spa-l1-paris-amenity-within
Map (reference ← swipe → agent)
0:00
I'm putting together a neighbourhood demographic crosswalk for the INSEE census team and need each amenity tagged with the Paris arrondissement it falls inside. Can you join `amenities` to `arrondissements` and write the result to `amenity_to_arrondissement.csv` with one row per amenity? The columns are `osm_id`, `amenity_class`, `arrondissement_number` (integer), and `arrondissement_name` (string).
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System info
{
"adapter": "openrouter",
"model": "deepseek/deepseek-v4-flash",
"base_url": "https://openrouter.ai/api/v1"
}
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Bash
ls /work/
paris_amenities.gpkg
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Bash
ls /work/arrondissements* 2>/dev/null; ls /work/*arrondissement* 2>/dev/null; ls...
/work/paris_amenities.gpkg
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0:11
Bash
python3 -c "
python3 -c "
import geopandas as gpd
layers = gpd.list_layers('/work/paris_amenities.gpkg')
print(layers)
"
name geometry_type 0 amenities Point 1 arrondissements Polygon
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0:22
Bash
python3 -c "
python3 -c "
import geopandas as gpd
amen = gpd.read_file('/work/paris_amenities.gpkg', layer='amenities')
arr = gpd.read_file('/work/paris_amenities.gpkg', layer='arrondissements')
print('=== AMENITIES ===')
print(amen.columns.tolist())
print(amen.head(3))
print(amen.crs)
print()
print('=== ARRONDISSEMENTS ===')
print(arr.columns.tolist())
print(arr.head(3))
print(arr.crs)
"
=== AMENITIES ===
['osm_id', 'amenity_class', 'name', 'geometry']
osm_id ... geometry
0 9000000000 ... POINT (652773.528 6864033.347)
1 9000000001 ... POINT (652322.91 6861774.142)
2 9000000002 ... POINT (653028.103 6863582.051)
[3 rows x 4 columns]
EPSG:2154
=== ARRONDISSEMENTS ===
['id', 'name', 'geometry']
id ... geometry
0 0cef9694-93f0-4acf-a44f-f54a01fce855 ... POLYGON ((651737.858 6858104.126, 651824.872 6...
1 0e2667a3-715f-45ef-8fd5-7cdba7344a12 ... POLYGON ((651390.128 6862244.403, 651327.017 6...
2 2747f137-3f7b-4ac4-b222-b4ac7acef256 ... POLYGON ((653870.967 6863517.544, 653863.816 6...
[3 rows x 3 columns]
EPSG:2154
0:38
The arrondissements layer has `id` and `name` columns. The name is like "Paris 1er Arrondissement" or similar. I need to extract the arrondissement number from either the `id` or `name`. Let me look at more data to understand the naming.
0:38
Bash
python3 -c "
python3 -c "
import geopandas as gpd
arr = gpd.read_file('/work/paris_amenities.gpkg', layer='arrondissements')
print(arr[['id','name']].to_string())
"
id name 0 0cef9694-93f0-4acf-a44f-f54a01fce855 Paris 13e Arrondissement 1 0e2667a3-715f-45ef-8fd5-7cdba7344a12 Paris 6e Arrondissement 2 2747f137-3f7b-4ac4-b222-b4ac7acef256 Paris 11e Arrondissement 3 32fbdc6a-f89d-4d02-ac87-6d0e4fc98969 Paris 3e Arrondissement 4 366fc115-880d-47a0-90d8-95f28f275224 Paris 2e Arrondissement 5 39c0e434-e46e-4ac9-b35a-100f804ede99 Paris 10e Arrondissement 6 4687f7be-db17-41c3-a9d0-09afa5523060 Paris 20e Arrondissement 7 4e7c04fe-3c0d-4401-b79d-ce3e2395e5fd Paris 8e Arrondissement 8 5134a455-e91f-4fdb-8638-c33ee7cb1383 Paris 19e Arrondissement 9 5537e76e-52db-4342-938d-a91168f4e6a7 Paris 5e Arrondissement 10 571cb253-40c3-4761-b663-d30deedf713f Paris 17e Arrondissement 11 75e0a62a-117b-46e6-8782-a4b225ce37e4 Paris 9e Arrondissement 12 7caa32e9-d051-48f2-87ae-29d09104547e Paris 16e Arrondissement 13 818e7bcb-32e9-4567-919a-c44153254398 Paris 14e Arrondissement 14 8a6c934a-8534-4e30-a9e5-e827de7a9891 Paris 12e Arrondissement 15 98f4ac3a-fc4a-40de-b535-2ebfa6f4e202 Paris 4e Arrondissement 16 dcc8aaa3-2adb-424f-a745-b9a23163f7c0 Paris 18e Arrondissement 17 ea79b3d9-590d-450e-8da6-30cb1b6fcc66 Paris 7e Arrondissement 18 ed5166f4-7111-4e42-bcbe-0630271cc71e Paris 1er Arrondissement 19 f22f8b89-a6ec-449f-bc9a-cf3c7644d0e0 Paris 15e Arrondissement
