Overview

Dataset statistics

Number of variables5
Number of observations1470
Missing cells32
Missing cells (%)0.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory57.6 KiB
Average record size in memory40.1 B

Variable types

Categorical1
Text3
DateTime1

Dataset

Description제주특별자치도 서귀포시 관내 휴게음식점(식품접객업)에 대한 데이터로 업종명, 업소명, 소재지(도로,지번)의 항목을 제공합니다.
Author제주특별자치도 서귀포시
URLhttps://www.data.go.kr/data/15055973/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
업종명 is highly imbalanced (86.0%)Imbalance
소재지(도로명) has 28 (1.9%) missing valuesMissing

Reproduction

Analysis started2024-04-06 08:05:06.533538
Analysis finished2024-04-06 08:05:08.811720
Duration2.28 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
휴게음식점
1441 
<NA>
 
29

Length

Max length5
Median length5
Mean length4.9802721
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row휴게음식점
2nd row휴게음식점
3rd row휴게음식점
4th row휴게음식점
5th row휴게음식점

Common Values

ValueCountFrequency (%)
휴게음식점 1441
98.0%
<NA> 29
 
2.0%

Length

2024-04-06T17:05:08.960345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:05:09.264135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
휴게음식점 1441
98.0%
na 29
 
2.0%

업소명
Text

Distinct1469
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
2024-04-06T17:05:09.889170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length28
Mean length7.9034014
Min length1

Characters and Unicode

Total characters11618
Distinct characters712
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1468 ?
Unique (%)99.9%

Sample

1st row제이(J)문화예술앤(&)공방찻집
2nd row휘베이글(Hwi Bagel)
3rd row씨유서귀포서홍점
4th row군것질
5th row파크삼(parc3)
ValueCountFrequency (%)
씨유 4
 
0.2%
세븐일레븐 4
 
0.2%
coffee 4
 
0.2%
카페 3
 
0.2%
스타월드 3
 
0.2%
서귀포 3
 
0.2%
서귀포중문점 2
 
0.1%
cafe 2
 
0.1%
tea 2
 
0.1%
아쿠아 2
 
0.1%
Other values (1570) 1574
98.2%
2024-04-06T17:05:11.037407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 597
 
5.1%
서 341
 
2.9%
귀 311
 
2.7%
포 241
 
2.1%
스 232
 
2.0%
주 201
 
1.7%
제 201
 
1.7%
씨 193
 
1.7%
유 183
 
1.6%
카 168
 
1.4%
Other values (702) 8950
77.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9867
84.9%
Lowercase Letter 518
 
4.5%
Uppercase Letter 510
 
4.4%
Decimal Number 281
 
2.4%
Close Punctuation 143
 
1.2%
Open Punctuation 143
 
1.2%
Space Separator 133
 
1.1%
Other Punctuation 22
 
0.2%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 597
 
6.1%
서 341
 
3.5%
귀 311
 
3.2%
포 241
 
2.4%
스 232
 
2.4%
주 201
 
2.0%
제 201
 
2.0%
씨 193
 
2.0%
유 183
 
1.9%
카 168
 
1.7%
Other values (634) 7199
73.0%
Uppercase Letter
ValueCountFrequency (%)
S 52
 
10.2%
E 51
 
10.0%
O 44
 
8.6%
C 41
 
8.0%
G 40
 
7.8%
A 35
 
6.9%
F 25
 
4.9%
P 22
 
4.3%
D 22
 
4.3%
M 20
 
3.9%
Other values (15) 158
31.0%
Lowercase Letter
ValueCountFrequency (%)
e 78
15.1%
a 63
12.2%
o 51
 
9.8%
l 34
 
6.6%
r 32
 
6.2%
n 31
 
6.0%
f 25
 
4.8%
c 25
 
4.8%
t 23
 
4.4%
i 21
 
4.1%
Other values (13) 135
26.1%
Decimal Number
ValueCountFrequency (%)
2 106
37.7%
5 98
34.9%
1 23
 
8.2%
0 14
 
5.0%
3 10
 
3.6%
7 8
 
2.8%
9 8
 
2.8%
4 7
 
2.5%
6 6
 
2.1%
8 1
 
0.4%
Other Punctuation
ValueCountFrequency (%)
& 11
50.0%
， 4
 
18.2%
' 3
 
13.6%
. 2
 
9.1%
: 1
 
4.5%
# 1
 
4.5%
Close Punctuation
ValueCountFrequency (%)
) 143
100.0%
Open Punctuation
ValueCountFrequency (%)
( 143
100.0%
Space Separator
ValueCountFrequency (%)
133
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9864
84.9%
Latin 1028
 
