Overview

Dataset statistics

Number of variables7
Number of observations81
Missing cells56
Missing cells (%)9.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.6 KiB
Average record size in memory57.6 B

Variable types

Text5
Categorical2

Dataset

Description키,명칭,행정 시,행정 구,행정 동,대표전화,홈페이지주소
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-13031/S/1/datasetView.do

Alerts

행정 시 is highly overall correlated with 행정 구High correlation
행정 구 is highly overall correlated with 행정 시High correlation
행정 동 has 50 (61.7%) missing valuesMissing
대표전화 has 5 (6.2%) missing valuesMissing
홈페이지주소 has 1 (1.2%) missing valuesMissing
키 has unique valuesUnique
명칭 has unique valuesUnique

Reproduction

Analysis started2023-12-11 03:54:03.130950
Analysis finished2023-12-11 03:54:03.993702
Duration0.86 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

키
Text

UNIQUE 

Distinct81
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size780.0 B
2023-12-11T12:54:04.220730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters972
Distinct characters16
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique81 ?
Unique (%)100.0%

Sample

1st rowBE_IW06-0001
2nd rowBE_IW06-0040
3rd rowBE_IW06-0041
4th rowBE_IW06-0042
5th rowBE_IW06-0043
ValueCountFrequency (%)
be_iw06-0001 1
 
1.2%
be_iw06-0080 1
 
1.2%
be_iw06-0018 1
 
1.2%
be_iw06-0017 1
 
1.2%
be_iw06-0016 1
 
1.2%
be_iw06-0015 1
 
1.2%
be_iw06-0014 1
 
1.2%
be_iw06-0013 1
 
1.2%
be_iw06-0012 1
 
1.2%
be_iw06-0011 1
 
1.2%
Other values (71) 71
87.7%
2023-12-11T12:54:04.718376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 260
26.7%
6 99
 
10.2%
B 81
 
8.3%
E 81
 
8.3%
_ 81
 
8.3%
I 81
 
8.3%
W 81
 
8.3%
- 81
 
8.3%
1 19
 
2.0%
4 18
 
1.9%
Other values (6) 90
 
9.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 486
50.0%
Uppercase Letter 324
33.3%
Connector Punctuation 81
 
8.3%
Dash Punctuation 81
 
8.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 260
53.5%
6 99
 
20.4%
1 19
 
3.9%
4 18
 
3.7%
2 18
 
3.7%
3 18
 
3.7%
5 18
 
3.7%
7 18
 
3.7%
8 10
 
2.1%
9 8
 
1.6%
Uppercase Letter
ValueCountFrequency (%)
B 81
25.0%
E 81
25.0%
I 81
25.0%
W 81
25.0%
Connector Punctuation
ValueCountFrequency (%)
_ 81
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 81
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 648
66.7%
Latin 324
33.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 260
40.1%
6 99
 
15.3%
_ 81
 
12.5%
- 81
 
12.5%
1 19
 
2.9%
4 18
 
2.8%
2 18
 
2.8%
3 18
 
2.8%
5 18
 
2.8%
7 18
 
2.8%
Other values (2) 18
 
2.8%
Latin
ValueCountFrequency (%)
B 81
25.0%
E 81
25.0%
I 81
25.0%
W 81
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 972
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 260
26.7%
6 99
 
10.2%
B 81
 
8.3%
E 81
 
8.3%
_ 81
 
8.3%
I 81
 
8.3%
W 81
 
8.3%
- 81
 
8.3%
1 19
 
2.0%
4 18
 
1.9%
Other values (6) 90
 
9.3%

명칭
Text

UNIQUE 

Distinct81
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size780.0 B
2023-12-11T12:54:05.029377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length29
Mean length19.91358
Min length4

Characters and Unicode

Total characters1613
Distinct characters62
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique81 ?
Unique (%)100.0%

Sample

1st row63 Convention Center
2nd rowSETEC(Seoul Trade Exhibition & Convention)
3rd rowCOEX(Convention & Exhibition)
4th rowHotel Riviera Seoul
5th rowJW Marriott Dongdaemun Square Seoul
ValueCountFrequency (%)
seoul 27
 
