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id
stringlengths
2
72
slug
stringlengths
2
72
name
stringlengths
2
79
country
stringclasses
245 values
region
stringlengths
3
36
timezone
stringclasses
394 values
lat
float64
-54.93
78.2
lng
float64
-179.12
179
population
int64
0
24.9M
sha
shanghai
Shanghai
CN
null
Asia/Shanghai
31.22
121.46
24,874,500
pek
beijing
Beijing
CN
null
Asia/Shanghai
39.91
116.4
18,960,744
shenzhen
shenzhen
Shenzhen
CN
Guangdong
Asia/Shanghai
22.55
114.07
17,494,398
can
guangzhou
Guangzhou
CN
null
Asia/Shanghai
23.12
113.25
16,096,724
kinshasa
kinshasa
Kinshasa
CD
null
Africa/Kinshasa
-4.33
15.31
16,000,000
ist
istanbul
Istanbul
TR
null
Europe/Istanbul
41.01
28.95
15,701,602
lagos
lagos
Lagos
NG
null
Africa/Lagos
6.45
3.39
15,388,000
sgn
hochiminhcity
Ho Chi Minh City
VN
null
Asia/Ho_Chi_Minh
10.82
106.63
14,002,598
chengdu
chengdu
Chengdu
CN
null
Asia/Shanghai
30.67
104.07
13,568,357
lahore
lahore
Lahore
PK
null
Asia/Karachi
31.56
74.35
13,004,135
mumbai
mumbai
Mumbai
IN
null
Asia/Kolkata
19.07
72.88
12,691,836
sao
saopaulo
São Paulo
BR
null
America/Sao_Paulo
-23.55
-46.64
12,400,232
mexicocity
mexicocity
Mexico City
MX
null
America/Mexico_City
19.43
-99.13
12,294,193
karachi
karachi
Karachi
PK
null
Asia/Karachi
24.86
67.01
11,624,219
tianjin
tianjin
Tianjin
CN
null
Asia/Shanghai
39.14
117.18
11,090,314
del
delhi
Delhi
IN
null
Asia/Kolkata
28.65
77.23
11,034,555
wuhan
wuhan
Wuhan
CN
null
Asia/Shanghai
30.58
114.27
10,392,693
moscow
moscow
Moscow
RU
null
Europe/Moscow
55.75
37.62
10,381,222
dhaka
dhaka
Dhaka
BD
null
Asia/Dhaka
23.71
90.41
10,356,500
sel
seoul
Seoul
KR
null
Asia/Seoul
37.57
126.98
10,349,312
tyo
tokyo
Tokyo
JP
null
Asia/Tokyo
35.69
139.69
9,733,276
dongguan
dongguan
Dongguan
CN
Guangdong
Asia/Shanghai
23.02
113.75
9,644,871
cai
cairo
Cairo
EG
null
Africa/Cairo
30.06
31.25
9,606,916
xian
xian
Xi’an
CN
Shaanxi
Asia/Shanghai
34.26
108.93
9,600,000
johannesburg
johannesburg
Johannesburg
ZA
null
Africa/Johannesburg
-26.2
28.04
9,418,183
nanjing
nanjing
Nanjing
CN
Jiangsu
Asia/Shanghai
32.06
118.78
9,314,685
hangzhou
hangzhou
Hangzhou
CN
null
Asia/Shanghai
30.29
120.16
9,236,032
foshan
foshan
Foshan
CN
Guangdong
Asia/Shanghai
23.03
113.13
9,042,509
lon
london
London
GB
null
Europe/London
51.51
-0.13
8,961,989
nyc
newyorkcity
New York City
US
null
America/New_York
40.71
-74.01
8,804,190
jkt
jakarta
Jakarta
ID
null
Asia/Jakarta
-6.21
106.85
8,540,121
bengaluru
bengaluru
Bengaluru
IN
null
Asia/Kolkata
12.97
77.59
8,495,492
hanoi
hanoi
Hanoi
VN
Hanoi
Asia/Bangkok
21.02
105.84
8,053,663
taipei
taipei
Taipei
TW
null
Asia/Taipei
25.05
121.53
7,871,900
lima
lima
Lima
PE
null
America/Lima
-12.04
-77.03
7,737,002
bogota
bogota
Bogotá
CO
null
America/Bogota
4.61
-74.08
7,674,366
chongqing
chongqing
Chongqing
CN
null
Asia/Shanghai
29.56
106.56
7,457,599
hkg
hongkong
Hong Kong
HK
null
Asia/Hong_Kong
22.28
114.17
7,396,076
baghdad
baghdad
Baghdad
IQ
null
Asia/Baghdad
33.34
44.4
7,216,000
wuzhong
wuzhong
Wuzhong
CN
null
Asia/Shanghai
37.99
106.2
7,202,654
qingdao
qingdao
Qingdao
CN
null
Asia/Shanghai
36.06
120.38
7,172,451
tehran
tehran
Tehran
IR
null
Asia/Tehran
35.69
51.42
7,153,309
shenyang
shenyang
Shenyang
CN
null
Asia/Shanghai
41.79
123.43
7,050,000
hyderabad
hyderabad
Hyderabad
IN
null
Asia/Kolkata
17.38
78.46
6,993,262
rio
riodejaneiro
Rio de Janeiro
BR
null
America/Sao_Paulo
-22.91
-43.18
6,747,815
suzhou
suzhou
Suzhou
CN
Jiangsu
Asia/Shanghai
31.3
120.6
6,715,559
ahmedabad
ahmedabad
Ahmedabad
IN
null
Asia/Kolkata
23.03
72.59
6,357,693
abidjan
abidjan
Abidjan
CI
null
Africa/Abidjan
5.35
-4
6,321,017
pudong
pudong
Pudong
CN
null
Asia/Shanghai
31.24
121.5
