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
New in Datalore: Automatic plots, Terminal, Pip package manager, and Community plan changes
Read this blog post to learn about how we improved the plotting workflow, integrated Terminal and Pip package manager, and adjusted the features on the Community plan.
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.
Pandas Tutorial: 10 Popular Questions for Python Data Frames
Pandas is one of the first libraries you will learn about when you start working with Python for data analysis and data science. In this tutorial, we will answer 10 of the most frequently asked questions people have when working with pandas.
10 Tips for Working With Data in Datalore
Greetings from the Datalore team! In this blog post we’ll show you 10 tricks you can use to help you work more productively with data files in Datalore. Try Datalore! Before we start In Datalore, files are persistently attached to notebooks. After you create a notebook and upload some data, you will have access to the data even after you restart the kernel or close and reopen Datalore. Tip
We Downloaded 10,000,000 Jupyter Notebooks From Github – This Is What We Learned
Here’s how we used the hundreds of thousands of publicly accessible repos on GitHub to learn more about the current state of data science.
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.
Datalore Pro: Online Jupyter Notebooks with GPU Access, Hosted by JetBrains
We have some really exciting news for you – we’ve introduced a new Datalore plan, called Datalore Professional. This new plan comes with increased processing power and added storage for even faster calculation of bigger datasets.