Overview

Dataset statistics

Number of variables5
Number of observations230
Missing cells48
Missing cells (%)4.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.1 KiB
Average record size in memory40.6 B

Variable types

Categorical1
Text4

Alerts

소재지전화 has 46 (20.0%) missing valuesMissing

Reproduction

Analysis started2024-01-09 21:27:47.292108
Analysis finished2024-01-09 21:27:47.801951
Duration0.51 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

Distinct15
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
미용업
111 
일반미용업
64 
피부미용업
22 
종합미용업
 
11
네일미용업
 
7
Other values (10)
15 

Length

Max length23
Median length19
Mean length4.8652174
Min length3

Unique

Unique6 ?
Unique (%)2.6%

Sample

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

Common Values

ValueCountFrequency (%)
미용업 111
48.3%
일반미용업 64
27.8%
피부미용업 22
 
9.6%
종합미용업 11
 
4.8%
네일미용업 7
 
3.0%
일반미용업, 네일미용업, 화장ㆍ분장 미용업 3
 
1.3%
화장ㆍ분장 미용업 2
 
0.9%
일반미용업, 피부미용업, 네일미용업 2
 
0.9%
피부미용업, 네일미용업, 화장ㆍ분장 미용업 2
 
0.9%
일반미용업, 피부미용업 1
 
0.4%
Other values (5) 5
 
2.2%

Length

2024-01-10T06:27:47.857727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
미용업 122
46.6%
일반미용업 72
27.5%
피부미용업 30
 
11.5%
네일미용업 16
 
6.1%
종합미용업 11
 
4.2%
화장ㆍ분장 11
 
4.2%

업소명
Text

Distinct228
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2024-01-10T06:27:48.051636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length18
Mean length5.7043478
Min length1

Characters and Unicode

Total characters1312
Distinct characters315
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique226 ?
Unique (%)98.3%

Sample

1st row평화미용실
2nd row미도미용실
3rd row동은미용실
4th row한진
5th row현대미용실
ValueCountFrequency (%)
hair 4
 
1.5%
우리미용실 2
 
0.8%
스타일 2
 
0.8%
제일 2
 
0.8%
어쩌다힐링 1
 
0.4%
읍내점 1
 
0.4%
에벤에셀 1
 
0.4%
헤어클리닉 1
 
0.4%
평화미용실 1
 
0.4%
리유헤어(reyou 1
 
0.4%
Other values (244) 244
93.8%
2024-01-10T06:27:48.363705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
어 89
 
6.8%
헤 87
 
6.6%
미 50
 
3.8%
리 39
 
3.0%
용 35
 
2.7%
실 33
 
2.5%
30
 
2.3%
이 24
 
1.8%
샵 24
 
1.8%
) 20
 
1.5%
Other values (305) 881
67.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1096
83.5%
Lowercase Letter 76
 
5.8%
Uppercase Letter 52
 
4.0%
Space Separator 30
 
2.3%
Close Punctuation 20
 
1.5%
Open Punctuation 20
 
1.5%
Other Punctuation 10
 
0.8%
Decimal Number 7
 
0.5%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
어 89
 
8.1%
헤 87
 
7.9%
미 50
 
4.6%
리 39
 
3.6%
용 35
 
3.2%
실 33
 
3.0%
이 24
 
2.2%
샵 24
 
2.2%
일 17
 
1.6%
아 16
 
1.5%
Other values (254) 682
62.2%
Lowercase Letter
ValueCountFrequency (%)
i 10
13.2%
e 10
13.2%
a 8
10.5%
r 7
9.2%
t 6
7.9%
n 5
6.6%
y 5
6.6%
l 5
6.6%
h 4
 
5.3%
s 4
 
5.3%
Other values (8) 12
15.8%
Uppercase Letter
ValueCountFrequency (%)
H 6
11.5%
T 4
 
