saturn

/home/coolhand/html/datavis/data_trove/cache/wild/nyc_311_sample.json 1,000 rows sample n=1,000 seed 42 2026-05-01T18:06:31+00:00

Overview

Source/home/coolhand/html/datavis/data_trove/cache/wild/nyc_311_sample.json
Total rows1,000
Profiled sample1,000
Columns47
Generated2026-05-01T18:06:31+00:00

Insights opt-in

Model-generated narrative. These are opinions, not facts — the stats below are what saturn measured. Generated by: anthropic:claude-opus-4-7.

Errors during insight pass (48)
  • dataset:__global__:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacHybUkPt8TZS3rNbkuo'}
  • column:unique_key:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacHybvnSR3719UbPDsLx'}
  • column:created_date:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacHycRJRpoBUs9jkZAvw'}
  • column:agency:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacHycvK8Yw2Xie8Rrjky'}
  • column:agency_name:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacHydQ5vKUpp1guPu3rn'}
  • column:complaint_type:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacHydwq6b4anKWgXs44h'}
  • column:descriptor:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacHyePcnJnscRMg2aR4F'}
  • column:location_type:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacHyestUoJ3KBq4eBp34'}
  • column:incident_zip:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacHyfQPYaAUcnD8DtDFu'}
  • column:incident_address:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacHyfuPyKtpfaNaoLxDM'}
  • column:street_name:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacHygPfmqZap7mKaXhbw'}
  • column:cross_street_1:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacHyiySi6ky7RAstMahN'}
  • column:cross_street_2:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacHyjmKTKDPSRV3wd1Sx'}
  • column:intersection_street_1:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacHymEsn6fon7hdzRwDq'}
  • column:intersection_street_2:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacHyoH9z77qD7fobSgmH'}
  • column:address_type:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacHyojShXMxrA37azKJs'}
  • column:city:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacHypGCFPqNRvMrhqSWD'}
  • column:landmark:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacHypovs8V4tQn2a8YdB'}
  • column:status:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacHyqGxgJFgWMWCDsP9e'}
  • column:community_board:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacHyqmUpfj4tcxXXaHiR'}
  • column:council_district:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacHyrDGPM8w2wPqX7Jn7'}
  • column:police_precinct:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacHyrdKjMi1zsp396nMf'}
  • column:bbl:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacHys7b8bnzSh7HyA1XV'}
  • column:borough:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacHysdr4Lnvut5hLeJpM'}
  • column:x_coordinate_state_plane:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacHyt8rRBr3NczFe2eWc'}
  • column:y_coordinate_state_plane:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacHyterxFukEvnGcvHeq'}
  • column:open_data_channel_type:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacHyuBN4HbTPTdM3EiDY'}
  • column:park_facility_name:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacHyujrHhXrYC3aAhnbG'}
  • column:park_borough:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacHyvGMAvNs68XHLy4KJ'}
  • column:latitude:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacHyvm7frHAfwJDJicqg'}
  • column:longitude:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacHywHcWsT8TJi3qwqL4'}
  • column:location:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacHywkeH7SezYKJ63D9t'}
  • column::@computed_region_f5dn_yrer:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacHyxEfVXqridGqSmcHs'}
  • column::@computed_region_yeji_bk3q:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacHyxv6V7YAgjhNYH6yY'}
  • column::@computed_region_sbqj_enih:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacHyyXoJ6Bf9EUTTgj9Q'}
  • column::@computed_region_92fq_4b7q:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacHyz4YywN7fedjPvs5B'}
  • column:descriptor_2:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacHyzbnwbh3zwR9u3wUT'}
  • column:resolution_description:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacHz15Ke4zcGPSYUS9LB'}
  • column:resolution_action_updated_date:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacHz1kFUyL2Q9v4ePfLk'}
  • column:closed_date:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacHz3LkRmB5VFLAEzHyC'}
  • column:taxi_pick_up_location:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacHz3tjRg7UZHibM7EXG'}
  • column:vehicle_type:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacHz4PWAaUyPmDBGyYUj'}
  • column:facility_type:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacHz4uG1mXeukQbPR8x1'}
  • column:taxi_company_borough:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacHz5TVRJjpbBiByy5hU'}
  • column:bridge_highway_name:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacHzAJwkU47mx2YnpcWZ'}
  • column:bridge_highway_direction:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacHzAxPbYW1K8jo6XYvN'}
  • column:road_ramp:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacHzCfpxU8N4GfrFvDz5'}
  • column:bridge_highway_segment:anthropic:claude-opus-4-7: BadRequestError — Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits.'}, 'request_id': 'req_011CacHzDALmW9dz7HAA8wRE'}

unique_key categorical

1000 singleton categories
rows1,000
null0 (0.0%)
unique1,000
top_value67519092
top_rate1.00e-03
cardinality1,000
entropy9.966
entropy_ratio1.000
Top values (rank 1–20)
  1. 67519092 — 1
  2. 67525266 — 1
  3. 67525239 — 1
  4. 67521094 — 1
  5. 67519046 — 1
  6. 67519060 — 1
  7. 67524218 — 1
  8. 67524221 — 1
  9. 67520253 — 1
  10. 67519078 — 1
  11. 67522157 — 1
  12. 67521098 — 1
  13. 67524234 — 1
  14. 67523183 — 1
  15. 67519091 — 1
  16. 67524231 — 1
  17. 67520104 — 1
  18. 67521095 — 1
  19. 67522127 — 1
  20. 67523186 — 1

