New in Datalore: Webinar, Parametrized SQL queries and More
In this blog post we’ll share a few updates to database support and SQL cells, announce the first Datalore webinar, and tell you how Datalore has become even more collaborative.
Introducing SQL Cells and Database Connections to Datalore Notebooks!
What are the most common ways to query SQL databases from a Python notebook? They might include using Python SQL libraries such as PySQL or SQLAlchemy... We can now suggest a more effective method: combine native SQL cells and Python code in Datalore notebooks.
New in Datalore: R and Scala Notebooks, Google Cloud Bucket Mounting and More
Greetings from the Datalore team! Exciting news for those of you who love more than just Python: Datalore now also supports R and Scala notebooks! Read on to learn more about the updates. R and Scala support Although Python is the most popular language in data science, R and Scala also do a great job for data science tasks and have a rich user community. That’s why we added support for Scala and R kernels in Datalore, so now you can: Create R 0.4.11 and Scala 2.12 notebooksGet smart code completion for R and Scala codeInvite your team members to collaborate on code in real-timePub
New in Datalore: Chart Cells, Spelling and Grammar Checking, Initialization Scripts, and More
Greetings from the Datalore team! Does the #Tesla stock price depend on Elon Musk’s mood? In this newsletter, we’ll share a new tutorial for sentiment analysis and talk about the new features that can improve your daily workflow in Datalore. Chart cells Could you imagine that working with visualizations in Python would be as easy as it is in spreadsheets? Last month we took a step further towards this idea and released a new type of cell – Chart cells. Chart cells allow you to create visualizations for any data frames you already have in your notebook with just a few clicks.
Revamped Reactive Mode and How It Makes Your Notebooks Reproducible
Greetings from the Datalore team! Jupyter notebooks can get messy. Perhaps you have tried different things in one notebook, or maybe you have chunks of outdated code and variable declarations all over the place. This isn’t necessarily a sign that something is wrong. Rather, the tool was designed to allow you to work this way. For the last 3 years, our Datalore team has been experimenting with ways to address the mess. Today we are happy to introduce the new Reactive mode, which helps you make sure your notebooks are always tidy and up-to-date 🚀 What is the new Reactive mode?
New in Datalore: Kernel Changes, New Automatic plots, Tutorials, and More
We have been busy this month laying the foundations for future features. This work will enable us to take some big steps with Datalore over the coming year.
🚀 New in Datalore: Interactive Controls, Hidden Cells, Collapsing Inputs and Outputs, and Bug Fixes
We believe that Jypyter notebooks could become a great presentation and reporting tool. Read on to learn how Datalore makes notebooks more friendly for non-tech people.
New in Datalore: Cell Redesign, PDF and Python File Export, Embedly Support, Twitter Challenge, and More
For the last month, we’ve been working on implementing a frequent user request to export notebooks into different types of files and to share code on other platforms. You might have also already noticed that the look of the editor has changed a bit. Read on to learn more about the recent updates in Datalore 👇🏻
New in Datalore: Publishing Update, Documentation, Pandas Tutorial and More
In January and February we introduced a lot of updates to Datalore: we integrated the UI for publishing notebooks, released the first version of Datalore’s documentation, updated the landing page, and introduced improvements for working with files from Python code.
Datalore Improvements in 2020: Datalore Professional, a Better Coding and UI Experience, and More
Last year presented an unexpected challenge for the world, one we all had to rise to. In 2020, we managed to launch Datalore Professional and deliver lots of great new features for our users. Here we’ve assembled a description of some of the most notable ones. Datalore Professional In November we launched Datalore Professional. It was designed for solving more complex tasks with larger datasets that need more powerful computation hardware. Here is a comparison table for Datalore Community and Datalore Professional. Take a closer look, and decide which plan best fits your needs! Community
New in Datalore: S3 Buckets Support, Workspace Files, Two Inspiring Research Posts and Other Updates
Though this is our final blog post of 2020, we have a bunch of new Datalore updates we’d like to share, including the results of two major studies we recently conducted.
New in Datalore: Pro Plan Launch and Future Changes, Anaconda Collaboration, Dark Theme, Soft-wrap and Advanced Visualization Tutorial
Greetings from the Datalore team! This November we released a major update: the Professional Plan is now available for Datalore users 🚀 Read on to learn more about the future of Datalore Pro.