Overview

Dataset statistics

Number of variables10
Number of observations809
Missing cells532
Missing cells (%)6.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory64.1 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 (6.4%) missing valuesMissing
전화번호 has 76 (9.4%) missing valuesMissing
웹사이트 has 258 (31.9%) missing valuesMissing
운영시간 has 114 (14.1%) missing valuesMissing
교통정보 has 32 (4.0%) missing valuesMissing
고유번호 has unique valuesUnique

Reproduction

Analysis started2024-05-18 09:51:42.528822
Analysis finished2024-05-18 09:51:48.127774
Duration5.6 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

고유번호
Real number (ℝ)

UNIQUE 

Distinct809
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22546.265
Minimum13
Maximum45760
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2024-05-18T18:51:48.292245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum13
5-th percentile284.8
Q19630
median20268
Q341818
95-th percentile44408.2
Maximum45760
Range45747
Interquartile range (IQR)32188

Descriptive statistics

Standard deviation16246.212
Coefficient of variation (CV)0.72057222
Kurtosis-1.4922088
Mean22546.265
Median Absolute Deviation (MAD)17667
Skewness0.043394977
Sum18239928
Variance2.639394 × 108
MonotonicityNot monotonic
2024-05-18T18:51:48.586245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
45758 1
 
0.1%
1356 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%
37402 1
 
0.1%
Other values (799) 799
98.8%
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 (%)
45760 1
0.1%
45759 1
0.1%
45758 1
0.1%
45757 1
0.1%
45756 1
0.1%
45752 1
0.1%
45751 1
0.1%
45750 1
0.1%
45717 1
0.1%
45715 1
0.1%

언어
Categorical

Distinct5
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
ko
222 
ja
193 
en
184 
zh-CN
180 
zh-TW
30 

Length

Max length5
Median length2
Mean length2.7787392
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
ko 222
27.4%
ja 193
23.9%
en 184
22.7%
zh-CN 180
22.2%
zh-TW 30
 
3.7%

Length

2024-05-18T18:51:48.968073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T18:51:49.305822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
ko 222
27.4%
ja 193
23.9%
en 184
22.7%
zh-cn 180
22.2%
zh-tw 30
 
3.7%

상호명
Text

Distinct762
Distinct (%)94.2%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
2024-05-18T18:51:49.840848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length126
Median length38
Mean length12.944376
Min length2

Characters and Unicode

Total characters10472
Distinct characters727
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

Unique726 ?
Unique (%)89.7%

Sample

1st rowThe Book Society
2nd row?流周?商品
3rd rowLoft Books
4th row孔陵洞 夜間市場
5th rowSeoul Folk Flea Market
ValueCountFrequency (%)
market 37
 
2.5%
mall 18
 
1.2%
the 18
 
1.2%
store 16
 
1.1%
musinsa 12
 
0.8%
shopping 11
 
0.7%
house 11
 
0.7%
flagship 11
 
0.7%
branch 11
 
0.7%
seoul 11
 
0.7%
Other values (941) 1352
89.7%
2024-05-18T18:51:50.738493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
727
 
6.9%
e 452
 
4.3%
a 375
 
3.6%
o 361
 
3.4%
n 337
 
3.2%
? 297
 
2.8%
r 263
 
2.5%
t 255
 
2.4%
i 201
 
1.9%
S 197
 
1.9%
Other values (717) 7007
66.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3637
34.7%
Lowercase Letter 3594
34.3%
Uppercase Letter 1798
17.2%
Space Separator 727
 
6.9%
Other Punctuation 343
 
3.3%
Open Punctuation 147
 
1.4%
Close 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
 
4.9%
店 107
 
2.9%
市 53
 
1.5%
스 51
 
1.4%
ッ 48
 
1.3%
ョ 42
 
1.2%
ト 42
 
1.2%
점 41
 
1.1%
洞 41
 
1.1%
ム 38
 
1.0%
Other values (637) 2994
82.3%
Lowercase Letter
ValueCountFrequency (%)
e 452
12.6%
a 375
10.4%
o 361
10.0%
n 337
 
9.4%
r 263
 
7.3%
t 255
 
7.1%
i 201
 
5.6%
l 188
 
5.2%
g 174
 
4.8%
u 140
 
3.9%
Other values (16) 848
23.6%
Uppercase Letter
ValueCountFrequency (%)
S 197
 
11.0%
M 150
 
8.3%
A 142
 
7.9%
E 137
 
7.6%
T 136
 
7.6%
O 126
 
7.0%
C 100
 
5.6%
R 87
 
4.8%
N 85
 
4.7%
D 69
 
3.8%
Other values (16) 569
31.6%
Other Punctuation
ValueCountFrequency (%)
? 297
86.6%
. 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%
Open Punctuation
ValueCountFrequency (%)
( 139
94.6%
（ 8
 
5.4%
Close Punctuation
ValueCountFrequency (%)
) 139
94.6%
） 8
 
5.4%
Final Punctuation
ValueCountFrequency (%)
” 2
50.0%
’ 2
50.0%
Initial Punctuation
ValueCountFrequency (%)
“ 2
66.7%
‘ 1
33.3%
Math Symbol
ValueCountFrequency (%)
< 2
50.0%
> 2
50.0%
Space Separator
ValueCountFrequency (%)
727
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5392
51.5%
Common 1443
 
13.8%
Hangul 1429
 
13.6%
Han 1127
 
10.8%
Katakana 1042
 
10.0%
Hiragana 39
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 51
 
3.6%
점 41
 
2.9%
리 37
 
2.6%
시 37
 
2.6%
장 32
 
2.2%
이 28
 
2.0%
동 25
 
1.7%
대 19
 
1.3%
아 18
 
1.3%
어 17
 
1.2%
Other values (303) 1124
78.7%
Han
ValueCountFrequency (%)
店 107
 
9.5%
市 53
 
4.7%
洞 41
 
3.6%
大 36
 
3.2%
街 27
 
2.4%
場 26
 
2.3%
明 23
 
2.0%
新 21
 
1.9%
南 21
 
1.9%
通 18
 
1.6%
Other values (235) 754
66.9%
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 452
 
8.4%
a 375
 
7.0%
o 361
 
6.7%
n 337
 
6.2%
r 263
 
4.9%
t 255
 
4.7%
i 201
 
3.7%
S 197
 
3.7%
l 188
 
3.5%
g 174
 
3.2%
Other values (42) 2589
48.0%
Common
ValueCountFrequency (%)
727
50.4%
? 297
20.6%
( 139
 
