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Jupyter VS PTC Mathcad

Compare Jupyter VS PTC Mathcad and see what are their differences

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Jupyter logo Jupyter

Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.

PTC Mathcad logo PTC Mathcad

PTC Mathcad PTC Mathcad is Engineering Math Software That Allows You to Perform, Analyze, and Share Your Most Vital Calculations.
  • Jupyter Landing page
    Landing page //
    2023-06-22
  • PTC Mathcad Landing page
    Landing page //
    2023-07-14

Jupyter features and specs

  • Interactive Computing
    Jupyter allows real-time interaction with the data and code, providing immediate feedback and making it easier to experiment and iterate.
  • Rich Media Output
    It supports output in various formats including HTML, images, videos, LaTeX, and more, enhancing the ability to visualize and interpret results.
  • Language Agnostic
    Jupyter supports multiple programming languages through its kernel system (e.g., Python, R, Julia), allowing flexibility in the choice of tools.
  • Collaborative Features
    It enables collaboration through shared notebooks, version control, and platform integrations like GitHub.
  • Educational Tool
    Jupyter is widely used for teaching, thanks to its easy-to-use interface and ability to combine narrative text with code, making it ideal for assignments and tutorials.
  • Extensibility
    Jupyter is highly extensible with a large ecosystem of plugins and extensions available for various functionalities.

Possible disadvantages of Jupyter

  • Performance Issues
    For larger datasets and more complex computations, Jupyter can be slower compared to running scripts directly in a dedicated IDE.
  • Version Control Challenges
    Managing version control for Jupyter notebooks can be cumbersome, as they are not plain text files and include metadata that can make diffing and merging complex.
  • Resource Intensive
    Running Jupyter notebooks can be resource-intensive, especially when working with multiple large notebooks simultaneously.
  • Security Concerns
    Because Jupyter allows code execution in the browser, it can be a potential security risk if notebooks from untrusted sources are run without restrictions.
  • Dependency Management
    Managing dependencies and ensuring that the notebook runs consistently across different environments can be challenging.
  • Less Suitable for Production
    Jupyter is often considered more as a research and educational tool rather than a production environment; transitioning from a notebook to production code can require significant refactoring.

PTC Mathcad features and specs

  • User-Friendly Interface
    PTC Mathcad offers a highly intuitive and visual workspace that allows users to document and solve problems with ease. This usability reduces the learning curve for new users.
  • Engineering Notation
    Mathcad supports natural math notation, making it easier for engineers to input and understand complex mathematical expressions as they would be written on paper.
  • Live Mathematical Calculations
    Mathcad performs real-time calculations, allowing users to instantly see the results of their inputs and changes, which aids in iterative design processes.
  • Integration Capabilities
    The software easily integrates with other PTC solutions like Creo and Windchill, enhancing its value in a comprehensive product development environment.
  • Collaboration Features
    Mathcad provides tools for sharing and collaboration, which are crucial for team-based engineering projects. Users can annotate, comment, and share their worksheets seamlessly.

Possible disadvantages of PTC Mathcad

  • Cost
    PTC Mathcad can be expensive, especially for small businesses or individual users. The cost may include license fees, maintenance fees, and potential training costs.
  • Software Performance
    Some users have reported performance issues with large or complex worksheets, which can slow down productivity and impact user experience.
  • Learning Curve for Advanced Features
    While the basic features are user-friendly, mastering advanced features and functionalities may require significant effort and time investment.
  • Limited Scripting Capabilities
    Mathcad's scripting and automation capabilities are limited compared to other tools such as MATLAB, restricting the flexibility for users who need advanced computational capabilities.
  • Resource Intensive
    Mathcad can be resource intensive, requiring considerable computing power and memory, which may necessitate hardware upgrades or limit its use on lower-end machines.

Analysis of PTC Mathcad

Overall verdict

  • Yes, PTC Mathcad is considered to be a strong tool for engineering calculations, particularly appreciated for its documentation capabilities and ease of use in handling mathematical expressions. It provides a good balance of power and simplicity, making it a popular choice in engineering fields.

Why this product is good

  • PTC Mathcad is known for its ability to perform complex engineering calculations while displaying them in a user-friendly, readable format. It is especially useful for engineers and professionals who require a straightforward way to document calculations alongside units and graphs. It integrates well with other engineering tools and offers extensive capabilities for solving, analyzing, and sharing engineering calculations.

Recommended for

  • Engineers who need to perform and document complex calculations
  • Students studying engineering or related fields
  • Professionals who require clear visualization of mathematical data
  • Administrators or managers who need to ensure accurate and consistent calculations in reports

Jupyter videos

+ Add

What is Jupyter Notebook?

