Overview

Dataset statistics

Number of variables6
Number of observations179
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.7 KiB
Average record size in memory49.7 B

Variable types

Numeric1
Text4
DateTime1

Dataset

Description국토연구원 세계도시정보에서는 세계도시정보에 대한 도시명, 위치 등 도시정보를 알 수 있습니다.
Author국토연구원
URLhttps://www.data.go.kr/data/15042620/fileData.do

Alerts

번호 has unique valuesUnique
상세페이지 링크 has unique valuesUnique

Reproduction

Analysis started2023-12-12 14:41:26.246380
Analysis finished2023-12-12 14:41:27.001709
Duration0.76 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct179
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean90
Minimum1
Maximum179
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-12T23:41:27.089008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile9.9
Q145.5
median90
Q3134.5
95-th percentile170.1
Maximum179
Range178
Interquartile range (IQR)89

Descriptive statistics

Standard deviation51.816986
Coefficient of variation (CV)0.57574428
Kurtosis-1.2
Mean90
Median Absolute Deviation (MAD)45
Skewness0
Sum16110
Variance2685
MonotonicityStrictly increasing
2023-12-12T23:41:27.240985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.6%
114 1
 
0.6%
116 1
 
0.6%
117 1
 
0.6%
118 1
 
0.6%
119 1
 
0.6%
120 1
 
0.6%
121 1
 
0.6%
122 1
 
0.6%
123 1
 
0.6%
Other values (169) 169
94.4%
ValueCountFrequency (%)
1 1
0.6%
2 1
0.6%
3 1
0.6%
4 1
0.6%
5 1
0.6%
6 1
0.6%
7 1
0.6%
8 1
0.6%
9 1
0.6%
10 1
0.6%
ValueCountFrequency (%)
179 1
0.6%
178 1
0.6%
177 1
0.6%
176 1
0.6%
175 1
0.6%
174 1
0.6%
173 1
0.6%
172 1
0.6%
171 1
0.6%
170 1
0.6%

나라
Text

Distinct73
Distinct (%)40.8%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-12T23:41:27.482442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length3.0837989
Min length2

Characters and Unicode

Total characters552
Distinct characters114
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)27.4%

Sample

1st row크로아티아
2nd row레바논
3rd row카자흐스탄
4th row태국
5th row에스토니아
ValueCountFrequency (%)
미국 25
 
13.9%
영국 16
 
8.9%
독일 11
 
6.1%
일본 9
 
5.0%
중국 8
 
4.4%
오스트레일리아 7
 
3.9%
프랑스 6
 
3.3%
스페인 5
 
2.8%
캐나다 5
 
2.8%
인도 4
 
2.2%
Other values (64) 84
46.7%
2023-12-12T23:41:27.889892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
국 54
 
9.8%
아 33
 
6.0%
스 31
 
5.6%
일 28
 
5.1%
미 27
 
4.9%
이 18
 
3.3%
리 17
 
3.1%
영 16
 
2.9%
트 14
 
2.5%
레 12
 
2.2%
Other values (104) 302
54.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 551
99.8%
Space Separator 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 54
 
9.8%
아 33
 
6.0%
스 31
 
5.6%
일 28
 
5.1%
미 27
 
4.9%
이 18
 
3.3%
리 17
 
3.1%
영 16
 
2.9%
트 14
 
2.5%
레 12
 
2.2%
Other values (103) 301
54.6%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 551
99.8%
Common 1
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 54
 
9.8%
아 33
 
6.0%
스 31
 
5.6%
일 28
 
5.1%
미 27
 
4.9%
이 18
 
3.3%
리 17
 
3.1%
영 16
 
2.9%
트 14
 
2.5%
레 12
 
2.2%
Other values (103) 301
54.6%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 551
99.8%
ASCII 1
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
국 54
 
9.8%
아 33
 
6.0%
스 31
 
5.6%
일 28
 
5.1%
미 27
 
4.9%
이 18
 
3.3%
리 17
 
3.1%
영 16
 
2.9%
트 14
 
2.5%
레 12
 
2.2%
Other values (103) 301
54.6%
ASCII
ValueCountFrequency (%)
1
100.0%

도시명
Text

Distinct172
Distinct (%)96.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-12T23:41:28.226292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length3.8268156
Min length1

