Overview

Dataset statistics

Number of variables8
Number of observations42
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.8 KiB
Average record size in memory69.1 B

Variable types

Text3
Numeric2
Categorical1
DateTime2

Dataset

Description제주특별자치도에서 지정하는 투자진흥지구지정 관련 지구명, 위치, 면적 (천㎡), 투자계획 (억원), 사업시행자 등 정보를 제공합니다.
URLhttps://www.data.go.kr/data/3084245/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
면적(천제곱미터) is highly overall correlated with 투자계획(억원)High correlation
투자계획(억원) is highly overall correlated with 면적(천제곱미터)High correlation
지구명 has unique valuesUnique
위치 has unique valuesUnique

Reproduction

Analysis started2023-12-12 00:37:40.191307
Analysis finished2023-12-12 00:37:41.081547
Duration0.89 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지구명
Text

UNIQUE 

Distinct42
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size468.0 B
2023-12-12T09:37:41.231595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length16
Mean length10.166667
Min length4

Characters and Unicode

Total characters427
Distinct characters178
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)100.0%

Sample

1st row그랜드메르 관광호텔
2nd row난타파크 관광호텔
3rd row더 베니스 랜드
4th row라온더마파크
5th row라온프라이빗타운
ValueCountFrequency (%)
호텔 4
 
6.1%
관광호텔 3
 
4.5%
제주 2
 
3.0%
cliff 1
 
1.5%
판타스틱트릭아트뮤지엄(박물관은살아있다 1
 
1.5%
한남녹차가공공장 1
 
1.5%
해비치 1
 
1.5%
헬로키티 1
 
1.5%
아일랜드 1
 
1.5%
레오 1
 
1.5%
Other values (50) 50
75.8%
2023-12-12T09:37:41.595150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
24
 
5.6%
13
 
3.0%
13
 
3.0%
12
 
2.8%
11
 
2.6%
10
 
2.3%
9
 
2.1%
9
 
2.1%
) 9
 
2.1%
9
 
2.1%
Other values (168) 308
72.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 347
81.3%
Space Separator 24
 
5.6%
Uppercase Letter 14
 
3.3%
Lowercase Letter 13
 
3.0%
Close Punctuation 9
 
2.1%
Open Punctuation 9
 
2.1%
Decimal Number 7
 
1.6%
Other Punctuation 4
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
13
 
3.7%
13
 
3.7%
12
 
3.5%
11
 
3.2%
10
 
2.9%
9
 
2.6%
9
 
2.6%
9
 
2.6%
8
 
2.3%
8
 
2.3%
Other values (136) 245
70.6%
Uppercase Letter
ValueCountFrequency (%)
H 2
14.3%
E 2
14.3%
N 1
7.1%
L 1
7.1%
B 1
7.1%
A 1
7.1%
G 1
7.1%
R 1
7.1%
T 1
7.1%
W 1
7.1%
Other values (2) 2
14.3%
Lowercase Letter
ValueCountFrequency (%)
e 3
23.1%
f 2
15.4%
l 2
15.4%
h 1
 
7.7%
u 1
 
7.7%
j 1
 
7.7%
t 1
 
7.7%
o 1
 
7.7%
i 1
 
7.7%
Decimal Number
ValueCountFrequency (%)
2 1
14.3%
3 1
14.3%
4 1
14.3%
1 1
14.3%
8 1
14.3%
9 1
14.3%
5 1
14.3%
Space Separator
ValueCountFrequency (%)
24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Other Punctuation
ValueCountFrequency (%)
. 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 347
81.3%
Common 53
 
12.4%
Latin 27
 
6.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
13
 
3.7%
13
 
3.7%
12
 
3.5%
11
 
3.2%
10
 
2.9%
9
 
2.6%
9
 
2.6%
9
 
2.6%
8
 
2.3%
8
 
2.3%
Other values (136) 245
70.6%
Latin
ValueCountFrequency (%)
e 3
 
11.1%
H 2
 
7.4%
f 2
 
7.4%
l 2
 
7.4%
E 2
 
7.4%
N 1
 
3.7%
L 1
 
3.7%
B 1
 
3.7%
A 1
 
3.7%
G 1
 
3.7%
Other values (11) 11
40.7%
Common
ValueCountFrequency (%)
24
45.3%
) 9
 
17.0%
( 9
 
17.0%
. 4
 
7.5%
2 1
 
1.9%
3 1
 
1.9%
4 1
 
1.9%
1 1
 
1.9%
8 1
 
1.9%
9 1
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 347
81.3%
ASCII 80
 
