
Readwise
Raindrop.io
Instapaper
Obsidian.md
Matter
Hardcover
Notion
My Mind
Exploratory
Scikit-learn
Pandas
NumPy
OpenCV
Dataiku
htm.java
Figure Eight
Exploratory is recommended for business analysts, data analysts, academic researchers, and any professionals who need to perform data analysis but may not have an extensive programming background. Its intuitive design makes it a good fit for users looking to conduct in-depth data exploration without needing to write extensive code.
I imported my kindle highlights, as many others. Now I daily review some highlights (thanks to a dashboard, I am motivated). And where I didn't create highlights, as I only listened to the audiobooks, I get the highlights from others. It also allows to create beautiful quotes. It adds the book cover and matches quote and background with colours found on the book title! Really nice!
Based on our record, Readwise seems to be a lot more popular than Exploratory. While we know about 88 links to Readwise, we've tracked only 6 mentions of Exploratory. 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.
Anyway, as I reached the end of the chapter, I wanted to read my Readwise's daily recap. However, my iPhone was in other room. I didn’t want to get up; I was tired. - Source: dev.to / 3 months ago
The only highlights that Readwise retrieves semi-automatically are from the books I buy from Kindle, by going into the Readwise app and clicking a button. If I upload them to Kindle or need highlights from the Apple Books app, I have to open the book, go to my highlights, select them all, and then email them to a Readwise email address. - Source: dev.to / over 1 year ago
Readwise also has this feature. I get a daily email with a random assortment of highlights that have been pulled in from multiple sources (Reader, Notion, Kindle, etc.) The product benefit in their case is that it's kind of like Zapier, but for notes. https://readwise.io/. - Source: Hacker News / over 1 year ago
Go to readwise.io and create an account if you don't already have one. - Source: dev.to / almost 2 years ago
Sign up for a Readwise account if you haven't already readwise.io. - Source: dev.to / almost 2 years ago
I'm a happy customer of https://exploratory.io/ - it's a very user-friendly interface on top of R and I think you might find it helpful. - Source: Hacker News / about 4 years ago
If the goal here is becoming productive quickly, try https://exploratory.io/ which is a sort of WYSIWYG environment for R that will still let you code by hand if needed. No affiliation, just a happy customer for 2 years. - Source: Hacker News / over 4 years ago
Give https://exploratory.io/ a look. It's free/cheap. It's a nice easy GUI wrapper for R and just works. I stumbled across it a year ago and now use it daily. - Source: Hacker News / over 4 years ago
I'm not associated with the company, but I have used their product extensively and recommended it before. Is there a reason people do not recommend Exploratory Desktop compared to something like Tableau? It is free for public use, and can do almost anything Tableau does but faster: https://exploratory.io/. Source: over 4 years ago
I've been using https://exploratory.io/ a lot, which is r in a really nice wrapper where you can do everything point and click, by writing code by hand or a mix. - Source: Hacker News / over 4 years ago
Raindrop.io - All your articles, photos, video & content from web & apps in one place.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Instapaper - Instapaper is a simple tool to save web pages for reading later.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Obsidian.md - A second brain, for you, forever. Obsidian is a powerful knowledge base that works on top of a local folder of plain text Markdown files.
NumPy - NumPy is the fundamental package for scientific computing with Python