created_date categorical

889 singleton categories
rows1,000
null0 (0.0%)
unique939
top_value2026-01-17T23:49:56.000
top_rate9.00e-03
cardinality939
entropy9.828
entropy_ratio0.995
Top values (rank 1–20)
  1. 2026-01-17T23:49:56.000 — 9
  2. 2026-01-17T23:43:55.000 — 4
  3. 2026-01-18T01:11:10.000 — 3
  4. 2026-01-17T23:04:06.000 — 3
  5. 2026-01-18T01:25:57.000 — 2
  6. 2026-01-18T01:25:16.000 — 2
  7. 2026-01-18T01:18:23.000 — 2
  8. 2026-01-18T01:12:27.000 — 2
  9. 2026-01-18T01:08:57.000 — 2
  10. 2026-01-18T01:07:55.000 — 2
  11. 2026-01-18T01:04:36.000 — 2
  12. 2026-01-18T01:02:54.000 — 2
  13. 2026-01-18T00:53:20.000 — 2
  14. 2026-01-18T00:47:20.000 — 2
  15. 2026-01-18T00:38:56.000 — 2
  16. 2026-01-18T00:35:43.000 — 2
  17. 2026-01-18T00:35:09.000 — 2
  18. 2026-01-18T00:31:54.000 — 2
  19. 2026-01-18T00:28:06.000 — 2
  20. 2026-01-18T00:26:25.000 — 2

agency categorical

rows1,000
null0 (0.0%)
unique11
top_valueNYPD
top_rate0.880
cardinality11
entropy0.772
entropy_ratio0.223
Top values (rank 1–20)
  1. NYPD — 880
  2. HPD — 74
  3. DOHMH — 13
  4. DOT — 11
  5. TLC — 6
  6. DSNY — 6
  7. DHS — 2
  8. OOS — 2
  9. DCWP — 2
  10. DPR — 2
  11. DEP — 2

agency_name categorical

rows1,000
null0 (0.0%)
unique11
top_valueNew York City Police Department
top_rate0.880
cardinality11
entropy0.772
entropy_ratio0.223
Top values (rank 1–20)
  1. New York City Police Department — 880
  2. Department of Housing Preservation and Development — 74
  3. Department of Health and Mental Hygiene — 13
  4. Department of Transportation — 11
  5. Taxi and Limousine Commission — 6
  6. Department of Sanitation — 6
  7. Department of Homeless Services — 2
  8. Office of the Sheriff — 2
  9. Department of Consumer and Worker Protection — 2
  10. Department of Parks and Recreation — 2
  11. Department of Environmental Protection — 2

complaint_type categorical

rows1,000
null0 (0.0%)
unique45
top_valueNoise - Residential
top_rate0.393
cardinality45
entropy2.935
entropy_ratio0.534
Top values (rank 1–20)
  1. Noise - Residential — 393
  2. Illegal Parking — 197
  3. Noise - Commercial — 148
  4. Blocked Driveway — 55
  5. HEAT/HOT WATER — 49
  6. Noise - Street/Sidewalk — 44
  7. Noise - Vehicle — 17
  8. UNSANITARY CONDITION — 12
  9. Street Condition — 7
  10. Non-Emergency Police Matter — 7
  11. Smoking or Vaping — 5
  12. Abandoned Vehicle — 5
  13. Animal-Abuse — 5
  14. Rodent — 4
  15. Encampment — 4
  16. Taxi Complaint — 3
  17. Dirty Condition — 3
  18. PAINT/PLASTER — 3
  19. GENERAL — 3
  20. Drinking — 2

descriptor categorical

rows1,000
null0 (0.0%)
unique71
top_valueLoud Music/Party
top_rate0.427
cardinality71
entropy3.540
entropy_ratio0.576
Top values (rank 1–20)
  1. Loud Music/Party — 427
  2. Banging/Pounding — 114
  3. Blocked Hydrant — 79
  4. No Access — 45
  5. Posted Parking Sign Violation — 42
  6. Loud Talking — 36
  7. ENTIRE BUILDING — 35
  8. Blocked Sidewalk — 21
  9. Commercial Overnight Parking — 20
  10. APARTMENT ONLY — 14
  11. Car/Truck Music — 13
  12. Double Parked Blocking Traffic — 13
  13. Loud Television — 10
  14. Partial Access — 10
  15. PESTS — 10
  16. Blocked Crosswalk — 9
  17. Pothole — 6
  18. Allowed in Smoke Free Area — 5
  19. With License Plate — 5
  20. No Shelter — 5

location_type categorical

rows1,000
null14 (1.4%)
unique20
top_valueResidential Building/House
top_rate0.402
cardinality20
entropy2.237
entropy_ratio0.518
Top values (rank 1–20)
  1. Residential Building/House — 396
  2. Street/Sidewalk — 324
  3. Club/Bar/Restaurant — 91
  4. RESIDENTIAL BUILDING — 74
  5. Store/Commercial — 60
  6. Street — 8
  7. Residential Building — 7
  8. Sidewalk — 5
  9. 3+ Family Apartment Building — 3
  10. House and Store — 3
  11. 3+ Family Apt. Building — 2
  12. Business — 2
  13. Subway — 2
  14. Other — 2
  15. Park/Playground — 2
  16. 1-2 Family Mixed Use Building — 1
  17. Restaurant/Bar/Deli/Bakery — 1
  18. Bridge — 1
  19. Taxi — 1
  20. 1-2 Family Dwelling — 1