11.2%
hotel 25
 
10.4%
center 8
 
3.3%
grand 4
 
1.7%
premier 4
 
1.7%
korea 4
 
1.7%
club 4
 
1.7%
4
 
1.7%
convention 4
 
1.7%
coex 3
 
1.2%
Other values (122) 153
63.7%
2023-12-11T12:54:05.551195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 166
 
10.3%
159
 
9.9%
o 133
 
8.2%
a 108
 
6.7%
n 106
 
6.6%
l 99
 
6.1%
t 98
 
6.1%
r 78
 
4.8%
u 64
 
4.0%
i 61
 
3.8%
Other values (52) 541
33.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1143
70.9%
Uppercase Letter 283
 
17.5%
Space Separator 159
 
9.9%
Other Punctuation 8
 
0.5%
Decimal Number 8
 
0.5%
Close Punctuation 3
 
0.2%
Open Punctuation 3
 
0.2%
Dash Punctuation 3
 
0.2%
Connector Punctuation 3
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 166
14.5%
o 133
11.6%
a 108
9.4%
n 106
9.3%
l 99
8.7%
t 98
8.6%
r 78
6.8%
u 64
 
5.6%
i 61
 
5.3%
s 38
 
3.3%
Other values (16) 192
16.8%
Uppercase Letter
ValueCountFrequency (%)
S 45
15.9%
H 34
12.0%
C 30
 
10.6%
P 16
 
5.7%
A 15
 
5.3%
W 14
 
4.9%
M 14
 
4.9%
T 13
 
4.6%
G 12
 
4.2%
E 11
 
3.9%
Other values (13) 79
27.9%
Decimal Number
ValueCountFrequency (%)
1 2
25.0%
0 2
25.0%
7 1
12.5%
5 1
12.5%
3 1
12.5%
6 1
12.5%
Other Punctuation
ValueCountFrequency (%)
& 6
75.0%
' 2
 
25.0%
Space Separator
ValueCountFrequency (%)
159
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1426
88.4%
Common 187
 
11.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 166
 
11.6%
o 133
 
9.3%
a 108
 
7.6%
n 106
 
7.4%
l 99
 
6.9%
t 98
 
6.9%
r 78
 
5.5%
u 64
 
4.5%
i 61
 
4.3%
S 45
 
3.2%
Other values (39) 468
32.8%
Common
ValueCountFrequency (%)
159
85.0%
& 6
 
3.2%
) 3
 
1.6%
( 3
 
1.6%
- 3
 
1.6%
_ 3
 
1.6%
1 2
 
1.1%
0 2
 
1.1%
' 2
 
1.1%
7 1
 
0.5%
Other values (3) 3
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1613
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 166
 
10.3%
159
 
9.9%
o 133
 
8.2%
a 108
 
6.7%
n 106
 
6.6%
l 99
 
6.1%
t 98
 
6.1%
r 78
 
4.8%
u 64
 
4.0%
i 61
 
3.8%
Other values (52) 541
33.5%

행정 시
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size780.0 B
<NA>
50 
Seoul
31 

Length

Max length5
Median length4
Mean length4.382716
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd rowSeoul
4th rowSeoul
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 50
61.7%
Seoul 31
38.3%

Length

2023-12-11T12:54:05.695883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:54:05.821462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 50
61.7%
seoul 31
38.3%

행정 구
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)12.3%
Missing0
Missing (%)0.0%
Memory size780.0 B
<NA>
50 
Gangnam-gu
13 
Jung-gu
6 
Seocho-gu
 
4
Songpa-gu
 
2
Other values (5)
6 

Length

Max length15
Median length4
Mean length6
Min length4

Unique

Unique4 ?
Unique (%)4.9%

Sample

1st row<NA>
2nd row<NA>
3rd rowGangnam-gu
4th rowGangnam-gu
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 50
61.7%
Gangnam-gu 13
 
16.0%
Jung-gu 6
 
7.4%
Seocho-gu 4
 
4.9%
Songpa-gu 2
 
2.5%
Mapo-gu 2
 
2.5%
Yeongdeungpo-gu 1
 
1.2%
Seongbuk-gu 1
 
1.2%
Jongno-gu 1
 
1.2%
Gangdong-gu 1
 
1.2%

Length

2023-12-11T12:54:05.943506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:54:06.095313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 50
61.7%
gangnam-gu 13
 
