Exploring Income Patterns with Python Pandas, Matplotlib, and Seaborn

Matplotlib vs Plotly: Which Python Chart Tool Should You Choose?

From Static Plots to Interactive Data Exploration The post Matplotlib vs Plotly: Which Python Chart Tool Should You Choose? appeared first on Towards Data Science .

Crowd-Sourced Geographies of Income: Using Google Maps Points of Interest as High-Frequency Proxies for Sub-Municipal Income Estimation in Sao Paulo, Brazil

arXiv:2608. 07871v1 Announce Type: cross Abstract: Accurate, up-to-date income data at the sub-municipal scale is essential for social policy in middle-income countries, yet in Brazil it depends on a costly decennial census whose intercensal gap recently exceeded a decade.

Introducing the Data Measurements Tool: an Interactive Tool for Looking at Datasets

The Problem with pandas Isn’t Performance. It’s Cognitive Overhead.

Faster dataframe engines are nice, but they don't reduce the amount of syntax an analyst has to hold in their head. The post The Problem with pandas Isn’t Performance.

Measuring Poverty and Inequality with Reduced Data: A Machine Learning Approach Using Nigerian Household Data

arXiv:2606. 07614v1 Announce Type: new Abstract: Reliable measurement of income and consumption is essential for monitoring poverty and inequality in low- and middle-income countries, yet full household surveys are costly and difficult to implement regularly.

PandasCorpus: A Resource of Real-World Pandas Workflows and Usage Patterns

arXiv:2608. 14742v1 Announce Type: cross Abstract: Pandas has emerged as the de facto library for data processing and machine learning, widely used for tasks, such as data loading, transformation, and analysis.

The Most Beautiful Statistic: The History and the Science of the Humble Mean

The mean keeps making its usefulness felt in all sorts of situations, often in truly non-obvious ways The post The Most Beautiful Statistic: The History and the Science of the Humble Mean appeared first on Towards Data Science .

Leveraging ChatGPT's Multimodal Vision Capabilities to Rank Satellite Images by Poverty Level: Advancing Tools for Social Science Research

arXiv:2501. 14546v2 Announce Type: replace-cross Abstract: This paper investigates the novel application of Large Language Models (LLMs) with vision capabilities to analyze satellite imagery for village-level poverty prediction.

Explainable Machine Learning for Broadband Adoption Disparities: Tract-Level Prediction and SHAP-Based Factor Profiling

arXiv:2608.29110v1 Announce Type: new Abstract: The United States has allocated approximately $65 billion through the Infrastructure Investment and Jobs Act for broadband expansion, yet evidence-base...

Should AI Developers Make the Switch from Polars to Pandas?

Not all Python data libraries are created equal! The post Should AI Developers Make the Switch from Polars to Pandas?

Global Ease of Living Index: a machine learning framework for longitudinal analysis of major economies

arXiv:2502. 06866v3 Announce Type: replace-cross Abstract: The drastic changes in the global economy, geopolitical conditions, and disruptions such as the COVID-19 pandemic have impacted the cost of living and quality of life.

TSExplorer: An interactive data annotation and exploration tool for time-series data

arXiv:2608.30514v1 Announce Type: cross Abstract: We present TSExplorer, a cross-platform tool for interactive annotation and exploration of time-series data. The tool enables users to inspect high-d...