Overview

Dataset statistics

Number of variables7
Number of observations78
Missing cells4
Missing cells (%)0.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.6 KiB
Average record size in memory60.7 B

Variable types

Text3
Numeric3
Categorical1

Dataset

Description서귀포시 휴양펜션업 등록현황(상호명, 소재지, 객실수, 연락처) 으로 휴양펜션업은 단순히 "펜션" 상호명을 사용하는 농어촌민박업과는 다른 관광사업(관광편의시설업) 업종임
Author제주특별자치도 서귀포시
URLhttps://www.data.go.kr/data/3044534/fileData.do

Alerts

데이터기준일 has constant value ""Constant
위도 is highly overall correlated with 경도High correlation
경도 is highly overall correlated with 위도High correlation
연락처 has 4 (5.1%) missing valuesMissing
상호명 has unique valuesUnique
소재지 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique

Reproduction

Analysis started2023-12-12 15:04:44.164869
Analysis finished2023-12-12 15:04:45.863256
Duration1.7 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

상호명
Text

UNIQUE 

Distinct78
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size756.0 B
2023-12-13T00:04:46.072272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length16
Mean length8.8717949
Min length3

Characters and Unicode

Total characters692
Distinct characters176
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique78 ?
Unique (%)100.0%

Sample

1st row솔바람풍경소리 휴양펜션
2nd row제주목화
3rd row예이츠산장
4th row포유펜션
5th row수망관광 휴양펜션
ValueCountFrequency (%)
휴양펜션 41
25.2%
펜션 7
 
4.3%
제주 4
 
2.5%
사계 3
 
1.8%
산방산 3
 
1.8%
愛(애 3
 
1.8%
빌리지 2
 
1.2%
서귀포 2
 
1.2%
솔바람풍경소리 1
 
0.6%
고성2119 1
 
0.6%
Other values (96) 96
58.9%
2023-12-13T00:04:46.473379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
85
 
12.3%
션 58
 
8.4%
펜 56
 
8.1%
휴 44
 
6.4%
양 44
 
6.4%
제 19
 
2.7%
주 16
 
2.3%
이 15
 
2.2%
라 14
 
2.0%
빌 13
 
1.9%
Other values (166) 328
47.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 592
85.5%
Space Separator 85
 
12.3%
Decimal Number 4
 
0.6%
Other Punctuation 3
 
0.4%
Close Punctuation 3
 
0.4%
Open Punctuation 3
 
0.4%
Uppercase Letter 1
 
0.1%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
션 58
 
9.8%
펜 56
 
9.5%
휴 44
 
7.4%
양 44
 
7.4%
제 19
 
3.2%
주 16
 
2.7%
이 15
 
2.5%
라 14
 
2.4%
빌 13
 
2.2%
스 10
 
1.7%
Other values (157) 303
51.2%
Decimal Number
ValueCountFrequency (%)
1 2
50.0%
9 1
25.0%
2 1
25.0%
Space Separator
ValueCountFrequency (%)
85
100.0%
Other Punctuation
ValueCountFrequency (%)
& 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
p 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 589
85.1%
Common 98
 
14.2%
Han 3
 
0.4%
Latin 2
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
션 58
 
9.8%
펜 56
 
9.5%
휴 44
 
7.5%
양 44
 
7.5%
제 19
 
3.2%
주 16
 
2.7%
이 15
 
2.5%
라 14
 
2.4%
빌 13
 
2.2%
스 10
 
1.7%
Other values (156) 300
50.9%
Common
ValueCountFrequency (%)
85
86.7%
& 3
 
3.1%
) 3
 
3.1%
( 3
 
3.1%
1 2
 
2.0%
9 1
 
1.0%
2 1
 
1.0%
Latin
ValueCountFrequency (%)
C 1
50.0%
p 1
50.0%
Han
ValueCountFrequency (%)
愛 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 589
85.1%
ASCII 100
 
