Overview

Dataset statistics

Number of variables7
Number of observations2695
Missing cells4764
Missing cells (%)25.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory155.4 KiB
Average record size in memory59.0 B

Variable types

Numeric2
Categorical2
Text2
Unsupported1

Dataset

Description경상남도 창원시 공중위생업 현황(업종명, 업소명, 주소)입니다.
Author경상남도 창원시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15006846

Alerts

업소일련번호 is highly overall correlated with 구청별High correlation
구청별 is highly overall correlated with 업소일련번호High correlation
업소일련번호 has 2064 (76.6%) missing valuesMissing
비고 has 2695 (100.0%) missing valuesMissing
비고 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-11 00:13:52.367382
Analysis finished2023-12-11 00:13:54.067125
Duration1.7 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소일련번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct137
Distinct (%)21.7%
Missing2064
Missing (%)76.6%
Infinite0
Infinite (%)0.0%
Mean38.41046
Minimum1
Maximum217
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.8 KiB
2023-12-11T09:13:54.152107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q110
median25
Q351
95-th percentile117
Maximum217
Range216
Interquartile range (IQR)41

Descriptive statistics

Standard deviation40.289128
Coefficient of variation (CV)1.0489103
Kurtosis4.1490408
Mean38.41046
Median Absolute Deviation (MAD)18
Skewness1.8918982
Sum24237
Variance1623.2138
MonotonicityNot monotonic
2023-12-11T09:13:54.294876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 33
 
1.2%
2 22
 
0.8%
5 16
 
0.6%
9 16
 
0.6%
3 15
 
0.6%
6 15
 
0.6%
4 15
 
0.6%
17 14
 
0.5%
7 13
 
0.5%
16 12
 
0.4%
Other values (127) 460
 
17.1%
(Missing) 2064
76.6%
ValueCountFrequency (%)
1 33
1.2%
2 22
0.8%
3 15
0.6%
4 15
0.6%
5 16
0.6%
6 15
0.6%
7 13
 
0.5%
8 12
 
0.4%
9 16
0.6%
10 9
 
0.3%
ValueCountFrequency (%)
217 1
< 0.1%
214 1
< 0.1%
210 1
< 0.1%
209 1
< 0.1%
205 2
0.1%
204 1
< 0.1%
198 1
< 0.1%
197 1
< 0.1%
189 1
< 0.1%
186 1
< 0.1%

연번
Real number (ℝ)

Distinct631
Distinct (%)23.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean275.42486
Minimum1
Maximum631
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.8 KiB
2023-12-11T09:13:54.440160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile27.7
Q1135
median270
Q3405
95-th percentile548.3
Maximum631
Range630
Interquartile range (IQR)270

Descriptive statistics

Standard deviation164.11489
Coefficient of variation (CV)0.59586084
Kurtosis-1.0436988
Mean275.42486
Median Absolute Deviation (MAD)135
Skewness0.14328022
Sum742270
Variance26933.697
MonotonicityNot monotonic
2023-12-11T09:13:54.626696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 5
 
0.2%
269 5
 
0.2%
279 5
 
0.2%
278 5
 
0.2%
277 5
 
0.2%
276 5
 
0.2%
275 5
 
0.2%
274 5
 
0.2%
273 5
 
0.2%
272 5
 
0.2%
Other values (621) 2645
98.1%
ValueCountFrequency (%)
1 5
0.2%
2 5
0.2%
3 5
0.2%
4 5
0.2%
5 5
0.2%
6 5
0.2%
7 5
0.2%
8 5
0.2%
9 5
0.2%
10 5
0.2%
ValueCountFrequency (%)
631 1
< 0.1%
630 1
< 0.1%
629 1
< 0.1%
628 1
< 0.1%
627 1
< 0.1%
626 1
< 0.1%
625 1
< 0.1%
624 1
< 0.1%
623 1
< 0.1%
622 1
< 0.1%

구청별
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size21.2 KiB
의창구
631 
성산구
575 
마산회원구
573 
마산합포구
509 
진해구
407 

Length

Max length5
Median length3
Mean length3.8029685
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
의창구 631
23.4%
성산구 575
21.3%
마산회원구 573
21.3%
마산합포구 509
18.9%
진해구 407
15.1%