incident_zip categorical

rows1,000
null3 (0.3%)
unique146
top_value10011
top_rate0.042
cardinality146
entropy6.696
entropy_ratio0.931
Top values (rank 1–20)
  1. 10011 — 42
  2. 11421 — 35
  3. 11385 — 29
  4. 10463 — 22
  5. 10031 — 22
  6. 11368 — 21
  7. 10456 — 20
  8. 10009 — 19
  9. 10462 — 17
  10. 10002 — 16
  11. 11206 — 15
  12. 11212 — 15
  13. 11226 — 14
  14. 11375 — 14
  15. 10012 — 14
  16. 11373 — 14
  17. 10461 — 13
  18. 10452 — 12
  19. 10468 — 12
  20. 10034 — 12

incident_address categorical

664 singleton categories
rows1,000
null5 (0.5%)
unique776
top_value126 WEST 13 STREET
top_rate0.031
cardinality776
entropy9.321
entropy_ratio0.971
Top values (rank 1–20)
  1. 126 WEST 13 STREET — 31
  2. 60 EAST 93 STREET — 13
  3. 71 LENOX AVENUE — 8
  4. 105 MACDOUGAL STREET — 8
  5. 1465 WASHINGTON AVENUE — 8
  6. 2918 BRUCKNER BOULEVARD — 7
  7. 190 AVENUE OF THE AMERICAS — 5
  8. 235 COURT STREET — 5
  9. 74-03 85 DRIVE — 5
  10. 85 TOMPKINS AVENUE — 5
  11. 1365 5 AVENUE — 4
  12. 112-17 NORTHERN BOULEVARD — 4
  13. 182 NAGLE AVENUE — 4
  14. 108-26 159 STREET — 4
  15. 402 ONDERDONK AVENUE — 4
  16. 465 SENECA AVENUE — 3
  17. 2140 MATTHEWS AVENUE — 3
  18. 28-10 JACKSON AVENUE — 3
  19. 62-11 108 STREET — 3
  20. 499 MYRTLE AVENUE — 3

street_name categorical

371 singleton categories
rows1,000
null5 (0.5%)
unique569
top_valueWEST 13 STREET
top_rate0.031
cardinality569
entropy8.742
entropy_ratio0.955
Top values (rank 1–20)
  1. WEST 13 STREET — 31
  2. EAST 93 STREET — 13
  3. JAMAICA AVENUE — 11
  4. WASHINGTON AVENUE — 11
  5. LENOX AVENUE — 10
  6. MACDOUGAL STREET — 10
  7. BROADWAY — 9
  8. BRUCKNER BOULEVARD — 8
  9. BROOKLYN AVENUE — 7
  10. NORTHERN BOULEVARD — 7
  11. 76 STREET — 7
  12. COURT STREET — 6
  13. EAST 74 STREET — 6
  14. GRAND STREET — 5
  15. BUSHWICK AVENUE — 5
  16. EAST 3 STREET — 5
  17. SENECA AVENUE — 5
  18. 111 AVENUE — 5
  19. AVENUE OF THE AMERICAS — 5
  20. AMSTERDAM AVENUE — 5

cross_street_1 categorical

324 singleton categories
rows1,000
null80 (8.0%)
unique511
top_valueAVENUE OF THE AMERICAS
top_rate0.038
cardinality511
entropy8.574
entropy_ratio0.953
Top values (rank 1–20)
  1. AVENUE OF THE AMERICAS — 35
  2. BLEECKER STREET — 11
  3. AMSTERDAM AVENUE — 11
  4. WEST 113 STREET — 8
  5. HIMROD STREET — 8
  6. 112 STREET — 8
  7. ST PAULS PLACE — 8
  8. DEXTER COURT — 8
  9. EAST TREMONT AVENUE — 7
  10. BROADWAY — 7
  11. BEND — 6
  12. 107 AVENUE — 6
  13. 80 STREET — 6
  14. AVENUE B — 6
  15. 3 AVENUE — 6
  16. EAST 182 STREET — 5
  17. 5 AVENUE — 5
  18. 4 AVENUE — 5
  19. VANDAM STREET — 5
  20. DEAD END — 5

cross_street_2 categorical

321 singleton categories
rows1,000
null79 (7.9%)
unique504
top_value7 AVENUE
top_rate0.039
cardinality504
entropy8.511
entropy_ratio0.948
Top values (rank 1–20)
  1. 7 AVENUE — 36
  2. BROADWAY — 19
  3. MINETTA LANE — 10
  4. DEAD END — 10
  5. 109 AVENUE — 9
  6. EAST 171 STREET — 9
  7. WEST 114 STREET — 8
  8. HARMAN STREET — 8
  9. 75 STREET — 8
  10. EDISON AVENUE — 7
  11. 112 PLACE — 7
  12. BEND — 7
  13. AVENUE D — 6
  14. DITMAS AVENUE — 6
  15. EAST 174 STREET — 6
  16. 10 AVENUE — 6
  17. 3 AVENUE — 6
  18. 1 AVENUE — 6
  19. EAST 170 STREET — 6
  20. BALTIC STREET — 6

