{
  "id": 10803250,
  "title": "How to use Pandas to analyze 100,000 rows in seconds",
  "url": "https://urgent.news/2026/09/29/como-usar-pandas-para-analizar-100000-filas-en-segundos",
  "topic": "tech",
  "section": "Tech",
  "published": "2026-09-29T23:00:16.000Z",
  "source": {
    "name": "Dev.to",
    "slug": "dev-to",
    "url": "https://dev.to/luis_carias_526fe58acbbb/como-usar-pandas-para-analizar-100000-filas-en-segundos-38fd"
  },
  "original_language": "es",
  "account": "The article discusses how to efficiently process large volumes of data using Pandas, a popular Python library for data manipulation and analysis. It highlights the importance of mastering techniques such as data loading, filtering, aggregation, and optimization to take full advantage of Pandas' capabilities. The article provides tips on how to configure the environment, load data efficiently, and apply optimizations to analyze 100,000 rows of data quickly. It also explains how Pandas combines the flexibility of a high-level programming language with the performance of vectorized operations implemented in low-level languages.",
  "summary": "Pandas es la biblioteca de Python más utilizada para manipulación y análisis de datos, y ofrece herramientas poderosas que permiten trabajar con datasets de cientos de miles de registros en tiempo récord. La clave para una eficiente análisis radica en dominar las técnicas correctas de carga, filtrado, agregación y optimización que aprovechan al máximo el motor subyacente de Pandas, construido sobre NumPy y escrito en C. Para analizar 100000 filas en segundos, es crucial configurar el entorno correctamente y cargar los datos de forma inteligente, aprovechando al máximo las funcionalidades de Pandas que operan de manera vectorizada y minimizan el uso de memoria.",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}