Length

2023-12-11T09:13:54.807414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:13:54.932478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
의창구 631
23.4%
성산구 575
21.3%
마산회원구 573
21.3%
마산합포구 509
18.9%
진해구 407
15.1%

업종명
Categorical

Distinct7
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size21.2 KiB
미용업(일반)
1202 
미용업
626 
미용업(피부)
423 
미용업(종합)
405 
미용업(손톱ㆍ발톱)
 
24
Other values (2)
 
15

Length

Max length19
Median length7
Mean length6.1632653
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row미용업(종합)
2nd row미용업(종합)
3rd row미용업(종합)
4th row미용업(종합)
5th row미용업(종합)

Common Values

ValueCountFrequency (%)
미용업(일반) 1202
44.6%
미용업 626
23.2%
미용업(피부) 423
 
15.7%
미용업(종합) 405
 
15.0%
미용업(손톱ㆍ발톱) 24
 
0.9%
미용업(일반), 미용업(손톱ㆍ발톱) 14
 
0.5%
미용업(일반), 미용업(피부) 1
 
< 0.1%

Length

2023-12-11T09:13:55.074006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:13:55.238098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미용업(일반 1217
44.9%
미용업 626
23.1%
미용업(피부 424
 
15.6%
미용업(종합 405
 
14.9%
미용업(손톱ㆍ발톱 38
 
1.4%

업소명
Text

Distinct2485
Distinct (%)92.2%
Missing0
Missing (%)0.0%
Memory size21.2 KiB
2023-12-11T09:13:55.618835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length22
Mean length5.8664193
Min length1

Characters and Unicode

Total characters15810
Distinct characters665
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2337 ?
Unique (%)86.7%

Sample

1st row무궁화미장원
2nd row세라미용실
3rd row장미미장원
4th row새자유미용실
5th row모아미용실
ValueCountFrequency (%)
헤어 46
 
1.5%
미용실 32
 
1.0%
헤어샵 20
 
0.7%
에스테틱 15
 
0.5%
스킨케어 14
 
0.5%
hair 13
 
0.4%
피부관리실 10
 
0.3%
네일 9
 
0.3%
8
 
0.3%
태후사랑 8
 
0.3%
Other values (2588) 2896
94.3%
2023-12-11T09:13:56.205471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
어 1321
 
8.4%
헤 1238
 
7.8%
미 705
 
4.5%
실 538
 
3.4%
용 505
 
3.2%
스 401
 
2.5%
리 396
 
2.5%
378
 
2.4%
샵 275
 
1.7%
이 229
 
1.4%
Other values (655) 9824
62.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14533
91.9%
Space Separator 378
 
2.4%
Lowercase Letter 312
 
2.0%
Uppercase Letter 289
 
1.8%
Other Punctuation 85
 
0.5%
Close Punctuation 79
 
0.5%
Open Punctuation 79
 
0.5%
Decimal Number 45
 
0.3%
Dash Punctuation 7
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
어 1321
 
9.1%
헤 1238
 
8.5%
미 705
 
4.9%
실 538
 
3.7%
용 505
 
3.5%
스 401
 
2.8%
리 396
 
2.7%
샵 275
 
1.9%
이 229
 
1.6%
라 202
 
1.4%
Other values (585) 8723
60.0%
Lowercase Letter
ValueCountFrequency (%)
a 44
14.1%
i 41
13.1%
e 37
11.9%
o 23
7.4%
r 23
7.4%
n 21
 
6.7%
l 20
 
6.4%
h 18
 
5.8%
y 15
 
4.8%
t 15
 
4.8%
Other values (13) 55
17.6%
Uppercase Letter
ValueCountFrequency (%)
S 38
13.1%
J 32
 
11.1%
H 22
 
7.6%
B 17
 
5.9%
A 17
 
5.9%
N 16
 
5.5%
C 16
 
5.5%
O 15
 
5.2%
K 14
 
4.8%
M 14
 
4.8%
Other values (13) 88
30.4%
Other Punctuation
ValueCountFrequency (%)
& 44
51.8%
. 19
22.4%
# 7
 