9.6%
) 139
 
9.6%
- 24
 
1.7%
0 11
 
0.8%
. 10
 
0.7%
· 10
 
0.7%
（ 8
 
0.6%
） 8
 
0.6%
Other values (18) 70
 
4.9%
Hiragana
ValueCountFrequency (%)
り 15
38.5%
お 3
 
7.7%
し 3
 
7.7%
の 3
 
7.7%
け 2
 
5.1%
い 2
 
5.1%
き 2
 
5.1%
ね 1
 
2.6%
ぎ 1
 
2.6%
か 1
 
2.6%
Other values (6) 6
 
15.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6802
65.0%
Hangul 1429
 
13.6%
CJK 1127
 
10.8%
Katakana 1042
 
10.0%
Hiragana 39
 
0.4%
None 26
 
0.2%
Punctuation 7
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
727
 
10.7%
e 452
 
6.6%
a 375
 
5.5%
o 361
 
5.3%
n 337
 
5.0%
? 297
 
4.4%
r 263
 
3.9%
t 255
 
3.7%
i 201
 
3.0%
S 197
 
2.9%
Other values (63) 3337
49.1%
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
 
9.5%
市 53
 
4.7%
洞 41
 
3.6%
大 36
 
3.2%
街 27
 
2.4%
場 26
 
2.3%
明 23
 
2.0%
新 21
 
1.9%
南 21
 
1.9%
通 18
 
1.6%
Other values (235) 754
66.9%
Hangul
ValueCountFrequency (%)
스 51
 
3.6%
점 41
 
2.9%
리 37
 
2.6%
시 37
 
2.6%
장 32
 
2.2%
이 28
 
2.0%
동 25
 
1.7%
대 19
 
1.3%
아 18
 
1.3%
어 17
 
1.2%
Other values (303) 1124
78.7%
Hiragana
ValueCountFrequency (%)
り 15
38.5%
お 3
 
7.7%
し 3
 
7.7%
の 3
 
7.7%
け 2
 
5.1%
い 2
 
5.1%
き 2
 
5.1%
ね 1
 
2.6%
ぎ 1
 
2.6%
か 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 

Distinct757
Distinct (%)100.0%
Missing52
Missing (%)6.4%
Memory size6.4 KiB
2024-05-18T18:51:51.607948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length182
Median length156
Mean length130.71995
Min length119

Characters and Unicode

Total characters98955
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

Unique757 ?
Unique (%)100.0%

Sample

1st rowhttps://english.visitseoul.net/shopping/2024-thebooksociety/ENPbxv0dg?utm_source=seoulopendata&utm_medium=shopping&utm_content=ENPbxv0dg
2nd rowhttps://japanese.visitseoul.net/shopping/2024-LoftBooks/JPPted0es?utm_source=seoulopendata&utm_medium=shopping&utm_content=JPPted0es
3rd rowhttps://chinese.visitseoul.net/shopping/2024-gongneungmarket/CNP7xadww?utm_source=seoulopendata&utm_medium=shopping&utm_content=CNP7xadww
4th rowhttps://english.visitseoul.net/shopping/Seoul-Folk-Flea-Market/ENP001600?utm_source=seoulopendata&utm_medium=shopping&utm_content=ENP001600
5th rowhttps://japanese.visitseoul.net/shopping/Techno-Mart-JP/JPP002231?utm_source=seoulopendata&utm_medium=shopping&utm_content=JPP002231
ValueCountFrequency (%)
https://korean.visitseoul.net/shopping/롯데월드타워-롯데월드몰/kop015859?utm_source=seoulopendata&utm_medium=shopping&utm_content=kop015859 1
 
0.1%
https://chinese.visitseoul.net/shopping/望理?街/cnp041785?utm_source=seoulopendata&utm_medium=shopping&utm_content=cnp041785 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://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%
https://chinese.visitseoul.net/shopping/?潭名品街/cnp001307?utm_source=seoulopendata&utm_medium=shopping&utm_content=cnp001307 1
 
0.1%
https://english.visitseoul.net/shopping/namdaemun-market/enp000085?utm_source=seoulopendata&utm_medium=shopping&utm_content=enp000085 1
 
0.1%
https://korean.visitseoul.net/shopping/메세나폴리스-kr/kop011104?utm_source=seoulopendata&utm_medium=shopping&utm_content=kop011104 1
 
0.1%
https://english.visitseoul.net/shopping/covernat/enp77xns8?utm_source=seoulopendata&utm_medium=shopping&utm_content=enp77xns8 1
 
0.1%
https://korean.visitseoul.net/shopping/회기역파전골목/kop041965?utm_source=seoulopendata&utm_medium=shopping&utm_content=kop041965 1
 
0.1%
https://korean.visitseoul.net/shopping/recode-샵/kop011227?utm_source=seoulopendata&utm_medium=shopping&utm_content=kop011227 1
 
0.1%
Other values (747) 747
98.7%
2024-05-18T18:51:53.154818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 8024
 
8.1%
e 7091
 
7.2%
s 6146
 
6.2%
o 6034
 
6.1%
n 5820
 
5.9%
u 5518
 
5.6%
p 4944
 
5.0%
i 4452
 
4.5%
m 3966
 
4.0%
/ 3785
 
3.8%
Other values (588) 43175
43.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 68511
69.2%
Other Punctuation 8551
 
8.6%
Decimal Number 8125
 
8.2%
Uppercase Letter 6205
 
6.3%
Connector Punctuation 2271
 
2.3%
Math Symbol 2271
 
2.3%
Other Letter 2252
 
2.3%
Dash Punctuation 749
 
0.8%
Open Punctuation 9
 
< 0.1%
Close 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 8024
11.7%
e 7091
10.4%
s 6146
9.0%
o 6034
8.8%
n 5820
8.5%
u 5518
8.1%
p 4944
 
7.2%
i 4452
 
6.5%
m 3966
 
5.8%
h 2824
 
4.1%
Other values (16) 13692
20.0%
Uppercase Letter
ValueCountFrequency (%)
P 1929
31.1%
N 766
 
12.3%
O 531
 
8.6%
C 502
 
8.1%
E 471
 
7.6%
K 459
 
7.4%
J 392
 
6.3%
S 186
 
3.0%
T 167
 
2.7%
M 131
 
2.1%
Other values (16) 671
 
10.8%
Decimal Number
ValueCountFrequency (%)
0 2591
31.9%
1 862
 
10.6%
2 835
 
10.3%
4 665
 
8.2%
5 607
 
7.5%
9 587
 
7.2%
7 570
 
7.0%
8 486
 
6.0%
3 464
 
5.7%
6 458
 
5.6%
Other Punctuation
ValueCountFrequency (%)
/ 3785
44.3%
. 1514
 
17.7%
& 1514
 
17.7%
? 975
 
11.4%
: 757
 
8.9%
· 6
 
0.1%
Connector Punctuation
ValueCountFrequency (%)
_ 2271
100.0%
Math Symbol
ValueCountFrequency (%)
= 2271
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 749
100.0%
Open Punctuation
ValueCountFrequency (%)
（ 9
100.0%
Close Punctuation
ValueCountFrequency (%)
） 9
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%
Format
ValueCountFrequency (%)
­ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 74716
75.5%
Common 21987
 
22.2%
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%
화 20
 
1.9%
이 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%
里 13
 
1.7%
明 13
 
1.7%
商 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 8024
10.7%
e 7091
 
9.5%
s 6146
 
8.2%
o 6034
 
8.1%
n 5820
 
7.8%
u 5518
 
7.4%
p 4944
 
6.6%
i 4452
 
6.0%
m 3966
 
5.3%
h 2824
 
3.8%
Other values (42) 19897
26.6%
Common
ValueCountFrequency (%)
/ 3785
17.2%
0 2591
11.8%
_ 2271
10.3%
= 2271
10.3%
. 1514
 
