Software Alternatives, Accelerators & Startups
Register | Login

66Analytics VS Matplotlib

Compare 66Analytics VS Matplotlib and see what are their differences

PrivacyNotes
Zero-knowledge encrypted notes, tasks, journals, files, and passwords in one app. Your keys never leave your device. One-time price, no subscription. Hosted in Switzerland. featured
Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.
Contents:
  1. ยป Base Details
  2. ยป Videos
  3. ยป Reviews
  4. ยป Alternatives

66Analytics logo 66Analytics

Self-hosted analytics, heatmaps & session recordings.

Matplotlib logo Matplotlib

matplotlib is a python 2D plotting library which produces publication quality figures in a variety...
  • 66Analytics Landing page
    Landing page //
    2023-08-26
  • Matplotlib Landing page
    Landing page //
    2023-06-14

66Analytics features and specs

  • Comprehensive Analytics
    66Analytics offers in-depth website analytics that can help users understand their audience, traffic sources, and user behavior in detail.
  • User-Friendly Interface
    The platform features a user-friendly and clean interface, making it easy for both beginners and experienced users to navigate and utilize the tool effectively.
  • Self-Hosted Solution
    66Analytics is a self-hosted analytics platform, giving users complete control over their data and privacy without relying on third-party services.
  • White Labeling
    The ability to customize the software with your own branding can be a major advantage for businesses that want to maintain a consistent brand image.
  • Custom Events and Goals
    Users can set up custom events and goals, allowing for tailored tracking that meets specific business needs and objectives.
  • Privacy-Focused
    Since itโ€™s self-hosted, 66Analytics offers enhanced privacy control, which can be crucial for GDPR compliance and other privacy regulations.
  • API Access
    The availability of an API allows users to expand the functionality and integrate 66Analytics with other tools and platforms.

Possible disadvantages of 66Analytics

  • Setup Complexity
    Setting up a self-hosted analytics platform requires technical knowledge and resources, which might be a barrier for non-technical users.
  • No Real-Time Data
    66Analytics does not provide real-time analytics, which can be a limitation for users who need immediate insights and data.
  • Limited Integrations
    Compared to other analytics platforms, 66Analytics has fewer direct integrations with third-party services and tools.
  • Cost of Hosting
    Users need to factor in the additional costs of self-hosting, including server, maintenance, and related expenses.
  • Initial Cost
    There is an upfront cost to purchase the software, which could be a concern for small businesses or startups with limited budgets.
  • Learning Curve
    Despite its user-friendly interface, there is still a learning curve involved in understanding and making the most out of the features provided.

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 66Analytics

Overall verdict

  • 66Analytics is generally considered a good web analytics platform, especially for those seeking a privacy-focused, self-hosted solution.

Why this product is good

  • It offers real-time analytics, user tracking, and event tracking features similar to larger platforms without the data privacy concerns.
  • The platform is easy to install and use, providing insightful reports that help in understanding website traffic and user behavior.
  • It offers customization options and can be installed on your own server, ensuring full control over your data.
  • The one-time purchase model is cost-effective for businesses that prefer not to deal with recurring subscription fees.

Recommended for

  • Small to medium-sized businesses looking for an affordable analytics solution.
  • Privacy-conscious organizations preferring to keep their data in-house.
  • Developers and tech-savvy users who can manage self-hosted applications.

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.

66Analytics videos

No 66Analytics videos yet. You could help us improve this page by suggesting one.

Add video

Matplotlib videos

+ Add

Learn Matplotlib in 6 minutes | Matplotlib Python Tutorial

Category Popularity

0-100% (relative to 66Analytics and Matplotlib)

66Analytics

Matplotlib

Analytics
100 100%
Analytics
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Web Analytics
100 100%
Web Analytics
0% 0
Technical Computing
0 0%
Technical Computing
100% 100

User comments

Share your experience with using 66Analytics and Matplotlib. For example, how are they different and which one is better?
Log in or Post with

Reviews

These are some of the external sources and on-site user reviews we've used to compare 66Analytics and Matplotlib

66Analytics Reviews

We have no reviews of 66Analytics yet.
Be the first one to post

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 66Analytics. While we know about 114 links to Matplotlib, we've tracked only 5 mentions of 66Analytics. 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.

66Analytics mentions (5)

  • 10 of the Best Web Analytics Tools for React Websites
    66analytics offers features such as real-time analytics, conversion tracking, heat maps, session recordings, and data ownership. This data visualization tool gives you a complete picture of your productโ€”everything that marketing, UX, or product management teams ask for. - Source: dev.to / over 1 year ago
  • Built a Google Analytics alternative with visitor journeys, heatmaps and replays
    Looks like this is a fork of https://66analytics.com/? One of Altumcodes products? - Source: Hacker News / over 1 year ago
  • What is a good, lightweight, free alternative to Google Analytics?
    Last year I stumbled upon https://66analytics.com/ and liked it quite a lot. It is very light but covers quite a lot of stuff that I wanted to have. Itโ€™s a one time payment but only around $60 I think and does not have any limitations after that. I liked the one time payment idea and that I could just run it on a shared Hoster that I had already around. Source: over 4 years ago
  • Show HN: PrivateAnalytix โ€“ Private Google Analytics and MS Clarity Alternative
    This is just another managed version of https://66analytics.com/ I like that you state GDPR and other compliance but I am 100% sure itโ€˜s not (just because 66analytics is claiming that, doesnโ€™t mean itโ€™s right. Have you checked anything back with a lawyer? - Source: Hacker News / almost 5 years ago
  • Made this tool, what do you think?
    For anyone interested, I think this is just a hosted version of https://66analytics.com/. Source: about 5 years ago

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

What are some alternatives?

When comparing 66Analytics and Matplotlib, you can also consider the following products

Fathom Analytics - Simple, trustworthy website analytics (finally)

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

Simple Analytics - The privacy-first Google Analytics alternative located in Europe.

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

Plausible.io - Plausible Analytics is a simple, open-source, lightweight (< 1 KB) and privacy-friendly web analytics alternative to Google Analytics. Made and hosted in the EU, powered by European-owned cloud infrastructure ๐Ÿ‡ช๐Ÿ‡บ

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

Loading...