Characters and Unicode

Total characters685
Distinct characters225
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique165 ?
Unique (%)92.2%

Sample

1st row자그레브
2nd row베이루트
3rd row아스타나
4th row방콕
5th row탈린
ValueCountFrequency (%)
클리블랜드 2
 
1.1%
맨체스터 2
 
1.1%
브라질리아 2
 
1.1%
버밍엄 2
 
1.1%
아바나(하바나 2
 
1.1%
뭄바이 2
 
1.1%
몬테비데오 2
 
1.1%
자그레브 1
 
0.5%
청두 1
 
0.5%
리즈 1
 
0.5%
Other values (166) 166
90.7%
2023-12-12T23:41:28.684351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 40
 
5.8%
이 22
 
3.2%
르 22
 
3.2%
리 21
 
3.1%
라 20
 
2.9%
바 18
 
2.6%
아 15
 
2.2%
드 13
 
1.9%
카 11
 
1.6%
오 11
 
1.6%
Other values (215) 492
71.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 670
97.8%
Space Separator 4
 
0.6%
Open Punctuation 3
 
0.4%
Close Punctuation 3
 
0.4%
Other Punctuation 3
 
0.4%
Uppercase Letter 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 40
 
6.0%
이 22
 
3.3%
르 22
 
3.3%
리 21
 
3.1%
라 20
 
3.0%
바 18
 
2.7%
아 15
 
2.2%
드 13
 
1.9%
카 11
 
1.6%
오 11
 
1.6%
Other values (208) 477
71.2%
Other Punctuation
ValueCountFrequency (%)
. 2
66.7%
, 1
33.3%
Uppercase Letter
ValueCountFrequency (%)
C 1
50.0%
D 1
50.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 670
97.8%
Common 13
 
1.9%
Latin 2
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 40
 
6.0%
이 22
 
3.3%
르 22
 
3.3%
리 21
 
3.1%
라 20
 
3.0%
바 18
 
2.7%
아 15
 
2.2%
드 13
 
1.9%
카 11
 
1.6%
오 11
 
1.6%
Other values (208) 477
71.2%
Common
ValueCountFrequency (%)
4
30.8%
( 3
23.1%
) 3
23.1%
. 2
15.4%
, 1
 
7.7%
Latin
ValueCountFrequency (%)
C 1
50.0%
D 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 670
97.8%
ASCII 15
 
2.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 40
 
6.0%
이 22
 
3.3%
르 22
 
3.3%
리 21
 
3.1%
라 20
 
3.0%
바 18
 
2.7%
아 15
 
2.2%
드 13
 
1.9%
카 11
 
1.6%
오 11
 
1.6%
Other values (208) 477
71.2%
ASCII
ValueCountFrequency (%)
4
26.7%
( 3
20.0%
) 3
20.0%
. 2
13.3%
C 1
 
6.7%
D 1
 
6.7%
, 1
 
6.7%

영문표기
Text

Distinct172
Distinct (%)96.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-12T23:41:29.020964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length24
Mean length9.1396648
Min length4

Characters and Unicode

Total characters1636
Distinct characters95
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique165 ?
Unique (%)92.2%

Sample

1st rowZagreb
2nd rowBeirut
3rd rowAstana
4th rowBangkok
5th rowTallinn
ValueCountFrequency (%)
la 3
 
1.4%
cleveland 2
 
0.9%
brisbane 2
 
0.9%
mexico 2
 
0.9%
de 2
 
0.9%
brasilia 2
 
0.9%
mumbai 2
 
0.9%
san 2
 
0.9%
montevideo 2
 
0.9%
habana 2
 
0.9%
Other values (190) 192
90.1%
2023-12-12T23:41:29.464439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 185
 
11.3%
n 123
 
7.5%
e 122
 
7.5%
o 98
 
6.0%
i 97
 
5.9%
r 85
 
5.2%
u 65
 
4.0%
s 65
 
4.0%
l 64
 
3.9%
t 60
 
3.7%
Other values (85) 672
41.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1282
78.4%
Uppercase Letter 216
 
13.2%
Space Separator 34
 
2.1%
Other Letter 33
 
2.0%
Close Punctuation 31
 
1.9%
Open Punctuation 31
 
1.9%
Other Punctuation 5
 
0.3%
Dash Punctuation 4
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 185
14.4%
n 123
 