6.9%
& 1514
 
6.9%
? 975
 
4.4%
1 862
 
3.9%
2 835
 
3.8%
: 757
 
3.4%
Other values (13) 4612
21.0%
Hiragana
ValueCountFrequency (%)
り 10
43.5%
け 2
 
8.7%
お 2
 
8.7%
の 2
 
8.7%
め 1
 
4.3%
ん 1
 
4.3%
し 1
 
4.3%
き 1
 
4.3%
ね 1
 
4.3%
ぎ 1
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 96677
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 8024
 
8.3%
e 7091
 
7.3%
s 6146
 
6.4%
o 6034
 
6.2%
n 5820
 
6.0%
u 5518
 
5.7%
p 4944
 
5.1%
i 4452
 
4.6%
m 3966
 
4.1%
/ 3785
 
3.9%
Other values (60) 40897
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%
里 13
 
1.7%
明 13
 
1.7%
商 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%
화 20
 
1.9%
이 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%
め 1
 
4.3%
ん 1
 
4.3%
し 1
 
4.3%
き 1
 
4.3%
ね 1
 
4.3%
ぎ 1
 
4.3%
None
ValueCountFrequency (%)
（ 9
36.0%
） 9
36.0%
· 6
24.0%
­ 1
 
4.0%
Punctuation
ValueCountFrequency (%)
’ 1
100.0%

주소
Text

Distinct565
Distinct (%)69.8%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
2024-05-18T18:51:53.835916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length85
Median length62
Mean length20.548826
Min length2

Characters and Unicode

Total characters16624
Distinct characters467
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 (%)67.4%

Sample

1st row 서울 종로구 옥인동 19-45
2nd row
3rd row 서울 종로구 부암동 251-4
4th row 서울 노원구 공릉동 561-35
5th row130-813 109-5, Sinseol-dong, Dongdaemun-gu, Seoul
ValueCountFrequency (%)
서울 207
 
9.1%
seoul 112
 
4.9%
중구 38
 
1.7%
강남구 36
 
1.6%
종로구 30
 
1.3%
korea 28
 
1.2%
jung-gu 23
 
1.0%
마포구 21
 
0.9%
jongno-gu 21
 
0.9%
gangnam-gu 20
 
0.9%
Other values (888) 1727
76.3%
2024-05-18T18:51:54.962032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2771
 
16.7%
1 1033
 
6.2%
- 964
 
5.8%
0 631
 
3.8%
? 504
 
3.0%
3 470
 
2.8%
2 468
 
2.8%
5 463
 
2.8%
o 445
 
2.7%
g 444
 
2.7%
Other values (457) 8431
50.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4407
26.5%
Other Letter 4274
25.7%
Lowercase Letter 2800
16.8%
Space Separator 2771
16.7%
Dash Punctuation 964
 
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 246
 
5.8%
구 228
 
5.3%
동 224
 
5.2%
울 216
 
5.1%
市 206
 
4.8%
洞 197
 
4.6%
ル 139
 
3.3%
ソ 134
 
3.1%
ウ 130
 
3.0%
首 127
 
3.0%
Other values (388) 2427
56.8%
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 1033
23.4%
0 631
14.3%
3 470
10.7%
2 468
10.6%
5 463
10.5%
4 331
 
7.5%
8 284
 
6.4%
9 263
 
6.0%
6 235
 
5.3%
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 (%)
2771
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 964
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 9109
54.8%
Latin 3241
 
19.5%
Hangul 1999
 
12.0%
Han 1720
 
10.3%
Katakana 552
 
3.3%
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 246
 
12.3%
구 228
 
11.4%
동 224
 
11.2%
울 216
 
10.8%
로 59
 
3.0%
가 54
 
2.7%
남 53
 
2.7%
강 40
 
2.0%
중 38
 
1.9%
종 38
 
1.9%
Other values (158) 803
40.2%
Katakana
ValueCountFrequency (%)
ル 139
25.2%
ソ 134
24.3%
ウ 130
23.6%
ン 31
 
5.6%
デ 7
 
1.3%
ム 7
 
1.3%
ク 6
 
1.1%
ギ 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 (%)
2771
30.4%
1 1033
 
11.3%
- 964
 
10.6%
0 631
 
6.9%
? 504
 
5.5%
3 470
 
5.2%
2 468
 
5.1%
5 463
 
5.1%
, 348
 
3.8%
4 331
 
3.6%
Other values (14) 1126
12.4%
Hiragana
ValueCountFrequency (%)
り 1
33.3%
び 1
33.3%
く 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12347
74.3%
Hangul 1997
 
12.0%
CJK 1718
 
10.3%
Katakana 552
 
3.3%
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 (%)
2771
22.4%
1 1033
 
8.4%
- 964
 
7.8%
0 631
 
5.1%
? 504
 
4.1%
3 470
 
3.8%
2 468
 
3.8%
5 463
 
3.7%
o 445
 
3.6%
g 444
 
3.6%
Other values (57) 4154
33.6%
Hangul
ValueCountFrequency (%)
서 246
 
12.3%
구 228
 
11.4%
동 224
 
11.2%
울 216
 
10.8%
로 59
 
3.0%
가 54
 
2.7%
남 53
 
2.7%
강 40
 
2.0%
중 38
 
1.9%
종 38
 
1.9%
Other values (157) 801
40.1%
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%
デ 7
 
1.3%
ム 7
 
1.3%
ク 6
 
1.1%
ギ 6
 
1.1%
ト 6
 
1.1%
ド 5
 
0.9%
Other values (44) 81
14.7%
Compat Jamo
ValueCountFrequency (%)
ㆍ 2
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
樓 2
100.0%
None
ValueCountFrequency (%)
， 2
66.7%
· 1
33.3%
Hiragana
ValueCountFrequency (%)
り 1
33.3%
び 1
33.3%
く 1
33.3%

신주소
Text

Distinct790
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
2024-05-18T18:51:55.564454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length100
Median length60
Mean length34.484549
Min length2

Characters and Unicode

Total characters27898
Distinct characters732
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

Unique785 ?
Unique (%)97.0%

Sample

1st row03035 B1, 25 Jahamun-ro 19-gil, Jongno-gu, Seoul
2nd row
3rd row03022 ソウル市チョンノ(鍾路)?チャンイムンロ129、2階
4th row01846 首爾市蘆?區東日路180街 53
5th row02586 21, Cheonho-daero 4-gil, Dongdaemun-gu, Seoul
ValueCountFrequency (%)
서울 186
 
4.9%
seoul 179
 
4.7%
중구 43
 
1.1%
jung-gu 38
 
1.0%
강남구 37
 
1.0%
gangnam-gu 32
 
0.8%
首?市 31
 
0.8%
종로구 31
 
0.8%
서울특별시 26
 
0.7%
04536 24
 
0.6%
Other values (1560) 3144
83.4%
2024-05-18T18:51:56.702951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3695
 
