Overview

Dataset statistics

Number of variables7
Number of observations1246
Missing cells50
Missing cells (%)0.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory68.3 KiB
Average record size in memory56.1 B

Variable types

Text3
DateTime1
Categorical3

Dataset

Description경상남도 빅데이터 허브 플랫폼 DB 내 인허가 세탁업 중 정상 영업상태인 업장에 대한 데이터로, 사업장명, 주소, 인허가일자, 영업상태, 업태구분(일반세탁업, 운동화전문 등) 정보를 제공합니다.
Author경상남도
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15122483

Alerts

영업상태 has constant value ""Constant
상세영업상태 is highly overall correlated with 업태구분High correlation
업태구분 is highly overall correlated with 상세영업상태High correlation
상세영업상태 is highly imbalanced (96.1%)Imbalance
업태구분 is highly imbalanced (81.3%)Imbalance
도로명주소 has 43 (3.5%) missing valuesMissing

Reproduction

Analysis started2023-12-10 23:57:50.512644
Analysis finished2023-12-10 23:57:51.473169
Duration0.96 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사업장명
Text

Distinct1026
Distinct (%)82.3%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
2023-12-11T08:57:51.744520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length5.5088283
Min length2

Characters and Unicode

Total characters6864
Distinct characters426
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

Unique907 ?
Unique (%)72.8%

Sample

1st row한일세탁소
2nd row파파스클린(PAPAS Clean)
3rd row한일세탁소
4th row아림세탁소
5th row119세탁소
ValueCountFrequency (%)
현대세탁소 12
 
0.9%
세탁소 12
 
0.9%
백조세탁소 10
 
0.8%
제일세탁소 8
 
0.6%
서울세탁소 7
 
0.5%
대동세탁소 7
 
0.5%
대성세탁소 7
 
0.5%
월드크리닝 7
 
0.5%
백설세탁소 6
 
0.5%
운동화 6
 
0.5%
Other values (1042) 1236
93.8%
2023-12-11T08:57:52.295549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
세 915
 
13.3%
탁 895
 
13.0%
소 605
 
8.8%
리 142
 
2.1%
크 137
 
2.0%
터 114
 
1.7%
퓨 106
 
1.5%
동 103
 
1.5%
성 102
 
1.5%
컴 102
 
1.5%
Other values (416) 3643
53.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6663
97.1%
Space Separator 73
 
1.1%
Uppercase Letter 51
 
0.7%
Decimal Number 34
 
0.5%
Close Punctuation 17
 
0.2%
Open Punctuation 17
 
0.2%
Lowercase Letter 6
 
0.1%
Other Punctuation 2
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
세 915
 
13.7%
탁 895
 
13.4%
소 605
 
9.1%
리 142
 
2.1%
크 137
 
2.1%
터 114
 
1.7%
퓨 106
 
1.6%
동 103
 
1.5%
성 102
 
1.5%
컴 102
 
1.5%
Other values (377) 3442
51.7%
Uppercase Letter
ValueCountFrequency (%)
L 6
11.8%
O 5
 
9.8%
C 5
 
9.8%
A 4
 
7.8%
K 4
 
7.8%
E 4
 
7.8%
N 3
 
5.9%
P 3
 
5.9%
M 2
 
3.9%
S 2
 
3.9%
Other values (11) 13
25.5%
Decimal Number
ValueCountFrequency (%)
1 18
52.9%
2 5
 
14.7%
7 3
 
8.8%
9 3
 
8.8%
3 2
 
5.9%
4 1
 
2.9%
5 1
 
2.9%
0 1
 
2.9%
Lowercase Letter
ValueCountFrequency (%)
e 3
50.0%
l 1
 
16.7%
a 1
 
16.7%
n 1
 
16.7%
Other Punctuation
ValueCountFrequency (%)
& 1
50.0%
. 1
50.0%
Space Separator
ValueCountFrequency (%)
73
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6663
97.1%
Common 144
 
