Overview

Dataset statistics

Number of variables10
Number of observations799
Missing cells532
Missing cells (%)6.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory63.3 KiB
Average record size in memory81.2 B

Variable types

Numeric1
Categorical1
Text8

Dataset

Description고유번호,언어,상호명,콘텐츠URL,주소,신주소,전화번호,웹사이트,운영시간,교통정보
Author서울관광재단
URLhttps://data.seoul.go.kr/dataList/OA-21053/S/1/datasetView.do

Alerts

콘텐츠URL has 52 (6.5%) missing valuesMissing
전화번호 has 76 (9.5%) missing valuesMissing
웹사이트 has 258 (32.3%) missing valuesMissing
운영시간 has 114 (14.3%) missing valuesMissing
교통정보 has 32 (4.0%) missing valuesMissing
고유번호 has unique valuesUnique

Reproduction

Analysis started2024-05-10 23:17:32.286917
Analysis finished2024-05-10 23:17:37.118411
Duration4.83 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

고유번호
Real number (ℝ)

UNIQUE 

Distinct799
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22255.886
Minimum13
Maximum45712
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2024-05-10T23:17:37.337210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum13
5-th percentile283.9
Q19627.5
median20240
Q341772.5
95-th percentile44263.1
Maximum45712
Range45699
Interquartile range (IQR)32145

Descriptive statistics

Standard deviation16137.438
Coefficient of variation (CV)0.72508629
Kurtosis-1.4827263
Mean22255.886
Median Absolute Deviation (MAD)17575
Skewness0.061623268
Sum17782453
Variance2.604169 × 108
MonotonicityNot monotonic
2024-05-10T23:17:37.754449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1653 1
 
0.1%
38752 1
 
0.1%
37816 1
 
0.1%
20202 1
 
0.1%
43512 1
 
0.1%
11440 1
 
0.1%
9645 1
 
0.1%
292 1
 
0.1%
41831 1
 
0.1%
9889 1
 
0.1%
Other values (789) 789
98.7%
ValueCountFrequency (%)
13 1
0.1%
61 1
0.1%
62 1
0.1%
64 1
0.1%
65 1
0.1%
66 1
0.1%
67 1
0.1%
68 1
0.1%
69 1
0.1%
70 1
0.1%
ValueCountFrequency (%)
45712 1
0.1%
45711 1
0.1%
45708 1
0.1%
45703 1
0.1%
45700 1
0.1%
45693 1
0.1%
45593 1
0.1%
45571 1
0.1%
45570 1
0.1%
45569 1
0.1%

언어
Categorical

Distinct5
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
ko
220 
ja
191 
en
182 
zh-CN
176 
zh-TW
30 

Length

Max length5
Median length2
Mean length2.7734668
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowen
2nd rowja
3rd rowzh-CN
4th rowzh-CN
5th rowja

Common Values

ValueCountFrequency (%)
ko 220
27.5%
ja 191
23.9%
en 182
22.8%
zh-CN 176
22.0%
zh-TW 30
 
3.8%

Length

2024-05-10T23:17:38.078457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:17:38.289460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
ko 220
27.5%
ja 191
23.9%
en 182
22.8%
zh-cn 176
22.0%
zh-tw 30
 
3.8%

상호명
Text

Distinct756
Distinct (%)94.6%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
2024-05-10T23:17:38.723371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length126
Median length38
Mean length12.974969
Min length2

Characters and Unicode

Total characters10367
Distinct characters722
Distinct categories13 ?
Distinct scripts6 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique722 ?
Unique (%)90.4%

Sample

1st rowSeoul Folk Flea Market
2nd rowテクノマ?ト
3rd row?流周?商品
4th rowAmorepacific 旗?店（?水）
5th rowHot Tracks(TIMES SQUARE店)
ValueCountFrequency (%)
market 37
 
2.5%
mall 18
 
1.2%
store 16
 
1.1%
the 15
 
1.0%
musinsa 12
 
0.8%
shopping 11
 
0.7%
seoul 11
 
0.7%
house 11
 
0.7%
flagship 11
 
0.7%
branch 11
 
0.7%
Other values (934) 1335
89.7%
2024-05-10T23:17:39.840388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
717
 
6.9%
e 446
 
4.3%
a 375
 
3.6%
o 343
 
3.3%
n 337
 
3.3%
? 296
 
2.9%
r 263
 
2.5%
t 249
 
2.4%
i 198
 
1.9%
S 194
 
1.9%
Other values (712) 6949
67.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3612
34.8%
Lowercase Letter 3540
34.1%
Uppercase Letter 1783
17.2%
Space Separator 717
 
6.9%
Other Punctuation 342
 
3.3%
Close Punctuation 147
 
1.4%
Open Punctuation 147
 
1.4%
Decimal Number 43
 
0.4%
Dash Punctuation 24
 
0.2%
Final Punctuation 4
 
< 0.1%
Other values (3) 8
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
ン 180
 
5.0%
店 107
 
3.0%
市 51
 
1.4%
스 50
 
1.4%
ッ 48
 
1.3%
ョ 42
 
1.2%
ト 42
 
1.2%
점 41
 
1.1%
洞 39
 
1.1%
ム 38
 
1.1%
Other values (632) 2974
82.3%
Lowercase Letter
ValueCountFrequency (%)
e 446
12.6%
a 375
10.6%
o 343
9.7%
n 337
9.5%
r 263
 
7.4%
t 249
 
7.0%
i 198
 
5.6%
l 188
 
5.3%
g 174
 
4.9%
u 140
 
4.0%
Other values (16) 827
23.4%
Uppercase Letter
ValueCountFrequency (%)
S 194
 
10.9%
M 150
 
8.4%
A 142
 
8.0%
E 137
 
7.7%
T 133
 
7.5%
O 126
 
7.1%
C 100
 
5.6%
R 87
 
4.9%
N 85
 
4.8%
D 69
 
3.9%
Other values (16) 560
31.4%
Other Punctuation
ValueCountFrequency (%)
? 296
86.5%
· 10
 
2.9%
. 10
 
2.9%
& 8
 
2.3%
@ 7
 
2.0%
' 5
 
1.5%
: 5
 
1.5%
! 1
 
0.3%
Decimal Number
ValueCountFrequency (%)
0 11
25.6%
2 8
18.6%
1 7
16.3%
6 6
14.0%
8 5
11.6%
3 5
11.6%
5 1
 
2.3%
Close Punctuation
ValueCountFrequency (%)
) 139
94.6%
） 8
 
5.4%
Open Punctuation
ValueCountFrequency (%)
( 139
94.6%
（ 8
 
5.4%
Final Punctuation
ValueCountFrequency (%)
’ 2
50.0%
” 2
50.0%
Math Symbol
ValueCountFrequency (%)
< 2
50.0%
> 2
50.0%
Initial Punctuation
ValueCountFrequency (%)
“ 2
66.7%
‘ 1
33.3%
Space Separator
ValueCountFrequency (%)
717
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5323
51.3%
Common 1432
 
13.8%
Hangul 1417
 
13.7%
Han 1114
 
10.7%
Katakana 1042
 
10.1%
Hiragana 39
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 50
 
3.5%
점 41
 
2.9%
시 37
 
2.6%
리 37
 
2.6%
장 32
 
2.3%
이 27
 
1.9%
동 25
 
1.8%
대 19
 
1.3%
아 18
 
1.3%
화 17
 
1.2%
Other values (303) 1114
78.6%
Han
ValueCountFrequency (%)
店 107
 
9.6%
市 51
 
4.6%
洞 39
 
3.5%
大 36
 
3.2%
街 27
 
2.4%
場 25
 
2.2%
明 23
 
2.1%
新 21
 
1.9%
南 21
 
1.9%
通 18
 
1.6%
Other values (230) 746
67.0%
Katakana
ValueCountFrequency (%)
ン 180
 
17.3%
ッ 48
 
4.6%
ョ 42
 
4.0%
ト 42
 
4.0%
ム 38
 
3.6%
ス 35
 
3.4%
ル 35
 
3.4%
シ 33
 
3.2%
フ 27
 
2.6%
ア 26
 
2.5%
Other values (63) 536
51.4%
Latin
ValueCountFrequency (%)
e 446
 
8.4%
a 375
 
7.0%
o 343
 
6.4%
n 337
 
6.3%
r 263
 
4.9%
t 249
 
4.7%
i 198
 
3.7%
S 194
 
3.6%
l 188
 
3.5%
g 174
 
3.3%
Other values (42) 2556
48.0%
Common
ValueCountFrequency (%)
717
50.1%
? 296
20.7%
) 139
 
