Datasets:
Country stringclasses 174
values | City stringlengths 2 30 | AQI Value int64 7 500 | AQI Category stringclasses 6
values | CO AQI Value int64 0 133 | CO AQI Category stringclasses 3
values | Ozone AQI Value int64 0 222 | Ozone AQI Category stringclasses 5
values | NO2 AQI Value int64 0 91 | NO2 AQI Category stringclasses 2
values | PM2.5 AQI Value int64 0 500 | PM2.5 AQI Category stringclasses 6
values | lat float64 -54.8 70.8 | lng float64 -171.75 178 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Russian Federation | Praskoveya | 51 | Moderate | 1 | Good | 36 | Good | 0 | Good | 51 | Moderate | 44.7444 | 44.2031 |
Brazil | Presidente Dutra | 41 | Good | 1 | Good | 5 | Good | 1 | Good | 41 | Good | -5.29 | -44.49 |
Brazil | Presidente Dutra | 41 | Good | 1 | Good | 5 | Good | 1 | Good | 41 | Good | -11.2958 | -41.9869 |
Italy | Priolo Gargallo | 66 | Moderate | 1 | Good | 39 | Good | 2 | Good | 66 | Moderate | 37.1667 | 15.1833 |
Poland | Przasnysz | 34 | Good | 1 | Good | 34 | Good | 0 | Good | 20 | Good | 53.0167 | 20.8833 |
United States of America | Punta Gorda | 54 | Moderate | 1 | Good | 14 | Good | 11 | Good | 54 | Moderate | 16.1005 | -88.8074 |
United States of America | Punta Gorda | 54 | Moderate | 1 | Good | 14 | Good | 11 | Good | 54 | Moderate | 26.8941 | -82.0513 |
Belgium | Puurs | 64 | Moderate | 1 | Good | 29 | Good | 7 | Good | 64 | Moderate | 51.0761 | 4.2803 |
Russian Federation | Pyatigorsk | 54 | Moderate | 1 | Good | 41 | Good | 1 | Good | 54 | Moderate | 44.05 | 43.0667 |
China | Qinzhou | 68 | Moderate | 2 | Good | 68 | Moderate | 1 | Good | 58 | Moderate | 21.95 | 108.6167 |
Netherlands | Raalte | 41 | Good | 1 | Good | 24 | Good | 6 | Good | 41 | Good | 52.3833 | 6.2667 |
France | Raismes | 59 | Moderate | 1 | Good | 30 | Good | 4 | Good | 59 | Moderate | 50.3892 | 3.4858 |
Italy | Ramacca | 55 | Moderate | 1 | Good | 47 | Good | 0 | Good | 55 | Moderate | 37.3833 | 14.7 |
United States of America | Phoenix | 72 | Moderate | 1 | Good | 4 | Good | 23 | Good | 72 | Moderate | 33.5722 | -112.0892 |
Poland | Piaseczno | 28 | Good | 1 | Good | 28 | Good | 2 | Good | 28 | Good | 52.0667 | 21.0167 |
Brazil | Pinheiral | 154 | Unhealthy | 5 | Good | 0 | Good | 13 | Good | 154 | Unhealthy | -22.5128 | -44.0008 |
Colombia | Plato | 67 | Moderate | 1 | Good | 16 | Good | 2 | Good | 67 | Moderate | 9.7919 | -74.7872 |
Romania | Poiana Mare | 62 | Moderate | 1 | Good | 37 | Good | 1 | Good | 62 | Moderate | 43.9333 | 23.0833 |
Russian Federation | Polevskoy | 31 | Good | 1 | Good | 31 | Good | 0 | Good | 17 | Good | 56.45 | 60.1833 |
France | Pontarlier | 56 | Moderate | 1 | Good | 35 | Good | 0 | Good | 56 | Moderate | 46.9061 | 6.3547 |
United States of America | Pontiac | 77 | Moderate | 2 | Good | 22 | Good | 15 | Good | 77 | Moderate | 42.6493 | -83.2878 |
United States of America | Pontiac | 77 | Moderate | 2 | Good | 22 | Good | 15 | Good | 77 | Moderate | 40.8894 | -88.6409 |
Indonesia | Pontianak | 44 | Good | 1 | Good | 15 | Good | 0 | Good | 44 | Good | -0.0206 | 109.3414 |
