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CoinTracking VS Matplotlib

Compare CoinTracking VS Matplotlib and see what are their differences

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

CoinTracking logo CoinTracking

All Coins, all Analyzes, all Calculations, all Charts and all Prices for Bitcoin, Litecoin...

Matplotlib logo Matplotlib

matplotlib is a python 2D plotting library which produces publication quality figures in a variety...
  • CoinTracking Landing page
    Landing page //
    2023-06-28
  • Matplotlib Landing page
    Landing page //
    2023-06-14

CoinTracking features and specs

  • Comprehensive Tracking
    CoinTracking supports tracking for over 20,000 different cryptocurrencies and tokens, providing a wide range of coverage for diverse portfolios.
  • Detailed Reports
    Generates detailed reports for tax purposes, helping users to stay compliant with local regulations and easily file their crypto taxes.
  • Real-Time Data
    Offers real-time updates on portfolio value, allowing investors to make timely decisions based on the latest market data.
  • API Integrations
    Supports API integrations with numerous exchanges and wallets, facilitating automatic import of transaction data.
  • Mobile Accessibility
    Provides a mobile app, enabling users to keep track of their cryptocurrency portfolio and investment performance on the go.
  • Security Features
    Implements advanced security measures like two-factor authentication (2FA) to protect user data and accounts.

Possible disadvantages of CoinTracking

  • Cost
    The full range of features is only available in the paid plans, which might be expensive for some users.
  • Complexity
    The platform can be overwhelming for beginners due to its wide array of features and detailed interface.
  • API Integration Issues
    Some users experience occasional difficulties with API integrations, leading to issues with transaction imports.
  • Customer Support
    Customer support can be slow at times, potentially frustrating users who need quick assistance.

Matplotlib features and specs

  • Versatility
    Matplotlib can generate a wide variety of plots, ranging from simple line plots to complex 3D plots. This versatility makes it a go-to library for many scientific and technical visualizations.
  • Customization
    It offers extensive customization options for virtually every element of a plot, including colors, labels, line styles, and more, allowing users to tailor plots to meet specific needs.
  • Integrations
    Matplotlib integrates well with other Python libraries such as NumPy, Pandas, and SciPy, making it easier to plot data directly from these sources.
  • Community and Documentation
    It has a large, active community and comprehensive documentation that includes tutorials, examples, and detailed references, which can help users solve problems and improve their plot-making skills.
  • Interactivity
    Matplotlib supports interactive plots, which can be embedded in Jupyter notebooks and GUIs, allowing for dynamic data exploration and presentation.
  • Publication-Quality
    The library is capable of producing high-quality, publication-ready graphics that meet the stringent requirements of academic journals and professional presentations.

Possible disadvantages of Matplotlib

  • Complexity
    While Matplotlib offers extensive customization, it can be complex and sometimes unintuitive for beginners, requiring a steep learning curve to master all its functionality.
  • Performance
    Rendering a large number of plots or handling very large datasets can be slow, making Matplotlib less suitable for real-time data visualization.
  • Modern Aesthetics
    Out-of-the-box plots from Matplotlib can look somewhat dated compared to those from newer plotting libraries like Seaborn or Plotly, requiring additional customization to achieve a modern look.
  • 3D Plots
    Although Matplotlib supports 3D plotting, its capabilities are relatively limited and less sophisticated compared to specialized 3D plotting libraries.
  • Size and Structure
    The package is relatively large and can be slow to import. Its extensive structure can make finding specific functions and understanding the overall architecture challenging.

Analysis of CoinTracking

Overall verdict

  • Overall, CoinTracking is a robust and reliable platform for both individuals and professionals looking to manage and analyze their cryptocurrency investments effectively.

Why this product is good

  • CoinTracking is considered a good choice for cryptocurrency portfolio management because it offers comprehensive tracking features, supports a wide range of exchanges and coins, and provides detailed analytical tools. Additionally, it offers tax reporting features that cater to various countries, which is particularly beneficial for users who need to adhere to tax regulations.

