Obsidian.md
Notion
Logseq
Joplin
Roam Research
Evernote
Standard Notes
TiddlyWiki
Matplotlib
Pandas
NumPy
Seaborn
D3.js
Plotly
GnuPlot
Jupyter
Obsidian.md MatplotlibPerhaps you know someone who swears by Obsidian, it may seem like a cult of overly devoted people for how passionate they are, but it's not without reason
I've been using Obsidian for over 3 years, at a point in my life when I felt I had to handle too much information and I felt like grasping water not being able to remember everything I wanted, language learning, programming, accounting, university, daily tasks. A friend recommended it to me next to Notion (of which he is a passionate cultist priest) and I reluctantly picked it and fell in love almost immediately.
Obsidian seems very simple, like a notepad with folder interface, similar to Sublime Text, but the ability to link files together in a Wiki style allows you to organize ideas in any way you want, one file may lead to a dozen or more ideas that are related
If you want to do something specific, Obsidian has a plethora of community created plugins that expand the functionality, in my case, I use obsidian to organize my classes both as a teacher and as a student, using local databases, calendars, dictionaries, slides, vector graphic drawings, excel-like tables, Anki connection, podcasts, and more
I've been using Obsidian for more than a year. It's been great. I think it offer a great balance of control, flexibility and extensibility. What is more, you own your own data, that's been a must-have feature for me. I just can't imagine putting all my knowledge into something that I don't have control over.
I think two of the most popular alternatives that people consider are Logseq and Roam Research. Although Logseq is a bit different, it's considered compatible with Obsidian. Supposedly, you can use them with a shared database (files. Both use simple text files for storage). I tried that once, a few months ago. It worked, yet it messed up a bit my Obsidian files ยฏ_(ใ)_/ยฏ.
Based on our record, Obsidian.md seems to be a lot more popular than Matplotlib. While we know about 1520 links to Obsidian.md, we've tracked only 114 mentions of Matplotlib. 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.
Install Obsidian: Download the client from obsidian.md and create a local Vault โ just a local folder. - Source: dev.to / 7 days ago
Obsidian (https://obsidian.md/) Honestly its not huge and most are probably obvious, but those are what I immediately install on my machines. - Source: Hacker News / 11 days ago
A place to store the feedback - I keep mine in an Obsidian vault, organised by type (interviewing, facilitation) and date. This makes trend tracking trivial. - Source: dev.to / 26 days ago
Option 2: Dedicated markdown app.Typora, Obsidian, or similar. Better editing experience, but now you're context-switching between your code editor and your docs editor. Copy-pasting paths, losing mental context, duplicating effort. - Source: dev.to / about 1 month ago
Obsidian is the storage. A desktop app that opens any folder of markdown files and adds links, search, and a graph view on top. Your files stay on your disk. No cloud unless you turn it on, no proprietary database, no export step. If you want your notes back, you already have them. - Source: dev.to / about 1 month ago
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
Numbers are useful, but sometimes itโs 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
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
NetworkX and Matplotlib were used to visualize the graph structure of the agent. - Source: dev.to / 9 months ago
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, Aโฆ. - Source: dev.to / 10 months ago
Notion - All-in-one workspace. One tool for your whole team. Write, plan, and get organized.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Logseq - Logseq is a local-first, non-linear, outliner notebook for organizing and sharing your personal knowledge base.
NumPy - NumPy is the fundamental package for scientific computing with Python
Joplin - 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.
Seaborn - Seaborn is a Python data visualization library that uses Matplotlib to make statistical graphics.