9.7%
( 139
 
9.7%
- 24
 
1.7%
0 11
 
0.8%
· 10
 
0.7%
. 10
 
0.7%
（ 8
 
0.6%
2 8
 
0.6%
Other values (18) 70
 
4.9%
Hiragana
ValueCountFrequency (%)
り 15
38.5%
の 3
 
7.7%
し 3
 
7.7%
お 3
 
7.7%
き 2
 
5.1%
い 2
 
5.1%
け 2
 
5.1%
ぎ 1
 
2.6%
ね 1
 
2.6%
ん 1
 
2.6%
Other values (6) 6
 
15.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6722
64.8%
Hangul 1417
 
13.7%
CJK 1114
 
10.7%
Katakana 1042
 
10.1%
Hiragana 39
 
0.4%
None 26
 
0.3%
Punctuation 7
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
717
 
10.7%
e 446
 
6.6%
a 375
 
5.6%
o 343
 
5.1%
n 337
 
5.0%
? 296
 
4.4%
r 263
 
3.9%
t 249
 
3.7%
i 198
 
2.9%
S 194
 
2.9%
Other values (63) 3304
49.2%
Katakana
ValueCountFrequency (%)
ン 180
 
17.3%
ッ 48
 
4.6%
ョ 42
 
4.0%
ト 42
 
4.0%
ム 38
 
3.6%
ス 35
 
3.4%
ル 35
 
3.4%
シ 33
 
3.2%
フ 27
 
2.6%
ア 26
 
2.5%
Other values (63) 536
51.4%
CJK
ValueCountFrequency (%)
店 107
 
9.6%
市 51
 
4.6%
洞 39
 
3.5%
大 36
 
3.2%
街 27
 
2.4%
場 25
 
2.2%
明 23
 
2.1%
新 21
 
1.9%
南 21
 
1.9%
通 18
 
1.6%
Other values (230) 746
67.0%
Hangul
ValueCountFrequency (%)
스 50
 
3.5%
점 41
 
2.9%
시 37
 
2.6%
리 37
 
2.6%
장 32
 
2.3%
이 27
 
1.9%
동 25
 
1.8%
대 19
 
1.3%
아 18
 
1.3%
화 17
 
1.2%
Other values (303) 1114
78.6%
Hiragana
ValueCountFrequency (%)
り 15
38.5%
の 3
 
7.7%
し 3
 
7.7%
お 3
 
7.7%
き 2
 
5.1%
い 2
 
5.1%
け 2
 
5.1%
ぎ 1
 
2.6%
ね 1
 
2.6%
ん 1
 
2.6%
Other values (6) 6
 
15.4%
None
ValueCountFrequency (%)
· 10
38.5%
（ 8
30.8%
） 8
30.8%
Punctuation
ValueCountFrequency (%)
’ 2
28.6%
“ 2
28.6%
” 2
28.6%
‘ 1
14.3%

콘텐츠URL
Text

MISSING 

Distinct747
Distinct (%)100.0%
Missing52
Missing (%)6.5%
Memory size6.4 KiB
2024-05-10T23:17:40.525345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length182
Median length156
Mean length130.6747
Min length119

Characters and Unicode

Total characters97614
Distinct characters598
Distinct categories12 ?
Distinct scripts6 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique747 ?
Unique (%)100.0%

Sample

1st rowhttps://english.visitseoul.net/shopping/Seoul-Folk-Flea-Market/ENP001600?utm_source=seoulopendata&utm_medium=shopping&utm_content=ENP001600
2nd rowhttps://japanese.visitseoul.net/shopping/Techno-Mart-JP/JPP002231?utm_source=seoulopendata&utm_medium=shopping&utm_content=JPP002231
3rd rowhttps://chinese.visitseoul.net/shopping/?水Amorepacific旗?店/CNP038399?utm_source=seoulopendata&utm_medium=shopping&utm_content=CNP038399
4th rowhttps://japanese.visitseoul.net/shopping/hot-tracks-time-square-jp/JPP012709?utm_source=seoulopendata&utm_medium=shopping&utm_content=JPP012709
5th rowhttps://japanese.visitseoul.net/shopping/MECLADS/JPPh55o29?utm_source=seoulopendata&utm_medium=shopping&utm_content=JPPh55o29
ValueCountFrequency (%)
https://korean.visitseoul.net/shopping/방학동-도깨비시장-kr/kop009631?utm_source=seoulopendata&utm_medium=shopping&utm_content=kop009631 1
 
0.1%
https://english.visitseoul.net/shopping/namdaemun-market/enp000085?utm_source=seoulopendata&utm_medium=shopping&utm_content=enp000085 1
 
0.1%
https://japanese.visitseoul.net/shopping/ソルファス雪花秀フラグシップストア/jpp038445?utm_source=seoulopendata&utm_medium=shopping&utm_content=jpp038445 1
 
0.1%
https://chinese.visitseoul.net/shopping/?山?子商街용산전자상가-cn/cnp009672?utm_source=seoulopendata&utm_medium=shopping&utm_content=cnp009672 1
 
0.1%
https://korean.visitseoul.net/shopping/recode-샵/kop011227?utm_source=seoulopendata&utm_medium=shopping&utm_content=kop011227 1
 
0.1%
https://japanese.visitseoul.net/shopping/itaewon-antique-furniture-street-jp/jpp029052?utm_source=seoulopendata&utm_medium=shopping&utm_content=jpp029052 1
 
0.1%
https://japanese.visitseoul.net/shopping/dongmyo-flea-market-jp/jpp009646?utm_source=seoulopendata&utm_medium=shopping&utm_content=jpp009646 1
 
0.1%
https://english.visitseoul.net/shopping/dongwha-duty-free-shop/enp009677?utm_source=seoulopendata&utm_medium=shopping&utm_content=enp009677 1
 
0.1%
https://english.visitseoul.net/shopping/gangnam-station-underground-shopping-center/enp017740?utm_source=seoulopendata&utm_medium=shopping&utm_content=enp017740 1
 
0.1%
https://chinese.visitseoul.net/shopping/新世界免稅店（明洞店）/cnp020071?utm_source=seoulopendata&utm_medium=shopping&utm_content=cnp020071 1
 
0.1%
Other values (737) 737
98.7%
2024-05-10T23:17:41.700924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 7903
 
8.1%
e 6979
 
7.1%
s 6051
 
6.2%
o 5935
 
6.1%
n 5747
 
5.9%
u 5446
 
5.6%
p 4882
 
5.0%
i 4390
 
4.5%
m 3913
 
4.0%
/ 3735
 
3.8%
Other values (588) 42633
43.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 67480
69.1%
Other Punctuation 8441
 
8.6%
Decimal Number 8063
 
8.3%
Uppercase Letter 6137
 
6.3%
Other Letter 2252
 
2.3%
Connector Punctuation 2241
 
2.3%
Math Symbol 2241
 
2.3%
Dash Punctuation 739
 
0.8%
Close Punctuation 9
 
< 0.1%
Open Punctuation 9
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
店 69
 
3.1%
ン 60
 
2.7%
점 37
 
1.6%
리 34
 
1.5%
市 32
 
1.4%
스 31
 
1.4%
시 31
 
1.4%
장 27
 
1.2%
大 25
 
1.1%
ッ 24
 
1.1%
Other values (513) 1882
83.6%
Lowercase Letter
ValueCountFrequency (%)
t 7903
11.7%
e 6979
10.3%
s 6051
9.0%
o 5935
8.8%
n 5747
8.5%
u 5446
8.1%
p 4882
 
7.2%
i 4390
 
6.5%
m 3913
 
5.8%
h 2783
 
4.1%
Other values (16) 13451
19.9%
Uppercase Letter
ValueCountFrequency (%)
P 1905
31.0%
N 754
 
12.3%
O 527
 
8.6%
C 494
 
8.0%
E 467
 
7.6%
K 455
 
7.4%
J 388
 
6.3%
S 186
 
3.0%
T 167
 
2.7%
M 131
 
2.1%
Other values (16) 663
 
10.8%
Decimal Number
ValueCountFrequency (%)
0 2565
31.8%
1 860
 
10.7%
2 815
 
10.1%
4 655
 
8.1%
5 607
 
7.5%
9 585
 
7.3%
7 568
 
7.0%
8 486
 
6.0%
3 464
 
5.8%
6 458
 
5.7%
Other Punctuation
ValueCountFrequency (%)
/ 3735
44.2%
& 1494
 
17.7%
. 1494
 
17.7%
? 965
 
11.4%
: 747
 
8.8%
· 6
 
0.1%
Connector Punctuation
ValueCountFrequency (%)
_ 2241
100.0%
Math Symbol
ValueCountFrequency (%)
= 2241
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 739
100.0%
Close Punctuation
ValueCountFrequency (%)
） 9
100.0%
Open Punctuation
ValueCountFrequency (%)
（ 9
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%
Format
ValueCountFrequency (%)
­ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 73617
75.4%
Common 21745
 
22.3%
Hangul 1060
 
1.1%
Han 752
 
0.8%
Katakana 417
 
0.4%
Hiragana 23
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 37
 
3.5%
리 34
 
3.2%
스 31
 
2.9%
시 31
 
2.9%
장 27
 
2.5%
동 21
 
2.0%
이 20
 
1.9%
화 20
 
1.9%
대 18
 
1.7%
가 15
 
1.4%
Other values (242) 806
76.0%
Han
ValueCountFrequency (%)
店 69
 
9.2%
市 32
 
4.3%
大 25
 
3.3%
洞 23
 
3.1%
街 22
 
2.9%
百 15
 
2.0%
明 13
 
1.7%
商 13
 
1.7%
里 13
 
1.7%
中 12
 
1.6%
Other values (189) 515
68.5%
Katakana
ValueCountFrequency (%)
ン 60
 
14.4%
ッ 24
 
5.8%
ョ 19
 
4.6%
ル 18
 
4.3%
ス 17
 
4.1%
シ 16
 
3.8%
ト 15
 
3.6%
ア 13
 
3.1%
グ 13
 
3.1%
フ 12
 
2.9%
Other values (51) 210
50.4%
Latin
ValueCountFrequency (%)
t 7903
10.7%
e 6979
 