8.2%
, 5
 
5.9%
' 4
 
4.7%
% 2
 
2.4%
· 2
 
2.4%
: 1
 
1.2%
? 1
 
1.2%
Decimal Number
ValueCountFrequency (%)
0 11
24.4%
1 10
22.2%
2 7
15.6%
5 4
 
8.9%
4 3
 
6.7%
3 3
 
6.7%
8 3
 
6.7%
9 3
 
6.7%
6 1
 
2.2%
Space Separator
ValueCountFrequency (%)
378
100.0%
Close Punctuation
ValueCountFrequency (%)
) 79
100.0%
Open Punctuation
ValueCountFrequency (%)
( 79
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14521
91.8%
Common 675
 
4.3%
Latin 602
 
3.8%
Han 12
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
어 1321
 
9.1%
헤 1238
 
8.5%
미 705
 
4.9%
실 538
 
3.7%
용 505
 
3.5%
스 401
 
2.8%
리 396
 
2.7%
샵 275
 
1.9%
이 229
 
1.6%
라 202
 
1.4%
Other values (578) 8711
60.0%
Latin
ValueCountFrequency (%)
a 44
 
7.3%
i 41
 
6.8%
S 38
 
6.3%
e 37
 
6.1%
J 32
 
5.3%
o 23
 
3.8%
r 23
 
3.8%
H 22
 
3.7%
n 21
 
3.5%
l 20
 
3.3%
Other values (37) 301
50.0%
Common
ValueCountFrequency (%)
378
56.0%
) 79
 
11.7%
( 79
 
11.7%
& 44
 
6.5%
. 19
 
2.8%
0 11
 
1.6%
1 10
 
1.5%
- 7
 
1.0%
2 7
 
1.0%
# 7
 
1.0%
Other values (13) 34
 
5.0%
Han
ValueCountFrequency (%)
美 6
50.0%
人 1
 
8.3%
利 1
 
8.3%
男 1
 
8.3%
子 1
 
8.3%
喜 1
 
8.3%
秀 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14521
91.8%
ASCII 1274
 
8.1%
CJK 12
 
0.1%
None 2
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
어 1321
 
9.1%
헤 1238
 
8.5%
미 705
 
4.9%
실 538
 
3.7%
용 505
 
3.5%
스 401
 
2.8%
리 396
 
2.7%
샵 275
 
1.9%
이 229
 
1.6%
라 202
 
1.4%
Other values (578) 8711
60.0%
ASCII
ValueCountFrequency (%)
378
29.7%
) 79
 
6.2%
( 79
 
6.2%
& 44
 
3.5%
a 44
 
3.5%
i 41
 
3.2%
S 38
 
3.0%
e 37
 
2.9%
J 32
 
2.5%
o 23
 
1.8%
Other values (58) 479
37.6%
CJK
ValueCountFrequency (%)
美 6
50.0%
人 1
 
8.3%
利 1
 
8.3%
男 1
 
8.3%
子 1
 
8.3%
喜 1
 
8.3%
秀 1
 
8.3%
None
ValueCountFrequency (%)
· 2
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

업소소재지(도로명)
Text

Distinct2662
Distinct (%)99.0%
Missing5
Missing (%)0.2%
Memory size21.2 KiB
2023-12-11T09:13:56.669705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length50
Mean length33.726766
Min length18

Characters and Unicode

Total characters90725
Distinct characters389
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2635 ?
Unique (%)98.0%

Sample

1st row 창원시 의창구 의안로27번길 13 (중동)
2nd row 창원시 의창구 서상로 55 (서상동)
3rd row 창원시 의창구 북면 천주로 1118-1
4th row 창원시 의창구 대원로93번길 1 (대원동,동양상가 A동 1층 C부분 제3호)
5th row 창원시 의창구 대원로64번길 1-9 (대원동,지하1층)
ValueCountFrequency (%)
창원시 2687
 
15.2%
경상남도 1552
 
8.8%
의창구 631
 
3.6%
마산회원구 573
 
3.2%
성산구 570
 
3.2%
마산합포구 500
 
2.8%
1층 408
 
2.3%
진해구 407
 
2.3%
상남동 136
 
0.8%
내서읍 136
 
0.8%
Other values (3044) 10127
57.1%
2023-12-11T09:13:57.322096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15928
 
