https://github.com/dmarks84/coursework_project_banks-web-scraping-sql

Project for IBM Data Engineering & Python course on ETL & Big Data -- Scraped website data and made API calls for additional data; wrangled and transformed this data and loaded into a SQL database.
https://github.com/dmarks84/coursework_project_banks-web-scraping-sql

apis beautifulsoup databases elt etl nosql numpy pandas pipelines python sql sqlite web-scraping

Last synced: 3 days ago
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Project for IBM Data Engineering & Python course on ETL & Big Data -- Scraped website data and made API calls for additional data; wrangled and transformed this data and loaded into a SQL database.

• Host: GitHub
• URL: https://github.com/dmarks84/coursework_project_banks-web-scraping-sql
• Owner: dmarks84
• License: bsd-3-clause
• Created: 2024-01-17T16:59:57.000Z (11 months ago)
• Default Branch: main
• Last Pushed: 2024-01-17T23:27:37.000Z (11 months ago)
• Last Synced: 2024-12-23T13:17:13.897Z (3 days ago)
• Topics: apis, beautifulsoup, databases, elt, etl, nosql, numpy, pandas, pipelines, python, sql, sqlite, web-scraping
• Language: Python
• Homepage:
• Size: 4.88 KB
• Stars: 2
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
## Project(Project_Banks-Web-Scraping-SQL)

### Part of the Coursera series: IBM Data Engineering & Python

    

## Summary

We scraped website data about world banks and then manipulated the data in order to load it into a SQL database, all via API calls in Jupyter Notebooks.  We had to wrangle and transform the data; we took every step in the extract, transform, load process.

## Skills (Developed & Applied)

Programming, Python, RDBMS & SQL, SQL (SQLite), Databases, Numpy, Pandas, BeautifulSoup, ETL &| ELT & Data Pipelines, Webscraping, APIs