Overview

Dataset statistics

Number of variables5
Number of observations1982
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory77.6 KiB
Average record size in memory40.1 B

Variable types

Categorical1
DateTime1
Text3

Dataset

Description광주광역시 서구 공중위생업소에 대한 데이터로 광주광역시 서구의 공중위생업소의 업종명, 업소명, 주소 등의 현황입니다.
URLhttps://www.data.go.kr/data/15011782/fileData.do

Reproduction

Analysis started2023-12-12 02:56:41.626530
Analysis finished2023-12-12 02:56:42.756360
Duration1.13 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

Distinct21
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
일반미용업
773 
피부미용업
260 
세탁업
193 
숙박업(일반)
140 
네일미용업
137 
Other values (16)
479 

Length

Max length23
Median length5
Mean length5.9762866
Min length3

Unique

Unique2 ?
Unique (%)0.1%

Sample

1st row숙박업(일반)
2nd row일반미용업
3rd row세탁업
4th row건물위생관리업
5th row건물위생관리업

Common Values

ValueCountFrequency (%)
일반미용업 773
39.0%
피부미용업 260
 
13.1%
세탁업 193
 
9.7%
숙박업(일반) 140
 
7.1%
네일미용업 137
 
6.9%
건물위생관리업 107
 
5.4%
이용업 83
 
4.2%
화장ㆍ분장 미용업 57
 
2.9%
피부미용업, 화장ㆍ분장 미용업 38
 
1.9%
목욕장업 36
 
1.8%
Other values (11) 158
 
8.0%

Length

2023-12-12T11:56:42.862070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반미용업 814
34.8%
피부미용업 363
15.5%
네일미용업 239
 
10.2%
세탁업 193
 
8.2%
미용업 167
 
7.1%
화장ㆍ분장 166
 
7.1%
숙박업(일반 140
 
6.0%
건물위생관리업 107
 
4.6%
이용업 83
 
3.5%
목욕장업 36
 
1.5%
Other values (2) 33
 
1.4%

신고일자
Date

Distinct1282
Distinct (%)64.7%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
Minimum1970-06-02 00:00:00
Maximum2022-08-05 00:00:00
2023-12-12T11:56:43.042605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:56:43.230928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업소명
Text

Distinct1929
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
2023-12-12T11:56:43.675929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length24
Mean length6.3037336
Min length1

Characters and Unicode

Total characters12494
Distinct characters655
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1888 ?
Unique (%)95.3%

Sample

1st row미광여인숙
2nd row유진헤어샵
3rd row미라보클리닝
4th row(주)도울환경
5th row동양기업주식회사
ValueCountFrequency (%)
헤어 36
 
1.4%
미용실 28
 
1.1%
hair 19
 
0.7%
nail 17
 
0.7%
주식회사 15
 
0.6%
모텔 15
 
0.6%
세탁소 14
 
0.5%
네일 12
 
0.5%
헤어샵 10
 
0.4%
beauty 10
 
0.4%
Other values (2114) 2379
93.1%
2023-12-12T11:56:44.551376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
573
 
4.6%
어 467
 
3.7%
헤 441
 
3.5%
스 302
 
2.4%
) 280
 
2.2%
( 279
 
2.2%
이 255
 
2.0%
일 216
 
1.7%
리 210
 
1.7%
네 194
 
1.6%
Other values (645) 9277
74.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9793
78.4%
Lowercase Letter 705
 
5.6%
Uppercase Letter 640
 
5.1%
Space Separator 573
 
4.6%
Close Punctuation 280
 
2.2%
Open Punctuation 279
 
2.2%
Decimal Number 123
 
1.0%
Other Punctuation 86
 
0.7%
Dash Punctuation 9
 
0.1%
Connector Punctuation 3
 
< 0.1%
Other values (3) 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
어 467
 
4.8%
헤 441
 
4.5%
스 302
 
3.1%
이 255
 
2.6%
일 216
 
2.2%
리 210
 
2.1%
네 194
 
2.0%
미 155
 
1.6%
사 151
 
1.5%
세 143
 
1.5%
Other values (568) 7259
74.1%
Uppercase Letter
ValueCountFrequency (%)
A 76
 
11.9%
N 53
 
8.3%
L 46
 
7.2%
H 45
 
7.0%
S 43
 
6.7%
O 42
 
6.6%
I 40
 
6.2%
E 39
 
6.1%
R 36
 
5.6%
M 30
 
4.7%
Other values (16) 190
29.7%
Lowercase Letter
ValueCountFrequency (%)
a 87
12.3%
e 82
11.6%
i 72
10.2%
l 61
 