18.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
24
30.0%
) 9
 
11.2%
( 9
 
11.2%
. 4
 
5.0%
e 3
 
3.8%
H 2
 
2.5%
f 2
 
2.5%
l 2
 
2.5%
E 2
 
2.5%
N 1
 
1.2%
Other values (22) 22
27.5%
Hangul
ValueCountFrequency (%)
13
 
3.7%
13
 
3.7%
12
 
3.5%
11
 
3.2%
10
 
2.9%
9
 
2.6%
9
 
2.6%
9
 
2.6%
8
 
2.3%
8
 
2.3%
Other values (136) 245
70.6%

위치
Text

UNIQUE 

Distinct42
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size468.0 B
2023-12-12T09:37:41.843659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length27
Mean length25.666667
Min length19

Characters and Unicode

Total characters1078
Distinct characters87
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

Unique42 ?
Unique (%)100.0%

Sample

1st row제주특별자치도 서귀포시 하예동 450-1 일원
2nd row제주특별자치도 제주시 오등동 10-1 일원
3rd row제주특별자치도 서귀포시 성산읍 난산리 2570 일원
4th row제주특별자치도 제주시 한림읍 월림리 2365 일원
5th row제주특별자치도 제주시 한림읍 협재리 산149-6 일원
ValueCountFrequency (%)
제주특별자치도 42
18.6%
일원 34
 
15.0%
서귀포시 24
 
10.6%
제주시 18
 
8.0%
애월읍 4
 
1.8%
중문동 4
 
1.8%
한림읍 4
 
1.8%
안덕면 4
 
1.8%
연동 3
 
1.3%
성산읍 3
 
1.3%
Other values (78) 86
38.1%
2023-12-12T09:37:42.187486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
184
 
17.1%
60
 
5.6%
60
 
5.6%
44
 
4.1%
42
 
3.9%
42
 
3.9%
42
 
3.9%
42
 
3.9%
42
 
3.9%
37
 
3.4%
Other values (77) 483
44.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 709
65.8%
Space Separator 184
 
17.1%
Decimal Number 163
 
15.1%
Dash Punctuation 22
 
2.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
60
 
8.5%
60
 
8.5%
44
 
6.2%
42
 
5.9%
42
 
5.9%
42
 
5.9%
42
 
5.9%
42
 
5.9%
37
 
5.2%
36
 
5.1%
Other values (65) 262
37.0%
Decimal Number
ValueCountFrequency (%)
2 34
20.9%
1 31
19.0%
0 19
11.7%
3 19
11.7%
5 13
 
8.0%
7 13
 
8.0%
4 12
 
7.4%
6 10
 
6.1%
9 7
 
4.3%
8 5
 
3.1%
Space Separator
ValueCountFrequency (%)
184
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 709
65.8%
Common 369
34.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
60
 
8.5%
60
 
8.5%
44
 
6.2%
42
 
5.9%
42
 
5.9%
42
 
5.9%
42
 
5.9%
42
 
5.9%
37
 
5.2%
36
 
5.1%
Other values (65) 262
37.0%
Common
ValueCountFrequency (%)
184
49.9%
2 34
 
9.2%
1 31
 
8.4%
- 22
 
6.0%
0 19
 
5.1%
3 19
 
5.1%
5 13
 
3.5%
7 13
 
3.5%
4 12
 
3.3%
6 10
 
2.7%
Other values (2) 12
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 709
65.8%
ASCII 369
34.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
184
49.9%
2 34
 