intersection_street_1 categorical

319 singleton categories
rows1,000
null85 (8.5%)
unique506
top_valueAVENUE OF THE AMERICAS
top_rate0.038
cardinality506
entropy8.558
entropy_ratio0.953
Top values (rank 1–20)
  1. AVENUE OF THE AMERICAS — 35
  2. BLEECKER STREET — 11
  3. AMSTERDAM AVENUE — 11
  4. WEST 113 STREET — 8
  5. HIMROD STREET — 8
  6. 112 STREET — 8
  7. ST PAULS PLACE — 8
  8. DEXTER COURT — 8
  9. EAST TREMONT AVENUE — 7
  10. BROADWAY — 7
  11. BEND — 6
  12. 5 AVENUE — 6
  13. 107 AVENUE — 6
  14. 80 STREET — 6
  15. AVENUE B — 6
  16. 3 AVENUE — 6
  17. EAST 182 STREET — 5
  18. 4 AVENUE — 5
  19. VANDAM STREET — 5
  20. DEAD END — 5

intersection_street_2 categorical

316 singleton categories
rows1,000
null84 (8.4%)
unique499
top_value7 AVENUE
top_rate0.039
cardinality499
entropy8.495
entropy_ratio0.948
Top values (rank 1–20)
  1. 7 AVENUE — 36
  2. BROADWAY — 19
  3. MINETTA LANE — 10
  4. DEAD END — 10
  5. 109 AVENUE — 9
  6. EAST 171 STREET — 9
  7. WEST 114 STREET — 8
  8. HARMAN STREET — 8
  9. 75 STREET — 8
  10. EDISON AVENUE — 7
  11. 112 PLACE — 7
  12. BEND — 7
  13. AVENUE D — 6
  14. DITMAS AVENUE — 6
  15. EAST 174 STREET — 6
  16. 10 AVENUE — 6
  17. 3 AVENUE — 6
  18. 1 AVENUE — 6
  19. EAST 170 STREET — 6
  20. BALTIC STREET — 6

address_type categorical

top value is 97.2% of rows
rows1,000
null2 (0.2%)
unique4
top_valueADDRESS
top_rate0.972
cardinality4
entropy0.217
entropy_ratio0.108
Top values (rank 1–20)
  1. ADDRESS — 970
  2. INTERSECTION — 19
  3. BLOCKFACE — 7
  4. PLACE — 2

city categorical

rows1,000
null21 (2.1%)
unique36
top_valueBROOKLYN
top_rate0.255
cardinality36
entropy3.282
entropy_ratio0.635
Top values (rank 1–20)
  1. BROOKLYN — 250
  2. NEW YORK — 249
  3. BRONX — 198
  4. WOODHAVEN — 35
  5. JAMAICA — 29
  6. RIDGEWOOD — 29
  7. CORONA — 20
  8. ASTORIA — 14
  9. ELMHURST — 14
  10. FOREST HILLS — 11
  11. STATEN ISLAND — 11
  12. SOUTH OZONE PARK — 11
  13. OZONE PARK — 9
  14. SOUTH RICHMOND HILL — 9
  15. REGO PARK — 9
  16. JACKSON HEIGHTS — 9
  17. RICHMOND HILL — 7
  18. COLLEGE POINT — 6
  19. QUEENS — 6
  20. WOODSIDE — 6

landmark categorical

335 singleton categories
rows1,000
null105 (10.5%)
unique515
top_valueWEST 13 STREET
top_rate0.035
cardinality515
entropy8.603
entropy_ratio0.955
Top values (rank 1–20)
  1. WEST 13 STREET — 31
  2. JAMAICA AVENUE — 11
  3. WASHINGTON AVENUE — 11
  4. LENOX AVENUE — 10
  5. MAC DOUGAL STREET — 10
  6. BRUCKNER BOULEVARD — 8
  7. BROADWAY — 8
  8. BROOKLYN AVENUE — 7
  9. NORTHERN BOULEVARD — 7
  10. 76 STREET — 7
  11. COURT STREET — 6
  12. EAST 74 STREET — 6
  13. GRAND STREET — 5
  14. BUSHWICK AVENUE — 5
  15. EAST 3 STREET — 5
  16. SENECA AVENUE — 5
  17. 111 AVENUE — 5
  18. AVENUE OF THE AMERICAS — 5
  19. MYRTLE AVENUE — 5
  20. 90 STREET — 5

status categorical

rows1,000
null0 (0.0%)
unique3
top_valueClosed
top_rate0.610
cardinality3
entropy1.260
entropy_ratio0.795
Top values (rank 1–20)
  1. Closed — 610
  2. In Progress — 305
  3. Open — 85

community_board categorical

rows1,000
null0 (0.0%)
unique65
top_value02 MANHATTAN
top_rate0.056
cardinality65
entropy5.610
entropy_ratio0.932
Top values (rank 1–20)
  1. 02 MANHATTAN — 56
  2. 09 QUEENS — 48
  3. 03 MANHATTAN — 38
  4. 05 QUEENS — 38
  5. 12 QUEENS — 30
  6. 03 BRONX — 29
  7. 12 MANHATTAN — 29
  8. 10 MANHATTAN — 28
  9. 08 BRONX — 28
  10. 09 MANHATTAN — 28
  11. 17 BROOKLYN — 27
  12. 10 QUEENS — 27
  13. 03 QUEENS — 25
  14. 01 BROOKLYN — 24
  15. 06 QUEENS — 24
  16. 11 BROOKLYN — 23
  17. 04 BROOKLYN — 22
  18. 09 BRONX — 21
  19. 04 QUEENS — 20
  20. 10 BRONX — 20

