Pandas Isn’t Going Anywhere: Why It’s Still My Go-To for Data Wrangling

Learn how to use Pandas GroupBy to summarize, compare, and analyze grouped data with simple, practical examples.

pandas remains the default choice for notebooks, exploratory analysis, visualization, and machine learning workflows. Polars focus on fast, memory-efficient DataFrame processing, while DuckDB brings a SQL-first approach for querying local files and embedded analytics. Each tool fits a different kind of local data workflow. In this article, we compare pandas, Polars, and DuckDB across performance, […] The post Pandas vs Polars vs DuckDB: Which Library Should You Choose? appeared first on Analytics Vidhya.

A beginner's tutorial on exploratory data analysis using Pandas, Matplolib, and Seaborn The post Exploring Patterns of Survival from the Titanic Dataset appeared first on Towards Data Science.

In this article, we explore three real data problems using real questions where Polars outpaces Pandas on every metric.

From 61 seconds to 0.20 seconds — and the mental model shift I didn't expect The post I Rewrote a Real Data Workflow in Polars. Pandas Didn’t Stand a Chance. appeared first on Towards Data Science.

Most slow Pandas code "works", until it doesn't. Learn how to spot hidden bottlenecks, avoid costly row-wise operations, and know when Pandas is no longer enough. The post I Reduced My Pandas Runtime by 95% — Here’s What I Was Doing Wrong appeared first on Towards Data Science.

Learn method chaining, pipe(), efficient joins, optimized groupby operations, and vectorized logic to write faster and cleaner pandas code

In this tutorial, we build a comprehensive, hands-on understanding of DuckDB-Python by working through its features directly in code on Colab. We start with the fundamentals of connection management and data generation, then move into real analytical workflows, including querying Pandas, Polars, and Arrow objects without manual loading, transforming results across multiple formats, and writing […] The post An Implementation Guide to Building a DuckDB-Python Analytics Pipeline with SQL, DataFrames, Parquet, UDFs, and Performance Profiling appeared first on MarkTechPost.