Overview

Dataset statistics

Number of variables7
Number of observations79
Missing cells11
Missing cells (%)2.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.6 KiB
Average record size in memory59.7 B

Variable types

Numeric2
Categorical1
DateTime1
Text3

Dataset

Description인천광역시 연수구 숙박업소(일반, 생활형)에 대한 현황으로써 숙박업소명, 신고일자, 주소, 전화번호, 객실수 현황의 항목을 제공합니다.
Author인천광역시 연수구
URLhttps://www.data.go.kr/data/15053180/fileData.do

Alerts

연번 is highly overall correlated with 업종명High correlation
객실수 is highly overall correlated with 업종명High correlation
업종명 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
소재지전화 has 10 (12.7%) missing valuesMissing
객실수 has 1 (1.3%) missing valuesMissing
연번 has unique valuesUnique
신고일자 has unique valuesUnique
업소명 has unique valuesUnique

Reproduction

Analysis started2024-04-06 08:36:30.138569
Analysis finished2024-04-06 08:36:32.470082
Duration2.33 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct79
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40
Minimum1
Maximum79
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size843.0 B
2024-04-06T17:36:32.619302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.9
Q120.5
median40
Q359.5
95-th percentile75.1
Maximum79
Range78
Interquartile range (IQR)39

Descriptive statistics

Standard deviation22.949219
Coefficient of variation (CV)0.57373048
Kurtosis-1.2
Mean40
Median Absolute Deviation (MAD)20
Skewness0
Sum3160
Variance526.66667
MonotonicityStrictly increasing
2024-04-06T17:36:33.006118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.3%
2 1
 
1.3%
59 1
 
1.3%
58 1
 
1.3%
57 1
 
1.3%
56 1
 
1.3%
55 1
 
1.3%
54 1
 
1.3%
53 1
 
1.3%
52 1
 
1.3%
Other values (69) 69
87.3%
ValueCountFrequency (%)
1 1
1.3%
2 1
1.3%
3 1
1.3%
4 1
1.3%
5 1
1.3%
6 1
1.3%
7 1
1.3%
8 1
1.3%
9 1
1.3%
10 1
1.3%
ValueCountFrequency (%)
79 1
1.3%
78 1
1.3%
77 1
1.3%
76 1
1.3%
75 1
1.3%
74 1
1.3%
73 1
1.3%
72 1
1.3%
71 1
1.3%
70 1
1.3%

업종명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size764.0 B
숙박업(일반)
65 
숙박업(생활)
14 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
숙박업(일반) 65
82.3%
숙박업(생활) 14
 
17.7%

Length

2024-04-06T17:36:33.314108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:36:33.510027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
숙박업(일반 65
82.3%
숙박업(생활 14
 
17.7%

신고일자
Date

UNIQUE 

Distinct79
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size764.0 B
Minimum1964-10-08 00:00:00
Maximum2024-03-18 00:00:00
2024-04-06T17:36:33.741454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:36:34.039933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업소명
Text

UNIQUE 

Distinct79
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size764.0 B
2024-04-06T17:36:34.681949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length14
Mean length7
Min length2

Characters and Unicode

Total characters553
Distinct characters165
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique79 ?
Unique (%)100.0%

Sample

1st row둥지모텔
2nd row삼미장여관
3rd row호텔뷰(VIEW)
4th row라마다송도호텔(주)
5th row여우비
ValueCountFrequency (%)
인천송도점 6
 
5.1%
호텔 5
 
4.3%
모텔 5
 
4.3%
송도 4
 
3.4%
스테이 3
 
2.6%
인천 2
 
1.7%
더 2
 
1.7%
인천송도호텔 1
 
0.9%
홀리데이인 1
 
0.9%
경원재앰배서더호텔 1
 
0.9%
Other values (87) 87
74.4%
2024-04-06T17:36:35.614268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
텔 53
 