7.7%
J 4
 
7.7%
I 4
 
7.7%
A 4
 
7.7%
L 4
 
7.7%
U 3
 
5.8%
R 3
 
5.8%
C 3
 
5.8%
N 3
 
5.8%
Other values (8) 14
26.9%
Decimal Number
ValueCountFrequency (%)
7 1
14.3%
6 1
14.3%
4 1
14.3%
9 1
14.3%
1 1
14.3%
5 1
14.3%
3 1
14.3%
Other Punctuation
ValueCountFrequency (%)
& 6
60.0%
, 2
 
20.0%
' 1
 
10.0%
# 1
 
10.0%
Space Separator
ValueCountFrequency (%)
30
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1096
83.5%
Latin 127
 
9.7%
Common 88
 
6.7%
Greek 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
어 89
 
8.1%
헤 87
 
7.9%
미 50
 
4.6%
리 39
 
3.6%
용 35
 
3.2%
실 33
 
3.0%
이 24
 
2.2%
샵 24
 
2.2%
일 17
 
1.6%
아 16
 
1.5%
Other values (254) 682
62.2%
Latin
ValueCountFrequency (%)
i 10
 
7.9%
e 10
 
7.9%
a 8
 
6.3%
r 7
 
5.5%
H 6
 
4.7%
t 6
 
4.7%
n 5
 
3.9%
y 5
 
3.9%
l 5
 
3.9%
T 4
 
3.1%
Other values (25) 61
48.0%
Common
ValueCountFrequency (%)
30
34.1%
) 20
22.7%
( 20
22.7%
& 6
 
6.8%
, 2
 
2.3%
' 1
 
1.1%
+ 1
 
1.1%
7 1
 
1.1%
# 1
 
1.1%
6 1
 
1.1%
Other values (5) 5
 
5.7%
Greek
ValueCountFrequency (%)
α 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1096
83.5%
ASCII 215
 
16.4%
None 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
어 89
 
8.1%
헤 87
 
7.9%
미 50
 
4.6%
리 39
 
3.6%
용 35
 
3.2%
실 33
 
3.0%
이 24
 
2.2%
샵 24
 
2.2%
일 17
 
1.6%
아 16
 
1.5%
Other values (254) 682
62.2%
ASCII
ValueCountFrequency (%)
30
 
14.0%
) 20
 
9.3%
( 20
 
9.3%
i 10
 
4.7%
e 10
 
4.7%
a 8
 
3.7%
r 7
 
3.3%
H 6
 
2.8%
t 6
 
2.8%
& 6
 
2.8%
Other values (40) 92
42.8%
None
ValueCountFrequency (%)
α 1
100.0%

업소소재지(도로명)
Text

Distinct218
Distinct (%)95.2%
Missing1
Missing (%)0.4%
Memory size1.9 KiB
2024-01-10T06:27:48.540621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length42
Mean length23.244541
Min length18

Characters and Unicode

Total characters5323
Distinct characters138
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique207 ?
Unique (%)90.4%

Sample

1st row충청남도 예산군 예산읍 주교로 57
2nd row충청남도 예산군 예산읍 예산로176번길 37
3rd row충청남도 예산군 예산읍 천변로 196
4th row충청남도 예산군 고덕면 고덕중앙로 58-1
5th row충청남도 예산군 덕산면 봉운로 27-1
ValueCountFrequency (%)
충청남도 229
18.7%
예산군 229
18.7%
예산읍 153
 
12.5%
삽교읍 30
 
2.4%
덕산면 24
 
2.0%
역전로 17
 
1.4%
예산로 16
 
1.3%
아리랑로 14
 
1.1%
벚꽃로155번길 13
 
1.1%
주교로 12
 
1.0%
Other values (267) 489
39.9%
2024-01-10T06:27:48.817952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
997
18.7%
산 448
 
8.4%
예 427
 
8.0%
1 260
 
4.9%
청 239
 
4.5%
충 233
 
4.4%
군 231
 
4.3%
남 230
 
4.3%
도 229
 
4.3%
로 216
 
4.1%
Other values (128) 1813
34.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3345
62.8%
Space Separator 997
 
18.7%
Decimal Number 844
 
15.9%
Dash Punctuation 56
 
1.1%
Other Punctuation 48
 
0.9%
Close Punctuation 12
 
0.2%
Open Punctuation 12
 
0.2%
Uppercase Letter 9
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 448
13.4%
예 427
12.8%
청 239
 
