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Integrating DuckDB & Python: An Analytics Guide

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By Josep Ferrer , KDnuggets AI Content Specialist on June 10, 2025 in Python Image by Author DuckDB is a fast, in-process analytical database designed for modern data analysis. DuckDB is a free, open-source, in-process OLAP database built for fast, local analytics. And this leads us to the following natural question.

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7 DuckDB SQL Queries That Save You Hours of Pandas Work

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By Nate Rosidi , KDnuggets Market Trends & SQL Content Specialist on July 7, 2025 in SQL Image by Author | Canva Pandas library has one of the fastest-growing communities. DuckDB is an SQL database that you can run right in your notebook. Unlike other SQL databases, you don’t need to configure the server.

SQL 265
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10 GitHub Repositories for Mastering Agents and MCPs

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By subscribing you accept KDnuggets Privacy Policy Leave this field empty if youre human: Get the FREE ebook The Great Big Natural Language Processing Primer and The Complete Collection of Data Science Cheat Sheets along with the leading newsletter on Data Science, Machine Learning, AI & Analytics straight to your inbox.

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8 Ways to Scale your Data Science Workloads

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It’s a great, no-cost way to start learning and experimenting with large-scale analytics. As a data scientist, you can access your BigQuery Sandbox from a Colab notebook. With just a few lines of authentication code, you can run SQL queries right from a notebook and pull the results into a Python DataFrame for analysis.

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Building End-to-End Data Pipelines: From Data Ingestion to Analysis

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Streaming: Use tools like Kafka or event-driven APIs to ingest data continuously. Its key goals are to ensure data quality, consistency, and usability and align data with analytical models or reporting needs. Data Storage Next, choose how and where to store your processed data for analysis and reporting.

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AI Agents in Analytics Workflows: Too Early or Already Behind?

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Blog Top Posts About Topics AI Career Advice Computer Vision Data Engineering Data Science Language Models Machine Learning MLOps NLP Programming Python SQL Datasets Events Resources Cheat Sheets Recommendations Tech Briefs Advertise Join Newsletter AI Agents in Analytics Workflows: Too Early or Already Behind?

Analytics 156
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Build ETL Pipelines for Data Science Workflows in About 30 Lines of Python

KDnuggets

Here, were loading our clean data into a proper SQLite database. def load_data_to_sqlite(df, db_name=ecommerce_data.db, table_name=transactions): print(f"Loading data to SQLite database {db_name}.") conn = sqlite3.connect(db_name)

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