9.5%
s 6051
 
8.2%
o 5935
 
8.1%
n 5747
 
7.8%
u 5446
 
7.4%
p 4882
 
6.6%
i 4390
 
6.0%
m 3913
 
5.3%
h 2783
 
3.8%
Other values (42) 19588
26.6%
Common
ValueCountFrequency (%)
/ 3735
17.2%
0 2565
11.8%
_ 2241
10.3%
= 2241
10.3%
& 1494
 
6.9%
. 1494
 
6.9%
? 965
 
4.4%
1 860
 
4.0%
2 815
 
3.7%
: 747
 
3.4%
Other values (13) 4588
21.1%
Hiragana
ValueCountFrequency (%)
り 10
43.5%
け 2
 
8.7%
お 2
 
8.7%
の 2
 
8.7%
ぎ 1
 
4.3%
ん 1
 
4.3%
き 1
 
4.3%
し 1
 
4.3%
め 1
 
4.3%
ね 1
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 95336
97.7%
Hangul 1060
 
1.1%
CJK 752
 
0.8%
Katakana 417
 
0.4%
None 25
 
< 0.1%
Hiragana 23
 
< 0.1%
Punctuation 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 7903
 
8.3%
e 6979
 
7.3%
s 6051
 
6.3%
o 5935
 
6.2%
n 5747
 
6.0%
u 5446
 
5.7%
p 4882
 
5.1%
i 4390
 
4.6%
m 3913
 
4.1%
/ 3735
 
3.9%
Other values (60) 40355
42.3%
CJK
ValueCountFrequency (%)
店 69
 
9.2%
市 32
 
4.3%
大 25
 
3.3%
洞 23
 
3.1%
街 22
 
2.9%
百 15
 
2.0%
明 13
 
1.7%
商 13
 
1.7%
里 13
 
1.7%
中 12
 
1.6%
Other values (189) 515
68.5%
Katakana
ValueCountFrequency (%)
ン 60
 
14.4%
ッ 24
 
5.8%
ョ 19
 
4.6%
ル 18
 
4.3%
ス 17
 
4.1%
シ 16
 
3.8%
ト 15
 
3.6%
ア 13
 
3.1%
グ 13
 
3.1%
フ 12
 
2.9%
Other values (51) 210
50.4%
Hangul
ValueCountFrequency (%)
점 37
 
3.5%
리 34
 
3.2%
스 31
 
2.9%
시 31
 
2.9%
장 27
 
2.5%
동 21
 
2.0%
이 20
 
1.9%
화 20
 
1.9%
대 18
 
1.7%
가 15
 
1.4%
Other values (242) 806
76.0%
Hiragana
ValueCountFrequency (%)
り 10
43.5%
け 2
 
8.7%
お 2
 
8.7%
の 2
 
8.7%
ぎ 1
 
4.3%
ん 1
 
4.3%
き 1
 
4.3%
し 1
 
4.3%
め 1
 
4.3%
ね 1
 
4.3%
None
ValueCountFrequency (%)
） 9
36.0%
（ 9
36.0%
· 6
24.0%
­ 1
 
4.0%
Punctuation
ValueCountFrequency (%)
’ 1
100.0%

주소
Text

Distinct563
Distinct (%)70.5%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
2024-05-10T23:17:42.238838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length85
Median length62
Mean length20.578223
Min length2

Characters and Unicode

Total characters16442
Distinct characters465
Distinct categories11 ?
Distinct scripts6 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique545 ?
Unique (%)68.2%

Sample

1st row130-813 109-5, Sinseol-dong, Dongdaemun-gu, Seoul
2nd row143-200 ソウル市?津?九宜洞 546-4 テクノマ?ト江?店
3rd row
4th row 首?市城???水洞2街
5th row ソウル市永登浦?永登浦洞4街 442タイムズスクエア2階 ?保文庫 Hot Tracks
ValueCountFrequency (%)
서울 197
 
8.9%
seoul 112
 
5.0%
중구 38
 
1.7%
강남구 36
 
1.6%
korea 28
 
1.3%
jung-gu 23
 
1.0%
종로구 22
 
1.0%
jongno-gu 21
 
0.9%
마포구 21
 
0.9%
gangnam-gu 20
 
0.9%
Other values (884) 1705
76.7%
2024-05-10T23:17:43.300291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2721
 
16.5%
1 1023
 
6.2%
- 954
 
5.8%
0 631
 
3.8%
? 504
 
3.1%
3 466
 
2.8%
2 464
 
2.8%
5 453
 
2.8%
o 445
 
2.7%
g 444
 
2.7%
Other values (455) 8337
50.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4365
26.5%
Other Letter 4194
25.5%
Lowercase Letter 2800
17.0%
Space Separator 2721
16.5%
Dash Punctuation 954
 
5.8%
Other Punctuation 861
 
5.2%
Uppercase Letter 441
 
2.7%
Close Punctuation 52
 
0.3%
Open Punctuation 51
 
0.3%
Control 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 236
 
5.6%
구 218
 
5.2%
동 214
 
5.1%
市 206
 
4.9%
울 206
 
4.9%
洞 197
 
4.7%
ル 139
 
3.3%
ソ 134
 
3.2%
ウ 130
 
3.1%
首 127
 
3.0%
Other values (386) 2387
56.9%
Lowercase Letter
ValueCountFrequency (%)
o 445
15.9%
g 444
15.9%
n 408
14.6%
u 320
11.4%
e 257
9.2%
a 234
8.4%
l 138
 
4.9%
d 131
 
4.7%
m 68
 
2.4%
i 66
 
2.4%
Other values (14) 289
10.3%
Uppercase Letter
ValueCountFrequency (%)
S 157
35.6%
J 59
 
13.4%
G 35
 
7.9%
K 30
 
6.8%
C 23
 
5.2%
Y 23
 
5.2%
M 17
 
3.9%
D 17
 
3.9%
E 14
 
3.2%
H 12
 
2.7%
Other values (11) 54
 
12.2%
Decimal Number
ValueCountFrequency (%)
1 1023
23.4%
0 631
14.5%
3 466
10.7%
2 464
10.6%
5 453
10.4%
4 323
 
7.4%
8 283
 
6.5%
9 259
 
5.9%
6 234
 
5.4%
7 229
 
5.2%
Other Punctuation
ValueCountFrequency (%)
? 504
58.5%
, 348
40.4%
， 2
 
0.2%
: 2
 
0.2%
/ 2
 
0.2%
. 1
 
0.1%
· 1
 
0.1%
& 1
 
0.1%
Space Separator
ValueCountFrequency (%)
2721
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 954
100.0%
Close Punctuation
ValueCountFrequency (%)
) 52
100.0%
Open Punctuation
ValueCountFrequency (%)
( 51
100.0%
Control
ValueCountFrequency (%)
2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9007
54.8%
Latin 3241
 
19.7%
Hangul 1919
 
11.7%
Han 1720
 
10.5%
Katakana 552
 
3.4%
Hiragana 3
 
< 0.1%

Most frequent character per script

Han
ValueCountFrequency (%)
市 206
 
12.0%
洞 197
 
11.5%
首 127
 
7.4%
路 90
 
5.2%
街 69
 
4.0%
江 58
 
3.4%
中 57
 
3.3%
南 53
 
3.1%
浦 38
 
2.2%
區 31
 
1.8%
Other values (163) 794
46.2%
Hangul
ValueCountFrequency (%)
서 236
 
12.3%
구 218
 
11.4%
동 214
 
11.2%
울 206
 
10.7%
가 54
 
2.8%
남 53
 
2.8%
로 51
 
2.7%
강 40
 
2.1%
중 38
 
2.0%
포 35
 
1.8%
Other values (156) 774
40.3%
Katakana
ValueCountFrequency (%)
ル 139
25.2%
ソ 134
24.3%
ウ 130
23.6%
ン 31
 
5.6%
ム 7
 
1.3%
デ 7
 
1.3%
ギ 6
 
1.1%
ク 6
 
1.1%
ト 6
 
1.1%
ド 5
 
0.9%
Other values (44) 81
14.7%
Latin
ValueCountFrequency (%)
o 445
13.7%
g 444
13.7%
n 408
12.6%
u 320
9.9%
e 257
7.9%
a 234
 
7.2%
S 157
 
4.8%
l 138
 
4.3%
d 131
 
4.0%
m 68
 
2.1%
Other values (35) 639
19.7%
Common
ValueCountFrequency (%)
2721
30.2%
1 1023
 
11.4%
- 954
 
10.6%
0 631
 
7.0%
? 504
 
5.6%
3 466
 
5.2%
2 464
 
5.2%
5 453
 
5.0%
, 348
 
3.9%
4 323
 
3.6%
Other values (14) 1120
12.4%
Hiragana
ValueCountFrequency (%)
り 1
33.3%
び 1
33.3%
く 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12245
74.5%
Hangul 1917
 
