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NumPy VS Gnumeric

Compare NumPy VS Gnumeric and see what are their differences

NumPy

NumPy is the fundamental package for scientific computing with Python

Rating
0 reviews
Pricing
Open source
Alternatives Is it good?
Gnumeric

Gnumeric

Rating
0 reviews
Alternatives Is it good?
Kanera
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Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

Which is more popular?

Based on our record, NumPy seems to be a lot more popular than Gnumeric. While we know about 122 links to NumPy, we've tracked only 2 mentions of Gnumeric.

social mentions
122 vs 2
Data Science And Machine Learning popularity
100% vs 0%
alternatives listed
189 vs 62

Base details

Website, pricing, platforms and company facts side by side.

NumPy
Gnumeric
Website numpy.org gnumeric.org
Pricing
Open source
—
Listed in
Data Science And Machine Learning Data Science Tools Python Tools Software Libraries +1
Office Suites Spreadsheets Project Management Databases +1

Features and specs

What each product offers, as listed by its team.

NumPy 5 features
Gnumeric 4 features
  • 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

  • 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.
  • Lightweight
    Gnumeric is known for being lightweight and faster to load compared to other spreadsheet software like Microsoft Excel or LibreOffice Calc, making it ideal for users with older hardware or for those who need quick access to spreadsheets.
  • Accuracy
    Gnumeric is renowned for its calculation accuracy, often outperforming other spreadsheet programs in complex mathematical computations, which is beneficial for users who require precise numerical results.
  • Open Source
    Being an open-source application, Gnumeric allows users to modify and distribute the software according to the GPL license, fostering a community of contributors and enabling transparency and customizability.
  • Compatibility
    Gnumeric supports a wide range of file formats, including Excel (.xls and .xlsx), allowing users to open and save documents in these formats which ensures interoperability with other spreadsheet tools.

Possible disadvantages

  • Limited Features
    While Gnumeric covers most basic and advanced spreadsheet functionalities, it lacks some of the more sophisticated features found in Excel or Google Sheets, such as advanced data visualization tools and certain analytic functions.
  • User Interface
    The user interface of Gnumeric may seem outdated or less intuitive compared to modern spreadsheet applications, which might not appeal to users accustomed to more polished UIs.
  • Ecosystem Integration
    Gnumeric does not integrate as seamlessly into productivity ecosystems compared to solutions like Microsoft Excel, which benefits from integration with other Microsoft Office applications.
  • Community Support
    Although Gnumeric is open-source, the community is smaller compared to bigger suites like LibreOffice or Microsoft Office, which might limit the availability of tutorials, forums, and third-party support resources.

Analysis

An editorial look at what each product does well and who it suits.

NumPy
Gnumeric

Overall verdict

  • Yes, NumPy is considered good. It is a foundational library in the Python ecosystem for numerical computing and is used globally by researchers, engineers, and data scientists.

Why this product is good

  • NumPy is widely regarded as a good library because it offers fast, flexible, and efficient array handling that is integral to scientific computing in Python. It provides tools for integrating C/C++ and Fortran code, useful linear algebra, random number capabilities, and a vast collection of mathematical functions. Its array broadcasting capabilities and versatility make complex mathematical computations straightforward.

Recommended for

  • Scientists and researchers working with large-scale scientific computations.
  • Data scientists engaged in data analysis and manipulation.
  • Engineers and developers needing performance-optimized mathematical computations.
  • Educators and students in STEM fields.

Overall verdict

  • Gnumeric is a good choice for users who need a reliable, fast, and accurate spreadsheet tool, particularly for complex calculations and data analysis. It may lack some advanced features found in mainstream commercial products, but it makes up for this with its precision and performance.

Why this product is good

  • Gnumeric is a free and open-source spreadsheet application that is part of the GNOME Free Software Desktop Project. It is highly regarded for its accuracy, especially in statistical operations, and it offers a wide range of features comparable to other spreadsheet software like Microsoft Excel. Gnumeric is lightweight, which makes it fast and efficient, and it supports various file formats, including Excel, making it easy to share and collaborate with users of other spreadsheet programs.

Recommended for

    Gnumeric is recommended for data analysts, researchers, and students who require a robust spreadsheet application for statistical analysis and computational tasks. It is also suitable for Linux users seeking a native spreadsheet solution, as well as users who prefer open-source software solutions.

Videos

Walkthroughs and reviews on video.

NumPy 3 videos + Add
Gnumeric 3 videos + Add

Learn NUMPY in 5 minutes - BEST Python Library!

More videos

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

Gnumeric.....Abiword's twin sister.....

More videos

  • - Gnumeric Portable
  • - Gnumeric online XLS editor

Category popularity

How often each product is chosen within a category, 0–100% relative to the other.

Score bands 0–20 21–40 41–50 51–60 61–100
NumPy
Gnumeric
100% 100%
Data Science And Machine Learning
0% 0%
0% 0%
Office Suites
100% 100%
100% 100%
Data Science Tools
0% 0%
0% 0%
Spreadsheets
100% 100%

User comments

Share your experience with using NumPy and Gnumeric. For example, how are they different and which one is better?

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Reviews and articles

External articles and on-site reviews we used to compare the two products.

NumPy no reviews yet
Gnumeric no reviews yet

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

Social recommendations and mentions

Recommendations tracked on public social media and blogs since March 2021.

NumPy 122 mentions
Gnumeric 2 mentions

View more

  • Ask HN: Why did Visual Basic die?
    Gnumeric is actually a good excel. The stats routines are shared with R so if ever someone demonstrates a bug, it is fixed! Free, fast, accurate. Pick any three! http://gnumeric.org. - Source: Hacker News / about 3 years ago
  • Any Suckless Excel like tool?
    I can recommend http://gnumeric.org/. It is really fast, accurate and relative light weight compared to libreoffice calc. Source: over 3 years ago

Alternatives to NumPy and Gnumeric

When comparing NumPy and Gnumeric, you can also consider the following products.

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