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Merge pull request #117 from c0d33ngr/duckdb-in-daytona
Building a DuckDB Playground with Daytona
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title: "DuckDB" | ||
description: "An open-source columnar relational database" | ||
date: 2024-09-22 | ||
author: "Jeffrey Whewhetu" | ||
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# DuckDB | ||
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## Definition | ||
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DuckDB is an open-source, columnar relational database designed for analytical query performance and ease of use, offering an SQL interface and support for various data types. | ||
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## Context and Usage | ||
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DuckDB is typically used in data analysis, data science, and business intelligence applications, where fast querying and aggregation are critical. Its columnar storage and SQL interface make it an ideal choice for handling complex data types. |
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title: "Matplotlib" | ||
description: "A Python data visualization library" | ||
date: 2024-09-22 | ||
author: "Jeffrey Whewhetu" | ||
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# Matplotlib | ||
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## Definition | ||
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Matplotlib is a popular Python data visualization library for creating static, animated, and interactive plots, providing a comprehensive set of tools for creating high-quality 2D and 3D plots. | ||
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## Context and Usage | ||
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Matplotlib is typically used in data exploration, scientific publishing, and web applications, where data visualization is essential. Its customization options, output formats, and integration with NumPy and Pandas make it a versatile tool. |
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definitions/20240922_definition_online_analytical_processing_olap.md
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title: "OLAP (Online Analytical Processing)" | ||
description: "A computing method that enables business users to quickly answer to multi-dimentional analytical queries" | ||
date: 2024-09-22 | ||
author: "Jeffrey Whewhetu" | ||
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# OLAP (Online Analytical Processing) | ||
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## Definition | ||
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OLAP (Online Analytical Processing) is a data analysis technology that enables fast and efficient querying and analysis of data, allowing users to easily and quickly analyze data from multiple dimensions. | ||
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It is well suited for complex queries that draws from multiple data sets. | ||
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## Context and Usage | ||
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OLAP is typically used in business intelligence, financial analysis, and data science applications, where complex data analysis and reporting are required. It provides a multidimensional view of data, enabling users to analyze trends, patterns, and relationships. |
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