spa-l1-capetown-hospital-nn
Map (reference ← swipe → agent)
0:00
I am putting together EMS coverage planning for the Western Cape and need each residential pickup address tagged with its nearest hospital so the ops-research team can join the result against shift schedules. For every address in `addresses.parquet`, find the nearest hospital from `hospitals.parquet` by straight-line distance and record that hospital's name plus the distance in metres. Keep the original `address_id` from the input so we can join back to the address master, and make sure `nearest_hospital_name` comes through as a non-empty string and `distance_m` as a numeric, finite, non-negative value in metres.
Please write the result to `nearest_hospital.gpkg` in GeoPackage format with one feature per input address, keeping the original address geometry and the columns `address_id`, `nearest_hospital_name`, and `distance_m`.
0:00
System info
{
"adapter": "openrouter",
"model": "google/gemma-4-26b-a4b-it",
"base_url": "https://openrouter.ai/api/v1"
}
0:03
Bash
ls -F
addresses.parquet hospitals.parquet
1:06
Write
/work/inspect.py
content · 51 lines · py
import pandas as pd
import geopandas as gpd
# Inspect the data
addresses = pd.read_parquet('addresses.parquet')
hospitals = pd.read_parquet('hospitals.parquet')
print("Addresses columns:", addresses.columns)
print("Addresses head:\n", addresses.head())
print("\nHospitals columns:", hospitals.columns)
print("Hospitals head:\n", hospitals.head())
# Check if they are GeoDataFrames or if we need to convert them
if not isinstance(addresses, gpd.GeoDataFrame):
print("\nAddresses is not a GeoDataFrame. Attempting conversion...")
# Assuming 'geometry' column exists or we need to create it from lat/lon
# Let's check for lat/lon columns if geometry is missing
if 'geometry' not in addresses.columns:
# Try to find common lat/lon names
potential_lon = [c for c in addresses.columns if 'lon' in c.lower() or 'lng' in c.lower() or 'x' in c.lower()]
potential_lat = [c for c in addresses.columns if 'lat' in c.lower() or 'y' in c.lower()]
if potential_lon and potential_lat:
from shapely.geometry import Point
addresses = gpd.GeoDataFrame(
addresses,
geometry=gpd.points_from_xy(addresses[potential_lon[0]], addresses[potential_lat[0]]),
crs="EPSG:4326"
)
print(f"Converted addresses using {potential_lon[0]}, {potential_lat[0]}")
else:
print("Could not find lon/lat columns to convert to GeoDataFrame.")
if not isinstance(hospitals, gpd.GeoDataFrame):
print("\nHospitals is not a GeoDataFrame. Attempting conversion...")
if 'geometry' not in hospitals.columns:
potential_lon = [c for c in hospitals.columns if 'lon' in c.lower() or 'lng' in c.lower() or 'x' in c.lower()]
potential_lat = [c for c in hospitals.columns if 'lat' in c.lower() or 'y' in c.lower()]
if potential_lon and potential_lat:
from shapely.geometry import Point
hospitals = gpd.GeoDataFrame(
hospitals,
geometry=gpd.points_from_xy(hospitals[potential_lon[0]], hospitals[potential_lat[0]]),
crs="EPSG:4326"
)
print(f"Converted hospitals using {potential_lon[0]}, {potential_lat[0]}")
else:
print("Could not find lon/lat columns to convert to GeoDataFrame.")
print("\nAddresses CRS:", addresses.crs)
print("Hospitals CRS:", hospitals.crs)
Wrote /work/inspect.py (2437 chars).