2.1%
Latin 57
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
세 915
 
13.7%
탁 895
 
13.4%
소 605
 
9.1%
리 142
 
2.1%
크 137
 
2.1%
터 114
 
1.7%
퓨 106
 
1.6%
동 103
 
1.5%
성 102
 
1.5%
컴 102
 
1.5%
Other values (377) 3442
51.7%
Latin
ValueCountFrequency (%)
L 6
 
10.5%
O 5
 
8.8%
C 5
 
8.8%
A 4
 
7.0%
K 4
 
7.0%
E 4
 
7.0%
N 3
 
5.3%
P 3
 
5.3%
e 3
 
5.3%
M 2
 
3.5%
Other values (15) 18
31.6%
Common
ValueCountFrequency (%)
73
50.7%
1 18
 
12.5%
) 17
 
11.8%
( 17
 
11.8%
2 5
 
3.5%
7 3
 
2.1%
9 3
 
2.1%
3 2
 
1.4%
4 1
 
0.7%
& 1
 
0.7%
Other values (4) 4
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6663
97.1%
ASCII 201
 
2.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
세 915
 
13.7%
탁 895
 
13.4%
소 605
 
9.1%
리 142
 
2.1%
크 137
 
2.1%
터 114
 
1.7%
퓨 106
 
1.6%
동 103
 
1.5%
성 102
 
1.5%
컴 102
 
1.5%
Other values (377) 3442
51.7%
ASCII
ValueCountFrequency (%)
73
36.3%
1 18
 
9.0%
) 17
 
8.5%
( 17
 
8.5%
L 6
 
3.0%
O 5
 
2.5%
2 5
 
2.5%
C 5
 
2.5%
A 4
 
2.0%
K 4
 
2.0%
Other values (29) 47
23.4%

지번주소
Text

Distinct1228
Distinct (%)99.1%
Missing7
Missing (%)0.6%
Memory size9.9 KiB
2023-12-11T08:57:52.759728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length48
Mean length27.149314
Min length17

Characters and Unicode

Total characters33638
Distinct characters340
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

Unique1218 ?
Unique (%)98.3%

Sample

1st row경상남도 거창군 거창읍 상림리 193-3번지
2nd row경상남도 창원시 마산회원구 구암동 278-2
3rd row경상남도 창원시 마산합포구 산호동 332 국제비치타운
4th row경상남도 거창군 거창읍 대동리 13-3번지
5th row경상남도 거창군 거창읍 중앙리 273-23번지
ValueCountFrequency (%)
경상남도 1239
 
18.8%
창원시 422
 
6.4%
김해시 179
 
2.7%
진주시 139
 
2.1%
의창구 117
 
1.8%
양산시 110
 
1.7%
1층 106
 
1.6%
마산회원구 95
 
1.4%
마산합포구 82
 
1.2%
거제시 72
 
1.1%
Other values (2019) 4022
61.1%
2023-12-11T08:57:53.360382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6463
19.2%
1 1596
 
4.7%
상 1550
 
4.6%
남 1333
 
4.0%
도 1288
 
3.8%
경 1258
 
3.7%
지 1222
 
3.6%
동 1155
 
3.4%
번 1105
 
3.3%
시 1080
 
3.2%
Other values (330) 15588
46.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19908
59.2%
Space Separator 6463
 
19.2%
Decimal Number 6085
 
18.1%
Dash Punctuation 1025
 
3.0%
Uppercase Letter 53
 
0.2%
Open Punctuation 36
 
0.1%
Close Punctuation 36
 
0.1%
Other Punctuation 28
 
0.1%
Lowercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 1550
 
7.8%
남 1333
 
6.7%
도 1288
 
6.5%
경 1258
 
6.3%
지 1222
 
6.1%
동 1155
 
5.8%
번 1105
 
5.6%
시 1080
 
5.4%
창 671
 
3.4%
원 571
 
2.9%
Other values (293) 8675
43.6%
Uppercase Letter
ValueCountFrequency (%)
A 14
26.4%
B 12
22.6%
T 5
 
9.4%
L 4
 
7.5%
C 3
 
5.7%
H 2
 
3.8%
I 2
 
3.8%
E 2
 
3.8%
Q 1
 
1.9%
X 1
 
1.9%
Other values (7) 7
13.2%
Decimal Number
ValueCountFrequency (%)
1 1596
26.2%
2 779
12.8%
3 607
 
10.0%
0 606
 
10.0%
4 506
 
8.3%
5 464
 
7.6%
6 454
 
7.5%
7 381
 
6.3%
9 349
 
5.7%
8 343
 
5.6%
Other Punctuation
ValueCountFrequency (%)
, 20
71.4%
* 5
 
17.9%
' 2
 
7.1%
. 1
 
3.6%
Lowercase Letter
ValueCountFrequency (%)
a 2
50.0%
e 2
50.0%
Space Separator
ValueCountFrequency (%)
6463
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1025
100.0%
Open Punctuation
ValueCountFrequency (%)
( 36
100.0%
Close Punctuation
ValueCountFrequency (%)
) 36
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 19908
59.2%
Common 13673
40.6%
Latin 57
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 1550
 
