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Matplotlib VS QlikSense

Compare Matplotlib VS QlikSense and see what are their differences

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Do-It-Yourself Data Analytics & Business Intelligence, Powered by AI featured
Contents:
  1. ยป Base Details
  2. ยป Videos
  3. ยป Reviews
  4. ยป Alternatives

Matplotlib logo Matplotlib

matplotlib is a python 2D plotting library which produces publication quality figures in a variety...

QlikSense logo QlikSense

A business discovery platform that delivers self-service business intelligence capabilities
  • Matplotlib Landing page
    Landing page //
    2023-06-14
  • QlikSense Landing page
    Landing page //
    2022-08-02

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.

QlikSense features and specs

  • Data integration
    QlikSense offers robust data integration capabilities, allowing users to easily combine data from multiple sources, leveraging an associative data engine for more comprehensive analysis.
  • User-friendly interface
    It features an intuitive and user-friendly interface that makes it easy for users with varying levels of technical expertise to create and interpret visualizations and reports.
  • Self-service BI
    QlikSense supports self-service business intelligence, enabling users to build their own dashboards and reports without heavy reliance on IT or data experts.
  • Advanced analytics
    It integrates advanced analytics capabilities, including predictive analytics and AI-driven insights, helping users gain deeper and more actionable insights from their data.
  • Scalability
    QlikSense is highly scalable, suitable for individual users, small teams, and large enterprises, providing flexibility in deployment and usage.

Possible disadvantages of QlikSense

  • Cost
    Compared to some other BI tools, QlikSense can be relatively expensive, especially for smaller organizations or users with limited budgets.
  • Learning curve
    While the interface is user-friendly, there can be a steep learning curve for new users to understand the full functionality and to use advanced features effectively.
  • Performance issues
    Some users may experience performance issues, particularly when working with very large datasets or complex calculations without proper optimization.
  • Customization limitations
    Although QlikSense offers a range of customization options, there might be limitations in terms of highly specific or niche custom requirements.
  • Partial offline capabilities
    QlikSense's offline capabilities can be limited, which could be a drawback for users who need full offline access and functionality.

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.

Analysis of QlikSense

Overall verdict

  • Yes, Qlik Sense is generally considered good, particularly for organizations seeking a comprehensive, scalable, and user-friendly business intelligence solution that supports advanced analytics and data visualization.

Why this product is good

  • Qlik Sense is known for its powerful data visualization and business intelligence capabilities. It allows users to create interactive dashboards that enable deep insight into data.
  • It uses an associative data model that allows for efficient data exploration and discovery, making it easy to uncover hidden insights.
  • Its self-service capabilities empower non-technical users to perform complex data analyses without needing extensive coding knowledge.
  • Qlik Sense supports a wide range of data sources and offers robust integration options, making it flexible for various business needs.
  • The platform provides robust security features, ensuring that sensitive data is well-protected.

Recommended for

  • Businesses looking for an intuitive and self-service BI tool for data visualization and exploration.
  • Data analysts and business analysts needing to uncover and share data insights easily.
  • Organizations seeking a platform that integrates with a variety of data sources and is scalable to large datasets.
  • Companies that require advanced analytics capabilities without relying heavily on IT staff.

Matplotlib videos

+ Add

Learn Matplotlib in 6 minutes | Matplotlib Python Tutorial

QlikSense videos

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Category Popularity

0-100% (relative to Matplotlib and QlikSense)

Matplotlib

QlikSense

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Data Dashboard
21 21%
Data Dashboard
79% 79
Technical Computing
100 100%
Technical Computing
0% 0
Business Intelligence
0 0%
Business Intelligence
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 Matplotlib and QlikSense

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

QlikSense Reviews

We have no reviews of QlikSense yet.
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Social recommendations and mentions

Based on our record, Matplotlib seems to be more popular. It has been mentiond 114 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.

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 / 4 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 / 7 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 / 7 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 / 8 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

QlikSense mentions (0)

We have not tracked any mentions of QlikSense yet. Tracking of QlikSense recommendations started around Mar 2021.

What are some alternatives?

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

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

Looker - Looker makes it easy for analysts to create and curate custom data experiencesโ€”so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.

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

Qlik - Qlik offers an Active Intelligence platform, delivering end-to-end, real-time data integration and analytics cloud solutions to close the gaps between data, insights, and action.

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

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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