Overview

Dataset statistics

Number of variables7
Number of observations86
Missing cells9
Missing cells (%)1.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.9 KiB
Average record size in memory58.5 B

Variable types

Numeric1
Categorical1
Text4
DateTime1

Dataset

Description인천광역시 남동구 관내 숙박업 현황에 대한 자료로 업종, 상호, 영업소소재지,전화번호, 데이터기준일자를 공개합니다.
URLhttps://www.data.go.kr/data/15038946/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
연번 is highly overall correlated with 업종명High correlation
업종명 is highly overall correlated with 연번High correlation
업종명 is highly imbalanced (55.4%)Imbalance
소재지전화 has 9 (10.5%) missing valuesMissing
연번 has unique valuesUnique
업소소재지(도로명) has unique valuesUnique

Reproduction

Analysis started2023-12-12 13:34:35.852940
Analysis finished2023-12-12 13:34:36.813848
Duration0.96 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct86
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean43.5
Minimum1
Maximum86
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size906.0 B
2023-12-12T22:34:36.882184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.25
Q122.25
median43.5
Q364.75
95-th percentile81.75
Maximum86
Range85
Interquartile range (IQR)42.5

Descriptive statistics

Standard deviation24.969982
Coefficient of variation (CV)0.57402257
Kurtosis-1.2
Mean43.5
Median Absolute Deviation (MAD)21.5
Skewness0
Sum3741
Variance623.5
MonotonicityStrictly increasing
2023-12-12T22:34:37.001357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.2%
56 1
 
1.2%
64 1
 
1.2%
63 1
 
1.2%
62 1
 
1.2%
61 1
 
1.2%
60 1
 
1.2%
59 1
 
1.2%
58 1
 
1.2%
57 1
 
1.2%
Other values (76) 76
88.4%
ValueCountFrequency (%)
1 1
1.2%
2 1
1.2%
3 1
1.2%
4 1
1.2%
5 1
1.2%
6 1
1.2%
7 1
1.2%
8 1
1.2%
9 1
1.2%
10 1
1.2%
ValueCountFrequency (%)
86 1
1.2%
85 1
1.2%
84 1
1.2%
83 1
1.2%
82 1
1.2%
81 1
1.2%
80 1
1.2%
79 1
1.2%
78 1
1.2%
77 1
1.2%

업종명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size820.0 B
숙박업(일반)
78 
숙박업(생활)
8 

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) 78
90.7%
숙박업(생활) 8
 
9.3%

Length

2023-12-12T22:34:37.134846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:34:37.241471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
숙박업(일반 78
90.7%
숙박업(생활 8
 
9.3%

업소명
Text

Distinct85
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size820.0 B
2023-12-12T22:34:37.513104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length13
Mean length5.8953488
Min length2

Characters and Unicode

Total characters507
Distinct characters150
Distinct categories7 ?
Distinct scripts5 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique84 ?
Unique (%)97.7%

Sample

1st row주얼리 모텔
2nd row화승여관
3rd row산장여인숙
4th row옥수장여관
5th row광명장 여관
ValueCountFrequency (%)
호텔 7
 
6.7%
모텔 3
 
2.9%
소래포구점 2
 
1.9%
엠(m)모텔 2
 
1.9%
파크마린 1
 
1.0%
라마다인천호텔 1
 
1.0%
엠플레이스 1
 
1.0%
카카오 1
 
1.0%
호텔月(호텔월 1
 
1.0%
소래호텔카카오 1
 
1.0%
Other values (84) 84
80.8%
2023-12-12T22:34:37.971013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
텔 62
 
12.2%
호 37
 
7.3%
모 22
 
4.3%
18
 
3.6%
( 12
 
2.4%
) 12
 
2.4%
리 11
 
2.2%
여 11
 
2.2%
스 11
 
2.2%
관 10
 
2.0%
Other values (140) 301
59.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 409
80.7%
Uppercase Letter 41
 
8.1%
Space Separator 18
 
3.6%
Open Punctuation 12
 
2.4%
Close Punctuation 12
 
2.4%
Decimal Number 12
 
2.4%
Lowercase Letter 3
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
텔 62
 
15.2%
호 37
 
9.0%
모 22
 
5.4%
리 11
 
2.7%
여 11
 
2.7%
스 11
 
2.7%
관 10
 
2.4%
라 8
 
2.0%
인 8
 
2.0%
이 8
 
2.0%
Other values (111) 221
54.0%
Uppercase Letter
ValueCountFrequency (%)
E 6
14.6%
S 5
12.2%
O 4
9.8%
H 3
 
