Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

[FEATURE] Create a single shapefile combining weighted voronoi and wealth index #26

Open
3 tasks done
sunayana opened this issue May 7, 2021 · 2 comments
Open
3 tasks done
Assignees
Labels
enhancement New feature or request
Milestone

Comments

@sunayana
Copy link
Collaborator

sunayana commented May 7, 2021

Aim of the feature:

  • Reduce the DHS file IAHR74FL.SAV from household recode to the main indexes : DHSCLUST, HV270, HV271
  • Merge it with the clipped weighted voronoi shape file
  • Write the merged dataframe to a new shapefile

Outcome
When this process is complete we will have the complete pipeline of assigning wealth indexes to the DHS clusters directly from DHS datasets and not rely on the DHS_PROCESSED_CLEANED.csv.

@sunayana sunayana self-assigned this May 7, 2021
@sunayana sunayana added the enhancement New feature or request label May 7, 2021
@sunayana sunayana added this to the OSM Scale up milestone May 7, 2021
sunayana added a commit to sunayana/WRI_WellBeing_Data_Layer that referenced this issue May 7, 2021
	- Reduce the DHS file IAHR74FL.SAV to important indexes
	- Merge the clipped weighted voronoi shape file to the dataframe obtained from above step
	- Creates and example file read_sav.ipynb to show usage of the methods.
sunayana added a commit that referenced this issue May 7, 2021
@sunayana
Copy link
Collaborator Author

sunayana commented May 7, 2021

@cmougan , @GvdDool , @rohaan2614 : So this commit resolves the issue of creating our own shapefile from clipped voronoi shape file and DHS data file IAHR74FL.SAV. Now we do not depend on file from Omdena and everything is transparent to us. You can check the methods:
read_and_reduce_sav in data_prep_voronoi.py to see how the aggregation is done. The example ipython notebook is read_sav.ipynb.

sunayana added a commit to sunayana/WRI_WellBeing_Data_Layer that referenced this issue May 7, 2021
sunayana added a commit that referenced this issue May 7, 2021
@rohaan2614
Copy link
Contributor

rohaan2614 commented May 7, 2021 via email

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
enhancement New feature or request
Projects
None yet
Development

No branches or pull requests

2 participants