Overview

Dataset statistics

Number of variables7
Number of observations132
Missing cells31
Missing cells (%)3.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.6 KiB
Average record size in memory59.0 B

Variable types

Text4
Numeric2
DateTime1

Dataset

Description경기도 연천군 관내의 이,미용업소의 명칭, 도로명주소, 지번주소, 위경도, 연락처 현황 정보를 조회할 수 있도록 제공하는 데이터목록입니다.
URLhttps://www.data.go.kr/data/3073148/fileData.do

Alerts

기준일자 has constant value ""Constant
전화번호 has 29 (22.0%) missing valuesMissing
기준일자 has 2 (1.5%) missing valuesMissing

Reproduction

Analysis started2023-12-12 23:41:56.803590
Analysis finished2023-12-12 23:41:57.897855
Duration1.09 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

Distinct130
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-13T08:41:58.142040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length16
Mean length5.5681818
Min length1

Characters and Unicode

Total characters735
Distinct characters209
Distinct categories7 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique128 ?
Unique (%)97.0%

Sample

1st row복지이발관
2nd row역전이발관
3rd row남양이발소
4th row마을이용원
5th row금수이발관
ValueCountFrequency (%)
헤어샵 4
 
2.4%
헤어 4
 
2.4%
미용실 3
 
1.8%
가새소리 2
 
1.2%
뷰티 2
 
1.2%
헤어살롱 2
 
1.2%
댕기머리 2
 
1.2%
미장원 2
 
1.2%
향원이발관 1
 
0.6%
j헤어컷 1
 
0.6%
Other values (141) 141
86.0%
2023-12-13T08:41:58.562797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
헤 43
 
5.9%
어 42
 
5.7%
미 41
 
5.6%
실 37
 
5.0%
용 37
 
5.0%
32
 
4.4%
이 32
 
4.4%
리 20
 
2.7%
발 19
 
2.6%
관 17
 
2.3%
Other values (199) 415
56.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 663
90.2%
Space Separator 32
 
4.4%
Uppercase Letter 22
 
3.0%
Lowercase Letter 6
 
0.8%
Open Punctuation 4
 
0.5%
Close Punctuation 4
 
0.5%
Other Punctuation 4
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
헤 43
 
6.5%
어 42
 
6.3%
미 41
 
6.2%
실 37
 
5.6%
용 37
 
5.6%
이 32
 
4.8%
리 20
 
3.0%
발 19
 
2.9%
관 17
 
2.6%
원 9
 
1.4%
Other values (176) 366
55.2%
Uppercase Letter
ValueCountFrequency (%)
A 4
18.2%
C 3
13.6%
J 3
13.6%
H 3
13.6%
N 2
9.1%
O 2
9.1%
Y 1
 
4.5%
S 1
 
4.5%
P 1
 
4.5%
L 1
 
4.5%
Lowercase Letter
ValueCountFrequency (%)
y 1
16.7%
t 1
16.7%
u 1
16.7%
a 1
16.7%
e 1
16.7%
b 1
16.7%
Other Punctuation
ValueCountFrequency (%)
# 2
50.0%
＃ 1
25.0%
. 1
25.0%
Space Separator
ValueCountFrequency (%)
32
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 662
90.1%
Common 44
 
6.0%
Latin 28
 
3.8%
Han 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
헤 43
 
6.5%
어 42
 
6.3%
미 41
 
6.2%
실 37
 
5.6%
용 37
 
5.6%
이 32
 
4.8%
리 20
 
3.0%
발 19
 
2.9%
관 17
 
2.6%
원 9
 
1.4%
Other values (175) 365
55.1%
Latin
ValueCountFrequency (%)
A 4
14.3%
C 3
10.7%
J 3
10.7%
H 3
10.7%
N 2
 
7.1%
O 2
 
7.1%
Y 1
 
3.6%
S 1
 
3.6%
P 1
 
3.6%
L 1
 
3.6%
Other values (7) 7
25.0%
Common
ValueCountFrequency (%)
32
72.7%
( 4
 
9.1%
) 4
 
9.1%
# 2
 
4.5%
＃ 1
 
2.3%
. 1
 
2.3%
Han
ValueCountFrequency (%)
秀 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 662
90.1%
ASCII 71
 