14.5%
CJK 3
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
85
85.0%
& 3
 
3.0%
) 3
 
3.0%
( 3
 
3.0%
1 2
 
2.0%
9 1
 
1.0%
2 1
 
1.0%
C 1
 
1.0%
p 1
 
1.0%
Hangul
ValueCountFrequency (%)
션 58
 
9.8%
펜 56
 
9.5%
휴 44
 
7.5%
양 44
 
7.5%
제 19
 
3.2%
주 16
 
2.7%
이 15
 
2.5%
라 14
 
2.4%
빌 13
 
2.2%
스 10
 
1.7%
Other values (156) 300
50.9%
CJK
ValueCountFrequency (%)
愛 3
100.0%

소재지
Text

UNIQUE 

Distinct78
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size756.0 B
2023-12-13T00:04:46.829768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length29
Mean length25.448718
Min length19

Characters and Unicode

Total characters1985
Distinct characters100
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique78 ?
Unique (%)100.0%

Sample

1st row제주특별자치도 서귀포시 남원읍 태수로143번길 132-37
2nd row제주특별자치도 서귀포시 남원읍 태위로 485
3rd row제주특별자치도 서귀포시 남원읍 516로 918
4th row제주특별자치도 서귀포시 남원읍 서의로 40-6
5th row제주특별자치도 서귀포시 남원읍 서성로 986-24
ValueCountFrequency (%)
제주특별자치도 78
21.6%
서귀포시 78
21.6%
안덕면 18
 
5.0%
남원읍 14
 
3.9%
성산읍 9
 
2.5%
표선면 7
 
1.9%
사계북로 4
 
1.1%
일주서로 3
 
0.8%
6 3
 
0.8%
칠십리로 3
 
0.8%
Other values (132) 144
39.9%
2023-12-13T00:04:47.335817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
283
 
14.3%
서 88
 
4.4%
주 86
 
4.3%
도 81
 
4.1%
제 79
 
4.0%
포 79
 
4.0%
특 78
 
3.9%
별 78
 
3.9%
자 78
 
3.9%
치 78
 
3.9%
Other values (90) 977
49.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1339
67.5%
Decimal Number 333
 
16.8%
Space Separator 283
 
14.3%
Dash Punctuation 30
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 88
 
6.6%
주 86
 
6.4%
도 81
 
6.0%
제 79
 
5.9%
포 79
 
5.9%
특 78
 
5.8%
별 78
 
5.8%
자 78
 
5.8%
치 78
 
5.8%
귀 78
 
5.8%
Other values (78) 536
40.0%
Decimal Number
ValueCountFrequency (%)
1 70
21.0%
2 39
11.7%
3 38
11.4%
4 36
10.8%
5 35
10.5%
8 27
 
8.1%
7 26
 
7.8%
0 23
 
6.9%
6 23
 
6.9%
9 16
 
4.8%
Space Separator
ValueCountFrequency (%)
283
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1339
67.5%
Common 646
32.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 88
 
6.6%
주 86
 
6.4%
도 81
 
6.0%
제 79
 
5.9%
포 79
 
5.9%
특 78
 
5.8%
별 78
 
5.8%
자 78
 
5.8%
치 78
 
5.8%
귀 78
 
5.8%
Other values (78) 536
40.0%
Common
ValueCountFrequency (%)
283
43.8%
1 70
 
10.8%
2 39
 
6.0%
3 38
 
5.9%
4 36
 
5.6%
5 35
 
5.4%
- 30
 
4.6%
8 27
 
4.2%
7 26
 
4.0%
0 23
 
3.6%
Other values (2) 39
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1339
67.5%
ASCII 646
32.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
283
43.8%
1 70
 
