Overview

Dataset statistics

Number of variables7
Number of observations1529
Missing cells507
Missing cells (%)4.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory86.7 KiB
Average record size in memory58.1 B

Variable types

Categorical1
Text3
Numeric2
DateTime1

Dataset

Description제주특별자치도 서귀포시 내 공중위생업소(숙박업, 목욕장업, 이용업, 세탁업 등)의 업종명,업소명,소재지,전화번호 정보를 제공합니다.
Author제주특별자치도 서귀포시
URLhttps://www.data.go.kr/data/3083281/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
위도 is highly overall correlated with 경도High correlation
경도 is highly overall correlated with 위도High correlation
전화번호 has 507 (33.2%) missing valuesMissing

Reproduction

Analysis started2023-12-12 23:12:14.377197
Analysis finished2023-12-12 23:12:15.405593
Duration1.03 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

Distinct7
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size12.1 KiB
미용업
684 
숙박업(일반)
304 
숙박업(생활)
280 
세탁업
105 
이용업
 
66
Other values (2)
90 

Length

Max length7
Median length3
Mean length4.647482
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row숙박업(일반)
2nd row숙박업(일반)
3rd row숙박업(일반)
4th row숙박업(일반)
5th row숙박업(일반)

Common Values

ValueCountFrequency (%)
미용업 684
44.7%
숙박업(일반) 304
19.9%
숙박업(생활) 280
18.3%
세탁업 105
 
6.9%
이용업 66
 
4.3%
목욕장업 59
 
3.9%
건물위생관리업 31
 
2.0%

Length

2023-12-13T08:12:15.486738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:12:15.599411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미용업 684
44.7%
숙박업(일반 304
19.9%
숙박업(생활 280
18.3%
세탁업 105
 
6.9%
이용업 66
 
4.3%
목욕장업 59
 
3.9%
건물위생관리업 31
 
2.0%

업소명
Text

Distinct1523
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size12.1 KiB
2023-12-13T08:12:16.125334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length26
Mean length6.4617397
Min length1

Characters and Unicode

Total characters9880
Distinct characters626
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1517 ?
Unique (%)99.2%

Sample

1st row정방게스트하우스
2nd row천제모텔
3rd row강남여인숙
4th row남강여관
5th row영원여인숙
ValueCountFrequency (%)
제주 10
 
0.6%
주식회사 9
 
0.5%
휴양펜션 7
 
0.4%
호텔 6
 
0.4%
서귀포 5
 
0.3%
호스텔 5
 
0.3%
beauty 4
 
0.2%
휴양콘도미니엄 4
 
0.2%
신신호텔 4
 
0.2%
애 3
 
0.2%
Other values (1608) 1648
96.7%
2023-12-13T08:12:16.519965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 320
 
3.2%
이 290
 
2.9%
어 229
 
2.3%
리 216
 
2.2%
텔 212
 
2.1%
미 208
 
2.1%
호 201
 
2.0%
용 185
 
1.9%
헤 177
 
1.8%
176
 
1.8%
Other values (616) 7666
77.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8927
90.4%
Lowercase Letter 253
 
2.6%
Uppercase Letter 227
 
2.3%
Space Separator 176
 
1.8%
Decimal Number 93
 
0.9%
Close Punctuation 89
 
0.9%
Open Punctuation 87
 
0.9%
Other Punctuation 22
 
0.2%
Dash Punctuation 5
 
0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 320
 
3.6%
이 290
 
3.2%
어 229
 
2.6%
리 216
 
2.4%
텔 212
 
2.4%
미 208
 
2.3%
호 201
 
2.3%
용 185
 
2.1%
헤 177
 
2.0%
제 168
 
1.9%
Other values (550) 6721
75.3%
Uppercase Letter
ValueCountFrequency (%)
A 31
13.7%
S 20
 
8.8%
J 15
 
6.6%
O 14
 
6.2%
E 14
 
6.2%
H 12
 
5.3%
P 12
 
5.3%
U 12
 
5.3%
T 11
 
4.8%
N 10
 
4.4%
Other values (14) 76
33.5%
Lowercase Letter
ValueCountFrequency (%)
a 33
13.0%
e 31
12.3%
l 23
 
9.1%
s 18
 
7.1%
i 17
 
6.7%
t 15
 
5.9%
o 14
 
5.5%
y 13
 
5.1%
n 13
 
5.1%
r 11
 
4.3%
Other values (12) 65
25.7%
Decimal Number
ValueCountFrequency (%)
2 23
24.7%
1 16
17.2%
0 13
14.0%
4 8
 