7.3%
T 3
 
7.3%
N 3
 
7.3%
M 3
 
7.3%
R 2
 
4.9%
L 2
 
4.9%
I 2
 
4.9%
Other values (7) 8
19.5%
Decimal Number
ValueCountFrequency (%)
2 3
25.0%
0 2
16.7%
5 2
16.7%
1 2
16.7%
3 2
16.7%
4 1
 
8.3%
Lowercase Letter
ValueCountFrequency (%)
c 1
33.3%
π 1
33.3%
f 1
33.3%
Space Separator
ValueCountFrequency (%)
18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 408
80.5%
Common 54
 
10.7%
Latin 43
 
8.5%
Han 1
 
0.2%
Greek 1
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
텔 62
 
15.2%
호 37
 
9.1%
모 22
 
5.4%
리 11
 
2.7%
여 11
 
2.7%
스 11
 
2.7%
관 10
 
2.5%
라 8
 
2.0%
인 8
 
2.0%
이 8
 
2.0%
Other values (110) 220
53.9%
Latin
ValueCountFrequency (%)
E 6
14.0%
S 5
11.6%
O 4
 
9.3%
H 3
 
7.0%
T 3
 
7.0%
N 3
 
7.0%
M 3
 
7.0%
R 2
 
4.7%
L 2
 
4.7%
I 2
 
4.7%
Other values (9) 10
23.3%
Common
ValueCountFrequency (%)
18
33.3%
( 12
22.2%
) 12
22.2%
2 3
 
5.6%
0 2
 
3.7%
5 2
 
3.7%
1 2
 
3.7%
3 2
 
3.7%
4 1
 
1.9%
Han
ValueCountFrequency (%)
月 1
100.0%
Greek
ValueCountFrequency (%)
π 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 408
80.5%
ASCII 97
 
19.1%
CJK 1
 
0.2%
None 1
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
텔 62
 
15.2%
호 37
 
9.1%
모 22
 
5.4%
리 11
 
2.7%
여 11
 
2.7%
스 11
 
2.7%
관 10
 
2.5%
라 8
 
2.0%
인 8
 
2.0%
이 8
 
2.0%
Other values (110) 220
53.9%
ASCII
ValueCountFrequency (%)
18
18.6%
( 12
12.4%
) 12
12.4%
E 6
 
6.2%
S 5
 
5.2%
O 4
 
4.1%
H 3
 
3.1%
T 3
 
3.1%
2 3
 
3.1%
N 3
 
3.1%
Other values (18) 28
28.9%
CJK
ValueCountFrequency (%)
月 1
100.0%
None
ValueCountFrequency (%)
π 1
100.0%

업소소재지(도로명)
Text

UNIQUE 

Distinct86
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size820.0 B
2023-12-12T22:34:38.301702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length49
Mean length32.546512
Min length22

Characters and Unicode

Total characters2799
Distinct characters102
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique86 ?
Unique (%)100.0%

Sample

1st row인천광역시 남동구 남동대로921번길 21 (간석동,(남동대로 921번길 21))
2nd row인천광역시 남동구 경인로644번길 12-1 (간석동)
3rd row인천광역시 남동구 남동대로916번길 83 (간석동)
4th row인천광역시 남동구 만수로71번길 6 (만수동,89,90번지)
5th row인천광역시 남동구 호구포로889번길 16, 3층 (간석동)
ValueCountFrequency (%)
인천광역시 86
 
17.1%
남동구 86
 
17.1%
간석동 37
 
7.3%
논현동 23
 
4.6%
구월동 15
 
3.0%
석촌로46번길 8
 
1.6%
백범로359번길 7
 
1.4%
일부 5
 
1.0%
28 5
 
1.0%
남동대로916번길 5
 
1.0%
Other values (151) 227
45.0%
2023-12-12T22:34:38.779495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
418
 
14.9%
동 193
 
6.9%
구 108
 
3.9%
남 106
 
3.8%
역 98
 
3.5%
1 97
 
3.5%
로 94
 
3.4%
) 92
 
3.3%
( 92
 
3.3%
인 92
 
3.3%
Other values (92) 1409
50.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1600
57.2%
Decimal Number 503
 
