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…
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PyCharm
Score 9.3 out of 10
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PyCharm is an extensive Integrated
Development Environment (IDE) for Python developers. Its
arsenal includes intelligent code completion, error detection, and rapid
problem-solving features, all of which aim to bolster efficiency. The product supports programmers in composing orderly and maintainable
code by offering PEP8 checks, testing assistance, intelligent refactorings, and
inspections. Moreover, it caters to web development frameworks like Django and
Flask by providing framework…
$99
per year per user
Pricing
Jupyter Notebook
PyCharm
Editions & Modules
No answers on this topic
For Individuals
$99
per year per user
All Products Pack for Organizations
$249
per year per user
All Products Pack for Individuals
$289
per year per user
For Organizations
$779
per year per user
Offerings
Pricing Offerings
Jupyter Notebook
PyCharm
Free Trial
No
Yes
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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More Pricing Information
Community Pulse
Jupyter Notebook
PyCharm
Features
Jupyter Notebook
PyCharm
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Jupyter Notebook
9.0
Ratings
7% above category average
PyCharm
-
Ratings
Connect to Multiple Data Sources
10.00 Ratings
00 Ratings
Extend Existing Data Sources
10.00 Ratings
00 Ratings
Automatic Data Format Detection
8.50 Ratings
00 Ratings
MDM Integration
7.40 Ratings
00 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Jupyter Notebook
7.0
Ratings
18% below category average
PyCharm
-
Ratings
Visualization
6.00 Ratings
00 Ratings
Interactive Data Analysis
8.00 Ratings
00 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Jupyter Notebook
9.5
Ratings
15% above category average
PyCharm
-
Ratings
Interactive Data Cleaning and Enrichment
10.00 Ratings
00 Ratings
Data Transformations
10.00 Ratings
00 Ratings
Data Encryption
8.50 Ratings
00 Ratings
Built-in Processors
9.30 Ratings
00 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
Jupyter Notebook
9.3
Ratings
10% above category average
PyCharm
-
Ratings
Multiple Model Development Languages and Tools
10.00 Ratings
00 Ratings
Automated Machine Learning
9.20 Ratings
00 Ratings
Single platform for multiple model development
10.00 Ratings
00 Ratings
Self-Service Model Delivery
8.00 Ratings
00 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
I would rate it 9/10 while recommending Jupyter Notebook as it offers me a wide range of functionality to operate. It is very well suited for someone who is new to python programming as the user interface helps you build code line by line. I personally have written multiple programs in Python using Jupyter Notebook as it helps me organize long code by breaking it in a structure. Also the ability to write comments using '#' helps a lot to a reader understand the code.
It's easy to create virtual environments and install packages for different projects as we may need project-specific packages for doing our experiments, also it's easy to see what changes we have made and create pull requests faster. But sometimes we want some light python editor like Jupiter notebook as PyCharm is relatively heavier, also Jupiter notebooks are a good option when we need to run remote code on local machines.
Git integration is really essential as it allows anyone to visually see the local and remote changes, compare revisions without the need for complex commands.
Complex debugging tools are basked into the IDE. Controls like break on exception are sometimes very helpful to identify errors quickly.
Multiple runtimes - Python, Flask, Django, Docker are native the to IDE. This makes development and debugging and even more seamless.
Integrates with Jupyter and Markdown files as well. Side by side rendering and editing makes it simple to develop such files.
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.
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.
It's pretty easy to use, but if it's your first time using it, you need time to adapt. Nevertheless, it has a lot of options, and everything is pretty easy to find. The console has a lot of advantages and lets you accelerate your development from the first day.
I rate 10/10 because I have never needed a direct customer support from the JetBrains so far. Whenever and for whatever kind of problems I came across, I have been able to resolve it within the internet community, simply by Googling because turns out most of the time, it was me who lacked the proper information to use the IDE or simply make the proper configuration. I have never came across a bug in PyCharm either so it deserves 10/10 for overall support
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 of needs I have for EDA, modeling, and data export that makes other software products fairly redundant.
It is more complete and can handle more projects at the same time. On the other hand, Visual Studio Code has better integration with LMS to help you code. PyCharm allows you to integrate with many external tools and external servers that Visual Studio Code has difficulties with.
Improved efficiency with coding assistance (templates, code completion, documentation), which helps us avoid 'reinventing the wheel' with new projects.
Extensive support for other packages/integrations: Docker support to test code, Git repo creation (for version control), and integration with different database systems (Postgres, MySQL).