8.6%
3 8
 
8.6%
8 6
 
6.5%
9 6
 
6.5%
7 5
 
5.4%
6 4
 
4.3%
5 4
 
4.3%
Other Punctuation
ValueCountFrequency (%)
& 12
54.5%
. 3
 
13.6%
' 3
 
13.6%
: 2
 
9.1%
# 2
 
9.1%
Space Separator
ValueCountFrequency (%)
176
100.0%
Close Punctuation
ValueCountFrequency (%)
) 89
100.0%
Open Punctuation
ValueCountFrequency (%)
( 87
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8926
90.3%
Latin 481
 
4.9%
Common 472
 
4.8%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 320
 
3.6%
이 290
 
3.2%
어 229
 
2.6%
리 216
 
2.4%
텔 212
 
2.4%
미 208
 
2.3%
호 201
 
2.3%
용 185
 
2.1%
헤 177
 
2.0%
제 168
 
1.9%
Other values (549) 6720
75.3%
Latin
ValueCountFrequency (%)
a 33
 
6.9%
e 31
 
6.4%
A 31
 
6.4%
l 23
 
4.8%
S 20
 
4.2%
s 18
 
3.7%
i 17
 
3.5%
t 15
 
3.1%
J 15
 
3.1%
O 14
 
2.9%
Other values (37) 264
54.9%
Common
ValueCountFrequency (%)
176
37.3%
) 89
18.9%
( 87
18.4%
2 23
 
4.9%
1 16
 
3.4%
0 13
 
2.8%
& 12
 
2.5%
4 8
 
1.7%
3 8
 
1.7%
8 6
 
1.3%
Other values (9) 34
 
7.2%
Han
ValueCountFrequency (%)
水 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8926
90.3%
ASCII 952
 
9.6%
CJK 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 320
 
3.6%
이 290
 
3.2%
어 229
 
2.6%
리 216
 
2.4%
텔 212
 
2.4%
미 208
 
2.3%
호 201
 
2.3%
용 185
 
2.1%
헤 177
 
2.0%
제 168
 
1.9%
Other values (549) 6720
75.3%
ASCII
ValueCountFrequency (%)
176
18.5%
) 89
 
9.3%
( 87
 
9.1%
a 33
 
3.5%
e 31
 
3.3%
A 31
 
3.3%
2 23
 
2.4%
l 23
 
2.4%
S 20
 
2.1%
s 18
 
1.9%
Other values (55) 421
44.2%
CJK
ValueCountFrequency (%)
水 1
100.0%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
100.0%

소재지
Text

Distinct1440
Distinct (%)94.2%
Missing0
Missing (%)0.0%
Memory size12.1 KiB
2023-12-13T08:12:16.839491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length49
Mean length29.28777
Min length22

Characters and Unicode

Total characters44781
Distinct characters312
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1366 ?
Unique (%)89.3%

Sample

1st row제주특별자치도 서귀포시 솔동산로21번길 16-1 (서귀동)
2nd row제주특별자치도 서귀포시 천제연로 189 (중문동)
3rd row제주특별자치도 서귀포시 서문로38번길 6 (서귀동)
4th row제주특별자치도 서귀포시 대정읍 최남단해안로 5
5th row제주특별자치도 서귀포시 태평로431번길 16 (서귀동)
ValueCountFrequency (%)
제주특별자치도 1529
 
18.2%
서귀포시 1529
 
18.2%
서귀동 327
 
3.9%
1층 209
 
2.5%
대정읍 168
 
2.0%
성산읍 148
 
1.8%
동홍동 132
 
1.6%
2층 120
 
1.4%
안덕면 116
 
1.4%
표선면 90
 
1.1%
Other values (1282) 4013
47.9%
2023-12-13T08:12:17.293137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6859
 
15.3%
서 2164
 
4.8%
귀 1875
 
4.2%
주 1614
 
3.6%
제 1600
 
3.6%
포 1578
 
3.5%
도 1567
 
3.5%
시 1562
 
3.5%
치 1537
 
3.4%
자 1532
 
3.4%
Other values (302) 22893
51.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 29698
66.3%
Space Separator 6859
 