Recommended for

  • Cryptocurrency enthusiasts who actively trade and want detailed insights into their portfolio performance.
  • Individuals seeking an integrated solution for cryptocurrency tax reporting.
  • Professional traders and investors who require advanced features for tracking and analysis of their digital assets.

Analysis of Matplotlib

Overall verdict

  • Yes, Matplotlib is a good library for data visualization, particularly for users who require a versatile and powerful plotting solution in Python.

Why this product is good

  • Matplotlib is highly regarded due to its extensive customization options, versatility in creating a wide range of static, animated, and interactive plots, and its large user community and support. It integrates well with other scientific libraries in Python, making it a staple for data visualization. The library is also open-source and frequently updated, ensuring it remains a reliable choice for users.

Recommended for

  • Data scientists and analysts needing to create detailed, customized visual representations of their data.
  • Researchers and engineers looking for a comprehensive plotting library that supports scientific and engineering formats.
  • Python developers who require integration with other scientific computing libraries like NumPy and Pandas.

CoinTracking videos

+ Add

Cointracking Review - Track Crypto Portfolio and Taxes - Should You Get?!

Matplotlib videos

+ Add

Learn Matplotlib in 6 minutes | Matplotlib Python Tutorial

Category Popularity

0-100% (relative to CoinTracking and Matplotlib)

CoinTracking

Matplotlib

Cryptocurrencies
100 100%
Cryptocurrencies
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Cryptocurrency Investment
100 100%
Cryptocurrency Investment
0% 0
Technical Computing
0 0%
Technical Computing
100% 100

User comments

Share your experience with using CoinTracking and Matplotlib. For example, how are they different and which one is better?
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Reviews

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

CoinTracking Reviews

Best Cryptocurrency Tax Software: Complete Guide to the Top Options
CoinTracking aims to help out traders and investors, through an all-inclusive chart history for over 7,000 coins, updated prices, coin statistics, trends, volumes and analyses. In fact, professional help is also provided, as the platform collaborates with numerous CPAs, and full-service experts, whose services can be utilized for accurate tax reporting.
Source: blockonomi.com
Best Cryptocurrency Portfolio Trackers 2021 โ€“ Altcoin Management Apps
If you are just starting and planning to devote your time into investment and trading of digital currencies, I would recommend CoinTracking. You can trade with more than 100 cryptocurrencies and it helps you with the calculation of taxes. And in addition to that, it shows your profit and loss. With all the data available with CoinTracking you can make daily trading decision...
Source: captainaltcoin.com
Blockfolio Alternatives: Best Portfolio Apps Similar to Blockfolio
Cointracking is a company that helps cryptocurrency traders in different countries with filing their taxes. However, the firm also offers a traditional cryptocurrency portfolio app that provides similar functionality to the rest of the apps covered in this article. The Cointracking app supports over 4,000 different cryptocurrencies.
Source: coincodex.com

Matplotlib Reviews

25 Python Frameworks to Master
Matplotlib is a widely used tool for data visualization in Python. It provides an object-oriented API for embedding plots into applications.
Source: kinsta.com
5 Best Python Libraries For Data Visualization in 2023
You can use this library for multiple purposes such as generating plots, bar charts, histograms, power spectra, stemplots, pie charts, and more. The best thing about Matplotlib is you just have to write a few lines of code and it handles the rest by itself. Metaplotilib focuses on static images for publication along with interactive figures using toolkits like Qt and GTK.
Source: www.technotification.com
15 data science tools to consider using in 2021
Matplotlib is an open source Python plotting library that's used to read, import and visualize data in analytics applications. Data scientists and other users can create static, animated and interactive data visualizations with Matplotlib, using it in Python scripts, the Python and IPython shells, Jupyter Notebook, web application servers and various GUI toolkits.
Source: searchbusinessanalytics.techtarget.com
Top Python Libraries For Image Processing In 2021
Matplotlib is primarily used for 2D visualizations such as scatter plots, bar graphs, histograms, and many more, but we can also use it for image processing. It is effective to get information out of an image. It doesnโ€™t support all file formats.
Source: www.analyticsvidhya.com
Top 8 Python Libraries for Data Visualization
Matplotlib is a data visualization library and 2-D plotting library of Python It was initially released in 2003 and it is the most popular and widely-used plotting library in the Python community. It comes with an interactive environment across multiple platforms. Matplotlib can be used in Python scripts, the Python and IPython shells, the Jupyter notebook, web application...
Source: www.geeksforgeeks.org