8.7%
n 57
 
8.1%
o 48
 
6.8%
r 44
 
6.2%
t 33
 
4.7%
u 33
 
4.7%
s 30
 
4.3%
Other values (15) 158
22.4%
Decimal Number
ValueCountFrequency (%)
1 26
21.1%
0 21
17.1%
2 18
14.6%
3 17
13.8%
5 13
10.6%
7 8
 
6.5%
8 7
 
5.7%
9 5
 
4.1%
6 4
 
3.3%
4 4
 
3.3%
Other Punctuation
ValueCountFrequency (%)
. 22
25.6%
& 19
22.1%
, 15
17.4%
# 14
16.3%
: 9
10.5%
' 4
 
4.7%
· 2
 
2.3%
% 1
 
1.2%
Space Separator
ValueCountFrequency (%)
573
100.0%
Close Punctuation
ValueCountFrequency (%)
) 280
100.0%
Open Punctuation
ValueCountFrequency (%)
( 279
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%
Other Symbol
ValueCountFrequency (%)
♡ 1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%
Modifier Symbol
ValueCountFrequency (%)
´ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9789
78.3%
Common 1356
 
10.9%
Latin 1345
 
10.8%
Han 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
어 467
 
4.8%
헤 441
 
4.5%
스 302
 
3.1%
이 255
 
2.6%
일 216
 
2.2%
리 210
 
2.1%
네 194
 
2.0%
미 155
 
1.6%
사 151
 
1.5%
세 143
 
1.5%
Other values (566) 7255
74.1%
Latin
ValueCountFrequency (%)
a 87
 
6.5%
e 82
 
6.1%
A 76
 
5.7%
i 72
 
5.4%
l 61
 
4.5%
n 57
 
4.2%
N 53
 
3.9%
o 48
 
3.6%
L 46
 
3.4%
H 45
 
3.3%
Other values (41) 718
53.4%
Common
ValueCountFrequency (%)
573
42.3%
) 280
20.6%
( 279
20.6%
1 26
 
1.9%
. 22
 
1.6%
0 21
 
1.5%
& 19
 
1.4%
2 18
 
1.3%
3 17
 
1.3%
, 15
 
1.1%
Other values (16) 86
 
6.3%
Han
ValueCountFrequency (%)
美 3
75.0%
林 1
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9789
78.3%
ASCII 2697
 
21.6%
CJK 4
 
< 0.1%
None 3
 
< 0.1%
Misc Symbols 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
573
21.2%
) 280
 
10.4%
( 279
 
10.3%
a 87
 
3.2%
e 82
 
3.0%
A 76
 
2.8%
i 72
 
2.7%
l 61
 
2.3%
n 57
 
2.1%
N 53
 
2.0%
Other values (64) 1077
39.9%
Hangul
ValueCountFrequency (%)
어 467
 
4.8%
헤 441
 
4.5%
스 302
 
3.1%
이 255
 
2.6%
일 216
 
2.2%
리 210
 
2.1%
네 194
 
2.0%
미 155
 
1.6%
사 151
 
1.5%
세 143
 
1.5%
Other values (566) 7255
74.1%
CJK
ValueCountFrequency (%)
美 3
75.0%
林 1
 
25.0%
None
ValueCountFrequency (%)
· 2
66.7%
´ 1
33.3%
Misc Symbols
ValueCountFrequency (%)
♡ 1
100.0%

도로명주소
Text

Distinct1907
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
2023-12-12T11:56:44.925268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length85
Median length53
Mean length32.159435
Min length20

Characters and Unicode

Total characters63740
Distinct characters306
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

Unique1835 ?
Unique (%)92.6%

Sample

1st row광주광역시 서구 천변좌로 216-10 (양동)
2nd row광주광역시 서구 풍암순환로 183, 117동 210호 (풍암동, 우미광장아파트)
3rd row광주광역시 서구 쌍촌로57번길 18-1, 1층 (쌍촌동)
4th row광주광역시 서구 상무대로1080번길 1, 지1층 (화정동)
5th row광주광역시 서구 무진대로 499, 2층 (덕흥동)
ValueCountFrequency (%)
광주광역시 1982
 
15.8%
서구 1982
 
15.8%
1층 761
 
6.1%
쌍촌동 391
 
3.1%
화정동 315
 
2.5%
치평동 250
 
2.0%
2층 227
 
1.8%
금호동 188
 
1.5%
상가동 169
 
1.3%
풍암동 168
 
1.3%
Other values (1565) 6121
48.8%
2023-12-12T11:56:45.401829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10572
 