9.7%
CJK 1
 
0.1%
None 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
헤 43
 
6.5%
어 42
 
6.3%
미 41
 
6.2%
실 37
 
5.6%
용 37
 
5.6%
이 32
 
4.8%
리 20
 
3.0%
발 19
 
2.9%
관 17
 
2.6%
원 9
 
1.4%
Other values (175) 365
55.1%
ASCII
ValueCountFrequency (%)
32
45.1%
( 4
 
5.6%
) 4
 
5.6%
A 4
 
5.6%
C 3
 
4.2%
J 3
 
4.2%
H 3
 
4.2%
N 2
 
2.8%
O 2
 
2.8%
# 2
 
2.8%
Other values (12) 12
 
16.9%
CJK
ValueCountFrequency (%)
秀 1
100.0%
None
ValueCountFrequency (%)
＃ 1
100.0%

도로명주소
Text

Distinct127
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-13T08:41:58.916608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length23
Mean length20.704545
Min length17

Characters and Unicode

Total characters2733
Distinct characters58
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

Unique123 ?
Unique (%)93.2%

Sample

1st row경기도 연천군 전곡읍 전곡역로 72번길 27
2nd row경기도 연천군 전곡읍 온골로 17
3rd row경기도 연천군 신서면 도대로 1
4th row경기도 연천군 백학면 두백로 26
5th row경기도 연천군 연천읍 연천로 269
ValueCountFrequency (%)
경기도 132
20.0%
연천군 132
20.0%
전곡읍 89
 
13.5%
연천읍 19
 
2.9%
은전로78번길 19
 
2.9%
전곡로 10
 
1.5%
은전로 8
 
1.2%
온골로 8
 
1.2%
청산면 8
 
1.2%
신서면 7
 
1.1%
Other values (152) 229
34.6%
2023-12-13T08:41:59.433645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
529
19.4%
연 162
 
5.9%
천 161
 
5.9%
전 158
 
5.8%
도 139
 
5.1%
군 139
 
5.1%
경 132
 
4.8%
기 132
 
4.8%
로 129
 
4.7%
곡 119
 
4.4%
Other values (48) 933
34.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1728
63.2%
Space Separator 529
 
19.4%
Decimal Number 453
 
16.6%
Dash Punctuation 23
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
연 162
9.4%
천 161
9.3%
전 158
9.1%
도 139
 
8.0%
군 139
 
8.0%
경 132
 
7.6%
기 132
 
7.6%
로 129
 
7.5%
곡 119
 
6.9%
읍 108
 
6.2%
Other values (36) 349
20.2%
Decimal Number
ValueCountFrequency (%)
1 101
22.3%
7 55
12.1%
8 49
10.8%
6 43
9.5%
2 41
9.1%
4 40
 
8.8%
3 39
 
8.6%
5 36
 
7.9%
9 26
 
5.7%
0 23
 
5.1%
Space Separator
ValueCountFrequency (%)
529
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1728
63.2%
Common 1005
36.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
연 162
9.4%
천 161
9.3%
전 158
9.1%
도 139
 
8.0%
군 139
 
8.0%
경 132
 
7.6%
기 132
 
7.6%
로 129
 
7.5%
곡 119
 
6.9%
읍 108
 
6.2%
Other values (36) 349
20.2%
Common
ValueCountFrequency (%)
529
52.6%
1 101
 
10.0%
7 55
 
5.5%
8 49
 
4.9%
6 43
 
4.3%
2 41
 
4.1%
4 40
 
4.0%
3 39
 
3.9%
5 36
 
3.6%
9 26
 
2.6%
Other values (2) 46
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1728
63.2%
ASCII 1005
36.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
529
52.6%
1 101
 
