For this mini-project, I created an ETL pipeline using Python, Pandas, and regular expressions to extract and transform the data provided on crowdfunding campaigns. I created 4 CSV tables (Category, Subcategory, Campaign, and Contacts) to create an ERD schema. The CSV's were then loaded into a Postgres database to display the data.
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Transformed crowdfunding data into 4 usable dataframes and then loaded the data into a Postgres SQL database
MM24J/Crowdfunding-Analysis-Using-ETL
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Transformed crowdfunding data into 4 usable dataframes and then loaded the data into a Postgres SQL database
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