11.7%
CJK 1718
 
10.4%
Katakana 552
 
3.4%
None 3
 
< 0.1%
Hiragana 3
 
< 0.1%
Compat Jamo 2
 
< 0.1%
CJK Compat Ideographs 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2721
22.2%
1 1023
 
8.4%
- 954
 
7.8%
0 631
 
5.2%
? 504
 
4.1%
3 466
 
3.8%
2 464
 
3.8%
5 453
 
3.7%
o 445
 
3.6%
g 444
 
3.6%
Other values (57) 4140
33.8%
Hangul
ValueCountFrequency (%)
서 236
 
12.3%
구 218
 
11.4%
동 214
 
11.2%
울 206
 
10.7%
가 54
 
2.8%
남 53
 
2.8%
로 51
 
2.7%
강 40
 
2.1%
중 38
 
2.0%
포 35
 
1.8%
Other values (155) 772
40.3%
CJK
ValueCountFrequency (%)
市 206
 
12.0%
洞 197
 
11.5%
首 127
 
7.4%
路 90
 
5.2%
街 69
 
4.0%
江 58
 
3.4%
中 57
 
3.3%
南 53
 
3.1%
浦 38
 
2.2%
區 31
 
1.8%
Other values (162) 792
46.1%
Katakana
ValueCountFrequency (%)
ル 139
25.2%
ソ 134
24.3%
ウ 130
23.6%
ン 31
 
5.6%
ム 7
 
1.3%
デ 7
 
1.3%
ギ 6
 
1.1%
ク 6
 
1.1%
ト 6
 
1.1%
ド 5
 
0.9%
Other values (44) 81
14.7%
None
ValueCountFrequency (%)
， 2
66.7%
· 1
33.3%
Compat Jamo
ValueCountFrequency (%)
ㆍ 2
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
樓 2
100.0%
Hiragana
ValueCountFrequency (%)
り 1
33.3%
び 1
33.3%
く 1
33.3%

신주소
Text

Distinct780
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
2024-05-10T23:17:44.017757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length100
Median length60
Mean length34.515645
Min length2

Characters and Unicode

Total characters27578
Distinct characters729
Distinct categories10 ?
Distinct scripts6 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique775 ?
Unique (%)97.0%

Sample

1st row02586 21, Cheonho-daero 4-gil, Dongdaemun-gu, Seoul
2nd row05116 ソウル市クァンジン(?津)?クァンナルロ56ギル85 (九宜洞)テクノマ?ト江?店
3rd row
4th row04797 首?市城??峨嵯山路11街7 (?水洞2街, ASEA E&T Co. Ltd.)
5th row07305 ソウル市ヨンドゥンポ(永登浦)?ヨンジュンロ15 (永登浦洞4街)タイムズスクエア2階 ?保文庫 Hot Tracks
ValueCountFrequency (%)
서울 184
 
4.9%
seoul 177
 
4.8%
중구 43
 
1.2%
jung-gu 38
 
1.0%
강남구 37
 
1.0%
gangnam-gu 32
 
0.9%
首?市 31
 
0.8%
종로구 29
 
0.8%
서울특별시 26
 
0.7%
04536 24
 
0.6%
Other values (1546) 3105
83.3%
2024-05-10T23:17:45.310458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3651
 
13.2%
0 1328
 
4.8%
1 934
 
3.4%
? 925
 
3.4%
4 795
 
2.9%
3 771
 
2.8%
o 681
 
2.5%
g 628
 
2.3%
, 627
 
2.3%
2 618
 
2.2%
Other values (719) 16620
60.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8823
32.0%
Decimal Number 6563
23.8%
Lowercase Letter 4350
15.8%
Space Separator 3651
13.2%
Other Punctuation 1598
 
5.8%
Uppercase Letter 870
 
3.2%
Open Punctuation 576
 
2.1%
Close Punctuation 575
 
2.1%
Dash Punctuation 562
 
2.0%
Math Symbol 10
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
ン 429
 
4.9%
市 344
 
3.9%
ル 307
 
3.5%
서 256
 
2.9%
路 250
 
2.8%
로 239
 
2.7%
구 237
 
2.7%
울 226
 
2.6%
ソ 225
 
2.6%
ウ 217
 
2.5%
Other values (645) 6093
69.1%
Uppercase Letter
ValueCountFrequency (%)
S 250
28.7%
J 83
 
9.5%
G 58
 
6.7%
M 57
 
6.6%
E 43
 
4.9%
F 39
 
4.5%
C 35
 
4.0%
Y 34
 
3.9%
T 33
 
3.8%
A 32
 
3.7%
Other values (15) 206
23.7%
Lowercase Letter
ValueCountFrequency (%)
o 681
15.7%
g 628
14.4%
n 529
12.2%
u 504
11.6%
e 414
9.5%
a 341
7.8%
l 309
7.1%
r 188
 
4.3%
i 148
 
3.4%
d 127
 
2.9%
Other values (13) 481
11.1%
Decimal Number
ValueCountFrequency (%)
0 1328
20.2%
1 934
14.2%
4 795
12.1%
3 771
11.7%
2 618
9.4%
5 598
9.1%
6 570
8.7%
7 379
 
5.8%
8 321
 
4.9%
9 249
 
3.8%
Other Punctuation
ValueCountFrequency (%)
? 925
57.9%
, 627
39.2%
、 19
 
1.2%
， 9
 
0.6%
/ 8
 
0.5%
& 3
 
0.2%
· 3
 
0.2%
. 2
 
0.1%
: 2
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 563
97.9%
） 12
 
2.1%
Open Punctuation
ValueCountFrequency (%)
( 563
97.7%
（ 13
 
2.3%
Space Separator
ValueCountFrequency (%)
3651
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 562
100.0%
Math Symbol
ValueCountFrequency (%)
~ 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13535
49.1%
Latin 5220
 
18.9%
Hangul 3405
 
12.3%
Han 2807
 
10.2%
Katakana 2602
 
9.4%
Hiragana 9
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 256
 
7.5%
로 239
 
7.0%
구 237
 
7.0%
울 226
 
6.6%
동 215
 
6.3%
길 105
 
3.1%
남 75
 
2.2%
대 74
 
2.2%
가 62
 
1.8%
강 53
 
1.6%
Other values (295) 1863
54.7%
Han
ValueCountFrequency (%)
市 344
 
12.3%
路 250
 
8.9%
首 201
 
7.2%
洞 180
 
6.4%
街 130
 
4.6%
南 100
 
3.6%
中 90
 
3.2%
江 88
 
3.1%
大 77
 
2.7%
浦 58
 
2.1%
Other values (261) 1289
45.9%
Katakana
ValueCountFrequency (%)
ン 429
16.5%
ル 307
 
11.8%
ソ 225
 
8.6%
ウ 217
 
8.3%
ロ 146
 
5.6%
チ 103
 
4.0%
ョ 96
 
3.7%
ギ 90
 
3.5%
ム 75
 
2.9%
ク 51
 
2.0%
Other values (61) 863
33.2%
Latin
ValueCountFrequency (%)
o 681
13.0%
g 628
12.0%
n 529
10.1%
u 504
9.7%
e 414
 
7.9%
a 341
 
6.5%
l 309
 
5.9%
S 250
 
4.8%
r 188
 
3.6%
i 148
 
2.8%
Other values (38) 1228
23.5%
Common
ValueCountFrequency (%)
3651
27.0%
0 1328
 
9.8%
1 934
 
6.9%
? 925
 
6.8%
4 795
 
5.9%
3 771
 
5.7%
, 627
 
4.6%
2 618
 
4.6%
5 598
 
4.4%
6 570
 
4.2%
Other values (16) 2718
20.1%
Hiragana
ValueCountFrequency (%)
の 2
22.2%
ぺ 1
11.1%
り 1
11.1%
か 1
11.1%
ら 1
11.1%
く 1
11.1%
せ 1
11.1%
び 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18699
67.8%
Hangul 3403
 
12.3%
CJK 2804
 
10.2%
Katakana 2602
 
9.4%
None 56
 
0.2%
Hiragana 9
 
< 0.1%
CJK Compat Ideographs 3
 
< 0.1%
Compat Jamo 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3651
19.5%
0 1328
 
7.1%
1 934
 
5.0%
? 925
 
4.9%
4 795
 
4.3%
3 771
 
4.1%
o 681
 
3.6%
g 628
 
3.4%
, 627
 
3.4%
2 618
 
3.3%
Other values (59) 7741
41.4%
Katakana
ValueCountFrequency (%)
ン 429
16.5%
ル 307
 
11.8%
ソ 225
 
8.6%
ウ 217
 
8.3%
ロ 146
 
5.6%
チ 103
 
4.0%
ョ 96
 
3.7%
ギ 90
 
3.5%
ム 75
 
2.9%
ク 51
 
2.0%
Other values (61) 863
33.2%
CJK
ValueCountFrequency (%)
市 344
 
12.3%
路 250
 
8.9%
首 201
 
7.2%
洞 180
 
6.4%
街 130
 
4.6%
南 100
 
3.6%
中 90
 
3.2%
江 88
 
3.1%
大 77
 
2.7%
浦 58
 
2.1%
Other values (259) 1286
45.9%
Hangul
ValueCountFrequency (%)
서 256
 
7.5%
로 239
 
7.0%
구 237
 
7.0%
울 226
 
6.6%
동 215
 
6.3%
길 105
 
3.1%
남 75
 
2.2%
대 74
 
2.2%
가 62
 
1.8%
강 53
 
1.6%
Other values (294) 1861
54.7%
None
ValueCountFrequency (%)
、 19
33.9%
（ 13
23.2%
） 12
21.4%
， 9
16.1%
· 3
 