8.8%
Common 723
 
6.2%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 597
 
6.1%
서 341
 
3.5%
귀 311
 
3.2%
포 241
 
2.4%
스 232
 
2.4%
주 201
 
2.0%
제 201
 
2.0%
씨 193
 
2.0%
유 183
 
1.9%
카 168
 
1.7%
Other values (631) 7196
73.0%
Latin
ValueCountFrequency (%)
e 78
 
7.6%
a 63
 
6.1%
S 52
 
5.1%
o 51
 
5.0%
E 51
 
5.0%
O 44
 
4.3%
C 41
 
4.0%
G 40
 
3.9%
A 35
 
3.4%
l 34
 
3.3%
Other values (38) 539
52.4%
Common
ValueCountFrequency (%)
) 143
19.8%
( 143
19.8%
133
18.4%
2 106
14.7%
5 98
13.6%
1 23
 
3.2%
0 14
 
1.9%
& 11
 
1.5%
3 10
 
1.4%
7 8
 
1.1%
Other values (10) 34
 
4.7%
Han
ValueCountFrequency (%)
茶 1
33.3%
素 1
33.3%
直 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9864
84.9%
ASCII 1747
 
15.0%
None 4
 
< 0.1%
CJK 3
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 597
 
6.1%
서 341
 
3.5%
귀 311
 
3.2%
포 241
 
2.4%
스 232
 
2.4%
주 201
 
2.0%
제 201
 
2.0%
씨 193
 
2.0%
유 183
 
1.9%
카 168
 
1.7%
Other values (631) 7196
73.0%
ASCII
ValueCountFrequency (%)
) 143
 
8.2%
( 143
 
8.2%
133
 
7.6%
2 106
 
6.1%
5 98
 
5.6%
e 78
 
4.5%
a 63
 
3.6%
S 52
 
3.0%
o 51
 
2.9%
E 51
 
2.9%
Other values (57) 829
47.5%
None
ValueCountFrequency (%)
， 4
100.0%
CJK
ValueCountFrequency (%)
茶 1
33.3%
素 1
33.3%
直 1
33.3%

소재지(도로명)
Text

MISSING 

Distinct1391
Distinct (%)96.5%
Missing28
Missing (%)1.9%
Memory size11.6 KiB
2024-04-06T17:05:11.763682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length48
Mean length30.151872
Min length22

Characters and Unicode

Total characters43479
Distinct characters312
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1346 ?
Unique (%)93.3%

Sample

1st row제주특별자치도 서귀포시 남원읍 위미해안로 118-5
2nd row제주특별자치도 서귀포시 중정로5번길 21， 1층 (서귀동)
3rd row제주특별자치도 서귀포시 중산간동로 8110， 1층 (서홍동)
4th row제주특별자치도 서귀포시 솜반천로 18， 1층 (서홍동)
5th row제주특별자치도 서귀포시 신동로67번길 31， 지하 1층 (서호동)
ValueCountFrequency (%)
제주특별자치도 1442
 
17.6%
서귀포시 1442
 
17.6%
1층 515
 
6.3%
서귀동 181
 
2.2%
성산읍 161
 
2.0%
대정읍 156
 
1.9%
안덕면 154
 
1.9%
남원읍 119
 
1.4%
표선면 111
 
1.4%
동홍동 95
 
1.2%
Other values (1482) 3832
46.7%
2024-04-06T17:05:13.101272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6766
 
15.6%
서 1939
 
4.5%
1 1661
 
3.8%
귀 1642
 
3.8%
주 1569
 
3.6%
제 1512
 
3.5%
도 1492
 
3.4%
포 1480
 
3.4%
시 1469
 
3.4%
로 1455
 
3.3%
Other values (302) 22494
51.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 27981
64.4%
Space Separator 6766
 
