Overview

Dataset statistics

Number of variables6
Number of observations120
Missing cells10
Missing cells (%)1.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.9 KiB
Average record size in memory50.1 B

Variable types

Numeric1
Categorical1
Text4

Dataset

Description이 자료는 연수구 관내 세탁업종 현황에 대한 데이터로 업종명, 업소명, 영업소 주소(도로명), 소재지 전화가 있는 자료입니다.
Author인천광역시 연수구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15038922&srcSe=7661IVAWM27C61E190

Alerts

업종명 has constant value ""Constant
소재지전화 has 10 (8.3%) missing valuesMissing
연번 has unique valuesUnique
영업소주소(도로명) has unique valuesUnique
영업소주소(지번) has unique valuesUnique

Reproduction

Analysis started2024-04-14 03:13:50.019446
Analysis finished2024-04-14 03:13:50.495966
Duration0.48 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct120
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean60.5
Minimum1
Maximum120
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-04-14T12:13:50.554858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.95
Q130.75
median60.5
Q390.25
95-th percentile114.05
Maximum120
Range119
Interquartile range (IQR)59.5

Descriptive statistics

Standard deviation34.785054
Coefficient of variation (CV)0.57495957
Kurtosis-1.2
Mean60.5
Median Absolute Deviation (MAD)30
Skewness0
Sum7260
Variance1210
MonotonicityStrictly increasing
2024-04-14T12:13:50.661583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.8%
62 1
 
0.8%
90 1
 
0.8%
89 1
 
0.8%
88 1
 
0.8%
87 1
 
0.8%
86 1
 
0.8%
85 1
 
0.8%
84 1
 
0.8%
83 1
 
0.8%
Other values (110) 110
91.7%
ValueCountFrequency (%)
1 1
0.8%
2 1
0.8%
3 1
0.8%
4 1
0.8%
5 1
0.8%
6 1
0.8%
7 1
0.8%
8 1
0.8%
9 1
0.8%
10 1
0.8%
ValueCountFrequency (%)
120 1
0.8%
119 1
0.8%
118 1
0.8%
117 1
0.8%
116 1
0.8%
115 1
0.8%
114 1
0.8%
113 1
0.8%
112 1
0.8%
111 1
0.8%

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
세탁업
120 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row세탁업
2nd row세탁업
3rd row세탁업
4th row세탁업
5th row세탁업

Common Values

ValueCountFrequency (%)
세탁업 120
100.0%

Length

2024-04-14T12:13:50.759453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-14T12:13:50.828994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
세탁업 120
100.0%

업소명
Text

Distinct114
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-04-14T12:13:51.031101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length10
Mean length6.3166667
Min length2

Characters and Unicode

Total characters758
Distinct characters209
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

Unique109 ?
Unique (%)90.8%

Sample

1st row현대퍼크로세탁소
2nd row안국사
3rd row선학 세탁
4th row에스케이뷰 세탁
5th row하야네
ValueCountFrequency (%)
세탁 13
 
8.0%
세탁소 9
 
5.6%
현대세탁소 3
 
1.9%
셀프 3
 
1.9%
크리닝 3
 
1.9%
세탁중 2
 
1.2%
금호세탁 2
 
1.2%
명품 2
 
1.2%
풍림세탁소 2
 
1.2%
더 2
 
1.2%
Other values (119) 121
74.7%
2024-04-14T12:13:51.371233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
세 98
 
12.9%
탁 97
 
12.8%
소 50
 
6.6%
42
 
5.5%
크 17
 
2.2%
대 15
 
2.0%
리 13
 
1.7%
이 12
 
1.6%
명 11
 
1.5%
품 11
 
1.5%
Other values (199) 392
51.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 672
88.7%
Space Separator 42
 