1:13
Bash
python inspect.py
Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/numpy/_core/__init__.py", line 24, in <module>
from . import multiarray
File "/usr/local/lib/python3.14/site-packages/numpy/_core/multiarray.py", line 11, in <module>
from . import _multiarray_umath, overrides
File "/usr/local/lib/python3.14/site-packages/numpy/_core/overrides.py", line 4, in <module>
import inspect
File "/work/inspect.py", line 2, in <module>
import geopandas as gpd
File "/usr/local/lib/python3.14/site-packages/geopandas/__init__.py", line 3, in <module>
from geopandas.geoseries import GeoSeries
File "/usr/local/lib/python3.14/site-packages/geopandas/geoseries.py", line 9, in <module>
from pandas import Series
ImportError: cannot import name 'Series' from partially initialized module 'pandas' (most likely due to a circular import) (/usr/local/lib/python3.14/site-packages/pandas/__init__.py)
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/pandas/__init__.py", line 11, in <module>
__import__(_dependency)
File "/usr/local/lib/python3.14/site-packages/numpy/__init__.py", line 112, in <module>
from numpy.__config__ import show_config
File "/usr/local/lib/python3.14/site-packages/numpy/__config__.py", line 4, in <module>
from numpy._core._multiarray_umath import (
File "/usr/local/lib/python3.14/site-packages/numpy/_core/__init__.py", line 85, in <module>
raise ImportError(msg) from exc
ImportError:
IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE!
Importing the numpy C-extensions failed. This error can happen for
many reasons, often due to issues with your setup or how NumPy was
installed.
We have compiled some common reasons and troubleshooting tips at:
https://numpy.org/devdocs/user/troubleshooting-importerror.html
Please note and check the following:
* The Python version is: Python 3.14 from "/usr/local/bin/python"
* The NumPy version is: "2.4.6"
and make sure that they are the versions you expect.
Please carefully study the information and documentation linked above.
This is unlikely to be a NumPy issue but will be caused by a bad install
or environment on your machine.
Original error was: cannot import name 'Series' from partially initialized module 'pandas' (most likely due to a circular import) (/usr/local/lib/python3.14/site-packages/pandas/__init__.py)
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/work/inspect.py", line 1, in <module>
import pandas as pd
File "/usr/local/lib/python3.14/site-packages/pandas/__init__.py", line 13, in <module>
raise ImportError(
ImportError: Unable to import required dependency numpy. Please see the traceback for details.
1:17
Bash
python -c "import pandas; print(pandas.__version__)"
Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/numpy/_core/__init__.py", line 24, in <module>
from . import multiarray
File "/usr/local/lib/python3.14/site-packages/numpy/_core/multiarray.py", line 11, in <module>
from . import _multiarray_umath, overrides
File "/usr/local/lib/python3.14/site-packages/numpy/_core/overrides.py", line 4, in <module>
import inspect
File "/work/inspect.py", line 2, in <module>
import geopandas as gpd
File "/usr/local/lib/python3.14/site-packages/geopandas/__init__.py", line 3, in <module>
from geopandas.geoseries import GeoSeries
File "/usr/local/lib/python3.14/site-packages/geopandas/geoseries.py", line 9, in <module>
from pandas import Series
ImportError: cannot import name 'Series' from partially initialized module 'pandas' (most likely due to a circular import) (/usr/local/lib/python3.14/site-packages/pandas/__init__.py)
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/pandas/__init__.py", line 11, in <module>
__import__(_dependency)
File "/usr/local/lib/python3.14/site-packages/numpy/__init__.py", line 112, in <module>
from numpy.__config__ import show_config
File "/usr/local/lib/python3.14/site-packages/numpy/__config__.py", line 4, in <module>
from numpy._core._multiarray_umath import (
File "/usr/local/lib/python3.14/site-packages/numpy/_core/__init__.py", line 85, in <module>
raise ImportError(msg) from exc
ImportError:
IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE!
Importing the numpy C-extensions failed. This error can happen for
many reasons, often due to issues with your setup or how NumPy was
installed.
We have compiled some common reasons and troubleshooting tips at:
https://numpy.org/devdocs/user/troubleshooting-importerror.html
Please note and check the following:
* The Python version is: Python 3.14 from "/usr/local/bin/python"
* The NumPy version is: "2.4.6"
and make sure that they are the versions you expect.