council_district categorical

rows1,000
null9 (0.9%)
unique51
top_value03
top_rate0.057
cardinality51
entropy5.412
entropy_ratio0.954
Top values (rank 1–20)
  1. 03 — 56
  2. 32 — 48
  3. 02 — 39
  4. 34 — 38
  5. 13 — 36
  6. 10 — 36
  7. 07 — 33
  8. 16 — 32
  9. 09 — 32
  10. 28 — 30
  11. 01 — 28
  12. 11 — 26
  13. 30 — 25
  14. 21 — 25
  15. 17 — 24
  16. 14 — 24
  17. 47 — 24
  18. 41 — 23
  19. 35 — 22
  20. 18 — 22

police_precinct categorical

rows1,000
null0 (0.0%)
unique76
top_valuePrecinct 6
top_rate0.050
cardinality76
entropy5.847
entropy_ratio0.936
Top values (rank 1–20)
  1. Precinct 6 — 50
  2. Precinct 102 — 48
  3. Precinct 104 — 38
  4. Precinct 42 — 29
  5. Precinct 50 — 28
  6. Precinct 67 — 27
  7. Precinct 106 — 27
  8. Precinct 30 — 26
  9. Precinct 110 — 24
  10. Precinct 112 — 24
  11. Precinct 62 — 23
  12. Precinct 115 — 23
  13. Precinct 83 — 22
  14. Precinct 43 — 21
  15. Precinct 9 — 20
  16. Precinct 103 — 20
  17. Precinct 45 — 20
  18. Precinct 49 — 19
  19. Precinct 34 — 19
  20. Precinct 32 — 18

bbl categorical

606 singleton categories
rows1,000
null55 (5.5%)
unique719
top_value1006080026
top_rate0.033
cardinality719
entropy9.189
entropy_ratio0.968
Top values (rank 1–20)
  1. 1006080026 — 31
  2. 3045950215 — 13
  3. 1018230033 — 8
  4. 1005420048 — 8
  5. 2029020036 — 8
  6. 2054190122 — 7
  7. 4017067501 — 7
  8. 1005040011 — 5
  9. 3003960004 — 5
  10. 4088380065 — 5
  11. 3017400001 — 5
  12. 1016180001 — 4
  13. 1022170047 — 4
  14. 4101460051 — 4
  15. 1021700112 — 4
  16. 4034270030 — 4
  17. 4034300001 — 3
  18. 2043230014 — 3
  19. 2039437501 — 3
  20. 2024090096 — 3

borough categorical

rows1,000
null0 (0.0%)
unique5
top_valueQUEENS
top_rate0.274
cardinality5
entropy2.057
entropy_ratio0.886
Top values (rank 1–20)
  1. QUEENS — 274
  2. MANHATTAN — 258
  3. BROOKLYN — 254
  4. BRONX — 203
  5. STATEN ISLAND — 11

x_coordinate_state_plane categorical

643 singleton categories
rows1,000
null7 (0.7%)
unique763
top_value984721
top_rate0.031
cardinality763
entropy9.292
entropy_ratio0.970
Top values (rank 1–20)
  1. 984721 — 31
  2. 1004501 — 13
  3. 997870 — 8
  4. 984032 — 8
  5. 1010885 — 8
  6. 1031969 — 7
  7. 983238 — 5
  8. 985877 — 5
  9. 1020825 — 5
  10. 999077 — 5
  11. 998703 — 4
  12. 1023829 — 4
  13. 1005224 — 4
  14. 1041463 — 4
  15. 1008285 — 4
  16. 1008323 — 3
  17. 995971 — 3
  18. 1022177 — 3
  19. 1007992 — 3
  20. 1001276 — 3

y_coordinate_state_plane categorical

651 singleton categories
rows1,000
null7 (0.7%)
unique768
top_value207809
top_rate0.031
cardinality768
entropy9.304
entropy_ratio0.971
Top values (rank 1–20)
  1. 207809 — 31
  2. 180649 — 13
  3. 230926 — 8
  4. 205111 — 8
  5. 244212 — 8
  6. 242900 — 7
  7. 203929 — 5
  8. 189205 — 5
  9. 191901 — 5
  10. 193110 — 5
  11. 230311 — 4
  12. 215511 — 4
  13. 253267 — 4
  14. 192497 — 4
  15. 197077 — 4
  16. 196526 — 3
  17. 250862 — 3
  18. 240061 — 3
  19. 211978 — 3
  20. 207649 — 3

open_data_channel_type categorical

rows1,000
null0 (0.0%)
unique4
top_valueONLINE
top_rate0.466
cardinality4
entropy1.589
entropy_ratio0.794
Top values (rank 1–20)
  1. ONLINE — 466
  2. MOBILE — 288
  3. PHONE — 236
  4. UNKNOWN — 10

park_facility_name categorical

top value is 99.9% of rows
rows1,000
null0 (0.0%)
unique2
top_valueUnspecified
top_rate0.999
cardinality2
entropy0.011
entropy_ratio0.011
Top values (rank 1–20)
  1. Unspecified — 999
  2. Flushing Meadows Corona Park — 1

park_borough categorical

rows1,000
null0 (0.0%)
unique5
top_valueQUEENS
top_rate0.274
cardinality5
entropy2.057
entropy_ratio0.886
Top values (rank 1–20)
  1. QUEENS — 274
  2. MANHATTAN — 258
  3. BROOKLYN — 254
  4. BRONX — 203
  5. STATEN ISLAND — 11