Brazil | Porecatu | 30 | Good | 1 | Good | 9 | Good | 2 | Good | 30 | Good | -22.7558 | -51.3789 |
Finland | Pori | 30 | Good | 1 | Good | 30 | Good | 1 | Good | 15 | Good | 61.4833 | 21.8 |
South Africa | Port Elizabeth | 79 | Moderate | 3 | Good | 18 | Good | 5 | Good | 79 | Moderate | -33.9581 | 25.6 |
United States of America | Port Neches | 34 | Good | 1 | Good | 19 | Good | 7 | Good | 34 | Good | 29.9765 | -93.9459 |
United Kingdom of Great Britain and Northern Ireland | Port Talbot | 51 | Moderate | 1 | Good | 20 | Good | 5 | Good | 51 | Moderate | 51.5906 | -3.7986 |
United States of America | Portales | 77 | Moderate | 1 | Good | 34 | Good | 0 | Good | 77 | Moderate | 34.1754 | -103.3565 |
United States of America | Post Falls | 61 | Moderate | 1 | Good | 32 | Good | 3 | Good | 61 | Moderate | 47.7213 | -116.9384 |
Brazil | Pouso Alegre | 32 | Good | 1 | Good | 7 | Good | 2 | Good | 32 | Good | -22.2281 | -45.9336 |
Russian Federation | Dalnegorsk | 29 | Good | 0 | Good | 29 | Good | 0 | Good | 25 | Good | 44.55 | 135.5833 |
India | Darbhanga | 247 | Very Unhealthy | 3 | Good | 162 | Unhealthy | 1 | Good | 247 | Very Unhealthy | 26.17 | 85.9 |
United States of America | Dayton | 45 | Good | 1 | Good | 32 | Good | 7 | Good | 45 | Good | 39.7805 | -84.2003 |
United States of America | Dayton | 45 | Good | 1 | Good | 32 | Good | 7 | Good | 45 | Good | 39.2592 | -119.5653 |
United States of America | Dayton | 45 | Good | 1 | Good | 32 | Good | 7 | Good | 45 | Good | 30.0315 | -94.9158 |
Belgium | Deinze | 36 | Good | 1 | Good | 25 | Good | 3 | Good | 36 | Good | 50.9833 | 3.5333 |
Haiti | Delmas | 124 | Unhealthy for Sensitive Groups | 2 | Good | 15 | Good | 5 | Good | 124 | Unhealthy for Sensitive Groups | 18.55 | -72.3 |
United States of America | Deming | 72 | Moderate | 1 | Good | 26 | Good | 2 | Good | 72 | Moderate | 32.2631 | -107.7525 |
United Kingdom of Great Britain and Northern Ireland | Denton | 55 | Moderate | 0 | Good | 32 | Good | 1 | Good | 55 | Moderate | 33.2175 | -97.1418 |
United Kingdom of Great Britain and Northern Ireland | Denton | 55 | Moderate | 0 | Good | 32 | Good | 1 | Good | 55 | Moderate | 53.4554 | -2.1122 |
United States of America | Destin | 31 | Good | 0 | Good | 31 | Good | 0 | Good | 25 | Good | 30.395 | -86.4701 |
India | Dharmapuri | 60 | Moderate | 1 | Good | 31 | Good | 1 | Good | 60 | Moderate | 12.127 | 78.158 |
Philippines | Dipolog | 30 | Good | 1 | Good | 17 | Good | 0 | Good | 30 | Good | 8.5872 | 123.3408 |
Latvia | Dobele | 44 | Good | 1 | Good | 34 | Good | 0 | Good | 44 | Good | 56.6167 | 23.2667 |
United States of America | Grandville | 47 | Good | 1 | Good | 37 | Good | 4 | Good | 47 | Good | 42.9004 | -85.7564 |
Netherlands | Grave | 37 | Good | 0 | Good | 32 | Good | 2 | Good | 37 | Good | 51.7667 | 5.7333 |
United States of America | Green Valley | 44 | Good | 1 | Good | 14 | Good | 8 | Good | 44 | Good | 31.8393 | -111.0009 |
United States of America | Green Valley | 44 | Good | 1 | Good | 14 | Good | 8 | Good | 44 | Good | 39.3414 | -77.24 |