10.8%
2 39
 
6.0%
3 38
 
5.9%
4 36
 
5.6%
5 35
 
5.4%
- 30
 
4.6%
8 27
 
4.2%
7 26
 
4.0%
0 23
 
3.6%
Other values (2) 39
 
6.0%
Hangul
ValueCountFrequency (%)
서 88
 
6.6%
주 86
 
6.4%
도 81
 
6.0%
제 79
 
5.9%
포 79
 
5.9%
특 78
 
5.8%
별 78
 
5.8%
자 78
 
5.8%
치 78
 
5.8%
귀 78
 
5.8%
Other values (78) 536
40.0%

객실수
Real number (ℝ)

Distinct8
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.6666667
Minimum3
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size834.0 B
2023-12-13T00:04:47.484319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile5
Q18
median10
Q310
95-th percentile10
Maximum10
Range7
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.7849782
Coefficient of variation (CV)0.20595902
Kurtosis0.73775647
Mean8.6666667
Median Absolute Deviation (MAD)0
Skewness-1.2650466
Sum676
Variance3.1861472
MonotonicityNot monotonic
2023-12-13T00:04:47.606096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
10 41
52.6%
8 12
 
15.4%
9 8
 
10.3%
7 6
 
7.7%
5 5
 
6.4%
6 4
 
5.1%
3 1
 
1.3%
4 1
 
1.3%
ValueCountFrequency (%)
3 1
 
1.3%
4 1
 
1.3%
5 5
 
6.4%
6 4
 
5.1%
7 6
 
7.7%
8 12
 
15.4%
9 8
 
10.3%
10 41
52.6%
ValueCountFrequency (%)
10 41
52.6%
9 8
 
10.3%
8 12
 
15.4%
7 6
 
7.7%
6 4
 
5.1%
5 5
 
6.4%
4 1
 
1.3%
3 1
 
1.3%

연락처
Text

MISSING 

Distinct71
Distinct (%)95.9%
Missing4
Missing (%)5.1%
Memory size756.0 B
2023-12-13T00:04:47.855092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.162162
Min length12

Characters and Unicode

Total characters900
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique69 ?
Unique (%)93.2%

Sample

1st row064-764-6002
2nd row064-764-7942
3rd row064-767-3746
4th row064-764-2777
5th row070-4151-5221
ValueCountFrequency (%)
064-794-0040 3
 
4.0%
064-792-4200 2
 
2.7%
064-733-3136 1
 
1.3%
064-762-3746 1
 
1.3%
064-767-2003 1
 
1.3%
064-738-0117 1
 
1.3%
064-767-9797 1
 
1.3%
064-735-9507 1
 
1.3%
064-764-6002 1
 
1.3%
064-738-7545 1
 
1.3%
Other values (62) 62
82.7%
2023-12-13T00:04:48.296063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 147
16.3%
0 138
15.3%
7 116
12.9%
4 113
12.6%
6 108
12.0%
3 65
7.2%
8 51
 
5.7%
9 44
 
4.9%
2 42
 
4.7%
1 42
 
4.7%
Other values (2) 34
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 752
83.6%
Dash Punctuation 147
 
16.3%
Space Separator 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 138
18.4%
7 116
15.4%
4 113
15.0%
6 108
14.4%
3 65
8.6%
8 51
 
6.8%
9 44
 
5.9%
2 42
 
5.6%
1 42
 
5.6%
5 33
 
4.4%
Dash Punctuation
ValueCountFrequency (%)
- 147
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 900
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 147
16.3%
0 138
15.3%
7 116
12.9%
4 113
12.6%
6 108
12.0%
3 65
7.2%
8 51
 
5.7%
9 44
 
4.9%
2 42
 
4.7%
1 42
 
4.7%
Other values (2) 34
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 900
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 147
16.3%
0 138
15.3%
7 116
12.9%
4 113
12.6%
6 108
12.0%
3 65
7.2%
8 51
 
5.7%
9 44
 
4.9%
2 42
 
4.7%
1 42
 
4.7%
Other values (2) 34
 
3.8%

위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct78
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.289149
Minimum33.226827
Maximum33.470255
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size834.0 B
2023-12-13T00:04:48.438130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.226827
5-th percentile33.238996
Q133.245878
median33.266019
Q333.302927
95-th percentile33.440144
Maximum33.470255
Range0.24342754
Interquartile range (IQR)0.05704956

