Service Description: Data for the Analyze Online Lending Interest Rates case study and Jupyter Notebook sample.
Service ItemId: a5fc47691df74fb098cb632dabb2448f
Has Versioned Data: false
Max Record Count: 2000
Supported query Formats: JSON
Supports applyEdits with GlobalIds: False
Supports Shared Templates: False
All Layers and Tables
Layers:
Description: This service has all the data needed to work through the Analyze Online Lending Interest Rates case study tutorial and Jupyter Notebook sample. Individual loan data was obtained from LendingClub and aggregated to 3-digit ZIP code areas for analysis. Individual loan grades for issued loans were summarized as average loan grade rankings. Individual loan interest rates were averaged. The case study shows you how to create a hot spot analysis of average loan interest rates, create a model to predict average interest rates based on average loan grades, and map variations in the relationship between average loan grades and average interest rates.
For more information, see the case study
story map.
For access to the step-by-step tutorial, see the
Learn Lesson.
Original data source: LendingClub; Web layer created by Lauren Scott Griffin
Spatial Reference: 102003 (102003)
Initial Extent:
XMin: -3327726.68812753
YMin: -2077976.67939774
XMax: 3219981.6037443
YMax: 2408015.19990949
Spatial Reference: 102003 (102003)
Full Extent:
XMin: -2892906.73408885
YMin: -1393439.94152235
XMax: 2921972.22047158
YMax: 1646309.53674068
Spatial Reference: 102003 (102003)
Units: esriMeters
Child Resources:
Info
Supported Operations:
Query
ConvertFormat
Get Estimates