5.4%
Compat Jamo
ValueCountFrequency (%)
ㆍ 2
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
樓 2
66.7%
龍 1
33.3%
Hiragana
ValueCountFrequency (%)
の 2
22.2%
ぺ 1
11.1%
り 1
11.1%
か 1
11.1%
ら 1
11.1%
く 1
11.1%
せ 1
11.1%
び 1
11.1%

전화번호
Text

MISSING 

Distinct367
Distinct (%)50.8%
Missing76
Missing (%)9.5%
Memory size6.4 KiB
2024-05-10T23:17:46.162474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length46
Mean length13.838174
Min length6

Characters and Unicode

Total characters10005
Distinct characters63
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique211 ?
Unique (%)29.2%

Sample

1st row+82-2-2232-3367
2nd row+82-2-3424-0114
3rd row+82-2-469-8600
4th row+82-507-1409-9961
5th row+82-2-6954-2389
ValueCountFrequency (%)
82-2-120 36
 
4.8%
02-120 13
 
1.7%
82-2-3449-4114 8
 
1.1%
5
 
0.7%
82-2-767-2233 4
 
0.5%
82-2-1588-1234 4
 
0.5%
82-2-6438-1234 4
 
0.5%
82-70-4006-4573 4
 
0.5%
82-2-3424-0114 4
 
0.5%
82-2-707-4700 4
 
0.5%
Other values (371) 658
88.4%
2024-05-10T23:17:47.195852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1899
19.0%
2 1731
17.3%
0 1026
10.3%
8 904
9.0%
1 742
 
7.4%
3 680
 
6.8%
4 534
 
5.3%
5 522
 
5.2%
+ 520
 
5.2%
7 513
 
5.1%
Other values (53) 934
9.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7450
74.5%
Dash Punctuation 1899
 
19.0%
Math Symbol 520
 
5.2%
Other Letter 40
 
0.4%
Lowercase Letter 30
 
0.3%
Other Punctuation 24
 
0.2%
Space Separator 21
 
0.2%
Close Punctuation 7
 
0.1%
Control 6
 
0.1%
Uppercase Letter 4
 
< 0.1%
Other values (2) 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
번 4
 
10.0%
호 4
 
10.0%
전 3
 
7.5%
문 2
 
5.0%
咨 2
 
5.0%
스 2
 
5.0%
팩 2
 
5.0%
화 2
 
5.0%
의 2
 
5.0%
모 1
 
2.5%
Other values (16) 16
40.0%
Lowercase Letter
ValueCountFrequency (%)
e 5
16.7%
n 4
13.3%
r 4
13.3%
u 3
10.0%
b 2
 
6.7%
m 2
 
6.7%
h 2
 
6.7%
i 2
 
6.7%
o 1
 
3.3%
q 1
 
3.3%
Other values (4) 4
13.3%
Decimal Number
ValueCountFrequency (%)
2 1731
23.2%
0 1026
13.8%
8 904
12.1%
1 742
10.0%
3 680
 
9.1%
4 534
 
7.2%
5 522
 
7.0%
7 513
 
6.9%
6 409
 
5.5%
9 389
 
5.2%
Uppercase Letter
ValueCountFrequency (%)
I 1
25.0%
P 1
25.0%
F 1
25.0%
O 1
25.0%
Other Punctuation
ValueCountFrequency (%)
? 14
58.3%
/ 10
41.7%
Dash Punctuation
ValueCountFrequency (%)
- 1899
100.0%
Math Symbol
ValueCountFrequency (%)
+ 520
100.0%
Space Separator
ValueCountFrequency (%)
21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Control
ValueCountFrequency (%)
6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Format
ValueCountFrequency (%)
­ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9931
99.3%
Hangul 37
 
0.4%
Latin 34
 
0.3%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
번 4
 
10.8%
호 4
 
10.8%
전 3
 
8.1%
문 2
 
5.4%
스 2
 
5.4%
팩 2
 
5.4%
화 2
 
5.4%
의 2
 
5.4%
모 1
 
2.7%
점 1
 
2.7%
Other values (14) 14
37.8%
Common
ValueCountFrequency (%)
- 1899
19.1%
2 1731
17.4%
0 1026
10.3%
8 904
9.1%
1 742
 
7.5%
3 680
 
6.8%
4 534
 
5.4%
5 522
 
5.3%
+ 520
 
5.2%
7 513
 
5.2%
Other values (9) 860
8.7%
Latin
ValueCountFrequency (%)
e 5
14.7%
n 4
11.8%
r 4
11.8%
u 3
 
8.8%
b 2
 
5.9%
m 2
 
5.9%
h 2
 
5.9%
i 2
 
5.9%
I 1
 
2.9%
o 1
 
2.9%
Other values (8) 8
23.5%
Han
ValueCountFrequency (%)
咨 2
66.7%
展 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9964
99.6%
Hangul 37
 
0.4%
CJK 3
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1899
19.1%
2 1731
17.4%
0 1026
10.3%
8 904
9.1%
1 742
 
7.4%
3 680
 
6.8%
4 534
 
5.4%
5 522
 
5.2%
+ 520
 
5.2%
7 513
 
5.1%
Other values (26) 893
9.0%
Hangul
ValueCountFrequency (%)
번 4
 
10.8%
호 4
 
10.8%
전 3
 
8.1%
문 2
 
5.4%
스 2
 
5.4%
팩 2
 
5.4%
화 2
 
5.4%
의 2
 
5.4%
모 1
 
2.7%
점 1
 
2.7%
Other values (14) 14
37.8%
CJK
ValueCountFrequency (%)
咨 2
66.7%
展 1
33.3%
None
ValueCountFrequency (%)
­ 1
100.0%

웹사이트
Text

MISSING 

Distinct221
Distinct (%)40.9%
Missing258
Missing (%)32.3%
Memory size6.4 KiB
2024-05-10T23:17:47.820429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length216
Median length60
Mean length33.465804
Min length10

Characters and Unicode

Total characters18105
Distinct characters68
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique99 ?
Unique (%)18.3%

Sample

1st rowhttp://www.pungmul.or.kr/index.html
2nd rowhttp://www.tm21.com
3rd rowhttps://www.amore-seongsu.com/main
4th rowhttp://www.hottracks.co.kr
5th rowwww.meclads.com
ValueCountFrequency (%)
https://www.kakaofriends.com/kr/index 8
 
1.5%
http://www.hottracks.co.kr 8
 
1.5%
https://www.instagram.com/musinsaterrace 8
 
1.5%
http://store.musinsa.com/musinsastandard 8
 
1.5%
http://www.tm21.com 5
 
0.9%
http://www.mariooutlet.co.kr 5
 
0.9%
https://www.thehyundaiseoul.com 5
 
0.9%
http://store.emart.com 5
 
0.9%
https://www.hdc-iparkmall.com/main/index.do 5
 
0.9%
https://www.starfield.co.kr/coexmall/main.do 5
 
0.9%
Other values (206) 479
88.5%
2024-05-10T23:17:49.018124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 1684
 
9.3%
/ 1665
 
9.2%
. 1253
 
6.9%
w 1181
 
6.5%
o 1159
 
6.4%
a 934
 
5.2%
e 830
 
4.6%
s 827
 
4.6%
m 793
 
4.4%
r 744
 
4.1%
Other values (58) 7035
38.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 13675
75.5%
Other Punctuation 3534
 
19.5%
Decimal Number 478
 
2.6%
Uppercase Letter 225
 
1.2%
Math Symbol 81
 
0.4%
Connector Punctuation 54
 
0.3%
Dash Punctuation 51
 
0.3%
Space Separator 7
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 1684
12.3%
w 1181
 
8.6%
o 1159
 
8.5%
a 934
 
6.8%
e 830
 
6.1%
s 827
 
6.0%
m 793
 
5.8%
r 744
 
5.4%
h 719
 
5.3%
n 711
 
5.2%
Other values (16) 4093
29.9%
Uppercase Letter
ValueCountFrequency (%)
P 37
16.4%
C 27
12.0%
D 26
11.6%
M 21
9.3%
B 16
 
7.1%
I 14
 
6.2%
S 13
 
5.8%
V 12
 
5.3%
A 9
 
4.0%
Y 8
 
3.6%
Other values (11) 42
18.7%
Decimal Number
ValueCountFrequency (%)
0 215
45.0%
2 75
 
15.7%
1 52
 
10.9%
6 36
 
7.5%
3 28
 
5.9%
4 17
 
3.6%
9 16
 
3.3%
8 14
 
2.9%
7 13
 
2.7%
5 12
 
2.5%
Other Punctuation
ValueCountFrequency (%)
/ 1665
47.1%
. 1253
35.5%
: 514
 
14.5%
? 52
 
1.5%
% 32
 
0.9%
& 17
 
0.5%
# 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
= 81
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 54
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 51
100.0%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 13900
76.8%
Common 4205
 