9.2%
1 31
 
8.4%
- 22
 
6.0%
0 19
 
5.1%
3 19
 
5.1%
5 13
 
3.5%
7 13
 
3.5%
4 12
 
3.3%
6 10
 
2.7%
Other values (2) 12
 
3.3%
Hangul
ValueCountFrequency (%)
60
 
8.5%
60
 
8.5%
44
 
6.2%
42
 
5.9%
42
 
5.9%
42
 
5.9%
42
 
5.9%
42
 
5.9%
37
 
5.2%
36
 
5.1%
Other values (65) 262
37.0%

면적(천제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct32
Distinct (%)76.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean285.66667
Minimum1
Maximum3791
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-12T09:37:42.334291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.05
Q18
median30
Q398.5
95-th percentile1418.55
Maximum3791
Range3790
Interquartile range (IQR)90.5

Descriptive statistics

Standard deviation807.45344
Coefficient of variation (CV)2.8265581
Kurtosis14.230574
Mean285.66667
Median Absolute Deviation (MAD)26
Skewness3.8025418
Sum11998
Variance651981.06
MonotonicityNot monotonic
2023-12-12T09:37:42.450927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
30 5
 
11.9%
1 3
 
7.1%
8 2
 
4.8%
6 2
 
4.8%
2 2
 
4.8%
4 2
 
4.8%
89 1
 
2.4%
132 1
 
2.4%
1452 1
 
2.4%
26 1
 
2.4%
Other values (22) 22
52.4%
ValueCountFrequency (%)
1 3
7.1%
2 2
4.8%
3 1
 
2.4%
4 2
4.8%
6 2
4.8%
8 2
4.8%
10 1
 
2.4%
18 1
 
2.4%
19 1
 
2.4%
20 1
 
2.4%
ValueCountFrequency (%)
3791 1
2.4%
3523 1
2.4%
1452 1
2.4%
783 1
2.4%
632 1
2.4%
294 1
2.4%
213 1
2.4%
203 1
2.4%
140 1
2.4%
132 1
2.4%

투자계획(억원)
Real number (ℝ)

HIGH CORRELATION 

Distinct41
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2148.2381
Minimum82
Maximum24333
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-12T09:37:42.580716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum82
5-th percentile99.15
Q1138.5
median370
Q31052.25
95-th percentile13366.6
Maximum24333
Range24251
Interquartile range (IQR)913.75

Descriptive statistics

Standard deviation5144.5902
Coefficient of variation (CV)2.3947952
Kurtosis10.790098
Mean2148.2381
Median Absolute Deviation (MAD)238
Skewness3.304236
Sum90226
Variance26466808
MonotonicityNot monotonic
2023-12-12T09:37:42.707872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
428 2
 
4.8%
135 1
 
2.4%
3870 1
 
2.4%
99 1
 
2.4%
149 1
 
2.4%
340 1
 
2.4%
164 1
 
2.4%
599 1
 
2.4%
400 1
 
2.4%
435 1
 
2.4%
Other values (31) 31
73.8%
ValueCountFrequency (%)
82 1
2.4%
93 1
2.4%
99 1
2.4%
102 1
2.4%
105 1
2.4%
110 1
2.4%
112 1
2.4%
121 1
2.4%
123 1
2.4%
129 1
2.4%
ValueCountFrequency (%)
24333 1
2.4%
19256 1
2.4%
13587 1
2.4%
9179 1
2.4%
4050 1
2.4%
3870 1
2.4%
2293 1
2.4%
1749 1
2.4%
1226 1
2.4%
1207 1
2.4%
Distinct36
Distinct (%)85.7%
Missing0
Missing (%)0.0%
Memory size468.0 B
2023-12-12T09:37:42.908924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length5.5952381
Min length2

Characters and Unicode

Total characters235
Distinct characters112
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)78.6%

Sample

1st row리켄코리아㈜
2nd row㈜피엠씨프러덕션
3rd row개인
4th row라온랜드㈜
5th row라온레저개발㈜
ValueCountFrequency (%)
㈜부영주택 4
 
9.5%
jdc 3
 
7.1%
개인 2
 
4.8%
㈜휘닉스중앙제주 1
 
2.4%
㈜리만코리아 1
 
2.4%
삼매봉개발㈜ 1
 
2.4%
㈜휘찬 1
 
2.4%
㈜한국폴로컨트리클럽 1
 
2.4%
제주뮤지엄컴플렉스㈜ 1
 
2.4%
㈜트릭아트뮤지엄 1
 
2.4%
Other values (26) 26
61.9%
2023-12-12T09:37:43.301074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
33
 