17.6%
1 3910
 
4.3%
원 3818
 
4.2%
창 3499
 
3.9%
동 3321
 
3.7%
구 2843
 
3.1%
) 2769
 
3.1%
( 2768
 
3.1%
시 2762
 
3.0%
상 2707
 
3.0%
Other values (379) 46400
51.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 52819
58.2%
Space Separator 15928
 
17.6%
Decimal Number 13499
 
14.9%
Close Punctuation 2769
 
3.1%
Open Punctuation 2768
 
3.1%
Other Punctuation 2291
 
2.5%
Dash Punctuation 472
 
0.5%
Uppercase Letter 145
 
0.2%
Lowercase Letter 31
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 3818
 
7.2%
창 3499
 
6.6%
동 3321
 
6.3%
구 2843
 
5.4%
시 2762
 
5.2%
상 2707
 
5.1%
남 2112
 
4.0%
산 2087
 
4.0%
로 1963
 
3.7%
도 1694
 
3.2%
Other values (338) 26013
49.2%
Uppercase Letter
ValueCountFrequency (%)
A 75
51.7%
B 23
 
15.9%
C 13
 
9.0%
T 8
 
5.5%
L 7
 
4.8%
S 3
 
2.1%
P 3
 
2.1%
H 2
 
1.4%
N 2
 
1.4%
K 2
 
1.4%
Other values (7) 7
 
4.8%
Decimal Number
ValueCountFrequency (%)
1 3910
29.0%
2 2117
15.7%
3 1410
 
10.4%
0 1375
 
10.2%
4 942
 
7.0%
5 928
 
6.9%
6 781
 
5.8%
7 746
 
5.5%
8 691
 
5.1%
9 599
 
4.4%
Other Punctuation
ValueCountFrequency (%)
, 2206
96.3%
· 48
 
2.1%
' 22
 
1.0%
@ 7
 
0.3%
. 6
 
0.3%
/ 2
 
0.1%
Lowercase Letter
ValueCountFrequency (%)
a 30
96.8%
c 1
 
3.2%
Space Separator
ValueCountFrequency (%)
15928
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2769
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2768
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 472
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 52819
58.2%
Common 37730
41.6%
Latin 176
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 3818
 
7.2%
창 3499
 
6.6%
동 3321
 
6.3%
구 2843
 
5.4%
시 2762
 
5.2%
상 2707
 
5.1%
남 2112
 
4.0%
산 2087
 
4.0%
로 1963
 
3.7%
도 1694
 
3.2%
Other values (338) 26013
49.2%
Common
ValueCountFrequency (%)
15928
42.2%
1 3910
 
10.4%
) 2769
 
7.3%
( 2768
 
7.3%
, 2206
 
5.8%
2 2117
 
5.6%
3 1410
 
3.7%
0 1375
 
3.6%
4 942
 
2.5%
5 928
 
2.5%
Other values (12) 3377
 
9.0%
Latin
ValueCountFrequency (%)
A 75
42.6%
a 30
 
17.0%
B 23
 
13.1%
C 13
 
7.4%
T 8
 
4.5%
L 7
 
4.0%
S 3
 
1.7%
P 3
 
1.7%
H 2
 
1.1%
N 2
 
1.1%
Other values (9) 10
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 52819
58.2%
ASCII 37858
41.7%
None 48
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15928
42.1%
1 3910
 
10.3%
) 2769
 
7.3%
( 2768
 
7.3%
, 2206
 
5.8%
2 2117
 
5.6%
3 1410
 
3.7%
0 1375
 
3.6%
4 942
 
2.5%
5 928
 
2.5%
Other values (30) 3505
 
9.3%
Hangul
ValueCountFrequency (%)
원 3818
 
7.2%
창 3499
 
6.6%
동 3321
 
6.3%
구 2843
 
5.4%
시 2762
 
5.2%
상 2707
 
5.1%
남 2112
 
4.0%
산 2087
 
4.0%
로 1963
 
3.7%
도 1694
 
3.2%
Other values (338) 26013
49.2%
None
ValueCountFrequency (%)
· 48
100.0%

비고
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2695
Missing (%)100.0%
Memory size23.8 KiB

