Overview

Dataset statistics

Number of variables6
Number of observations2367
Missing cells1066
Missing cells (%)7.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory113.4 KiB
Average record size in memory49.1 B

Variable types

Numeric1
Categorical2
Text3

Dataset

Description경기도 용인시 관내 미용업소 현황입니다. 업종명, 업소명, 업소소재지 등의 데이터를 제공합니다. ※ 데이터기준일자 : 2023-03-31
URLhttps://www.data.go.kr/data/3072103/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
업종명 is highly imbalanced (50.3%)Imbalance
소재지전화 has 1066 (45.0%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 22:50:43.014220
Analysis finished2023-12-12 22:50:43.942964
Duration0.93 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct2367
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1184
Minimum1
Maximum2367
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size20.9 KiB
2023-12-13T07:50:44.049465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile119.3
Q1592.5
median1184
Q31775.5
95-th percentile2248.7
Maximum2367
Range2366
Interquartile range (IQR)1183

Descriptive statistics

Standard deviation683.43837
Coefficient of variation (CV)0.57722835
Kurtosis-1.2
Mean1184
Median Absolute Deviation (MAD)592
Skewness0
Sum2802528
Variance467088
MonotonicityStrictly increasing
2023-12-13T07:50:44.210809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
1574 1
 
< 0.1%
1576 1
 
< 0.1%
1577 1
 
< 0.1%
1578 1
 
< 0.1%
1579 1
 
< 0.1%
1580 1
 
< 0.1%
1581 1
 
< 0.1%
1582 1
 
< 0.1%
1583 1
 
< 0.1%
Other values (2357) 2357
99.6%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
2367 1
< 0.1%
2366 1
< 0.1%
2365 1
< 0.1%
2364 1
< 0.1%
2363 1
< 0.1%
2362 1
< 0.1%
2361 1
< 0.1%
2360 1
< 0.1%
2359 1
< 0.1%
2358 1
< 0.1%

업종명
Categorical

IMBALANCE 

Distinct16
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
일반미용업
1491 
피부미용업
316 
네일미용업
198 
종합미용업
 
104
피부미용업, 네일미용업
 
64
Other values (11)
194 

Length

Max length23
Median length5
Mean length6.0502746
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반미용업 1491
63.0%
피부미용업 316
 
13.4%
네일미용업 198
 
8.4%
종합미용업 104
 
4.4%
피부미용업, 네일미용업 64
 
2.7%
네일미용업, 화장ㆍ분장 미용업 49
 
2.1%
화장ㆍ분장 미용업 39
 
1.6%
피부미용업, 네일미용업, 화장ㆍ분장 미용업 23
 
1.0%
피부미용업, 화장ㆍ분장 미용업 20
 
0.8%
일반미용업, 화장ㆍ분장 미용업 18
 
0.8%
Other values (6) 45
 
1.9%

Length

2023-12-13T07:50:44.382381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반미용업 1551
55.5%
피부미용업 438
 
15.7%
네일미용업 363
 
13.0%
미용업 171
 
6.1%
화장ㆍ분장 168
 
6.0%
종합미용업 104
 
3.7%

업소명
Text

Distinct2214
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
2023-12-13T07:50:44.727336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length28
Mean length6.5340093
Min length1

Characters and Unicode

Total characters15466
Distinct characters670
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

Unique2121 ?
Unique (%)89.6%

Sample

1st row공주네일
2nd row라크슈미네일앤젤(Nail&Jel)
3rd row노메이크업
4th row쉬끄
5th row오늘네일
ValueCountFrequency (%)
hair 37
 
1.3%
헤어 30
 
1.1%
nail 19
 
0.7%
salon 15
 
0.5%
de 13
 
0.5%
네일 12
 
0.4%
올가드림뷰티 12
 
0.4%
헤어살롱 11
 
0.4%
나이스가이 10
 
0.4%
에스테틱 9
 
0.3%
Other values (2389) 2689
94.1%
2023-12-13T07:50:45.245309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
어 1088
 
7.0%
헤 1049
 
6.8%
492
 
3.2%
스 395
 
2.6%
이 330
 
2.1%
일 299
 
1.9%
( 298
 
1.9%
) 298
 
1.9%
리 279
 
1.8%
네 279
 
1.8%
Other values (660) 10659
68.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11974
77.4%
Lowercase Letter 1164
 