Please carefully study the information and documentation linked above.
This is unlikely to be a NumPy issue but will be caused by a bad install
or environment on your machine.
Original error was: cannot import name 'Series' from partially initialized module 'pandas' (most likely due to a circular import) (/usr/local/lib/python3.14/site-packages/pandas/__init__.py)
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "<string>", line 1, in <module>
File "/usr/local/lib/python3.14/site-packages/pandas/__init__.py", line 13, in <module>
raise ImportError(
ImportError: Unable to import required dependency numpy. Please see the traceback for details.
1:24
Bash
pip list | grep -E "pandas|numpy|geopandas"
geopandas 1.1.3 numpy 2.4.6 pandas 3.0.3
1:40
Write
/work/inspect_duckdb.py
content · 19 lines · py
import duckdb
import pandas as pd
# Since pandas/numpy seems to have issues with the current python environment (Python 3.14 is very new),
# let's use duckdb to inspect the parquet files first.
con = duckdb.connect()
print("--- Addresses Schema ---")
con.execute("DESCRIBE SELECT * FROM 'addresses.parquet'").show()
print("\n--- Hospitals Schema ---")
con.execute("DESCRIBE SELECT * FROM 'hospitals.parquet'").show()
print("\n--- Addresses Sample ---")
con.execute("SELECT * FROM 'addresses.parquet' LIMIT 5").show()
print("\n--- Hospitals Sample ---")
con.execute("SELECT * FROM 'hospitals.parquet' LIMIT 5").show()
Wrote /work/inspect_duckdb.py (623 chars).
1:47
Bash
python inspect_duckdb.py
Traceback (most recent call last):
File "/work/inspect_duckdb.py", line 1, in <module>
import duckdb
File "/usr/local/lib/python3.14/site-packages/duckdb/__init__.py", line 168, in <module>
from duckdb._version import (
File "/usr/local/lib/python3.14/site-packages/duckdb/_version.py", line 9, in <module>
from importlib.metadata import version as _dist_version
File "/usr/local/lib/python3.14/importlib/metadata/__init__.py", line 10, in <module>
import inspect
File "/work/inspect.py", line 1, in <module>
import pandas as pd
File "/usr/local/lib/python3.14/site-packages/pandas/__init__.py", line 11, in <module>
__import__(_dependency)
File "/usr/local/lib/python3.14/site-packages/numpy/__init__.py", line 112, in <module>
from numpy.__config__ import show_config
File "/usr/local/lib/python3.14/site-packages/numpy/__config__.py", line 4, in <module>
from numpy._core._multiarray_umath import (
File "/usr/local/lib/python3.14/site-packages/numpy/_core/__init__.py", line 24, in <module>
from . import multiarray
File "/usr/local/lib/python3.14/site-packages/numpy/_core/multiarray.py", line 115, in <module>
@array_function_from_c_func_and_dispatcher(_multiarray_umath.empty_like)
File "/usr/local/lib/python3.14/site-packages/numpy/_core/overrides.py", line 185, in decorator
return array_function_dispatch(
File "/usr/local/lib/python3.14/site-packages/numpy/_core/overrides.py", line 161, in decorator
doc = inspect.cleandoc(dispatcher.__doc__)
AttributeError: module 'inspect' has no attribute 'cleandoc' (consider renaming '/work/inspect.py' since it has the same name as the standard library module named 'inspect' and prevents importing that standard library module)
1:50
Bash
rm /work/inspect.py
(no output)
2:04
Write
/work/inspect_duckdb_v2.py
content · 19 lines · py
import duckdb
import pandas as pd
# Since pandas/numpy seems to have issues with the current python environment (Python 3.14 is very new),
# let's use duckdb to inspect the parquet files first.
con = duckdb.connect()
print("--- Addresses Schema ---")
con.execute("DESCRIBE SELECT * FROM 'addresses.parquet'").show()
print("\n--- Hospitals Schema ---")
con.execute("DESCRIBE SELECT * FROM 'hospitals.parquet'").show()
print("\n--- Addresses Sample ---")
con.execute("SELECT * FROM 'addresses.parquet' LIMIT 5").show()
print("\n--- Hospitals Sample ---")
con.execute("SELECT * FROM 'hospitals.parquet' LIMIT 5").show()
Wrote /work/inspect_duckdb_v2.py (623 chars).
