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fix: make sure to include areas with disputed regions #74

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merged 6 commits into from
Jan 3, 2025
Merged

fix: make sure to include areas with disputed regions #74

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15ff8f0
fix: make sure administrative areas including disputed countries are …
12rambau Dec 3, 2024
b90613b
use pd.merge on GIDs to map between gpkg and geojson dfs
julianwid Dec 4, 2024
44f8c8c
Merge branch 'china' into main
12rambau Jan 3, 2025
fa0894b
use pd.merge on GIDs to map between gpkg and geojson dfs (#75)
12rambau Jan 3, 2025
dcfa2e0
refactor: fix linting
12rambau Jan 3, 2025
535070c
fix: make sure the final GDF is still filtered
12rambau Jan 3, 2025
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22 changes: 18 additions & 4 deletions pygadm/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -229,18 +229,32 @@ def _items(self, name: str = "", admin: str = "", content_level: int = -1) -> gp
)

level_gdf = gpd.GeoDataFrame.from_features(data)
level_gdf.rename(columns={"COUNTRY": "NAME_0"}, inplace=True)
level_gdf = level_gdf.rename(columns={"COUNTRY": "NAME_0"})

# countries can embed multiple iso codes as some places are disputed so we need to gather them
# from the geojson file
isos = level_gdf.GID_0.dropna().unique()

# workaround for the wrong naming convention in the geojson files
# https://gis.stackexchange.com/questions/467848/how-to-get-back-spaces-in-administrative-names-in-gadm-4-1
# it should disappear in the next version of GADM
# we are forced to retrieve all the names from the df (sourced from.gpkg) to replace the one from
# the geojson that are all in camelCase
complete_df = Names(admin=iso_3, content_level=content_level, complete=True)
# the geojson that are all in camelCase.
df_list = [Names(admin=iso, content_level=content_level, complete=True) for iso in isos]
complete_df = pd.concat(df_list)
for i in range(int(content_level) + 1):
level_gdf.loc[:, f"NAME_{i}"] = complete_df[f"NAME_{i}"].values

gdf = level_gdf[level_gdf[column.format(level)].str.fullmatch(id, case=False)]
df_list = [Names(admin=iso, content_level=content_level, complete=True) for iso in isos]
complete_df = pd.concat(df_list)
# GID columns to merge on; they (should) match exactly
shared_cols = [f"GID_{i}" for i in range(int(content_level) + 1)]
# Camel-case columns to drop
drop_cols = [f"NAME_{i}" for i in range(int(content_level) + 1)]
gdf = pd.merge(level_gdf.drop(drop_cols, axis=1), complete_df, how="inner", on=shared_cols)

# now we can filter this dataframe with the appropriate name or admin code
gdf = gdf[gdf[column.format(level)].str.fullmatch(id, case=False)]

return gdf

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