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NumPy VS Plates by Splitwise

Compare NumPy VS Plates by Splitwise and see what are their differences

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Contents:
  1. ยป Base Details
  2. ยป Videos
  3. ยป Reviews
  4. ยป Alternatives

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python

Plates by Splitwise logo Plates by Splitwise

Plates by Splitwise is one of the simple and powerful bill management platforms that lets you equally distribute all the expenditure results as group gathering, reunion, traveling, and many others.
  • NumPy Landing page
    Landing page //
    2023-05-13
  • Plates by Splitwise Landing page
    Landing page //
    2021-07-12

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.

Plates by Splitwise features and specs

No features have been listed yet.

Analysis of NumPy

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.

NumPy videos

+ Add

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

Plates by Splitwise videos

+ Add

Plates by Splitwise: Bill Splitter for iOS

Category Popularity

0-100% (relative to NumPy and Plates by Splitwise)

NumPy

Plates by Splitwise

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
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Finance
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Finance
100% 100
Data Science Tools
100 100%
Data Science Tools
0% 0
Online Payments
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Online Payments
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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 Plates by Splitwise

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

Plates by Splitwise Reviews

12 Best Bill Splitting Apps in 2023
If you wish to save time and smoothen out the process of splitting bills among a large group of people, Plates by Splitwise is the best-suited one for you. You can also stack plates if someone decides to pay together with their partners. With an accurate calculation of tax, tips, and individual shares, Plates by Splitwise is definitely worth giving a try.
Source: www.mobileappdaily.com
Best Bill-Splitting Apps
There are two types of group dinersโ€”those who donโ€™t mind splitting the bill evenly and those who want to precisely split the bill based on what they owe exactly. Plates by Splitwise lets you handle both. The iPhone-only app gives everyone in the group a โ€œplate.โ€ Then as you add items to the group, they can be placed on a specific personโ€™s plate or split up among the entire...
Source: www.thebalancemoney.com

Social recommendations and mentions

Based on our record, NumPy seems to be a lot more popular than Plates by Splitwise. While we know about 122 links to NumPy, we've tracked only 1 mention of Plates by Splitwise. 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 (122)

View more

Plates by Splitwise mentions (1)

  • Expense Sharing App for Roommates
    I use the Plates App by Splitwise for long dinner bills where we split the bill by items ordered/shared. This could easily work for bulk grocery trips where items need to be charged to one or two people. Source: over 3 years ago

What are some alternatives?

When comparing NumPy and Plates by Splitwise, 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.

Splitwise - Splitwise is a free tool for friends and roommates to track bills and other shared expenses, so that everyone gets paid back. On the web, iPhone, and Android!

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

Splid - Splid helps friends manage their money.

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

Settle Up - SETTLE UP is an indispensable app for friends and flatmates who need to keep track of shared bills...

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