Social recommendations and mentions

CoinTracking might be a bit more popular than Matplotlib. We know about 162 links to it since March 2021 and only 114 links to Matplotlib. 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.

CoinTracking mentions (162)

  • Can I see my balance from any past date?
    Https://cointracking.info/ does taxes too. Source: about 3 years ago
  • Received $20,000 tax bill
    Upload your entire wallet history to cointracking.info. It's what we recommend to our clients and it'll produce mostly accurate tax forms. If you've been doing any "advanced crypto shenanigans" it won't get those right, but for basic trades and exchanges, it'll be good. Source: over 3 years ago
  • Crypto tax software
    I've been using cointracking.info since 2017 and have been happy with it. Use it for both crypto and nfts and it works great. You can use my referral to get 10% off too: https://cointracking.info?ref=P584886. Source: over 3 years ago
  • Rolling up transactions for Taxes
    You can use fairspot to generate a csv to import into https://cointracking.info/. Has good reporting and can get tax forms for your country. Source: over 3 years ago
  • Defi Crypto taxes
    For the past two years, I've been using CoinTracking (https://cointracking.info/). Of course, it has its own drawbacks and learning curve for defi, but if you have most of your transactions on the main EVM chains (Avalanche, Fantom, Arbitrum, and of course Ethereum), they've gotten better at importing LPs and yield farming over the years. Source: over 3 years ago
View more

Matplotlib mentions (114)

  • The soul file
    In February, an AI agent named MJ Rathbun submitted a pull request to matplotlib โ€” the Python plotting library used by half the scientific computing world. Scott Shambaugh, a volunteer maintainer, rejected it. Standard code review. Nothing unusual. - Source: dev.to / 4 months ago
  • How to Analyze CSV Files with Python and Pandas
    Numbers are useful, but sometimes itโ€™s easier to spot patterns when you can actually see your data. Pandas works seamlessly with Matplotlib, a popular Python library for creating visualizations. Together, they make it easy to turn raw numbers into clear charts. - Source: dev.to / 7 months ago
  • libmalloc, jemalloc, tcmalloc, mimalloc - Exploring Different Memory Allocators
    We are storing the results in JSON files, which we combine, analyze and visualize using matplotlib in Python. Here's the structure of a benchmark result file:. - Source: dev.to / 8 months ago
  • Building an AI Scoring Agent: Step-By-Step
    NetworkX and Matplotlib were used to visualize the graph structure of the agent. - Source: dev.to / 9 months ago
  • Top 5 GitHub Repositories for Data Science in 2026
    The book introduces the core libraries essential for working with data in Python: particularly IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and related packages Familiarity with Python as a language is assumed; if you need a quick introduction to the language itself, see the free companion project, Aโ€ฆ. - Source: dev.to / 10 months ago
View more

What are some alternatives?

When comparing CoinTracking and Matplotlib, you can also consider the following products

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

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

CoinMarketCap - Crypto-currency market capitalizations.

NumPy - NumPy is the fundamental package for scientific computing with Python

CoinStats - CoinStats is a cryptocurrency research and portfolio tracker, that allows to access market data on over 3000 cryptocurrencies, track bitcoin and altcoin investments.

Seaborn - Seaborn is a Python data visualization library that uses Matplotlib to make statistical graphics.

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