Overview

Dataset statistics

Number of variables8
Number of observations26
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.8 KiB
Average record size in memory72.1 B

Variable types

Numeric3
Text3
DateTime2

Dataset

Description부산광역시_자매도시현황_20230930
Author부산광역시
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15088427

Alerts

데이터기준일자 has constant value ""Constant
순번 has unique valuesUnique
도시명 has unique valuesUnique
결연일자 has unique valuesUnique
인구(천명) has unique valuesUnique
비고 has unique valuesUnique

Reproduction

Analysis started2023-12-10 16:49:27.488043
Analysis finished2023-12-10 16:49:29.150211
Duration1.66 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.5
Minimum1
Maximum26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-11T01:49:29.237773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.25
Q17.25
median13.5
Q319.75
95-th percentile24.75
Maximum26
Range25
Interquartile range (IQR)12.5

Descriptive statistics

Standard deviation7.6485293
Coefficient of variation (CV)0.56655772
Kurtosis-1.2
Mean13.5
Median Absolute Deviation (MAD)6.5
Skewness0
Sum351
Variance58.5
MonotonicityStrictly increasing
2023-12-11T01:49:29.395729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
1 1
 
3.8%
15 1
 
3.8%
26 1
 
3.8%
25 1
 
3.8%
24 1
 
3.8%
23 1
 
3.8%
22 1
 
3.8%
21 1
 
3.8%
20 1
 
3.8%
19 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
1 1
3.8%
2 1
3.8%
3 1
3.8%
4 1
3.8%
5 1
3.8%
6 1
3.8%
7 1
3.8%
8 1
3.8%
9 1
3.8%
10 1
3.8%
ValueCountFrequency (%)
26 1
3.8%
25 1
3.8%
24 1
3.8%
23 1
3.8%
22 1
3.8%
21 1
3.8%
20 1
3.8%
19 1
3.8%
18 1
3.8%
17 1
3.8%

도시명
Text

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size340.0 B
2023-12-11T01:49:29.695012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length19
Mean length15.615385
Min length8

Characters and Unicode

Total characters406
Distinct characters125
Distinct categories7 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)100.0%

Sample

1st row가오슝(高雄) Kaoshiung
2nd row로스엔젤레스 Los Angeles
3rd row시모노세키(下) Shimonoseki
4th row바르셀로나 Barcelona
5th row리우데자네이루 Rio de Janeiro
ValueCountFrequency (%)
가오슝(高雄 1
 
1.6%
상트페테르부르그 1
 
1.6%
western 1
 
1.6%
cape 1
 
1.6%
government 1
 
1.6%
몬트리올 1
 
1.6%
montreal 1
 
1.6%
이스탄불 1
 
1.6%
istanbul 1
 
1.6%
두바이 1
 
1.6%
Other values (52) 52
83.9%
2023-12-11T01:49:30.169221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36
 
8.9%
a 30
 
7.4%
n 20
 
4.9%
o 19
 
4.7%
i 19
 
4.7%
e 17
 
4.2%
s 12
 
3.0%
u 11
 
2.7%
h 10
 
2.5%
r 10
 
2.5%
Other values (115) 222
54.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 204
50.2%
Other Letter 122
30.0%
Space Separator 36
 
8.9%
Uppercase Letter 35
 
8.6%
Close Punctuation 4
 
1.0%
Open Punctuation 4
 
1.0%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 7
 
5.7%
스 5
 
4.1%
바 4
 
3.3%
카 4
 
3.3%
르 3
 
2.5%
리 3
 
2.5%
로 3
 
2.5%
시 3
 
2.5%
오 3
 
2.5%
라 3
 
2.5%
Other values (71) 84
68.9%
Lowercase Letter
ValueCountFrequency (%)
a 30
14.7%
n 20
9.8%
o 19
9.3%
i 19
9.3%
e 17
 
8.3%
s 12
 
5.9%
u 11
 
5.4%
h 10
 
4.9%
r 10
 
4.9%
t 9
 
4.4%
Other values (11) 47
23.0%
Uppercase Letter
ValueCountFrequency (%)
C 6
17.1%
S 4
11.4%
V 3
 