5.5%
Uppercase Letter 17
 
2.2%
Lowercase Letter 11
 
1.5%
Close Punctuation 5
 
0.7%
Open Punctuation 5
 
0.7%
Decimal Number 4
 
0.5%
Other Punctuation 1
 
0.1%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
세 98
 
14.6%
탁 97
 
14.4%
소 50
 
7.4%
크 17
 
2.5%
대 15
 
2.2%
리 13
 
1.9%
이 12
 
1.8%
명 11
 
1.6%
품 11
 
1.6%
린 10
 
1.5%
Other values (170) 338
50.3%
Uppercase Letter
ValueCountFrequency (%)
I 2
11.8%
S 2
11.8%
L 2
11.8%
C 1
 
5.9%
P 1
 
5.9%
O 1
 
5.9%
H 1
 
5.9%
Y 1
 
5.9%
R 1
 
5.9%
D 1
 
5.9%
Other values (4) 4
23.5%
Lowercase Letter
ValueCountFrequency (%)
n 3
27.3%
i 2
18.2%
e 2
18.2%
g 1
 
9.1%
a 1
 
9.1%
l 1
 
9.1%
h 1
 
9.1%
Decimal Number
ValueCountFrequency (%)
3 2
50.0%
1 1
25.0%
2 1
25.0%
Space Separator
ValueCountFrequency (%)
42
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Other Punctuation
ValueCountFrequency (%)
? 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 672
88.7%
Common 58
 
7.7%
Latin 28
 
3.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
세 98
 
14.6%
탁 97
 
14.4%
소 50
 
7.4%
크 17
 
2.5%
대 15
 
2.2%
리 13
 
1.9%
이 12
 
1.8%
명 11
 
1.6%
품 11
 
1.6%
린 10
 
1.5%
Other values (170) 338
50.3%
Latin
ValueCountFrequency (%)
n 3
 
10.7%
i 2
 
7.1%
I 2
 
7.1%
S 2
 
7.1%
e 2
 
7.1%
L 2
 
7.1%
g 1
 
3.6%
a 1
 
3.6%
l 1
 
3.6%
C 1
 
3.6%
Other values (11) 11
39.3%
Common
ValueCountFrequency (%)
42
72.4%
) 5
 
8.6%
( 5
 
8.6%
3 2
 
3.4%
1 1
 
1.7%
2 1
 
1.7%
? 1
 
1.7%
- 1
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 672
88.7%
ASCII 86
 
11.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
세 98
 
14.6%
탁 97
 
14.4%
소 50
 
7.4%
크 17
 
2.5%
대 15
 
2.2%
리 13
 
1.9%
이 12
 
1.8%
명 11
 
1.6%
품 11
 
1.6%
린 10
 
1.5%
Other values (170) 338
50.3%
ASCII
ValueCountFrequency (%)
42
48.8%
) 5
 
5.8%
( 5
 
5.8%
n 3
 
3.5%
i 2
 
2.3%
I 2
 
2.3%
S 2
 
2.3%
e 2
 
2.3%
3 2
 
2.3%
L 2
 
2.3%
Other values (19) 19
22.1%

영업소주소(도로명)
Text

UNIQUE 

Distinct120
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-04-14T12:13:51.602232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length73
Median length49
Mean length42.241667
Min length22

Characters and Unicode

Total characters5069
Distinct characters216
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique120 ?
Unique (%)100.0%

Sample

1st row인천광역시 연수구 원인재로 56 (동춘동)
2nd row인천광역시 연수구 원인재로 315 (연수동)
3rd row인천광역시 연수구 선학로 14 (선학동)
4th row인천광역시 연수구 랜드마크로 19 송도 SK VIEW 207호 (송도동 송도 SK VIEW)
5th row인천광역시 연수구 한나루로196번길 13-5 (옥련동)
ValueCountFrequency (%)
인천광역시 120
 