9.6%
38
 
6.9%
호 36
 
6.5%
도 24
 
4.3%
송 23
 
4.2%
이 21
 
3.8%
모 19
 
3.4%
스 18
 
3.3%
인 15
 
2.7%
천 12
 
2.2%
Other values (155) 294
53.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 462
83.5%
Space Separator 38
 
6.9%
Uppercase Letter 22
 
4.0%
Decimal Number 9
 
1.6%
Open Punctuation 8
 
1.4%
Close Punctuation 8
 
1.4%
Lowercase Letter 6
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
텔 53
 
11.5%
호 36
 
7.8%
도 24
 
5.2%
송 23
 
5.0%
이 21
 
4.5%
모 19
 
4.1%
스 18
 
3.9%
인 15
 
3.2%
천 12
 
2.6%
테 12
 
2.6%
Other values (125) 229
49.6%
Uppercase Letter
ValueCountFrequency (%)
E 4
18.2%
H 3
13.6%
V 2
9.1%
A 2
9.1%
U 2
9.1%
N 1
 
4.5%
T 1
 
4.5%
L 1
 
4.5%
F 1
 
4.5%
Y 1
 
4.5%
Other values (4) 4
18.2%
Decimal Number
ValueCountFrequency (%)
0 2
22.2%
2 2
22.2%
8 1
11.1%
9 1
11.1%
4 1
11.1%
3 1
11.1%
5 1
11.1%
Lowercase Letter
ValueCountFrequency (%)
m 1
16.7%
a 1
16.7%
l 1
16.7%
e 1
16.7%
t 1
16.7%
o 1
16.7%
Space Separator
ValueCountFrequency (%)
38
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 462
83.5%
Common 63
 
11.4%
Latin 28
 
5.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
텔 53
 
11.5%
호 36
 
7.8%
도 24
 
5.2%
송 23
 
5.0%
이 21
 
4.5%
모 19
 
4.1%
스 18
 
3.9%
인 15
 
3.2%
천 12
 
2.6%
테 12
 
2.6%
Other values (125) 229
49.6%
Latin
ValueCountFrequency (%)
E 4
 
14.3%
H 3
 
10.7%
V 2
 
7.1%
A 2
 
7.1%
U 2
 
7.1%
N 1
 
3.6%
T 1
 
3.6%
L 1
 
3.6%
F 1
 
3.6%
m 1
 
3.6%
Other values (10) 10
35.7%
Common
ValueCountFrequency (%)
38
60.3%
( 8
 
12.7%
) 8
 
12.7%
0 2
 
3.2%
2 2
 
3.2%
8 1
 
1.6%
9 1
 
1.6%
4 1
 
1.6%
3 1
 
1.6%
5 1
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 462
83.5%
ASCII 91
 
16.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
텔 53
 
11.5%
호 36
 
7.8%
도 24
 
5.2%
송 23
 
5.0%
이 21
 
4.5%
모 19
 
4.1%
스 18
 
3.9%
인 15
 
3.2%
천 12
 
2.6%
테 12
 
2.6%
Other values (125) 229
49.6%
ASCII
ValueCountFrequency (%)
38
41.8%
( 8
 
8.8%
) 8
 
8.8%
E 4
 
4.4%
H 3
 
3.3%
0 2
 
2.2%
2 2
 
2.2%
V 2
 
2.2%
A 2
 
2.2%
U 2
 
2.2%
Other values (20) 20
22.0%

영업소주소(도로명)
Text

Distinct75
Distinct (%)94.9%
Missing0
Missing (%)0.0%
Memory size764.0 B
2024-04-06T17:36:36.207987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length89
Median length53
Mean length34.708861
Min length21

Characters and Unicode

Total characters2742
Distinct characters90
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

Unique72 ?
Unique (%)91.1%

Sample

1st row인천광역시 연수구 능허대로 175 (옥련동)
2nd row인천광역시 연수구 능허대로167번길 6 (옥련동)
3rd row인천광역시 연수구 대암로 8 (옥련동)
4th row인천광역시 연수구 능허대로267번길 29 (동춘동)
5th row인천광역시 연수구 능허대로191번길 11 (옥련동)
ValueCountFrequency (%)
인천광역시 79
 