10.0%
7 55
 
5.5%
8 49
 
4.9%
6 43
 
4.3%
2 41
 
4.1%
4 40
 
4.0%
3 39
 
3.9%
5 36
 
3.6%
9 26
 
2.6%
Other values (2) 46
 
4.6%
Hangul
ValueCountFrequency (%)
연 162
9.4%
천 161
9.3%
전 158
9.1%
도 139
 
8.0%
군 139
 
8.0%
경 132
 
7.6%
기 132
 
7.6%
로 129
 
7.5%
곡 119
 
6.9%
읍 108
 
6.2%
Other values (36) 349
20.2%

지번주소
Text

Distinct127
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-13T08:41:59.808377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length22
Mean length21.666667
Min length19

Characters and Unicode

Total characters2860
Distinct characters57
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

Unique123 ?
Unique (%)93.2%

Sample

1st row경기도 연천군 전곡읍 전곡리 333-308
2nd row경기도 연천군 전곡읍 전곡리 300-17
3rd row경기도 연천군 신서면 도신리 273-11
4th row경기도 연천군 백학면 두일리 528-18
5th row경기도 연천군 연천읍 차탄리 34-248
ValueCountFrequency (%)
경기도 132
20.0%
연천군 132
20.0%
전곡읍 89
13.5%
전곡리 79
12.0%
연천읍 19
 
2.9%
차탄리 14
 
2.1%
은대리 10
 
1.5%
청산면 8
 
1.2%
도신리 7
 
1.1%
신서면 7
 
1.1%
Other values (144) 163
24.7%
2023-12-13T08:42:00.251433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
528
18.5%
전 169
 
5.9%
곡 168
 
5.9%
연 151
 
5.3%
천 151
 
5.3%
도 139
 
4.9%
군 136
 
4.8%
경 132
 
4.6%
리 132
 
4.6%
기 132
 
4.6%
Other values (47) 1022
35.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1582
55.3%
Decimal Number 624
 
21.8%
Space Separator 528
 
18.5%
Dash Punctuation 126
 
4.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 169
10.7%
곡 168
10.6%
연 151
9.5%
천 151
9.5%
도 139
8.8%
군 136
8.6%
경 132
8.3%
리 132
8.3%
기 132
8.3%
읍 108
6.8%
Other values (35) 164
10.4%
Decimal Number
ValueCountFrequency (%)
3 121
19.4%
4 100
16.0%
2 78
12.5%
1 64
10.3%
5 64
10.3%
6 58
9.3%
0 45
 
7.2%
8 35
 
5.6%
9 31
 
5.0%
7 28
 
4.5%
Space Separator
ValueCountFrequency (%)
528
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 126
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1582
55.3%
Common 1278
44.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 169
10.7%
곡 168
10.6%
연 151
9.5%
천 151
9.5%
도 139
8.8%
군 136
8.6%
경 132
8.3%
리 132
8.3%
기 132
8.3%
읍 108
6.8%
Other values (35) 164
10.4%
Common
ValueCountFrequency (%)
528
41.3%
- 126
 
9.9%
3 121
 
9.5%
4 100
 
7.8%
2 78
 
6.1%
1 64
 
5.0%
5 64
 
5.0%
6 58
 
4.5%
0 45
 
3.5%
8 35
 
2.7%
Other values (2) 59
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1582
55.3%
ASCII 1278
44.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
528
41.3%
- 126
 
9.9%
3 121
 
9.5%
4 100
 
7.8%
2 78
 
6.1%
1 64
 
5.0%
5 64
 
5.0%
6 58
 
4.5%
0 45
 
3.5%
8 35
 
2.7%
Other values (2) 59
 
4.6%
Hangul
ValueCountFrequency (%)
전 169
10.7%
곡 168
10.6%
연 151
9.5%
천 151
9.5%
도 139
8.8%
군 136
8.6%
경 132
8.3%
리 132
8.3%
기 132
8.3%
읍 108
6.8%
Other values (35) 164
10.4%

위도
Real number (ℝ)