23.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 1684
 
12.1%
w 1181
 
8.5%
o 1159
 
8.3%
a 934
 
6.7%
e 830
 
6.0%
s 827
 
5.9%
m 793
 
5.7%
r 744
 
5.4%
h 719
 
5.2%
n 711
 
5.1%
Other values (37) 4318
31.1%
Common
ValueCountFrequency (%)
/ 1665
39.6%
. 1253
29.8%
: 514
 
12.2%
0 215
 
5.1%
= 81
 
1.9%
2 75
 
1.8%
_ 54
 
1.3%
? 52
 
1.2%
1 52
 
1.2%
- 51
 
1.2%
Other values (11) 193
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18105
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 1684
 
9.3%
/ 1665
 
9.2%
. 1253
 
6.9%
w 1181
 
6.5%
o 1159
 
6.4%
a 934
 
5.2%
e 830
 
4.6%
s 827
 
4.6%
m 793
 
4.4%
r 744
 
4.1%
Other values (58) 7035
38.9%

운영시간
Text

MISSING 

Distinct560
Distinct (%)81.8%
Missing114
Missing (%)14.3%
Memory size6.4 KiB
2024-05-10T23:17:49.562863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length318
Median length156
Mean length28.414599
Min length5

Characters and Unicode

Total characters19464
Distinct characters515
Distinct categories11 ?
Distinct scripts6 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique481 ?
Unique (%)70.2%

Sample

1st rowDaily 10:00 - 19:00 KST *Closed Tuesdays* Restaurant, Daily 10:00 - 22:00 KST *Closed Tuesdays*
2nd row江?店／10:00~20:00(?月第2?第4火曜日定休) (KST) 新道林店／月?木曜日月~金 10:30~20:00 (KST)、土~日 11:00~20:00 (KST)
3rd row10:30 ~ 20:30 (KST)
4th row10:30?22:00 KST
5th row火曜日?日曜日12:00-21:00 KST
ValueCountFrequency (%)
kst 465
 
14.5%
442
 
13.8%
10:30 97
 
3.0%
daily 95
 
3.0%
20:00 84
 
2.6%
10:00 75
 
2.3%
22:00 59
 
1.8%
11:00 58
 
1.8%
21:00 51
 
1.6%
18:00 38
 
1.2%
Other values (721) 1746
54.4%
2024-05-10T23:17:50.860341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3698
19.0%
2638
 
13.6%
: 1663
 
8.5%
1 1247
 
6.4%
2 836
 
4.3%
S 542
 
2.8%
~ 513
 
2.6%
T 506
 
2.6%
K 491
 
2.5%
3 467
 
2.4%
Other values (505) 6863
35.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6671
34.3%
Space Separator 2638
 
13.6%
Other Letter 2525
 
13.0%
Other Punctuation 2209
 
11.3%
Lowercase Letter 2021
 
10.4%
Uppercase Letter 1815
 
9.3%
Math Symbol 521
 
2.7%
Dash Punctuation 430
 
2.2%
Open Punctuation 312
 
1.6%
Close Punctuation 312
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
日 152
 
6.0%
일 104
 
4.1%
周 93
 
3.7%
店 58
 
2.3%
매 51
 
2.0%
曜 47
 
1.9%
週 39
 
1.5%
이 36
 
1.4%
시 35
 
1.4%
토 31
 
1.2%
Other values (425) 1879
74.4%
Lowercase Letter
ValueCountFrequency (%)
a 257
12.7%
y 207
10.2%
e 195
9.6%
r 171
8.5%
i 153
 
7.6%
s 145
 
7.2%
l 134
 
6.6%
o 132
 
6.5%
n 110
 
5.4%
u 98
 
4.8%
Other values (15) 419
20.7%
Uppercase Letter
ValueCountFrequency (%)
S 542
29.9%
T 506
27.9%
K 491
27.1%
D 85
 
4.7%
H 32
 
1.8%
O 26
 
1.4%
M 23
 
1.3%
F 19
 
1.0%
C 18
 
1.0%
W 17
 
0.9%
Other values (11) 56
 
3.1%
Other Punctuation
ValueCountFrequency (%)
: 1663
75.3%
? 299
 
13.5%
, 71
 
3.2%
* 49
 
2.2%
、 30
 
1.4%
/ 24
 
1.1%
： 22
 
1.0%
※ 16
 
0.7%
， 14
 
0.6%
. 7
 
0.3%
Other values (4) 14
 
0.6%
Decimal Number
ValueCountFrequency (%)
0 3698
55.4%
1 1247
 
18.7%
2 836
 
12.5%
3 467
 
7.0%
9 169
 
2.5%
8 140
 
2.1%
4 39
 
0.6%
7 35
 
0.5%
5 24
 
0.4%
6 16
 
0.2%
Math Symbol
ValueCountFrequency (%)
~ 513
98.5%
> 4
 
0.8%
< 4
 
0.8%
Open Punctuation
ValueCountFrequency (%)
( 304
97.4%
（ 8
 
2.6%
Close Punctuation
ValueCountFrequency (%)
) 303
97.1%
） 9
 
2.9%
Space Separator
ValueCountFrequency (%)
2638
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 430
100.0%
Format
ValueCountFrequency (%)
­ 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13103
67.3%
Latin 3836
 
19.7%
Han 1219
 
6.3%
Hangul 1017
 
5.2%
Hiragana 201
 
1.0%
Katakana 88
 
0.5%

Most frequent character per script

Han
ValueCountFrequency (%)
日 152
 
12.5%
周 93
 
7.6%
店 58
 
4.8%
曜 47
 
3.9%
週 39
 
3.2%
各 29
 
2.4%
異 29
 
2.4%
一 29
 
2.4%
月 27
 
2.2%
同 26
 
2.1%
Other values (181) 690
56.6%
Hangul
ValueCountFrequency (%)
일 104
 
10.2%
매 51
 
5.0%
이 36
 
3.5%
시 35
 
3.4%
토 31
 
3.0%
월 30
 
2.9%
장 29
 
2.9%
금 25
 
2.5%
요 21
 
2.1%
간 21
 
2.1%
Other values (172) 634
62.3%
Latin
ValueCountFrequency (%)
S 542
14.1%
T 506
13.2%
K 491
12.8%
a 257
 
6.7%
y 207
 
5.4%
e 195
 
5.1%
r 171
 
4.5%
i 153
 
4.0%
s 145
 
3.8%
l 134
 
3.5%
Other values (36) 1035
27.0%
Katakana
ValueCountFrequency (%)
ン 10
 
11.4%
ト 7
 
8.0%
ラ 5
 
5.7%
ス 5
 
5.7%
イ 5
 
5.7%
レ 5
 
5.7%
ッ 4
 
4.5%
ェ 4
 
4.5%
ロ 3
 
3.4%
テ 3
 
3.4%
Other values (25) 37
42.0%
Common
ValueCountFrequency (%)
0 3698
28.2%
2638
20.1%
: 1663
12.7%
1 1247
 
9.5%
2 836
 
6.4%
~ 513
 
3.9%
3 467
 
3.6%
- 430
 
3.3%
( 304
 
2.3%
) 303
 
2.3%
Other values (24) 1004
 
7.7%
Hiragana
ValueCountFrequency (%)
に 28
13.9%
な 27
13.4%
る 26
12.9%
よ 26
12.9%
り 26
12.9%
ま 8
 
4.0%
は 7
 
3.5%
の 7
 
3.5%
っ 5
 
2.5%
て 5
 
2.5%
Other values (17) 36
17.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16822
86.4%
CJK 1219
 
6.3%
Hangul 1017
 
5.2%
Hiragana 201
 
1.0%
None 101
 
0.5%
Katakana 88
 
0.5%
Punctuation 16
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3698
22.0%
2638
15.7%
: 1663
 
9.9%
1 1247
 
7.4%
2 836
 
5.0%
S 542
 
3.2%
~ 513
 
3.0%
T 506
 
3.0%
K 491
 
2.9%
3 467
 
2.8%
Other values (60) 4221
25.1%
CJK
ValueCountFrequency (%)
日 152
 
12.5%
周 93
 
7.6%
店 58
 
4.8%
曜 47
 
3.9%
週 39
 
3.2%
各 29
 
2.4%
異 29
 
2.4%
一 29
 
2.4%
月 27
 
2.2%
同 26
 
2.1%
Other values (181) 690
56.6%
Hangul
ValueCountFrequency (%)
일 104
 
10.2%
매 51
 
5.0%
이 36
 
3.5%
시 35
 
3.4%
토 31
 
3.0%
월 30
 
2.9%
장 29
 
2.9%
금 25
 
2.5%
요 21
 
2.1%
간 21
 
2.1%
Other values (172) 634
62.3%
None
ValueCountFrequency (%)
、 30
29.7%
： 22
21.8%
， 14
13.9%
­ 10
 
9.9%
） 9
 
8.9%
（ 8
 
7.9%
。 5
 
5.0%
／ 2
 
2.0%
· 1
 
1.0%
Hiragana
ValueCountFrequency (%)
に 28
13.9%
な 27
13.4%
る 26
12.9%
よ 26
12.9%
り 26
12.9%
ま 8
 
4.0%
は 7
 
3.5%
の 7
 
3.5%
っ 5
 
2.5%
て 5
 
2.5%
Other values (17) 36
17.9%
Punctuation
ValueCountFrequency (%)
※ 16
100.0%
Katakana
ValueCountFrequency (%)
ン 10
 