Descriptive statistics

Standard deviation0.062435693
Coefficient of variation (CV)0.0018755569
Kurtosis1.4892265
Mean33.289149
Median Absolute Deviation (MAD)0.02303709
Skewness1.5529281
Sum2596.5536
Variance0.0038982157
MonotonicityNot monotonic
2023-12-13T00:04:48.606671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.29049621 1
 
1.3%
33.25144872 1
 
1.3%
33.27613834 1
 
1.3%
33.25167707 1
 
1.3%
33.24163585 1
 
1.3%
33.24625437 1
 
1.3%
33.25513164 1
 
1.3%
33.25262413 1
 
1.3%
33.26024233 1
 
1.3%
33.25248282 1
 
1.3%
Other values (68) 68
87.2%
ValueCountFrequency (%)
33.226827 1
1.3%
33.22928552 1
1.3%
33.23554304 1
1.3%
33.2372019 1
1.3%
33.23931294 1
1.3%
33.23940279 1
1.3%
33.23945689 1
1.3%
33.23949263 1
1.3%
33.23993738 1
1.3%
33.24108531 1
1.3%
ValueCountFrequency (%)
33.47025454 1
1.3%
33.46758373 1
1.3%
33.4441104 1
1.3%
33.4433554 1
1.3%
33.43957712 1
1.3%
33.43858184 1
1.3%
33.40508271 1
1.3%
33.401368 1
1.3%
33.38981513 1
1.3%
33.37952123 1
1.3%

경도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct78
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.58136
Minimum126.29584
Maximum126.92043
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size834.0 B
2023-12-13T00:04:48.794126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.29584
5-th percentile126.30364
Q1126.42163
median126.59532
Q3126.72342
95-th percentile126.90094
Maximum126.92043
Range0.6245852
Interquartile range (IQR)0.301794

Descriptive statistics

Standard deviation0.19487855
Coefficient of variation (CV)0.0015395517
Kurtosis-1.1206095
Mean126.58136
Median Absolute Deviation (MAD)0.14901625
Skewness0.061551569
Sum9873.3463
Variance0.037977649
MonotonicityNot monotonic
2023-12-13T00:04:48.970995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.7244377 1
 
1.3%
126.4319036 1
 
1.3%
126.6066599 1
 
1.3%
126.6225633 1
 
1.3%
126.6041435 1
 
1.3%
126.5860314 1
 
1.3%
126.4915105 1
 
1.3%
126.4550864 1
 
1.3%
126.6095179 1
 
1.3%
126.6171799 1
 
1.3%
Other values (68) 68
87.2%
ValueCountFrequency (%)
126.2958405 1
1.3%
126.2971002 1
1.3%
126.3032646 1
1.3%
126.3035399 1
1.3%
126.3036537 1
1.3%
126.3037314 1
1.3%
126.3039016 1
1.3%
126.3046314 1
1.3%
126.3059954 1
1.3%
126.3085163 1
1.3%
ValueCountFrequency (%)
126.9204257 1
1.3%
126.9178471 1
1.3%
126.9133848 1
1.3%
126.9065668 1
1.3%
126.8999488 1
1.3%
126.8992145 1
1.3%
126.8640016 1
1.3%
126.8615474 1
1.3%
126.8466141 1
1.3%
126.8382797 1
1.3%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size756.0 B
2023-10-04
78 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-10-04
2nd row2023-10-04
3rd row2023-10-04
4th row2023-10-04
5th row2023-10-04

Common Values

ValueCountFrequency (%)
2023-10-04 78
100.0%

Length

2023-12-13T00:04:49.108910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:04:49.206097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-10-04 78
100.0%