8.6%
M 3
 
8.6%
P 3
 
8.6%
A 2
 
5.7%
T 2
 
5.7%
I 1
 
2.9%
G 1
 
2.9%
W 1
 
2.9%
Other values (9) 9
25.7%
Space Separator
ValueCountFrequency (%)
36
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 239
58.9%
Hangul 113
27.8%
Common 45
 
11.1%
Han 9
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 7
 
6.2%
스 5
 
4.4%
바 4
 
3.5%
카 4
 
3.5%
르 3
 
2.7%
리 3
 
2.7%
로 3
 
2.7%
시 3
 
2.7%
오 3
 
2.7%
라 3
 
2.7%
Other values (63) 75
66.4%
Latin
ValueCountFrequency (%)
a 30
 
12.6%
n 20
 
8.4%
o 19
 
7.9%
i 19
 
7.9%
e 17
 
7.1%
s 12
 
5.0%
u 11
 
4.6%
h 10
 
4.2%
r 10
 
4.2%
t 9
 
3.8%
Other values (30) 82
34.3%
Han
ValueCountFrequency (%)
州 2
22.2%
岡 1
11.1%
福 1
11.1%
下 1
11.1%
雄 1
11.1%
高 1
11.1%
海 1
11.1%
上 1
11.1%
Common
ValueCountFrequency (%)
36
80.0%
) 4
 
8.9%
( 4
 
8.9%
. 1
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 284
70.0%
Hangul 113
 
27.8%
CJK 9
 
2.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
36
 
12.7%
a 30
 
10.6%
n 20
 
7.0%
o 19
 
6.7%
i 19
 
6.7%
e 17
 
6.0%
s 12
 
4.2%
u 11
 
3.9%
h 10
 
3.5%
r 10
 
3.5%
Other values (34) 100
35.2%
Hangul
ValueCountFrequency (%)
이 7
 
6.2%
스 5
 
4.4%
바 4
 
3.5%
카 4
 
3.5%
르 3
 
2.7%
리 3
 
2.7%
로 3
 
2.7%
시 3
 
2.7%
오 3
 
2.7%
라 3
 
2.7%
Other values (63) 75
66.4%
CJK
ValueCountFrequency (%)
州 2
22.2%
岡 1
11.1%
福 1
11.1%
下 1
11.1%
雄 1
11.1%
高 1
11.1%
海 1
11.1%
上 1
11.1%

국가명
Text

Distinct23
Distinct (%)88.5%
Missing0
Missing (%)0.0%
Memory size340.0 B
2023-12-11T01:49:30.443638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length6
Mean length3.2692308
Min length2

Characters and Unicode

Total characters85
Distinct characters56
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)76.9%

Sample

1st row대만
2nd row미국
3rd row일본
4th row스페인
5th row브라질
ValueCountFrequency (%)
일본 2
 
7.4%
러시아 2
 
7.4%
미국 2
 
7.4%
캐나다 1
 
3.7%
대만 1
 
3.7%
공화국 1
 
3.7%
남아프리카 1
 
3.7%
필리핀 1
 
3.7%
모로코 1
 
3.7%
그리스 1
 
3.7%
Other values (14) 14
51.9%
2023-12-11T01:49:30.841411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
국 6
 
7.1%
아 5
 
5.9%
시 4
 
4.7%
인 3
 
3.5%
미 3
 
3.5%
리 3
 
3.5%
일 2
 
2.4%
본 2
 
2.4%
공 2
 
2.4%
남 2
 
2.4%
Other values (46) 53
62.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 79
92.9%
Uppercase Letter 3
 
3.5%
Other Punctuation 2
 
2.4%
Space Separator 1
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 6
 
7.6%
아 5
 
6.3%
시 4
 
5.1%
인 3
 
3.8%
미 3
 
3.8%
리 3
 
3.8%
일 2
 
2.5%
본 2
 
2.5%
공 2
 
2.5%
남 2
 
2.5%
Other values (41) 47
59.5%
Uppercase Letter
ValueCountFrequency (%)
E 1
33.3%
A 1
33.3%
U 1
33.3%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 79
92.9%
Common 3
 