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0:48
Write
/work/solve.py
content · 34 lines · py
import geopandas as gpd
import re
# Read both layers
amen = gpd.read_file('/work/paris_amenities.gpkg', layer='amenities')
arr = gpd.read_file('/work/paris_amenities.gpkg', layer='arrondissements')
# Both are EPSG:2154, so spatial join works directly
joined = gpd.sjoin(amen, arr, how='left', predicate='within')
# Extract arrondissement number from name like "Paris 13e Arrondissement" or "Paris 1er Arrondissement"
def extract_arr_number(name):
if pd.isna(name):
return None
m = re.search(r'(\d+)', name)
return int(m.group(1)) if m else None
import pandas as pd
joined['arrondissement_number'] = joined['name_right'].apply(extract_arr_number)
joined['arrondissement_name'] = joined['name_right']
# Build output with required columns
result = joined[['osm_id', 'amenity_class', 'arrondissement_number', 'arrondissement_name']].copy()
# Ensure integer type for arrondissement_number (nullable)
result['arrondissement_number'] = result['arrondissement_number'].astype('Int64')
# Write CSV
result.to_csv('/work/amenity_to_arrondissement.csv', index=False)
print(f"Wrote {len(result)} rows to amenity_to_arrondissement.csv")
print(result.head(10))
print(result.dtypes)Wrote /work/solve.py (1195 chars).
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Bash
cd /work && python solve.py
Wrote 85 rows to amenity_to_arrondissement.csv
osm_id amenity_class arrondissement_number arrondissement_name
0 9000000000 restaurant 10 Paris 10e Arrondissement
1 9000000001 restaurant 4 Paris 4e Arrondissement
2 9000000002 bakery 10 Paris 10e Arrondissement
3 9000000003 bakery 13 Paris 13e Arrondissement
4 9000000004 restaurant 9 Paris 9e Arrondissement
5 9000000005 restaurant 15 Paris 15e Arrondissement
6 9000000006 restaurant 20 Paris 20e Arrondissement
7 9000000007 cafe 6 Paris 6e Arrondissement
8 9000000008 restaurant 18 Paris 18e Arrondissement
9 9000000009 cafe 5 Paris 5e Arrondissement
osm_id int64
amenity_class str
arrondissement_number Int64
arrondissement_name str
dtype: object
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0:56
Bash
cd /work && python3 -c "
cd /work && python3 -c "
import pandas as pd
df = pd.read_csv('amenity_to_arrondissement.csv')
print('Shape:', df.shape)
print('Columns:', df.columns.tolist())
print('Dtypes:')
print(df.dtypes)
print()
print('Null arrondissements:', df['arrondissement_number'].isna().sum())
print()
print(df.to_string())
"
Shape: (85, 4)
Columns: ['osm_id', 'amenity_class', 'arrondissement_number', 'arrondissement_name']
Dtypes:
osm_id int64
amenity_class str
arrondissement_number int64
arrondissement_name str
dtype: object
Null arrondissements: 0
osm_id amenity_class arrondissement_number arrondissement_name
0 9000000000 restaurant 10 Paris 10e Arrondissement
1 9000000001 restaurant 4 Paris 4e Arrondissement
2 9000000002 bakery 10 Paris 10e Arrondissement
3 9000000003 bakery 13 Paris 13e Arrondissement
4 9000000004 restaurant 9 Paris 9e Arrondissement
5 9000000005 restaurant 15 Paris 15e Arrondissement
6 9000000006 restaurant 20 Paris 20e Arrondissement
7 9000000007 cafe 6 Paris 6e Arrondissement
8 9000000008 restaurant 18 Paris 18e Arrondissement
9 9000000009 cafe 5 Paris 5e Arrondissement
10 9000000010 restaurant 17 Paris 17e Arrondissement
11 9000000011 restaurant 6 Paris 6e Arrondissement
12 9000000012 restaurant 8 Paris 8e Arrondissement
