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Code NASA VS NumPy

Compare Code NASA VS NumPy and see what are their differences

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Code NASA logo Code NASA

253 NASA open source software projects

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python
  • Code NASA Landing page
    Landing page //
    2023-10-15
  • NumPy Landing page
    Landing page //
    2023-05-13

Code NASA features and specs

  • Open Access
    The platform provides open access to a wealth of software projects developed by NASA, making it easier for researchers, developers, and the public to utilize and contribute to advancements in technology and science.
  • Educational Value
    Offers educational opportunities by allowing students and educators to explore and use high-quality software from a leading scientific organization, fostering learning and innovation.
  • Collaborative Potential
    Encourages collaboration between NASA, educational institutions, private companies, and individual developers, which can lead to the enhancement and creation of new technologies.
  • Cost Savings
    Utilization of these open-source projects can lead to significant cost savings for organizations and developers by reducing the need to develop similar software from scratch.

Possible disadvantages of Code NASA

  • Limited Commercial Support
    The platform may not provide the level of commercial support that businesses might require, possibly complicating the integration of NASA's code into commercial products.
  • Complex Licensing
    Some projects may have complex licensing agreements that require careful review to ensure compliance, especially for commercial use.
  • Outdated or Discontinued Projects
    Some projects may be outdated or no longer actively maintained, which could pose challenges in terms of usability and security.
  • Technical Barrier
    There may be a high technical barrier to entry for some users, as the software is often highly specialized and may require expertise in particular domains to effectively implement.

NumPy features and specs

  • Performance
    NumPy operations are executed with highly optimized C and Fortran libraries, making them significantly faster than standard Python arithmetic operations, especially for large datasets.
  • Versatility
    NumPy supports a vast range of mathematical, logical, shape manipulation, sorting, selecting, I/O, and basic linear algebra operations, making it a versatile tool for scientific and numeric computing.
  • Ease of Use
    NumPy provides an intuitive, easy-to-understand syntax that extends Python's ability to handle arrays and matrices, lowering the barrier to performing complex scientific computations.
  • Community Support
    With a large and active community, NumPy offers extensive documentation, tutorials, and support for troubleshooting issues, as well as continuous updates and enhancements.
  • Integrations
    NumPy integrates seamlessly with other libraries in Python's scientific stack like SciPy, Matplotlib, and Pandas, facilitating a streamlined workflow for data science and analysis tasks.

Possible disadvantages of NumPy

  • Memory Consumption
    NumPy arrays can consume large amounts of memory, especially when working with very large datasets, which can become a limitation on systems with limited memory capacity.
  • Learning Curve
    For users new to scientific computing or coming from different programming backgrounds, understanding the intricacies of NumPy's operations and efficient usage can take time and effort.
  • Limited GPU Support
    NumPy primarily runs on the CPU and doesn't natively support GPU acceleration, which can be a disadvantage for extremely compute-intensive tasks that could benefit from parallel processing.
  • Dependency on Python
    Since NumPy is a Python library, it depends on the Python runtime environment. This can be a limitation in environments where Python is not the primary language or isn't supported.
  • Indexing Complexity
    Although NumPy's slicing and indexing capabilities are powerful, they can sometimes be complex or unintuitive, especially for multi-dimensional arrays, leading to potential errors and confusion.

Code NASA videos

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NumPy videos

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Learn NUMPY in 5 minutes - BEST Python Library!

More videos:

  • Review - Python for Data Analysis by Wes McKinney: Review | Learn python, numpy, pandas and jupyter notebooks
  • Review - Effective Computation in Physics: Review | Learn python, numpy, regular expressions, install python

Category Popularity

0-100% (relative to Code NASA and NumPy)

Code NASA

NumPy

Open Source
100 100%
Open Source
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Productivity
100 100%
Productivity
0% 0
Data Science Tools
0 0%
Data Science Tools
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Code NASA and NumPy

