplication for adaptation

Return on Investment

  • 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

Alternatives Considered

Lucidchart, GitHub, Microsoft Visual Studio Code, Docker, Zoom, Slack and Microsoft Excel

Other Software Used

Slack, Tableau Desktop, Microsoft Visual Studio Code, Zoom, gedit, Docker

Jupyter Pros and Cons

Incentivized
Rita Lo
in Corporate at Lyft Inc. (1001-5000 employees employees)

Pros

  • Sharing/showcasing work in a step by step manner
  • Exploratory data analysis/viewing code in-line
  • Data exploration/visualization
  • Switch between different coding languages

Cons

  • No IDE integration/linting
  • No testing integrations
  • Difficult to view changes in GitHub
  • Notebook harder to productionize than scripts

Most Important Features

  • Data Visualization
  • Machine Learning
  • Statistical Modeling

Return on Investment

  • Positive understanding of where to invest next
  • Greater exposure to current business trends and forecasts
  • Pinpoint market leaders/laggers

Alternatives Considered

PyCharm

Other Software Used

Jira Software, Mode Analytics, Sublime Text

Python programming made easy with Jupyter!

Incentivized
Rounak Verma
Data Analyst in Engineering at Raymour and Flanigan (1001-5000 employees employees)

Pros

  • 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.

Cons

  • The ability to use night mode background.
  • The ability to select multiple lines of code to run and see the output.
  • The ability to open .py extension file as well along with .ipynb

Most Important Features

  • Easy download and sharing Python programming files easily across teams.
  • The libraries it hold helps a lot while building programs.
  • The ability to visualize certain results and see the output right away rather than using some other visualization tool.

Return on Investment

  • Jupyter Notebook helped me write an efficient code which helped us understand and forecast our sales number.
  • Jupyter Notebook is extremely cost effective for a small-medium organization.
  • The ability to use different formats of data sources helped us save a lot of cost spent after data source conversion software.

Alternatives Considered

PyCharm

Other Software Used

PyCharm, Tableau Desktop, DataGrip