fio-l1-nyc-csvwkt-addresses
Map (reference ← swipe → agent)
0:00
The vendor SQL export `nyc_addresses` needs proper GeoParquet so `WHERE recorded_at > '2024-01-01'` and `SUM(unit_count)` work without CASTs. Convert it to `addresses.geoparquet`: Point geometry in EPSG:4326, `recorded_at` as `timestamp[us]`, `unit_count` as `int32`, all other columns as string.
0:00
System info
{
"adapter": "openrouter",
"model": "deepseek/deepseek-v4-flash",
"base_url": "https://openrouter.ai/api/v1"
}
0:02
Let me start by examining the vendor SQL export file to understand its structure.
0:02
Read
/work/nyc_addresses
file does not exist: /work/nyc_addresses
0:06
Let me check what files are available in the working directory.
0:06
Bash
ls -la /work/
total 144 drwxr-xr-x 1 agent agent 34 Jun 18 06:05 . drwxr-xr-x 1 root root 14 Jun 18 06:05 .. -rw-r--r-- 1 agent agent 143422 Jun 18 06:05 nyc_addresses.csv
0:14
The file is `nyc_addresses.csv` not `nyc_addresses`. Let me read it.
0:14
Read
/work/nyc_addresses.csv
1 "id","country","postcode","street","number","unit","postal_city","recorded_at","unit_count","geometry_wkt"
2 "0005eda0-2540-4e36-bc81-dfb52e323d99","US","10002","ALLEN ST","37","1/2","","2024-01-01T00:00:00Z","0","POINT (-73.9922338 40.716163)"
3 "00587e13-6253-485d-9258-e47d43af7559","US","10038","MADISON ST","45","","","2024-01-12T07:13:17Z","0","POINT (-73.9983308 40.71204)"
4 "0070f126-d36a-43b3-b767-a8fbb7156602","US","10038","PECK SLIP","44","","","2024-01-23T14:26:34Z","0","POINT (-74.0015005 40.7073293)"
5 "00a8fc38-5d9a-42da-94a9-7d2f4101f82c","US","11201","FRONT ST","11","","","2024-02-03T21:39:51Z","0","POINT (-73.9928578 40.702681)"
6 "00f815af-51f6-44c2-b0d6-ee23092d14b2","US","10280","ALBANY ST","340","","","2024-02-14T04:52:08Z","1","POINT (-74.0175967 40.7102422)"
7 "014806e3-0deb-4be3-abd5-2be10dedf40c","US","10013","CHURCH ST","299","","","2024-02-25T11:05:25Z","0","POINT (-74.0043074 40.7193005)"
8 "018c3b29-04d1-4890-a12b-8098f6f0c7de","US","10013","WALKER ST","37","","","2024-03-07T18:18:42Z","0","POINT (-74.0040214 40.7192277)"
9 "01cbed19-2940-4b4a-9d90-6f0be7f1b604","US","10012","MOTT ST","184","","","2024-03-18T01:31:59Z","0","POINT (-73.9957225 40.7207067)"
10 "01fadb51-074c-4050-a670-4a615337d972","US","10002","E BROADWAY","53","","","2024-03-29T08:44:16Z","2","POINT (-73.9955533 40.7135006)"
11 "02338589-3333-46a3-8adb-84b4ab20dd49","US","10007","WORLD TRADE CENTER","1","","","2024-04-09T15:57:33Z","0","POINT (-74.0130135 40.7132465)"
12 "028bc5b7-7987-49b6-b764-be1f6f81f309","US","10012","THOMPSON ST","68","","","2024-04-20T22:10:50Z","0","POINT (-74.0030133 40.7242823)"
13 "02ad9ccb-a580-45ef-8488-d3b35b58f3e4","US","10014","AVE OF THE AMERICAS","260","","","2024-05-01T05:23:07Z","0","POINT (-74.0023323 40.7289513)"
14 "02eb28d4-4e3d-4eb0-a72d-b3795bdb5a5b","US","10012","WOOSTER ST","139","","","2024-05-12T12:36:24Z","3","POINT (-73.9998396 40.7258502)"
15 "031f3e1d-7b14-4f57-8b3f-50d3fb2242e7","US","10013","DESBROSSES ST","2","","","2024-05-23T19:49:41Z","0","POINT (-74.0084458 40.7234422)"
16 "037716a1-f77e-4fda-bb9f-5861994e15ef","US","10013","MOTT ST","85","","","2024-06-03T02:02:58Z","0","POINT (-73.9979789 40.7166695)"
17 "03b4681c-0c78-4483-9d20-714c8315ea11","US","10013","BAXTER ST","120","","","2024-06-14T09:15:15Z","0","POINT (-73.9991465 40.7180102)"
18 "0400947d-6748-449c-9ab9-177fa96ccaaf","US","10013","GRAND ST","154","","","2024-06-25T16:28:32Z","4","POINT (-73.9988115 40.7200596)"
19 "04382316-a3fe-4442-bef1-b0e1b64f0502","US","11201","MIDDAGH ST","12","","","2024-07-06T23:41:49Z","0","POINT (-73.9946485 40.7007669)"
20 "04858323-61a9-4293-a2bf-14d3e8f97359","US","10012","MAC DOUGAL ST","48","","","2024-07-17T06:54:06Z","0","POINT (-74.0026039 40.7273331)"
21 "04d5ee66-5723-4893-b10f-281e240f44d7","US","10002","HESTER ST","124","A","","2024-07-28T13:07:23Z","0","POINT (-73.9947517 40.7169841)"
22 "0523460c-2fa8-4e46-a2f9-32a6338c9996","US","10003","E 2 ST","8","","","2024-08-08T20:20:40Z","5","POINT (-73.9914287 40.7255015)"
23 "055bb440-332b-41e9-965f-65011adcb899","US","10013","BROADWAY","440","","","2024-08-19T03:33:57Z","0","POINT (-74.0011001 40.7201053)"
