Based on our record, Google BigQuery should be more popular than iPython. It has been mentiond 35 times since March 2021. 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.
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
Third, if possible use a command line interpreter to test things out. I recommend ipython for this purpose. You can use your browser's developer console this way if you are learning Javascript. Source: about 1 year ago
IJulia is an interactive notebook environment powered by the Julia programming language. Its backend is integrated with that of the Jupyter environment. The interface is web-based, similar to the iPython notebook. It is open-source and cross-platform. - Source: dev.to / about 1 year ago
Also, take a look at installing iPthon to give you a much richer shell environment. This underpins Jupyter Notebooks, so is well known, proven and trusted. Source: about 1 year ago
I know this isn't quite what you're asking for, but IPython (https://ipython.org/) is very capable as a Python + bash (or other) shell, as it allows you to easily integrate the system shell into the interactive environment. Although they now recommend Xonsh (https://xon.sh/) for such purposes. Source: about 1 year ago
Either an online python interpreter like replit.com or simply any python interpreter, like `ipython`, or the default, barebones one that ships with the python installation pacakge. Source: over 1 year ago
Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.What is Apache Spark?
Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.
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.
PyCharm - Python & Django IDE with intelligent code completion, on-the-fly error checking, quick-fixes, and much more...
IDLE - Default IDE which come installed with the Python programming language.
Presto DB - Distributed SQL Query Engine for Big Data (by Facebook)