Software Alternatives, Accelerators & Startups

Matplotlib VS Anaplan

Compare Matplotlib VS Anaplan and see what are their differences

Matplotlib logo Matplotlib

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

Anaplan logo Anaplan

Planning & performance management platform
  • Matplotlib Landing page
    Landing page //
    2023-06-14
  • Anaplan Landing page
    Landing page //
    2023-09-15

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.

Anaplan features and specs

  • Scalability
    Anaplan is designed to handle large data sets and complex models, making it suitable for enterprises with extensive and growing data needs.
  • User-Friendly Interface
    The platform offers a visually intuitive interface that allows users to create and modify models without deep technical expertise.
  • Real-Time Data Processing
    Anaplan enables real-time collaboration and immediate updates, ensuring that all users work with the most current data.
  • Customization
    The system provides a high level of customization, allowing businesses to tailor solutions to their specific requirements and workflows.
  • Integrated Planning
    Anaplan offers integrated business planning, connecting various departments and enabling cohesive decision-making.

Possible disadvantages of Anaplan

  • Cost
    Anaplan can be relatively expensive, especially for small and medium-sized enterprises, potentially making it a less viable option for those with limited budgets.
  • Complex Implementation
    Setting up Anaplan can be complex and time-consuming, often requiring specialized knowledge and possibly external consultants for effective deployment.
  • Learning Curve
    Though the interface is user-friendly, mastering Anaplanโ€™s full capabilities can require substantial training and experience.
  • Resource Intensive
    The platform can be resource-intensive, requiring robust hardware and network capabilities to ensure optimal performance.
  • Limited Third-Party Integrations
    While Anaplan integrates well with some major applications, it may offer limited compatibility with certain third-party tools, potentially requiring additional steps for integration.

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 Anaplan

Overall verdict

  • Anaplan is generally considered a powerful tool for enterprises looking for comprehensive planning and forecasting solutions. Users appreciate its ability to handle complex modeling and its user-friendly interface, though some note that the initial learning curve can be steep.

Why this product is good

  • Anaplan is widely regarded as a robust platform for business planning and performance management. It offers a cloud-based solution that allows for interconnected planning, ensuring that various departments like finance, HR, and supply chain can collaborate seamlessly. The platform is highly praised for its flexibility, scalability, and real-time data analytics, which enable organizations to make informed decisions quickly.

Recommended for

    Anaplan is best suited for medium to large enterprises that require advanced planning, budgeting, and forecasting capabilities across multiple departments. It is particularly beneficial for organizations seeking to align operations with strategic goals using data-driven insights.

Matplotlib videos

Learn Matplotlib in 6 minutes | Matplotlib Python Tutorial

Anaplan videos

The Top 10 Things You Need to Know About Anaplan

More videos:

  • Review - Anaplan CEO predicts 'dramatic shift' in business planning
  • Review - Demo: Anaplan Sales Forecasting in Action

Category Popularity

0-100% (relative to Matplotlib and Anaplan)
Data Science And Machine Learning
Data Dashboard
38 38%
62% 62
Technical Computing
100 100%
0% 0
Financial Performance Management

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 Anaplan

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.
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.
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.
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...

Anaplan Reviews

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

Based on our record, Matplotlib seems to be a lot more popular than Anaplan. While we know about 114 links to Matplotlib, we've tracked only 1 mention of Anaplan. 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 / 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
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Anaplan mentions (1)

  • Cashflow forecast based on client average days to pay
    Anaplan (anaplan.com) is an option as you'll need to setup an integration via tray.io. They are not add-ons but separate applications that will take your Xero data and replicate a copy of the data into Anaplan. Once the Xero data is in Anaplan you'll be able to do the detailed Cash Flow. I don't work for any of the companies discussed here. Source: over 3 years ago

What are some alternatives?

When comparing Matplotlib and Anaplan, 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.

Prophix Software - Prophix develops Corporate Performance Management (CPM) software that automates important financial and operational processes.

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

Planful - Planful is an online development platform with different remarkable services and features that enable users to make a rolling forecast, helping their business meet with every change.

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

Board - Unified BI, CPM and predictive analytics software.