United States of America | Greendale | 58 | Moderate | 2 | Good | 14 | Good | 24 | Good | 58 | Moderate | 42.9371 | -88.0018 |
Colombia | Guamo | 89 | Moderate | 3 | Good | 3 | Good | 6 | Good | 89 | Moderate | 4.0833 | -74.9167 |
Italy | Guardiagrele | 52 | Moderate | 2 | Good | 38 | Good | 7 | Good | 52 | Moderate | 42.2 | 14.2167 |
United Kingdom of Great Britain and Northern Ireland | Guildford | 51 | Moderate | 1 | Good | 25 | Good | 6 | Good | 51 | Moderate | 51.2365 | -0.5703 |
Russian Federation | Gukovo | 38 | Good | 1 | Good | 38 | Good | 0 | Good | 13 | Good | 48.05 | 39.9167 |
United States of America | Hazelwood | 88 | Moderate | 2 | Good | 11 | Good | 20 | Good | 88 | Moderate | 38.7931 | -90.3899 |
Germany | Heddesheim | 54 | Moderate | 1 | Good | 31 | Good | 3 | Good | 54 | Moderate | 49.5053 | 8.6033 |
Germany | Heiligenhaus | 44 | Good | 1 | Good | 28 | Good | 3 | Good | 44 | Good | 51.3167 | 6.9667 |
United Kingdom of Great Britain and Northern Ireland | Hemel Hempstead | 51 | Moderate | 1 | Good | 26 | Good | 6 | Good | 51 | Moderate | 51.7526 | -0.4692 |
United States of America | Hicksville | 67 | Moderate | 2 | Good | 15 | Good | 23 | Good | 67 | Moderate | 40.7637 | -73.5245 |
Germany | Haiger | 49 | Good | 1 | Good | 25 | Good | 3 | Good | 49 | Good | 50.7422 | 8.2039 |
China | Hangzhou | 203 | Very Unhealthy | 5 | Good | 203 | Very Unhealthy | 5 | Good | 151 | Unhealthy | 30.25 | 120.1675 |
Germany | Harrislee | 35 | Good | 0 | Good | 32 | Good | 0 | Good | 35 | Good | 54.7972 | 9.3764 |
United States of America | Harrison | 90 | Moderate | 1 | Good | 25 | Good | 2 | Good | 90 | Moderate | 40.7431 | -74.1531 |
United States of America | Harrison | 90 | Moderate | 1 | Good | 25 | Good | 2 | Good | 90 | Moderate | 41.0236 | -73.7193 |
United States of America | Harrison | 90 | Moderate | 1 | Good | 25 | Good | 2 | Good | 90 | Moderate | 36.2438 | -93.1198 |
United States of America | Harrison | 90 | Moderate | 1 | Good | 25 | Good | 2 | Good | 90 | Moderate | 39.2584 | -84.7868 |
United States of America | Harrison | 90 | Moderate | 1 | Good | 25 | Good | 2 | Good | 90 | Moderate | 44.1935 | -88.2941 |
United States of America | Harrison | 90 | Moderate | 1 | Good | 25 | Good | 2 | Good | 90 | Moderate | 40.6374 | -79.7173 |
Germany | Hasbergen | 36 | Good | 0 | Good | 34 | Good | 1 | Good | 36 | Good | 52.2167 | 7.9167 |
France | Haubourdin | 48 | Good | 1 | Good | 28 | Good | 4 | Good | 48 | Good | 50.6092 | 2.9869 |
United States of America | Taunton | 41 | Good | 1 | Good | 28 | Good | 10 | Good | 41 | Good | 51.019 | -3.1 |
United States of America | Taunton | 41 | Good | 1 | Good | 28 | Good | 10 | Good | 41 | Good | 41.9036 | -71.0943 |
New Zealand | Tauranga | 19 | Good | 0 | Good | 19 | Good | 1 | Good | 17 | Good | -37.6833 | 176.1667 |
Italy | Teano | 47 | Good | 1 | Good | 47 | Good | 1 | Good | 36 | Good | 41.25 | 14.0667 |
India | Tekkali | 155 | Unhealthy | 3 | Good | 82 | Moderate | 1 | Good | 155 | Unhealthy | 18.6057 | 84.2355 |