13.2%
0 1347
 
4.8%
1 951
 
3.4%
? 942
 
3.4%
4 797
 
2.9%
3 786
 
2.8%
o 689
 
2.5%
2 638
 
2.3%
g 634
 
2.3%
, 632
 
2.3%
Other values (722) 16787
60.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8917
32.0%
Decimal Number 6656
23.9%
Lowercase Letter 4394
15.8%
Space Separator 3695
13.2%
Other Punctuation 1622
 
5.8%
Uppercase Letter 878
 
3.1%
Open Punctuation 580
 
2.1%
Close Punctuation 579
 
2.1%
Dash Punctuation 567
 
2.0%
Math Symbol 10
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
ン 434
 
4.9%
市 348
 
3.9%
ル 310
 
3.5%
서 258
 
2.9%
路 258
 
2.9%
로 243
 
2.7%
구 239
 
2.7%
울 228
 
2.6%
ソ 227
 
2.5%
ウ 219
 
2.5%
Other values (648) 6153
69.0%
Uppercase Letter
ValueCountFrequency (%)
S 252
28.7%
J 86
 
9.8%
G 58
 
6.6%
M 57
 
6.5%
E 43
 
4.9%
F 40
 
4.6%
C 36
 
4.1%
Y 34
 
3.9%
T 33
 
3.8%
A 32
 
3.6%
Other values (15) 207
23.6%
Lowercase Letter
ValueCountFrequency (%)
o 689
15.7%
g 634
14.4%
n 536
12.2%
u 511
11.6%
e 416
9.5%
a 344
7.8%
l 312
7.1%
r 190
 
4.3%
i 150
 
3.4%
d 127
 
2.9%
Other values (13) 485
11.0%
Decimal Number
ValueCountFrequency (%)
0 1347
20.2%
1 951
14.3%
4 797
12.0%
3 786
11.8%
2 638
9.6%
5 606
9.1%
6 571
8.6%
7 379
 
5.7%
8 324
 
4.9%
9 257
 
3.9%
Other Punctuation
ValueCountFrequency (%)
? 942
58.1%
, 632
39.0%
、 21
 
1.3%
， 9
 
0.6%
/ 8
 
0.5%
& 3
 
0.2%
· 3
 
0.2%
: 2
 
0.1%
. 2
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 567
97.8%
（ 13
 
2.2%
Close Punctuation
ValueCountFrequency (%)
) 567
97.9%
） 12
 
2.1%
Space Separator
ValueCountFrequency (%)
3695
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 567
100.0%
Math Symbol
ValueCountFrequency (%)
~ 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13709
49.1%
Latin 5272
 
18.9%
Hangul 3432
 
12.3%
Han 2845
 
10.2%
Katakana 2631
 
9.4%
Hiragana 9
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 258
 
7.5%
로 243
 
7.1%
구 239
 
7.0%
울 228
 
6.6%
동 217
 
6.3%
길 106
 
3.1%
남 75
 
2.2%
대 74
 
2.2%
가 62
 
1.8%
강 53
 
1.5%
Other values (295) 1877
54.7%
Han
ValueCountFrequency (%)
市 348
 
12.2%
路 258
 
9.1%
首 205
 
7.2%
洞 180
 
6.3%
街 133
 
4.7%
南 100
 
3.5%
中 90
 
3.2%
江 88
 
3.1%
大 77
 
2.7%
浦 58
 
2.0%
Other values (264) 1308
46.0%
Katakana
ValueCountFrequency (%)
ン 434
16.5%
ル 310
 
11.8%
ソ 227
 
8.6%
ウ 219
 
8.3%
ロ 148
 
5.6%
チ 107
 
4.1%
ョ 98
 
3.7%
ギ 91
 
3.5%
ム 77
 
2.9%
ク 51
 
1.9%
Other values (61) 869
33.0%
Latin
ValueCountFrequency (%)
o 689
13.1%
g 634
12.0%
n 536
10.2%
u 511
9.7%
e 416
 
7.9%
a 344
 
6.5%
l 312
 
5.9%
S 252
 
4.8%
r 190
 
3.6%
i 150
 
2.8%
Other values (38) 1238
23.5%
Common
ValueCountFrequency (%)
3695
27.0%
0 1347
 
9.8%
1 951
 
6.9%
? 942
 
6.9%
4 797
 
5.8%
3 786
 
5.7%
2 638
 
4.7%
, 632
 
4.6%
5 606
 
4.4%
6 571
 
4.2%
Other values (16) 2744
20.0%
Hiragana
ValueCountFrequency (%)
の 2
22.2%
ぺ 1
11.1%
り 1
11.1%
か 1
11.1%
ら 1
11.1%
せ 1
11.1%
び 1
11.1%
く 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18923
67.8%
Hangul 3430
 
12.3%
CJK 2842
 
10.2%
Katakana 2631
 
9.4%
None 58
 
0.2%
Hiragana 9
 
< 0.1%
CJK Compat Ideographs 3
 
< 0.1%
Compat Jamo 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3695
19.5%
0 1347
 
7.1%
1 951
 
5.0%
? 942
 
5.0%
4 797
 
4.2%
3 786
 
4.2%
o 689
 
3.6%
2 638
 
3.4%
g 634
 
3.4%
, 632
 
3.3%
Other values (59) 7812
41.3%
Katakana
ValueCountFrequency (%)
ン 434
16.5%
ル 310
 
11.8%
ソ 227
 
8.6%
ウ 219
 
8.3%
ロ 148
 
5.6%
チ 107
 
4.1%
ョ 98
 
3.7%
ギ 91
 
3.5%
ム 77
 
2.9%
ク 51
 
1.9%
Other values (61) 869
33.0%
CJK
ValueCountFrequency (%)
市 348
 
12.2%
路 258
 
9.1%
首 205
 
7.2%
洞 180
 
6.3%
街 133
 
4.7%
南 100
 
3.5%
中 90
 
3.2%
江 88
 
3.1%
大 77
 
2.7%
浦 58
 
2.0%
Other values (262) 1305
45.9%
Hangul
ValueCountFrequency (%)
서 258
 
7.5%
로 243
 
7.1%
구 239
 
7.0%
울 228
 
6.6%
동 217
 
6.3%
길 106
 
3.1%
남 75
 
2.2%
대 74
 
2.2%
가 62
 
1.8%
강 53
 
1.5%
Other values (294) 1875
54.7%
None
ValueCountFrequency (%)
、 21
36.2%
（ 13
22.4%
） 12
20.7%
， 9
15.5%
· 3
 
5.2%
Compat Jamo
ValueCountFrequency (%)
ㆍ 2
100.0%
Hiragana
ValueCountFrequency (%)
の 2
22.2%
ぺ 1
11.1%
り 1
11.1%
か 1
11.1%
ら 1
11.1%
せ 1
11.1%
び 1
11.1%
く 1
11.1%
CJK Compat Ideographs
ValueCountFrequency (%)
樓 2
66.7%
龍 1
33.3%

