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Matplotlib vs Tableau: What are the differences?

Introduction: In this article, we will explore the key differences between Matplotlib and Tableau in terms of their features and functionalities.

  1. Visualization Types: Matplotlib is a powerful Python library that allows users to create a wide range of visualizations, including line plots, scatter plots, bar plots, histograms, and more. It provides a high level of customization and control over the visual elements. On the other hand, Tableau is a comprehensive data visualization tool that offers a variety of pre-built visualizations, such as maps, dashboards, bubble charts, treemaps, and more. Tableau focuses on providing an intuitive and user-friendly interface for creating interactive visualizations.

  2. Data Source Connectivity: Matplotlib primarily relies on the user to import and preprocess data from various sources using Python programming. It requires users to write code to load data, perform any necessary data transformations, and then plot the visualizations. In contrast, Tableau provides seamless connectivity to a wide range of data sources, including spreadsheets, databases, cloud services, and web connectors. Users can easily connect to their data sources without writing any complex code and visualize the data in real-time.

  3. Interactivity and Dynamic Visualizations: Matplotlib allows users to create interactive visualizations, but it requires additional code to enable interactivity. Users need to write event handlers or animators to incorporate interactive elements such as zooming, panning, or toggling between data views. On the other hand, Tableau provides a drag-and-drop interface that allows users to easily add interactivity to their visualizations. Users can create dynamic visualizations by simply dragging and dropping elements like filters, parameters, or actions onto the canvas.

  4. Collaboration and Sharing: Matplotlib visualizations are typically created within Python programming environments, which makes collaboration and sharing slightly more complex. Users often need to share the code along with the visualizations, and the recipients need to have the necessary Python environment set up to run the code. In contrast, Tableau provides a platform that allows users to share interactive visualizations online or embed them in websites or presentations. Tableau also offers collaboration features, such as commenting and annotation tools, which make it easier for multiple users to collaborate on the same visualization.

  5. Advanced Analytics and Data Manipulation: Matplotlib is primarily focused on visualization and lacks advanced analytics capabilities. Users need to perform data manipulation and advanced statistical analysis separately using other Python libraries. In comparison, Tableau offers built-in data manipulation tools, such as data blending, pivot tables, and calculations. Additionally, Tableau provides advanced analytics features, such as forecasting, clustering, and trend analysis, which can be directly applied to the visualizations.

  6. Learning Curve and Ease of Use: Matplotlib is a highly flexible and powerful library, but it has a steeper learning curve compared to Tableau. Users need to have a strong understanding of Python programming and data visualization concepts to effectively use Matplotlib. On the other hand, Tableau provides a user-friendly and intuitive interface that allows users to quickly create visualizations without any programming knowledge. It is designed to be used by users with varying levels of technical expertise, making it more accessible to a wider audience.

In Summary, Matplotlib is a Python library that provides versatile customization and control over visualizations, while Tableau is a comprehensive data visualization tool that offers pre-built visualizations and an intuitive interface. Matplotlib requires users to write code to load data and create visualizations, while Tableau provides seamless connectivity to various data sources. Tableau offers drag-and-drop interactivity and collaboration features, whereas Matplotlib requires additional code for interactivity and sharing. Tableau includes advanced analytics and data manipulation tools, while Matplotlib focuses solely on visualization. Tableau has a lower learning curve and is more user-friendly compared to Matplotlib.

Decisions about Matplotlib and Tableau

Very easy-to-use UI. Good way to make data available inside the company for analysis.

Has some built-in visualizations and can be easily integrated with other JS visualization libraries such as D3.

Can be embedded into product to provide reporting functions.

Support team are helpful.

The only complain I have is lack of API support. Hard to track changes as codes and automate report deployment.

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Vojtech Kopal
Head of Data at Mews Systems · | 3 upvotes · 306.5K views

Power BI is really easy to start with. If you have just several Excel sheets or CSV files, or you build your first automated pipeline, it is actually quite intuitive to build your first reports.

And as we have kept growing, all the additional features and tools were just there within the Azure platform and/or Office 365.

Since we started building Mews, we have already passed several milestones in becoming start up, later also a scale up company and now getting ready to grow even further, and during all these phases Power BI was just the right tool for us.

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Pros of Matplotlib
Pros of Tableau
  • 10
    The standard Swiss Army Knife of plotting
  • 6
    Capable of visualising billions of rows
  • 1
    Intuitive and easy to learn
  • 1

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Cons of Matplotlib
Cons of Tableau
  • 5
    Lots of code
  • 2
    Very expensive for small companies

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

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What are some alternatives to Matplotlib and Tableau?
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 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.
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 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.
It is a general scheme for data visualization which breaks up graphs into semantic components such as scales and layers.
See all alternatives