18.0%
Space Separator 418
 
14.9%
Close Punctuation 92
 
3.3%
Open Punctuation 92
 
3.3%
Other Punctuation 61
 
2.2%
Math Symbol 19
 
0.7%
Dash Punctuation 10
 
0.4%
Uppercase Letter 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 193
 
12.1%
구 108
 
6.8%
남 106
 
6.6%
역 98
 
6.1%
로 94
 
5.9%
인 92
 
5.8%
천 91
 
5.7%
광 88
 
5.5%
시 87
 
5.4%
번 75
 
4.7%
Other values (72) 568
35.5%
Decimal Number
ValueCountFrequency (%)
1 97
19.3%
2 60
11.9%
6 58
11.5%
4 48
9.5%
5 48
9.5%
3 45
8.9%
9 43
8.5%
7 36
 
7.2%
0 34
 
6.8%
8 34
 
6.8%
Uppercase Letter
ValueCountFrequency (%)
L 2
50.0%
B 1
25.0%
T 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 60
98.4%
. 1
 
1.6%
Space Separator
ValueCountFrequency (%)
418
100.0%
Close Punctuation
ValueCountFrequency (%)
) 92
100.0%
Open Punctuation
ValueCountFrequency (%)
( 92
100.0%
Math Symbol
ValueCountFrequency (%)
~ 19
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1600
57.2%
Common 1195
42.7%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 193
 
12.1%
구 108
 
6.8%
남 106
 
6.6%
역 98
 
6.1%
로 94
 
5.9%
인 92
 
5.8%
천 91
 
5.7%
광 88
 
5.5%
시 87
 
5.4%
번 75
 
4.7%
Other values (72) 568
35.5%
Common
ValueCountFrequency (%)
418
35.0%
1 97
 
8.1%
) 92
 
7.7%
( 92
 
7.7%
2 60
 
5.0%
, 60
 
5.0%
6 58
 
4.9%
4 48
 
4.0%
5 48
 
4.0%
3 45
 
3.8%
Other values (7) 177
14.8%
Latin
ValueCountFrequency (%)
L 2
50.0%
B 1
25.0%
T 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1600
57.2%
ASCII 1199
42.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
418
34.9%
1 97
 
8.1%
) 92
 
7.7%
( 92
 
7.7%
2 60
 
5.0%
, 60
 
5.0%
6 58
 
4.8%
4 48
 
4.0%
5 48
 
4.0%
3 45
 
3.8%
Other values (10) 181
15.1%
Hangul
ValueCountFrequency (%)
동 193
 
12.1%
구 108
 
6.8%
남 106
 
6.6%
역 98
 
6.1%
로 94
 
5.9%
인 92
 
5.8%
천 91
 
5.7%
광 88
 
5.5%
시 87
 
5.4%
번 75
 
4.7%
Other values (72) 568
35.5%

업소소재지(지번)
Text

Distinct85
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size820.0 B
2023-12-12T22:34:39.164820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length43
Mean length24.406977
Min length18

Characters and Unicode

Total characters2099
Distinct characters89
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique84 ?
Unique (%)97.7%

Sample

1st row인천광역시 남동구 간석동 315-6 (남동대로 921번길 21)
2nd row인천광역시 남동구 간석동 110-4
3rd row인천광역시 남동구 간석동 124-13
4th row인천광역시 남동구 만수동 5-89 89,90번지
5th row인천광역시 남동구 간석동 916-12
ValueCountFrequency (%)
인천광역시 86
21.4%
남동구 86
21.4%
간석동 40
 
10.0%
논현동 25
 
6.2%
구월동 16
 
4.0%
만수동 5
 
1.2%
1층일부 2
 
0.5%
1층 2
 
0.5%
678-3 2
 
0.5%
일부 2
 
0.5%
Other values (132) 136
33.8%
2023-12-12T22:34:39.711567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
402
19.2%
동 175
 
8.3%
1 133
 
6.3%
구 103
 
4.9%
남 88
 
4.2%
광 87
 
4.1%
시 87
 
4.1%
인 86
 
4.1%
역 86
 
4.1%
천 86
 
4.1%
Other values (79) 766
36.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1105
52.6%
Decimal Number 468
22.3%
Space Separator 402
 
19.2%
Dash Punctuation 85
 
4.0%
Math Symbol 14
 
0.7%
Other Punctuation 9
 
0.4%
Close Punctuation 6
 
0.3%
Open Punctuation 6
 
0.3%
Uppercase Letter 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 175
15.8%
구 103
9.3%
남 88
 
8.0%
광 87
 
7.9%
시 87
 
7.9%
인 86
 
7.8%
역 86
 
7.8%
천 86
 
7.8%
석 41
 
3.7%
간 40
 
3.6%
Other values (59) 226
20.5%
Decimal Number
ValueCountFrequency (%)
1 133
28.4%
6 70
15.0%
7 56
12.0%
4 46
 