15.3%
Decimal Number 5937
 
13.3%
Close Punctuation 944
 
2.1%
Open Punctuation 944
 
2.1%
Dash Punctuation 342
 
0.8%
Uppercase Letter 51
 
0.1%
Math Symbol 4
 
< 0.1%
Letter Number 1
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 2164
 
7.3%
귀 1875
 
6.3%
주 1614
 
5.4%
제 1600
 
5.4%
포 1578
 
5.3%
도 1567
 
5.3%
시 1562
 
5.3%
치 1537
 
5.2%
자 1532
 
5.2%
로 1531
 
5.2%
Other values (272) 13138
44.2%
Uppercase Letter
ValueCountFrequency (%)
B 15
29.4%
A 10
19.6%
C 6
 
11.8%
L 4
 
7.8%
E 4
 
7.8%
F 2
 
3.9%
S 2
 
3.9%
V 2
 
3.9%
I 2
 
3.9%
D 1
 
2.0%
Other values (3) 3
 
5.9%
Decimal Number
ValueCountFrequency (%)
1 1352
22.8%
2 996
16.8%
3 634
10.7%
4 502
 
8.5%
5 493
 
8.3%
0 423
 
7.1%
7 421
 
7.1%
6 405
 
6.8%
9 356
 
6.0%
8 355
 
6.0%
Space Separator
ValueCountFrequency (%)
6859
100.0%
Close Punctuation
ValueCountFrequency (%)
) 944
100.0%
Open Punctuation
ValueCountFrequency (%)
( 944
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 342
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 29698
66.3%
Common 15031
33.6%
Latin 52
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 2164
 
7.3%
귀 1875
 
6.3%
주 1614
 
5.4%
제 1600
 
5.4%
포 1578
 
5.3%
도 1567
 
5.3%
시 1562
 
5.3%
치 1537
 
5.2%
자 1532
 
5.2%
로 1531
 
5.2%
Other values (272) 13138
44.2%
Common
ValueCountFrequency (%)
6859
45.6%
1 1352
 
9.0%
2 996
 
6.6%
) 944
 
6.3%
( 944
 
6.3%
3 634
 
4.2%
4 502
 
3.3%
5 493
 
3.3%
0 423
 
2.8%
7 421
 
2.8%
Other values (6) 1463
 
9.7%
Latin
ValueCountFrequency (%)
B 15
28.8%
A 10
19.2%
C 6
 
11.5%
L 4
 
7.7%
E 4
 
7.7%
F 2
 
3.8%
S 2
 
3.8%
V 2
 
3.8%
I 2
 
3.8%
D 1
 
1.9%
Other values (4) 4
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 29698
66.3%
ASCII 15082
33.7%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6859
45.5%
1 1352
 
9.0%
2 996
 
6.6%
) 944
 
6.3%
( 944
 
6.3%
3 634
 
4.2%
4 502
 
3.3%
5 493
 
3.3%
0 423
 
2.8%
7 421
 
2.8%
Other values (19) 1514
 
10.0%
Hangul
ValueCountFrequency (%)
서 2164
 
7.3%
귀 1875
 
6.3%
주 1614
 
5.4%
제 1600
 
5.4%
포 1578
 
5.3%
도 1567
 
5.3%
시 1562
 
5.3%
치 1537
 
5.2%
자 1532
 
5.2%
로 1531
 
5.2%
Other values (272) 13138
44.2%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

전화번호
Text

MISSING 

Distinct983
Distinct (%)96.2%
Missing507
Missing (%)33.2%
Memory size12.1 KiB
2023-12-13T08:12:17.594683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.000978
Min length9

Characters and Unicode

Total characters12265
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

Unique950 ?
Unique (%)93.0%

Sample

1st row064-762-0169
2nd row064-738-1115
3rd row064-762-4075
4th row064-794-2150
5th row064-762-2244
ValueCountFrequency (%)
064-784-7337 4
 
0.4%
064-717-7300 3
 
0.3%
064-792-6678 3
 
0.3%
064-908-6000 3
 
0.3%
064-738-6600 3
 
0.3%
064-738-8383 2
 
0.2%
064-731-5500 2
 
0.2%
064-738-4466 2
 
0.2%
064-780-8221 2
 
0.2%
064-784-0007 2
 
0.2%
Other values (976) 999
97.5%
2023-12-13T08:12:17.952741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 2039
16.6%
0 1827
14.9%
6 1627
13.3%
7 1455
11.9%
4 1453
11.8%
3 977
8.0%
8 730
 