9.6%
e 122
 
9.5%
o 98
 
7.6%
i 97
 
7.6%
r 85
 
6.6%
u 65
 
5.1%
s 65
 
5.1%
l 64
 
5.0%
t 60
 
4.7%
Other values (24) 318
24.8%
Other Letter
ValueCountFrequency (%)
京 4
 
12.1%
北 2
 
6.1%
都 2
 
6.1%
上 1
 
3.0%
藏 1
 
3.0%
野 1
 
3.0%
大 1
 
3.0%
阪 1
 
3.0%
香 1
 
3.0%
橫 1
 
3.0%
Other values (18) 18
54.5%
Uppercase Letter
ValueCountFrequency (%)
M 23
 
10.6%
B 22
 
10.2%
A 19
 
8.8%
L 18
 
8.3%
C 16
 
7.4%
S 14
 
6.5%
P 13
 
6.0%
T 12
 
5.6%
D 11
 
5.1%
H 9
 
4.2%
Other values (17) 59
27.3%
Other Punctuation
ValueCountFrequency (%)
, 3
60.0%
. 2
40.0%
Space Separator
ValueCountFrequency (%)
34
100.0%
Close Punctuation
ValueCountFrequency (%)
) 31
100.0%
Open Punctuation
ValueCountFrequency (%)
( 31
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1481
90.5%
Common 105
 
6.4%
Han 33
 
2.0%
Cyrillic 17
 
1.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 185
 
12.5%
n 123
 
8.3%
e 122
 
8.2%
o 98
 
6.6%
i 97
 
6.5%
r 85
 
5.7%
u 65
 
4.4%
s 65
 
4.4%
l 64
 
4.3%
t 60
 
4.1%
Other values (40) 517
34.9%
Han
ValueCountFrequency (%)
京 4
 
12.1%
北 2
 
6.1%
都 2
 
6.1%
上 1
 
3.0%
藏 1
 
3.0%
野 1
 
3.0%
大 1
 
3.0%
阪 1
 
3.0%
香 1
 
3.0%
橫 1
 
3.0%
Other values (18) 18
54.5%
Cyrillic
ValueCountFrequency (%)
о 3
17.6%
в 2
11.8%
с 2
11.8%
к 2
11.8%
а 2
11.8%
М 1
 
5.9%
т 1
 
5.9%
и 1
 
5.9%
д 1
 
5.9%
л 1
 
5.9%
Common
ValueCountFrequency (%)
34
32.4%
) 31
29.5%
( 31
29.5%
- 4
 
3.8%
, 3
 
2.9%
. 2
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1586
96.9%
CJK 33
 
2.0%
Cyrillic 17
 
1.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 185
 
11.7%
n 123
 
7.8%
e 122
 
7.7%
o 98
 
6.2%
i 97
 
6.1%
r 85
 
5.4%
u 65
 
4.1%
s 65
 
4.1%
l 64
 
4.0%
t 60
 
3.8%
Other values (46) 622
39.2%
CJK
ValueCountFrequency (%)
京 4
 
12.1%
北 2
 
6.1%
都 2
 
6.1%
上 1
 
3.0%
藏 1
 
3.0%
野 1
 
3.0%
大 1
 
3.0%
阪 1
 
3.0%
香 1
 
3.0%
橫 1
 
3.0%
Other values (18) 18
54.5%
Cyrillic
ValueCountFrequency (%)
о 3
17.6%
в 2
11.8%
с 2
11.8%
к 2
11.8%
а 2
11.8%
М 1
 
5.9%
т 1
 
5.9%
и 1
 
5.9%
д 1
 
5.9%
л 1
 
5.9%

등록일
Date

Distinct44
Distinct (%)24.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
Minimum2008-12-01 00:00:00
Maximum2012-07-27 00:00:00
2023-12-12T23:41:29.634351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:41:29.772034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)

상세페이지 링크
Text

UNIQUE 

Distinct179
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-12T23:41:30.068486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length79
Median length78
Mean length77.77095
Min length76

Characters and Unicode

Total characters13921
Distinct characters35
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique179 ?
Unique (%)100.0%