Distinct127
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.047161
Minimum37.997363
Maximum38.186728
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-13T08:42:00.392274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.997363
5-th percentile38.021267
Q138.025514
median38.027856
Q338.035217
95-th percentile38.156404
Maximum38.186728
Range0.189365
Interquartile range (IQR)0.00970294

Descriptive statistics

Standard deviation0.043343821
Coefficient of variation (CV)0.001139213
Kurtosis3.3637081
Mean38.047161
Median Absolute Deviation (MAD)0.00305215
Skewness2.0014855
Sum5022.2252
Variance0.0018786869
MonotonicityNot monotonic
2023-12-13T08:42:00.507341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
38.02554373 3
 
2.3%
38.02850035 2
 
1.5%
38.03051851 2
 
1.5%
38.0281256 2
 
1.5%
38.02319336 1
 
0.8%
38.10094902 1
 
0.8%
38.03313197 1
 
0.8%
38.10111031 1
 
0.8%
38.02892931 1
 
0.8%
38.02763321 1
 
0.8%
Other values (117) 117
88.6%
ValueCountFrequency (%)
37.99736311 1
0.8%
37.99837965 1
0.8%
37.99881243 1
0.8%
38.00953782 1
0.8%
38.01478006 1
0.8%
38.01804816 1
0.8%
38.02037018 1
0.8%
38.02200134 1
0.8%
38.02270901 1
0.8%
38.02277897 1
0.8%
ValueCountFrequency (%)
38.18672811 1
0.8%
38.18602381 1
0.8%
38.18580138 1
0.8%
38.18568789 1
0.8%
38.1852678 1
0.8%
38.1848573 1
0.8%
38.18418812 1
0.8%
38.13367241 1
0.8%
38.1331714 1
0.8%
38.10231273 1
0.8%

경도
Real number (ℝ)

Distinct127
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.06778
Minimum126.91353
Maximum127.1353
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-13T08:42:00.628878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.91353
5-th percentile127.01891
Q1127.06814
median127.06947
Q3127.07296
95-th percentile127.10725
Maximum127.1353
Range0.2217633
Interquartile range (IQR)0.004825725

Descriptive statistics

Standard deviation0.028880075
Coefficient of variation (CV)0.00022728086
Kurtosis17.178738
Mean127.06778
Median Absolute Deviation (MAD)0.0017789
Skewness-3.4537032
Sum16772.947
Variance0.00083405871
MonotonicityNot monotonic
2023-12-13T08:42:00.741351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.069808 3
 
2.3%
127.0710716 2
 
1.5%
127.0623365 2
 
1.5%
127.0685801 2
 
1.5%
127.0715141 1
 
0.8%
127.0752968 1
 
0.8%
127.0718548 1
 
0.8%
127.0763816 1
 
0.8%
127.0701204 1
 
0.8%
127.0684898 1
 
0.8%
Other values (117) 117
88.6%
ValueCountFrequency (%)
126.9135342 1
0.8%
126.9142253 1
0.8%
126.9144486 1
0.8%
127.0118674 1
0.8%
127.0127945 1
0.8%
127.0182047 1
0.8%
127.0187568 1
0.8%
127.0190338 1
0.8%
127.0204405 1
0.8%
127.0623365 2
1.5%
ValueCountFrequency (%)
127.1352975 1
0.8%
127.1095058 1
0.8%
127.109186 1
0.8%
127.1084168 1
0.8%
127.1079465 1
0.8%
127.1075299 1
0.8%
127.1074239 1
0.8%
127.1071085 1
0.8%
127.1067123 1
0.8%
127.1066683 1
0.8%

전화번호
Text

MISSING 

Distinct98
Distinct (%)95.1%
Missing29
Missing (%)22.0%
Memory size1.2 KiB
2023-12-13T08:42:00.968562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.009709
Min length12

Characters and Unicode

Total characters1237
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

Unique93 ?
Unique (%)90.3%

Sample

1st row031-832-3468
2nd row031-832-2996
3rd row031-834-9543
4th row031-835-5360
5th row031-834-2322
ValueCountFrequency (%)
031-833-5515 2
 
