You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
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.
The text was updated successfully, but these errors were encountered:
- 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.
@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
Aim of the feature:
DHSCLUST
,HV270
,HV271
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
.The text was updated successfully, but these errors were encountered: