cortlandCrimeScraper is a Python-based web scraping tool designed to gather and store detailed information about local news stories from the Cortland Standard & Cortland Voice websites. The primary purpose of this tool is to facilitate data collection for analysis and querying of local news incidents.
- Scrapes local news articles from the Cortland Standard and Cortland Voice websites.
- Extracts and stores article details such as title, author, publish date, and content.
- Populates an
incidentstable with relevant data extracted from articles. - Further refines data into a
chargestable for detailed analysis.
- Purpose: Serves as the primary data source, capturing all relevant information from each news article.
- Fields: Includes title, author, publish date, URL, and content.
- Role: Acts as a foundational table from which other, more specific data tables are populated.
- Derived From: Article table data.
- Function: Focuses on specific incidents reported in Police/Fire categorized articles, extracting key details for deeper analysis.
- Relation to Article Table: Each incident is linked to an article to maintain traceability and context.
- Derived From: Incident table data.
- Purpose: Provides a granular view of the charges associated with each incident, supporting detailed legal and statistical analyses.
- Relation to Incident Table: Each entry in the charges table corresponds to a specific incident, allowing for a clear understanding of the legal aspects associated with each case.