전화번호
Text

MISSING 

Distinct371
Distinct (%)50.6%
Missing76
Missing (%)9.4%
Memory size6.4 KiB
2024-05-18T18:51:57.202706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length46
Mean length13.86221
Min length6

Characters and Unicode

Total characters10161
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

Unique213 ?
Unique (%)29.1%

Sample

1st row+82-70-8621-5676
2nd row+82-507-1310-3225
3rd row+82-2-976-4143
4th row+82-2-2232-3367
5th row+82-2-3424-0114
ValueCountFrequency (%)
82-2-120 36
 
4.8%
02-120 13
 
1.7%
82-2-3449-4114 8
 
1.1%
5
 
0.7%
82-2-2124-1538 4
 
0.5%
82-2-2627-1307 4
 
0.5%
82-2-6438-1234 4
 
0.5%
82-70-4006-4573 4
 
0.5%
82-2-3213-5000 4
 
0.5%
82-2-6002-5300 4
 
0.5%
Other values (375) 668
88.6%
2024-05-18T18:51:58.060360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1927
19.0%
2 1755
17.3%
0 1041
10.2%
8 916
9.0%
1 757
 
7.5%
3 691
 
6.8%
4 536
 
5.3%
5 536
 
5.3%
+ 528
 
5.2%
7 526
 
5.2%
Other values (53) 948
9.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7570
74.5%
Dash Punctuation 1927
 
19.0%
Math Symbol 528
 
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 (%)
호 4
 
10.0%
번 4
 
10.0%
전 3
 
7.5%
의 2
 
5.0%
문 2
 
5.0%
咨 2
 
5.0%
화 2
 
5.0%
팩 2
 
5.0%
스 2
 
5.0%
청 1
 
2.5%
Other values (16) 16
40.0%
Lowercase Letter
ValueCountFrequency (%)
e 5
16.7%
r 4
13.3%
n 4
13.3%
u 3
10.0%
h 2
 
6.7%
i 2
 
6.7%
m 2
 
6.7%
b 2
 
6.7%
a 1
 
3.3%
o 1
 
3.3%
Other values (4) 4
13.3%
Decimal Number
ValueCountFrequency (%)
2 1755
23.2%
0 1041
13.8%
8 916
12.1%
1 757
10.0%
3 691
 
9.1%
4 536
 
7.1%
5 536
 
7.1%
7 526
 
6.9%
6 422
 
5.6%
9 390
 
5.2%
Uppercase Letter
ValueCountFrequency (%)
F 1
25.0%
P 1
25.0%
I 1
25.0%
O 1
25.0%
Other Punctuation
ValueCountFrequency (%)
? 14
58.3%
/ 10
41.7%
Dash Punctuation
ValueCountFrequency (%)
- 1927
100.0%
Math Symbol
ValueCountFrequency (%)
+ 528
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 10087
99.3%
Hangul 37
 
0.4%
Latin 34
 
0.3%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
호 4
 
10.8%
번 4
 
10.8%
전 3
 
8.1%
의 2
 
5.4%
문 2
 
5.4%
화 2
 
5.4%
팩 2
 
5.4%
스 2
 
5.4%
청 1
 
2.7%
입 1
 
2.7%
Other values (14) 14
37.8%
Common
ValueCountFrequency (%)
- 1927
19.1%
2 1755
17.4%
0 1041
10.3%
8 916
9.1%
1 757
 
7.5%
3 691
 
6.9%
4 536
 
5.3%
5 536
 
5.3%
+ 528
 
5.2%
7 526
 
5.2%
Other values (9) 874
8.7%
Latin
ValueCountFrequency (%)
e 5
14.7%
r 4
11.8%
n 4
11.8%
u 3
 
8.8%
h 2
 
5.9%
i 2
 
5.9%
m 2
 
5.9%
b 2
 
5.9%
F 1
 
2.9%
a 1
 
2.9%
Other values (8) 8
23.5%
Han
ValueCountFrequency (%)
咨 2
66.7%
展 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10120
99.6%
Hangul 37
 
0.4%
CJK 3
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1927
19.0%
2 1755
17.3%
0 1041
10.3%
8 916
9.1%
1 757
 
7.5%
3 691
 
6.8%
4 536
 
5.3%
5 536
 
5.3%
+ 528
 
5.2%
7 526
 
5.2%
Other values (26) 907
9.0%
Hangul
ValueCountFrequency (%)
호 4
 
10.8%
번 4
 
10.8%
전 3
 
8.1%
의 2
 
5.4%
문 2
 
5.4%
화 2
 
5.4%
팩 2
 
5.4%
스 2
 
5.4%
청 1
 
2.7%
입 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 

Distinct223
Distinct (%)40.5%
Missing258
Missing (%)31.9%
Memory size6.4 KiB
2024-05-18T18:51:58.620740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length216
Median length60
Mean length33.526316
Min length10

Characters and Unicode

Total characters18473
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 (%)18.0%

Sample

1st rowhttps://www.thebooksociety.org/blog
2nd rowhttps://www.instagram.com/loftbooks_seoul/
3rd rowhttps://www.gogoma.kr/
4th rowhttp://www.pungmul.or.kr/index.html
5th rowhttp://www.tm21.com
ValueCountFrequency (%)
http://www.hottracks.co.kr 8
 
1.5%
http://store.musinsa.com/musinsastandard 8
 
1.5%
https://www.instagram.com/musinsaterrace 8
 
1.5%
https://www.kakaofriends.com/kr/index 8
 
1.5%
http://store.emart.com 5
 
0.9%
http://www.mariooutlet.co.kr 5
 
0.9%
http://www.tm21.com 5
 
0.9%
https://www.hdc-iparkmall.com/main/index.do 5
 
0.9%
https://www.thehyundaiseoul.com 5
 
0.9%
http://company.lottemart.com 5
 
0.9%
Other values (208) 489
88.7%
2024-05-18T18:51:59.511221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 1721
 
9.3%
/ 1699
 
9.2%
. 1273
 
6.9%
w 1212
 
6.6%
o 1202
 
6.5%
a 946
 
5.1%
s 854
 
4.6%
e 842
 
4.6%
m 804
 
4.4%
r 755
 
4.1%
Other values (58) 7165
38.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 13970
75.6%
Other Punctuation 3598
 
19.5%
Decimal Number 479
 
2.6%
Uppercase Letter 225
 
1.2%
Math Symbol 81
 
0.4%
Connector Punctuation 58
 
0.3%
Dash Punctuation 51
 
0.3%
Space Separator 11
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 1721
12.3%
w 1212
 
8.7%
o 1202
 
8.6%
a 946
 
6.8%
s 854
 
6.1%
e 842
 
6.0%
m 804
 
5.8%
r 755
 
5.4%
h 733
 
5.2%
n 716
 
5.1%
Other values (16) 4185
30.0%
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
44.9%
2 76
 