11.4%
ト 7
 
8.0%
ラ 5
 
5.7%
ス 5
 
5.7%
イ 5
 
5.7%
レ 5
 
5.7%
ッ 4
 
4.5%
ェ 4
 
4.5%
ロ 3
 
3.4%
テ 3
 
3.4%
Other values (25) 37
42.0%

교통정보
Text

MISSING 

Distinct729
Distinct (%)95.0%
Missing32
Missing (%)4.0%
Memory size6.4 KiB
2024-05-10T23:17:51.754725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length191
Median length114
Mean length34.718383
Min length7

Characters and Unicode

Total characters26629
Distinct characters609
Distinct categories11 ?
Distinct scripts6 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique696 ?
Unique (%)90.7%

Sample

1st rowSubway Lines 1 & 2, Sinseoldong Station, Exit 9
2nd row地下?2?線?カンビョン??地下?行通路に連結
3rd row?水站2?出口步行264米
4th row地下?1?線「ヨンドゥンポ」?3番出口500m
5th row地下?6?線「ハンガンジン」?2番出口
ValueCountFrequency (%)
station 208
 
5.2%
line 187
 
4.7%
subway 178
 
4.4%
exit 158
 
3.9%
출구 152
 
3.8%
113
 
2.8%
2 104
 
2.6%
4 89
 
2.2%
3 86
 
2.1%
1 81
 
2.0%
Other values (1047) 2665
66.3%
2024-05-10T23:17:53.132532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3707
 
13.9%
? 1754
 
6.6%
n 948
 
3.6%
i 813
 
3.1%
t 739
 
2.8%
o 683
 
2.6%
a 600
 
2.3%
, 561
 
2.1%
1 557
 
2.1%
口 466
 
1.7%
Other values (599) 15801
59.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8656
32.5%
Lowercase Letter 6691
25.1%
Space Separator 3707
13.9%
Decimal Number 3008
 
11.3%
Other Punctuation 2698
 
10.1%
Uppercase Letter 1197
 
4.5%
Close Punctuation 302
 
1.1%
Open Punctuation 302
 
1.1%
Dash Punctuation 39
 
0.1%
Math Symbol 16
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
口 466
 
5.4%
出 462
 
5.3%
ン 389
 
4.5%
線 338
 
3.9%
구 299
 
3.5%
선 278
 
3.2%
번 274
 
3.2%
地 265
 
3.1%
番 262
 
3.0%
출 250
 
2.9%
Other values (518) 5373
62.1%
Lowercase Letter
ValueCountFrequency (%)
n 948
14.2%
i 813
12.2%
t 739
11.0%
o 683
10.2%
a 600
9.0%
e 457
 
6.8%
u 361
 
5.4%
g 298
 
4.5%
y 266
 
4.0%
s 203
 
3.0%
Other values (15) 1323
19.8%
Uppercase Letter
ValueCountFrequency (%)
S 426
35.6%
L 222
18.5%
E 215
18.0%
M 37
 
3.1%
A 34
 
2.8%
H 32
 
2.7%
G 31
 
2.6%
J 27
 
2.3%
B 24
 
2.0%
D 22
 
1.8%
Other values (13) 127
 
10.6%
Other Punctuation
ValueCountFrequency (%)
? 1754
65.0%
, 561
 
20.8%
/ 112
 
4.2%
、 93
 
3.4%
& 60
 
2.2%
* 46
 
1.7%
· 34
 
1.3%
， 20
 
0.7%
. 8
 
0.3%
。 5
 
0.2%
Other values (2) 5
 
0.2%
Decimal Number
ValueCountFrequency (%)
1 557
18.5%
2 459
15.3%
3 422
14.0%
5 409
13.6%
4 355
11.8%
6 245
8.1%
0 188
 
6.2%
7 162
 
5.4%
8 128
 
4.3%
9 83
 
2.8%
Close Punctuation
ValueCountFrequency (%)
」 194
64.2%
) 105
34.8%
） 3
 
1.0%
Open Punctuation
ValueCountFrequency (%)
「 194
64.2%
( 105
34.8%
（ 3
 
1.0%
Math Symbol
ValueCountFrequency (%)
~ 10
62.5%
→ 6
37.5%
Space Separator
ValueCountFrequency (%)
3707
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 39
100.0%
Control
ValueCountFrequency (%)
13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10085
37.9%
Latin 7888
29.6%
Han 3749
 
14.1%
Hangul 3072
 
11.5%
Katakana 1653
 
6.2%
Hiragana 182
 
0.7%

Most frequent character per script

Han
ValueCountFrequency (%)
口 466
 
12.4%
出 462
 
12.3%
線 338
 
9.0%
地 265
 
7.1%
番 262
 
7.0%
站 249
 
6.6%
下 211
 
5.6%
分 98
 
2.6%
號 83
 
2.2%
行 52
 
1.4%
Other values (232) 1263
33.7%
Hangul
ValueCountFrequency (%)
구 299
 
9.7%
선 278
 
9.0%
번 274
 
8.9%
출 250
 
8.1%
호 238
 
7.7%
역 234
 
7.6%
분 77
 
2.5%
로 69
 
2.2%
서 58
 
1.9%
도 56
 
1.8%
Other values (184) 1239
40.3%
Katakana
ValueCountFrequency (%)
ン 389
23.5%
ョ 108
 
6.5%
ク 76
 
4.6%
ム 57
 
3.4%
チ 52
 
3.1%
プ 50
 
3.0%
デ 48
 
2.9%
ジ 46
 
2.8%
イ 44
 
2.7%
ア 43
 
2.6%
Other values (58) 740
44.8%
Latin
ValueCountFrequency (%)
n 948
12.0%
i 813
 
10.3%
t 739
 
9.4%
o 683
 
8.7%
a 600
 
7.6%
e 457
 
5.8%
S 426
 
5.4%
u 361
 
4.6%
g 298
 
3.8%
y 266
 
3.4%
Other values (38) 2297
29.1%
Common
ValueCountFrequency (%)
3707
36.8%
? 1754
17.4%
, 561
 
5.6%
1 557
 
5.5%
2 459
 
4.6%
3 422
 
4.2%
5 409
 
4.1%
4 355
 
3.5%
6 245
 
2.4%
」 194
 
1.9%
Other values (23) 1422
 
14.1%
Hiragana
ValueCountFrequency (%)
か 54
29.7%
ら 54
29.7%
の 10
 
5.5%
り 9
 
4.9%
に 8
 
4.4%
を 5
 
2.7%
え 4
 
2.2%
で 4
 
2.2%
し 4
 
2.2%
と 4
 
2.2%
Other values (14) 26
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17419
65.4%
CJK 3749
 
14.1%
Hangul 3072
 
11.5%
Katakana 1653
 
6.2%
None 548
 
2.1%
Hiragana 182
 
0.7%
Arrows 6
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3707
21.3%
? 1754
 
10.1%
n 948
 
5.4%
i 813
 
4.7%
t 739
 
4.2%
o 683
 
3.9%
a 600
 
3.4%
, 561
 
3.2%
1 557
 
3.2%
2 459
 
2.6%
Other values (61) 6598
37.9%
CJK
ValueCountFrequency (%)
口 466
 
12.4%
出 462
 
12.3%
線 338
 
9.0%
地 265
 
7.1%
番 262
 
7.0%
站 249
 
6.6%
下 211
 
5.6%
分 98
 
2.6%
號 83
 
2.2%
行 52
 
1.4%
Other values (232) 1263
33.7%
Katakana
ValueCountFrequency (%)
ン 389
23.5%
ョ 108
 
6.5%
ク 76
 
4.6%
ム 57
 
3.4%
チ 52
 
3.1%
プ 50
 
3.0%
デ 48
 
2.9%
ジ 46
 
2.8%
イ 44
 
2.7%
ア 43
 
2.6%
Other values (58) 740
44.8%
Hangul
ValueCountFrequency (%)
구 299
 
9.7%
선 278
 
9.0%
번 274
 
8.9%
출 250
 
8.1%
호 238
 
7.7%
역 234
 
7.6%
분 77
 
2.5%
로 69
 
2.2%
서 58
 
1.9%
도 56
 
1.8%
Other values (184) 1239
40.3%
None
ValueCountFrequency (%)
」 194
35.4%
「 194
35.4%
、 93
17.0%
· 34
 
6.2%
， 20
 
3.6%
。 5
 
0.9%
） 3
 
0.5%
（ 3
 
0.5%
： 2
 
0.4%
Hiragana
ValueCountFrequency (%)
か 54
29.7%
ら 54
29.7%
の 10
 
5.5%
り 9
 
4.9%
に 8
 
4.4%
を 5
 
2.7%
え 4
 
2.2%
で 4
 
2.2%
し 4
 
2.2%
と 4
 
2.2%
Other values (14) 26
14.3%
Arrows
ValueCountFrequency (%)
→ 6
100.0%

Interactions

2024-05-10T23:17:36.123089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-10T23:17:53.489584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
고유번호언어
고유번호1.0000.094
언어0.0941.000
2024-05-10T23:17:53.796063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
고유번호언어
고유번호1.0000.054
언어0.0541.000