3.5%
Latin 3
 
3.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 6
 
7.6%
아 5
 
6.3%
시 4
 
5.1%
인 3
 
3.8%
미 3
 
3.8%
리 3
 
3.8%
일 2
 
2.5%
본 2
 
2.5%
공 2
 
2.5%
남 2
 
2.5%
Other values (41) 47
59.5%
Latin
ValueCountFrequency (%)
E 1
33.3%
A 1
33.3%
U 1
33.3%
Common
ValueCountFrequency (%)
. 2
66.7%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 79
92.9%
ASCII 6
 
7.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
국 6
 
7.6%
아 5
 
6.3%
시 4
 
5.1%
인 3
 
3.8%
미 3
 
3.8%
리 3
 
3.8%
일 2
 
2.5%
본 2
 
2.5%
공 2
 
2.5%
남 2
 
2.5%
Other values (41) 47
59.5%
ASCII
ValueCountFrequency (%)
. 2
33.3%
E 1
16.7%
1
16.7%
A 1
16.7%
U 1
16.7%

결연일자
Date

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size340.0 B
Minimum1966-06-30 00:00:00
Maximum2013-01-14 00:00:00
2023-12-11T01:49:30.982469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:49:31.167601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)

면적(제곱킬로미터)
Real number (ℝ)

Distinct25
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15545.692
Minimum19
Maximum237659
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-11T01:49:31.359740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19
5-th percentile156.75
Q1347.75
median859.5
Q32734.25
95-th percentile98612.5
Maximum237659
Range237640
Interquartile range (IQR)2386.5

Descriptive statistics

Standard deviation51793.874
Coefficient of variation (CV)3.3317187
Kurtosis15.001383
Mean15545.692
Median Absolute Deviation (MAD)534.5
Skewness3.856026
Sum404188
Variance2.6826054 × 109
MonotonicityNot monotonic
2023-12-11T01:49:31.536989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
326 2
 
7.7%
2946 1
 
3.8%
1003 1
 
3.8%
599 1
 
3.8%
4933 1
 
3.8%
324 1
 
3.8%
19 1
 
3.8%
438 1
 
3.8%
678 1
 
3.8%
1439 1
 
3.8%
Other values (15) 15
57.7%
ValueCountFrequency (%)
19 1
3.8%
101 1
3.8%
324 1
3.8%
326 2
7.7%
331 1
3.8%
342 1
3.8%
365 1
3.8%
438 1
3.8%
599 1
3.8%
606 1
3.8%
ValueCountFrequency (%)
237659 1
3.8%
129370 1
3.8%
6340 1
3.8%
4933 1
3.8%
4894 1
3.8%
4114 1
3.8%
2946 1
3.8%
2099 1
3.8%
1564 1
3.8%
1439 1
3.8%

인구(천명)
Real number (ℝ)

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4876.7308
Minimum277
Maximum22208
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-11T01:49:31.695729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum277
5-th percentile306.25
Q11541.25
median2897.5
Q35830.75
95-th percentile17200
Maximum22208
Range21931
Interquartile range (IQR)4289.5

Descriptive statistics

Standard deviation5497.6322
Coefficient of variation (CV)1.1273192
Kurtosis3.9617335
Mean4876.7308
Median Absolute Deviation (MAD)1562.5
Skewness2.059023
Sum126795
Variance30223960
MonotonicityNot monotonic
2023-12-11T01:49:31.863376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
2770 1
 
3.8%
3824 1
 
3.8%
7360 1
 
3.8%
2938 1
 
3.8%
3672 1
 
3.8%
325 1
 
3.8%
18000 1
 
3.8%
2078 1
 
3.8%
5323 1
 
3.8%
2800 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
277 1
3.8%
300 1
3.8%
325 1
3.8%
606 1
3.8%
1200 1
3.8%
1470 1
3.8%
1520 1
3.8%
1605 1
3.8%
2078 1
3.8%
2260 1
3.8%
ValueCountFrequency (%)
22208 1
3.8%
18000 1
3.8%
14800 1
3.8%
8224 1
3.8%
7360 1
3.8%
6358 1
3.8%
6000 1
3.8%
5323 1
3.8%
4110 1
3.8%
3910 1
3.8%