15.6%
Decimal Number 5966
 
13.7%
Other Punctuation 837
 
1.9%
Close Punctuation 755
 
1.7%
Open Punctuation 755
 
1.7%
Dash Punctuation 287
 
0.7%
Uppercase Letter 65
 
0.1%
Lowercase Letter 62
 
0.1%
Math Symbol 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 1939
 
6.9%
귀 1642
 
5.9%
주 1569
 
5.6%
제 1512
 
5.4%
도 1492
 
5.3%
포 1480
 
5.3%
시 1469
 
5.2%
로 1455
 
5.2%
별 1443
 
5.2%
자 1443
 
5.2%
Other values (256) 12537
44.8%
Uppercase Letter
ValueCountFrequency (%)
A 17
26.2%
B 15
23.1%
C 6
 
9.2%
J 6
 
9.2%
E 5
 
7.7%
P 5
 
7.7%
H 2
 
3.1%
U 2
 
3.1%
G 2
 
3.1%
D 1
 
1.5%
Other values (4) 4
 
6.2%
Lowercase Letter
ValueCountFrequency (%)
e 12
19.4%
u 11
17.7%
a 10
16.1%
n 6
9.7%
j 5
8.1%
l 5
8.1%
q 5
8.1%
t 5
8.1%
z 1
 
1.6%
o 1
 
1.6%
Decimal Number
ValueCountFrequency (%)
1 1661
27.8%
2 882
14.8%
4 512
 
8.6%
3 490
 
8.2%
6 451
 
7.6%
0 435
 
7.3%
5 412
 
6.9%
8 397
 
6.7%
7 392
 
6.6%
9 334
 
5.6%
Other Punctuation
ValueCountFrequency (%)
， 832
99.4%
. 4
 
0.5%
* 1
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 754
99.9%
] 1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 754
99.9%
[ 1
 
0.1%
Space Separator
ValueCountFrequency (%)
6766
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 287
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 27981
64.4%
Common 15370
35.4%
Latin 128
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 1939
 
6.9%
귀 1642
 
5.9%
주 1569
 
5.6%
제 1512
 
5.4%
도 1492
 
5.3%
포 1480
 
5.3%
시 1469
 
5.2%
로 1455
 
5.2%
별 1443
 
5.2%
자 1443
 
5.2%
Other values (256) 12537
44.8%
Latin
ValueCountFrequency (%)
A 17
13.3%
B 15
11.7%
e 12
 
9.4%
u 11
 
8.6%
a 10
 
7.8%
C 6
 
4.7%
J 6
 
4.7%
n 6
 
4.7%
j 5
 
3.9%
E 5
 
3.9%
Other values (16) 35
27.3%
Common
ValueCountFrequency (%)
6766
44.0%
1 1661
 
10.8%
2 882
 
5.7%
， 832
 
5.4%
) 754
 
4.9%
( 754
 
4.9%
4 512
 
3.3%
3 490
 
3.2%
6 451
 
2.9%
0 435
 
2.8%
Other values (10) 1833
 
11.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 27981
64.4%
ASCII 14665
33.7%
None 832
 
1.9%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6766
46.1%
1 1661
 
11.3%
2 882
 
6.0%
) 754
 
5.1%
( 754
 
5.1%
4 512
 
3.5%
3 490
 
3.3%
6 451
 
3.1%
0 435
 
3.0%
5 412
 
2.8%
Other values (34) 1548
 
10.6%
Hangul
ValueCountFrequency (%)
서 1939
 
6.9%
귀 1642
 
5.9%
주 1569
 
5.6%
제 1512
 
5.4%
도 1492
 
5.3%
포 1480
 
5.3%
시 1469
 
5.2%
로 1455
 
5.2%
별 1443
 
5.2%
자 1443
 
5.2%
Other values (256) 12537
44.8%
None
ValueCountFrequency (%)
， 832
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

소재지(지번)
Text

Distinct1395
Distinct (%)95.2%
Missing4
Missing (%)0.3%
Memory size11.6 KiB
2024-04-06T17:05:13.643686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length42
Mean length26.676671
Min length19

Characters and Unicode

Total characters39108
Distinct characters248
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1336 ?
Unique (%)91.1%

Sample

1st row제주특별자치도 서귀포시 남원읍 위미리 3032-2
2nd row제주특별자치도 서귀포시 서귀동 322-8
3rd row제주특별자치도 서귀포시 서홍동 1645-1
4th row제주특별자치도 서귀포시 서홍동 422-11
5th row제주특별자치도 서귀포시 서호동 1458-1
ValueCountFrequency (%)
제주특별자치도 1466
21.0%
서귀포시 1466
21.0%
서귀동 181
 
