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Portfolio Performance VS Plotly

Compare Portfolio Performance VS Plotly and see what are their differences

Lucris
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Portfolio Performance logo Portfolio Performance

Stock portfolio tracking

Plotly logo Plotly

Low-Code Data Apps
  • Portfolio Performance Landing page
    Landing page //
    2021-09-27
  • Plotly Landing page
    Landing page //
    2023-07-31

Portfolio Performance features and specs

  • Free and Open Source
    Portfolio Performance is completely free to use and is open source, allowing users to access and modify the source code if desired.
  • Comprehensive Tracking
    The software provides detailed tracking of your investment portfolio, including performance over time, asset allocation, dividends, and fees.
  • Cross-Platform Compatibility
    It is available on multiple platforms, including Windows, macOS, and Linux, making it accessible to a wide range of users.
  • Customizable Reports and Charts
    Provides a variety of customizable reports and charts to help users analyze portfolio performance in detail.
  • Offline Usage
    The software can be used offline, providing user privacy and security without the need for internet connectivity.

Possible disadvantages of Portfolio Performance

  • Steep Learning Curve
    The software can be complex and may require some time for new users to fully understand all the features and functionalities.
  • Limited User Support
    As an open-source project, it may lack formal customer support, relying instead on community forums for assistance.
  • Manual Data Entry
    Users often need to input data manually, which can be time-consuming and prone to errors, particularly with large portfolios.
  • No Mobile App
    Currently, there is no dedicated mobile app, which might be inconvenient for users who prefer managing their portfolio on the go.
  • Interface Design
    The user interface may not be as polished or intuitive as some commercial alternatives, potentially affecting user experience.

Plotly features and specs

  • Interactivity
    Plotly offers highly interactive plots that allow users to pan, zoom, and hover over data points for more information. This enhances the user experience and provides deeper insights.
  • High-quality visualizations
    It provides aesthetically pleasing and highly customizable charts, making it suitable for publication-quality visuals.
  • Versatility
    Plotly supports multiple chart types including line charts, scatter plots, bar charts, and 3D plots, making it suitable for a wide range of applications.
  • Python integration
    Plotly is well-integrated with Python and works seamlessly with other popular data science libraries like Pandas, NumPy, and Scikit-learn.
  • Web-based
    The plots can be easily embedded in web applications or dashboards, making it ideal for sharing insights over the internet.
  • Open-source
    Plotly offers an open-source version, which allows users to create and share visualizations without any cost.

Possible disadvantages of Plotly

  • Performance
    Rendering very large datasets can sometimes be slow, which may not be suitable for real-time data visualization requirements.
  • Learning curve
    Even though the library is well-documented, the extensive range of features can have a steep learning curve for beginners.
  • Cost for advanced features
    While the basic functionality is free, more advanced features, such as export to certain formats and additional customizable options, require a paid subscription.
  • Dependency management
    Plotly has a number of dependencies that need to be managed properly, which can sometimes complicate the setup process.
  • Complexity
    For simple visualizations, Plotly might be overkill and simpler libraries like Matplotlib or Seaborn could be more appropriate.

Analysis of Plotly

Overall verdict

  • Overall, Plotly is a strong choice for those looking to create dynamic and interactive data visualizations, thanks to its range of features and ease of integration with web technologies.

Why this product is good

  • Plotly is considered good because it offers a comprehensive suite of tools for creating interactive visualizations that can be used in web applications, reports, and dashboards. It supports many different types of plots, is easy to use for both beginners and experienced developers, and integrates well with popular programming languages like Python, R, and JavaScript.

Recommended for

    Plotly is recommended for data scientists, analysts, and developers who need to create interactive and visually appealing data visualizations. It's particularly useful for those who work with Python or R and want the ability to embed their visualizations in web applications or dashboards.