Missing values

2024-05-10T23:17:36.347308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-10T23:17:36.628229image/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.
2024-05-10T23:17:36.934582image/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

고유번호언어상호명콘텐츠URL주소신주소전화번호웹사이트운영시간교통정보
01653enSeoul Folk Flea Markethttps://english.visitseoul.net/shopping/Seoul-Folk-Flea-Market/ENP001600?utm_source=seoulopendata&utm_medium=shopping&utm_content=ENP001600130-813 109-5, Sinseol-dong, Dongdaemun-gu, Seoul02586 21, Cheonho-daero 4-gil, Dongdaemun-gu, Seoul+82-2-2232-3367http://www.pungmul.or.kr/index.htmlDaily 10:00 - 19:00 KST *Closed Tuesdays* Restaurant, Daily 10:00 - 22:00 KST *Closed Tuesdays*Subway Lines 1 & 2, Sinseoldong Station, Exit 9
12231jaテクノマ?トhttps://japanese.visitseoul.net/shopping/Techno-Mart-JP/JPP002231?utm_source=seoulopendata&utm_medium=shopping&utm_content=JPP002231143-200 ソウル市?津?九宜洞 546-4 テクノマ?ト江?店05116 ソウル市クァンジン(?津)?クァンナルロ56ギル85 (九宜洞)テクノマ?ト江?店+82-2-3424-0114http://www.tm21.com江?店／10:00~20:00(?月第2?第4火曜日定休) (KST) 新道林店／月?木曜日月~金 10:30~20:00 (KST)、土~日 11:00~20:00 (KST)地下?2?線?カンビョン??地下?行通路に連結
2270zh-CN?流周?商品<NA><NA><NA><NA><NA>
338759zh-CNAmorepacific 旗?店（?水）https://chinese.visitseoul.net/shopping/?水Amorepacific旗?店/CNP038399?utm_source=seoulopendata&utm_medium=shopping&utm_content=CNP038399首?市城???水洞2街04797 首?市城??峨嵯山路11街7 (?水洞2街, ASEA E&T Co. Ltd.)+82-2-469-8600https://www.amore-seongsu.com/main10:30 ~ 20:30 (KST)?水站2?出口步行264米
412710jaHot Tracks(TIMES SQUARE店)https://japanese.visitseoul.net/shopping/hot-tracks-time-square-jp/JPP012709?utm_source=seoulopendata&utm_medium=shopping&utm_content=JPP012709ソウル市永登浦?永登浦洞4街 442タイムズスクエア2階 ?保文庫 Hot Tracks07305 ソウル市ヨンドゥンポ(永登浦)?ヨンジュンロ15 (永登浦洞4街)タイムズスクエア2階 ?保文庫 Hot Tracks+82-507-1409-9961http://www.hottracks.co.kr10:30?22:00 KST地下?1?線「ヨンドゥンポ」?3番出口500m
543595jaMECLADS ハンナムドン(漢南洞)セレクトショップhttps://japanese.visitseoul.net/shopping/MECLADS/JPPh55o29?utm_source=seoulopendata&utm_medium=shopping&utm_content=JPPh55o2904399 ソウル市ヨンサン(龍山)?ハンナムデロ27ガギル14、1階 MECLADS+82-2-6954-2389www.meclads.com火曜日?日曜日12:00-21:00 KST地下?6?線「ハンガンジン」?2番出口
643611ko이화명주https://korean.visitseoul.net/shopping/202345/KOPgloa3i?utm_source=seoulopendata&utm_medium=shopping&utm_content=KOPgloa3i06577 서울 서초구 사평대로26길 3002-593-4411http://www.ewhamj.com/10:00~19:003?7?9호선 고속터미널역 5번 출구에서 667m
744152zh-CNSeeSaw眼?店 新村店https://chinese.visitseoul.net/shopping/SeeSawOpticalStore/CNP6ubtgx?utm_source=seoulopendata&utm_medium=shopping&utm_content=CNP6ubtgx03776 首?市 西大?? 名物街 19 J Tower 3?+82-2-6369-9709https://seesawsc.modoo.at/10:00~21:00 KST2?? 新村站 3?出口
827132zh-CN松林手工鞋https://chinese.visitseoul.net/shopping/松林手工鞋1/CNP026955?utm_source=seoulopendata&utm_medium=shopping&utm_content=CNP02695504543 中?水?路60-1，3?+82-507-1429-1910www.songlim1936.com周一~周五10:00~18:00，周六 10:00~17:00 KST距쎇2-3??乙支路3街站2?出口43米
91814jaムンジョンドン(文井洞)ロデオ通りhttps://japanese.visitseoul.net/shopping/文井洞ロデオ通り/JPP001811?utm_source=seoulopendata&utm_medium=shopping&utm_content=JPP00181105805 ソウル市松坡?文井洞41-505805 ソウル市ソンパ(松坡)?トンナムロ4ギル10 (文井洞)+82-2-400-1633<NA><NA>地下?8?線「ムンジョン」?1番出口から徒?15分
고유번호언어상호명콘텐츠URL주소신주소전화번호웹사이트운영시간교통정보
78943521zh-CN合德超市https://chinese.visitseoul.net/shopping/Hapdeok/CNPfz3wx0?utm_source=seoulopendata&utm_medium=shopping&utm_content=CNPfz3wx004400 首?市 ?山? 梨泰院路42街20<NA><NA>每天 10:00 ~ 22:00 KST6?? 梨泰院站 3?出口
79041785ko망리단길https://korean.visitseoul.net/shopping/망리단길/KOP041785?utm_source=seoulopendata&utm_medium=shopping&utm_content=KOP041785서울 마포구 망원동 403-704015 서울 마포구 포은로 일대<NA><NA><NA>6호선 망원역 2번출구
79143756ko무신사 스탠다드 홍대https://korean.visitseoul.net/shopping/MusinsaStandardHongdae/KOPjuf6ry?utm_source=seoulopendata&utm_medium=shopping&utm_content=KOPjuf6ry서울 마포구 동교동 162-504050 서울 마포구 양화로 144 (동교동, MERCURE 앰배서더 HOTEL 홍대)1644-2107http://store.musinsa.com/musinsastandard매일 11:00~21:002호선 홍대입구역 9번 출구
79243753jaMUSINSA STANDARDカンナム(江南)https://japanese.visitseoul.net/shopping/MusinsaStandardGangnam/JPPp5guss?utm_source=seoulopendata&utm_medium=shopping&utm_content=JPPp5guss06611 ソウル市ソチョ(瑞草)?ソチョデロ77ギル54、B2-1F+82-504-570-3469http://store.musinsa.com/musinsastandard?日11:00-21:00 KST地下?9?線/シン·ブンダン線「シンノンヒョン」?7番出口
79344139ko엠프티https://korean.visitseoul.net/shopping/EMPTY/KOPoigt91?utm_source=seoulopendata&utm_medium=shopping&utm_content=KOPoigt91서울 성동구 성수동2가 315-10804782 서울 성동구 성수이로 97 (성수동2가) 1~4층02-1833-9118https://empty.seoul.kr/일~목 11:00~20:00, 금~토 11:00~21:002호선 성수역 3번 출구
79442256enFigure and Groundhttps://english.visitseoul.net/shopping/Figure-and-Ground/ENP042255?utm_source=seoulopendata&utm_medium=shopping&utm_content=ENP04225506036 53, Nonhyeon-ro 153-gil, Gangnam-gu, Seoul<NA><NA>Ground level caf?, Conflict Store : Daily 11:00 ~ 22:00<NA>
79543495ko세븐웰https://korean.visitseoul.net/shopping/2023110/KOPqlzpr0?utm_source=seoulopendata&utm_medium=shopping&utm_content=KOPqlzpr004509 서울 중구 칠패로 602-711-9336sevenwell.modoo.at월~금 09:00~18:00, 토 09:00~17:002?5호선 충정로역 4번 출구에서 430m
79643516jaテソン表具社https://japanese.visitseoul.net/shopping/Daesung/JPP3iuk2x?utm_source=seoulopendata&utm_medium=shopping&utm_content=JPP3iuk2x04404 龍山? イテウォンロ 216 1階+82-2-794-3681<NA>月?土 10:30?18:00 KST6?線梨泰院?3番出口から334m
79743511enItaewon Bookshttps://english.visitseoul.net/shopping/ItaewonBooks/ENPkv7z3y?utm_source=seoulopendata&utm_medium=shopping&utm_content=ENPkv7z3y04345 1F, 208 Noksapyeong-daero, Yongsan-gu, Seoul+82-2-793-8249www.instagram.com/itaewon_books11:00 - 19:30 / Saturday 10:00 - 20:00 (KST)258 meters from Exit 3 of Noksapyeong Station on Line 6
79843272ko엔터식스 패션스트릿 강남점https://korean.visitseoul.net/shopping/Enter-6-Fashion-street/KOPpic8xu?utm_source=seoulopendata&utm_medium=shopping&utm_content=KOPpic8xu06546 서울 서초구 반포동 19-3 고속터미널역 B106546 서울 서초구 신반포로 176 (반포동, 센트럴시티) 고속터미널역 B102-6321-6000https://store.enter6.co.kr10:30 ~ 22:003,7,9호선, 고속터미널역