Overview

Dataset statistics

Number of variables5
Number of observations96
Missing cells22
Missing cells (%)4.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.0 KiB
Average record size in memory42.4 B

Variable types

Numeric1
Text4

Dataset

Description인천광역시 미추홀구 컴퓨터수리업체 목록에 대한 데이터입니다. 상호명, 지번주소, 도로명주소, 전화번호 등의 항목을 제공하고 있습니다.
URLhttps://www.data.go.kr/data/15088506/fileData.do

Alerts

도로명주소 has 10 (10.4%) missing valuesMissing
전화번호 has 12 (12.5%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 15:21:17.165427
Analysis finished2023-12-12 15:21:18.174026
Duration1.01 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct96
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean48.5
Minimum1
Maximum96
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size996.0 B
2023-12-13T00:21:18.257875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.75
Q124.75
median48.5
Q372.25
95-th percentile91.25
Maximum96
Range95
Interquartile range (IQR)47.5

Descriptive statistics

Standard deviation27.856777
Coefficient of variation (CV)0.57436653
Kurtosis-1.2
Mean48.5
Median Absolute Deviation (MAD)24
Skewness0
Sum4656
Variance776
MonotonicityStrictly increasing
2023-12-13T00:21:18.430762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.0%
50 1
 
1.0%
72 1
 
1.0%
71 1
 
1.0%
70 1
 
1.0%
69 1
 
1.0%
68 1
 
1.0%
67 1
 
1.0%
66 1
 
1.0%
65 1
 
1.0%
Other values (86) 86
89.6%
ValueCountFrequency (%)
1 1
1.0%
2 1
1.0%
3 1
1.0%
4 1
1.0%
5 1
1.0%
6 1
1.0%
7 1
1.0%
8 1
1.0%
9 1
1.0%
10 1
1.0%
ValueCountFrequency (%)
96 1
1.0%
95 1
1.0%
94 1
1.0%
93 1
1.0%
92 1
1.0%
91 1
1.0%
90 1
1.0%
89 1
1.0%
88 1
1.0%
87 1
1.0%

상호명
Text

Distinct52
Distinct (%)54.2%
Missing0
Missing (%)0.0%
Memory size900.0 B
2023-12-13T00:21:18.722223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length5
Mean length7.40625
Min length1

Characters and Unicode

Total characters711
Distinct characters130
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)50.0%

Sample

1st row컴퓨터수리
2nd row컴퓨터수리
3rd row컴퓨터수리
4th row컴퓨터수리
5th row컴퓨터수리
ValueCountFrequency (%)
컴퓨터수리 42
39.3%
빠른출장컴퓨터수리컴닥터pc119 3
 
2.8%
가장빠른번개컴퓨터출장수리컴닥터pc119 2
 
1.9%
진짜빠른컴퓨터출장수리컴닥터pc119 2
 
1.9%
인천점 2
 
1.9%
학익점 2
 
1.9%
주비젼컴 1
 
0.9%
빠른출장윈도우10설치포맷컴닥터pc119 1
 
0.9%
컴수리 1
 
0.9%
휴먼컴퓨터 1
 
0.9%
Other values (50) 50
46.7%
2023-12-13T00:21:19.216477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
컴 93
 
13.1%
터 89
 
12.5%
퓨 76
 
10.7%
리 64
 
9.0%
수 63
 
8.9%
1 20
 
2.8%
장 13
 
1.8%
C 13
 
1.8%
P 12
 
1.7%
11
 
1.5%
Other values (120) 257
36.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 628
88.3%
Uppercase Letter 34
 
4.8%
Decimal Number 33
 
4.6%
Space Separator 11
 
1.5%
Lowercase Letter 4
 
0.6%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
컴 93
14.8%
터 89
14.2%
퓨 76
12.1%
리 64
 
10.2%
수 63
 
10.0%
장 13
 
2.1%
출 11
 
1.8%
닥 11
 
1.8%
빠 10
 
1.6%
른 10
 
1.6%
Other values (98) 188
29.9%
Uppercase Letter
ValueCountFrequency (%)
C 13
38.2%
P 12
35.3%
T 1
 