5,681,512
sin
singapore
Singapore
SG
null
Asia/Singapore
1.29
103.85
5,638,700
syd
sydney
Sydney
AU
null
Australia/Sydney
-33.87
151.21
5,557,233
daressalaam
daressalaam
Dar es Salaam
TZ
null
Africa/Dar_es_Salaam
-6.82
39.27
5,383,728
saintpetersburg
saintpetersburg
Saint Petersburg
RU
null
Europe/Moscow
59.94
30.31
5,351,935
mel
melbourne
Melbourne
AU
null
Australia/Melbourne
-37.81
144.96
5,350,705
alexandria
alexandria
Alexandria
EG
null
Africa/Cairo
31.2
29.92
5,263,542
harbin
harbin
Harbin
CN
null
Asia/Shanghai
45.75
126.65
5,242,897
bkk
bangkok
Bangkok
TH
null
Asia/Bangkok
13.75
100.5
5,104,476
hefei
hefei
Hefei
CN
null
Asia/Shanghai
31.86
117.28
5,050,000
dalian
dalian
Dalian
CN
Liaoning
Asia/Shanghai
38.91
121.6
4,913,879
kano
kano
Kano
NG
null
Africa/Lagos
12
8.52
4,910,000
santiago
santiago
Santiago
CL
null
America/Santiago
-33.46
-70.65
4,837,295
capetown
capetown
Cape Town
ZA
null
Africa/Johannesburg
-33.93
18.42
4,772,846
peshawar
peshawar
Peshawar
PK
null
Asia/Karachi
34.01
71.58
4,758,762
changchun
changchun
Changchun
CN
Jilin
Asia/Shanghai
43.88
125.32
4,714,996
jeddah
jeddah
Jeddah
SA
null
Asia/Riyadh
21.49
39.19
4,697,000
chennai
chennai
Chennai
IN
null
Asia/Kolkata
13.09
80.28
4,681,087
kolkata
kolkata
Kolkata
IN
null
Asia/Kolkata
22.56
88.36
4,631,392
xiamen
xiamen
Xiamen
CN
null
Asia/Shanghai
24.48
118.08
4,617,251
surat
surat
Surat
IN
null
Asia/Kolkata
21.2
72.83
4,591,246
yangon
yangon
Yangon
MM
null
Asia/Yangon
16.81
96.16
4,477,638
baoan
baoan
Bao'an
CN
Guangdong
Asia/Shanghai
22.55
113.88
4,476,554
kabul
kabul
Kabul
AF
null
Asia/Kabul
34.53
69.17
4,434,550
nairobi
nairobi
Nairobi
KE
null
Africa/Nairobi
-1.28
36.82
4,397,073
wuxi
wuxi
Wuxi
CN
Jiangsu
Asia/Shanghai
31.57
120.29
4,396,835
giza
giza
Giza
EG
null
Africa/Cairo
30.01
31.21
4,367,343
jinan
jinan
Jinan
CN
Shandong
Asia/Shanghai
36.67
117
4,335,989
taiyuan
taiyuan
Taiyuan
CN
Shanxi
Asia/Shanghai
37.87
112.56
4,303,673
zhengzhou
zhengzhou
Zhengzhou
CN
null
Asia/Shanghai
34.76
113.65
4,253,913
bamako
bamako
Bamako
ML
null
Africa/Bamako
12.61
-7.98
4,227,569
riyadh
riyadh
Riyadh
SA
null
Asia/Riyadh
24.69
46.72
4,205,961
newtaipeicity
newtaipeicity
New Taipei City
TW
null
Asia/Taipei
25.06
121.46
4,004,367
newterritories
newterritories
New Territories
HK
null
Asia/Hong_Kong
22.42
114.11
3,984,077
shijiazhuang
shijiazhuang
Shijiazhuang
CN
Hebei
Asia/Shanghai
38.04
114.48
3,938,513
chattogram
chattogram
Chattogram
BD
null
Asia/Dhaka
22.34
91.83
3,920,222
addisababa
addisababa
Addis Ababa
ET
null
Africa/Addis_Ababa
9.02
38.75
3,860,000
kunming
kunming
Kunming
CN
null
Asia/Shanghai
25.04
102.72
3,855,346
zhongshan
zhongshan
Zhongshan
CN
Guangdong
Asia/Shanghai
22.52
113.38
3,841,873
nanning
nanning
Nanning
CN
null
Asia/Shanghai
22.82
108.32
3,839,800
shantou
shantou
Shantou
CN
null
Asia/Shanghai
23.35
116.68
3,838,900
la
losangeles
Los Angeles
US
null
America/Los_Angeles
34.05
-118.24
3,820,914
faisalabad
faisalabad
Faisalabad
PK
null
Asia/Karachi
31.42
73.09
3,800,193
dxb
dubai
Dubai
AE
null
Asia/Dubai
25.08
55.31
3,790,000
yokohama
yokohama
Yokohama
JP
Kanagawa
Asia/Tokyo
35.43
139.65
3,777,491
fuzhou
fuzhou
Fuzhou
CN
Fujian
Asia/Shanghai
26.06
119.31
3,740,000
ningbo
ningbo
Ningbo
CN
null
Asia/Shanghai
29.88
121.55
3,731,203
casablanca
casablanca
Casablanca
MA
null
Africa/Casablanca
33.59
-7.61
3,665,954
ibadan
ibadan
Ibadan
NG
null
Africa/Lagos
7.38
3.91
3,649,000
puyang
puyang
Puyang
CN
Zhejiang
Asia/Shanghai
29.46
119.89
3,590,000
ankara
ankara
Ankara
TR
null
Europe/Istanbul
39.92
32.85
3,517,182
shiyan
shiyan
Shiyan
CN
Hubei
Asia/Shanghai
32.65
110.78
3,460,000
End of preview. Expand in Data Studio

