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Developed an ETL (Extract, Transform, Load) pipeline using Python, Pandas, and Python dictionary methods to process data for crowdfunding campaigns, ensuring accuracy and quality. Implemented SQL to establish a Postgres database in PGAdmin for storing the refined data, alongside creating an entity relationship diagram for comprehensive visuals.

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cavallon/crowdfunding_ETL

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Crowdfunding_ETL

This repository contains all necessary files for Project 2

DATA ACQUISITION:

Located in the Resources Folder:

  • contacts.xlsx
  • crowdfunding.xlsx

CODE FOR FINAL GRADING

  • ETL_Mini_Project_CAvallon_THipkins.ipynb

    • Contains code creating the category DataFrame and is exported as category.csv
    Screenshot 2024-02-01 at 9 00 52 PM
    • Contains code creating the subcategory DataFrame and is exported as subcategory.csv
Screenshot 2024-02-01 at 9 01 51 PM
* Contains code creating the campaign DataFrame and is exported as campaign.csv
Screenshot 2024-02-01 at 8 59 29 PM
* Contains code creating the contacts DataFrame and is exported as contacts.csv
Screenshot 2024-02-01 at 8 56 17 PM
  • crowdfunding_db_schema.sql

    • Has detailed instructions on how to create crowdfunding_db and schema within the new database.
    • Contains SQL code to create and view necessary tables.
    • Includes instructions on which files to import into which table, and the correct order for importing them.
  • erd_project_12_crowdfunding.png

    • The sketch an ERD of the tables by using QuickDBD
Screenshot 2024-02-01 at 9 07 53 PM

About

Developed an ETL (Extract, Transform, Load) pipeline using Python, Pandas, and Python dictionary methods to process data for crowdfunding campaigns, ensuring accuracy and quality. Implemented SQL to establish a Postgres database in PGAdmin for storing the refined data, alongside creating an entity relationship diagram for comprehensive visuals.

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