latitude categorical

655 singleton categories
rows1,000
null7 (0.7%)
unique770
top_value40.73706433046593
top_rate0.031
cardinality770
entropy9.308
entropy_ratio0.971
Top values (rank 1–20)
  1. 40.73706433046593 — 31
  2. 40.662493333971206 — 13
  3. 40.800504000346805 — 8
  4. 40.72965899371875 — 8
  5. 40.83694066292417 — 8
  6. 40.83325085108711 — 7
  7. 40.726414636772915 — 5
  8. 40.68600063896156 — 5
  9. 40.693325110944265 — 5
  10. 40.696706691928384 — 5
  11. 40.79881467021513 — 4
  12. 40.75811580959723 — 4
  13. 40.861809211135316 — 4
  14. 40.694851633900804 — 4
  15. 40.70757495380374 — 4
  16. 40.7060624863299 — 3
  17. 40.85515165955753 — 3
  18. 40.82555561649529 — 3
  19. 40.74849081688869 — 3
  20. 40.73652935637317 — 3

longitude categorical

655 singleton categories
rows1,000
null7 (0.7%)
unique770
top_value-73.99830041620608
top_rate0.031
cardinality770
entropy9.308
entropy_ratio0.971
Top values (rank 1–20)
  1. -73.99830041620608 — 31
  2. -73.9270067970956 — 13
  3. -73.95080595870716 — 8
  4. -74.00078655646078 — 8
  5. -73.90374441298103 — 8
  6. -73.82755893872277 — 7
  7. -74.00365117608368 — 5
  8. -73.994133534454 — 5
  9. -73.86810717317749 — 5
  10. -73.94652977407227 — 5
  11. -73.94779857268328 — 4
  12. -73.85713563386481 — 4
  13. -73.92417422718809 — 4
  14. -73.79367980321378 — 4
  15. -73.91330906170826 — 4
  16. -73.91317397090971 — 3
  17. -73.86289896839915 — 3
  18. -73.91421404014056 — 3
  19. -73.93855184851218 — 3
  20. -73.85143729064244 — 3

location unknown

no profiler for kind=unknown
rows1,000
null0 (0.0%)

:@computed_region_f5dn_yrer categorical

rows1,000
null7 (0.7%)
unique62
top_value57
top_rate0.056
cardinality62
entropy5.591
entropy_ratio0.939
Top values (rank 1–20)
  1. 57 — 56
  2. 46 — 48
  3. 70 — 38
  4. 54 — 37
  5. 41 — 30
  6. 34 — 29
  7. 47 — 29
  8. 18 — 28
  9. 48 — 28
  10. 37 — 28
  11. 61 — 27
  12. 62 — 27
  13. 65 — 25
  14. 36 — 24
  15. 1 — 23
  16. 42 — 22
  17. 58 — 21
  18. 40 — 21
  19. 66 — 20
  20. 43 — 20

:@computed_region_yeji_bk3q categorical

rows1,000
null7 (0.7%)
unique5
top_value3
top_rate0.271
cardinality5
entropy2.054
entropy_ratio0.885
Top values (rank 1–20)
  1. 3 — 269
  2. 4 — 266
  3. 2 — 254
  4. 5 — 193
  5. 1 — 11

:@computed_region_sbqj_enih categorical

rows1,000
null7 (0.7%)
unique75
top_value3
top_rate0.050
cardinality75
entropy5.846
entropy_ratio0.939
Top values (rank 1–20)
  1. 3 — 50
  2. 60 — 48
  3. 62 — 37
  4. 25 — 29
  5. 33 — 28
  6. 40 — 27
  7. 64 — 27
  8. 19 — 26
  9. 68 — 23
  10. 37 — 23
  11. 73 — 23
  12. 53 — 22
  13. 26 — 21
  14. 70 — 21
  15. 61 — 20
  16. 28 — 20
  17. 32 — 19
  18. 5 — 19
  19. 22 — 19
  20. 20 — 18

:@computed_region_92fq_4b7q categorical

rows1,000
null7 (0.7%)
unique51
top_value10
top_rate0.064
cardinality51
entropy5.376
entropy_ratio0.948
Top values (rank 1–20)
  1. 10 — 64
  2. 34 — 54
  3. 30 — 40
  4. 36 — 36
  5. 32 — 36
  6. 12 — 35
  7. 39 — 35
  8. 46 — 34
  9. 23 — 33
  10. 42 — 28
  11. 50 — 27
  12. 21 — 27
  13. 43 — 27
  14. 40 — 25
  15. 28 — 25
  16. 48 — 24
  17. 45 — 23
  18. 29 — 22
  19. 17 — 22
  20. 35 — 21

descriptor_2 categorical

27 singleton categories 88.2% null
rows1,000
null882 (88.2%)
unique43
top_valueNO HEAT
top_rate0.280
cardinality43
entropy4.376
entropy_ratio0.807
Top values (rank 1–20)
  1. NO HEAT — 33
  2. NO HEAT AND NO HOT WATER — 10
  3. N/A — 9
  4. NO HOT WATER — 7
  5. Cannabis Smoking or Vaping — 5
  6. ROACHES — 4
  7. Unsafe Driving - Non-Passenger — 3
  8. Dog — 3
  9. OTHER — 3
  10. Not Cleaned by Property Owner — 2
  11. Parked In Front Of Fire Hydrant — 2
  12. Operating Improperly — 2
  13. AT WALL OR CEILING — 2
  14. FLIES — 2
  15. BROKEN OR MISSING — 2
  16. MISSING OR INADEQUATE CANS/LID — 2
  17. Loose or Improperly Stored Garbage or Food — 1
  18. Droppings — 1
  19. Fare/Tip Complaint — 1
  20. Waste — 1