More videos:

  • Tutorial - Jupyter Notebook Tutorial: Introduction, Setup, and Walkthrough
  • Review - JupyterLab: The Next Generation Jupyter Web Interface

PTC Mathcad videos

+ Add

PTC Mathcad Prime 6.0 - Overview

More videos:

  • Review - PTC Mathcad Prime 6.0 is Here!
  • Review - Engineering Calculations with PTC Mathcad Prime 5.0

Category Popularity

0-100% (relative to Jupyter and PTC Mathcad)

Jupyter

PTC Mathcad

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Technical Computing
0 0%
Technical Computing
100% 100
Data Dashboard
100 100%
Data Dashboard
0% 0
Numerical Computation
0 0%
Numerical Computation
100% 100

User comments

Share your experience with using Jupyter and PTC Mathcad. For example, how are they different and which one is better?
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Reviews

These are some of the external sources and on-site user reviews we've used to compare Jupyter and PTC Mathcad

Jupyter Reviews

Jupyter Notebook & 10 Alternatives: Data Notebook Review [2023]
Once you install nteract, you can open your notebook without having to launch the Jupyter Notebook or visit the Jupyter Lab. The nteract environment is similar to Jupyter Notebook but with more control and the possibility of extension via libraries like Papermill (notebook parameterization), Scrapbook (saving your notebook’s data and photos), and Bookstore (versioning).
Source: lakefs.io
7 best Colab alternatives in 2023
JupyterLab is the next-generation user interface for Project Jupyter. Like Colab, it's an interactive development environment for working with notebooks, code, and data. However, JupyterLab offers more flexibility as it can be self-hosted, enabling users to use their own hardware resources. It also supports extensions for integrating other services, making it a highly...
Source: deepnote.com
12 Best Jupyter Notebook Alternatives [2023] – Features, pros & cons, pricing
Jupyter Notebook is a widely popular tool for data scientists to work on data science projects. This article reviews the top 12 alternatives to Jupyter Notebook that offer additional features and capabilities.
Source: noteable.io
15 data science tools to consider using in 2021
Jupyter Notebook's roots are in the programming language Python -- it originally was part of the IPython interactive toolkit open source project before being split off in 2014. The loose combination of Julia, Python and R gave Jupyter its name; along with supporting those three languages, Jupyter has modular kernels for dozens of others.
Source: searchbusinessanalytics.techtarget.com
Top 4 Python and Data Science IDEs for 2021 and Beyond
Yep — it’s the most popular IDE among data scientists. Jupyter Notebooks made interactivity a thing, and Jupyter Lab took the user experience to the next level. It’s a minimalistic IDE that does the essentials out of the box and provides options and hacks for more advanced use.
Source: towardsdatascience.com

PTC Mathcad Reviews

We have no reviews of PTC Mathcad yet.
Be the first one to post

Social recommendations and mentions

Based on our record, Jupyter seems to be more popular. It has been mentiond 216 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Jupyter mentions (216)

  • The 3 Best Python Frameworks To Build UIs for AI Apps
    Showcase and share: Easily embed UIs in Jupyter Notebook, Google Colab or share them on Hugging Face using a public link. - Source: dev.to / 3 months ago
  • LangChain: From Chains to Threads
    LangChain wasn’t designed in isolation — it was built in the data pipeline world, where every data engineer’s tool of choice was Jupyter Notebooks. Jupyter was an innovative tool, making pipeline programming easy to experiment with, iterate on, and debug. It was a perfect fit for machine learning workflows, where you preprocess data, train models, analyze outputs, and fine-tune parameters — all in a structured,... - Source: dev.to / 4 months ago
  • Applied Artificial Intelligence & its role in an AGI World
    Leverage versatile resources to prototype and refine your ideas, such as Jupyter Notebooks for rapid iterations, Google Colabs for cloud-based experimentation, OpenAI’s API Playground for testing and fine-tuning prompts, and Anthropic's Prompt Engineering Library for inspiration and guidance on advanced prompting techniques. For frontend experimentation, tools like v0 are invaluable, providing a seamless way to... - Source: dev.to / 5 months ago
  • Jupyter Notebook for Java
    Lately I've been working on Langgraph4J which is a Java implementation of the more famous Langgraph.js which is a Javascript library used to create agent and multi-agent workflows by Langchain. Interesting note is that [Langchain.js] uses Javascript Jupyter notebooks powered by a DENO Jupiter Kernel to implement and document How-Tos. So, I faced a dilemma on how to use (or possibly simulate) the same approach in... - Source: dev.to / 9 months ago
  • JIRA Analytics with Pandas
    One of the most convenient ways to play with datasets is to utilize Jupyter. If you are not familiar with this tool, do not worry. I will show how to use it to solve our problem. For local experiments, I like to use DataSpell by JetBrains, but there are services available online and for free. One of the most well-known services among data scientists is Kaggle. However, their notebooks don't allow you to make... - Source: dev.to / 12 months ago
View more

PTC Mathcad mentions (0)

We have not tracked any mentions of PTC Mathcad yet. Tracking of PTC Mathcad recommendations started around Mar 2021.

What are some alternatives?

When comparing Jupyter and PTC Mathcad, you can also consider the following products

Looker - Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.

SMath Studio - Tiny, powerful, free mathematical program with WYSIWYG editor and complete units of measurements support.

Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.‎What is Apache Spark?

Wolfram Mathematica - Mathematica has characterized the cutting edge in specialized processing—and gave the chief calculation environment to a large number of pioneers, instructors, understudies, and others around the globe.

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

MATLAB - A high-level language and interactive environment for numerical computation, visualization, and programming

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