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Qalculate! VS Matplotlib

Compare Qalculate! VS Matplotlib and see what are their differences

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Qalculate! logo Qalculate!

Qalculate! is a multiplatform multi-purpose desktop calculator.

Matplotlib logo Matplotlib

matplotlib is a python 2D plotting library which produces publication quality figures in a variety...
  • Qalculate! Landing page
    Landing page //
    2023-10-11
  • Matplotlib Landing page
    Landing page //
    2023-06-14

Qalculate! features and specs

  • Versatility
    Qalculate! supports a wide range of calculations, including basic arithmetic, algebra, calculus, and complex mathematical functions, making it suitable for various users from students to professionals.
  • Extensive Unit Conversions
    It provides extensive support for unit conversions across different measurement systems, which is very useful for scientific and engineering computations.
  • Currency Conversion
    The tool includes real-time currency conversion capabilities, allowing users to perform financial calculations with current exchange rates.
  • Customizability
    Users can define their own functions and variables, offering a high degree of customization to cater to specific needs.
  • User-Friendly Interface
    Qalculate! features an intuitive and user-friendly interface, making it accessible even to those who are not highly technically proficient.
  • Cross-Platform
    It is available on multiple operating systems, including Windows, macOS, and Linux, ensuring accessibility for a wide user base.
  • Free and Open Source
    Being open-source and free to use, it offers a cost-effective solution compared to commercial software without compromising on features.

Possible disadvantages of Qalculate!

  • Learning Curve
    Despite its user-friendly interface, the vast array of features and functionalities may present a steep learning curve for new users.
  • Documentation
    While there is documentation available, it may not be as comprehensive or as user-friendly as some users might require, making it challenging to fully utilize all features.
  • Performance
    For very large or complex calculations, the performance might not be as robust or fast as some specialized or commercial tools.
  • GUI Limitations
    The graphical user interface (GUI) might have limitations in presenting very complex calculations or notations as compared to some professional-grade mathematical software.
  • Lack of Community Support
    Being a niche tool, it may not have as large of a community for support and resources as more popular commercial alternatives.

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.

Qalculate! videos

+ Add

DSP Raspberry Pi 4 Qalculate! Install

Matplotlib videos

+ Add

Learn Matplotlib in 6 minutes | Matplotlib Python Tutorial

Category Popularity

0-100% (relative to Qalculate! and Matplotlib)

Qalculate!

Matplotlib

Calculators
100 100%
Calculators
0% 0
Technical Computing
0 0%
Technical Computing
100% 100
Advanced Calculator
100 100%
Advanced Calculator
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
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 Qalculate! and Matplotlib

Qalculate! Reviews

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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 doesn’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 should be more popular than Qalculate!. It has been mentiond 107 times since March 2021. 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.

Qalculate! mentions (34)

  • Show HN: Unsure Calculator – back-of-a-napkin probabilistic calculator
    Https://qalculate.github.io can do this also for as long as I've used it (only a couple years to be fair). I've got it on my phone, my laptop, even my server with the qalc command. Super convenient, supports everything from unit conversion to uncertainty tracking The histogram is neat, I don't think qalc has that. On the other hand, it took 8 seconds to calculate the default (exceedingly trivial) example. Is that... - Source: Hacker News / about 1 month ago
  • Frink
    Interesting project. I use command line Qalculate [1] for this (has a very similar feature set to Frink AFAICT) and Pint [2] for scripting. I feel like unit-aware calculators are hugely underused by physical engineers, it's the same idea and benefit as type safety but they're virtually unheard of, everyone just uses excel. Having guaranteed dimensional correctness is so great for the early design stage, it makes... - Source: Hacker News / 2 months ago
  • "A calculator app? Anyone could make that."
    I use qalculate, it behaves well enough for my needs. https://qalculate.github.io/. - Source: Hacker News / 3 months ago
  • Students, what features would you like to see on Windows 12?
    1) a scientific calculator with history and variables with a UI similar to https://sourceforge.net/projects/alt1-calculator/ that also can do units like https://qalculate.github.io/ 2) a tiny text chat direct message program that is similarly as easily accessible at Atl1 3) a minimalist dock of as many instances you would like similar to https://punklabs.com/rocketdock, and like where WIN opens the start menu, WIN... Source: over 1 year ago
  • Paint on Windows is getting layers and transparency support
    Qalculate is my go-to for cross platform calculator that is useful and is not limited to the most basic +-*/ operations. https://qalculate.github.io/. - Source: Hacker News / over 1 year ago
View more

Matplotlib mentions (107)

  • Python for Data Visualization: Best Tools and Practices
    Matplotlib is the backbone of Python data visualization. It’s a flexible, reliable library for creating static plots. Whether you're making simple bar charts or complex graphs, Matplotlib allows extensive customization. You can adjust nearly every aspect of a plot to suit your needs. - Source: dev.to / about 2 months ago
  • Build a Competitive Intelligence Tool Powered by AI
    Add data visualization to make it actionable for your business using pandas.pydata.org and matplotlib.org. - Source: dev.to / 6 months ago
  • Data Visualisation Basics
    Matplotlib: a versatile library for visualizations, but it can take some code effort to put together common visualizations. - Source: dev.to / 9 months ago
  • Creating a CSV to Graph Generator App Using ToolJet and Python Libraries
    In this tutorial, we'll create a CSV to Graph Generator app using ToolJet and Python code. This app enables users to upload a CSV file and generate various types of graphs, including line, scatter, bar, histogram, and box plots. Since ToolJet supports Python (and JavaScript) code out of the box, we'll incorporate Python code and the matplotlib library to handle the graph generation. Additionally, we'll use... - Source: dev.to / 10 months ago
  • Something is strange with CrowdStrike timeline
    It looks like matplotlib to me: https://matplotlib.org/. - Source: Hacker News / 10 months ago
View more

What are some alternatives?

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

SpeedCrunch - SpeedCrunch. SpeedCrunch is a high-precision scientific calculator featuring a fast, keyboard-driven user interface. It is free and open-source software, licensed under the GPL. Download Documentation Donate .

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

Numi App - Numi is a beautiful text calculator for Mac.

GnuPlot - Gnuplot is a portable command-line driven interactive data and function plotting utility.

Event Viewer - Get help, support, and tutorials for Windows products—Windows 10, Windows 8.1, Windows 7, and Windows 10 Mobile.

Plotly - Low-Code Data Apps

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