Based on our record, Google BigQuery seems to be a lot more popular than Hydrogen of nteract. While we know about 35 links to Google BigQuery, we've tracked only 3 mentions of Hydrogen of nteract. 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.
Hydrogen [https://atom.io/packages/hydrogen] running on Atom is the cleanest multi-lingual data science IDE in existence and has been my go-to for years. Haven't found a drop-in replacement elsewhere [vscode's language support is scattered: native python integration, different for R, Julia etc]. Anyone on HN have recs [besides vim slime or send-to-terminal options in other editors, which work but are clunky] ? - Source: Hacker News / almost 2 years ago
I can share two of my vim-user solutions with you. First one is a Atom based and is a bit more convinient if you have to do some plotting. I have vim-mode-plus plugin for vim-like navigation in the code, atom ex-mode plugin for ex commands within atom and a top of that I use Hydrogen for in place code execution. Source: about 3 years ago
Of it still doesn't work you could try to install the package hydrogen which works with an iPython kerbel like the jupiter notebook (hydrogen package). Source: about 3 years ago
Using the Galaxy UI, knowledge workers can systematically review the best results from all configured services including Apache Solr, ChatGPT, Elastic, OpenSearch, PostgreSQL, Google BigQuery, plus generic HTTP/GET/POST with configurations for premium services like Google's Programmable Search Engine, Miro and Northern Light Research. - Source: dev.to / 8 months ago
Data Transformations: This phase involves modifying and integrating tables to generate new tables optimized for analytical use. Consider this example: you want to understand the purchasing behavior of customers aged between 20-30 in your online shop. This means you'll need to join product, customer, and transaction data to create a unified table for analytics. These data preparation tasks (e.g., joining... - Source: dev.to / 8 months ago
Introduction In today's data-driven world, transforming raw data into valuable insights is crucial. This process, however, often involves complex tasks that demand efficiency, scalability, and reliability. Enter dbt Cloud—a powerful tool that simplifies data transformations on Google BigQuery. In this article, we'll take you through a step-by-step guide on how to run BigQuery transformations using dbt Cloud.... - Source: dev.to / 9 months ago
You'll want to evaluate what BigQuery has to offer and see if it makes sense for you to move over. Source: 10 months ago
Watch the introductory videos on BigQuery on the Google Cloud Platform website (https://cloud.google.com/bigquery). Source: 10 months ago
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