7.8%
남 1333
 
6.7%
도 1288
 
6.5%
경 1258
 
6.3%
지 1222
 
6.1%
동 1155
 
5.8%
번 1105
 
5.6%
시 1080
 
5.4%
창 671
 
3.4%
원 571
 
2.9%
Other values (293) 8675
43.6%
Latin
ValueCountFrequency (%)
A 14
24.6%
B 12
21.1%
T 5
 
8.8%
L 4
 
7.0%
C 3
 
5.3%
a 2
 
3.5%
H 2
 
3.5%
I 2
 
3.5%
E 2
 
3.5%
e 2
 
3.5%
Other values (9) 9
15.8%
Common
ValueCountFrequency (%)
6463
47.3%
1 1596
 
11.7%
- 1025
 
7.5%
2 779
 
5.7%
3 607
 
4.4%
0 606
 
4.4%
4 506
 
3.7%
5 464
 
3.4%
6 454
 
3.3%
7 381
 
2.8%
Other values (8) 792
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 19908
59.2%
ASCII 13730
40.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6463
47.1%
1 1596
 
11.6%
- 1025
 
7.5%
2 779
 
5.7%
3 607
 
4.4%
0 606
 
4.4%
4 506
 
3.7%
5 464
 
3.4%
6 454
 
3.3%
7 381
 
2.8%
Other values (27) 849
 
6.2%
Hangul
ValueCountFrequency (%)
상 1550
 
7.8%
남 1333
 
6.7%
도 1288
 
6.5%
경 1258
 
6.3%
지 1222
 
6.1%
동 1155
 
5.8%
번 1105
 
5.6%
시 1080
 
5.4%
창 671
 
3.4%
원 571
 
2.9%
Other values (293) 8675
43.6%

도로명주소
Text

MISSING 

Distinct1192
Distinct (%)99.1%
Missing43
Missing (%)3.5%
Memory size9.9 KiB
2023-12-11T08:57:53.834110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length49
Mean length29.594347
Min length18

Characters and Unicode

Total characters35602
Distinct characters377
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

Unique1182 ?
Unique (%)98.3%

Sample

1st row경상남도 거창군 거창읍 중앙로 66
2nd row경상남도 창원시 마산회원구 구암북2길 22, 1층 (구암동)
3rd row경상남도 창원시 마산합포구 합포동5길 22, 4동 1층 411호 (산호동, 국제비치타운)
4th row경상남도 거창군 거창읍 동동6길 77
5th row경상남도 거창군 거창읍 시장길 5
ValueCountFrequency (%)
경상남도 1203
 
16.4%
창원시 403
 
5.5%
1층 202
 
2.8%
김해시 180
 
2.5%
진주시 139
 
1.9%
의창구 116
 
1.6%
마산회원구 95
 
1.3%
양산시 91
 
1.2%
거제시 73
 
1.0%
마산합포구 69
 
0.9%
Other values (2099) 4759
64.9%
2023-12-11T08:57:54.436699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6129
 
17.2%
1 1625
 
4.6%
상 1502
 
4.2%
남 1383
 
3.9%
도 1260
 
3.5%
동 1241
 
3.5%
경 1232
 
3.5%
시 1063
 
3.0%
) 939
 
2.6%
( 939
 
2.6%
Other values (367) 18289
51.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 21124
59.3%
Space Separator 6129
 
17.2%
Decimal Number 5410
 
15.2%
Close Punctuation 939
 
2.6%
Open Punctuation 939
 
2.6%
Other Punctuation 690
 
1.9%
Dash Punctuation 316
 
0.9%
Uppercase Letter 49
 
0.1%
Lowercase Letter 4
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 1502
 
7.1%
남 1383
 
6.5%
도 1260
 
6.0%
동 1241
 
5.9%
경 1232
 
5.8%
시 1063
 
5.0%
로 869
 
4.1%
길 713
 
3.4%
창 686
 
3.2%
원 604
 
2.9%
Other values (330) 10571
50.0%
Uppercase Letter
ValueCountFrequency (%)
A 13
26.5%
B 10
20.4%
T 4
 
8.2%
C 3
 
6.1%
L 3
 
6.1%
D 3
 
6.1%
H 2
 
4.1%
I 2
 
4.1%
E 2
 
4.1%
V 1
 
2.0%
Other values (6) 6
12.2%
Decimal Number
ValueCountFrequency (%)
1 1625
30.0%
2 794
14.7%
3 538
 
