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https://github.com/open-risk-academy/academy-course-pyt26065
Resources for Open Risk Academy Course: "Processing US Agency Mortgage Data with Awk and Pandas - Part 1: Static Data"
https://github.com/open-risk-academy/academy-course-pyt26065
awk data-science elearning mortgage-data-analysis mortgages pandas pandas-dataframe python risk-analysis
Last synced: about 2 months ago
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Resources for Open Risk Academy Course: "Processing US Agency Mortgage Data with Awk and Pandas - Part 1: Static Data"
- Host: GitHub
- URL: https://github.com/open-risk-academy/academy-course-pyt26065
- Owner: Open-Risk-Academy
- License: apache-2.0
- Created: 2023-02-02T12:20:43.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2024-05-13T18:33:49.000Z (8 months ago)
- Last Synced: 2024-05-13T19:47:14.704Z (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=65
- Size: 312 KB
- Stars: 2
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Academy-Course-PYT26065
Processing Agency Mortgage Data with Awk, Pandas and Django - Part 1: Static Data![Course Image](pyt26065_course_image.png)
This [crash course](https://www.openriskacademy.com/course/view.php?id=65) illustrates how to process loan-level US Agency mortgage data using awk, pandas and django. The first part of the course focuses on static (acquisition) type attributes. The course is at a core technical level. It requires familiarity with command line tools (Ideally a linux environment) and Python. The repository includes various scripts used in the course.
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
PYT26065