7.1%
충 233
 
7.0%
군 231
 
6.9%
남 230
 
6.9%
도 229
 
6.8%
로 216
 
6.5%
읍 183
 
5.5%
길 62
 
1.9%
Other values (107) 847
25.3%
Decimal Number
ValueCountFrequency (%)
1 260
30.8%
2 119
14.1%
5 86
 
10.2%
4 75
 
8.9%
3 67
 
7.9%
0 62
 
7.3%
6 53
 
6.3%
9 46
 
5.5%
7 44
 
5.2%
8 32
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
B 4
44.4%
A 1
 
11.1%
C 1
 
11.1%
N 1
 
11.1%
L 1
 
11.1%
H 1
 
11.1%
Space Separator
ValueCountFrequency (%)
997
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 56
100.0%
Other Punctuation
ValueCountFrequency (%)
, 48
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3345
62.8%
Common 1969
37.0%
Latin 9
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 448
13.4%
예 427
12.8%
청 239
 
7.1%
충 233
 
7.0%
군 231
 
6.9%
남 230
 
6.9%
도 229
 
6.8%
로 216
 
6.5%
읍 183
 
5.5%
길 62
 
1.9%
Other values (107) 847
25.3%
Common
ValueCountFrequency (%)
997
50.6%
1 260
 
13.2%
2 119
 
6.0%
5 86
 
4.4%
4 75
 
3.8%
3 67
 
3.4%
0 62
 
3.1%
- 56
 
2.8%
6 53
 
2.7%
, 48
 
2.4%
Other values (5) 146
 
7.4%
Latin
ValueCountFrequency (%)
B 4
44.4%
A 1
 
11.1%
C 1
 
11.1%
N 1
 
11.1%
L 1
 
11.1%
H 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3345
62.8%
ASCII 1978
37.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
997
50.4%
1 260
 
13.1%
2 119
 
6.0%
5 86
 
4.3%
4 75
 
3.8%
3 67
 
3.4%
0 62
 
3.1%
- 56
 
2.8%
6 53
 
2.7%
, 48
 
2.4%
Other values (11) 155
 
7.8%
Hangul
ValueCountFrequency (%)
산 448
13.4%
예 427
12.8%
청 239
 
7.1%
충 233
 
7.0%
군 231
 
6.9%
남 230
 
6.9%
도 229
 
6.8%
로 216
 
6.5%
읍 183
 
5.5%
길 62
 
1.9%
Other values (107) 847
25.3%

업소소재지(지번)
Text

Distinct203
Distinct (%)88.6%
Missing1
Missing (%)0.4%
Memory size1.9 KiB
2024-01-10T06:27:49.121227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length35
Mean length23.580786
Min length20

Characters and Unicode

Total characters5400
Distinct characters106
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

Unique185 ?
Unique (%)80.8%

Sample

1st row충청남도 예산군 예산읍 예산리 215-7
2nd row충청남도 예산군 예산읍 예산리 448-1
3rd row충청남도 예산군 예산읍 예산리 268
4th row충청남도 예산군 고덕면 대천리 786
5th row충청남도 예산군 덕산면 읍내리 341-4
ValueCountFrequency (%)
충청남도 229
19.4%
예산군 229
19.4%
예산읍 153
13.0%
예산리 55
 
4.7%
산성리 48
 
4.1%
삽교읍 31
 
2.6%
주교리 26
 
2.2%
덕산면 24
 
2.0%
읍내리 22
 
1.9%
목리 17
 
1.4%
Other values (243) 344
29.2%
2024-01-10T06:27:49.544877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1175
21.8%
산 512
 
9.5%
예 439
 
8.1%
리 232
 
4.3%
충 229
 
4.2%
남 229
 
4.2%
도 229
 
4.2%
군 229
 
4.2%
청 229
 
4.2%
읍 206
 
3.8%
Other values (96) 1691
31.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3101
57.4%
Space Separator 1175
 