비고
Text

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size340.0 B
2023-12-11T01:49:32.163186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length23.5
Mean length20.769231
Min length6

Characters and Unicode

Total characters540
Distinct characters159
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)100.0%

Sample

1st row대만 제1의 항만도시
2nd row북미 태평양연안 최대항만도시,우주항공 중심지
3rd row수산업이 발달한 서부 일본의 교통중심 도시
4th row문화예술도시이자 상공업중심도시
5th row세계3대미항, 브라질 제2의 수출입 항구도시
ValueCountFrequency (%)
중심 5
 
5.2%
최대 3
 
3.1%
항구도시 3
 
3.1%
항만도시 2
 
2.1%
제1의 2
 
2.1%
중심지 2
 
2.1%
도시 2
 
2.1%
중심도시 2
 
2.1%
위치한 1
 
1.0%
제2도시,제1항만 1
 
1.0%
Other values (74) 74
76.3%
2023-12-11T01:49:32.684220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
72
 
13.3%
도 32
 
5.9%
시 32
 
5.9%
중 18
 
3.3%
의 18
 
3.3%
제 16
 
3.0%
, 16
 
3.0%
항 16
 
3.0%
심 15
 
2.8%
대 10
 
1.9%
Other values (149) 295
54.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 415
76.9%
Space Separator 72
 
13.3%
Other Punctuation 28
 
5.2%
Decimal Number 16
 
3.0%
Uppercase Letter 7
 
1.3%
Close Punctuation 1
 
0.2%
Open Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 32
 
7.7%
시 32
 
7.7%
중 18
 
4.3%
의 18
 
4.3%
제 16
 
3.9%
항 16
 
3.9%
심 15
 
3.6%
대 10
 
2.4%
만 9
 
2.2%
업 8
 
1.9%
Other values (130) 241
58.1%
Uppercase Letter
ValueCountFrequency (%)
A 2
28.6%
U 1
14.3%
E 1
14.3%
T 1
14.3%
F 1
14.3%
N 1
14.3%
Other Punctuation
ValueCountFrequency (%)
, 16
57.1%
· 8
28.6%
. 2
 
7.1%
% 1
 
3.6%
: 1
 
3.6%
Decimal Number
ValueCountFrequency (%)
2 7
43.8%
1 5
31.2%
3 2
 
12.5%
0 1
 
6.2%
8 1
 
6.2%
Space Separator
ValueCountFrequency (%)
72
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 415
76.9%
Common 118
 
21.9%
Latin 7
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 32
 
7.7%
시 32
 
7.7%
중 18
 
4.3%
의 18
 
4.3%
제 16
 
3.9%
항 16
 
3.9%
심 15
 
3.6%
대 10
 
2.4%
만 9
 
2.2%
업 8
 
1.9%
Other values (130) 241
58.1%
Common
ValueCountFrequency (%)
72
61.0%
, 16
 
13.6%
· 8
 
6.8%
2 7
 
5.9%
1 5
 
4.2%
. 2
 
1.7%
3 2
 
1.7%
% 1
 
0.8%
0 1
 
0.8%
8 1
 
0.8%
Other values (3) 3
 
2.5%
Latin
ValueCountFrequency (%)
A 2
28.6%
U 1
14.3%
E 1
14.3%
T 1
14.3%
F 1
14.3%
N 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 415
76.9%
ASCII 117
 