15.6%
연수구 79
 
15.6%
옥련동 50
 
9.9%
송도동 20
 
4.0%
아트센터대로168번길 13
 
2.6%
대암로 10
 
2.0%
능허대로 9
 
1.8%
능허대로179번길 8
 
1.6%
능허대로191번길 7
 
1.4%
100 7
 
1.4%
Other values (127) 224
44.3%
2024-04-06T17:36:37.147513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
491
 
17.9%
1 153
 
5.6%
동 92
 
3.4%
인 90
 
3.3%
시 88
 
3.2%
연 82
 
3.0%
수 82
 
3.0%
천 80
 
2.9%
광 79
 
2.9%
역 79
 
2.9%
Other values (80) 1426
52.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1539
56.1%
Space Separator 491
 
17.9%
Decimal Number 474
 
17.3%
Close Punctuation 79
 
2.9%
Open Punctuation 79
 
2.9%
Dash Punctuation 37
 
1.3%
Math Symbol 25
 
0.9%
Uppercase Letter 18
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 92
 
6.0%
인 90
 
5.8%
시 88
 
5.7%
연 82
 
5.3%
수 82
 
5.3%
천 80
 
5.2%
광 79
 
5.1%
역 79
 
5.1%
구 79
 
5.1%
로 79
 
5.1%
Other values (62) 709
46.1%
Decimal Number
ValueCountFrequency (%)
1 153
32.3%
2 42
 
8.9%
5 37
 
7.8%
9 37
 
7.8%
8 35
 
7.4%
7 35
 
7.4%
6 35
 
7.4%
3 34
 
7.2%
0 33
 
7.0%
4 33
 
7.0%
Uppercase Letter
ValueCountFrequency (%)
A 9
50.0%
C 6
33.3%
B 3
 
16.7%
Space Separator
ValueCountFrequency (%)
491
100.0%
Close Punctuation
ValueCountFrequency (%)
) 79
100.0%
Open Punctuation
ValueCountFrequency (%)
( 79
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 37
100.0%
Math Symbol
ValueCountFrequency (%)
~ 25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1539
56.1%
Common 1185
43.2%
Latin 18
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 92
 
6.0%
인 90
 
5.8%
시 88
 
5.7%
연 82
 
5.3%
수 82
 
5.3%
천 80
 
5.2%
광 79
 
5.1%
역 79
 
5.1%
구 79
 
5.1%
로 79
 
5.1%
Other values (62) 709
46.1%
Common
ValueCountFrequency (%)
491
41.4%
1 153
 
12.9%
) 79
 
6.7%
( 79
 
6.7%
2 42
 
3.5%
5 37
 
3.1%
9 37
 
3.1%
- 37
 
3.1%
8 35
 
3.0%
7 35
 
3.0%
Other values (5) 160
 
13.5%
Latin
ValueCountFrequency (%)
A 9
50.0%
C 6
33.3%
B 3
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1539
56.1%
ASCII 1203
43.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
491
40.8%
1 153
 
12.7%
) 79
 
6.6%
( 79
 
6.6%
2 42
 
3.5%
5 37
 
3.1%
9 37
 
3.1%
- 37
 
3.1%
8 35
 
2.9%
7 35
 
2.9%
Other values (8) 178
 
14.8%
Hangul
ValueCountFrequency (%)
동 92
 
6.0%
인 90
 
5.8%
시 88
 
5.7%
연 82
 
5.3%
수 82
 
5.3%
천 80
 
5.2%
광 79
 
5.1%
역 79
 
5.1%
구 79
 
5.1%
로 79
 
5.1%
Other values (62) 709
46.1%

소재지전화
Text

MISSING 

Distinct69
Distinct (%)100.0%
Missing10
Missing (%)12.7%
Memory size764.0 B
2024-04-06T17:36:37.630642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length13.985507
Min length13

Characters and Unicode

Total characters965
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 (%)100.0%