6.0%
2 717
 
5.8%
9 525
 
4.3%
1 495
 
4.0%
Other values (2) 420
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10223
83.4%
Dash Punctuation 2039
 
16.6%
Space Separator 3
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1827
17.9%
6 1627
15.9%
7 1455
14.2%
4 1453
14.2%
3 977
9.6%
8 730
 
7.1%
2 717
 
7.0%
9 525
 
5.1%
1 495
 
4.8%
5 417
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 2039
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12265
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 2039
16.6%
0 1827
14.9%
6 1627
13.3%
7 1455
11.9%
4 1453
11.8%
3 977
8.0%
8 730
 
6.0%
2 717
 
5.8%
9 525
 
4.3%
1 495
 
4.0%
Other values (2) 420
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12265
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 2039
16.6%
0 1827
14.9%
6 1627
13.3%
7 1455
11.9%
4 1453
11.8%
3 977
8.0%
8 730
 
6.0%
2 717
 
5.8%
9 525
 
4.3%
1 495
 
4.0%
Other values (2) 420
 
3.4%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct1322
Distinct (%)86.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.275755
Minimum33.206833
Maximum33.477514
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.6 KiB
2023-12-13T08:12:18.092752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.206833
5-th percentile33.223697
Q133.24706
median33.252323
Q333.275785
95-th percentile33.44817
Maximum33.477514
Range0.27068103
Interquartile range (IQR)0.02872412

Descriptive statistics

Standard deviation0.059459004
Coefficient of variation (CV)0.0017868566
Kurtosis3.4246283
Mean33.275755
Median Absolute Deviation (MAD)0.00842235
Skewness2.1028651
Sum50878.63
Variance0.0035353731
MonotonicityNot monotonic
2023-12-13T08:12:18.214114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.46029772 5
 
0.3%
33.32260009 5
 
0.3%
33.30601155 5
 
0.3%
33.24801841 5
 
0.3%
33.25254887 4
 
0.3%
33.27904494 4
 
0.3%
33.25273777 4
 
0.3%
33.24859947 4
 
0.3%
33.24329739 4
 
0.3%
33.30497288 4
 
0.3%
Other values (1312) 1485
97.1%
ValueCountFrequency (%)
33.2068333 1
0.1%
33.20893755 1
0.1%
33.20923622 1
0.1%
33.21138845 1
0.1%
33.2151115 1
0.1%
33.21649093 1
0.1%
33.21664549 1
0.1%
33.21667149 1
0.1%
33.21773379 1
0.1%
33.2177365 1
0.1%
ValueCountFrequency (%)
33.47751433 1
0.1%
33.47517659 1
0.1%
33.47465805 1
0.1%
33.47445676 1
0.1%
33.47413979 1
0.1%
33.47342588 1
0.1%
33.47318941 1
0.1%
33.47184639 1
0.1%
33.47025034 1
0.1%
33.46911965 1
0.1%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct1322
Distinct (%)86.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.54668
Minimum126.17943
Maximum126.93517
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.6 KiB
2023-12-13T08:12:18.330378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.17943
5-th percentile126.25263
Q1126.42509
median126.56039
Q3126.57669
95-th percentile126.91326
Maximum126.93517
Range0.7557406
Interquartile range (IQR)0.1515991

Descriptive statistics

Standard deviation0.18296746
Coefficient of variation (CV)0.0014458495
Kurtosis-0.2629294
Mean126.54668
Median Absolute Deviation (MAD)0.0749393
Skewness0.31695117
Sum193489.88
Variance0.033477092
MonotonicityNot monotonic
2023-12-13T08:12:18.454481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.9294504 5
 