resolution_description categorical

30.7% null
rows1,000
null307 (30.7%)
unique16
top_valueThe New York City Police Department responded to the complaint and their investigation determined that no criminal violation existed. The condition was corrected without the need to issue a summons or effect an arrest. If the problem persists, please contact 311 to create another complaint. If possible, provide contact information so responding officers may reach out to you for more details. If necessary, your complaint may be referred to your local precinct's special operations units (Quality of Life, etc.). Thank you for your attention to this matter. We count on New Yorkers like yourself to maintain a safe City, so please let us know if you see other conditions that require our attention.
top_rate0.354
cardinality16
entropy2.777
entropy_ratio0.694
Top values (rank 1–20)
  1. The New York City Police Department responded to the complaint and their investigation determined that no criminal violation existed. The condition was corrected without the need to issue a summons or effect an arrest. If the problem persists, please contact 311 to create another complaint. If possible, provide contact information so responding officers may reach out to you for more details. If necessary, your complaint may be referred to your local precinct's special operations units (Quality of Life, etc.). Thank you for your attention to this matter. We count on New Yorkers like yourself to maintain a safe City, so please let us know if you see other conditions that require our attention. — 245
  2. The New York City Police Department responded to the complaint and with the information available observed no evidence of a criminal violation at that time. If the problem persists, please contact 311 to create another complaint. If possible, provide contact information so responding officers may reach out to you for more details. If necessary, your complaint may be referred to your local precinct's special operations units (Quality of Life, etc.). We count on New Yorkers like yourself to maintain a safe City, so please let us know if you see other conditions that require our attention. — 161
  3. The New York City Police Department responded to the complaint and their investigation determined that a violation of law occurred. Police issued a summons in response to the complaint. Thank you for attention to this matter. We count on New Yorkers like yourself to maintain a safe City, so please let us know if you see other conditions that require our attention. — 68
  4. The New York City Police Department responded to the complaint but officers were unable to gain entry into the premises. If the problem persists, please contact 311 to create another complaint and ensure that contact information (e.g., buzzer number, phone number, etc.) is available to assist the responding officers in gaining entry to properly investigate the complaint. We count on New Yorkers like yourself to maintain a safe City, so please let us know if you see other conditions that require our attention. — 50
  5. The following complaint conditions are still open. HPD has already attempted to notify the property owner that the condition exists; the tenant should provide access for the owner to make the repair. HPD may attempt to contact the tenant by phone to verify the correction of the condition or an HPD Inspector may attempt to conduct an inspection. — 44
  6. The New York City Police Department responded to the complaint and their investigation determined that police action was not necessary. If the problem persists, please contact 311 to create another complaint. If possible, provide contact information so responding officers may reach out to you for more details. We count on New Yorkers like yourself to maintain a safe City, so please let us know if you see other conditions that require our attention. — 40
  7. The New York City Police Department responded to the complaint and observed no criminal violation upon their arrival. If the problem persists, please contact 311 to create another complaint. If possible, provide contact information so responding officers may reach out to you for more details. We count on New Yorkers like yourself to maintain a safe City, so please let us know if you see other conditions that require our attention. — 31
  8. This complaint is a duplicate of a building-wide condition already reported by another tenant. The original complaint is still open, and HPD may only need to confirm that the condition exists by inspecting one apartment. If we cannot contact the tenant from the original complaint or get access to that apartment, HPD may attempt to contact the person who filed this complaint to verify the correction of the condition or may conduct an inspection of your unit. You can check HPDONLINE to see if a — 29
  9. The Department of Transportation referred this complaint to the appropriate Maintenance Unit for repair. — 6
  10. Your complaint has been received but does not fall under the jurisdiction of the New York City Police Department. Please contact your local precinct for more information, including which City agency your request was referred to. We count on New Yorkers like yourself to maintain a safe City, so please let us know if you see other conditions that require our attention. — 5
  11. The Police Department reviewed your complaint and provided additional information below. — 4
  12. The New York City Police Department responded to the complaint and a report was prepared as part of their investigation. Thank you for attention to this matter. We count on New Yorkers like yourself to maintain a safe City, so please let us know if you see other conditions that require our attention. — 3
  13. The Department of Health and Mental Hygiene has sent official written notification to the Owner/Landlord warning them of potential violations and instructing them to correct the situation. If the situation persists 21 days after your initial complaint, please make a new complaint. — 3
  14. The New York City Police Department responded to the complaint and observed an encampment at the noted location. The complaint has been referred to the Department of Homeless Services (DHS) for further action. DHS will inspect the condition and update your service request with more information. Thank you for attention to this matter. We count on New Yorkers like yourself to maintain a safe City, so please let us know if you see other conditions that require our attention. — 2
  15. Your complaint has been received by the New York City Police Department and assigned to a unit at your local precinct. The responding officers will conduct an assessment of the complaint and may contact you for further information, if you left contact information. Our team is committed to resolving this matter promptly, and we appreciate your contribution to maintaining the well-being of our community. — 1
  16. The New York City Police Department responded to the complaint and their investigation determined another specific tow is required. Please contact the local precinct for more information. Thank you for attention to this matter. We count on New Yorkers like yourself to maintain a safe City, so please let us know if you see other conditions that require our attention. — 1