7.5%
Uppercase Letter 915
 
5.9%
Space Separator 492
 
3.2%
Open Punctuation 299
 
1.9%
Close Punctuation 299
 
1.9%
Other Punctuation 160
 
1.0%
Decimal Number 145
 
0.9%
Connector Punctuation 8
 
0.1%
Dash Punctuation 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
어 1088
 
9.1%
헤 1049
 
8.8%
스 395
 
3.3%
이 330
 
2.8%
일 299
 
2.5%
리 279
 
2.3%
네 279
 
2.3%
미 249
 
2.1%
티 172
 
1.4%
라 172
 
1.4%
Other values (578) 7662
64.0%
Lowercase Letter
ValueCountFrequency (%)
a 177
15.2%
i 131
11.3%
e 118
10.1%
o 93
8.0%
l 90
7.7%
r 87
7.5%
n 84
 
7.2%
s 59
 
5.1%
h 59
 
5.1%
y 49
 
4.2%
Other values (16) 217
18.6%
Uppercase Letter
ValueCountFrequency (%)
A 108
11.8%
N 81
 
8.9%
H 78
 
8.5%
S 67
 
7.3%
I 64
 
7.0%
J 53
 
5.8%
O 52
 
5.7%
L 51
 
5.6%
R 50
 
5.5%
B 47
 
5.1%
Other values (15) 264
28.9%
Other Punctuation
ValueCountFrequency (%)
& 51
31.9%
. 44
27.5%
# 22
13.8%
, 19
 
11.9%
' 14
 
8.8%
: 3
 
1.9%
! 2
 
1.2%
/ 2
 
1.2%
; 1
 
0.6%
· 1
 
0.6%
Decimal Number
ValueCountFrequency (%)
1 35
24.1%
0 21
14.5%
5 19
13.1%
3 17
11.7%
2 14
 
9.7%
4 12
 
8.3%
7 12
 
8.3%
9 7
 
4.8%
6 4
 
2.8%
8 4
 
2.8%
Math Symbol
ValueCountFrequency (%)
> 1
33.3%
< 1
33.3%
+ 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 298
99.7%
[ 1
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 298
99.7%
] 1
 
0.3%
Space Separator
ValueCountFrequency (%)
492
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11953
77.3%
Latin 2079
 
13.4%
Common 1413
 
9.1%
Han 21
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
어 1088
 
9.1%
헤 1049
 
8.8%
스 395
 
3.3%
이 330
 
2.8%
일 299
 
2.5%
리 279
 
2.3%
네 279
 
2.3%
미 249
 
2.1%
티 172
 
1.4%
라 172
 
1.4%
Other values (571) 7641
63.9%
Latin
ValueCountFrequency (%)
a 177
 
8.5%
i 131
 
6.3%
e 118
 
5.7%
A 108
 
5.2%
o 93
 
4.5%
l 90
 
4.3%
r 87
 
4.2%
n 84
 
4.0%
N 81
 
3.9%
H 78
 
3.8%
Other values (41) 1032
49.6%
Common
ValueCountFrequency (%)
492
34.8%
( 298
21.1%
) 298
21.1%
& 51
 
3.6%
. 44
 
3.1%
1 35
 
2.5%
# 22
 
1.6%
0 21
 
1.5%
, 19
 
1.3%
5 19
 
1.3%
Other values (21) 114
 
8.1%
Han
ValueCountFrequency (%)
美 14
66.7%
秀 2
 
9.5%
安 1
 
4.8%
男 1
 
4.8%
丹 1
 
4.8%
多 1
 
4.8%
映 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11951
77.3%
ASCII 3491
 