0.3%
126.8439794 5
 
0.3%
126.7928925 5
 
0.3%
126.4086825 5
 
0.3%
126.5186116 4
 
0.3%
126.2743248 4
 
0.3%
126.5042505 4
 
0.3%
126.4104102 4
 
0.3%
126.5383599 4
 
0.3%
126.3163537 4
 
0.3%
Other values (1312) 1485
97.1%
ValueCountFrequency (%)
126.1794319 1
0.1%
126.1889173 1
0.1%
126.1896633 1
0.1%
126.1896977 1
0.1%
126.1898167 1
0.1%
126.1898404 1
0.1%
126.1899923 1
0.1%
126.1904349 1
0.1%
126.1960071 1
0.1%
126.2029632 1
0.1%
ValueCountFrequency (%)
126.9351725 1
0.1%
126.9351515 1
0.1%
126.9344414 1
0.1%
126.9343356 1
0.1%
126.9339118 1
0.1%
126.9336778 1
0.1%
126.9336233 1
0.1%
126.9335986 1
0.1%
126.9335179 1
0.1%
126.933132 1
0.1%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size12.1 KiB
Minimum2023-10-18 00:00:00
Maximum2023-10-18 00:00:00
2023-12-13T08:12:18.589288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:12:18.685167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T08:12:15.031599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:12:14.877705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:12:15.108210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:12:14.948783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:12:18.749307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명위도경도
업종명1.0000.2010.173
위도0.2011.0000.902
경도0.1730.9021.000
2023-12-13T08:12:18.832974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도업종명
위도1.0000.5860.103
경도0.5861.0000.088
업종명0.1030.0881.000

Missing values

2023-12-13T08:12:15.223683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:12:15.366193image/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

업종명업소명소재지전화번호위도경도데이터기준일자
0숙박업(일반)정방게스트하우스제주특별자치도 서귀포시 솔동산로21번길 16-1 (서귀동)064-762-016933.242494126.5654332023-10-18
1숙박업(일반)천제모텔제주특별자치도 서귀포시 천제연로 189 (중문동)064-738-111533.251893126.4248262023-10-18
2숙박업(일반)강남여인숙제주특별자치도 서귀포시 서문로38번길 6 (서귀동)064-762-407533.250201126.5582582023-10-18
3숙박업(일반)남강여관제주특별자치도 서귀포시 대정읍 최남단해안로 5064-794-215033.220083126.2523672023-10-18
4숙박업(일반)영원여인숙제주특별자치도 서귀포시 태평로431번길 16 (서귀동)064-762-224433.246964126.5660582023-10-18
5숙박업(일반)중앙여인숙제주특별자치도 서귀포시 태평로431번길 12 (서귀동)064-762-891433.246631126.5660632023-10-18
6숙박업(일반)영림여관제주특별자치도 서귀포시 중정로91번길 28 (서귀동)064-732-883333.250323126.5640932023-10-18
7숙박업(일반)노블모텔제주특별자치도 서귀포시 정방로 7-1 (서귀동)064-762-659433.24817126.5681412023-10-18
8숙박업(일반)락희여관제주특별자치도 서귀포시 중정로91번길 11 (서귀동)064-763-331133.249283126.5653552023-10-18
9숙박업(일반)삼화여관제주특별자치도 서귀포시 동문로 54 (서귀동)064-762-716733.249507126.5660492023-10-18
업종명업소명소재지전화번호위도경도데이터기준일자
1519건물위생관리업예스콘인제주특별자치도 서귀포시 안덕면 평화로 1241<NA>33.338341126.3487192023-10-18
1520건물위생관리업원케어제주특별자치도 서귀포시 하신상로 42 1층 (하효동)064-733-211533.26458126.6177052023-10-18
1521건물위생관리업주식회사 제주지키미제주특별자치도 서귀포시 동홍중앙로90번길 4-6 1층 (동홍동)<NA>33.25828126.5723662023-10-18
1522건물위생관리업주식회사 도연제주특별자치도 서귀포시 동홍서로 43 2층 201호 (동홍동)064-739-949633.252639126.5694642023-10-18
1523건물위생관리업빌리스코리아 표선지점제주특별자치도 서귀포시 표선면 일주동로 6347-17 샤인빌 샤인빌리지 4층 11호<NA>33.306012126.7928922023-10-18
1524건물위생관리업이레2호점제주특별자치도 서귀포시 동홍중앙로 92 (동홍동)<NA>33.25882126.5722712023-10-18
1525건물위생관리업주식회사 들불제주특별자치도 서귀포시 대정읍 영어도시로 70 2층1899-762833.278503126.2794342023-10-18
1526건물위생관리업주식회사 빌리스코리아제주특별자치도 서귀포시 천제연로 273-22 제B동 지하1층 B106호 (중문동 중문 스마트타운)064-738-532633.252838126.433932023-10-18
1527건물위생관리업명선제주특별자치도 서귀포시 동문로 9 3층 (서귀동)<NA>33.252054126.562522023-10-18
1528건물위생관리업싹쓸이클린케어제주특별자치도 서귀포시 대정읍 상모로 247 1층064-792-821933.224149126.2626592023-10-18