9.9%
0 479
 
8.9%
5 433
 
8.0%
4 364
 
6.7%
7 323
 
6.0%
6 319
 
5.9%
8 277
 
5.1%
9 258
 
4.8%
Other Punctuation
ValueCountFrequency (%)
, 681
98.7%
· 4
 
0.6%
* 3
 
0.4%
' 2
 
0.3%
Lowercase Letter
ValueCountFrequency (%)
a 2
50.0%
e 2
50.0%
Space Separator
ValueCountFrequency (%)
6129
100.0%
Close Punctuation
ValueCountFrequency (%)
) 939
100.0%
Open Punctuation
ValueCountFrequency (%)
( 939
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 316
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 21124
59.3%
Common 14425
40.5%
Latin 53
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 1502
 
7.1%
남 1383
 
6.5%
도 1260
 
6.0%
동 1241
 
5.9%
경 1232
 
5.8%
시 1063
 
5.0%
로 869
 
4.1%
길 713
 
3.4%
창 686
 
3.2%
원 604
 
2.9%
Other values (330) 10571
50.0%
Common
ValueCountFrequency (%)
6129
42.5%
1 1625
 
11.3%
) 939
 
6.5%
( 939
 
6.5%
2 794
 
5.5%
, 681
 
4.7%
3 538
 
3.7%
0 479
 
3.3%
5 433
 
3.0%
4 364
 
2.5%
Other values (9) 1504
 
10.4%
Latin
ValueCountFrequency (%)
A 13
24.5%
B 10
18.9%
T 4
 
7.5%
C 3
 
5.7%
L 3
 
5.7%
D 3
 
5.7%
a 2
 
3.8%
H 2
 
3.8%
I 2
 
3.8%
E 2
 
3.8%
Other values (8) 9
17.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 21124
59.3%
ASCII 14474
40.7%
None 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6129
42.3%
1 1625
 
11.2%
) 939
 
6.5%
( 939
 
6.5%
2 794
 
5.5%
, 681
 
4.7%
3 538
 
3.7%
0 479
 
3.3%
5 433
 
3.0%
4 364
 
2.5%
Other values (26) 1553
 
10.7%
Hangul
ValueCountFrequency (%)
상 1502
 
7.1%
남 1383
 
6.5%
도 1260
 
6.0%
동 1241
 
5.9%
경 1232
 
5.8%
시 1063
 
5.0%
로 869
 
4.1%
길 713
 
3.4%
창 686
 
3.2%
원 604
 
2.9%
Other values (330) 10571
50.0%
None
ValueCountFrequency (%)
· 4
100.0%

인허가일자
Date

Distinct946
Distinct (%)75.9%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
Minimum1987-02-22 00:00:00
Maximum2022-11-30 00:00:00
2023-12-11T08:57:54.615033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:57:54.757734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

영업상태
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
영업/정상
1246 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영업/정상
2nd row영업/정상
3rd row영업/정상
4th row영업/정상
5th row영업/정상

Common Values

ValueCountFrequency (%)
영업/정상 1246
100.0%

Length

2023-12-11T08:57:54.907425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:57:55.024403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 1246
100.0%

상세영업상태
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
영업
1238 
영업중
 
4
변경
 
4

Length

Max length3
Median length2
Mean length2.0032103
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 1238
99.4%
영업중 4
 
0.3%
변경 4
 
0.3%

Length

2023-12-11T08:57:55.120028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:57:55.222613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 1238
99.4%
영업중 4
 
0.3%
변경 4
 
0.3%

업태구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
일반세탁업
1172 
운동화전문세탁업
 
31
빨래방업
 
18
세탁업 기타
 
17
<NA>
 
8

Length

Max length8
Median length5
Mean length5.0674157
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반세탁업 1172
94.1%
운동화전문세탁업 31
 
2.5%
빨래방업 18
 
1.4%
세탁업 기타 17
 
1.4%
<NA> 8
 
0.6%

Length

2023-12-11T08:57:55.358725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:57:55.480743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반세탁업 1172
92.8%
운동화전문세탁업 31
 
2.5%
빨래방업 18
 
1.4%
세탁업 17
 
1.3%
기타 17
 
1.3%
na 8
 
0.6%

Correlations

2023-12-11T08:57:55.553152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상세영업상태업태구분
상세영업상태1.000NaN
업태구분NaN1.000
2023-12-11T08:57:55.640874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상세영업상태업태구분
상세영업상태1.0001.000
업태구분1.0001.000
2023-12-11T08:57:55.736540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상세영업상태업태구분
상세영업상태1.0001.000
업태구분1.0001.000