2.6%
성산읍 164
 
2.3%
안덕면 157
 
2.2%
대정읍 156
 
2.2%
남원읍 123
 
1.8%
표선면 118
 
1.7%
1층 114
 
1.6%
동홍동 104
 
1.5%
Other values (1537) 2934
42.0%
2024-04-06T17:05:14.540410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6960
 
17.8%
서 1805
 
4.6%
귀 1662
 
4.2%
1 1536
 
3.9%
시 1492
 
3.8%
포 1484
 
3.8%
제 1482
 
3.8%
주 1480
 
3.8%
도 1475
 
3.8%
별 1468
 
3.8%
Other values (238) 18264
46.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 24354
62.3%
Space Separator 6960
 
17.8%
Decimal Number 6514
 
16.7%
Dash Punctuation 1110
 
2.8%
Lowercase Letter 66
 
0.2%
Other Punctuation 60
 
0.2%
Uppercase Letter 36
 
0.1%
Open Punctuation 3
 
< 0.1%
Close Punctuation 3
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 1805
 
7.4%
귀 1662
 
6.8%
시 1492
 
6.1%
포 1484
 
6.1%
제 1482
 
6.1%
주 1480
 
6.1%
도 1475
 
6.1%
별 1468
 
6.0%
치 1467
 
6.0%
자 1466
 
6.0%
Other values (203) 9073
37.3%
Decimal Number
ValueCountFrequency (%)
1 1536
23.6%
2 924
14.2%
3 642
9.9%
4 605
 
9.3%
5 536
 
8.2%
6 482
 
7.4%
0 481
 
7.4%
7 479
 
7.4%
9 418
 
6.4%
8 411
 
6.3%
Uppercase Letter
ValueCountFrequency (%)
A 8
22.2%
J 6
16.7%
P 6
16.7%
B 4
11.1%
U 3
 
8.3%
C 3
 
8.3%
S 2
 
5.6%
G 2
 
5.6%
F 1
 
2.8%
E 1
 
2.8%
Lowercase Letter
ValueCountFrequency (%)
a 12
18.2%
u 12
18.2%
e 12
18.2%
q 6
9.1%
l 6
9.1%
j 6
9.1%
n 6
9.1%
t 6
9.1%
Space Separator
ValueCountFrequency (%)
6960
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1110
100.0%
Other Punctuation
ValueCountFrequency (%)
， 60
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 24354
62.3%
Common 14651
37.5%
Latin 103
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 1805
 
7.4%
귀 1662
 
6.8%
시 1492
 
6.1%
포 1484
 
6.1%
제 1482
 
6.1%
주 1480
 
6.1%
도 1475
 
6.1%
별 1468
 
6.0%
치 1467
 
6.0%
자 1466
 
6.0%
Other values (203) 9073
37.3%
Latin
ValueCountFrequency (%)
a 12
11.7%
u 12
11.7%
e 12
11.7%
A 8
 
7.8%
J 6
 
5.8%
q 6
 
5.8%
P 6
 
5.8%
l 6
 
5.8%
j 6
 
5.8%
n 6
 
5.8%
Other values (9) 23
22.3%
Common
ValueCountFrequency (%)
6960
47.5%
1 1536
 
10.5%
- 1110
 
7.6%
2 924
 
6.3%
3 642
 
4.4%
4 605
 
4.1%
5 536
 
3.7%
6 482
 
3.3%
0 481
 
3.3%
7 479
 
3.3%
Other values (6) 896
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 24354
62.3%
ASCII 14693
37.6%
None 60
 
0.2%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6960
47.4%
1 1536
 
10.5%
- 1110
 
7.6%
2 924
 
6.3%
3 642
 
4.4%
4 605
 
4.1%
5 536
 
3.6%
6 482
 
3.3%
0 481
 
3.3%
7 479
 
3.3%
Other values (23) 938
 
6.4%
Hangul
ValueCountFrequency (%)
서 1805
 
7.4%
귀 1662
 
6.8%
시 1492
 
6.1%
포 1484
 
6.1%
제 1482
 
6.1%
주 1480
 
6.1%
도 1475
 
6.1%
별 1468
 
6.0%
치 1467
 
6.0%
자 1466
 
6.0%
Other values (203) 9073
37.3%
None
ValueCountFrequency (%)
， 60
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
Minimum2024-04-01 00:00:00
Maximum2024-04-01 00:00:00
2024-04-06T17:05:14.783945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:05:15.034493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Missing values