12.9%
연수구 120
 
12.9%
송도동 44
 
4.7%
1층 24
 
2.6%
연수동 24
 
2.6%
동춘동 19
 
2.0%
상가동 16
 
1.7%
송도 15
 
1.6%
원인재로 14
 
1.5%
옥련동 14
 
1.5%
Other values (342) 520
55.9%
2024-04-14T12:13:51.958475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
921
 
18.2%
1 252
 
5.0%
동 203
 
4.0%
( 149
 
2.9%
) 149
 
2.9%
연 149
 
2.9%
수 149
 
2.9%
인 138
 
2.7%
시 134
 
2.6%
로 133
 
2.6%
Other values (206) 2692
53.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2941
58.0%
Space Separator 921
 
18.2%
Decimal Number 853
 
16.8%
Open Punctuation 149
 
2.9%
Close Punctuation 149
 
2.9%
Uppercase Letter 33
 
0.7%
Dash Punctuation 12
 
0.2%
Other Punctuation 4
 
0.1%
Lowercase Letter 4
 
0.1%
Math Symbol 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 203
 
6.9%
연 149
 
5.1%
수 149
 
5.1%
인 138
 
4.7%
시 134
 
4.6%
로 133
 
4.5%
천 125
 
4.3%
광 121
 
4.1%
구 120
 
4.1%
역 120
 
4.1%
Other values (169) 1549
52.7%
Uppercase Letter
ValueCountFrequency (%)
B 4
12.1%
A 4
12.1%
L 3
9.1%
E 3
9.1%
I 3
9.1%
V 2
 
6.1%
K 2
 
6.1%
S 2
 
6.1%
W 2
 
6.1%
H 2
 
6.1%
Other values (5) 6
18.2%
Decimal Number
ValueCountFrequency (%)
1 252
29.5%
2 131
15.4%
0 118
13.8%
3 73
 
8.6%
5 61
 
7.2%
4 61
 
7.2%
7 49
 
5.7%
8 39
 
4.6%
9 35
 
4.1%
6 34
 
4.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
25.0%
t 1
25.0%
s 1
25.0%
a 1
25.0%
Other Punctuation
ValueCountFrequency (%)
@ 2
50.0%
. 1
25.0%
? 1
25.0%
Space Separator
ValueCountFrequency (%)
921
100.0%
Open Punctuation
ValueCountFrequency (%)
( 149
100.0%
Close Punctuation
ValueCountFrequency (%)
) 149
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2941
58.0%
Common 2091
41.3%
Latin 37
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 203
 
6.9%
연 149
 
5.1%
수 149
 
5.1%
인 138
 
4.7%
시 134
 
4.6%
로 133
 
4.5%
천 125
 
4.3%
광 121
 
4.1%
구 120
 
4.1%
역 120
 
4.1%
Other values (169) 1549
52.7%
Latin
ValueCountFrequency (%)
B 4
 
10.8%
A 4
 
10.8%
L 3
 
8.1%
E 3
 
8.1%
I 3
 
8.1%
V 2
 
5.4%
K 2
 
5.4%
S 2
 
5.4%
W 2
 
5.4%
H 2
 
5.4%
Other values (9) 10
27.0%
Common
ValueCountFrequency (%)
921
44.0%
1 252
 
12.1%
( 149
 
7.1%
) 149
 
7.1%
2 131
 
6.3%
0 118
 
5.6%
3 73
 
3.5%
5 61
 
2.9%
4 61
 
2.9%
7 49
 
2.3%
Other values (8) 127
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2941
58.0%
ASCII 2128
42.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
921
43.3%
1 252
 
11.8%
( 149
 
7.0%
) 149
 
7.0%
2 131
 
6.2%
0 118
 
5.5%
3 73
 
3.4%
5 61
 
2.9%
4 61
 
2.9%
7 49
 
2.3%
Other values (27) 164
 
7.7%
Hangul
ValueCountFrequency (%)
동 203
 
6.9%
연 149
 
5.1%
수 149
 
5.1%
인 138
 
4.7%
시 134
 
4.6%
로 133
 
4.5%
천 125
 
4.3%
광 121
 
4.1%
구 120
 
4.1%
역 120
 
4.1%
Other values (169) 1549
52.7%

영업소주소(지번)
Text

UNIQUE 

Distinct120
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-04-14T12:13:52.172818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length40
Mean length33.266667
Min length18