2:09
Bash
python inspect_duckdb_v2.py
--- Addresses Schema ---
Traceback (most recent call last):
File "/work/inspect_duckdb_v2.py", line 9, in <module>
con.execute("DESCRIBE SELECT * FROM 'addresses.parquet'").show()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
AttributeError: '_duckdb.DuckDBPyConnection' object has no attribute 'show'
2:24
Write
/work/inspect_duckdb_v3.py
content · 19 lines · py
import duckdb
import pandas as pd
# Since pandas/numpy seems to have issues with the current python environment (Python 3.14 is very new),
# let's use duckdb to inspect the parquet files first.
con = duckdb.connect()
print("--- Addresses Schema ---")
print(con.execute("DESCRIBE SELECT * FROM 'addresses.parquet'").df())
print("\n--- Hospitals Schema ---")
print(con.execute("DESCRIBE SELECT * FROM 'hospitals.parquet'").df())
print("\n--- Addresses Sample ---")
print(con.execute("SELECT * FROM 'addresses.parquet' LIMIT 5").df())
print("\n--- Hospitals Sample ---")
print(con.execute("SELECT * FROM 'hospitals.parquet' LIMIT 5").df())
Wrote /work/inspect_duckdb_v3.py (643 chars).
2:38
Bash
python inspect_duckdb_v3.py
--- Addresses Schema ---
column_name column_type ... default extra
0 address_id VARCHAR ... None None
1 geometry GEOMETRY('{"$schema":"https://proj.org/schemas... ... None None
[2 rows x 6 columns]
--- Hospitals Schema ---
column_name column_type ... default extra
0 hospital_id VARCHAR ... None None
1 name VARCHAR ... None None
2 geometry GEOMETRY('{"$schema":"https://proj.org/schemas... ... None None
[3 rows x 6 columns]
--- Addresses Sample ---
address_id geometry
0 A0001 [1, 1, 0, 0, 0, 194, 153, 36, 44, 207, 136, 50...
1 A0002 [1, 1, 0, 0, 0, 252, 103, 191, 18, 194, 128, 5...
2 A0003 [1, 1, 0, 0, 0, 184, 168, 128, 127, 71, 136, 5...
3 A0004 [1, 1, 0, 0, 0, 1, 86, 120, 118, 213, 114, 50,...
4 A0005 [1, 1, 0, 0, 0, 204, 167, 187, 240, 208, 127, ...
--- Hospitals Sample ---
hospital_id ... geometry
0 H001 ... [1, 1, 0, 0, 0, 183, 39, 39, 94, 142, 121, 50,...
1 H002 ... [1, 1, 0, 0, 0, 181, 1, 84, 72, 100, 119, 50, ...
2 H003 ... [1, 1, 0, 0, 0, 11, 232, 75, 144, 141, 107, 50...
3 H004 ... [1, 1, 0, 0, 0, 2, 212, 212, 178, 181, 110, 50...
4 H005 ... [1, 1, 0, 0, 0, 63, 107, 101, 95, 5, 120, 50, ...
[5 rows x 3 columns]