22.6%
CJK 21
 
0.1%
Compat Jamo 2
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
어 1088
 
9.1%
헤 1049
 
8.8%
스 395
 
3.3%
이 330
 
2.8%
일 299
 
2.5%
리 279
 
2.3%
네 279
 
2.3%
미 249
 
2.1%
티 172
 
1.4%
라 172
 
1.4%
Other values (570) 7639
63.9%
ASCII
ValueCountFrequency (%)
492
 
14.1%
( 298
 
8.5%
) 298
 
8.5%
a 177
 
5.1%
i 131
 
3.8%
e 118
 
3.4%
A 108
 
3.1%
o 93
 
2.7%
l 90
 
2.6%
r 87
 
2.5%
Other values (71) 1599
45.8%
CJK
ValueCountFrequency (%)
美 14
66.7%
秀 2
 
9.5%
安 1
 
4.8%
男 1
 
4.8%
丹 1
 
4.8%
多 1
 
4.8%
映 1
 
4.8%
Compat Jamo
ValueCountFrequency (%)
ㅋ 2
100.0%
None
ValueCountFrequency (%)
· 1
100.0%

업소소재지(도로명)
Text

Distinct2340
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
2023-12-13T07:50:45.591051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length67
Median length57
Mean length39.846641
Min length18

Characters and Unicode

Total characters94317
Distinct characters433
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2315 ?
Unique (%)97.8%

Sample

1st row경기도 용인시 처인구 모현읍 백옥대로2366번길 10-33 (동양주택)
2nd row경기도 용인시 처인구 용문로 146, 2층 (김량장동)
3rd row경기도 용인시 처인구 금령로13번길 13, 106호 (김량장동, 어울림아파트 상가)
4th row경기도 용인시 처인구 금령로99번길 7, 에이동 148호 (김량장동)
5th row경기도 용인시 처인구 금령로 46 (김량장동, 1층일부)
ValueCountFrequency (%)
경기도 2367
 
12.1%
용인시 2367
 
12.1%
기흥구 931
 
4.8%
수지구 721
 
3.7%
처인구 715
 
3.7%
1층 664
 
3.4%
2층 263
 
1.3%
상가동 243
 
1.2%
일부 170
 
0.9%
상현동 154
 
0.8%
Other values (2723) 10931
56.0%
2023-12-13T07:50:46.097767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17167
 
18.2%
1 4637
 
4.9%
기 3396
 
3.6%
동 3221
 
3.4%
인 3197
 
3.4%
구 2709
 
2.9%
, 2635
 
2.8%
2 2609
 
2.8%
용 2500
 
2.7%
시 2449
 
2.6%
Other values (423) 49797
52.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 53521
56.7%
Space Separator 17167
 
18.2%
Decimal Number 15478
 
16.4%
Other Punctuation 2655
 
2.8%
Close Punctuation 2222
 
2.4%
Open Punctuation 2222
 
2.4%
Dash Punctuation 573
 
0.6%
Uppercase Letter 444
 
0.5%
Lowercase Letter 27
 
< 0.1%
Math Symbol 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 3396
 
6.3%
동 3221
 
6.0%
인 3197
 
6.0%
구 2709
 
5.1%
용 2500
 
4.7%
시 2449
 
4.6%
로 2425
 
4.5%
경 2410
 
4.5%
도 2386
 
4.5%
호 1861
 
3.5%
Other values (366) 26967
50.4%
Uppercase Letter
ValueCountFrequency (%)
B 123
27.7%
A 95
21.4%
C 34
 
7.7%
T 23
 
5.2%
I 22
 
5.0%
R 19
 
4.3%
E 18
 
4.1%
H 18
 
4.1%
S 15
 
3.4%
K 10
 
2.3%
Other values (15) 67
15.1%
Decimal Number
ValueCountFrequency (%)
1 4637
30.0%
2 2609
16.9%
0 2127
13.7%
3 1433
 
9.3%
4 956
 
6.2%
5 951
 
6.1%
6 808
 
5.2%
7 772
 
5.0%
8 654
 
4.2%
9 531
 
3.4%
Lowercase Letter
ValueCountFrequency (%)
e 12
44.4%
a 3
 
11.1%
r 2
 
7.4%
w 2
 
7.4%
o 2
 
7.4%
t 2
 
7.4%
b 1
 
3.7%
c 1
 
3.7%
p 1
 
3.7%
m 1
 
3.7%
Other Punctuation
ValueCountFrequency (%)
, 2635
99.2%
. 7
 
0.3%
/ 5
 
0.2%
@ 4
 
0.2%
& 3
 
0.1%
; 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
17167
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2222
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2222
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 573
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 53520
56.7%
Common 40323
42.8%
Latin 473
 