9.8%
3 40
 
8.5%
2 38
 
8.1%
8 24
 
5.1%
9 23
 
4.9%
5 22
 
4.7%
0 16
 
3.4%
Uppercase Letter
ValueCountFrequency (%)
L 2
50.0%
T 1
25.0%
B 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 8
88.9%
. 1
 
11.1%
Space Separator
ValueCountFrequency (%)
402
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 85
100.0%
Math Symbol
ValueCountFrequency (%)
~ 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1105
52.6%
Common 990
47.2%
Latin 4
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 175
15.8%
구 103
9.3%
남 88
 
8.0%
광 87
 
7.9%
시 87
 
7.9%
인 86
 
7.8%
역 86
 
7.8%
천 86
 
7.8%
석 41
 
3.7%
간 40
 
3.6%
Other values (59) 226
20.5%
Common
ValueCountFrequency (%)
402
40.6%
1 133
 
13.4%
- 85
 
8.6%
6 70
 
7.1%
7 56
 
5.7%
4 46
 
4.6%
3 40
 
4.0%
2 38
 
3.8%
8 24
 
2.4%
9 23
 
2.3%
Other values (7) 73
 
7.4%
Latin
ValueCountFrequency (%)
L 2
50.0%
T 1
25.0%
B 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1105
52.6%
ASCII 994
47.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
402
40.4%
1 133
 
13.4%
- 85
 
8.6%
6 70
 
7.0%
7 56
 
5.6%
4 46
 
4.6%
3 40
 
4.0%
2 38
 
3.8%
8 24
 
2.4%
9 23
 
2.3%
Other values (10) 77
 
7.7%
Hangul
ValueCountFrequency (%)
동 175
15.8%
구 103
9.3%
남 88
 
8.0%
광 87
 
7.9%
시 87
 
7.9%
인 86
 
7.8%
역 86
 
7.8%
천 86
 
7.8%
석 41
 
3.7%
간 40
 
3.6%
Other values (59) 226
20.5%

소재지전화
Text

MISSING 

Distinct77
Distinct (%)100.0%
Missing9
Missing (%)10.5%
Memory size820.0 B
2023-12-12T22:34:40.000187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters924
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique77 ?
Unique (%)100.0%

Sample

1st row032-428-7779
2nd row032-434-5330
3rd row032-434-5437
4th row032-467-9962
5th row032-435-0113
ValueCountFrequency (%)
032-463-5441 1
 
1.3%
032-710-1025 1
 
1.3%
032-426-2500 1
 
1.3%
032-437-2900 1
 
1.3%
032-424-9993 1
 
1.3%
032-439-7700 1
 
1.3%
032-437-1913 1
 
1.3%
032-429-7478 1
 
1.3%
032-472-9500 1
 
1.3%
032-424-4997 1
 
1.3%
Other values (67) 67
87.0%
2023-12-12T22:34:40.676554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 155
16.8%
- 154
16.7%
2 148
16.0%
3 144
15.6%
4 106
11.5%
7 47
 
5.1%
9 38
 
4.1%
6 37
 
4.0%
5 33
 
3.6%
1 33
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 770
83.3%
Dash Punctuation 154
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 155
20.1%
2 148
19.2%
3 144
18.7%
4 106
13.8%
7 47
 
6.1%
9 38
 
4.9%
6 37
 
4.8%
5 33
 
4.3%
1 33
 
4.3%
8 29
 
3.8%
Dash Punctuation
ValueCountFrequency (%)
- 154
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 924
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 155
16.8%
- 154
16.7%
2 148
16.0%
3 144
15.6%
4 106
11.5%
7 47
 
5.1%
9 38
 
4.1%
6 37
 
4.0%
5 33
 
3.6%
1 33
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 924
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 155
16.8%
- 154
16.7%
2 148
16.0%
3 144
15.6%
4 106
11.5%
7 47
 
5.1%
9 38
 
4.1%
6 37
 
4.0%
5 33
 
3.6%
1 33
 
3.6%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size820.0 B
Minimum2023-06-14 00:00:00
Maximum2023-06-14 00:00:00
2023-12-12T22:34:40.799320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:34:40.890339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T22:34:36.570615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:34:40.958592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종명업소명업소소재지(도로명)업소소재지(지번)소재지전화
연번1.0000.9940.9461.0000.9461.000
업종명0.9941.0001.0001.0001.0001.000
업소명0.9461.0001.0001.0000.9991.000
업소소재지(도로명)1.0001.0001.0001.0001.0001.000
업소소재지(지번)0.9461.0000.9991.0001.0001.000
소재지전화1.0001.0001.0001.0001.0001.000
2023-12-12T22:34:41.054008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종명
연번1.0000.884
업종명0.8841.000

