Software Alternatives, Accelerators & Startups
Register | Login

Android VS NumPy

Compare Android VS NumPy and see what are their differences

LibHunt
LibHunt tracks mentions of software libraries on relevant social networks. Based on that data, you can find the most popular projects and their alternatives. featured
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.
Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

Android logo Android

Android is an open source mobile operating system initially released by Google in 2008 and has since become of the most widely used operating systems on any platform.

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python
  • Android Landing page
    Landing page //
    2023-10-14
  • NumPy Landing page
    Landing page //
    2023-05-13

Android features and specs

  • Customization
    Android offers extensive customization options, allowing users to personalize their device appearance and functionality.
  • Diverse Hardware Options
    Android is available on a wide range of devices from various manufacturers, giving users numerous choices in terms of size, design, and price.
  • Google Services Integration
    Android provides seamless integration with Google services like Google Search, Maps, Gmail, and Google Assistant.
  • Open Source
    Android is based on an open-source platform, encouraging innovation and allowing developers to modify and improve the system.
  • App Variety
    The Google Play Store offers a vast selection of apps and games, often with a greater variety than other platforms.
  • Multi-Tasking
    Android supports robust multi-tasking capabilities, letting users switch between apps and use them simultaneously with features like split-screen.

Possible disadvantages of Android

  • Fragmentation
    Due to the diversity of devices and manufacturer customizations, Android fragmentation can lead to inconsistent performance and delayed software updates.
  • Security Risks
    The open-source nature of Android can make it more vulnerable to malware and security breaches if users download applications from untrusted sources.
  • Bloatware
    Many Android devices come with pre-installed applications (bloatware) that can be difficult to remove and consume storage and resources.
  • Inconsistent User Experience
    The user experience may vary significantly across different devices and manufacturers, leading to inconsistency in performance and features.
  • Ads and In-App Purchases
    Many free Android apps rely heavily on advertisements and in-app purchases, which can sometimes diminish the user experience.
  • Battery Life
    Some Android devices may suffer from poor battery optimization, leading to shorter battery life compared to other platforms.

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.

Analysis of Android

Overall verdict

  • Yes, Android is considered to be a good operating system due to its versatility and user-friendly design. It's regularly updated with new features and security improvements.

Why this product is good

  • Android is a highly popular mobile operating system developed by Google. It offers open-source flexibility, a wide range of device compatibility, and a large app ecosystem through the Google Play Store. Users appreciate its customization options and integration with Google services.

Recommended for

  • Users who enjoy customizing their devices
  • Individuals who prefer a wide choice of hardware options
  • People who are heavily invested in the Google services ecosystem
  • Developers who want an open-source platform
  • Users looking for a variety of apps and games

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.

Android videos

+ Add

Android 10 Review: This is Android in 2020! [Android Q]

More videos:

  • Review - Google Pixel 4 and 4 XL review: the best Android experience
  • Review - iPhone User Spends 17 Days on Android | Galaxy S10 Plus Review

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

Category Popularity

0-100% (relative to Android and NumPy)

Android

NumPy

Mobile OS
100 100%
Mobile OS
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Mobile SDK
100 100%
Mobile SDK
0% 0
Data Science Tools
0 0%
Data Science Tools
100% 100

User comments

Share your experience with using Android and NumPy. For example, how are they different and which one is better?
Log in or Post with

Reviews

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

Android Reviews

Top 5 Mobile Operating Systems 2023 (Alternatives to Android)
Planned essentially for touch-screen phones and tablets, Android is first created by Android Inc. that Google purchased later in the year 2005. Android Operating System was revealed in the year 2007, and then the first Android device was launched in September 2008.
Source: www.pcmobitech.com
Best Open Source Android Alternative OS for Smartphones
As most of the trade and technology-loving persons already heard about the US-China Trade War and Huawei-Google fight. Now, so many Huawei device users and Android enthusiasts are wondering what will be the next Android alternative OS (Operating System) for smartphones. Without Google and its services, the Android platform is difficult to run properly on a smartphone. But we...
Source: www.getdroidtips.com
Android Alternative: Top 12 Mobile Operating Systems
Android has become the de-facto operating system for smartphones, IoT devices, cars, TVs, and other electronic devices. The open-source project is being deployed almost everywhere because of the vast app support, lightweight profile, compatibility with a variety of hardware, huge developer support, etc. Apple’s iOS is putting up a good fight, but it’s nowhere close to...
Source: beebom.com
12 Best Android Custom ROMs For 2020 That You Must Try
Well, say hello to one of the top tier customization Kings of the Android Custom ROM World. Resurrection Remix has been around for almost the same time as any of the ROMs we’ve mentioned below. Starting its development in the early days of Android 4.0, RR has never failed to impress me with its feature-packed settings menu to tailor the Android smartphone to your heart’s...
Source: fossbytes.com
Open Source Mobile OS Alternatives To Android
It’s no exaggeration to say that open source operating systems rule the world of mobile devices. Android is still an open source project, after all. But, due to the bundle of proprietary software that comes along with Android on consumer devices, many people don’t consider it an open source operating system.
Source: itsfoss.com

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 Android. While we know about 119 links to NumPy, we've tracked only 11 mentions of Android. 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.

Android mentions (11)

  • What is the best wearos watch according to google? :)
    Of course it's the Watch 5 Pro. Go to android.com it's even used in a promote video lol. Pixel Watch is just a joke. Source: about 2 years ago
  • Surface Duo 2 November Update Build 2022.817.23
    I've been running with it for a short-while now. Need to go to android.com and see what fixes they made. Source: over 2 years ago
  • Jetpack Compose: Horrifically slow in text input?
    As a follow-up, if jetpack can be used to build real and performant apps, does anyone have a good recommendation for a tutorial? I was trying to follow the demos linked of android.com, but it seemed as if there were vast differences between what they were saying to do, and what was in a newly bootstrapped project and the gradle files. Source: over 2 years ago
  • Anyone else having Malwarebytes say Google.com is malware?
    This seems to be effecting all of Google's products. I can't get into any of my G-Suite sites, GMail accounts, google.com, android.com, etc. From any device that has Malwarebytes installed. The constant popups from Malwarebytes are annoying, but on a positive note, it is letting me see just how many apps on my computer phone in to Google. NZXT is the biggest offender, and seems to be constantly hitting up... Source: over 2 years ago
  • Why do none of the major distros have KDE Plasma as default?
    I wish I could go to android.com download the latest ROM and install it myself, like I do with Linux, I hate waiting for phone manufacturers to release OS updates and security fixes. Source: almost 3 years ago
View more

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 / 9 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 / 10 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 / 10 months ago
View more

What are some alternatives?

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

LineageOS - Operating system for smartphones and tablet computers, based on the Android

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

GrapheneOS - GrapheneOS is an open source privacy and security focused mobile OS with Android app compatibility.

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

Ubuntu Touch - Read more about Ubuntu Touch. Our free and open source mobile OS is made and maintained by UBports! We care about your freedom and privacy.

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

Loading...