Missing values

2023-12-11T08:57:51.202160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:57:51.316131image/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.
2023-12-11T08:57:51.415499image/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

사업장명지번주소도로명주소인허가일자영업상태상세영업상태업태구분
0한일세탁소경상남도 거창군 거창읍 상림리 193-3번지경상남도 거창군 거창읍 중앙로 661991-05-08영업/정상영업일반세탁업
1파파스클린(PAPAS Clean)경상남도 창원시 마산회원구 구암동 278-2경상남도 창원시 마산회원구 구암북2길 22, 1층 (구암동)2020-04-03영업/정상영업세탁업 기타
2한일세탁소경상남도 창원시 마산합포구 산호동 332 국제비치타운경상남도 창원시 마산합포구 합포동5길 22, 4동 1층 411호 (산호동, 국제비치타운)2010-12-07영업/정상영업일반세탁업
3아림세탁소경상남도 거창군 거창읍 대동리 13-3번지경상남도 거창군 거창읍 동동6길 772008-08-08영업/정상영업일반세탁업
4119세탁소경상남도 거창군 거창읍 중앙리 273-23번지경상남도 거창군 거창읍 시장길 52008-04-23영업/정상영업일반세탁업
5킹스세탁소빨래방<NA>경상남도 거창군 거창읍 수남로 2268, 1층2005-01-07영업/정상영업일반세탁업
6북부컴퓨터세탁소경상남도 거창군 거창읍 중앙리 43-13번지경상남도 거창군 거창읍 거열로 178-12003-01-20영업/정상영업일반세탁업
7금호세탁소경상남도 거창군 거창읍 상림리 570번지경상남도 거창군 거창읍 중앙로 182001-08-07영업/정상영업일반세탁업
8스타세탁소경상남도 거창군 거창읍 대동리 736번지경상남도 거창군 거창읍 강변로9길 89, 1층1999-05-14영업/정상영업일반세탁업
9코아루세탁소경상남도 거창군 거창읍 대평리 1513번지경상남도 거창군 거창읍 강남로 266, 107호1998-05-14영업/정상영업일반세탁업
사업장명지번주소도로명주소인허가일자영업상태상세영업상태업태구분
1236정우세탁산업경상남도 창원시 의창구 동읍 봉산리 153-1 1층경상남도 창원시 의창구 동읍 자여로 50-24, 1층2021-12-20영업/정상영업일반세탁업
1237대성크리닝경상남도 창원시 마산회원구 내서읍 삼계리 512경상남도 창원시 마산회원구 내서읍 숲속로 13-2, 1층2022-06-22영업/정상영업일반세탁업
1238워시워시경상남도 창원시 의창구 봉곡동 70-1경상남도 창원시 의창구 창이대로205번길 38, 1층 (봉곡동)2022-02-17영업/정상영업일반세탁업
1239아이이불 창원경상남도 창원시 의창구 서상동 579 2층경상남도 창원시 의창구 읍성로17번길 8-1, 2층 (서상동)2022-02-21영업/정상영업일반세탁업
1240시민세탁경상남도 진주시 평안동 57 1층경상남도 진주시 의곡길16번길 4, 1층 (평안동)2022-02-23영업/정상영업일반세탁업
1241대성크리닝 주식회사경상남도 창원시 마산합포구 진북면 대티리 518-1경상남도 창원시 마산합포구 진북면 대티3길 392010-08-11영업/정상영업일반세탁업
1242래더체인즈경상남도 창원시 마산합포구 중앙동1가 5-4경상남도 창원시 마산합포구 3·15대로 115-2, 1층 (중앙동1가)2022-04-14영업/정상영업일반세탁업
1243코코세탁경상남도 김해시 안동 333-2 대아아파트 상가경상남도 김해시 삼안로111번길 17, 대아아파트 상가 D동 1층 (안동)2022-05-06영업/정상영업일반세탁업
1244경남크린산업경상남도 김해시 진영읍 본산리 315-7경상남도 김해시 진영읍 본산2로79번길 212022-05-18영업/정상영업일반세탁업
1245영희네세탁경상남도 거제시 고현동 1003경상남도 거제시 중곡1로2길 12, 1층 (고현동)2022-05-23영업/정상영업일반세탁업