2.9%
G 1
 
2.9%
L 1
 
2.9%
S 1
 
2.9%
I 1
 
2.9%
D 1
 
2.9%
E 1
 
2.9%
M 1
 
2.9%
Decimal Number
ValueCountFrequency (%)
1 20
60.6%
9 9
27.3%
0 2
 
6.1%
4 1
 
3.0%
2 1
 
3.0%
Lowercase Letter
ValueCountFrequency (%)
c 1
25.0%
p 1
25.0%
u 1
25.0%
v 1
25.0%
Space Separator
ValueCountFrequency (%)
11
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 628
88.3%
Common 45
 
6.3%
Latin 38
 
5.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
컴 93
14.8%
터 89
14.2%
퓨 76
12.1%
리 64
 
10.2%
수 63
 
10.0%
장 13
 
2.1%
출 11
 
1.8%
닥 11
 
1.8%
빠 10
 
1.6%
른 10
 
1.6%
Other values (98) 188
29.9%
Latin
ValueCountFrequency (%)
C 13
34.2%
P 12
31.6%
T 1
 
2.6%
G 1
 
2.6%
c 1
 
2.6%
p 1
 
2.6%
L 1
 
2.6%
u 1
 
2.6%
v 1
 
2.6%
S 1
 
2.6%
Other values (5) 5
 
13.2%
Common
ValueCountFrequency (%)
1 20
44.4%
11
24.4%
9 9
20.0%
0 2
 
4.4%
& 1
 
2.2%
4 1
 
2.2%
2 1
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 628
88.3%
ASCII 83
 
11.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
컴 93
14.8%
터 89
14.2%
퓨 76
12.1%
리 64
 
10.2%
수 63
 
10.0%
장 13
 
2.1%
출 11
 
1.8%
닥 11
 
1.8%
빠 10
 
1.6%
른 10
 
1.6%
Other values (98) 188
29.9%
ASCII
ValueCountFrequency (%)
1 20
24.1%
C 13
15.7%
P 12
14.5%
11
13.3%
9 9
10.8%
0 2
 
2.4%
T 1
 
1.2%
G 1
 
1.2%
c 1
 
1.2%
p 1
 
1.2%
Other values (12) 12
14.5%

지번주소
Text

Distinct89
Distinct (%)92.7%
Missing0
Missing (%)0.0%
Memory size900.0 B
2023-12-13T00:21:19.521493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length33
Mean length22.6875
Min length14

Characters and Unicode

Total characters2178
Distinct characters98
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique83 ?
Unique (%)86.5%

Sample

1st row인천광역시 미추홀구 용현동 659 엑슬루타워 102동
2nd row인천광역시 미추홀구 주안동 1420-6 103호
3rd row인천광역시 미추홀구 주안동 169 신성쇼핑 102호
4th row인천광역시 미추홀구 숭의동 339-6
5th row인천광역시 미추홀구 문학동 396-2
ValueCountFrequency (%)
인천광역시 96
22.1%
미추홀구 96
22.1%
주안동 38
 
8.7%
도화동 16
 
3.7%
용현동 14
 
3.2%
학익동 11
 
2.5%
숭의동 9
 
2.1%
1층 6
 
1.4%
문학동 4
 
0.9%
102동 3
 
0.7%
Other values (128) 142
32.6%
2023-12-13T00:21:20.081410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
344
 
15.8%
동 101
 
4.6%
인 97
 
4.5%
광 97
 
4.5%
천 97
 
4.5%
역 96
 
4.4%
시 96
 
4.4%
미 96
 
4.4%
추 96
 
4.4%
홀 96
 
4.4%
Other values (88) 962
44.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1296
59.5%
Decimal Number 453
 
20.8%
Space Separator 344
 
15.8%
Dash Punctuation 81
 
3.7%
Uppercase Letter 3
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 101
 
