Closed gnodnooh closed 1 month ago
Thanks @gnodnooh. @janet6868 Please address the above comments in data card or data preparation notebook. Thanks.
@gnodnooh
@krsnapaudel I have included my comments above.
@gnodnooh please check again, the shapefile is okay from my side. However, I have just uploaded it again to be sure.
@janet6868 Thanks. Are we looking at the same folder Mali Data (Africa)? It does not show any files for me when I signed in the Google. In the incognito mode, I can see the shapefile files that has below characteristics:
Not sure what the problem is here.
@gnodnooh
756 represents the sectors in the one large polygon (MultiPolygon)
when you check the attribute table:
@gnodnooh please let me know if you would like me to share it as geojson.
Thanks, @janet6868. Your comments are very helpful. My point is that we may only need a single feature or polygon (row) for each adm_id for the further process of aggregating climate data. I see that each adm_id has 28 duplicated polygons (rows). It’s not a significant issue, but it would just be a preference 👌
Hello @gnodnooh I'm so sorry, I understand your point now. If you look at the data, we have 28 years for each adm_id (1990-2017), making 28 rows for each adm_id. Let me know if this info helps. Thanks
Hi @janet6868, If it is convenient for you, It would be beneficial to have a single feature per adm_id. This approach aligns with our separate data file and ensures consistency with other shapefiles. Thanks!
@gnodnooh
Here is one challenge of using a single feature per
adm_id
. I am working with third-level administrative boundaries, where each level can contain two or more sectors. Removing duplicates could result in losing important features, as illustrated by the purple-colored features that would be dropped. To address this, I will append the sector's unique ID to the administrative ID, ensuring each of the 27 features remains unique. I will update you once this is completed.
@gnodnooh it's done.
Kindly check it out.
Looks good to me. Thanks for your work!
I'm raising the following points after quick-checking the Mali data:
This crop statistics report covers the southern parts of Mali, which are the major producing regions, rather than the entire country.
It might be helpful to explain the contents of each CSV file. The “maize_aggregated_yield_stats.csv” file contains general statistics about the data, not the data itself.
While crop statistics data has "adm3_pcode" column, the shapefile does not have any relevant ID column. It only includes “CMDTsector” and “CMDYsecto2”.
For the file “maize_production_area_aggre_yield_data.csv”: