Software Alternatives, Accelerators & Startups

NumPy VS Rows

Compare NumPy VS Rows and see what are their differences

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NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python

Rows logo Rows

The spreadsheet where teams work faster
  • NumPy Landing page
    Landing page //
    2023-05-13
  • Rows Landing page
    Landing page //
    2023-02-23

Slick design. Built-in integrations. Revolutionary sharing. Rows reinvented spreadsheets so teams do more, crazy fast.

Rows

Website
rows.com
$ Details
-
Release Date
2016 January
Startup details
Country
Germany
State
Berlin
City
Berlin
Founder(s)
Humberto Ayres Pereira
Employees
10 - 19

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.

Rows features and specs

  • User-Friendly Interface
    Rows provides an intuitive and easy-to-use spreadsheet interface that is accessible for users of all skill levels, from beginners to advanced.
  • Integration Capabilities
    Supports a variety of integrations with other software services and APIs, allowing for seamless data import and export.
  • Real-Time Collaboration
    Allows multiple users to work on the same spreadsheet simultaneously, enhancing team productivity and ensuring everyone has the latest information.
  • Customization and Automation
    Offers powerful automation features and the ability to write custom scripts, which can save time and reduce manual errors.
  • Template Library
    Provides a rich library of pre-designed templates that can help users quickly get started on common business tasks.

Possible disadvantages of Rows

  • Learning Curve
    While user-friendly, more advanced features and scripting capabilities may require a significant learning curve for new users.
  • Limited Offline Functionality
    Primarily a cloud-based tool, which means it relies heavily on internet connection and offers limited offline functionality.
  • Pricing
    The cost of premium features or larger scale deployments can be high, which may not be affordable for small businesses or individual users.
  • Dependency on Integrations
    Heavily reliant on third-party integrations, which means any issues or changes in connected services can impact Rows' functionality.
  • Security Concerns
    As with any cloud-based service, there may be concerns about data security and privacy, especially for sensitive or confidential information.

NumPy videos

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

Rows videos

Welcome to Rows

More videos:

  • Review - The Truth about Barbell Rows (AVOID MISTAKES!)
  • Review - 9/21/21 bentover rows review

Category Popularity

0-100% (relative to NumPy and Rows)
Data Science And Machine Learning
Spreadsheets
0 0%
100% 100
Data Science Tools
100 100%
0% 0
Productivity
0 0%
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 NumPy and Rows

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.
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

Rows Reviews

The best no-code tools for sales teams
You can bring your data to life. With Rows, you can jazz up your spreadsheets with slick charts, images, audio and even interactive features such as buttons and checkboxes. What’s more, you can share your spreadsheets with colleagues and clients in the form of interactive dashboards and websites.
Source: www.nocode.tech

Social recommendations and mentions

Based on our record, NumPy should be more popular than Rows. It has been mentiond 119 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.

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 / 3 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 / 7 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
View more

Rows mentions (24)

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What are some alternatives?

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

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

Airtable - Airtable works like a spreadsheet but gives you the power of a database to organize anything. Sign up for free.

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

NocoDB - The Open Source Airtable alternative

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

Baserow - Open source no-code database and Airtable alternative. Create your own online database without technical experience. Performant with high volumes of data, can be self hosted and supports plugins