3:15
Write
/work/solve.py
content · 100 lines · py
import geopandas as gpd
import pandas as pd
# The previous error might have been due to the 'inspect.py' file in the directory.
# I've removed it. Let's try again.
try:
addresses = gpd.read_parquet('addresses.parquet')
hospitals = gpd.read_parquet('hospitals.parquet')
print("Addresses head:\n", addresses.head())
print("\nHospitals head:\n", hospitals.head())
# Ensure they have the same CRS and it is a projected CRS for distance in metres
# Or use a metric CRS for distance calculation.
# Assuming they are in EPSG:4326 (WGS84) based on typical lat/lon data,
# but let's check the actual CRS.
if addresses.crs is None:
addresses.set_crs("EPSG:4326", inplace=True)
if hospitals.crs is None:
hospitals.set_crs("EPSG:4326", inplace=True)
print(f"Addresses CRS: {addresses.crs}")
print(f"Hospitals CRS: {hospitals.crs}")
# To get distance in metres, we should project to a metric CRS.
# For Western Cape, UTM Zone 34S (EPSG:32734) is appropriate.
target_crs = "EPSG:32734"
addresses_proj = addresses.to_crs(target_crs)
hospitals_proj = hospitals.to_crs(target_crs)
# Find nearest hospital for each address
# We can use the sindex for efficiency.
def find_nearest(row, hospitals_gdf):
# Use the spatial index to find nearest points
# nearest_geometry is a bit tricky in older geopandas,
# let's use a more robust way.
# For each address, find the closest hospital.
# dists = hospitals_gdf.distance(row.geometry)
# idx = dists.idxmin()
# return hospitals_gdf.iloc[idx].name, dists.min()
# Actually, geopandas has a more efficient way for large datasets:
pass
# Using a more efficient approach:
# We want to find the nearest hospital for each address.
# We'll use the distance calculation on all pairs or use a spatial join if possible.
# Since we need the distance, a spatial join won't directly give it without extra work.
# Let's use the standard geopandas distance method with spatial index for speed
from shapely.ops import nearest_points
# Since we need distance in metres, we use the projected GDFs
# For every address, we find the nearest hospital
# Using the spatial index (sindex) for efficiency
sindex = hospitals_proj.sindex
nearest_hospital_names = []
distances_m = []
for idx, addr in addresses_proj.iterrows():
# Find the nearest point in hospitals_proj
# We use the sindex to get candidates (though for distance, it's slightly different)
# nearest_neighbors can be used or just brute force if the dataset isn't huge.
# Let's try the simple way first and see if it's fast enough.
dists = hospitals_proj.distance(addr.geometry)
min_dist = dists.min()
nearest_idx = dists.idxmin()
nearest_hospital_names.append(hospitals_proj.loc[nearest_idx, 'name'])
distances_m.append(min_dist)
# Add the results to the original addresses GDF (the one with the original geometry)
# We must be careful to use the original addresses to preserve the original geometry and CRS
# However, we've calculated distances using the projected ones.
# The distance in metres is correct because we used the projected GDF.
results_df = addresses.copy()
results_df['nearest_hospital_name'] = nearest_hospital_names
results_df['distance_m'] = distances_m
# Filter columns as requested
output_gdf = results_df[['address_id', 'nearest_hospital_name', 'distance_m', 'geometry']]
# Write to GeoPackage
output_gdf.to_file('nearest_hospital.gpkg', driver='GPKG')
print("\nSuccessfully wrote nearest_hospital.gpkg")
except Exception as e:
print(f"Error: {e}")
import traceback
traceback.print_exc()
Wrote /work/solve.py (3909 chars).
