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Matplotlib

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Victory

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Matplotlib vs Victory: What are the differences?

Matplotlib: A plotting library for the Python programming language. It is a Python 2D plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments across platforms. It can be used in Python scripts, the Python and IPython shells, the Jupyter notebook, web application servers, and four graphical user interface toolkits; Victory: ReactJS library for building interactive data visualizations. A collection of composable React components for building interactive data visualizations.

Matplotlib and Victory can be primarily classified as "Charting Libraries" tools.

Victory is an open source tool with 7.33K GitHub stars and 311 GitHub forks. Here's a link to Victory's open source repository on GitHub.

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Pros of Matplotlib
Pros of Victory
  • 10
    The standard Swiss Army Knife of plotting
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    Cons of Matplotlib
    Cons of Victory
    • 5
      Lots of code
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      - No public GitHub repository available -

      What is Matplotlib?

      It is a Python 2D plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments across platforms. It can be used in Python scripts, the Python and IPython shells, the Jupyter notebook, web application servers, and four graphical user interface toolkits.

      What is Victory?

      A collection of composable React components for building interactive data visualizations.

      Need advice about which tool to choose?Ask the StackShare community!

      What companies use Matplotlib?
      What companies use Victory?
      See which teams inside your own company are using Matplotlib or Victory.
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      What tools integrate with Matplotlib?
      What tools integrate with Victory?

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      What are some alternatives to Matplotlib and Victory?
      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.
      MATLAB
      Using MATLAB, you can analyze data, develop algorithms, and create models and applications. The language, tools, and built-in math functions enable you to explore multiple approaches and reach a solution faster than with spreadsheets or traditional programming languages, such as C/C++ or Java.
      Bokeh
      Bokeh is an interactive visualization library for modern web browsers. It provides elegant, concise construction of versatile graphics, and affords high-performance interactivity over large or streaming datasets.
      R Language
      R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, ...) and graphical techniques, and is highly extensible.
      Plotly.js
      It is a standalone Javascript data visualization library, and it also powers the Python and R modules named plotly in those respective ecosystems (referred to as Plotly.py and Plotly.R). It can be used to produce dozens of chart types and visualizations, including statistical charts, 3D graphs, scientific charts, SVG and tile maps, financial charts and more.
      See all alternatives