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Matplotlib VS Whatagraph

Compare Matplotlib VS Whatagraph and see what are their differences

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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...

Whatagraph logo Whatagraph

Whatagraph is the most visual multi-source marketing reporting platform. Built in collaboration with digital marketing agencies
  • Matplotlib Landing page
    Landing page //
    2023-06-14
  • Whatagraph Landing page
    Landing page //
    2023-07-22

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.

Whatagraph features and specs

  • User-Friendly Interface
    Whatagraph's intuitive design makes it easy for users, even those without technical expertise, to create and understand comprehensive reports.
  • Customization
    Offers extensive customization options for reports, allowing users to tailor them to specific needs and branding requirements.
  • Integrations
    Seamlessly integrates with popular marketing tools and platforms such as Google Analytics, Facebook, and Mailchimp, providing a centralized reporting solution.
  • Automation
    Enables automated reporting, saving time and ensuring that reports are consistently delivered on schedule.
  • Collaboration
    Facilitates collaboration by allowing multiple users to access and edit reports, streamlining team workflows.
  • Visual Appeal
    Produces visually appealing, professional reports that can enhance presentations and client communications.

Possible disadvantages of Whatagraph

  • Pricing
    Whatagraph may be considered expensive for small businesses or startups due to its subscription model.
  • Learning Curve
    While relatively user-friendly, some users may experience a learning curve when first starting out with the platform.
  • Template Limitations
    Some users have reported limited flexibility in template designs, which may not suit highly specific reporting needs.
  • Data Sync Delays
    There can be occasional delays in data syncing from integrated platforms, which might affect the timeliness of reports.
  • Customer Support
    Some users have indicated that customer support can be slow to respond or not as helpful as desired.

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 Whatagraph

Overall verdict

  • Whatagraph is generally considered a good solution for marketing teams that need to consolidate and simplify their reporting processes. Its intuitive interface and robust features make it an attractive option for both small businesses and larger enterprises looking to enhance their data-driven decision-making.

Why this product is good

  • Whatagraph is a marketing reporting tool that aggregates data from multiple sources and presents it in visually appealing formats. It's highly valued for its ease of use, customization options, and the ability to automate report creation, saving marketing teams significant time. The platform supports integration with a wide range of marketing tools, which allows for comprehensive reporting across different channels and metrics.

Recommended for

  • Marketing agencies looking for a streamlined reporting solution
  • Businesses seeking to automate and customize their marketing reports
  • Teams that require integration across multiple marketing platforms
  • Professionals who value visually appealing and easy-to-understand reports

Matplotlib videos

+ Add

Learn Matplotlib in 6 minutes | Matplotlib Python Tutorial

Whatagraph videos

+ Add

Top 4 Whatagraph Features Released in 2019

More videos:

  • Review - Whatagraph Reviews - Honest thoughts after using the whatagraph tool (whatagraph review)
  • Review - whatagraph review - Everything You Need To Know About The Tool (whatagraph review 2019)

Category Popularity

0-100% (relative to Matplotlib and Whatagraph)

Matplotlib

Whatagraph

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Data Dashboard
24 24%
Data Dashboard
76% 76
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 Whatagraph

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

Whatagraph Reviews

8 Databox Alternatives: Which One Is The Best?
Customers mainly use Whatagraph for tracking campaign results from various channels. The platform provides visualizations, reports, and data insights in the manner of leading your companyโ€™s success. It offers some features that you may not find in other competitor tools such as monitoring multiple channels at once or styling reports based on your needs.
Source: hockeystack.com
25 Best Reporting Tools for 2022
Whatagraph is known as a reporting tool that allows you to compare and monitor the performance of various campaigns. It also allows you to transfer custom data from API and Google Sheets.
Source: hevodata.com

Social recommendations and mentions

Based on our record, Matplotlib seems to be a lot more popular than Whatagraph. While we know about 114 links to Matplotlib, we've tracked only 4 mentions of Whatagraph. 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 / 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

Whatagraph mentions (4)

  • Linking visibility and positions data in google data studio
    I recommend pulling this easily into whatagraph.com through drag & drop functionality. Amazing integration depth, also! Source: about 5 years ago
  • Does this tool exist?
    Try whatagraph.com. Should do the job for you. Source: about 5 years ago
  • V2.0 of Google Data Studio
    Hey everyone, Just like the title says that's what Whatagraph.com is - those of you who are looking to significantly improve your data aggregation, visualization, and reporting capabilities, I would love to invite you to our webinar next week on Tuesday at 3pm BST.https://www.linkedin.com/events/6793088092371763200/. Source: about 5 years ago
  • New data analyst tasked with major overhaul needing guidance!
    The space I am more aware of is the data integration part of the process, and my team uses hotglue (though hotglue is built for developers) to collate the data into one place, do any transformations necessary (the transformations are done in Python in hotglue), and then send it to the tool we use (we recently switched from Databox to Whatagraph). The nice thing about this for us is we can actually remain on the... Source: over 5 years ago

What are some alternatives?

When comparing Matplotlib and Whatagraph, 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.

Owler - Owler is a crowdsourced data model allowing users to follow, track, and research companies.

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

QlikSense - A business discovery platform that delivers self-service business intelligence capabilities

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

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.

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