3:18
Bash
python solve.py
Addresses head:
address_id geometry
0 A0001 POINT (18.53441 -33.94184)
1 A0002 POINT (18.50296 -33.93623)
2 A0003 POINT (18.53234 -33.95918)
3 A0004 POINT (18.44857 -33.98103)
4 A0005 POINT (18.49928 -33.99649)
Hospitals head:
hospital_id name geometry
0 H001 Mowbray Maternity Hospital POINT (18.47483 -33.94921)
1 H002 Life Claremont Hospital POINT (18.46637 -33.98695)
2 H003 Old Somerset Hospital POINT (18.42013 -33.9158)
3 H004 Mpheni Block C Elim Hospital POINT (18.43246 -33.92207)
4 H005 Life Kingsbury Hospital POINT (18.46883 -33.98645)
Addresses CRS: {"$schema": "https://proj.org/schemas/v0.7/projjson.schema.json", "type": "GeographicCRS", "name": "WGS 84", "datum_ensemble": {"name": "World Geodetic System 1984 ensemble", "members": [{"name": "World Geodetic System 1984 (Transit)"}, {"name": "World Geodetic System 1984 (G730)"}, {"name": "World Geodetic System 1984 (G873)"}, {"name": "World Geodetic System 1984 (G1150)"}, {"name": "World Geodetic System 1984 (G1674)"}, {"name": "World Geodetic System 1984 (G1762)"}, {"name": "World Geodetic System 1984 (G2139)"}, {"name": "World Geodetic System 1984 (G2296)"}], "ellipsoid": {"name": "WGS 84", "semi_major_axis": 6378137, "inverse_flattening": 298.257223563}, "accuracy": "2.0", "id": {"authority": "EPSG", "code": 6326}}, "coordinate_system": {"subtype": "ellipsoidal", "axis": [{"name": "Geodetic latitude", "abbreviation": "Lat", "direction": "north", "unit": "degree"}, {"name": "Geodetic longitude", "abbreviation": "Lon", "direction": "east", "unit": "degree"}]}, "scope": "Horizontal component of 3D system.", "area": "World.", "bbox": {"south_latitude": -90, "west_longitude": -180, "north_latitude": 90, "east_longitude": 180}, "id": {"authority": "EPSG", "code": 4326}}
Hospitals CRS: {"$schema": "https://proj.org/schemas/v0.7/projjson.schema.json", "type": "GeographicCRS", "name": "WGS 84", "datum_ensemble": {"name": "World Geodetic System 1984 ensemble", "members": [{"name": "World Geodetic System 1984 (Transit)"}, {"name": "World Geodetic System 1984 (G730)"}, {"name": "World Geodetic System 1984 (G873)"}, {"name": "World Geodetic System 1984 (G1150)"}, {"name": "World Geodetic System 1984 (G1674)"}, {"name": "World Geodetic System 1984 (G1762)"}, {"name": "World Geodetic System 1984 (G2139)"}, {"name": "World Geodetic System 1984 (G2296)"}], "ellipsoid": {"name": "WGS 84", "semi_major_axis": 6378137, "inverse_flattening": 298.257223563}, "accuracy": "2.0", "id": {"authority": "EPSG", "code": 6326}}, "coordinate_system": {"subtype": "ellipsoidal", "axis": [{"name": "Geodetic latitude", "abbreviation": "Lat", "direction": "north", "unit": "degree"}, {"name": "Geodetic longitude", "abbreviation": "Lon", "direction": "east", "unit": "degree"}]}, "scope": "Horizontal component of 3D system.", "area": "World.", "bbox": {"south_latitude": -90, "west_longitude": -180, "north_latitude": 90, "east_longitude": 180}, "id": {"authority": "EPSG", "code": 4326}}
Successfully wrote nearest_hospital.gpkg
3:22
Bash
python -c "import geopandas as gpd; gdf = gpd.read_file('nearest_hospital.gpkg')...
address_id ... geometry 0 A0001 ... POINT (18.53441 -33.94184) 1 A0002 ... POINT (18.50296 -33.93623) 2 A0003 ... POINT (18.53234 -33.95918) 3 A0004 ... POINT (18.44857 -33.98103) 4 A0005 ... POINT (18.49928 -33.99649) [5 rows x 4 columns] address_id str nearest_hospital_name str distance_m float64 geometry geometry dtype: object
4:15