Characters and Unicode

Total characters3992
Distinct characters191
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique120 ?
Unique (%)100.0%

Sample

1st row인천광역시 연수구 동춘동 928-206
2nd row인천광역시 연수구 연수동 533
3rd row인천광역시 연수구 선학동 347
4th row인천광역시 연수구 송도동 315-1 송도 SK VIEW 207호
5th row인천광역시 연수구 옥련동 308-20
ValueCountFrequency (%)
인천광역시 120
 
15.4%
연수구 120
 
15.4%
송도동 44
 
5.6%
연수동 24
 
3.1%
동춘동 19
 
2.4%
상가동 14
 
1.8%
옥련동 14
 
1.8%
송도 13
 
1.7%
1층 13
 
1.7%
청학동 11
 
1.4%
Other values (305) 387
49.7%
2024-04-14T12:13:52.504980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
736
 
18.4%
1 232
 
5.8%
동 200
 
5.0%
연 148
 
3.7%
수 148
 
3.7%
시 124
 
3.1%
인 123
 
3.1%
천 123
 
3.1%
광 121
 
3.0%
역 120
 
3.0%
Other values (181) 1917
48.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2260
56.6%
Decimal Number 823
 
20.6%
Space Separator 736
 
18.4%
Dash Punctuation 79
 
2.0%
Close Punctuation 29
 
0.7%
Open Punctuation 29
 
0.7%
Uppercase Letter 28
 
0.7%
Lowercase Letter 4
 
0.1%
Other Punctuation 3
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 200
 
8.8%
연 148
 
6.5%
수 148
 
6.5%
시 124
 
5.5%
인 123
 
5.4%
천 123
 
5.4%
광 121
 
5.4%
역 120
 
5.3%
구 120
 
5.3%
호 95
 
4.2%
Other values (144) 938
41.5%
Uppercase Letter
ValueCountFrequency (%)
A 5
17.9%
B 4
14.3%
L 3
10.7%
H 2
 
7.1%
E 2
 
7.1%
I 2
 
7.1%
F 2
 
7.1%
G 1
 
3.6%
W 1
 
3.6%
V 1
 
3.6%
Other values (5) 5
17.9%
Decimal Number
ValueCountFrequency (%)
1 232
28.2%
0 103
12.5%
3 96
11.7%
2 92
 
11.2%
4 72
 
8.7%
5 66
 
8.0%
9 54
 
6.6%
6 47
 
5.7%
7 34
 
4.1%
8 27
 
3.3%
Lowercase Letter
ValueCountFrequency (%)
e 1
25.0%
t 1
25.0%
s 1
25.0%
a 1
25.0%
Other Punctuation
ValueCountFrequency (%)
@ 1
33.3%
. 1
33.3%
? 1
33.3%
Space Separator
ValueCountFrequency (%)
736
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 79
100.0%
Close Punctuation
ValueCountFrequency (%)
) 29
100.0%
Open Punctuation
ValueCountFrequency (%)
( 29
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2260
56.6%
Common 1700
42.6%
Latin 32
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 200
 
8.8%
연 148
 
6.5%
수 148
 
6.5%
시 124
 
5.5%
인 123
 
5.4%
천 123
 
5.4%
광 121
 
5.4%
역 120
 
5.3%
구 120
 
5.3%
호 95
 
4.2%
Other values (144) 938
41.5%
Latin
ValueCountFrequency (%)
A 5
15.6%
B 4
12.5%
L 3
 