14.0%
8
 
3.4%
8
 
3.4%
6
 
2.6%
6
 
2.6%
5
 
2.1%
4
 
1.7%
4
 
1.7%
4
 
1.7%
4
 
1.7%
Other values (102) 153
65.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 191
81.3%
Other Symbol 33
 
14.0%
Uppercase Letter 9
 
3.8%
Close Punctuation 1
 
0.4%
Open Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
8
 
4.2%
8
 
4.2%
6
 
3.1%
6
 
3.1%
5
 
2.6%
4
 
2.1%
4
 
2.1%
4
 
2.1%
4
 
2.1%
4
 
2.1%
Other values (96) 138
72.3%
Uppercase Letter
ValueCountFrequency (%)
J 3
33.3%
D 3
33.3%
C 3
33.3%
Other Symbol
ValueCountFrequency (%)
33
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 224
95.3%
Latin 9
 
3.8%
Common 2
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
33
 
14.7%
8
 
3.6%
8
 
3.6%
6
 
2.7%
6
 
2.7%
5
 
2.2%
4
 
1.8%
4
 
1.8%
4
 
1.8%
4
 
1.8%
Other values (97) 142
63.4%
Latin
ValueCountFrequency (%)
J 3
33.3%
D 3
33.3%
C 3
33.3%
Common
ValueCountFrequency (%)
) 1
50.0%
( 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 191
81.3%
None 33
 
14.0%
ASCII 11
 
4.7%

Most frequent character per block

None
ValueCountFrequency (%)
33
100.0%
Hangul
ValueCountFrequency (%)
8
 
4.2%
8
 
4.2%
6
 
3.1%
6
 
3.1%
5
 
2.6%
4
 
2.1%
4
 
2.1%
4
 
2.1%
4
 
2.1%
4
 
2.1%
Other values (96) 138
72.3%
ASCII
ValueCountFrequency (%)
J 3
27.3%
D 3
27.3%
C 3
27.3%
) 1
 
9.1%
( 1
 
9.1%

업종
Categorical

Distinct10
Distinct (%)23.8%
Missing0
Missing (%)0.0%
Memory size468.0 B
전문휴양업
14 
관광호텔업
13 
연수원
종합휴양업
문화산업
Other values (5)

Length

Max length8
Median length5
Mean length4.9285714
Min length3

Unique

Unique3 ?
Unique (%)7.1%

Sample

1st row관광호텔업
2nd row관광호텔업
3rd row전문휴양업
4th row전문휴양업
5th row전문휴양업

Common Values

ValueCountFrequency (%)
전문휴양업 14
33.3%
관광호텔업 13
31.0%
연수원 3
 
7.1%
종합휴양업 3
 
7.1%
문화산업 2
 
4.8%
식료품제조업 2
 
4.8%
의료기관 2
 
4.8%
청소년수련시설업 1
 
2.4%
종합유원 시설업 1
 
2.4%
국제학교 1
 
2.4%

Length

2023-12-12T09:37:43.439033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:37:43.576512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전문휴양업 14
32.6%
관광호텔업 13
30.2%
연수원 3
 
7.0%
종합휴양업 3
 
7.0%
문화산업 2
 
4.7%
식료품제조업 2
 
4.7%
의료기관 2
 
4.7%
청소년수련시설업 1
 
2.3%
종합유원 1
 
2.3%
시설업 1
 
2.3%
Distinct29
Distinct (%)69.0%
Missing0
Missing (%)0.0%
Memory size468.0 B
Minimum2007-06-20 00:00:00
Maximum2022-12-30 00:00:00
2023-12-12T09:37:43.744541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:37:43.940091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size468.0 B
Minimum2023-08-18 00:00:00
Maximum2023-08-18 00:00:00
2023-12-12T09:37:44.069479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:37:44.186759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T09:37:40.743625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:37:40.579189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:37:40.822036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:37:40.663008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T09:37:44.276930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지구명위치면적(천제곱미터)투자계획(억원)사업시행자업종지정일
지구명1.0001.0001.0001.0001.0001.0001.000
위치1.0001.0001.0001.0001.0001.0001.000
면적(천제곱미터)1.0001.0001.0000.9020.0000.7510.875
투자계획(억원)1.0001.0000.9021.0000.0000.6940.772
사업시행자1.0001.0000.0000.0001.0000.0000.793
업종1.0001.0000.7510.6940.0001.0000.806
지정일1.0001.0000.8750.7720.7930.8061.000
2023-12-12T09:37:44.429851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
면적(천제곱미터)투자계획(억원)업종
면적(천제곱미터)1.0000.7410.373
투자계획(억원)0.7411.0000.426
업종0.3730.4261.000

