Overview

Dataset statistics

Number of variables5
Number of observations230
Missing cells1
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.1 KiB
Average record size in memory40.6 B

Variable types

Categorical1
Text4

Reproduction

Analysis started2024-01-09 21:27:50.739787
Analysis finished2024-01-09 21:27:51.174016
Duration0.43 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

2024-01-10T06:27:51.243430image/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
2024-01-10T06:27:51.468116image/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%
2024-01-10T06:27:51.770215image/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
2024-01-10T06:27:51.944265image/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%
2024-01-10T06:27:52.217200image/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

Distinct204
Distinct (%)88.7%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2024-01-10T06:27:52.528754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length35
Mean length23.508696
Min length7

Characters and Unicode

Total characters5407
Distinct characters111
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

Unique186 ?
Unique (%)80.9%

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 (245) 346
29.3%
2024-01-10T06:27:52.948097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1176
21.7%
산 512
 
9.5%
예 439
 
8.1%
리 232
 
4.3%
충 229
 
4.2%
군 229
 
4.2%
청 229
 
4.2%
도 229
 
4.2%
남 229
 
4.2%
읍 206
 
3.8%
Other values (101) 1697
31.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3107
57.5%
Space Separator 1176
 
21.7%
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
14.1%
리 232
7.5%
충 229
7.4%
군 229
7.4%
청 229
7.4%
도 229
7.4%
남 229
7.4%
읍 206
 
6.6%
교 57
 
1.8%
Other values (84) 516
16.6%
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 (%)
1176
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 186
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3107
57.5%
Common 2296
42.5%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 512
16.5%
예 439
14.1%
리 232
7.5%
충 229
7.4%
군 229
7.4%
청 229
7.4%
도 229
7.4%
남 229
7.4%
읍 206
 
6.6%
교 57
 
1.8%
Other values (84) 516
16.6%
Common
ValueCountFrequency (%)
1176
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 3107
57.5%
ASCII 2300
42.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1176
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
14.1%
리 232
7.5%
충 229
7.4%
군 229
7.4%
청 229
7.4%
도 229
7.4%
남 229
7.4%
읍 206
 
6.6%
교 57
 
1.8%
Other values (84) 516
16.6%

소재지전화
Text

Distinct184
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2024-01-10T06:27:53.172888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.013043
Min length7

Characters and Unicode

Total characters2533
Distinct characters18
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique182 ?
Unique (%)79.1%

Sample

1st row041-334-8111
2nd row041-335-3882
3rd row041-332-1632
4th row041-337-8110
5th row041-338-1177
ValueCountFrequency (%)
데이터 46
 
16.7%
미집계 46
 
16.7%
041-332-9355 2
 
0.7%
041-333-3833 1
 
0.4%
041-338-4784 1
 
0.4%
041-333-5536 1
 
0.4%
041-338-9535 1
 
0.4%
041-335-7781 1
 
0.4%
041-337-2772 1
 
0.4%
041-331-0068 1
 
0.4%
Other values (175) 175
63.4%
2024-01-10T06:27:53.497530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 485
19.1%
- 368
14.5%
1 269
10.6%
0 264
10.4%
4 261
10.3%
5 114
 
4.5%
7 109
 
4.3%
8 108
 
4.3%
2 99
 
3.9%
6 78
 
3.1%
Other values (8) 378
14.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1843
72.8%
Dash Punctuation 368
 
14.5%
Other Letter 276
 
10.9%
Space Separator 46
 
1.8%

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%
Other Letter
ValueCountFrequency (%)
이 46
16.7%
계 46
16.7%
집 46
16.7%
미 46
16.7%
터 46
16.7%
데 46
16.7%
Dash Punctuation
ValueCountFrequency (%)
- 368
100.0%
Space Separator
ValueCountFrequency (%)
46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2257
89.1%
Hangul 276
 
10.9%

Most frequent character per script

Common
ValueCountFrequency (%)
3 485
21.5%
- 368
16.3%
1 269
11.9%
0 264
11.7%
4 261
11.6%
5 114
 
5.1%
7 109
 
4.8%
8 108
 
4.8%
2 99
 
4.4%
6 78
 
3.5%
Other values (2) 102
 
4.5%
Hangul
ValueCountFrequency (%)
이 46
16.7%
계 46
16.7%
집 46
16.7%
미 46
16.7%
터 46
16.7%
데 46
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2257
89.1%
Hangul 276
 
10.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 485
21.5%
- 368
16.3%
1 269
11.9%
0 264
11.7%
4 261
11.6%
5 114
 
5.1%
7 109
 
4.8%
8 108
 
4.8%
2 99
 
4.4%
6 78
 
3.5%
Other values (2) 102
 
4.5%
Hangul
ValueCountFrequency (%)
이 46
16.7%
계 46
16.7%
집 46
16.7%
미 46
16.7%
터 46
16.7%
데 46
16.7%

Missing values

2024-01-10T06:27:51.074771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T06:27:51.145710image/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

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 704데이터 미집계
221네일미용업, 화장ㆍ분장 미용업네일,그대와충청남도 예산군 예산읍 역전로 133, 2호충청남도 예산군 예산읍 산성리 820 우주빌딩데이터 미집계
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 268-4데이터 미집계
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 515-1데이터 미집계
227일반미용업, 네일미용업, 화장ㆍ분장 미용업채움뷰티케어충청남도 예산군 덕산면 시량부흥길 75-16충청남도 예산군 덕산면 시량리 15-8데이터 미집계
228피부미용업, 네일미용업, 화장ㆍ분장 미용업정네일&피부충청남도 예산군 덕산면 덕산온천로 455충청남도 예산군 덕산면 읍내리 235-9데이터 미집계
229피부미용업, 네일미용업, 화장ㆍ분장 미용업푸른달Nail충청남도 예산군 예산읍 벚꽃로155번길 18-4, 102호충청남도 예산군 예산읍 발연리 85-11041-331-0459