0.5%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 3396
 
6.3%
동 3221
 
6.0%
인 3197
 
6.0%
구 2709
 
5.1%
용 2500
 
4.7%
시 2449
 
4.6%
로 2425
 
4.5%
경 2410
 
4.5%
도 2386
 
4.5%
호 1861
 
3.5%
Other values (365) 26966
50.4%
Latin
ValueCountFrequency (%)
B 123
26.0%
A 95
20.1%
C 34
 
7.2%
T 23
 
4.9%
I 22
 
4.7%
R 19
 
4.0%
E 18
 
3.8%
H 18
 
3.8%
S 15
 
3.2%
e 12
 
2.5%
Other values (26) 94
19.9%
Common
ValueCountFrequency (%)
17167
42.6%
1 4637
 
11.5%
, 2635
 
6.5%
2 2609
 
6.5%
) 2222
 
5.5%
( 2222
 
5.5%
0 2127
 
5.3%
3 1433
 
3.6%
4 956
 
2.4%
5 951
 
2.4%
Other values (11) 3364
 
8.3%
Han
ValueCountFrequency (%)
家 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 53520
56.7%
ASCII 40794
43.3%
Number Forms 2
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17167
42.1%
1 4637
 
11.4%
, 2635
 
6.5%
2 2609
 
6.4%
) 2222
 
5.4%
( 2222
 
5.4%
0 2127
 
5.2%
3 1433
 
3.5%
4 956
 
2.3%
5 951
 
2.3%
Other values (46) 3835
 
9.4%
Hangul
ValueCountFrequency (%)
기 3396
 
6.3%
동 3221
 
6.0%
인 3197
 
6.0%
구 2709
 
5.1%
용 2500
 
4.7%
시 2449
 
4.6%
로 2425
 
4.5%
경 2410
 
4.5%
도 2386
 
4.5%
호 1861
 
3.5%
Other values (365) 26966
50.4%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
100.0%
CJK
ValueCountFrequency (%)
家 1
100.0%

소재지전화
Text

MISSING 

Distinct1293
Distinct (%)99.4%
Missing1066
Missing (%)45.0%
Memory size18.6 KiB
2023-12-13T07:50:46.397274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.200615
Min length9

Characters and Unicode

Total characters15873
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1285 ?
Unique (%)98.8%

Sample

1st row031-328-8394
2nd row0507-1400-4875
3rd row031-335-0017
4th row031-335-3018
5th row0507-1403-5542
ValueCountFrequency (%)
031-322-8745 2
 
0.2%
031-285-0901 2
 
0.2%
031-320-8395 2
 
0.2%
031-333-0387 2
 
0.2%
031-339-1404 2
 
0.2%
031-202-7760 2
 
0.2%
031-336-0732 2
 
0.2%
031-337-1908 2
 
0.2%
031-693-6444 1
 
0.1%
031-8005-6630 1
 
0.1%
Other values (1283) 1283
98.6%
2023-12-13T07:50:46.799193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 2620
16.5%
- 2602
16.4%
0 2157
13.6%
1 1992
12.5%
2 1481
9.3%
8 999
 
6.3%
7 938
 
5.9%
6 913
 
5.8%
5 887
 
5.6%
4 688
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13271
83.6%
Dash Punctuation 2602
 
16.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 2620
19.7%
0 2157
16.3%
1 1992
15.0%
2 1481
11.2%
8 999
 
7.5%
7 938
 
7.1%
6 913
 
6.9%
5 887
 
6.7%
4 688
 
5.2%
9 596
 
4.5%
Dash Punctuation
ValueCountFrequency (%)
- 2602
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15873
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 2620
16.5%
- 2602
16.4%
0 2157
13.6%
1 1992
12.5%
2 1481
9.3%
8 999
 
6.3%
7 938
 
5.9%
6 913
 
5.8%
5 887
 
5.6%
4 688
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15873
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 2620
16.5%
- 2602
16.4%
0 2157
13.6%
1 1992
12.5%
2 1481
9.3%
8 999
 