7.8%
인 97
 
7.5%
광 97
 
7.5%
천 97
 
7.5%
역 96
 
7.4%
시 96
 
7.4%
미 96
 
7.4%
추 96
 
7.4%
홀 96
 
7.4%
구 96
 
7.4%
Other values (72) 328
25.3%
Decimal Number
ValueCountFrequency (%)
1 89
19.6%
2 63
13.9%
6 47
10.4%
4 46
10.2%
3 44
9.7%
0 42
9.3%
5 38
8.4%
7 36
7.9%
8 24
 
5.3%
9 24
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
S 1
33.3%
K 1
33.3%
A 1
33.3%
Space Separator
ValueCountFrequency (%)
344
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 81
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1296
59.5%
Common 879
40.4%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 101
 
7.8%
인 97
 
7.5%
광 97
 
7.5%
천 97
 
7.5%
역 96
 
7.4%
시 96
 
7.4%
미 96
 
7.4%
추 96
 
7.4%
홀 96
 
7.4%
구 96
 
7.4%
Other values (72) 328
25.3%
Common
ValueCountFrequency (%)
344
39.1%
1 89
 
10.1%
- 81
 
9.2%
2 63
 
7.2%
6 47
 
5.3%
4 46
 
5.2%
3 44
 
5.0%
0 42
 
4.8%
5 38
 
4.3%
7 36
 
4.1%
Other values (3) 49
 
5.6%
Latin
ValueCountFrequency (%)
S 1
33.3%
K 1
33.3%
A 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1296
59.5%
ASCII 882
40.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
344
39.0%
1 89
 
10.1%
- 81
 
9.2%
2 63
 
7.1%
6 47
 
5.3%
4 46
 
5.2%
3 44
 
5.0%
0 42
 
4.8%
5 38
 
4.3%
7 36
 
4.1%
Other values (6) 52
 
5.9%
Hangul
ValueCountFrequency (%)
동 101
 
7.8%
인 97
 
7.5%
광 97
 
7.5%
천 97
 
7.5%
역 96
 
7.4%
시 96
 
7.4%
미 96
 
7.4%
추 96
 
7.4%
홀 96
 
7.4%
구 96
 
7.4%
Other values (72) 328
25.3%

도로명주소
Text

MISSING 

Distinct85
Distinct (%)98.8%
Missing10
Missing (%)10.4%
Memory size900.0 B
2023-12-13T00:21:20.419311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length31
Mean length24.104651
Min length17

Characters and Unicode

Total characters2073
Distinct characters133
Distinct categories6 ?
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 미추홀구 아암대로29번길 16 엑슬루타워 102동
2nd row인천광역시 미추홀구 미추홀대로575번길 116 103호
3rd row인천광역시 미추홀구 주안중로 25 신성쇼핑 102호
4th row인천광역시 미추홀구 인주대로45번길 39-1
5th row인천광역시 미추홀구 문학길125번길 33-21
ValueCountFrequency (%)
인천광역시 86
20.4%
미추홀구 86
20.4%
석정로 7
 
1.7%
1층 6
 
1.4%
학익소로 4
 
1.0%
경인로 4
 
1.0%
102동 4
 
1.0%
소성로 4
 
1.0%
석바위로 4
 
1.0%
주안로 3
 
0.7%
Other values (185) 213
50.6%
2023-12-13T00:21:20.936510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
335
 
16.2%
인 104
 
5.0%
미 91
 
4.4%
추 90
 
4.3%
홀 90
 
4.3%
천 89
 
4.3%
광 87
 
4.2%
역 86
 
4.1%
시 86
 
4.1%
구 86
 
4.1%
Other values (123) 929
44.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1309
63.1%
Decimal Number 394
 
19.0%
Space Separator 335
 
16.2%
Dash Punctuation 23
 
1.1%
Uppercase Letter 10
 
0.5%
Lowercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 104
 
7.9%
미 91
 
7.0%
추 90
 
6.9%
홀 90
 
6.9%
천 89
 
6.8%
광 87
 
6.6%
역 86
 
6.6%
시 86
 
6.6%
구 86
 
6.6%
로 79
 
6.0%
Other values (102) 421
32.2%
Decimal Number
ValueCountFrequency (%)
1 82
20.8%
2 54
13.7%
3 50
12.7%
4 40
10.2%
0 37
9.4%
5 32
 
