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Stonk Journal VS Matplotlib

Compare Stonk Journal 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

Stonk Journal logo Stonk Journal

Free trading journal with an AI coach that reviews your trades and helps you improve.

Matplotlib logo Matplotlib

matplotlib is a python 2D plotting library which produces publication quality figures in a variety...
  • Stonk Journal
    Image date //
    2026-06-10
  • Stonk Journal
    Image date //
    2026-06-10

Stonk Journal turns your trade history into evidence you can actually act on. Log trades manually or import them by CSV or Excel, then see exactly where your edge comes from: win rate, profit factor, expectancy, R-multiple, average win and loss, hold time, equity curve, drawdown, and 30+ more metrics. A daily P&L heatmap shows your performance day by day with drill-down into every trade.

Set your own risk rules (max risk per trade, position size, daily loss limits, required fields) and get flagged in real time when a trade breaks one, so you can measure what your discipline is actually costing or earning you. Track paper, live, prop, and futures accounts separately, or view them aggregated. Filter your whole history by symbol, status, market, direction, tags, P&L range, date, and rule compliance in a single query. Multi-leg option spreads are detected automatically.

On Pro, the AI Coach reads only your journal to surface costly behavioral leaks like revenge sizing, overconfidence, and the disposition effect, and answers natural-language questions about your own trades. You can also generate shareable performance cards for X, Reddit, LinkedIn, and more.

No ads, no data sold, not financial advice. Established 2021, with over 10 million trades logged.

Key Features

  • 30+ performance metrics โ€” win rate, profit factor, expectancy, R-multiple, drawdown, equity curve
  • Daily P&L calendar heatmap with trade-level drill-down
  • Custom risk rules with real-time compliance flagging
  • AI Coach & AI chat over your own trade history (Pro)
  • Multi-account tracking (paper, live, prop, futures) plus an aggregated dashboard (Pro)
  • Universal filtering across symbol, market, tags, P&L, date, and compliance
  • Multi-leg options support with automatic spread detection
  • CSV & Excel import (Pro)
  • Shareable performance cards
  • Installable PWA with offline support
  • Stocks, options, futures, forex, and crypto
  • Matplotlib Landing page
    Landing page //
    2023-06-14

Stonk Journal features and specs

  • User-Friendly Interface
    Stonk Journal offers a clean and intuitive design making it easy for users to navigate and find information on stocks and markets.
  • Comprehensive Analytics
    Provides detailed analytics and insights into market trends that help users make informed investment decisions.
  • Timely Updates
    Delivers real-time updates and notifications on stock performance and market news, ensuring users are always informed.
  • Community Interaction
    Includes a community feature for discussions and sharing insights with other users, fostering a collaborative environment.
  • Customizable Watchlists
    Allows users to create and customize watchlists to track their stocks of interest easily.

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 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.

Stonk Journal videos

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Matplotlib videos

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Learn Matplotlib in 6 minutes | Matplotlib Python Tutorial

Category Popularity

0-100% (relative to Stonk Journal and Matplotlib)

Stonk Journal

Matplotlib

Trading
100 100%
Trading
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Finance
100 100%
Finance
0% 0
Technical Computing
0 0%
Technical Computing
100% 100

Questions & Answers

As answered by people managing Stonk Journal and Matplotlib.

What makes your product unique?

Stonk Journal's answer

User experience: providing a user-friendly interface and experience that caters to both beginners and experienced investors.

Why should a person choose your product over its competitors?

Stonk Journal's answer

Just try it. You don't need to buy it. ๐Ÿ˜€

User comments

Share your experience with using Stonk Journal 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 Stonk Journal and Matplotlib

Stonk Journal Reviews

We have no reviews of Stonk Journal yet.
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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

Based on our record, Matplotlib seems to be a lot more popular than Stonk Journal. While we know about 114 links to Matplotlib, we've tracked only 2 mentions of Stonk Journal. 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.

Stonk Journal mentions (2)

  • May was a good month!
    I'm using StonkJournal. It's a separate app from my broker (TDA). Source: about 3 years ago
  • Trading Journal
    I built a journal stonkjournal.com... No import yet but I'm working on it. Check it out let me know what you think. It's free but if you really wan to pay for.. There is a way. :). Source: over 3 years ago

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
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What are some alternatives?

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

TraderSync - Biometric trading journal to trade without emotion

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

TradesViz - An online trade logging platform that does it all! Logging, charting, sharing, trade management, risk analysis and many more! The best trading journal to find and visualize your trading edge.

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

Trademetria - Trading journal for traders and investors.

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

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