16.6%
광 4123
 
6.5%
1 3301
 
5.2%
동 2392
 
3.8%
) 2263
 
3.6%
( 2263
 
3.6%
시 2078
 
3.3%
주 2061
 
3.2%
, 2052
 
3.2%
구 1997
 
3.1%
Other values (296) 30638
48.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 35362
55.5%
Decimal Number 10584
 
16.6%
Space Separator 10572
 
16.6%
Close Punctuation 2263
 
3.6%
Open Punctuation 2263
 
3.6%
Other Punctuation 2070
 
3.2%
Dash Punctuation 460
 
0.7%
Uppercase Letter 85
 
0.1%
Math Symbol 58
 
0.1%
Lowercase Letter 23
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 4123
 
11.7%
동 2392
 
6.8%
시 2078
 
5.9%
주 2061
 
5.8%
구 1997
 
5.6%
서 1993
 
5.6%
역 1982
 
5.6%
로 1942
 
5.5%
층 1418
 
4.0%
길 1015
 
2.9%
Other values (256) 14361
40.6%
Uppercase Letter
ValueCountFrequency (%)
B 16
18.8%
A 12
14.1%
C 8
9.4%
S 6
 
7.1%
D 6
 
7.1%
Y 5
 
5.9%
E 5
 
5.9%
T 5
 
5.9%
P 5
 
5.9%
K 4
 
4.7%
Other values (5) 13
15.3%
Decimal Number
ValueCountFrequency (%)
1 3301
31.2%
2 1565
14.8%
0 1021
 
9.6%
3 879
 
8.3%
4 864
 
8.2%
5 684
 
6.5%
7 592
 
5.6%
9 577
 
5.5%
8 569
 
5.4%
6 532
 
5.0%
Lowercase Letter
ValueCountFrequency (%)
e 8
34.8%
t 3
 
13.0%
l 3
 
13.0%
a 3
 
13.0%
r 3
 
13.0%
n 3
 
13.0%
Other Punctuation
ValueCountFrequency (%)
, 2052
99.1%
@ 12
 
0.6%
. 4
 
0.2%
& 2
 
0.1%
Space Separator
ValueCountFrequency (%)
10572
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2263
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2263
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 460
100.0%
Math Symbol
ValueCountFrequency (%)
~ 58
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 35362
55.5%
Common 28270
44.4%
Latin 108
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 4123
 
11.7%
동 2392
 
6.8%
시 2078
 
5.9%
주 2061
 
5.8%
구 1997
 
5.6%
서 1993
 
5.6%
역 1982
 
5.6%
로 1942
 
5.5%
층 1418
 
4.0%
길 1015
 
2.9%
Other values (256) 14361
40.6%
Latin
ValueCountFrequency (%)
B 16
14.8%
A 12
 
11.1%
e 8
 
7.4%
C 8
 
7.4%
S 6
 
5.6%
D 6
 
5.6%
Y 5
 
4.6%
E 5
 
4.6%
T 5
 
4.6%
P 5
 
4.6%
Other values (11) 32
29.6%
Common
ValueCountFrequency (%)
10572
37.4%
1 3301
 
11.7%
) 2263
 
8.0%
( 2263
 
8.0%
, 2052
 
7.3%
2 1565
 
5.5%
0 1021
 
3.6%
3 879
 
3.1%
4 864
 
3.1%
5 684
 
2.4%
Other values (9) 2806
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 35362
55.5%
ASCII 28378
44.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10572
37.3%
1 3301
 
11.6%
) 2263
 
8.0%
( 2263
 
8.0%
, 2052
 
7.2%
2 1565
 
5.5%
0 1021
 
3.6%
3 879
 
3.1%
4 864
 
3.0%
5 684
 
2.4%
Other values (30) 2914
 
10.3%
Hangul
ValueCountFrequency (%)
광 4123
 
11.7%
동 2392
 
6.8%
시 2078
 
5.9%
주 2061
 
5.8%
구 1997
 
5.6%
서 1993
 
5.6%
역 1982
 
5.6%
로 1942
 
5.5%
층 1418
 
4.0%
길 1015
 
2.9%
Other values (256) 14361
40.6%

지번주소
Text

Distinct1920
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
2023-12-12T11:56:45.794261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length43
Mean length25.011604
Min length16

Characters and Unicode

Total characters49573
Distinct characters313
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

