Notivo is a private, per-person notebook for managers. Capture feedback, commitments, and 1:1 context as it happens — from web, iOS, WhatsApp, email, ChatGPT, or Claude — then get it back later, organized by person.
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Which is more popular?
Based on our record, Obsidian
seems to be a lot more popular than Matplotlib.
While we know about 1524 links to Obsidian,
we've tracked only 114 mentions of Matplotlib.
social mentions
114 vs 1,524
Data Science And Machine Learning popularity
100% vs 0%
Base details
Website, pricing, platforms and company facts side by side.
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
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.
Local-first Obsidian stores your notes locally on your device, giving you full control over your data and enhancing privacy.
Markdown Support Obsidian uses Markdown, making it easy to format text and compatible with many other text editors and tools.
Bidirectional Linking You can create bidirectional links between notes, which helps in building a knowledge graph and navigating related information more easily.
Customizability Obsidian is highly customizable with community plugins, themes, and various settings to fit different workflows.
Graph View Provides a visual graph view of your notes and their connections, aiding in understanding relationships and discovering insights.
Offline Access Since the notes are stored locally, you can access and edit them without an internet connection.
Possible disadvantages
Learning Curve Obsidian can be complex and overwhelming for beginners due to its extensive features and customizable nature.
Sync Limitations While local-first is great for privacy, it requires additional steps or third-party solutions for syncing across devices.
No True Real-time Collaboration Obsidian lacks native real-time collaboration features, making it less suitable for collaborative work compared to cloud-based solutions.
Limited Mobile Features The mobile version of Obsidian, while functional, is not as robust as the desktop application, potentially hindering productivity on the go.
Dependence on Plugins Many advanced features require the use of third-party plugins, which could lead to compatibility issues and reliance on community support.
Performance on Large Vaults Performance might degrade with a very large number of notes or complex graphs, impacting usability.
Analysis
An editorial look at what each product does well and who it suits.
MatplotlibObsidian
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.
Overall verdict
Overall, Obsidian.md is an excellent tool for users looking for a versatile and powerful note-taking application. Its unique features such as backlinking, markdown support, and robust customization options make it a favorite among knowledge management enthusiasts.
Why this product is good
Obsidian.md is considered good by many users because it is a powerful knowledge management and note-taking application that leverages Markdown for document formatting. It allows for bi-directional linking between notes, which helps in creating a network of interconnected ideas, often described as a 'second brain.' Its ability to support plugins, themes, and robust graph visualization also adds to its appeal. Additionally, it stores notes locally, ensuring privacy and data ownership, while being cross-platform compatible across Windows, macOS, and Linux.
Recommended for
Knowledge workers who need a powerful tool to organize and connect their thoughts.
Students who are looking to create a structured and visually interconnected note system.
Writers and researchers who benefit from linking related ideas and maintaining detailed notes.
Tech-savvy users or developers who appreciate the local storage and open ecosystem for plugins and customization.
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...
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...
One thing to note: Notion bills itself as an Evernote competitor for personal users. It can be—but it's too much for most people, and its offline functionality isn't the best. If you love the idea of Notion, go right...
This app is the kind of thing that, if you’re into it, will have you exploring its various ins, outs, and add-ons for days and weeks on end. Obsidian uses the Markdown format for its notes (which means they can be...
However, it's important to note that Obsidian's whiteboard functionality is not as robust as dedicated collaboration tools. While it lacks real-time basic collaboration features, Obsidian compensates with its vibrant...
Recommendations tracked on public social media and blogs since March 2021.
Matplotlib114 mentionsObsidian1524 mentions
The soul file
In February, an AI agent named MJ Rathbun submitted a pull request to matplotlib — the Python plotting library used by half the scientific computing world. Scott Shambaugh, a volunteer maintainer, rejected it. Standard code review....
- Source: dev.to
/
6 months ago
Numbers are useful, but sometimes it’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...
- Source: dev.to
/
9 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
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10 months ago
I Built SelfContext So I Could Stop Re-explaining Myself to AI
The vault is compatible with Obsidian because the files are just Markdown, YAML frontmatter, and standard relative links.
- Source: dev.to
/
2 days ago
Inline preview, usually called WYSIWYG. Obsidian's Live Preview mode hides the syntax except where the cursor is. Obsidian is a far better personal knowledge base than anything else on this page, with backlinks, a graph and years of...
- Source: dev.to
/
18 days ago
I Built a Self-Evolving Knowledge Base — Here's the Architecture
The stack is all open source: Obsidian, GBrain, Horizon, PGLite, and a couple of small Python scripts for the state machine and quality gates. None of the interesting parts are proprietary — the interesting part is the discipline.
- Source: dev.to
/
24 days ago
Joplin is a free, open source note taking and to-do application, which can handle a large number of notes organised into notebooks. The notes are searchable, tagged and modified either from the applications directly or from your own text editor.
Pandas
NumPy
Seaborn
D3.js
Plotly
GnuPlot
Jupyter