Code NASA Reviews

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NumPy Reviews

25 Python Frameworks to Master
SciPy provides a collection of algorithms and functions built on top of the NumPy. It helps to perform common scientific and engineering tasks such as optimization, signal processing, integration, linear algebra, and more.
Source: kinsta.com
Top 8 Image-Processing Python Libraries Used in Machine Learning
Scipy is used for mathematical and scientific computations but can also perform multi-dimensional image processing using the submodule scipy.ndimage. It provides functions to operate on n-dimensional Numpy arrays and at the end of the day images are just that.
Source: neptune.ai
Top Python Libraries For Image Processing In 2021
Numpy It is an open-source python library that is used for numerical analysis. It contains a matrix and multi-dimensional arrays as data structures. But NumPy can also use for image processing tasks such as image cropping, manipulating pixels, and masking of pixel values.
Source: www.analyticsvidhya.com
4 open source alternatives to MATLAB
NumPy is the main package for scientific computing with Python (as its name suggests). It can process N-dimensional arrays, complex matrix transforms, linear algebra, Fourier transforms, and can act as a gateway for C and C++ integration. It's been used in the world of game and film visual effect development, and is the fundamental data-array structure for the SciPy Stack,...
Source: opensource.com

Social recommendations and mentions

Based on our record, NumPy seems to be a lot more popular than Code NASA. While we know about 119 links to NumPy, we've tracked only 7 mentions of Code NASA. 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.

Code NASA mentions (7)

  • NASA Stennis Releases First Open-Source Software
    Just to be clear this is one center’s first open source release. There’s open source from other centers at https://github.com/nasa. - Source: Hacker News / 10 days ago
  • FBI, Partners Dismantle Qakbot Infrastructure in Multinational Cyber Takedown
    NASA has a good set of open source projects available for public use: https://code.nasa.gov/. - Source: Hacker News / over 1 year ago
  • NASA's Software Catalog offers hundreds of new software programs for free
    Yes, this is no-cost but not necessarily open source. NASA open source software can be found at: https://code.nasa.gov/. - Source: Hacker News / almost 2 years ago
  • Public satellite telemetry data?
    As for public telemetry it might be hard to get it for free as satellite owners do it for money. NASA maintains a public software page at code.nasa.gov and software.nasa.gov which includes OpenMCT mission control software that can do simulated data. Source: over 3 years ago
  • Internship/research as a physics major
    Don't underestimate the strength of personal projects. If you ask a professor about their research, I find very often, they ask about things you have done in the past, which sort of feels like shit if youve done nothing huh? I know people who made cloud chambers or shot ions or massive simulations in HS and I was like, a theatre kid which is so irrelevant. BUT. The reason they ask this is that previous experience... Source: about 4 years ago
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NumPy mentions (119)

  • Building an AI-powered Financial Data Analyzer with NodeJS, Python, SvelteKit, and TailwindCSS - Part 0
    The AI Service will be built using aiohttp (asynchronous Python web server) and integrates PyTorch, Hugging Face Transformers, numpy, pandas, and scikit-learn for financial data analysis. - Source: dev.to / 4 months ago
  • F1 FollowLine + HSV filter + PID Controller
    This library provides functions for working in domain of linear algebra, fourier transform, matrices and arrays. - Source: dev.to / 8 months ago
  • Intro to Ray on GKE
    The Python Library components of Ray could be considered analogous to solutions like numpy, scipy, and pandas (which is most analogous to the Ray Data library specifically). As a framework and distributed computing solution, Ray could be used in place of a tool like Apache Spark or Python Dask. It’s also worthwhile to note that Ray Clusters can be used as a distributed computing solution within Kubernetes, as... - Source: dev.to / 8 months ago
  • Streamlit 101: The fundamentals of a Python data app
    It's compatible with a wide range of data libraries, including Pandas, NumPy, and Altair. Streamlit integrates with all the latest tools in generative AI, such as any LLM, vector database, or various AI frameworks like LangChain, LlamaIndex, or Weights & Biases. Streamlit’s chat elements make it especially easy to interact with AI so you can build chatbots that “talk to your data.”. - Source: dev.to / 9 months ago
  • A simple way to extract all detected objects from image and save them as separate images using YOLOv8.2 and OpenCV
    The OpenCV image is a regular NumPy array. You can see it shape:. - Source: dev.to / 9 months ago
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What are some alternatives?

When comparing Code NASA and NumPy, you can also consider the following products

Google Open Source - All of Googles open source projects under a single umbrella

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

Open NASA - NASA data, tools, and resources

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

NASA Exoplanet Posters - Imagine visiting worlds outside our solar system

OpenCV - OpenCV is the world's biggest computer vision library

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