21.8%
Decimal Number 933
 
17.3%
Dash Punctuation 186
 
3.4%
Uppercase Letter 4
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 512
16.5%
예 439
14.2%
리 232
7.5%
충 229
7.4%
남 229
7.4%
도 229
7.4%
군 229
7.4%
청 229
7.4%
읍 206
6.6%
교 57
 
1.8%
Other values (79) 510
16.4%
Decimal Number
ValueCountFrequency (%)
1 176
18.9%
2 126
13.5%
3 104
11.1%
4 95
10.2%
5 92
9.9%
7 83
8.9%
0 72
7.7%
6 69
 
7.4%
8 64
 
6.9%
9 52
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
L 1
25.0%
H 1
25.0%
C 1
25.0%
N 1
25.0%
Space Separator
ValueCountFrequency (%)
1175
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 186
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3101
57.4%
Common 2295
42.5%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 512
16.5%
예 439
14.2%
리 232
7.5%
충 229
7.4%
남 229
7.4%
도 229
7.4%
군 229
7.4%
청 229
7.4%
읍 206
6.6%
교 57
 
1.8%
Other values (79) 510
16.4%
Common
ValueCountFrequency (%)
1175
51.2%
- 186
 
8.1%
1 176
 
7.7%
2 126
 
5.5%
3 104
 
4.5%
4 95
 
4.1%
5 92
 
4.0%
7 83
 
3.6%
0 72
 
3.1%
6 69
 
3.0%
Other values (3) 117
 
5.1%
Latin
ValueCountFrequency (%)
L 1
25.0%
H 1
25.0%
C 1
25.0%
N 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3101
57.4%
ASCII 2299
42.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1175
51.1%
- 186
 
8.1%
1 176
 
7.7%
2 126
 
5.5%
3 104
 
4.5%
4 95
 
4.1%
5 92
 
4.0%
7 83
 
3.6%
0 72
 
3.1%
6 69
 
3.0%
Other values (7) 121
 
5.3%
Hangul
ValueCountFrequency (%)
산 512
16.5%
예 439
14.2%
리 232
7.5%
충 229
7.4%
남 229
7.4%
도 229
7.4%
군 229
7.4%
청 229
7.4%
읍 206
6.6%
교 57
 
1.8%
Other values (79) 510
16.4%

소재지전화
Text

MISSING 

Distinct184
Distinct (%)100.0%
Missing46
Missing (%)20.0%
Memory size1.9 KiB
2024-01-10T06:27:49.771650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length14.25
Min length12

Characters and Unicode

Total characters2622
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique184 ?
Unique (%)100.0%

Sample

1st row041- 334-8111
2nd row041- 335-3882
3rd row041- 332-1632
4th row041- 337-8110
5th row041- 338-1177
ValueCountFrequency (%)
041 179
41.3%
333 13
 
3.0%
338 10
 
2.3%
337 10
 
2.3%
331 9
 
2.1%
334 9
 
2.1%
332 8
 
1.8%
335 8
 
1.8%
3833 2
 
0.5%
070 2
 
0.5%
Other values (183) 183
42.3%
2024-01-10T06:27:50.101983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 485
18.5%
411
15.7%
- 368
14.0%
1 269
10.3%
0 264
10.1%
4 261
10.0%
5 114
 
4.3%
7 109
 
4.2%
8 108
 
4.1%
2 99
 
3.8%
Other values (2) 134
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1843
70.3%
Space Separator 411
 
15.7%
Dash Punctuation 368
 
14.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 485
26.3%
1 269
14.6%
0 264
14.3%
4 261
14.2%
5 114
 
6.2%
7 109
 
5.9%
8 108
 
5.9%
2 99
 
5.4%
6 78
 
4.2%
9 56
 
3.0%
Space Separator
ValueCountFrequency (%)
411
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 368
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2622
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 485
18.5%
411
15.7%
- 368
14.0%
1 269
10.3%
0 264
10.1%
4 261
10.0%
5 114
 
4.3%
7 109
 
4.2%
8 108
 
4.1%
2 99
 
3.8%
Other values (2) 134
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2622
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 485
18.5%
411
15.7%
- 368
14.0%
1 269
10.3%
0 264
10.1%
4 261
10.0%
5 114
 
