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…
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,…
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…
The Future of DataFrames: Intro to Polars for High-Performance Python (2026 Guide)
For years, Pandas has been the undisputed king of DataFrames. But as datasets have grown into 10s or 100s of gigabytes, a new tool has…
Machine Learning Project: K-Means Clustering for Customer Segmentation
We’ve done Regression (predicting prices) and Classification (predicting species). Both are Supervised learning (they need labeled answers). Now let’s dive into K-Means Clustering Python, a…
Machine Learning Project: Your First Classifier (Iris Dataset)
In our House Price project, we did Regression (predicting a number). Today, we’ll do Classification (predicting a category). We’re going to explore a Machine Learning…
Machine Learning Project: Predicting House Prices with Scikit-Learn
In our Scikit-Learn intro, we used tiny fake data. Now we’ll use Python to predict house prices and build a real model. We’ll use a…
