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NumPy VS Coinpanda

Compare NumPy VS Coinpanda and see what are their differences

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NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python

Coinpanda logo Coinpanda

Calculate & file tax reports for Bitcoin and cryptocurrencies. Made for traders and investors.
  • NumPy Landing page
    Landing page //
    2023-05-13
  • Coinpanda Landing page
    Landing page //
    2023-09-19

Coinpanda is the easiest way to calculate and file your taxes for digital currencies. Directly connect all of your exchanges to Coinpanda with API keys, and synchronize your crypto balances and transactions automatically. Gain insight to your trades, and learn how to optimize your profits.

Our platform is built to make cryptocurrency tax calculations simple, automated and painless. Easily review your tax summary, and download tax reports ready to be filed. We support the US, UK, Canada, Germany, Norway and 20+ other countries.

It's 100% free to create account and use all the features: https://app.coinpanda.io/register

Coinpanda

$ Details
freemium $49.0 / Annually (Hodler (100 transactions))
Platforms
Browser Web Google Chrome Internet Explorer Firefox Safari
Release Date
2019 January

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.

Coinpanda features and specs

  • Easy to Set-up and use
  • Analytics and Reporting
  • Clean UI

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

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

Coinpanda videos

CoinPanda Payment Proof | Fast Payments - Earn IT

Category Popularity

0-100% (relative to NumPy and Coinpanda)
Data Science And Machine Learning
Cryptocurrencies
0 0%
100% 100
Data Science Tools
100 100%
0% 0
Fintech
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 Coinpanda

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

Coinpanda Reviews

  1. Very simple to use

    I am really happy with how easy Coinpanda is. I trade mostly on Coinbase and Binance and I could import all my transactions without issues. Will recommend this product to all crypto traders.

    ๐Ÿ Competitors: CoinTracker, Koinly, ZenLedger, Accointing, BearTax
    ๐Ÿ‘ Pros:    Easy user interface|User-friendly|Great customer support

14 Best Crypto Tax Software to Ease Your Calculation and Be Compliant
Coinpanda should be your go-to crypto trading tax solution if you want to start without paying a penny. Its free option is feature-packed and misses only a few that are reserved for the top-of-the-line subscription.
Source: geekflare.com
15 Best Koinly Alternatives 2022
This platform was built after its makers had gone through a series of tax frustrations so the team understands your case very well. With Coinpanda, youโ€™ll save more time downloading your tax reports in a few minutes, minimizing your taxes and maximizing your profits.

Social recommendations and mentions

Based on our record, NumPy seems to be a lot more popular than Coinpanda. While we know about 122 links to NumPy, we've tracked only 8 mentions of Coinpanda. 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

Coinpanda mentions (8)

  • Why doesnโ€™t snowtrace csv export show the price at time of txn?
    I was waiting on koinly.io to incorporate Avalanche, but then someone mentioned coinpanda.io. I'm looking into it as an automated transaction compiler for tax purposes. Source: over 4 years ago
  • Calculate P&L for a financial year
    This website has something http://coinpanda.io but it is asking for a lot of money. Source: over 4 years ago
  • Iโ€™ve tried crypto tax software so you donโ€™t have to.
    Iโ€™ve moved to coin panda next - https://coinpanda.io/ Great selection of exchanges and all sorts of wallets, compliance with both US regulations and EU regulations. But UI/UX was a bit complicated to me compared to Koinly + Koinly was 10$ cheaper for my amount of transactions ๐Ÿ˜ Obvious move to Koinly. Source: over 4 years ago
  • Goals & porftolio tracking product
    What I mean is: you have entered your entries + goals for selling coins on futures and spot & set goals that you want to reach with your porftolio? Cointracker.io & https://coinpanda.io/ are great but they don't really give me this possibility, excel or google sheet with some advanced scripts can deal with this issue but nothing else. Feedback is much appreciated! Source: over 4 years ago
  • US tax strategies
    I was reading coinpanda.io musings on how the IRS breaks down staking for "business" vs "hobby". Source: over 4 years ago
View more

What are some alternatives?

When comparing NumPy and Coinpanda, 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.

Koinly - Koinly is the easiest way to monitor your crypto activity & file your taxes.

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

Blockpit - Keep track of your crypto portfolio & taxes in one place

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

ZenLedger - Automated IRS tax calculation & forms for crypto investors