In the <ETL_Mini_Project_SBotica.ipynb> file you will find the following:

The Category and Sub_category DataFrames created. The two DataFrames <category.csv> and <subcategory.csv> files have been exported to the Resources folder.

The Campaign DataFrame was created. The <campaign.csv> file was exported to the Resources folder.

To create the Contacts DataFrame I chose Option 1. The <contacts.csv> file was exported to the Resources folder. You will find some cell blocks after this code where I checked SELECT statements used in Part 4 in PgAdmin4. Explained below.

I also had time to practise using regres and completed Option 2 The <contacts_option_2.csv> file was exported to the Resources folder.

The Crowdfunding Database was created using QUICK DBD. An image of the ERD used to create the schema is in the Resources folder. The file is <QuickDBD_Project1.png> The database schema is saved in Resources as <crowdfunding_db_schema.sql> A Postgres(pgAdmin4)database was created called <crowdfunding_db> Tables were created, verified with a SELECT statement and CSV files imported to each table. A select statement was run for each table to check the correct data was running.

I was also really please I was able to run an inner join SELECT statement across all 4 tables. This can be found at the bottom of the <crowdfunding_db_schema.sql>

A check of these select statement was also run after option 1 in the <ETL_Mini_Project_SBotica.ipynb> to compare data extracted with SELECT statements in PgAdmin4.

Above these blocks cells of code in <ETL_Mini_Project_SBotica.ipynb> you will find some code exploring the data.

Enjoy marking this assignment! Thank you Sandra