Brazil | Teodoro Sampaio | 46 | Good | 1 | Good | 9 | Good | 1 | Good | 46 | Good | -22.5328 | -52.1678 |
Mexico | Tequila | 64 | Moderate | 1 | Good | 15 | Good | 2 | Good | 64 | Moderate | 20.8794 | -103.8356 |
Italy | Teramo | 44 | Good | 1 | Good | 44 | Good | 1 | Good | 38 | Good | 42.6589 | 13.7039 |
China | Tianjin | 142 | Unhealthy for Sensitive Groups | 4 | Good | 113 | Unhealthy for Sensitive Groups | 9 | Good | 142 | Unhealthy for Sensitive Groups | 39.1467 | 117.2056 |
Philippines | Toboso | 54 | Moderate | 1 | Good | 20 | Good | 0 | Good | 54 | Moderate | 10.7167 | 123.5167 |
Japan | Tokorozawa | 60 | Moderate | 1 | Good | 44 | Good | 3 | Good | 60 | Moderate | 35.7996 | 139.4686 |
Mexico | Toluca | 166 | Unhealthy | 4 | Good | 8 | Good | 19 | Good | 166 | Unhealthy | 19.2925 | -99.6569 |
Brazil | Itapissuma | 27 | Good | 0 | Good | 23 | Good | 1 | Good | 27 | Good | -7.7764 | -34.8919 |
Brazil | Itarantim | 23 | Good | 1 | Good | 7 | Good | 1 | Good | 23 | Good | -15.66 | -40.0658 |
Brazil | Itumbiara | 31 | Good | 1 | Good | 13 | Good | 0 | Good | 31 | Good | -18.4167 | -49.2167 |
El Salvador | Izalco | 90 | Moderate | 2 | Good | 22 | Good | 9 | Good | 90 | Moderate | 13.7333 | -89.6667 |
Russian Federation | Izberbash | 51 | Moderate | 1 | Good | 38 | Good | 0 | Good | 51 | Moderate | 42.5633 | 47.8636 |
India | Jabalpur | 170 | Unhealthy | 1 | Good | 38 | Good | 0 | Good | 170 | Unhealthy | 23.1667 | 79.9333 |
Brazil | Jaguaquara | 22 | Good | 0 | Good | 9 | Good | 1 | Good | 22 | Good | -13.5308 | -39.9708 |
Poland | Jarocin | 47 | Good | 1 | Good | 27 | Good | 2 | Good | 47 | Good | 51.9667 | 17.5 |
Philippines | Jasaan | 59 | Moderate | 1 | Good | 32 | Good | 0 | Good | 59 | Moderate | 8.65 | 124.75 |
Nigeria | Ilobu | 133 | Unhealthy for Sensitive Groups | 4 | Good | 23 | Good | 3 | Good | 133 | Unhealthy for Sensitive Groups | 7.84 | 4.486 |
Finland | Imatra | 29 | Good | 1 | Good | 29 | Good | 1 | Good | 7 | Good | 61.1833 | 28.7667 |
Brazil | Indaial | 73 | Moderate | 2 | Good | 2 | Good | 8 | Good | 73 | Moderate | -26.8978 | -49.2319 |
Philippines | Indang | 50 | Good | 0 | Good | 24 | Good | 0 | Good | 50 | Good | 14.2 | 120.8833 |
Brazil | Itagi | 25 | Good | 0 | Good | 9 | Good | 1 | Good | 25 | Good | -14.1628 | -40.0058 |
Nigeria | Iseyin | 90 | Moderate | 3 | Good | 18 | Good | 2 | Good | 90 | Moderate | 7.9667 | 3.6 |
Mexico | Isla | 81 | Moderate | 2 | Good | 26 | Good | 3 | Good | 81 | Moderate | 18.0292 | -95.5264 |
Brazil | Itaitinga | 29 | Good | 0 | Good | 20 | Good | 1 | Good | 29 | Good | -3.9689 | -38.5278 |
Brazil | Itapemirim | 44 | Good | 1 | Good | 16 | Good | 1 | Good | 44 | Good | -21.0108 | -40.8339 |
End of preview. Expand in Data Studio
World Air Quality Index by City and Coordinates
A Comprehensive Dataset on Cities, Latitude, Longitude, and Pollution Levels
Dataset Info
- Source: Kaggle
- Original Size: 0.36 MB
- Kaggle Downloads: 11,064
- Files: 1
Files
AQI and Lat Long of Countries.csv
Mirrored from Kaggle
- Downloads last month
- 27