Sample

1st rowhttp://ubin.krihs.re.kr/ubin/wurban/city_info_intro.php?no=1126&frommain=1&fm=y
2nd rowhttp://ubin.krihs.re.kr/ubin/wurban/city_info_intro.php?no=1105&frommain=1&fm=y
3rd rowhttp://ubin.krihs.re.kr/ubin/wurban/city_info_intro.php?no=1082&frommain=1&fm=y
4th rowhttp://ubin.krihs.re.kr/ubin/wurban/city_info_intro.php?no=1067&frommain=1&fm=y
5th rowhttp://ubin.krihs.re.kr/ubin/wurban/city_info_intro.php?no=1054&frommain=1&fm=y
ValueCountFrequency (%)
http://ubin.krihs.re.kr/ubin/wurban/city_info_intro.php?no=1126&frommain=1&fm=y 1
 
0.6%
http://ubin.krihs.re.kr/ubin/wurban/city_info_intro.php?no=109&frommain=1&fm=y 1
 
0.6%
http://ubin.krihs.re.kr/ubin/wurban/city_info_intro.php?no=141&frommain=1&fm=y 1
 
0.6%
http://ubin.krihs.re.kr/ubin/wurban/city_info_intro.php?no=121&frommain=1&fm=y 1
 
0.6%
http://ubin.krihs.re.kr/ubin/wurban/city_info_intro.php?no=123&frommain=1&fm=y 1
 
0.6%
http://ubin.krihs.re.kr/ubin/wurban/city_info_intro.php?no=126&frommain=1&fm=y 1
 
0.6%
http://ubin.krihs.re.kr/ubin/wurban/city_info_intro.php?no=146&frommain=1&fm=y 1
 
0.6%
http://ubin.krihs.re.kr/ubin/wurban/city_info_intro.php?no=132&frommain=1&fm=y 1
 
0.6%
http://ubin.krihs.re.kr/ubin/wurban/city_info_intro.php?no=137&frommain=1&fm=y 1
 
0.6%
http://ubin.krihs.re.kr/ubin/wurban/city_info_intro.php?no=149&frommain=1&fm=y 1
 
0.6%
Other values (169) 169
94.4%
2023-12-12T23:41:30.551061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 1253
 
9.0%
n 1253
 
9.0%
r 1074
 
7.7%
/ 895
 
6.4%
t 716
 
5.1%
. 716
 
5.1%
o 716
 
5.1%
h 537
 
3.9%
p 537
 
3.9%
m 537
 
3.9%
Other values (25) 5687
40.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 10024
72.0%
Other Punctuation 2327
 
16.7%
Decimal Number 675
 
4.8%
Math Symbol 537
 
3.9%
Connector Punctuation 358
 
2.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 1253
12.5%
n 1253
12.5%
r 1074
10.7%
t 716
 
7.1%
o 716
 
7.1%
h 537
 
5.4%
p 537
 
5.4%
m 537
 
5.4%
u 537
 
5.4%
b 537
 
5.4%
Other values (8) 2327
23.2%
Decimal Number
ValueCountFrequency (%)
1 310
45.9%
6 53
 
7.9%
7 52
 
7.7%
8 45
 
6.7%
5 42
 
6.2%
0 37
 
5.5%
2 35
 
5.2%
4 35
 
5.2%
9 34
 
5.0%
3 32
 
4.7%
Other Punctuation
ValueCountFrequency (%)
/ 895
38.5%
. 716
30.8%
& 358
 
15.4%
: 179
 
7.7%
? 179
 
7.7%
Math Symbol
ValueCountFrequency (%)
= 537
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 358
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10024
72.0%
Common 3897
 
28.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 1253
12.5%
n 1253
12.5%
r 1074
10.7%
t 716
 
7.1%
o 716
 
7.1%
h 537
 
5.4%
p 537
 
5.4%
m 537
 
5.4%
u 537
 
5.4%
b 537
 
5.4%
Other values (8) 2327
23.2%
Common
ValueCountFrequency (%)
/ 895
23.0%
. 716
18.4%
= 537
13.8%
& 358
 
9.2%
_ 358
 
9.2%
1 310
 
8.0%
: 179
 
4.6%
? 179
 
4.6%
6 53
 
1.4%
7 52
 
1.3%
Other values (7) 260
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13921
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 1253
 