Sample

1st row 032- 833-6222
2nd row 032- 832-1525
3rd row032 -832 -1500
4th row 032- 832-1311
5th row032 -832 -9700
ValueCountFrequency (%)
032 64
40.8%
834 3
 
1.9%
832 2
 
1.3%
0000 2
 
1.3%
833 2
 
1.3%
7502 1
 
0.6%
1771 1
 
0.6%
2222 1
 
0.6%
813 1
 
0.6%
832-3258 1
 
0.6%
Other values (79) 79
50.3%
2024-04-06T17:36:38.368920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 151
15.6%
- 138
14.3%
130
13.5%
0 126
13.1%
2 126
13.1%
8 80
8.3%
1 55
 
5.7%
4 42
 
4.4%
5 39
 
4.0%
7 35
 
3.6%
Other values (2) 43
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 697
72.2%
Dash Punctuation 138
 
14.3%
Space Separator 130
 
13.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 151
21.7%
0 126
18.1%
2 126
18.1%
8 80
11.5%
1 55
 
7.9%
4 42
 
6.0%
5 39
 
5.6%
7 35
 
5.0%
6 23
 
3.3%
9 20
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 138
100.0%
Space Separator
ValueCountFrequency (%)
130
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 965
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 151
15.6%
- 138
14.3%
130
13.5%
0 126
13.1%
2 126
13.1%
8 80
8.3%
1 55
 
5.7%
4 42
 
4.4%
5 39
 
4.0%
7 35
 
3.6%
Other values (2) 43
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 965
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 151
15.6%
- 138
14.3%
130
13.5%
0 126
13.1%
2 126
13.1%
8 80
8.3%
1 55
 
5.7%
4 42
 
4.4%
5 39
 
4.0%
7 35
 
3.6%
Other values (2) 43
 
4.5%

객실수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct45
Distinct (%)57.7%
Missing1
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean66.487179
Minimum5
Maximum423
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size843.0 B
2024-04-06T17:36:38.653256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile14
Q127
median36
Q350.75
95-th percentile282.15
Maximum423
Range418
Interquartile range (IQR)23.75

Descriptive statistics

Standard deviation82.936174
Coefficient of variation (CV)1.247401
Kurtosis5.9538933
Mean66.487179
Median Absolute Deviation (MAD)12
Skewness2.5148485
Sum5186
Variance6878.4089
MonotonicityNot monotonic
2024-04-06T17:36:38.916495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
30 9
 
11.4%
40 5
 
6.3%
46 4
 
5.1%
36 3
 
3.8%
19 3
 
3.8%
48 3
 
3.8%
24 3
 
3.8%
18 2
 
2.5%
21 2
 
2.5%
31 2
 
2.5%
Other values (35) 42
53.2%
ValueCountFrequency (%)
5 1
 
1.3%
12 2
2.5%
14 2
2.5%
15 1
 
1.3%
18 2
2.5%
19 3
3.8%
21 2
2.5%
23 2
2.5%
24 3
3.8%
26 1
 
1.3%
ValueCountFrequency (%)
423 1
1.3%
321 1
1.3%
300 2
2.5%
279 1
1.3%
241 1
1.3%
208 1
1.3%
204 1
1.3%
202 1
1.3%
143 1
1.3%
142 1
1.3%

Interactions

2024-04-06T17:36:31.442891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:36:30.998260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:36:31.718244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:36:31.243004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:36:39.152424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종명신고일자업소명영업소주소(도로명)소재지전화객실수
연번1.0000.9931.0001.0000.9901.0000.291
업종명0.9931.0001.0001.0001.0001.0000.571
신고일자1.0001.0001.0001.0001.0001.0001.000
업소명1.0001.0001.0001.0001.0001.0001.000
영업소주소(도로명)0.9901.0001.0001.0001.0001.0000.000
소재지전화1.0001.0001.0001.0001.0001.0001.000
객실수0.2910.5711.0001.0000.0001.0001.000
2024-04-06T17:36:39.393566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번객실수업종명
연번1.0000.4410.874
객실수0.4411.0000.546
업종명0.8740.5461.000

