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Uber VS NumPy

Compare Uber 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
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Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

Uber logo Uber

Uber is a website and mobile app that allows you to get a ride similar to a taxi service from your phone.

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python
  • Uber Landing page
    Landing page //
    2023-09-24
  • NumPy Landing page
    Landing page //
    2023-05-13

Uber features and specs

  • Convenience
    Uber provides a highly convenient means of transportation, allowing users to book a ride through their smartphone app at any time and from almost any location.
  • Availability
    Uber operates in many cities around the world, offering a wide reach and making it easier for users to find rides even in less populated areas.
  • Upfront Pricing
    Users can see the estimated cost of their trip before confirming the ride, which adds transparency and helps in budgeting.
  • Safety Features
    Uber includes several safety features, such as driver background checks, GPS tracking of rides, sharing trip details with trusted contacts, and an emergency assistance button.
  • Variety of Services
    Uber offers different types of services (UberX, UberXL, Uber Black, Uber Eats, etc.) catering to diverse needs, from solo travelers to group rides and food delivery.

Possible disadvantages of Uber

  • Surge Pricing
    Uber's pricing can increase significantly during peak times or in high-demand areas, which can result in much higher fares for riders.
  • Driver Earnings
    There have been concerns and reports about Uber drivers not earning a sustainable income due to the company's commission structure and operating costs.
  • Regulatory Issues
    Uber has faced various legal and regulatory challenges in different countries and cities, often leading to temporary shutdowns or operational restrictions.
  • Service Inconsistency
    The quality of service can vary greatly depending on the driver, vehicle condition, and location, leading to an inconsistent user experience.
  • Data Privacy
    There are ongoing concerns about how Uber collects, uses, and protects user data, including location information and personal details.

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 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.

Uber videos

+ Add

Uber Driver Pay | This Is Why You Should Not Be An Uber Driver | Is Uber Worth It

More videos:

  • Review - Real Earnings from ONE WEEK as an Uber Driver in 2020
  • Review - One Year of Driving for Uber/Lyft 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 Uber and NumPy)

Uber

NumPy

Ride Sharing
100 100%
Ride Sharing
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Taxi
100 100%
Taxi
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 Uber and NumPy

Uber Reviews

The Best Travel Apps for 2025
Uber operates around the world, and while the in-app options vary from place to place, the general concept is the same everywhere. There are a few reasons that ride-on-demand apps work so well for travelers. First, it eliminates the need to carry local currency. Second, you don't have to speak the same language as your driver to get to where you need to go. Third, there's no...
Source: www.pcmag.com
Can ride-pooling service Via catch up to Uber and Lyft by being the friendly alternative?
Can ride-pooling service Via catch up to Uber and Lyft by being the friendly alternative?This month Via hit 50 million rides, versus Uber’s 10 billion and Lyft’s 500 million–but with much less of the vitriol, and productive relationships with the cities in which it operates. [Photo: courtesy Via] By Ainsley Harris4 minute...
Source: www.fastcompany.com
Via Rideshare: Get Shared Rides for Less
Much like Uber and Lyft, Via may charge extra fees for drop-offs at special destinations (like Chicago’s Navy Pier), though you’ll always see these fees upfront before you ride. You can see real-time rates in your Via app. A $3 fee may also apply for no-shows and cancellations, which is actually $2 cheaper than Uber cancellation fees.
Source: www.ridester.com
Uber, Lyft, Gett, Juno, and Via: Which of these 5 NYC taxi alternatives is right for you?
​Price: It varies; UberX has $2.55 baseline fare and is 35 cents/minute after that; UberXL has a base of $3.85 and then costs 50 cents a minute; UberBlack has a base of $7 and is 65 cents a minute; and UberSUV has a base of $14 and a per-minute rate of 80 cents. There's also UberTaxi—which simply flags down a regular yellow or green cab for you—and UberPool, which matches...
Source: www.brickunderground.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 should be more popular than Uber. 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.

Uber mentions (25)

  • How can I find out if Uber is available in my area?
    Use the website on uber.com for estimating fares between A and B. Source: almost 2 years ago
  • Creating spreadsheet of customer ride price vs expense paid to others (inc driver)
    Open browser on uber.com summary of trip earnings. Source: almost 2 years ago
  • Uber ignoring me
    Have you tried signing in to your Uber account at uber.com? Maybe you can receive a OTP by email instead of your phone number? Source: about 2 years ago
  • Missing/Late/Wrong Prop 22 Earnings and other Uber F*ckery
    I have never been able to see the breakdown in the app (though others say they have found it). I usually go online to the uber.com website and login. You can see earnings statements there. Go to the Activity tab. Source: about 2 years ago
  • PSA: GRT U-Pass Referendum from Jan. 24-26
    A relatively average Uber trip maybe ≈$10, one way. In fact, uber.com estimates the trip from Pub on King to Marshall street (for example) to be $9.00, one way. Source: over 2 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 / 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

What are some alternatives?

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

Lyft - Lyft is a mobile app that lets you get rides from pace to place for a fee. If you want to be a Lyft driver, you can go to their website and easily sign up to start driving for them. Read more about Lyft.

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

Yandex.Taxi - The Yandex.Taxi app is a quick, easy, and safe way to order a taxi.

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

BlaBlaCar - BlaBlaCar is a ride sharing service that connects travelers throughout Europe.

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

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