9.0%
n 1253
 
9.0%
r 1074
 
7.7%
/ 895
 
6.4%
t 716
 
5.1%
. 716
 
5.1%
o 716
 
5.1%
h 537
 
3.9%
p 537
 
3.9%
m 537
 
3.9%
Other values (25) 5687
40.9%

Interactions

2023-12-12T23:41:26.725990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:41:30.670396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호나라등록일
번호1.0000.9440.592
나라0.9441.0000.984
등록일0.5920.9841.000

Missing values

2023-12-12T23:41:26.852875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:41:26.960456image/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

번호나라도시명영문표기등록일상세페이지 링크
01크로아티아자그레브Zagreb2012-07-27http://ubin.krihs.re.kr/ubin/wurban/city_info_intro.php?no=1126&frommain=1&fm=y
12레바논베이루트Beirut2012-06-27http://ubin.krihs.re.kr/ubin/wurban/city_info_intro.php?no=1105&frommain=1&fm=y
23카자흐스탄아스타나Astana2012-05-22http://ubin.krihs.re.kr/ubin/wurban/city_info_intro.php?no=1082&frommain=1&fm=y
34태국방콕Bangkok2012-04-20http://ubin.krihs.re.kr/ubin/wurban/city_info_intro.php?no=1067&frommain=1&fm=y
45에스토니아탈린Tallinn2012-03-27http://ubin.krihs.re.kr/ubin/wurban/city_info_intro.php?no=1054&frommain=1&fm=y
56인도뭄바이Mumbai2012-02-23http://ubin.krihs.re.kr/ubin/wurban/city_info_intro.php?no=1052&frommain=1&fm=y
67루마니아부쿠레슈티Bucuresti2012-02-06http://ubin.krihs.re.kr/ubin/wurban/city_info_intro.php?no=1034&frommain=1&fm=y
78캄보디아프놈펜Phnom Penh2011-12-29http://ubin.krihs.re.kr/ubin/wurban/city_info_intro.php?no=1022&frommain=1&fm=y
89모로코카사블랑카Casablanca2011-11-17http://ubin.krihs.re.kr/ubin/wurban/city_info_intro.php?no=1012&frommain=1&fm=y
910콜롬비아카르타헤나Cartagena2011-10-19http://ubin.krihs.re.kr/ubin/wurban/city_info_intro.php?no=1008&frommain=1&fm=y
번호나라도시명영문표기등록일상세페이지 링크
169170프랑스소피아 앙티폴리스Sophia Antipolis2008-12-01http://ubin.krihs.re.kr/ubin/wurban/city_info_intro.php?no=168&frommain=1&fm=y
170171프랑스스트라스부르Strasbourg2008-12-01http://ubin.krihs.re.kr/ubin/wurban/city_info_intro.php?no=169&frommain=1&fm=y
171172프랑스파리Paris2008-12-01http://ubin.krihs.re.kr/ubin/wurban/city_info_intro.php?no=170&frommain=1&fm=y
172173핀란드오울루Oulu2008-12-01http://ubin.krihs.re.kr/ubin/wurban/city_info_intro.php?no=160&frommain=1&fm=y
173174핀란드헬싱키Helsinki2008-12-01http://ubin.krihs.re.kr/ubin/wurban/city_info_intro.php?no=163&frommain=1&fm=y
174175필리핀마닐라Manila2008-12-01http://ubin.krihs.re.kr/ubin/wurban/city_info_intro.php?no=136&frommain=1&fm=y
175176헝가리부다페스트Budapest2008-12-01http://ubin.krihs.re.kr/ubin/wurban/city_info_intro.php?no=172&frommain=1&fm=y
176177말레이시아푸트라자야Putrajaya2008-12-01http://ubin.krihs.re.kr/ubin/wurban/city_info_intro.php?no=542&frommain=1&fm=y
177178미국뉴욕New york2008-12-01http://ubin.krihs.re.kr/ubin/wurban/city_info_intro.php?no=135&frommain=1&fm=y
178179중국난징Nanjing(南京)2008-12-01http://ubin.krihs.re.kr/ubin/wurban/city_info_intro.php?no=544&frommain=1&fm=y