Portfolio Performance videos

+ Add

Evaluating Portfolio Performance How to Evaluate Your Portfolio

More videos:

  • Review - 2020: CFA Level III - Portfolio Performance Evaluation
  • Tutorial - How To Track Your Peer to Peer Lending Investments with Portfolio Performance

Plotly videos

+ Add

Create Real-time Chart with Javascript | Plotly.js Tutorial

More videos:

  • Review - Introducing plotly.py 3.0
  • Review - Is Plotly The Better Matplotlib?
  • Tutorial - Plotly Tutorial 2021
  • Review - Data Visualization as The First and Last Mile of Data Science Plotly Express and Dash | SciPy 2021

Category Popularity

0-100% (relative to Portfolio Performance and Plotly)

Portfolio Performance

Plotly

Finance
100 100%
Finance
0% 0
Data Visualization
0 0%
Data Visualization
100% 100
Investing
100 100%
Investing
0% 0
Charting Libraries
0 0%
Charting Libraries
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 Portfolio Performance and Plotly

Portfolio Performance Reviews

We have no reviews of Portfolio Performance yet.
Be the first one to post

Plotly Reviews

Best 8 Redash Alternatives in 2023 [In Depth Guide]
Plotly is specifically designed for companies who want to build and deploy analytic applications like dashboards using Python, Julia, or R without needing DevOps or Javascript developers.
Source: www.datapad.io
5 Best Python Libraries For Data Visualization in 2023
Plotly is a web-based data visualization toolkit that comes with unique functionalities such as dendrograms, 3D charts, and also contour plots, which is not very common in other libraries. It has a great API offering scatter plots, line charts, bar charts, error bars, box plots, and other visualizations. Plotly can even be accessed from a Python Notebook.
Source: www.technotification.com
Top 8 Python Libraries for Data Visualization
Plotly is a free open-source graphing library that can be used to form data visualizations. Plotly (plotly.py) is built on top of the Plotly JavaScript library (plotly.js) and can be used to create web-based data visualizations that can be displayed in Jupyter notebooks or web applications using Dash or saved as individual HTML files. Plotly provides more than 40 unique...
Source: www.geeksforgeeks.org
5 top picks for JavaScript chart libraries
Plotly is a graphing library that’s available for various runtime environments, including the browser. It supports many kinds of charts and graphs that we can configure with a variety of options.
Source: blog.logrocket.com

Social recommendations and mentions

Based on our record, Plotly seems to be a lot more popular than Portfolio Performance. While we know about 34 links to Plotly, we've tracked only 1 mention of Portfolio Performance. 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.

Portfolio Performance mentions (1)

  • Application/Software to Manage personal Finances & Budget
    To keep track of investment performance I use the open source tool PortfolioPerformance. It’s stored locally and not in the cloud (like an excel sheet) and gives a pretty nice interface with stats and graphs. (See: https://portfolio-performance.info). Source: over 4 years ago

Plotly mentions (34)

  • How to Analyze 47 Million Hacker News Posts: A Data Scientist's Dream Dataset Just Got Better
    Let's dive into some practical examples. First, you'll need to set up your environment with the right tools. I recommend using pandas for data manipulation and plotly for visualization. - Source: dev.to / 6 months ago
  • Python for Data Visualization: Best Tools and Practices
    Plotly is perfect for interactive visualizations. You can create interactive charts and graphs that allow users to hover, click, and zoom in. Plotly is also great for web-based visuals, making it easy to share your findings online. - Source: dev.to / over 1 year ago
  • Generative AI Powered QnA & Visualization Chatbot
    Front End: A React application that leverages React-Chatbotify library to easily integrate a chatbot GUI. It also uses the Plotly library to display the charts/visualizations. The generative AI implementation and details are entirely abstracted from the front end. The front-end application depends on a single REST endpoint of the backend application. - Source: dev.to / over 1 year ago
  • Build a Stock Dashboard in less than 40 lines of Python code!🤓
    In this tutorial, Mariya Sha will guide you through building a stock value dashboard using Taipy, Plotly, and a dataset from Kaggle. - Source: dev.to / almost 2 years ago
  • Essential Deep Learning Checklist: Best Practices Unveiled
    How to Accomplish: Utilize visualization libraries like Matplotlib, Seaborn, or Plotly in Python to create histograms, scatter plots, and bar charts. For image data, use tools that visualize images alongside their labels to check for labeling accuracy. For structured data, correlation matrices and pair plots can be highly informative. - Source: dev.to / about 2 years ago
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What are some alternatives?

When comparing Portfolio Performance and Plotly, you can also consider the following products

Sharesight - Online stock portfolio tracker that automatically tracks prices, dividends, performance and tax.

D3.js - D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG, and CSS.

Snowball Analytics - Simple and powerful portfolio tracker for investors. Dividend tracker, portfolio performance and quick portfolio rebalancing. Supports thousands of stocks, funds and cryptocurrencies from all over the world.

RAWGraphs - RAWGraphs is an open source app built with the goal of making the visualization of complex data...

getquin - Track all your investments in one place

Tableau - Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.

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