15.9%
1 52
 
10.9%
6 36
 
7.5%
3 28
 
5.8%
4 17
 
3.5%
9 16
 
3.3%
8 14
 
2.9%
7 13
 
2.7%
5 12
 
2.5%
Other Punctuation
ValueCountFrequency (%)
/ 1699
47.2%
. 1273
35.4%
: 524
 
14.6%
? 52
 
1.4%
% 32
 
0.9%
& 17
 
0.5%
# 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
= 81
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 58
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 51
100.0%
Space Separator
ValueCountFrequency (%)
11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 14195
76.8%
Common 4278
 
23.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 1721
 
12.1%
w 1212
 
8.5%
o 1202
 
8.5%
a 946
 
6.7%
s 854
 
6.0%
e 842
 
5.9%
m 804
 
5.7%
r 755
 
5.3%
h 733
 
5.2%
n 716
 
5.0%
Other values (37) 4410
31.1%
Common
ValueCountFrequency (%)
/ 1699
39.7%
. 1273
29.8%
: 524
 
12.2%
0 215
 
5.0%
= 81
 
1.9%
2 76
 
1.8%
_ 58
 
1.4%
? 52
 
1.2%
1 52
 
1.2%
- 51
 
1.2%
Other values (11) 197
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18473
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 1721
 
9.3%
/ 1699
 
9.2%
. 1273
 
6.9%
w 1212
 
6.6%
o 1202
 
6.5%
a 946
 
5.1%
s 854
 
4.6%
e 842
 
4.6%
m 804
 
4.4%
r 755
 
4.1%
Other values (58) 7165
38.8%

운영시간
Text

MISSING 

Distinct569
Distinct (%)81.9%
Missing114
Missing (%)14.1%
Memory size6.4 KiB
2024-05-18T18:52:00.101091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length318
Median length156
Mean length28.260432
Min length5

Characters and Unicode

Total characters19641
Distinct characters516
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

Unique489 ?
Unique (%)70.4%

Sample

1st rowTue-Sun 13:00-19:00
2nd row水曜日~土曜日: 14:30-19:30
3rd row市場店앻不同營運時間有異
4th rowDaily 10:00 - 19:00 KST *Closed Tuesdays* Restaurant, Daily 10:00 - 22:00 KST *Closed Tuesdays*
5th 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)
ValueCountFrequency (%)
kst 465
 
14.4%
447
 
13.8%
10:30 97
 
3.0%
daily 95
 
2.9%
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%
12:00 38
 
1.2%
Other values (729) 1767
54.6%
2024-05-18T18:52:01.111881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3727
19.0%
2654
 
13.5%
: 1685
 
8.6%
1 1264
 
6.4%
2 837
 
4.3%
S 544
 
2.8%
~ 516
 
2.6%
T 507
 
2.6%
K 491
 
2.5%
3 480
 
2.4%
Other values (506) 6936
35.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6743
34.3%
Space Separator 2654
 
13.5%
Other Letter 2564
 
13.1%
Other Punctuation 2232
 
11.4%
Lowercase Letter 2029
 
10.3%
Uppercase Letter 1819
 
9.3%
Math Symbol 524
 
2.7%
Dash Punctuation 442
 
2.3%
Open Punctuation 312
 
1.6%
Close Punctuation 312
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
日 159
 
6.2%
일 105
 
4.1%
周 97
 
3.8%
店 59
 
2.3%
曜 51
 
2.0%
매 51
 
2.0%
週 39
 
1.5%
이 36
 
1.4%
시 35
 
1.4%
토 32
 
1.2%
Other values (426) 1900
74.1%
Lowercase Letter
ValueCountFrequency (%)
a 258
12.7%
y 207
10.2%
e 197
9.7%
r 171
8.4%
i 153
 
7.5%
s 145
 
7.1%
l 134
 
6.6%
o 132
 
6.5%
n 111
 
5.5%
u 100
 
4.9%
Other values (15) 421
20.7%
Uppercase Letter
ValueCountFrequency (%)
S 544
29.9%
T 507
27.9%
K 491
27.0%
D 85
 
4.7%
H 32
 
1.8%
O 26
 
1.4%
M 23
 
1.3%
F 19
 
1.0%
W 18
 
1.0%
C 18
 
1.0%
Other values (11) 56
 
3.1%
Other Punctuation
ValueCountFrequency (%)
: 1685
75.5%
? 300
 
13.4%
, 71
 
3.2%
* 49
 
2.2%
、 30
 
1.3%
/ 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 3727
55.3%
1 1264
 
18.7%
2 837
 
12.4%
3 480
 
7.1%
9 177
 
2.6%
8 140
 
2.1%
4 43
 
0.6%
7 35
 
0.5%
5 24
 
0.4%
6 16
 
0.2%
Math Symbol
ValueCountFrequency (%)
~ 516
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 (%)
2654
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 442
100.0%
Format
ValueCountFrequency (%)
­ 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13229
67.4%
Latin 3848
 
19.6%
Han 1253
 
6.4%
Hangul 1022
 
5.2%
Hiragana 201
 
1.0%
Katakana 88
 
0.4%

Most frequent character per script

Han
ValueCountFrequency (%)
日 159
 
12.7%
周 97
 
7.7%
店 59
 
4.7%
曜 51
 
4.1%
週 39
 
3.1%
異 30
 
2.4%
一 29
 
2.3%
各 29
 
2.3%
同 27
 
2.2%
不 27
 
2.2%
Other values (181) 706
56.3%
Hangul
ValueCountFrequency (%)
일 105
 
10.3%
매 51
 
5.0%
이 36
 
3.5%
시 35
 
3.4%
토 32
 
3.1%
월 30
 
2.9%
장 29
 
2.8%
금 25
 
2.4%
간 21
 
2.1%
요 21
 
2.1%
Other values (173) 637
62.3%
Latin
ValueCountFrequency (%)
S 544
14.1%
T 507
13.2%
K 491
12.8%
a 258
 
6.7%
y 207
 
5.4%
e 197
 
5.1%
r 171
 
4.4%
i 153
 
4.0%
s 145
 
3.8%
l 134
 
3.5%
Other values (36) 1041
27.1%
Katakana
ValueCountFrequency (%)
ン 10
 
11.4%
ト 7
 
8.0%
ラ 5
 
5.7%
イ 5
 
5.7%
レ 5
 
5.7%
ス 5
 
5.7%
ェ 4
 
4.5%
ッ 4
 
4.5%
ロ 3
 
3.4%
テ 3
 
3.4%
Other values (25) 37
42.0%
Common
ValueCountFrequency (%)
0 3727
28.2%
2654
20.1%
: 1685
12.7%
1 1264
 
9.6%
2 837
 
6.3%
~ 516
 
3.9%
3 480
 
3.6%
- 442
 
3.3%
( 304
 
2.3%
) 303
 
2.3%
Other values (24) 1017
 
7.7%
Hiragana
ValueCountFrequency (%)
に 28
13.9%
な 27
13.4%
る 26
12.9%
り 26
12.9%
よ 26
12.9%
ま 8
 
4.0%
は 7
 
3.5%
の 7
 
3.5%
て 5
 
2.5%
っ 5
 
2.5%
Other values (17) 36
17.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16960
86.3%
CJK 1253
 
