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NumPy VS stats.fm

Compare NumPy VS stats.fm and see what are their differences

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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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NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python

stats.fm logo stats.fm

With the click of a button you'll be logged with your Spotify account and you'll instantly gain access to a valhalla of cool stats and insights.
  • NumPy Landing page
    Landing page //
    2023-05-13
  • stats.fm Landing page
    Landing page //
    2022-12-22

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.

stats.fm features and specs

  • Detailed Analytics
    Stats.fm provides in-depth insights into your music listening habits, offering detailed statistics on your favorite tracks, artists, and genres.
  • User-Friendly Interface
    The platform features an intuitive and easy-to-navigate interface, making it accessible for users of all experience levels.
  • Personalization
    It offers personalized music recommendations based on your listening history, helping users discover new music tailored to their preferences.
  • Integration with Streaming Services
    Stats.fm integrates seamlessly with popular music streaming services like Spotify, enhancing the user experience by providing comprehensive analytics.

Possible disadvantages of stats.fm

  • Privacy Concerns
    Users need to allow access to their streaming data, which may raise privacy concerns for some individuals.
  • Limited Free Features
    Many of the platform’s features are locked behind a paywall, requiring a subscription for full access.
  • Platform Dependency
    Stats.fm's effectiveness is dependent on the streaming service's API, and any changes or limitations in data access can impact its functionality.
  • Inconsistent Updates
    Some users have reported delays in the updating of statistics, which can affect the accuracy and timeliness of data insights.

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

stats.fm videos

+ Add

SPOTISTATS / STATS.FM - HOW TO USE?

Category Popularity

0-100% (relative to NumPy and stats.fm)

NumPy

stats.fm

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Music
0 0%
Music
100% 100
Data Science Tools
100 100%
Data Science Tools
0% 0
Spotify
0 0%
Spotify
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 stats.fm

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

stats.fm Reviews

We have no reviews of stats.fm yet.
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Social recommendations and mentions

NumPy might be a bit more popular than stats.fm. We know about 119 links to it since March 2021 and only 104 links to stats.fm. 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 / 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 / 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

stats.fm mentions (104)

  • Show HN: I made a tool to turn your Spotify profile into a website
    If you're interested in something for consumers, I recommend you try https://stats.fm/. - Source: Hacker News / over 1 year ago
  • A song with lyrics he got word that overnight his friend went to sleep and never woke again
    If you cannot find it, you always have the option of paying and importing your stats to stats.fm and it should hopefully be there on the songs you have played! Source: over 1 year ago
  • Notbused this App before
    Stats.fm is just for spotify right? I use last.fm to track music on almost any interface you can think of:. Source: over 1 year ago
  • From what number of minutes do 0.001% and 0.0001 start?
    Not sure if the stats.fm 'leader board' for top listeners are correct since there seems to be some users with inflated minutes. Some random dude has 157,274 minutes on 'Fantastic Magic' alone which is unbelievable. Source: over 1 year ago
  • I need advice, falsely quarantined streams
    I tried contacting support about this but they just hit me with a "we think you deserve it so we're not going to do anything" (not literally, but it has those vibes). I do not farm streams or practice fraudulent behavior in any manner, and y'all are free to check this out yourselves. I use Spotify very frequently, whether it be to drown out noise or to distract me from other things. I also have diagnosed ADHD and... Source: over 1 year ago
View more

What are some alternatives?

When comparing NumPy and stats.fm, 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.

Last.fm - The world's largest online music service. Listen online, find out more about your favourite artists, and get music recommendations, only at Last.fm

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

ListenBrainz - Open source music website that allows users to import their listen history.

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

BandNext - Discover bands that sound similar to artists you already love with BandNext. A single click saves your results to a Youtube playlist.

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