Interactions

2023-12-13T00:04:45.377175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:04:44.523309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:04:44.782541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:04:45.493480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:04:44.621601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:04:45.167642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:04:45.586067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:04:44.698198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:04:45.258877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:04:49.286974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상호명소재지객실수연락처위도경도
상호명1.0001.0001.0001.0001.0001.000
소재지1.0001.0001.0001.0001.0001.000
객실수1.0001.0001.0001.0000.3820.335
연락처1.0001.0001.0001.0001.0001.000
위도1.0001.0000.3821.0001.0000.842
경도1.0001.0000.3351.0000.8421.000
2023-12-13T00:04:49.421880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
객실수위도경도
객실수1.000-0.261-0.323
위도-0.2611.0000.815
경도-0.3230.8151.000

Missing values

2023-12-13T00:04:45.711298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:04:45.816913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

상호명소재지객실수연락처위도경도데이터기준일
0솔바람풍경소리 휴양펜션제주특별자치도 서귀포시 남원읍 태수로143번길 132-3710064-764-600233.290496126.7244382023-10-04
1제주목화제주특별자치도 서귀포시 남원읍 태위로 48510064-764-794233.275784126.6994132023-10-04
2예이츠산장제주특별자치도 서귀포시 남원읍 516로 91810064-767-374633.325724126.6010472023-10-04
3포유펜션제주특별자치도 서귀포시 남원읍 서의로 40-67064-764-277733.296078126.7109782023-10-04
4수망관광 휴양펜션제주특별자치도 서귀포시 남원읍 서성로 986-247070-4151-522133.336503126.6983012023-10-04
5소랑호젠 펜션제주특별자치도 서귀포시 남원읍 태위로 54510064-764-801633.275811126.7052372023-10-04
6리틀램 스테이 휴양펜션제주특별자치도 서귀포시 남원읍 태위로894번길 365064-764-700433.281792126.7413792023-10-04
7큰엉해올레 펜션제주특별자치도 서귀포시 남원읍 태위로510번길 31-89064-764-745633.27182126.7000482023-10-04
8제주펜션 모이헤이제주특별자치도 서귀포시 남원읍 신례로379번길 36-2810064-767-100533.293128126.6210392023-10-04
9제주남원숙소 르페도라 감성펜션제주특별자치도 서귀포시 남원읍 신례중앙로 610064-732-700233.289637126.6292842023-10-04
상호명소재지객실수연락처위도경도데이터기준일
68오션브릭풀빌라 휴양펜션제주특별자치도 서귀포시 안덕면 산방로 75-310064-792-410033.242025126.3249682023-10-04
69하이재 휴양펜션제주특별자치도 서귀포시 성산읍 신풍하동로 133<NA>33.362023126.838282023-10-04
70더라온 휴양펜션제주특별자치도 서귀포시 표선면 번영로 2587-4360507-1359-117833.405083126.7858052023-10-04
71제주 아이니 휴양펜션제주특별자치도 서귀포시 남원읍 태위로894번길 20-3040507-1409-420233.283392126.7399822023-10-04
72C&p 리조트 휴양펜션제주특별자치도 서귀포시 성산읍 중산간동로 4328-6310<NA>33.389815126.8308432023-10-04
73상예 그리너리 빌리지 휴양펜션제주특별자치도 서귀포시 소보리당로 200100507-1375-677433.261539126.3841662023-10-04
74제주 은빌레 휴양펜션제주특별자치도 서귀포시 남원읍 한신로 247-3100507-1415-222333.311741126.7168332023-10-04
75쎄로 델 쏠제주특별자치도 서귀포시 안덕면 일주서로1488번길 2610064-792-119933.262174126.3573622023-10-04
76바다연제주특별자치도 서귀포시 표선면 민속해안로 22 247064-787-881533.30521126.8062112023-10-04
77강정동 씨앤알 휴양펜션제주특별자치도 서귀포시 말질로 3225064-739-996733.226827126.4714952023-10-04