Handling Missing Data in Polars (null, fill_null, drop_nulls)
Just like Pandas has NaN, Polars has null to represent missing or empty data. Before you can analyze a dataset, you must have a strategy…
Master Polars: A Guide to groupby and Aggregations
The most common data analysis task is “Split-Apply-Combine.” When using Polars, the groupby operation is essential for this task. In Polars, this is done with…
Joining DataFrames in Polars: The Blazing Fast join() Method
In Pandas, you use pd.merge() to combine datasets. In Polars, you use the join() method, which is one of the fastest in any library. If…
PyScript and APIs: How to fetch Data from the Web
A PyScript app is great, but it’s isolated. To build a real dashboard (like a weather app or a crypto tracker), you need to get…
Full-Stack Python: A PyScript Dashboard with Hugging Face & Polars
This is the future. Our dashboard will showcase how you can combine PyScript, Hugging Face, and Polars to create advanced data apps. We are going…
Master Polars: A Guide to the Expression API (select, filter, with_columns)
In our Polars vs. Pandas article, we showed that Polars is faster. The reason it’s faster is its Expression API. In this article, we’ll take…
PyScript for Data Science: How to Use Pandas & Matplotlib in HTML
You’ve learned how PyScript can run Python in a browser and how to interact with the page. Now, let’s do something powerful. In this article,…
PyScript in Action: How to Interact with HTML and the DOM
In our Intro to PyScript, we showed how to run Python in a browser. But how do you make it interactive? If you want to…
Polars vs. Pandas: A 2026 Guide to Syntax and Performance
You’ve used Pandas. You’ve read our Intro to Polars. Now, let’s answer the big question: “Why should I switch, and how hard is it?” This…
Python in the Browser: What is PyScript and WebAssembly? (2026 Guide)
This Python PyScript Guide aims to help you understand the latest developments. For 20 years the rule was simple: WebAssembly (WASM) changed everything. It’s a…