Missing values

2023-12-12T09:37:40.916559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:37:41.038824image/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

지구명위치면적(천제곱미터)투자계획(억원)사업시행자업종지정일데이터기준일자
0그랜드메르 관광호텔제주특별자치도 서귀포시 하예동 450-1 일원8135리켄코리아㈜관광호텔업2016-01-222023-08-18
1난타파크 관광호텔제주특별자치도 제주시 오등동 10-1 일원19427㈜피엠씨프러덕션관광호텔업2016-01-222023-08-18
2더 베니스 랜드제주특별자치도 서귀포시 성산읍 난산리 2570 일원30200개인전문휴양업2014-03-072023-08-18
3라온더마파크제주특별자치도 제주시 한림읍 월림리 2365 일원203239라온랜드㈜전문휴양업2009-03-182023-08-18
4라온프라이빗타운제주특별자치도 제주시 한림읍 협재리 산149-6 일원7834050라온레저개발㈜전문휴양업2011-04-112023-08-18
5마레보리조트제주특별자치도 제주시 애월읍 고내리 41 일원30205㈜마레보전문휴양업2014-01-282023-08-18
6무민랜드제주특별자치도 서귀포시 안덕면 상천리 470-6 일원6102㈜제이콥문화산업2020-08-182023-08-18
7미스터밀크 유가공공장제주특별자치도 제주시 한림읍 금악리 1720-3 일원382㈜미스터밀크식료품제조업2022-02-252023-08-18
8부영리조트제주특별자치도 서귀포시 중문동 2700-3321203㈜부영주택전문휴양업2012-12-312023-08-18
9부영청소년수련원제주특별자치도 서귀포시 중문동 221820123㈜부영주택청소년수련시설업2013-02-222023-08-18
지구명위치면적(천제곱미터)투자계획(억원)사업시행자업종지정일데이터기준일자
32신화역사공원제주특별자치도 서귀포시 안덕면 서광리 산 35-7 일원352324333JDC종합휴양업2009-12-302023-08-18
33제주뮤지엄컴플렉스 (그리스신화박물관)제주특별자치도 제주시 한림읍 금악리 산30-1259228제주뮤지엄컴플렉스㈜전문휴양업2012-07-042023-08-18
34제주영어교육도시제주특별자치도 서귀포시 대정읍 구억리 산1 일원379119256JDC국제학교2012-07-042023-08-18
35제주폴로승마리조트제주특별자치도 제주시 구좌읍 행원리 3260 일원213593㈜한국폴로컨트리클럽전문휴양업2009-07-012023-08-18
36제주헬스케어타운제주특별자치도 서귀포시 동홍동 2032 일원145213587JDC종합휴양업2010-11-032023-08-18
37한라힐링파크제주특별자치도 서귀포시 안덕면 상천리 산 70 일원132600㈜휘찬전문휴양업2010-03-102023-08-18
38삼매봉밸리유원지(덴앤델리조트)제주특별자치도 서귀포시 호근동 399 일원892293삼매봉개발㈜전문휴양업2011-04-112023-08-18
39제주 리만 빌리지제주특별자치도 서귀포시 남원읍 위미리 4159 일원6121㈜리만코리아연수원2022-12-302023-08-18
40제주 한남녹차가공공장제주특별자치도 서귀포시 남원읍 한남리 1443 일원23428㈜오설록농장식료품제조업2022-12-302023-08-18
41부영호텔2.3.4.5제주특별자치도 서귀포시 중문동 2725-1 일원2949179㈜부영주택관광호텔업2013-02-222023-08-18