4.3%
7 109
 
4.2%
8 108
 
4.1%
2 99
 
3.8%
Other values (2) 134
 
5.1%

Missing values

2024-01-10T06:27:47.623142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T06:27:47.692942image/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.
2024-01-10T06:27:47.763147image/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

업종명업소명업소소재지(도로명)업소소재지(지번)소재지전화
0미용업평화미용실충청남도 예산군 예산읍 주교로 57충청남도 예산군 예산읍 예산리 215-7041- 334-8111
1미용업미도미용실충청남도 예산군 예산읍 예산로176번길 37충청남도 예산군 예산읍 예산리 448-1041- 335-3882
2미용업동은미용실충청남도 예산군 예산읍 천변로 196충청남도 예산군 예산읍 예산리 268041- 332-1632
3미용업한진충청남도 예산군 고덕면 고덕중앙로 58-1충청남도 예산군 고덕면 대천리 786041- 337-8110
4미용업현대미용실충청남도 예산군 덕산면 봉운로 27-1충청남도 예산군 덕산면 읍내리 341-4041- 338-1177
5미용업문화충청남도 예산군 예산읍 주교로 42충청남도 예산군 예산읍 주교리 204-1041- 334-8304
6미용업송월미용실충청남도 예산군 예산읍 산성천길 3충청남도 예산군 예산읍 산성리 342-5041- 334-5690
7미용업미충청남도 예산군 삽교읍 삽교로 99충청남도 예산군 삽교읍 두리 570-47041- 338-2551
8미용업대우충청남도 예산군 예산읍 신례원로 164충청남도 예산군 예산읍 신례원리 284-7041- 334-6644
9미용업헤어로드충청남도 예산군 예산읍 예산로176번길 28-1충청남도 예산군 예산읍 예산리 401-2041- 333-4284
업종명업소명업소소재지(도로명)업소소재지(지번)소재지전화
220피부미용업, 화장ㆍ분장 미용업콤마브로우충청남도 예산군 예산읍 역전로 150-2충청남도 예산군 예산읍 산성리 704<NA>
221네일미용업, 화장ㆍ분장 미용업네일,그대와충청남도 예산군 예산읍 역전로 133, 2호충청남도 예산군 예산읍 산성리 820 우주빌딩<NA>
222일반미용업, 피부미용업, 네일미용업네일러브충청남도 예산군 예산읍 벚꽃로155번길 43충청남도 예산군 예산읍 산성리 638041- 331-4321
223일반미용업, 피부미용업, 네일미용업어쩌다힐링충청남도 예산군 덕산면 온천단지1로 43충청남도 예산군 덕산면 사동리 384041 -337 -3884
224일반미용업, 피부미용업, 화장ㆍ분장 미용업인(in)뷰티&왁싱충청남도 예산군 덕산면 충의로 3, 102호충청남도 예산군 덕산면 읍내리 268-4<NA>
225일반미용업, 네일미용업, 화장ㆍ분장 미용업쩡쓰(쩡's)헤어충청남도 예산군 예산읍 예산로 146충청남도 예산군 예산읍 예산리 710-1041 -332 -1909
226일반미용업, 네일미용업, 화장ㆍ분장 미용업추송하네일헤어샵충청남도 예산군 예산읍 예산로 224충청남도 예산군 예산읍 예산리 515-1<NA>
227일반미용업, 네일미용업, 화장ㆍ분장 미용업채움뷰티케어충청남도 예산군 덕산면 시량부흥길 75-16충청남도 예산군 덕산면 시량리 15-8<NA>
228피부미용업, 네일미용업, 화장ㆍ분장 미용업정네일&피부충청남도 예산군 덕산면 덕산온천로 455충청남도 예산군 덕산면 읍내리 235-9<NA>
229피부미용업, 네일미용업, 화장ㆍ분장 미용업푸른달Nail충청남도 예산군 예산읍 벚꽃로155번길 18-4, 102호충청남도 예산군 예산읍 발연리 85-11041 -331 -0459