Based on our record, Jupyter seems to be a lot more popular than Exploratory. While we know about 205 links to Jupyter, 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.
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 / over 1 year 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 / almost 2 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 / about 2 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: about 2 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 / about 2 years ago
JupyterLab: JupyterLab is an interactive development environment that allows you to create and share documents containing live code, equations, visualizations, and narrative text. It's particularly well-suited for data science and research-oriented projects. - Source: dev.to / 6 days ago
Jupyter Lab web-based interactive development environment. - Source: dev.to / 17 days ago
Choosing IDE: Selecting a suitable Integrated Development Environment (IDE) is crucial for efficient coding. Consider popular options such as PyCharm, Visual Studio Code, or Jupyter Notebook. Install your preferred IDE and ensure it's configured to work with Python. - Source: dev.to / 12 days ago
Jupyter Notebooks is very popular among data people specially Python users. So, I tried to find a way to run the Groovy kernel inside a Jupyter Notebook, and to my surprise, I found a way, BeakerX! - Source: dev.to / about 2 months ago
Note. Nowadays, there are many flavors of notebooks (Jupyter, VSCode, Databricks, etc.), but they’re all built on top of IPython. Therefore, the Magics developed should be reusable across environments. - Source: dev.to / about 2 months ago
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Looker - Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.What is Apache Spark?
NumPy - NumPy is the fundamental package for scientific computing with Python
Google BigQuery - A fully managed data warehouse for large-scale data analytics.