Interactions

2023-12-11T09:13:53.415631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:13:53.144431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:13:53.554187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:13:53.271922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T09:13:57.454893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소일련번호연번구청별업종명
업소일련번호1.0000.682NaN0.429
연번0.6821.0000.3830.601
구청별NaN0.3831.0000.585
업종명0.4290.6010.5851.000
2023-12-11T09:13:57.595858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구청별업종명
구청별1.0000.426
업종명0.4261.000
2023-12-11T09:13:57.693052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소일련번호연번구청별업종명
업소일련번호1.000-0.3621.0000.191
연번-0.3621.0000.1680.358
구청별1.0000.1681.0000.426
업종명0.1910.3580.4261.000

Missing values

2023-12-11T09:13:53.723974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:13:53.881068image/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.
2023-12-11T09:13:54.000456image/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

업소일련번호연번구청별업종명업소명업소소재지(도로명)비고
041의창구미용업(종합)무궁화미장원창원시 의창구 의안로27번길 13 (중동)<NA>
162의창구미용업(종합)세라미용실창원시 의창구 서상로 55 (서상동)<NA>
213의창구미용업(종합)장미미장원창원시 의창구 북면 천주로 1118-1<NA>
324의창구미용업(종합)새자유미용실창원시 의창구 대원로93번길 1 (대원동,동양상가 A동 1층 C부분 제3호)<NA>
415의창구미용업(종합)모아미용실창원시 의창구 대원로64번길 1-9 (대원동,지하1층)<NA>
556의창구미용업(종합)김아람미용실창원시 의창구 소계로84번길 3 (소계동,진한빌딩 102호)<NA>
687의창구미용업(종합)초원미용실창원시 의창구 의안로31번길 2 (중동)<NA>
798의창구미용업(종합)이화헤어스튜디오창원시 의창구 의창대로261번길 24 (소답동,행운빌라상가102)<NA>
879의창구미용업(종합)로데오헤어라인미용실창원시 의창구 소계로 97 (소계동)<NA>
91010의창구미용업(종합)보람미용실창원시 의창구 의안로 15 (중동,성동아파트102호)<NA>
업소일련번호연번구청별업종명업소명업소소재지(도로명)비고
2685<NA>398진해구미용업(종합)퀸즈헤나경상남도 창원시 진해구 풍호로3번길 6, 풍산상가동 1층 108호 (풍호동)<NA>
2686<NA>399진해구미용업(종합)엄지공주경상남도 창원시 진해구 충장로 325, 1층 105호 (경화동, 한빛프라자)<NA>
2687<NA>400진해구미용업(종합)현경뷰티샵경상남도 창원시 진해구 진해대로801번길 7, 1층 (석동, 크리스탈빌)<NA>
2688<NA>401진해구미용업(종합)노랑머리경상남도 창원시 진해구 냉천로 107, 2층 203호 (석동, 롬타워)<NA>
2689<NA>402진해구미용업(종합)메이드헤어경상남도 창원시 진해구 진해대로 980-7, 4층 (자은동)<NA>
2690<NA>403진해구미용업(일반), 미용업(피부)다올스킨케어경상남도 창원시 진해구 태평로 28, 1층 (태평동)<NA>
2691<NA>404진해구미용업(일반), 미용업(손톱ㆍ발톱)덕산헤어스토리경상남도 창원시 진해구 진해대로 945, 201호 (자은동, 덕산해군아파트 상가동)<NA>
2692<NA>405진해구미용업(일반), 미용업(손톱ㆍ발톱)슈가네일아트경상남도 창원시 진해구 진해대로 762, 지1층 (석동, 진해미래쇼핑센터 B101-1호일부, B101-2호일부)<NA>
2693<NA>406진해구미용업(일반), 미용업(손톱ㆍ발톱)네일라떼경상남도 창원시 진해구 냉천로 87, 1층 106호 (석동, 와이존빌딩)<NA>
2694<NA>407진해구미용업(일반), 미용업(손톱ㆍ발톱)아로마뷰티샵경상남도 창원시 진해구 벚꽃로60번길 22-1, 1층 (송학동)<NA>