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Jupyter Notebook has found a wide range of use cases across various industries and roles. Data analysts, scientists, and engineers have …
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…
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Popular Features
- Visualization (22)9.595%
- Interactive Data Analysis (22)9.595%
- Connect to Multiple Data Sources (22)9.090%
- Data Transformations (22)8.989%
Video Reviews
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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…
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Product Demos
H2O TensorFlow Deep Learning Demo
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EXPORT JUPYTER to EXCEL | nb2xls | Demo & My Thoughts | Jupyter Notebook to Excel Spreadsheet
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Jupyter Notebook using Docker for Data Science (Demo)
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Lecture 11, Python Demo for Distribution
YouTube
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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 Systems | Unspecified |
|---|---|
| Mobile Application | No |
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 9.5.
The most common users of Jupyter Notebook are from Enterprises (1,001+ employees).
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Reviews
(1-23 of 23)Companies can't remove reviews or game the system. Here's why
April 29, 2022
Jupyter feels like you are on moon
Score 7 out of 10
Vetted Review
Verified User
- Easy to use
- Easy to understand
- Faster
- User Interface can be improved
- More features in online Jupyter lab can be added
- Good & free documentation
December 16, 2021
Jupyter Notebook: A boon to present codes
- Coding and error correction line by line
- Simple and Effectiveness
- Easy to use for visualisation and presentation of code
- Could be used at any place any time without hassle
- could have some standard python libraries imported already
- compiled images and results should be alterable in size
- compiler runtime
November 29, 2021
Feedback - Jupyter Notebook
Score 10 out of 10
Vetted Review
Verified User
- Great interface.
- Segments for codes.
- Markdown for code explanation.
- Sometimes I have to restart it when I import any new python library.
- Should be available for more languages.
October 24, 2021
A Notebook for All
- Giving presentation to a client or explaining your code to a colleague
- Developing code snippets for big or small projects
- Easy to share your work with others
- Highly recommended data analysis presentation
- 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.
October 08, 2021
Jupyter "THE ATTRACTIVE" Notebook
Score 10 out of 10
Vetted Review
Verified User
- We can use it as a notebook and share the slide and also publish it online through GitHub.
- Attractive programming environment.
- Easy navigation platform.
- Should work on Configuration setup, it takes a lot of time.
- Work on code styling correction, sometimes it makes a major difference.
- There is no IDE integration.
- Should include more programming language.
September 27, 2021
Jupyter Pros and Cons
- Sharing/showcasing work in a step by step manner
- Exploratory data analysis/viewing code in-line
- Data exploration/visualization
- Switch between different coding languages
- No IDE integration/linting
- No testing integrations
- Difficult to view changes in GitHub
- Notebook harder to productionize than scripts
- Visually intuitive organization of code.
- Static (but changeable) display of function outputs.
- Easy replication of notebooks or into new notebooks, or into PDFs.
- 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.
- User-friendly UI.
- Easy to debug at each code line.
- Great support for Python Math libraries.
- Advanced data visualization capabilities.
- Notebook sharing feature.
- Intellisense not up to the mark.
- Limited collaboration scope.
- No IDE integration supported.
- Can become sluggish at times when datasets are huge.
June 01, 2021
Python programming made easy with Jupyter!
- 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.
- 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
- Interactive
- Efficient
- Quick
- More languages support
- Enhanced GPU support
- Multi-environment support
May 24, 2021
Review of the Jupyter Notebook
- Easy to use and handle as it takes less hardware requirements.
- Helps [in] creating the data visualization.
- Provide support for difficult language.
- Needs more code styling.
- The markdown is limited.
- For the new user, there [should be] some intro videos or tutorial for that.
May 13, 2021
Jupyter makes life easier.
- Its one by one cell execution.
- It is user friendly and easy to work on.
- Only installing Anaconda can bring us to use this Jupyter Notebook easily.
- Freely available.
- Sometimes we face issues in executing the code because Jupyter Notebook hangs.
- Auto save option is not there which sometimes creates issues in saving your work.
- Markdown for comments/explanations.
- Interactive programming.
- Easy to use and share notebooks.
- Doesn't have some features that competitors have.
- Difficult to do direct collaboration on the same notebook.
- Doesn't provide great code style support/corrections.
May 02, 2021
Jupyter Notebook for quick in-depth analysis
- Easy to learn and use
- Data [modeling]
- Data analysis and reporting
- Predefined visualizations models
- Not much troubleshooting support available
- No support for IDE
- Deployment is complex for cloud environments
May 02, 2021
Great product for data modeling
- Great visualizations
- Easy to edit and track data flows
- Colaborative working
- Literate programming
- Interactive programming
- Server side deployment supporting many users to code via web browser.
- Lacks some features like autoindent code.
- Too many different instructions for deployment.
- Could have better environment isolation.
May 01, 2021
Best to get started for data scientists
- Data Analytics
- easy visualization
- ML possibilities
- slows down device sometimes
- can't identify syntax errors
- no collaboration
May 01, 2021
All in one workspace for Data Sciences
- Easy and interactive Python environment.
- Latex markdown for explanations.
- Terminal access through cell itself.
- Fast Intellisense.
- Documentation access through cell commands.
- Intuitive Key Bindings.
- Creating and installing a virtual environment can be tricky.
- Conda environment can be granular to work with.
April 30, 2021
Jupyter Notebook for the win!
- Data plotting
- Easy to switch settings and see the changes right away in the plots.
- Easy user interface, and commands.
- None that I can think of.
- Data Analysis
- Visualizations
- Documentation
- Limited Markdown Styling
- Complex to handle multiple kernels
- Difficult python code styling
February 24, 2021
Jupyter Notebook, the perfect place to start
- Python
- Markdown presentation
- Easy to learn
- Good organization
- Can be more visually appealing to users
- Easier ways to link projects to websites like Wix
- Ability to work collaboratively on the platform
January 26, 2021
Light user of Jupyter Notebook
- Big data analysis on cloud desktop.
- Exploratory analysis.
- Common machine learning models.
- Nicer output format for explanatory analysis.
- Easy update on packages.
- Better compatibility with AWS tools.
October 22, 2020
Jupyter or nothing
- 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