Missing values

2024-04-06T17:36:31.938220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:36:32.180795image/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.
2024-04-06T17:36:32.371371image/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

연번업종명신고일자업소명영업소주소(도로명)소재지전화객실수
01숙박업(일반)1964-10-08둥지모텔인천광역시 연수구 능허대로 175 (옥련동)032- 833-622218
12숙박업(일반)1984-08-23삼미장여관인천광역시 연수구 능허대로167번길 6 (옥련동)032- 832-152514
23숙박업(일반)1985-06-22호텔뷰(VIEW)인천광역시 연수구 대암로 8 (옥련동)032 -832 -150028
34숙박업(일반)1985-10-14라마다송도호텔(주)인천광역시 연수구 능허대로267번길 29 (동춘동)032- 832-1311204
45숙박업(일반)1986-07-19여우비인천광역시 연수구 능허대로191번길 11 (옥련동)032 -832 -970018
56숙박업(일반)1986-01-29필드모텔인천광역시 연수구 대암로 4 (옥련동)032-0832-123912
67숙박업(일반)1987-08-03가빈인천광역시 연수구 인권로 17 (옥련동)032- 832-356130
78숙박업(일반)1988-11-04호텔메이인천광역시 연수구 인권로9번길 10 (옥련동)032 -834 -550536
89숙박업(일반)1989-12-26큐(Q)모텔인천광역시 연수구 대암로8번길 14 (옥련동)032- 831-948814
910숙박업(일반)1990-08-06노리터모텔인천광역시 연수구 인권로 15 (옥련동)032 -858 -866415
연번업종명신고일자업소명영업소주소(도로명)소재지전화객실수
6970숙박업(생활)2021-07-06달빛스테이인천광역시 연수구 아트센터대로168번길 100 한라 웨스턴파크 송도 A-C동 5 7-15 17-21 23-30 32-37층 일부 (송도동)032- 833-165091
7071숙박업(생활)2021-07-09더노벰버스테이인천광역시 연수구 아트센터대로168번길 101 송도랜드마크푸르지오시티 A-B동 4-14 16-36층 (송도동)032 -817 -1988208
7172숙박업(생활)2021-08-24어반스테이 인천송도점인천광역시 연수구 아트센터대로168번길 101 송도랜드마크푸르지오시티 1 4~14 16~35층 (송도동)032 -1644-7694142
7273숙박업(생활)2022-12-07UH FLAT 더 송도(유에이치플랫더송도)인천광역시 연수구 아트센터대로168번길 100 한라 웨스턴파크 송도 A-C동 7-8 11-15 17 19 21-23 25 31-37층 (송도동)0704-9430-54831
7374숙박업(생활)2023-07-20윤슬스테이인천광역시 연수구 아트센터대로168번길 101 송도랜드마크푸르지오시티 (송도동)<NA>30
7475숙박업(생활)2023-08-07모두스테이 송도인천광역시 연수구 아트센터대로168번길 101 송도랜드마크푸르지오시티 A-B동 일부호 (송도동)032- 217-525230
7576숙박업(생활)2023-11-06골든스테이인천광역시 연수구 아트센터대로168번길 101 송도랜드마크푸르지오시티 A-B동 일부호 (송도동)<NA>29
7677숙박업(생활)2023-11-08송도달빛공원스테이인천광역시 연수구 아트센터대로168번길 100 한라 웨스턴파크 송도 A-C동 일부호 (송도동)<NA>104
7778숙박업(생활)2023-11-15위테이크 송도인천광역시 연수구 아트센터대로168번길 100 한라 웨스턴파크 송도 A-C동 일부호 (송도동)<NA>31
7879숙박업(생활)2024-01-03가든하우스인송도인천광역시 연수구 아트센터대로168번길 100 한라 웨스턴파크 송도 A-C동 일부호 (송도동)<NA>30