Unique1859 ?
Unique (%)93.8%

Sample

1st row광주광역시 서구 양동 344
2nd row광주광역시 서구 풍암동 1132 우미광장아파트 117동 210호
3rd row광주광역시 서구 쌍촌동 987-18 (1층)
4th row광주광역시 서구 화정동 774-4 지1층
5th row광주광역시 서구 덕흥동 42-1 2층
ValueCountFrequency (%)
광주광역시 1982
19.2%
서구 1982
19.2%
1층 536
 
5.2%
쌍촌동 441
 
4.3%
화정동 357
 
3.5%
치평동 291
 
2.8%
금호동 218
 
2.1%
풍암동 197
 
1.9%
상가동 149
 
1.4%
2층 147
 
1.4%
Other values (2010) 4027
39.0%
2023-12-12T11:56:46.456620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9967
20.1%
광 4111
 
8.3%
1 3176
 
6.4%
동 2343
 
4.7%
주 2032
 
4.1%
시 2025
 
4.1%
구 1985
 
4.0%
서 1984
 
4.0%
역 1982
 
4.0%
2 1557
 
3.1%
Other values (303) 18411
37.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 25571
51.6%
Decimal Number 11462
23.1%
Space Separator 9967
 
20.1%
Dash Punctuation 1546
 
3.1%
Open Punctuation 413
 
0.8%
Close Punctuation 412
 
0.8%
Uppercase Letter 85
 
0.2%
Other Punctuation 52
 
0.1%
Math Symbol 47
 
0.1%
Lowercase Letter 18
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 4111
16.1%
동 2343
 
9.2%
주 2032
 
7.9%
시 2025
 
7.9%
구 1985
 
7.8%
서 1984
 
7.8%
역 1982
 
7.8%
층 1008
 
3.9%
호 790
 
3.1%
촌 471
 
1.8%
Other values (264) 6840
26.7%
Uppercase Letter
ValueCountFrequency (%)
B 16
18.8%
A 16
18.8%
T 10
11.8%
P 10
11.8%
C 7
8.2%
Y 5
 
5.9%
E 4
 
4.7%
D 3
 
3.5%
K 3
 
3.5%
S 3
 
3.5%
Other values (4) 8
9.4%
Decimal Number
ValueCountFrequency (%)
1 3176
27.7%
2 1557
13.6%
3 1090
 
9.5%
0 1080
 
9.4%
4 806
 
7.0%
7 786
 
6.9%
8 785
 
6.8%
6 768
 
6.7%
5 742
 
6.5%
9 672
 
5.9%
Lowercase Letter
ValueCountFrequency (%)
e 7
38.9%
a 3
16.7%
n 2
 
11.1%
t 2
 
11.1%
r 2
 
11.1%
l 2
 
11.1%
Other Punctuation
ValueCountFrequency (%)
, 31
59.6%
@ 16
30.8%
. 3
 
5.8%
& 2
 
3.8%
Space Separator
ValueCountFrequency (%)
9967
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1546
100.0%
Open Punctuation
ValueCountFrequency (%)
( 413
100.0%
Close Punctuation
ValueCountFrequency (%)
) 412
100.0%
Math Symbol
ValueCountFrequency (%)
~ 47
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 25571
51.6%
Common 23899
48.2%
Latin 103
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 4111
16.1%
동 2343
 
9.2%
주 2032
 
7.9%
시 2025
 
7.9%
구 1985
 
7.8%
서 1984
 
7.8%
역 1982
 
7.8%
층 1008
 
3.9%
호 790
 
3.1%
촌 471
 
1.8%
Other values (264) 6840
26.7%
Latin
ValueCountFrequency (%)
B 16
15.5%
A 16
15.5%
T 10
9.7%
P 10
9.7%
C 7
 
6.8%
e 7
 
6.8%
Y 5
 
4.9%
E 4
 
3.9%
D 3
 
2.9%
K 3
 
2.9%
Other values (10) 22
21.4%
Common
ValueCountFrequency (%)
9967
41.7%
1 3176
 
13.3%
2 1557
 
6.5%
- 1546
 
6.5%
3 1090
 
4.6%
0 1080
 
4.5%
4 806
 
3.4%
7 786
 
3.3%
8 785
 
3.3%
6 768
 
3.2%
Other values (9) 2338
 
9.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 25571
51.6%
ASCII 24002
48.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9967
41.5%
1 3176
 
