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Power BI Desktop VS Matplotlib

Compare Power BI Desktop 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

Power BI Desktop logo Power BI Desktop

Create interactive reports with data modeling tools from Power BI Desktop. Connect to any data and easily gain actionable insightsโ€”for free.

Matplotlib logo Matplotlib

matplotlib is a python 2D plotting library which produces publication quality figures in a variety...
  • Power BI Desktop Landing page
    Landing page //
    2023-08-21
  • Matplotlib Landing page
    Landing page //
    2023-06-14

Power BI Desktop features and specs

  • User-Friendly Interface
    Power BI Desktop offers a highly intuitive interface that is easy to navigate, making it accessible for users with varying levels of technical expertise.
  • Data Visualization
    The tool provides a wide range of data visualization options that help users create insightful reports and dashboards to better understand their data.
  • Integration Capabilities
    Power BI Desktop seamlessly integrates with numerous data sources, including Microsoft Excel, SQL Server, Azure, and other services, allowing for easy data connectivity.
  • Cost-Effectiveness
    As a part of the Microsoft ecosystem, Power BI offers a free tier with significant capabilities, providing a cost-effective solution for many businesses.
  • Custom Visualization Support
    The platform supports custom visualizations, allowing users to create and share tailored visuals using the open-source R and Python programming languages.

Possible disadvantages of Power BI Desktop

  • Limited Data Handling
    Power BI Desktop may struggle with very large datasets and complex calculations, which can affect performance and responsiveness.
  • Learning Curve for Advanced Features
    While the basic functionalities are easy to learn, mastering advanced capabilities, such as DAX (Data Analysis Expressions) or M (Power Query Formula Language), requires time and technical understanding.
  • Dependency on Microsoft Ecosystem
    Optimal use of Power BI often depends on compatibility with the Microsoft ecosystem, which might not be suitable for organizations using alternative platforms.
  • Limited Customization in Free Version
    The free version of Power BI Desktop has limitations in terms of customization and sharing capabilities compared to the premium versions.
  • Data Refresh Limitations
    There are restrictions on the frequency and volume of data refreshes, especially in the free version, which can be a constraint for real-time data analysis needs.

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 Power BI Desktop

Overall verdict

  • Power BI Desktop is a powerful and cost-effective business intelligence tool that excels at data modeling, visualization, and reporting, backed by an active Microsoft Fabric community for support and learning.

Why this product is good

  • Free to download and use for individual report creation and data analysis
  • Robust data connectivity with hundreds of built-in connectors to databases, cloud services, and files
  • Powerful data modeling and transformation capabilities via Power Query and DAX
  • Rich, interactive visualizations that make insights easy to explore and share
  • Strong integration with the broader Microsoft ecosystem, including Excel, Azure, and Microsoft Fabric
  • Active community forum (community.fabric.microsoft.com) offering tutorials, troubleshooting, and best practices
  • Regular monthly updates adding new features and improvements

Recommended for

  • Data analysts and business intelligence professionals building interactive dashboards
  • Small to large organizations already invested in the Microsoft ecosystem
  • Individuals learning data visualization and analytics on a budget
  • Teams needing to transform and model data from multiple sources
  • Report developers who benefit from community-driven support and resources

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.

Power BI Desktop 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 Power BI Desktop and Matplotlib)

Power BI Desktop

Matplotlib

Business Intelligence
100 100%
Business Intelligence
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Data Dashboard
14 14%
Data Dashboard
86% 86
Technical Computing
0 0%
Technical Computing
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 Power BI Desktop and Matplotlib

Power BI Desktop Reviews

We have no reviews of Power BI Desktop 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 Power BI Desktop. While we know about 114 links to Matplotlib, we've tracked only 7 mentions of Power BI Desktop. 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.

Power BI Desktop mentions (7)

  • Using Power BI to visualize Edge data sent to Azure IoT Hub
    Navigate to the official website and click Download free. - Source: dev.to / over 3 years ago
  • Powerful new feature upcoming in Power BI
    There is a hidden gem in the August 2022 release of Power BI Desktop: a secret new DAX function EvaluateAndLog that is not listed in the feature summary of the official blogpost. Yet this function will become a great learning and debugging tool for anyone who writes DAX code in the years to come. Source: almost 4 years ago
  • Using Azure SQL and PowerBI to report on Speaking Events
    You will need PowerBI Desktop installed on your machine for this next stage. You can download the latest version form here. - Source: dev.to / about 4 years ago
  • Microsoft Power BI: New Starter Reports for BigCommerce
    Havenโ€™t set up Microsoft Power BI Desktop? See Microsoft Power BI Desktop to get started. Source: about 4 years ago
  • Full list of NZ Postcodes and Rural District postcodes
    Microsoft Power BI Desktop (free) can automatically extract the table data from those PDFs. From there you can export to Excel/CSV. Source: almost 5 years ago
View more

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 / 5 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 / 8 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
View more

What are some alternatives?

When comparing Power BI Desktop and Matplotlib, you can also consider the following products

Kyvos Insights - Kyvos is a semantic layer for AI and BI. It gives organizations a single, consistent, business-friendly view of their entire data estate.

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

Hexpandify - Visualize your business performance like never before with an interactive strategic hexagonal map

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

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.

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

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