8.1%
7 30
 
7.6%
6 24
 
6.1%
8 23
 
5.8%
9 22
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
S 3
30.0%
K 2
20.0%
A 1
 
10.0%
W 1
 
10.0%
V 1
 
10.0%
I 1
 
10.0%
E 1
 
10.0%
Lowercase Letter
ValueCountFrequency (%)
k 1
50.0%
y 1
50.0%
Space Separator
ValueCountFrequency (%)
335
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1309
63.1%
Common 752
36.3%
Latin 12
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 104
 
7.9%
미 91
 
7.0%
추 90
 
6.9%
홀 90
 
6.9%
천 89
 
6.8%
광 87
 
6.6%
역 86
 
6.6%
시 86
 
6.6%
구 86
 
6.6%
로 79
 
6.0%
Other values (102) 421
32.2%
Common
ValueCountFrequency (%)
335
44.5%
1 82
 
10.9%
2 54
 
7.2%
3 50
 
6.6%
4 40
 
5.3%
0 37
 
4.9%
5 32
 
4.3%
7 30
 
4.0%
6 24
 
3.2%
8 23
 
3.1%
Other values (2) 45
 
6.0%
Latin
ValueCountFrequency (%)
S 3
25.0%
K 2
16.7%
A 1
 
8.3%
W 1
 
8.3%
k 1
 
8.3%
y 1
 
8.3%
V 1
 
8.3%
I 1
 
8.3%
E 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1309
63.1%
ASCII 764
36.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
335
43.8%
1 82
 
10.7%
2 54
 
7.1%
3 50
 
6.5%
4 40
 
5.2%
0 37
 
4.8%
5 32
 
4.2%
7 30
 
3.9%
6 24
 
3.1%
8 23
 
3.0%
Other values (11) 57
 
7.5%
Hangul
ValueCountFrequency (%)
인 104
 
7.9%
미 91
 
7.0%
추 90
 
6.9%
홀 90
 
6.9%
천 89
 
6.8%
광 87
 
6.6%
역 86
 
6.6%
시 86
 
6.6%
구 86
 
6.6%
로 79
 
6.0%
Other values (102) 421
32.2%

전화번호
Text

MISSING 

Distinct84
Distinct (%)100.0%
Missing12
Missing (%)12.5%
Memory size900.0 B
2023-12-13T00:21:21.227656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length13.095238
Min length9

Characters and Unicode

Total characters1100
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

Unique84 ?
Unique (%)100.0%

Sample

1st row032-889-7721
2nd row070-4834-2221
3rd row0507-1472-9550
4th row0507-1316-3433
5th row070-4834-4400
ValueCountFrequency (%)
070-7980-7912 1
 
1.2%
032-876-3434 1
 
1.2%
070-4542-8621 1
 
1.2%
070-4538-5971 1
 
1.2%
0505-150-8282 1
 
1.2%
0507-1334-8213 1
 
1.2%
032-207-8709 1
 
1.2%
0507-1313-9448 1
 
1.2%
0507-1429-8311 1
 
1.2%
032-435-0069 1
 
1.2%
Other values (74) 74
88.1%
2023-12-13T00:21:21.720911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 195
17.7%
- 167
15.2%
7 123
11.2%
3 98
8.9%
4 95
8.6%
1 92
8.4%
5 91
8.3%
2 86
7.8%
8 71
 
6.5%
9 41
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 933
84.8%
Dash Punctuation 167
 
15.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 195
20.9%
7 123
13.2%
3 98
10.5%
4 95
10.2%
1 92
9.9%
5 91
9.8%
2 86
9.2%
8 71
 
7.6%
9 41
 
4.4%
6 41
 
4.4%
Dash Punctuation
ValueCountFrequency (%)
- 167
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1100
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 195
17.7%
- 167
15.2%
7 123
11.2%
3 98
8.9%
4 95
8.6%
1 92
8.4%
5 91
8.3%
2 86
7.8%
8 71
 