6.4%
Hangul 1022
 
5.2%
Hiragana 201
 
1.0%
None 101
 
0.5%
Katakana 88
 
0.4%
Punctuation 16
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3727
22.0%
2654
15.6%
: 1685
 
9.9%
1 1264
 
7.5%
2 837
 
4.9%
S 544
 
3.2%
~ 516
 
3.0%
T 507
 
3.0%
K 491
 
2.9%
3 480
 
2.8%
Other values (60) 4255
25.1%
CJK
ValueCountFrequency (%)
日 159
 
12.7%
周 97
 
7.7%
店 59
 
4.7%
曜 51
 
4.1%
週 39
 
3.1%
異 30
 
2.4%
一 29
 
2.3%
各 29
 
2.3%
同 27
 
2.2%
不 27
 
2.2%
Other values (181) 706
56.3%
Hangul
ValueCountFrequency (%)
일 105
 
10.3%
매 51
 
5.0%
이 36
 
3.5%
시 35
 
3.4%
토 32
 
3.1%
월 30
 
2.9%
장 29
 
2.8%
금 25
 
2.4%
간 21
 
2.1%
요 21
 
2.1%
Other values (173) 637
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%
り 26
12.9%
よ 26
12.9%
ま 8
 
4.0%
は 7
 
3.5%
の 7
 
3.5%
て 5
 
2.5%
っ 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%
イ 5
 
5.7%
レ 5
 
5.7%
ス 5
 
5.7%
ェ 4
 
4.5%
ッ 4
 
4.5%
ロ 3
 
3.4%
テ 3
 
3.4%
Other values (25) 37
42.0%

교통정보
Text

MISSING 

Distinct739
Distinct (%)95.1%
Missing32
Missing (%)4.0%
Memory size6.4 KiB
2024-05-18T18:52:01.819844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length191
Median length114
Mean length34.705277
Min length7

Characters and Unicode

Total characters26966
Distinct characters611
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

Unique706 ?
Unique (%)90.9%

Sample

1st row775m from Subway Line 3, Gyeongbokgung Station, Exit 2
2nd row地下?3?線「キョンボックン」?3番出口から7212、7022、1020バスに搭?
3rd row6、7號線 泰陵入口站 4號出口
4th rowSubway Lines 1 & 2, Sinseoldong Station, Exit 9
5th row地下?2?線?カンビョン??地下?行通路に連結
ValueCountFrequency (%)
station 210
 
5.2%
line 189
 
4.6%
subway 179
 
4.4%
exit 160
 
3.9%
출구 152
 
3.7%
113
 
2.8%
2 105
 
2.6%
4 89
 
2.2%
3 89
 
2.2%
1 81
 
2.0%
Other values (1062) 2702
66.4%
2024-05-18T18:52:03.006620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3747
 
13.9%
? 1774
 
6.6%
n 957
 
3.5%
i 819
 
3.0%
t 746
 
2.8%
o 693
 
2.6%
a 605
 
2.2%
, 569
 
2.1%
1 565
 
2.1%
2 484
 
1.8%
Other values (601) 16007
59.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8749
32.4%
Lowercase Letter 6766
25.1%
Space Separator 3747
13.9%
Decimal Number 3092
 
11.5%
Other Punctuation 2729
 
10.1%
Uppercase Letter 1207
 
4.5%
Close Punctuation 304
 
1.1%
Open Punctuation 304
 
1.1%
Dash Punctuation 39
 
0.1%
Math Symbol 16
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
口 473
 
5.4%
出 469
 
5.4%
ン 393
 
4.5%
線 341
 
3.9%
구 301
 
3.4%
선 280
 
3.2%
번 276
 
3.2%
地 267
 
3.1%
番 264
 
3.0%
站 253
 
2.9%
Other values (520) 5432
62.1%
Lowercase Letter
ValueCountFrequency (%)
n 957
14.1%
i 819
12.1%
t 746
11.0%
o 693
10.2%
a 605
8.9%
e 462
 
6.8%
u 365
 
5.4%
g 304
 
4.5%
y 269
 
4.0%
b 206
 
3.0%
Other values (15) 1340
19.8%
Uppercase Letter
ValueCountFrequency (%)
S 429
35.5%
L 224
18.6%
E 217
18.0%
M 37
 
3.1%
A 34
 
2.8%
G 33
 
2.7%
H 32
 
2.7%
J 27
 
2.2%
B 24
 
2.0%
D 22
 
1.8%
Other values (13) 128
 
10.6%
Other Punctuation
ValueCountFrequency (%)
? 1774
65.0%
, 569
 
20.9%
/ 112
 
4.1%
、 96
 
3.5%
& 60
 
2.2%
* 46
 
1.7%
· 34
 
1.2%
， 20
 
0.7%
. 8
 
0.3%
。 5
 
0.2%
Other values (2) 5
 
0.2%
Decimal Number
ValueCountFrequency (%)
1 565
18.3%
2 484
15.7%
3 434
14.0%
5 413
13.4%
4 358
11.6%
6 248
8.0%
0 200
 
6.5%
7 179
 
5.8%
8 128
 
4.1%
9 83
 
2.7%
Close Punctuation
ValueCountFrequency (%)
」 196
64.5%
) 105
34.5%
） 3
 
1.0%
Open Punctuation
ValueCountFrequency (%)
「 196
64.5%
( 105
34.5%
（ 3
 
1.0%
Math Symbol
ValueCountFrequency (%)
~ 10
62.5%
→ 6
37.5%
Space Separator
ValueCountFrequency (%)
3747
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 39
100.0%
Control
ValueCountFrequency (%)
13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10244
38.0%
Latin 7973
29.6%
Han 3795
 
14.1%
Hangul 3098
 
11.5%
Katakana 1669
 
6.2%
Hiragana 187
 
0.7%

Most frequent character per script

Han
ValueCountFrequency (%)
口 473
 
12.5%
出 469
 
12.4%
線 341
 
9.0%
地 267
 
7.0%
番 264
 
7.0%
站 253
 
6.7%
下 213
 
5.6%
分 98
 
2.6%
號 85
 
2.2%
行 53
 
1.4%
Other values (234) 1279
33.7%
Hangul
ValueCountFrequency (%)
구 301
 
9.7%
선 280
 
9.0%
번 276
 
8.9%
출 252
 
8.1%
호 240
 
7.7%
역 236
 
7.6%
분 77
 
2.5%
로 69
 
2.2%
서 60
 
1.9%
도 56
 
1.8%
Other values (184) 1251
40.4%
Katakana
ValueCountFrequency (%)
ン 393
23.5%
ョ 110
 
6.6%
ク 78
 
4.7%
ム 57
 
3.4%
チ 52
 
3.1%
プ 50
 
3.0%
デ 48
 
2.9%
ジ 46
 
2.8%
イ 44
 
2.6%
ア 43
 
2.6%
Other values (58) 748
44.8%
Latin
ValueCountFrequency (%)
n 957
12.0%
i 819
 
10.3%
t 746
 
9.4%
o 693
 
8.7%
a 605
 
7.6%
e 462
 
5.8%
S 429
 
5.4%
u 365
 
4.6%
g 304
 
3.8%
y 269
 
3.4%
Other values (38) 2324
29.1%
Common
ValueCountFrequency (%)
3747
36.6%
? 1774
17.3%
, 569
 