16.0%
jung-gu 6
 
7.4%
seocho-gu 4
 
4.9%
songpa-gu 2
 
2.5%
mapo-gu 2
 
2.5%
yeongdeungpo-gu 1
 
1.2%
seongbuk-gu 1
 
1.2%
jongno-gu 1
 
1.2%
gangdong-gu 1
 
1.2%

행정 동
Text

MISSING 

Distinct22
Distinct (%)71.0%
Missing50
Missing (%)61.7%
Memory size780.0 B
2023-12-11T12:54:06.316934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length12.290323
Min length10

Characters and Unicode

Total characters381
Distinct characters34
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)54.8%

Sample

1st rowSamseong1-dong
2nd rowCheongdam-dong
3rd rowBanpo4-dong
4th rowYangjae2-dong
5th rowYeoksam1-dong
ValueCountFrequency (%)
yeoksam1-dong 4
 
12.9%
sogong-dong 3
 
9.7%
cheongdam-dong 3
 
9.7%
banpo4-dong 2
 
6.5%
samseong1-dong 2
 
6.5%
jongam-dong 1
 
3.2%
jangchung-dong 1
 
3.2%
sinsa-dong 1
 
3.2%
cheonho2-dong 1
 
3.2%
samcheong-dong 1
 
3.2%
Other values (12) 12
38.7%
2023-12-11T12:54:06.686341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 62
16.3%
n 57
15.0%
g 50
13.1%
d 34
8.9%
- 31
8.1%
a 23
 
6.0%
e 17
 
4.5%
m 15
 
3.9%
h 10
 
2.6%
s 9
 
2.4%
Other values (24) 73
19.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 305
80.1%
Dash Punctuation 31
 
8.1%
Uppercase Letter 31
 
8.1%
Decimal Number 14
 
3.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 62
20.3%
n 57
18.7%
g 50
16.4%
d 34
11.1%
a 23
 
7.5%
e 17
 
5.6%
m 15
 
4.9%
h 10
 
3.3%
s 9
 
3.0%
i 4
 
1.3%
Other values (9) 24
 
7.9%
Uppercase Letter
ValueCountFrequency (%)
S 9
29.0%
Y 6
19.4%
C 4
12.9%
J 4
12.9%
N 2
 
6.5%
B 2
 
6.5%
E 1
 
3.2%
D 1
 
3.2%
M 1
 
3.2%
O 1
 
3.2%
Decimal Number
ValueCountFrequency (%)
1 7
50.0%
2 4
28.6%
4 2
 
14.3%
3 1
 
7.1%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 336
88.2%
Common 45
 
11.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 62
18.5%
n 57
17.0%
g 50
14.9%
d 34
10.1%
a 23
 
6.8%
e 17
 
5.1%
m 15
 
4.5%
h 10
 
3.0%
s 9
 
2.7%
S 9
 
2.7%
Other values (19) 50
14.9%
Common
ValueCountFrequency (%)
- 31
68.9%
1 7
 
15.6%
2 4
 
8.9%
4 2
 
4.4%
3 1
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 381
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 62
16.3%
n 57
15.0%
g 50
13.1%
d 34
8.9%
- 31
8.1%
a 23
 
6.0%
e 17
 
4.5%
m 15
 
3.9%
h 10
 
2.6%
s 9
 
2.4%
Other values (24) 73
19.2%

대표전화
Text

MISSING 

Distinct75
Distinct (%)98.7%
Missing5
Missing (%)6.2%
Memory size780.0 B
2023-12-11T12:54:06.941627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length12
Mean length11.763158
Min length11

Characters and Unicode

Total characters894
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)97.4%

Sample

1st row02-789-5704
2nd row02-2222-3811
3rd row02-6000-1125
4th row02-541-3111
5th row02-2276-3000
ValueCountFrequency (%)
02-3210-2100 2
 