13.2%
2 1557
 
6.5%
- 1546
 
6.4%
3 1090
 
4.5%
0 1080
 
4.5%
4 806
 
3.4%
7 786
 
3.3%
8 785
 
3.3%
6 768
 
3.2%
Other values (29) 2441
 
10.2%
Hangul
ValueCountFrequency (%)
광 4111
16.1%
동 2343
 
9.2%
주 2032
 
7.9%
시 2025
 
7.9%
구 1985
 
7.8%
서 1984
 
7.8%
역 1982
 
7.8%
층 1008
 
3.9%
호 790
 
3.1%
촌 471
 
1.8%
Other values (264) 6840
26.7%

Missing values

2023-12-12T11:56:42.556989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T11:56:42.701264image/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

업종명신고일자업소명도로명주소지번주소
0숙박업(일반)1970-06-02미광여인숙광주광역시 서구 천변좌로 216-10 (양동)광주광역시 서구 양동 344
1일반미용업1985-04-17유진헤어샵광주광역시 서구 풍암순환로 183, 117동 210호 (풍암동, 우미광장아파트)광주광역시 서구 풍암동 1132 우미광장아파트 117동 210호
2세탁업1987-05-30미라보클리닝광주광역시 서구 쌍촌로57번길 18-1, 1층 (쌍촌동)광주광역시 서구 쌍촌동 987-18 (1층)
3건물위생관리업1996-01-03(주)도울환경광주광역시 서구 상무대로1080번길 1, 지1층 (화정동)광주광역시 서구 화정동 774-4 지1층
4건물위생관리업1996-02-12동양기업주식회사광주광역시 서구 무진대로 499, 2층 (덕흥동)광주광역시 서구 덕흥동 42-1 2층
5이용업1996-10-21태양이발광주광역시 서구 군분로119번길 18, 태양사우나 3층 (화정동)광주광역시 서구 화정동 1403 태양사우나 3층
6건물위생관리업1999-10-07광주보건환경광주광역시 서구 화정로271번길 3-1 (농성동,(이층))광주광역시 서구 농성동 664-40 (이층)
7미용업1999-10-25안토니오헤어샾광주광역시 서구 화정로 105, 상가동 1층 106호 (쌍촌동, 빛고을파크)광주광역시 서구 쌍촌동 1228-1 빛고을파크 상가동 106호
8이용업2000-05-02발산이발관광주광역시 서구 발산로45번길 6, 1층 (양동)광주광역시 서구 양동 438-281 1층
9일반미용업2000-10-16헤어뷰티광주광역시 서구 독립로185번길 32, 1층 (양동)광주광역시 서구 양동 5-124 1층
업종명신고일자업소명도로명주소지번주소
1972피부미용업2022-07-25고운빛깔상무점광주광역시 서구 시청로 27, 테라스가든동 211호 (치평동, 상무광명메이루즈)광주광역시 서구 치평동 1249 상무광명메이루즈 테라스가든동 211호
1973일반미용업2022-07-28살롱드 솔광주광역시 서구 유림로98번길 11, 1층 (동천동)광주광역시 서구 동천동 603 1층
1974일반미용업2022-07-28리나헤어광주광역시 서구 금호심곡길 22-1, 1층 (금호동)광주광역시 서구 금호동 331-1 1층
1975피부미용업, 화장ㆍ분장 미용업2022-07-28프리뷰티광주광역시 서구 풍암신흥로 13, 2층 (풍암동)광주광역시 서구 풍암동 918-1 2층
1976피부미용업, 화장ㆍ분장 미용업2022-08-01유앤미뷰티광주광역시 서구 내방로 415, 광천 중해마루힐 주상복합 상가동 2층 201호 (농성동)광주광역시 서구 농성동 417-22 광천 중해마루힐 주상복합 상가동 201호
1977네일미용업2022-08-03온리유 네일광주광역시 서구 화운로 278, 133동 1층 108호 (광천동, 광천 e편한세상)광주광역시 서구 광천동 895 광천 e편한세상 133동 108호
1978피부미용업, 네일미용업, 화장ㆍ분장 미용업2022-08-04아이, 네일광주광역시 서구 풍암운리로23번길 4-1, 1층 (풍암동)광주광역시 서구 풍암동 989-11 1층
1979일반미용업2022-08-05릿(LIT)광주광역시 서구 화개중앙로87번길 24, 1층 102호 (금호동)광주광역시 서구 금호동 1078 1층 102호
1980네일미용업2022-08-05루크광주광역시 서구 상무오월로3번길 14-17, 1층 (쌍촌동)광주광역시 서구 쌍촌동 1294-11 1층
1981일반미용업, 화장ㆍ분장 미용업2022-08-05루크뷰티샵광주광역시 서구 상무오월로3번길 14-17, 1층 (쌍촌동)광주광역시 서구 쌍촌동 1294-11 1층