9.4%
H 2
 
6.2%
E 2
 
6.2%
I 2
 
6.2%
F 2
 
6.2%
e 1
 
3.1%
t 1
 
3.1%
s 1
 
3.1%
Other values (9) 9
28.1%
Common
ValueCountFrequency (%)
736
43.3%
1 232
 
13.6%
0 103
 
6.1%
3 96
 
5.6%
2 92
 
5.4%
- 79
 
4.6%
4 72
 
4.2%
5 66
 
3.9%
9 54
 
3.2%
6 47
 
2.8%
Other values (8) 123
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2260
56.6%
ASCII 1732
43.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
736
42.5%
1 232
 
13.4%
0 103
 
5.9%
3 96
 
5.5%
2 92
 
5.3%
- 79
 
4.6%
4 72
 
4.2%
5 66
 
3.8%
9 54
 
3.1%
6 47
 
2.7%
Other values (27) 155
 
8.9%
Hangul
ValueCountFrequency (%)
동 200
 
8.8%
연 148
 
6.5%
수 148
 
6.5%
시 124
 
5.5%
인 123
 
5.4%
천 123
 
5.4%
광 121
 
5.4%
역 120
 
5.3%
구 120
 
5.3%
호 95
 
4.2%
Other values (144) 938
41.5%

소재지전화
Text

MISSING 

Distinct109
Distinct (%)99.1%
Missing10
Missing (%)8.3%
Memory size1.1 KiB
2024-04-14T12:13:52.690850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters1320
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

Unique108 ?
Unique (%)98.2%

Sample

1st row032-811-7946
2nd row032-811-1229
3rd row032-813-1467
4th row032-813-1416
5th row032-832-7669
ValueCountFrequency (%)
032-851-8899 2
 
1.8%
032-858-8844 1
 
0.9%
032-811-7946 1
 
0.9%
032-813-0496 1
 
0.9%
032-835-1000 1
 
0.9%
032-831-3330 1
 
0.9%
032-831-8182 1
 
0.9%
032-835-6606 1
 
0.9%
032-831-0705 1
 
0.9%
032-815-5427 1
 
0.9%
Other values (99) 99
90.0%
2024-04-14T12:13:52.966028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 220
16.7%
3 203
15.4%
2 173
13.1%
8 168
12.7%
0 159
12.0%
1 126
9.5%
5 63
 
4.8%
6 58
 
4.4%
9 56
 
4.2%
7 47
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1100
83.3%
Dash Punctuation 220
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 203
18.5%
2 173
15.7%
8 168
15.3%
0 159
14.5%
1 126
11.5%
5 63
 
5.7%
6 58
 
5.3%
9 56
 
5.1%
7 47
 
4.3%
4 47
 
4.3%
Dash Punctuation
ValueCountFrequency (%)
- 220
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1320
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 220
16.7%
3 203
15.4%
2 173
13.1%
8 168
12.7%
0 159
12.0%
1 126
9.5%
5 63
 
4.8%
6 58
 
4.4%
9 56
 
4.2%
7 47
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1320
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 220
16.7%
3 203
15.4%
2 173
13.1%
8 168
12.7%
0 159
12.0%
1 126
9.5%
5 63
 
4.8%
6 58
 
4.4%
9 56
 
4.2%
7 47
 
3.6%

Interactions

2024-04-14T12:13:50.302768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2024-04-14T12:13:50.386919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-14T12:13:50.464447image/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

