From a 10-row sample across 27 columns.
number_of_residents_who_13number_of_residents_who_6number_of_residents_who+14number_of_residents_who_13number_of_residents_who_6number_of_residents_who+14number_of_residents_who_13Has borough codes (`borough`) — joinable, but needs boundary shapes to draw.
| year | borough | number_of_residents_who | number_of_residents_who_1 | number_of_residents_who_2 | number_of_residents_who_3 | number_of_residents_who_4 | number_of_residents_who_5 | number_of_residents_who_6 | number_of_residents_who_7 | number_of_residents_who_8 | number_of_residents_who_9 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2017 | Bronx | 52 | < 5 | NA | < 5 | NA | 0 | NA | 119 | 13 | 24 |
The machine field names SoQL needs, with the publisher's own description of each.
| Field | Type | Description | Null | Values |
|---|---|---|---|---|
year | categorical | — | 0% | 20182017of 2 |
borough | categorical | — | 0% | QueensBrooklynStaten Islandof 6 |
number_of_residents_who | categorical | — | 0% | 2752127of 10 |
number_of_residents_who_1 | categorical | — | 0% | NA< 50of 3 |
GET /api/datasets/g4tm-nibn GET /api/datasets/g4tm-nibn/quality GET /api/datasets/g4tm-nibn/related GET /api/columns?dataset=g4tm-nibn
boroughnumber_of_residents_who_6yearboroughyearboroughyearboroughyearboroughyear| 2017 | Brooklyn | 27 | 0 | NA | 0 | NA | 0 | NA | NA | NA | NA |
| 2017 | Mahattan | 19 | < 5 | NA | < 5 | NA | 0 | NA | NA | NA | NA |
| 2017 | Queens | 127 | < 5 | NA | 8 | NA | < 5 | NA | NA | NA | NA |
| 2017 | Staten Island | < 5 | 0 | NA | 0 | NA | 0 | NA | NA | NA | NA |
| 2018 | Bronx | 58 | NA | <5 | NA | 6 | NA | <5 | NA | NA | NA |
| 2018 | Brooklyn | 41 | NA | <5 | NA | <5 | NA | <5 | NA | NA | NA |
| 2018 | Manhattan | 22 | NA | <5 | NA | 5 | NA | 0 | NA | NA | NA |
| 2018 | Queens | 106 | NA | 7 | NA | 17 | NA | 0 | NA | NA | NA |
| 2018 | Staten Island | <5 | NA | 0 | NA | 0 | NA | 0 | NA | NA | NA |
Showing 12 of 27 columns. All of them are listed below.
number_of_residents_who_2| categorical |
| — |
| 0% |
NA<57of 4 |
number_of_residents_who_3 | categorical | — | 0% | NA0< 5of 4 |
number_of_residents_who_4 | categorical | — | 0% | NA617of 6 |
number_of_residents_who_5 | categorical | — | 0% | NA0< 5of 3 |
number_of_residents_who_6 | categorical | — | 0% | NA0<5of 3 |
number_of_residents_who_7 | categorical | — | 0% | NA119of 2 |
number_of_residents_who_8 | categorical | — | 0% | NA13of 2 |
number_of_residents_who_9 | categorical | — | 0% | NA24of 2 |
number_of_residents_who_10 | categorical | — | 0% | NA< 5of 2 |
number_of_residents_who_11 | categorical | — | 0% | 0< 5<5of 3 |
number_of_residents_who_12 | categorical | — | 0% | NA0of 2 |
number_of_residents_through | categorical | — | 0% | NA0of 2 |
number_of_residents_who_13 | categorical | — | 0% | NA0of 2 |
number_of_residents_through_1 | categorical | — | 0% | NA0<5of 3 |
number_of_residents_who_14 | categorical | — | 0% | NA0of 2 |
number_of_residents_through_2 | categorical | — | 0% | NA0of 2 |
number_of_residents_who_15 | categorical | — | 0% | 0< 5<5of 4 |
number_of_residents_who_16 | categorical | — | 0% | NA0of 2 |
number_of_residents_who_17 | categorical | — | 0% | NA0of 2 |
number_of_residents_who_18 | categorical | — | 0% | NA0of 2 |
number_of_residents_who_19 | categorical | — | 0% | NA0of 2 |
number_of_residents_who_20 | categorical | — | 0% | NA0of 2 |
number_of_residents_who_21 | categorical | — | 0% | NA0of 2 |