City Slugs

Two canonical, URL-safe identifiers for each of 234,136 cities and towns worldwide (every GeoNames populated place with population ≥ 500), fixed by a deterministic rule:

  • id — the short, recognizable form: ber, sf, nyc, tyo for cities with a curated metro / airport / colloquial code; equal to the slug otherwise.
  • slug — the written-out form: berlin, sanfrancisco, newyorkcity.

Both are globally unique and resolve to the same city. Geocoding ids (GeoNames ids, place ids) are stable but opaque; names are readable but ambiguous (there are six Heidelbergs). This dataset gives each place a single readable identifier that survives in a URL, a config file, or a conversation.

Schema

column type notes
id string short canonical id (ber); equals slug when no curated short form
slug string written-out canonical slug (berlin)
name string display name
country string ISO 3166-1 alpha-2
region string | null GeoNames admin-1 name, present where it disambiguates
timezone string IANA zone
lat, lng float coordinates, rounded to 2 decimals (~1 km)
population int GeoNames population
id   slug          name             country  population
ber  berlin        Berlin           DE        3644826
sf   sanfrancisco  San Francisco    US         864816
nyc  newyorkcity   New York City    US        8804190
—    heidelberg    Heidelberg       DE         160355
—    paloalto      Palo Alto        US          66853

Assignment rules

Slugs are claimed in global population order; each city takes the shortest free form: namename_ccname_cc_regionname_cc_region_N. The bare name goes to the most populous bearer (paloalto = Palo Alto, California), namesakes fall to the disambiguated forms (paloalto_mx).

Ids equal the slug unless a curated short form exists, claimed over the same namespace (so an id never collides with another city's slug): colloquial name (sf) → metro code (nyc) → iconic airport code (ber, curated allow-list — cryptic codes like bom/msy stay search aliases) → else id = slug.

Deterministic: the same GeoNames snapshot yields the same assignment. Treat published ids and slugs as append-only.

Usage

from datasets import load_dataset
ds = load_dataset("mirkokiefer/city-slugs", split="train")
ds.filter(lambda r: r["country"] == "DE" and r["population"] > 50000)
import duckdb
duckdb.sql("SELECT id, slug, name FROM 'city-slugs.parquet' WHERE id != slug LIMIT 10")

Provenance & license

Derived from GeoNames (cities500 + admin1CodesASCII), CC BY 4.0; this dataset is published under the same license.

Also available as an npm package (city-slugs, with JSON tiers + a byId / bySlug API) and on GitHub. Born in Zeit — a world clock for iPhone, Mac, and the web, where the ids power short share URLs (zeit.xyz/?c=ber,sf,nyc).

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