On the other hand, frameworks like React and Vue are taking over and new trends seem to be in their favor. This means th

In this article, we looked at a GUI-based tool for analyzing pandas dataframes. This tool has a number of interesting features like filtering, sorting, visualizing, and even aggregating, which we saw in detail with an example dataset. Since PandasGUI is under active development, we might see some more features in the coming days. Such libraries can be a boon for people who are not very comfortable with coding or are looking for a low code environment. Whatever the ultimate goal is, it is always good to know about another open-source tool to add to our data science toolkit.

Sometimes, there is a need to reshape the data to get more distinct insights. PandasGUI provides two functions — pivot and melts to achieve the same. Let’s see how to pivot the data via this tool.

According to the documentation, Svelte is a component framework — like React or Vue — but with an important difference. The difference is Svelte runs at build time, converting your code to highly efficient JavaScript. So you can get the benefits of the component framework without the performance penalty.

Last week, battery scientists and clean energy researchers Nicholas Yiu, Crystal Jain, and Melissa Zhang chronicled the recent history of fraud in battery commercialization, “ranging from misrepresentation to investors to various forms of sugarcoating promises of their new technologies,” the co-authors wrote on Medium. After a decade of low simmering investments, Wall Street and Silicon Valley are suddenly pouring billions of dollars into the invention of a superbattery for a mass-market electric vehicle industry. But if the often-sordid, 140-year history of automotive batteries is any guide, some of the unicorns that have emerged will turn out to be exaggerations and failures, with the very real chance of an outright fraud, or two.

If you have directly imported a dataframe onto the PandasGUI interface, you can access the same in the familiar juptyer notebook also, with just a few lines of code. From there, you can carry the data analysis process in the notebook itself, if you wish.

The new approach will be based on a SvelteKit. Its goal is to focus on the developer experience, with fast builds, hot module reloading, error overlays, and serverless support. If Svelte can add a seamless experience and out-of-the-box SSR support, it may be a game-changer.

In this article, we looked at a GUI-based tool for analyzing pandas dataframes. This tool has a number of interesting features like filtering, sorting, visualizing, and even aggregating, which we saw in detail with an example dataset. Since PandasGUI is under active development, we might see some more features in the coming days. Such libraries can be a boon for people who are not very comfortable with coding or are looking for a low code environment. Whatever the ultimate goal is, it is always good to know about another open-source tool to add to our data science toolkit.

Let’s now look at the various capabilities of the PandasGUI library with an example. PandasGUI comes with some example datasets already. So we’ll use the Titanic dataset, which comes packaged with the library. Titanic is a fairly known ‘Hello World’ dataset in machine learning, where the task is to create a model that predicts which passengers survived the Titanic shipwreck.

This has been a tough year for working parents. Many people are attempting to do their jobs while overseeing children’s virtual schooling, a situation that basically requires feeling fragmented. I get it — I have five children of my own, and it always seems like there’s just not enough time to put in long hours at work and deal with my intense personal responsibilities. A recent McKinsey