2.6%
02-810-5113 1
 
1.3%
02-789-5704 1
 
1.3%
02-2077-9000-02-2077-9227 1
 
1.3%
02-6670-3642 1
 
1.3%
02-6203-1162 1
 
1.3%
02-2660-9020 1
 
1.3%
02-411-4922 1
 
1.3%
02-2153-0072 1
 
1.3%
02-2158-9000 1
 
1.3%
Other values (65) 65
85.5%
2023-12-11T12:54:07.420595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 209
23.4%
2 161
18.0%
- 155
17.3%
1 82
 
9.2%
5 57
 
6.4%
7 49
 
5.5%
3 48
 
5.4%
6 45
 
5.0%
4 43
 
4.8%
9 25
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 739
82.7%
Dash Punctuation 155
 
17.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 209
28.3%
2 161
21.8%
1 82
 
11.1%
5 57
 
7.7%
7 49
 
6.6%
3 48
 
6.5%
6 45
 
6.1%
4 43
 
5.8%
9 25
 
3.4%
8 20
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
- 155
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 894
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 209
23.4%
2 161
18.0%
- 155
17.3%
1 82
 
9.2%
5 57
 
6.4%
7 49
 
5.5%
3 48
 
5.4%
6 45
 
5.0%
4 43
 
4.8%
9 25
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 894
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 209
23.4%
2 161
18.0%
- 155
17.3%
1 82
 
9.2%
5 57
 
6.4%
7 49
 
5.5%
3 48
 
5.4%
6 45
 
5.0%
4 43
 
4.8%
9 25
 
2.8%

홈페이지주소
Text

MISSING 

Distinct80
Distinct (%)100.0%
Missing1
Missing (%)1.2%
Memory size780.0 B
2023-12-11T12:54:07.775466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length28
Mean length21.6625
Min length9

Characters and Unicode

Total characters1733
Distinct characters38
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique80 ?
Unique (%)100.0%

Sample

1st rowhttp://www.63convention.co.kr
2nd rowsetec.or.kr
3rd rowwww.coex.co.kr
4th rowwww.riviera.co.kr
5th rowwww.jwmarriottddm.com
ValueCountFrequency (%)
http://www.63convention.co.kr 1
 
1.2%
setec.or.kr 1
 
1.2%
http://www.minsclub.co.kr 1
 
1.2%
http://www.jfac.or.kr 1
 
1.2%
http://www.mayfield.co.kr 1
 
1.2%
http://www.maydining.co.kr 1
 
1.2%
http://www.luka511.kr 1
 
1.2%
http://www.lotteworld.com 1
 
1.2%
http://www.theraum.co.kr 1
 
1.2%
http://www.dugahun.com 1
 
1.2%
Other values (70) 70
87.5%
2023-12-11T12:54:08.371068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 181
 
10.4%
w 178
 
10.3%
o 145
 
8.4%
t 143
 
8.3%
r 104
 
6.0%
/ 90
 
5.2%
e 89
 
5.1%
a 88
 
5.1%
c 88
 
5.1%
h 69
 
4.0%
Other values (28) 558
32.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1407
81.2%
Other Punctuation 309
 
17.8%
Decimal Number 13
 
0.8%
Dash Punctuation 2
 
0.1%
Uppercase Letter 1
 
0.1%
Space Separator 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 178
12.7%
o 145
 
10.3%
t 143
 
10.2%
r 104
 
7.4%
e 89
 
6.3%
a 88
 
6.3%
c 88
 
6.3%
h 69
 
4.9%
n 63
 
4.5%
k 62
 
4.4%
Other values (16) 378
26.9%
Decimal Number
ValueCountFrequency (%)
0 4
30.8%
1 3
23.1%
3 2
15.4%
6 2
15.4%
7 1
 
7.7%
5 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
. 181
58.6%
/ 90
29.1%
: 38
 
12.3%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Uppercase Letter
ValueCountFrequency (%)
S 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1408
81.2%
Common 325
 
18.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 178
12.6%
o 145
 
10.3%
t 143
 
10.2%
r 104
 
7.4%
e 89
 
6.3%
a 88
 
6.2%
c 88
 
6.2%
h 69
 
4.9%
n 63
 
4.5%
k 62
 
4.4%
Other values (17) 379
26.9%
Common
ValueCountFrequency (%)
. 181
55.7%
/ 90
27.7%
: 38
 