13 9000000013 restaurant 1 Paris 1er Arrondissement
14 9000000014 restaurant 10 Paris 10e Arrondissement
15 9000000015 cafe 15 Paris 15e Arrondissement
16 9000000016 cafe 12 Paris 12e Arrondissement
17 9000000017 bakery 15 Paris 15e Arrondissement
18 9000000018 cafe 3 Paris 3e Arrondissement
19 9000000019 bakery 9 Paris 9e Arrondissement
20 9000000020 restaurant 19 Paris 19e Arrondissement
21 9000000021 cafe 9 Paris 9e Arrondissement
22 9000000022 restaurant 15 Paris 15e Arrondissement
23 9000000023 bakery 7 Paris 7e Arrondissement
24 9000000024 pharmacy 9 Paris 9e Arrondissement
25 9000000025 library 10 Paris 10e Arrondissement
26 9000000026 bakery 10 Paris 10e Arrondissement
27 9000000027 restaurant 8 Paris 8e Arrondissement
28 9000000028 bakery 18 Paris 18e Arrondissement
29 9000000029 restaurant 15 Paris 15e Arrondissement
30 9000000030 restaurant 11 Paris 11e Arrondissement
31 9000000031 bakery 15 Paris 15e Arrondissement
32 9000000032 bakery 19 Paris 19e Arrondissement
33 9000000033 pharmacy 14 Paris 14e Arrondissement
34 9000000034 pharmacy 15 Paris 15e Arrondissement
35 9000000035 cafe 1 Paris 1er Arrondissement
36 9000000036 restaurant 17 Paris 17e Arrondissement
37 9000000037 cafe 15 Paris 15e Arrondissement
38 9000000038 library 7 Paris 7e Arrondissement
39 9000000039 bakery 15 Paris 15e Arrondissement
40 9000000040 bakery 15 Paris 15e Arrondissement
41 9000000041 library 13 Paris 13e Arrondissement
42 9000000042 pharmacy 19 Paris 19e Arrondissement
43 9000000043 cafe 6 Paris 6e Arrondissement
44 9000000044 bakery 13 Paris 13e Arrondissement
45 9000000045 library 13 Paris 13e Arrondissement
46 9000000046 cafe 18 Paris 18e Arrondissement
47 9000000047 cafe 1 Paris 1er Arrondissement
48 9000000048 pharmacy 15 Paris 15e Arrondissement
49 9000000049 bakery 8 Paris 8e Arrondissement
50 9000000050 bakery 5 Paris 5e Arrondissement
51 9000000051 pharmacy 2 Paris 2e Arrondissement
52 9000000052 bakery 5 Paris 5e Arrondissement
53 9000000053 cafe 1 Paris 1er Arrondissement
54 9000000054 pharmacy 8 Paris 8e Arrondissement
55 9000000055 pharmacy 14 Paris 14e Arrondissement
56 9000000056 cafe 6 Paris 6e Arrondissement
57 9000000057 cafe 16 Paris 16e Arrondissement
58 9000000058 cafe 15 Paris 15e Arrondissement
59 9000000059 cafe 9 Paris 9e Arrondissement
60 9000000060 pharmacy 3 Paris 3e Arrondissement
61 9000000061 pharmacy 16 Paris 16e Arrondissement
62 9000000062 cafe 17 Paris 17e Arrondissement
63 9000000063 cafe 19 Paris 19e Arrondissement
64 9000000064 cafe 18 Paris 18e Arrondissement
65 9000000065 cafe 15 Paris 15e Arrondissement
66 9000000066 pharmacy 16 Paris 16e Arrondissement
67 9000000067 library 10 Paris 10e Arrondissement
68 9000000068 pharmacy 19 Paris 19e Arrondissement
69 9000000069 pharmacy 4 Paris 4e Arrondissement
70 9000000070 pharmacy 13 Paris 13e Arrondissement
71 9000000071 pharmacy 9 Paris 9e Arrondissement
72 9000000072 library 7 Paris 7e Arrondissement
73 9000000073 library 19 Paris 19e Arrondissement
74 9000000074 pharmacy 12 Paris 12e Arrondissement
75 9000000075 pharmacy 7 Paris 7e Arrondissement
76 9000000076 library 10 Paris 10e Arrondissement
77 9000000077 library 14 Paris 14e Arrondissement
78 9000000078 library 19 Paris 19e Arrondissement
79 9000000079 library 7 Paris 7e Arrondissement
80 9000000080 library 5 Paris 5e Arrondissement
81 9000000081 library 5 Paris 5e Arrondissement
82 9000000082 library 12 Paris 12e Arrondissement
83 9000000083 library 1 Paris 1er Arrondissement
84 9000000084 library 13 Paris 13e Arrondissement
1:07
1:07
Bash
ls -la /work/amenity_to_arrondissement.csv
-rw-r--r-- 1 agent agent 3988 Jun 16 07:46 /work/amenity_to_arrondissement.csv
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