https://github.com/leftcoastnerdgirl/extract_transform_load

This mini project introduces data cleaning through ETL
https://github.com/leftcoastnerdgirl/extract_transform_load

data-cleaning etl extract-transform-load json merge-sort numpy pandas-dataframe pandas-python

Last synced: 10 days ago
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This mini project introduces data cleaning through ETL

• Host: GitHub
• URL: https://github.com/leftcoastnerdgirl/extract_transform_load
• Owner: LeftCoastNerdGirl
• Created: 2024-01-20T21:47:31.000Z (10 months ago)
• Default Branch: main
• Last Pushed: 2024-07-27T20:53:14.000Z (4 months ago)
• Last Synced: 2024-07-28T20:00:43.992Z (4 months ago)
• Topics: data-cleaning, etl, extract-transform-load, json, merge-sort, numpy, pandas-dataframe, pandas-python
• Language: Jupyter Notebook
• Homepage: https://extension.berkeley.edu/search/publicCourseSearchDetails.do?method=load&courseId=35106003
• Size: 620 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Using an Extract, Transform, Load (ETL) process to clean up crowdfunding campaign data

This mini project required a fair amount of data cleaning and prep. This was Group Project #2, though some 'groups' were individuals. I completed this project as a 'group' of one.  

First I worked on the crowdfunding spreadsheet  

-Imported as a pandas dataframe.  

-Split 'category & sub-category' column into two separate columns.  

-Created variables to store lists of the category and subcategory names.  

-Created category and subcategory ids and paired them with the variables in the last step.  

-Used those pairs to create category and subcategory csv files and exported.  

Campaign data  

-Made a new dataframe using the crowdfunding info.  

-Renamed columns, changed data types, formatted data as needed.  

-Merged with category and subcategory files.  

-Removed unwanted columns to simplify.  

-Created csv file and exported.  

Contacts list  

-Used pandas to import contact info.  

-Contact id, name, and email were all in a single cell so I split them into separate columns.  

-Split the name into two columns with first name and last name.  

-Reordered columns.  

-Created csv file and exported.