2024-04-06T17:05:08.331542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:05:08.532260image/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.
2024-04-06T17:05:08.708923image/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

업종명업소명소재지(도로명)소재지(지번)데이터기준일자
0휴게음식점제이(J)문화예술앤(&)공방찻집제주특별자치도 서귀포시 남원읍 위미해안로 118-5제주특별자치도 서귀포시 남원읍 위미리 3032-22024-04-01
1휴게음식점휘베이글(Hwi Bagel)제주특별자치도 서귀포시 중정로5번길 21， 1층 (서귀동)제주특별자치도 서귀포시 서귀동 322-82024-04-01
2휴게음식점씨유서귀포서홍점제주특별자치도 서귀포시 중산간동로 8110， 1층 (서홍동)제주특별자치도 서귀포시 서홍동 1645-12024-04-01
3휴게음식점군것질제주특별자치도 서귀포시 솜반천로 18， 1층 (서홍동)제주특별자치도 서귀포시 서홍동 422-112024-04-01
4휴게음식점파크삼(parc3)제주특별자치도 서귀포시 신동로67번길 31， 지하 1층 (서호동)제주특별자치도 서귀포시 서호동 1458-12024-04-01
5휴게음식점씨유남제주점제주특별자치도 서귀포시 남원읍 태위로 673， CU 1층제주특별자치도 서귀포시 남원읍 남원리 105 CU2024-04-01
6휴게음식점서호주택제주특별자치도 서귀포시 신북로 6 (서호동)제주특별자치도 서귀포시 서호동 1233-22024-04-01
7휴게음식점패스브루(path brew)제주특별자치도 서귀포시 안덕면 사계북로41번길 27-49제주특별자치도 서귀포시 안덕면 사계리 31912024-04-01
8휴게음식점카페더씨씨(Cafe the SEASEE)제주특별자치도 서귀포시 성산읍 환해장성로 43제주특별자치도 서귀포시 성산읍 신산리 445-12024-04-01
9휴게음식점공차제주영어교육도시점제주특별자치도 서귀포시 대정읍 에듀시티로239번길 12， 1층제주특별자치도 서귀포시 대정읍 보성리 2476-22024-04-01
업종명업소명소재지(도로명)소재지(지번)데이터기준일자
1460<NA>뽕뽕식당제주특별자치도 서귀포시 중앙로42번길 33， 1층 (서귀동)제주특별자치도 서귀포시 서귀동 272-17번지2024-04-01
1461<NA>곰다방제주특별자치도 서귀포시 표선면 표선중앙로 76제주특별자치도 서귀포시 표선면 표선리 699번지2024-04-01
1462<NA>김밥천국서귀포점제주특별자치도 서귀포시 중정로 60 (서귀동)제주특별자치도 서귀포시 서귀동 423-4번지2024-04-01
1463<NA>동미다방제주특별자치도 서귀포시 중정로 95-2 (서귀동)제주특별자치도 서귀포시 서귀동 256-11번지2024-04-01
1464<NA>화신다방제주특별자치도 서귀포시 안덕면 화순로 100-1제주특별자치도 서귀포시 안덕면 화순리 336번지2024-04-01
1465<NA>에덴분식제주특별자치도 서귀포시 중정로73번길 2 (서귀동)제주특별자치도 서귀포시 서귀동 273-8번지2024-04-01
1466<NA>해당화다방제주특별자치도 서귀포시 동문로 60， 2층 (서귀동)제주특별자치도 서귀포시 서귀동 256-25번지2024-04-01
1467<NA>보물섬다방제주특별자치도 서귀포시 솔동산로 6-1 (서귀동)제주특별자치도 서귀포시 서귀동 584-32024-04-01
1468<NA>우성다방제주특별자치도 서귀포시 중정로91번길 15， 2층 (서귀동)제주특별자치도 서귀포시 서귀동 272-18번지2024-04-01
1469<NA>수궁다방제주특별자치도 서귀포시 대정읍 하모항구로 78제주특별자치도 서귀포시 대정읍 하모리 938-17번지2024-04-01