연번업종명업소명영업소주소(도로명)영업소주소(지번)소재지전화
01세탁업현대퍼크로세탁소인천광역시 연수구 원인재로 56 (동춘동)인천광역시 연수구 동춘동 928-206032-811-7946
12세탁업안국사인천광역시 연수구 원인재로 315 (연수동)인천광역시 연수구 연수동 533032-811-1229
23세탁업선학 세탁인천광역시 연수구 선학로 14 (선학동)인천광역시 연수구 선학동 347032-813-1467
34세탁업에스케이뷰 세탁인천광역시 연수구 랜드마크로 19 송도 SK VIEW 207호 (송도동 송도 SK VIEW)인천광역시 연수구 송도동 315-1 송도 SK VIEW 207호032-813-1416
45세탁업하야네인천광역시 연수구 한나루로196번길 13-5 (옥련동)인천광역시 연수구 옥련동 308-20032-832-7669
56세탁업현대세탁소인천광역시 연수구 옥련로 33 상가동 (옥련동 현대1차아파트)인천광역시 연수구 옥련동 628 현대1차아파트 상가동032-833-5080
67세탁업금호세탁인천광역시 연수구 선학로 100 1층 2호 (선학동 금호타운상가)인천광역시 연수구 선학동 350 금호타운상가 2호032-814-7773
78세탁업충청유천빨래방인천광역시 연수구 먼우금로 302 상가동 (연수동 연수유천아파트)인천광역시 연수구 연수동 534 연수유천아파트 상가동032-816-8289
89세탁업유일세탁소인천광역시 연수구 청학로 23 (청학동)인천광역시 연수구 청학동 521-11032-833-2749
910세탁업빛나라 세탁소인천광역시 연수구 청학로16번길 61-1 (청학동)인천광역시 연수구 청학동 540-11 5통4반032-833-5849
연번업종명업소명영업소주소(도로명)영업소주소(지번)소재지전화
110111세탁업신(Shin)세탁인천광역시 연수구 랜드마크로 113 상가 A동 2층 217호 (송도동 e편한세상 송도)인천광역시 연수구 송도동 319-1 e편한세상 송도 상가A동 217호032-812-3365
111112세탁업세탁나라인천광역시 연수구 능허대로 343 상가동 103호 (동춘동 송도 파크레인 동일하이빌)인천광역시 연수구 동춘동 0 송도 파크레인 동일하이빌 상가동 103호032-832-1227
112113세탁업그린앙팡인천광역시 연수구 원인재로 180 상가동 지하10호 (연수동 연수우성2차아파트)인천광역시 연수구 연수동 634 연수우성2차아파트 상가동 지하10호<NA>
113114세탁업동남스포피아 세탁인천광역시 연수구 새말로 27 동남아파트 상가동 105호 (연수동)인천광역시 연수구 연수동 536 동남아파트 상가동동 105호032-812-0191
114115세탁업마리나 명품 세탁인천광역시 연수구 랜드마크로 160 1동 201호 (송도동 더샵 송도 마리나베이)인천광역시 연수구 송도동 308-1 더샵 송도 마리나베이 1동 201호<NA>
115116세탁업더 세탁(마리나베이점)인천광역시 연수구 랜드마크로 160 근린생활시설3동 106호 (송도동 더샵 송도 마리나베이)인천광역시 연수구 송도동 308-1 더샵 송도 마리나베이 근린생활시설3동 106호<NA>
116117세탁업랜드명품세탁인천광역시 연수구 랜드마크로 68 301동 1층 2호 (송도동 랜드마크시티센트럴더샵)인천광역시 연수구 송도동 311 랜드마크시티센트럴더샵 301동 1층 2호032-831-0022
117118세탁업푸르지오세탁인천광역시 연수구 송도문화로28번길 28 202동 1층 2-118호 (송도동 송도글로벌캠퍼스푸르지오)인천광역시 연수구 송도동 190-2 송도글로벌캠퍼스푸르지오 202동 2-118호032-851-8899
118119세탁업런더리샵(LAUNDRY SHOP)인천광역시 연수구 인천타워대로231번길 97 근린생활시설동 1층 106호 (송도동 더샵 송도프라임뷰 20BL)인천광역시 연수구 송도동 109 더샵 송도프라임뷰 20BL 근린생활시설동 106호<NA>
119120세탁업송도 명품세탁인천광역시 연수구 랜드마크로 20 111동 148호 (송도동 호반써밋 송도)인천광역시 연수구 송도동 312-1 호반써밋 송도 111동 148호<NA>