Missing values

2023-12-12T22:34:36.668862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:34:36.772406image/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

연번업종명업소명업소소재지(도로명)업소소재지(지번)소재지전화데이터기준일자
01숙박업(일반)주얼리 모텔인천광역시 남동구 남동대로921번길 21 (간석동,(남동대로 921번길 21))인천광역시 남동구 간석동 315-6 (남동대로 921번길 21)032-428-77792023-06-14
12숙박업(일반)화승여관인천광역시 남동구 경인로644번길 12-1 (간석동)인천광역시 남동구 간석동 110-4032-434-53302023-06-14
23숙박업(일반)산장여인숙인천광역시 남동구 남동대로916번길 83 (간석동)인천광역시 남동구 간석동 124-13032-434-54372023-06-14
34숙박업(일반)옥수장여관인천광역시 남동구 만수로71번길 6 (만수동,89,90번지)인천광역시 남동구 만수동 5-89 89,90번지032-467-99622023-06-14
45숙박업(일반)광명장 여관인천광역시 남동구 호구포로889번길 16, 3층 (간석동)인천광역시 남동구 간석동 916-12032-435-01132023-06-14
56숙박업(일반)명성여관인천광역시 남동구 하촌로70번길 73 (만수동)인천광역시 남동구 만수동 961-22032-461-22372023-06-14
67숙박업(일반)청운모텔인천광역시 남동구 구월말로 118 (만수동)인천광역시 남동구 만수동 896032-462-02852023-06-14
78숙박업(일반)렉스리빙텔인천광역시 남동구 남동대로916번길 89 (간석동)인천광역시 남동구 간석동 124-4032-438-97002023-06-14
89숙박업(일반)도원장인천광역시 남동구 남동대로921번길 23 (간석동)인천광역시 남동구 간석동 315-1032-424-52972023-06-14
910숙박업(일반)새여인숙인천광역시 남동구 백범로214번길 6-6 (만수동,(백범로214번길 6-6))인천광역시 남동구 만수동 861-1 (백범로214번길 6-6)032-463-54412023-06-14
연번업종명업소명업소소재지(도로명)업소소재지(지번)소재지전화데이터기준일자
7677숙박업(일반)골드코스트호텔인천인천광역시 남동구 논현로26번길 46, 1층 일부,6~15층 일부호 (논현동)인천광역시 남동구 논현동 645-8032-710-52302023-06-14
7778숙박업(일반)에이치에비뉴 소래포구점인천광역시 남동구 소래역로46번길 28, 대영로데오 8,9층 801,901호 (논현동)인천광역시 남동구 논현동 676-2 대영로데오02-2188-65402023-06-14
7879숙박업(생활)로얄모텔인천광역시 남동구 용천로153번길 52 (간석동)인천광역시 남동구 간석동 170-5<NA>2023-06-14
7980숙박업(생활)애플텔인천광역시 남동구 남동대로915번길 28 (간석동)인천광역시 남동구 간석동 315-4<NA>2023-06-14
8081숙박업(생활)가야텔인천광역시 남동구 백범로359번길 16 (간석동)인천광역시 남동구 간석동 173-26<NA>2023-06-14
8182숙박업(생활)메종인천광역시 남동구 백범로359번길 8 (간석동)인천광역시 남동구 간석동 173-37<NA>2023-06-14
8283숙박업(생활)옥천텔인천광역시 남동구 백범로359번길 17 (간석동)인천광역시 남동구 간석동 174-19<NA>2023-06-14
8384숙박업(생활)라마다인천호텔인천광역시 남동구 소래역로 36, 6~16층 (논현동)인천광역시 남동구 논현동 677-6 6~16층032-460-11002023-06-14
8485숙박업(생활)파크마린 관광호텔인천광역시 남동구 소래역로 44, 파크마린호텔 1층일부, 4~10층 (논현동)인천광역시 남동구 논현동 677-1 파크마린호텔 1층일부, 4~10층032-425-27002023-06-14
8586숙박업(생활)(주)유승건설인천광역시 남동구 논현로46번길 51, 유승테라폴리스 6층 일부, 20~27층 일부호 (논현동)인천광역시 남동구 논현동 642-1 유승테라폴리스032-717-13522023-06-14