6.5%
9 41
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1100
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 195
17.7%
- 167
15.2%
7 123
11.2%
3 98
8.9%
4 95
8.6%
1 92
8.4%
5 91
8.3%
2 86
7.8%
8 71
 
6.5%
9 41
 
3.7%

Interactions

2023-12-13T00:21:17.762820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:21:21.841826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번상호명지번주소도로명주소전화번호
연번1.0000.7890.7820.9381.000
상호명0.7891.0000.9430.9931.000
지번주소0.7820.9431.0001.0001.000
도로명주소0.9380.9931.0001.0001.000
전화번호1.0001.0001.0001.0001.000

Missing values

2023-12-13T00:21:17.897402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:21:18.024346image/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.
2023-12-13T00:21:18.125694image/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

연번상호명지번주소도로명주소전화번호
01컴퓨터수리인천광역시 미추홀구 용현동 659 엑슬루타워 102동인천광역시 미추홀구 아암대로29번길 16 엑슬루타워 102동032-889-7721
12컴퓨터수리인천광역시 미추홀구 주안동 1420-6 103호인천광역시 미추홀구 미추홀대로575번길 116 103호070-4834-2221
23컴퓨터수리인천광역시 미추홀구 주안동 169 신성쇼핑 102호인천광역시 미추홀구 주안중로 25 신성쇼핑 102호0507-1472-9550
34컴퓨터수리인천광역시 미추홀구 숭의동 339-6인천광역시 미추홀구 인주대로45번길 39-10507-1316-3433
45컴퓨터수리인천광역시 미추홀구 문학동 396-2인천광역시 미추홀구 문학길125번길 33-21070-4834-4400
56컴퓨터수리인천광역시 미추홀구 도화동 103-27인천광역시 미추홀구 석정로 2580507-1380-0830
67컴퓨터수리인천광역시 미추홀구 주안동 206-10인천광역시 미추홀구 석바위로 58-1 영빌딩 7층 712-2호0507-1355-4688
78컴퓨터수리인천광역시 미추홀구 문학동 367-6인천광역시 미추홀구 문학길 9-240507-1447-4181
89컴퓨터수리인천광역시 미추홀구 용현동 621-5인천광역시 미추홀구 토금중로40번길 4070-4516-0641
910컴퓨터수리인천광역시 미추홀구 숭의동 203-31인천광역시 미추홀구 독정이로 75070-7944-4877
연번상호명지번주소도로명주소전화번호
8687Luv피씨인천광역시 미추홀구 주안동 22-5 1층 1호인천광역시 미추홀구 석정로440번길 20<NA>
8788뚱보컴퓨터인천광역시 미추홀구 용현동 87-31 1층 뚱보컴퓨터인천광역시 미추홀구 재넘이길 142 1층 뚱보컴퓨터0507-1388-3340
8889미로컴인천광역시 미추홀구 학익동 52-5 신동아쇼핑센터 104호인천광역시 미추홀구 매소홀로 473 신동아쇼핑센터 104호032-866-1891
8990원픽컴퓨터인천광역시 미추홀구 주안동 5-2 101-1호인천광역시 미추홀구 염전로 330 101-1호<NA>
9091진인천광역시 미추홀구 용현동 165-3 4호 컴퓨터전문점인천광역시 미추홀구 인하로 47 4호 컴퓨터전문점0507-1347-0777
9192미라클컴퓨터인천광역시 미추홀구 도화동 90-7인천광역시 미추홀구 석정로 224032-882-3902
9293로민컴퓨터인천광역시 미추홀구 학익동 252-9 5층 502호인천광역시 미추홀구 소성로 164 5층 502호<NA>
9394다나컴퓨터 인천점인천광역시 미추홀구 주안동 1571-24인천광역시 미추홀구 인하로 385 101호0507-1436-8223
9495가온시스템인천광역시 미추홀구 주안동 453-187인천광역시 미추홀구 독정이로33번길 39070-7622-9535
9596필존컴퍼니인천광역시 미추홀구 주안동 169 신성쇼핑타워 217호인천광역시 미추홀구 주안중로 25 신성타워 217호0507-1359-0300