24 "05a1d228-5dbf-4339-ae06-3eeeb55b637c","US","10012","MULBERRY ST","247","","","2024-08-30T10:46:14Z","0","POINT (-73.9959353 40.7230647)"
25 "05eefdfd-eece-4b75-b983-605c7550a79e","US","10012","BROADWAY","648","","","2024-09-10T17:59:31Z","0","POINT (-73.9955221 40.7266978)"
26 "062c5f30-b919-491c-847c-c046603f6f4f","US","10013","MOTT ST","67","","","2024-09-21T00:12:48Z","6","POINT (-73.9982654 40.7161944)"
27 "068ed55c-f9dc-4b82-b931-7d26b54929d2","US","10013","N MOORE ST","43","","","2024-10-02T07:25:05Z","0","POINT (-74.0082641 40.7200255)"
28 "06b7f9d4-be62-4f8b-bb2a-614a7c6dbe8f","US","10013","RENWICK ST","15","","","2024-10-13T14:38:22Z","0","POINT (-74.0086515 40.7248328)"
29 "06ea3554-26cc-4954-a81f-736e51b626db","US","10013","BAXTER ST","89","","","2024-10-24T21:51:39Z","0","POINT (-73.9996297 40.7168333)"
30 "07193249-32ce-4761-9b50-d0a9bdf2b9dc","US","10013","CORTLANDT ALY","41","","","2024-11-04T04:04:56Z","7","POINT (-74.0014248 40.7187065)"
<system-reminder>Showed lines 1-30 of 1057. Re-call Read with offset=31 to continue, or raise limit.</system-reminder>
0:19
I can see the CSV structure. Let me write a Python script to convert it to GeoParquet with proper types. The columns are: - id: string - country: string - postcode: string - street: string - number: string - unit: string - postal_city: string - recorded_at: timestamp[us] - unit_count: int32 - geometry_wkt: WKT geometry (POINT in EPSG:4326) I need to: 1. Read the CSV 2. Parse geometry from WKT to shapely geometry 3. Set types: recorded_at as timestamp[us], unit_count as int32, others as string 4. Write to GeoParquet with EPSG:4326 CRS Let me write the script.
0:19
Write
/work/solve.py
content · 36 lines · py
import pandas as pd
import geopandas as gpd
from shapely import wkt
import pyarrow as pa
# Read the CSV
df = pd.read_csv('/work/nyc_addresses.csv')
# Convert geometry from WKT
df['geometry'] = df['geometry_wkt'].apply(wkt.loads)
# Create GeoDataFrame
gdf = gpd.GeoDataFrame(df, geometry='geometry', crs='EPSG:4326')
# Drop the WKT column
gdf = gdf.drop(columns=['geometry_wkt'])
# Ensure column types
# string columns (already strings from CSV)
string_cols = ['id', 'country', 'postcode', 'street', 'number', 'unit', 'postal_city']
for col in string_cols:
gdf[col] = gdf[col].astype(str)
# unit_count as int32
gdf['unit_count'] = gdf['unit_count'].astype('int32')
# recorded_at as timestamp[us]
gdf['recorded_at'] = pd.to_datetime(gdf['recorded_at'])
# Write to GeoParquet
gdf.to_parquet('/work/addresses.geoparquet', index=False, engine='pyarrow')
print("Done! Written addresses.geoparquet")
print(f"CRS: {gdf.crs}")
print(f"dtypes:\n{gdf.dtypes}")
print(f"Shape: {gdf.shape}")Wrote /work/solve.py (991 chars).
0:26
Let me run the script and verify the output.
0:26
Bash
cd /work && python solve.py
Done! Written addresses.geoparquet CRS: EPSG:4326 dtypes: id str country str postcode str street str number str unit str postal_city str recorded_at datetime64[us, UTC] unit_count int32 geometry geometry dtype: object Shape: (1056, 10)
0:32
Let me verify the file was created and also test the queries mentioned by the user.
0:32
0:32
Bash
cd /work && python -c "
cd /work && python -c "
import geopandas as gpd
gdf = gpd.read_parquet('addresses.geoparquet')
print('Records with recorded_at > 2024-01-01:', len(gdf[gdf['recorded_at'] > '2024-01-01']))
print('SUM(unit_count):', gdf['unit_count'].sum())
print()
print('Schema:')
print(gdf.dtypes)
print()
print('First 3 rows:')
print(gdf.head(3))
"
Records with recorded_at > 2024-01-01: 1055
SUM(unit_count): 1566
Schema:
id str
country str
postcode str
street str
number str
unit str
postal_city str
recorded_at datetime64[us, UTC]
unit_count int32
geometry geometry
dtype: object
First 3 rows:
id ... geometry
0 0005eda0-2540-4e36-bc81-dfb52e323d99 ... POINT (-73.99223 40.71616)
1 00587e13-6253-485d-9258-e47d43af7559 ... POINT (-73.99833 40.71204)
2 0070f126-d36a-43b3-b767-a8fbb7156602 ... POINT (-74.0015 40.70733)
[3 rows x 10 columns]
0:41
Everything works correctly. Let me also verify the GeoParquet file exists and check its size.
0:41