resolution_action_updated_date categorical

548 singleton categories 30.6% null
rows1,000
null306 (30.6%)
unique585
top_value2026-01-17T00:00:00.000
top_rate0.107
cardinality585
entropy8.673
entropy_ratio0.944
Top values (rank 1–20)
  1. 2026-01-17T00:00:00.000 — 74
  2. 2026-01-18T02:03:44.000 — 2
  3. 2026-01-18T02:04:03.000 — 2
  4. 2026-01-18T02:01:54.000 — 2
  5. 2026-01-18T01:35:08.000 — 2
  6. 2026-01-18T01:41:49.000 — 2
  7. 2026-01-18T01:26:35.000 — 2
  8. 2026-01-18T01:32:28.000 — 2
  9. 2026-01-18T01:25:53.000 — 2
  10. 2026-01-18T01:54:39.000 — 2
  11. 2026-01-18T01:19:59.000 — 2
  12. 2026-01-18T01:09:47.000 — 2
  13. 2026-01-18T01:00:57.000 — 2
  14. 2026-01-18T01:04:36.000 — 2
  15. 2026-01-18T00:58:56.000 — 2
  16. 2026-01-18T01:07:50.000 — 2
  17. 2026-01-18T01:27:34.000 — 2
  18. 2026-01-18T00:46:07.000 — 2
  19. 2026-01-18T00:55:02.000 — 2
  20. 2026-01-18T00:40:32.000 — 2

closed_date categorical

561 singleton categories 39.0% null
rows1,000
null390 (39.0%)
unique585
top_value2026-01-18T00:41:26.000
top_rate4.92e-03
cardinality585
entropy9.169
entropy_ratio0.998
Top values (rank 1–20)
  1. 2026-01-18T00:41:26.000 — 3
  2. 2026-01-18T02:02:35.000 — 2
  3. 2026-01-18T02:03:41.000 — 2
  4. 2026-01-18T01:41:47.000 — 2
  5. 2026-01-18T01:26:28.000 — 2
  6. 2026-01-18T01:45:29.000 — 2
  7. 2026-01-18T01:54:33.000 — 2
  8. 2026-01-18T01:07:46.000 — 2
  9. 2026-01-18T01:27:29.000 — 2
  10. 2026-01-18T00:46:04.000 — 2
  11. 2026-01-18T00:40:28.000 — 2
  12. 2026-01-18T00:55:27.000 — 2
  13. 2026-01-18T00:41:08.000 — 2
  14. 2026-01-18T00:20:14.000 — 2
  15. 2026-01-18T00:37:27.000 — 2
  16. 2026-01-18T00:22:36.000 — 2
  17. 2026-01-18T00:36:52.000 — 2
  18. 2026-01-18T00:17:49.000 — 2
  19. 2026-01-18T00:28:52.000 — 2
  20. 2026-01-18T00:20:55.000 — 2

taxi_pick_up_location categorical

6 singleton categories 99.4% null
rows1,000
null994 (99.4%)
unique6
top_value55 LITTLE WEST 12 STREET, MANHATTAN (NEW YORK), NY, 10014
top_rate0.167
cardinality6
entropy2.585
entropy_ratio1.000
Top values (rank 1–20)
  1. 55 LITTLE WEST 12 STREET, MANHATTAN (NEW YORK), NY, 10014 — 1
  2. JOHN F KENNEDY AIRPORT, QUEENS (JAMAICA) ,NY, 11430 — 1
  3. 11 WATER STREET, BROOKLYN, NY, 11201 — 1
  4. 9 AVENUE AND WEST 43 STREET, MANHATTAN, NY, 10036 — 1
  5. 30 AVENUE AND 33 STREET, QUEENS, NY, 11102 — 1
  6. 30-08 33 STREET, QUEENS (ASTORIA), NY, 11102 — 1

vehicle_type categorical

96.5% null
rows1,000
null965 (96.5%)
unique4
top_valueCar
top_rate0.771
cardinality4
entropy1.097
entropy_ratio0.548
Top values (rank 1–20)
  1. Car — 27
  2. Other — 4
  3. SUV — 3
  4. Van — 1

facility_type categorical

99.0% null top value is 100.0% of rows
rows1,000
null990 (99.0%)
unique1
top_valueN/A
top_rate1.000
cardinality1
entropy-0.000
entropy_ratio0.000
Top values (rank 1–20)
  1. N/A — 10

taxi_company_borough categorical

1 singleton categories 99.9% null top value is 100.0% of rows
rows1,000
null999 (99.9%)
unique1
top_valueBROOKLYN
top_rate1.000
cardinality1
entropy-0.000
entropy_ratio0.000
Top values (rank 1–20)
  1. BROOKLYN — 1

bridge_highway_name categorical

99.7% null
rows1,000
null997 (99.7%)
unique2
top_valueE
top_rate0.667
cardinality2
entropy0.918
entropy_ratio0.918
Top values (rank 1–20)
  1. E — 2
  2. Kosciuszko Br - BQE — 1

bridge_highway_direction categorical

99.7% null
rows1,000
null997 (99.7%)
unique2
top_valueC E Local Downtown & Brooklyn
top_rate0.667
cardinality2
entropy0.918
entropy_ratio0.918
Top values (rank 1–20)
  1. C E Local Downtown & Brooklyn — 2
  2. Queens Bound — 1

road_ramp categorical

1 singleton categories 99.9% null top value is 100.0% of rows
rows1,000
null999 (99.9%)
unique1
top_valueRamp
top_rate1.000
cardinality1
entropy-0.000
entropy_ratio0.000
Top values (rank 1–20)
  1. Ramp — 1

bridge_highway_segment categorical

99.7% null
rows1,000
null997 (99.7%)
unique2
top_valuePlatform
top_rate0.667
cardinality2
entropy0.918
entropy_ratio0.918
Top values (rank 1–20)
  1. Platform — 2
  2. Ramp — 1