5.6%
1 565
 
5.5%
2 484
 
4.7%
3 434
 
4.2%
5 413
 
4.0%
4 358
 
3.5%
6 248
 
2.4%
0 200
 
2.0%
Other values (23) 1452
 
14.2%
Hiragana
ValueCountFrequency (%)
か 56
29.9%
ら 56
29.9%
の 10
 
5.3%
に 9
 
4.8%
り 9
 
4.8%
を 5
 
2.7%
よ 4
 
2.1%
え 4
 
2.1%
で 4
 
2.1%
し 4
 
2.1%
Other values (14) 26
13.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17656
65.5%
CJK 3795
 
14.1%
Hangul 3098
 
11.5%
Katakana 1669
 
6.2%
None 555
 
2.1%
Hiragana 187
 
0.7%
Arrows 6
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3747
21.2%
? 1774
 
10.0%
n 957
 
5.4%
i 819
 
4.6%
t 746
 
4.2%
o 693
 
3.9%
a 605
 
3.4%
, 569
 
3.2%
1 565
 
3.2%
2 484
 
2.7%
Other values (61) 6697
37.9%
CJK
ValueCountFrequency (%)
口 473
 
12.5%
出 469
 
12.4%
線 341
 
9.0%
地 267
 
7.0%
番 264
 
7.0%
站 253
 
6.7%
下 213
 
5.6%
分 98
 
2.6%
號 85
 
2.2%
行 53
 
1.4%
Other values (234) 1279
33.7%
Katakana
ValueCountFrequency (%)
ン 393
23.5%
ョ 110
 
6.6%
ク 78
 
4.7%
ム 57
 
3.4%
チ 52
 
3.1%
プ 50
 
3.0%
デ 48
 
2.9%
ジ 46
 
2.8%
イ 44
 
2.6%
ア 43
 
2.6%
Other values (58) 748
44.8%
Hangul
ValueCountFrequency (%)
구 301
 
9.7%
선 280
 
9.0%
번 276
 
8.9%
출 252
 
8.1%
호 240
 
7.7%
역 236
 
7.6%
분 77
 
2.5%
로 69
 
2.2%
서 60
 
1.9%
도 56
 
1.8%
Other values (184) 1251
40.4%
None
ValueCountFrequency (%)
」 196
35.3%
「 196
35.3%
、 96
17.3%
· 34
 
6.1%
， 20
 
3.6%
。 5
 
0.9%
） 3
 
0.5%
（ 3
 
0.5%
： 2
 
0.4%
Hiragana
ValueCountFrequency (%)
か 56
29.9%
ら 56
29.9%
の 10
 
5.3%
に 9
 
4.8%
り 9
 
4.8%
を 5
 
2.7%
よ 4
 
2.1%
え 4
 
2.1%
で 4
 
2.1%
し 4
 
2.1%
Other values (14) 26
13.9%
Arrows
ValueCountFrequency (%)
→ 6
100.0%

Interactions

2024-05-18T18:51:46.590948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T18:52:03.276213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
고유번호언어
고유번호1.0000.095
언어0.0951.000
2024-05-18T18:52:03.516220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
고유번호언어
고유번호1.0000.054
언어0.0541.000

Missing values

2024-05-18T18:51:46.955041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T18:51:47.461919image/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.
2024-05-18T18:51:47.861536image/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
045758enThe Book Societyhttps://english.visitseoul.net/shopping/2024-thebooksociety/ENPbxv0dg?utm_source=seoulopendata&utm_medium=shopping&utm_content=ENPbxv0dg서울 종로구 옥인동 19-4503035 B1, 25 Jahamun-ro 19-gil, Jongno-gu, Seoul+82-70-8621-5676https://www.thebooksociety.org/blogTue-Sun 13:00-19:00775m from Subway Line 3, Gyeongbokgung Station, Exit 2
1270zh-CN?流周?商品<NA><NA><NA><NA><NA>
245751jaLoft Bookshttps://japanese.visitseoul.net/shopping/2024-LoftBooks/JPPted0es?utm_source=seoulopendata&utm_medium=shopping&utm_content=JPPted0es서울 종로구 부암동 251-403022 ソウル市チョンノ(鍾路)?チャンイムンロ129、2階+82-507-1310-3225https://www.instagram.com/loftbooks_seoul/水曜日~土曜日: 14:30-19:30地下?3?線「キョンボックン」?3番出口から7212、7022、1020バスに搭?
345715zh-CN孔陵洞 夜間市場https://chinese.visitseoul.net/shopping/2024-gongneungmarket/CNP7xadww?utm_source=seoulopendata&utm_medium=shopping&utm_content=CNP7xadww서울 노원구 공릉동 561-3501846 首爾市蘆?區東日路180街 53+82-2-976-4143https://www.gogoma.kr/市場店앻不同營運時間有異6、7號線 泰陵入口站 4號出口
41653enSeoul 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
52231ja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
638759zh-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
745756enLoft Bookshttps://english.visitseoul.net/shopping/2024-LoftBooks/ENPted0es?utm_source=seoulopendata&utm_medium=shopping&utm_content=ENPted0es서울 종로구 부암동 251-403022 129 Changuimun-ro, Jongno-gu, Seoul+82-507-1310-3225https://www.instagram.com/loftbooks_seoul/Wed-Sat: 14:30 - 19:30Take bus 7212, 7022, or 1020 at Exit 3 of Gyeongbokgung Station on Line 3
89631ko방학동 도깨비시장https://korean.visitseoul.net/shopping/방학동-도깨비시장-KR/KOP009631?utm_source=seoulopendata&utm_medium=shopping&utm_content=KOP009631132-841 서울 도봉구 방학동 631-5 632-01358 서울 도봉구 도당로13다길 30 (방학동)02-954-1225http://bhdokkaebi.modoo.at/08:00~21:301호선 방학역 2번 출구 1126번 환승 후 원약국 정류장 하차
911598ja10 Corso Comohttps://japanese.visitseoul.net/shopping/10-Corso-Como-JP/JPP011597?utm_source=seoulopendata&utm_medium=shopping&utm_content=JPP011597135-100 ソウル市江南??潭洞 7906015 ソウル市カンナム(江南)?アックジョンロ416 (?潭洞)+82-2-547-3010http://www.10corsocomo.com11:00-16:30, 18:00-22:00 (KST)<NA>
고유번호언어상호명콘텐츠URL주소신주소전화번호웹사이트운영시간교통정보
79943521zh-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
80041785ko망리단길https://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
80143756ko무신사 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
80243753jaMUSINSA 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
80344139ko엠프티https://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
80442256enFigure 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>
80543495ko세븐웰https://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
80643516ja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
80743511enItaewon 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
80843272ko엔터식스 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