21.7%
None 8
 
1.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
72
61.5%
, 16
 
13.7%
2 7
 
6.0%
1 5
 
4.3%
A 2
 
1.7%
. 2
 
1.7%
3 2
 
1.7%
% 1
 
0.9%
0 1
 
0.9%
8 1
 
0.9%
Other values (8) 8
 
6.8%
Hangul
ValueCountFrequency (%)
도 32
 
7.7%
시 32
 
7.7%
중 18
 
4.3%
의 18
 
4.3%
제 16
 
3.9%
항 16
 
3.9%
심 15
 
3.6%
대 10
 
2.4%
만 9
 
2.2%
업 8
 
1.9%
Other values (130) 241
58.1%
None
ValueCountFrequency (%)
· 8
100.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size340.0 B
Minimum2023-09-30 00:00:00
Maximum2023-09-30 00:00:00
2023-12-11T01:49:32.850334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:49:32.977497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-11T01:49:28.519458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:49:27.888335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:49:28.242718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:49:28.597963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:49:28.006657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:49:28.337440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:49:28.746777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:49:28.132081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:49:28.438157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:49:33.075347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번도시명국가명결연일자면적(제곱킬로미터)인구(천명)비고
순번1.0001.0000.7531.0000.6070.0001.000
도시명1.0001.0001.0001.0001.0001.0001.000
국가명0.7531.0001.0001.0001.0000.9741.000
결연일자1.0001.0001.0001.0001.0001.0001.000
면적(제곱킬로미터)0.6071.0001.0001.0001.0000.0001.000
인구(천명)0.0001.0000.9741.0000.0001.0001.000
비고1.0001.0001.0001.0001.0001.0001.000
2023-12-11T01:49:33.207539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번면적(제곱킬로미터)인구(천명)
순번1.000-0.1850.138
면적(제곱킬로미터)-0.1851.0000.387
인구(천명)0.1380.3871.000

Missing values

2023-12-11T01:49:28.914079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:49:29.080502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

순번도시명국가명결연일자면적(제곱킬로미터)인구(천명)비고데이터기준일자
01가오슝(高雄) Kaoshiung대만1966-06-3029462770대만 제1의 항만도시2023-09-30
12로스엔젤레스 Los Angeles미국1967-12-1813003910북미 태평양연안 최대항만도시,우주항공 중심지2023-09-30
23시모노세키(下) Shimonoseki일본1976-10-11716300수산업이 발달한 서부 일본의 교통중심 도시2023-09-30
34바르셀로나 Barcelona스페인1983-10-251011605문화예술도시이자 상공업중심도시2023-09-30
45리우데자네이루 Rio de Janeiro브라질1985-09-2313566000세계3대미항, 브라질 제2의 수출입 항구도시2023-09-30
56블라디보스토크 Vladivostok러시아1992-06-30331606러시아연방. 극동지역 최대 항만도시2023-09-30
67상하이(上海) Shanghai중국1993-08-24634022208중국 제1의 항구도시, 상업금융무역의 중심2023-09-30
78수라바야 Surabaya인도네시아1994-08-293262857동자바 수도2023-09-30
89빅토리아州 Victoria호주1994-10-172376596358에너지산업 주종, 교통항만중심지 (주도:멜번)2023-09-30
910티후아나 Tijuana멕시코1995-01-1715641200NAFTA권의멕시코공업·무역 중심도시2023-09-30
순번도시명국가명결연일자면적(제곱킬로미터)인구(천명)비고데이터기준일자
1617두바이 DubaiU.A.E2006-11-1341142260중동의 항만물류관광 중심도시2023-09-30
1718후쿠오카(福岡) Fukuoka일본2007-02-023421520일본큐슈 동북단에 위치한 서일본 거점도시2023-09-30
1819시카고 Chicago미국2007-05-076062800전시컨벤션도시, 세계선물시장의 중심2023-09-30
1920상트페테르부르그 St. Petersburg러시아2008-06-1114395323러시아 제2도시,제1항만, 관광·문화·행정·산업·공업 중심2023-09-30
2021프놈펜 Phnom Penh캄보디아왕국2009-06-116782078캄보디아수도,제1도시 메콩강을통한 내륙항만 보유2023-09-30
2122뭄바이 Mumbai인도공화국2009-11-1943818000인도의 경제수도2023-09-30
2223데살로니키 Thessaloniki그리스2010-03-0819325그리스의 제2도시이자 문화수도2023-09-30
2324카사블랑카 Casablanca모로코2011-04-263243672모로코 제2도시, 항만·관광 중심 도시2023-09-30
2425세부州 Cebu필리핀2011-12-1649332938동남아시아 최대 관광.휴양도시2023-09-30
2526양곤시 Yangon미얀마2013-01-145997360미얀마 최대 항구, 해외무역 80%담당, 경제,상업교역 중심2023-09-30