6.3%
7 938
 
5.9%
6 913
 
5.8%
5 887
 
5.6%
4 688
 
4.3%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
2023-03-31
2367 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-03-31
2nd row2023-03-31
3rd row2023-03-31
4th row2023-03-31
5th row2023-03-31

Common Values

ValueCountFrequency (%)
2023-03-31 2367
100.0%

Length

2023-12-13T07:50:46.981658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:50:47.077121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-03-31 2367
100.0%

Interactions

2023-12-13T07:50:43.669910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T07:50:47.143337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종명
연번1.0000.674
업종명0.6741.000
2023-12-13T07:50:47.234441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종명
연번1.0000.341
업종명0.3411.000

Missing values

2023-12-13T07:50:43.785323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:50:43.890260image/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

연번업종명업소명업소소재지(도로명)소재지전화데이터기준일자
01네일미용업공주네일경기도 용인시 처인구 모현읍 백옥대로2366번길 10-33 (동양주택)031-328-83942023-03-31
12네일미용업라크슈미네일앤젤(Nail&Jel)경기도 용인시 처인구 용문로 146, 2층 (김량장동)0507-1400-48752023-03-31
23네일미용업노메이크업경기도 용인시 처인구 금령로13번길 13, 106호 (김량장동, 어울림아파트 상가)031-335-00172023-03-31
34네일미용업쉬끄경기도 용인시 처인구 금령로99번길 7, 에이동 148호 (김량장동)031-335-30182023-03-31
45네일미용업오늘네일경기도 용인시 처인구 금령로 46 (김량장동, 1층일부)0507-1403-55422023-03-31
56네일미용업엽이네일(Yeobi Nail)경기도 용인시 처인구 명지로 24, 239호 (역북동)<NA>2023-03-31
67네일미용업네일언니경기도 용인시 처인구 경안천로42번길 3 (마평동, 1층 일부)0507-1360-25812023-03-31
78네일미용업네일링경기도 용인시 처인구 백암면 근창로 3, 1층0507-1390-65452023-03-31
89네일미용업미녀작업실경기도 용인시 처인구 중부대로 1123, 2층 201호 (삼가동)0507-1332-84072023-03-31
910네일미용업네일숲경기도 용인시 처인구 남사읍 한숲로 54, 아곡프라자 2층 206호 일부0507-1328-41822023-03-31
연번업종명업소명업소소재지(도로명)소재지전화데이터기준일자
23572358화장ㆍ분장 미용업더하다(THE HADA)경기도 용인시 수지구 현암로 139, 가동 1층 104호 (죽전동)<NA>2023-03-31
23582359화장ㆍ분장 미용업눈썹애빠지다경기도 용인시 수지구 대지로 36, 105호 (죽전동)<NA>2023-03-31
23592360화장ㆍ분장 미용업누누블리경기도 용인시 수지구 수풍로 89, 상가동 3층 302호 (동천동, 더샵 동천 이스트포레)<NA>2023-03-31
23602361화장ㆍ분장 미용업에이드로잉경기도 용인시 수지구 만현로 113, 미래프라자 4층 406호 일부호 (상현동)<NA>2023-03-31
23612362화장ㆍ분장 미용업래쉬미경기도 용인시 수지구 포은대로313번길 7-10, 124동 102-1호 (풍덕천동, e편한세상 수지)<NA>2023-03-31
23622363화장ㆍ분장 미용업티나스타일 수지점경기도 용인시 수지구 죽전로 146, 보람프라자 2층 201호 일부호 (죽전동)<NA>2023-03-31
23632364화장ㆍ분장 미용업브로우 꿈경기도 용인시 수지구 풍덕천로147번길 3, 세원빌딩 7층 일부호 (풍덕천동)<NA>2023-03-31
23642365화장ㆍ분장 미용업올가뷰티 성복점경기도 용인시 수지구 성복2로 17, 골드프라자1 지하1층 B103호 (성복동)<NA>2023-03-31
23652366화장ㆍ분장 미용업글로시슈가앤브로우경기도 용인시 수지구 광교중앙로 313, 광교 프리미워 타워 5층 501호 일부호 (상현동)<NA>2023-03-31
23662367화장ㆍ분장 미용업JIN BROW경기도 용인시 수지구 만현로 120, SR프라자 2층 202호 일부호 (상현동)<NA>2023-03-31