https://github.com/open-risk-academy/academy-course-pyt37067

Resources for Open Risk Academy Course: "Processing US Agency Mortgage Data with Awk and Pandas - Part 2: Performing Book"
https://github.com/open-risk-academy/academy-course-pyt37067

awk data-science elearning mortgage-data-analysis mortgages pandas pandas-dataframe python risk-analysis

Last synced: about 1 month ago
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Resources for Open Risk Academy Course: "Processing US Agency Mortgage Data with Awk and Pandas - Part 2: Performing Book"

• Host: GitHub
• URL: https://github.com/open-risk-academy/academy-course-pyt37067
• Owner: Open-Risk-Academy
• License: apache-2.0
• Created: 2023-02-27T15:20:16.000Z (almost 2 years ago)
• Default Branch: main
• Last Pushed: 2024-05-14T18:38:55.000Z (8 months ago)
• Last Synced: 2024-05-15T15:05:55.067Z (8 months ago)
• Topics: awk, data-science, elearning, mortgage-data-analysis, mortgages, pandas, pandas-dataframe, python, risk-analysis
• Language: Python
• Homepage: https://www.openriskacademy.com/course/view.php?id=67
• Size: 189 KB
• Stars: 1
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Academy-Course-PYT37067

Processing Agency Mortgage Data with Awk, Pandas and Django - Part 2: Performing Book

This [crash course](https://www.openriskacademy.com/course/view.php?id=67) illustrates how to process loan-level US Agency mortgage data using awk, pandas and django. The second part of the course focuses on performing book attributes. It requires familiarity with command line tools (Ideally a linux environment) and Python. The repository includes various scripts used in the course.

![Course Image](pyt37067_course_image.png)



Please Note: Replicating the data processing steps on an actual Fannie Mae dataset requires the Academy student to download such data themselves from the Data Dynamics website and abide with their terms and conditions.



Course Level and Type:


    

    

        

        Introductory Level

        Core Level

        Advanced Level

    

    

        Non-Technical

        

        

        

    

    

        Technical

        

        CrashProgram
PYT37067