11.7%
0 4
 
1.2%
1 3
 
0.9%
3 2
 
0.6%
- 2
 
0.6%
6 2
 
0.6%
7 1
 
0.3%
5 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1733
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 181
 
10.4%
w 178
 
10.3%
o 145
 
8.4%
t 143
 
8.3%
r 104
 
6.0%
/ 90
 
5.2%
e 89
 
5.1%
a 88
 
5.1%
c 88
 
5.1%
h 69
 
4.0%
Other values (28) 558
32.2%

Correlations

2023-12-11T12:54:08.525177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
키명칭행정 구행정 동대표전화홈페이지주소
키1.0001.0001.0001.0001.0001.000
명칭1.0001.0001.0001.0001.0001.000
행정 구1.0001.0001.0001.0001.0001.000
행정 동1.0001.0001.0001.0001.0001.000
대표전화1.0001.0001.0001.0001.0001.000
홈페이지주소1.0001.0001.0001.0001.0001.000
2023-12-11T12:54:08.687203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정 시행정 구
행정 시1.0001.000
행정 구1.0001.000
2023-12-11T12:54:08.805982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정 시행정 구
행정 시1.0001.000
행정 구1.0001.000

Missing values

2023-12-11T12:54:03.592300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T12:54:03.748899image/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.
2023-12-11T12:54:03.903178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

키명칭행정 시행정 구행정 동대표전화홈페이지주소
0BE_IW06-000163 Convention Center<NA><NA><NA>02-789-5704http://www.63convention.co.kr
1BE_IW06-0040SETEC(Seoul Trade Exhibition & Convention)<NA><NA><NA>02-2222-3811setec.or.kr
2BE_IW06-0041COEX(Convention & Exhibition)SeoulGangnam-guSamseong1-dong02-6000-1125www.coex.co.kr
3BE_IW06-0042Hotel Riviera SeoulSeoulGangnam-guCheongdam-dong02-541-3111www.riviera.co.kr
4BE_IW06-0043JW Marriott Dongdaemun Square Seoul<NA><NA><NA>02-2276-3000www.jwmarriottddm.com
5BE_IW06-0044JW Marriott Hotel SeoulSeoulSeocho-guBanpo4-dong02-6282-6262www.marriott.com/seljw
6BE_IW06-0045Stanford Hotel Seoul<NA><NA><NA>02-6016-0001www.stanfordseoul.com
7BE_IW06-0046The_K Hotel SeoulSeoulSeocho-guYangjae2-dong02-571-8100www.thek-hotel.co.kr
8BE_IW06-0047Grand Ambassadors Seoul<NA><NA><NA>02-2275-1101www.ambatel.com
9BE_IW06-0048Grand InterContinental Seoul Parnas<NA><NA><NA>02-555-5656www.ihg.com/intercontinental/hotels/kr/ko/reservation
키명칭행정 시행정 구행정 동대표전화홈페이지주소
71BE_IW06-0030yiod Artce<NA><NA><NA>02-741-2411http://www.yido.kr
72BE_IW06-0031Ilmin Museum of Art<NA><NA><NA>02-2020-2050http://www.ilmin.org
73BE_IW06-0032Jinjinbara<NA><NA><NA>02-3454-0633http://www.jinjinbara.com
74BE_IW06-0033Coex Aquarium<NA><NA><NA>02-6002-6200http://www.coexaqua.com
75BE_IW06-0034Top Claud<NA><NA><NA>02-2198-3300http://www.topcloud.co.kr/
76BE_IW06-0035Dia PradeshSeoulSeocho-guJamwon-dong02-3477-0033http://www.fradia.co.kr
77BE_IW06-0036South Korea Furniture Museum<NA><NA><NA>02-745-0181http://www.kofum.com
78BE_IW06-0037Korea House<NA><NA><NA>02-2270-1123http://www.koreahouse.or.kr
79BE_IW06-0038HwaSooMok&The gatheringbar<NA><NA><NA>070-7760-5392<NA>
80BE_IW06-0039aT Center<NA><NA><NA>02-6300-1114atcenter.at.or.kr