1.9%
031-832-8997 2
 
1.9%
031-835-6301 2
 
1.9%
031-833-9476 2
 
1.9%
031-833-0965 2
 
1.9%
031-835-0446 1
 
1.0%
031-833-1515 1
 
1.0%
031-466-4882 1
 
1.0%
031-833-9980 1
 
1.0%
031-834-3232 1
 
1.0%
Other values (88) 88
85.4%
2023-12-13T08:42:01.327911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 263
21.3%
- 206
16.7%
0 158
12.8%
1 139
11.2%
8 134
10.8%
2 87
 
7.0%
5 65
 
5.3%
4 55
 
4.4%
7 45
 
3.6%
6 44
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1031
83.3%
Dash Punctuation 206
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 263
25.5%
0 158
15.3%
1 139
13.5%
8 134
13.0%
2 87
 
8.4%
5 65
 
6.3%
4 55
 
5.3%
7 45
 
4.4%
6 44
 
4.3%
9 41
 
4.0%
Dash Punctuation
ValueCountFrequency (%)
- 206
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1237
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 263
21.3%
- 206
16.7%
0 158
12.8%
1 139
11.2%
8 134
10.8%
2 87
 
7.0%
5 65
 
5.3%
4 55
 
4.4%
7 45
 
3.6%
6 44
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1237
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 263
21.3%
- 206
16.7%
0 158
12.8%
1 139
11.2%
8 134
10.8%
2 87
 
7.0%
5 65
 
5.3%
4 55
 
4.4%
7 45
 
3.6%
6 44
 
3.6%

기준일자
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)0.8%
Missing2
Missing (%)1.5%
Memory size1.2 KiB
Minimum2023-07-03 00:00:00
Maximum2023-07-03 00:00:00
2023-12-13T08:42:01.428194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:42:01.518741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T08:41:57.446024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:41:57.046721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:41:57.551924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:41:57.129090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:42:01.575532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도전화번호
위도1.0000.7520.000
경도0.7521.0000.955
전화번호0.0000.9551.000
2023-12-13T08:42:01.662382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.214
경도0.2141.000

Missing values

2023-12-13T08:41:57.652147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:41:57.769967image/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.
2023-12-13T08:41:57.853442image/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

업소명도로명주소지번주소위도경도전화번호기준일자
0복지이발관경기도 연천군 전곡읍 전곡역로 72번길 27경기도 연천군 전곡읍 전곡리 333-30838.023193127.071514031-832-34682023-07-03
1역전이발관경기도 연천군 전곡읍 온골로 17경기도 연천군 전곡읍 전곡리 300-1738.022709127.069585031-832-29962023-07-03
2남양이발소경기도 연천군 신서면 도대로 1경기도 연천군 신서면 도신리 273-1138.186728127.107946031-834-95432023-07-03
3마을이용원경기도 연천군 백학면 두백로 26경기도 연천군 백학면 두일리 528-1838.031662126.914449031-835-53602023-07-03
4금수이발관경기도 연천군 연천읍 연천로 269경기도 연천군 연천읍 차탄리 34-24838.100974127.074612031-834-23222023-07-03
5맘보이발관경기도 연천군 전곡읍 온골로 55경기도 연천군 전곡읍 전곡리 477-838.025808127.067686031-832-00622023-07-03
6향원이발관경기도 연천군 청산면 학담로103번길 10-1경기도 연천군 청산면 초성리 209-4737.99838127.071953031-832-58772023-07-03
7양지이발관경기도 연천군 청산면 궁평로 80-1경기도 연천군 청산면 궁평리 16938.030175127.109186031-835-77672023-07-03
8태양이발관경기도 연천군 신서면 도대로3번길 50경기도 연천군 신서면 도신리 290-9238.184857127.106668031-834-87732023-07-03
9제일이발관경기도 연천군 전곡읍 은전로 88경기도 연천군 전곡읍 전곡리 454-5938.028461127.069441031-832-33352023-07-03
업소명도로명주소지번주소위도경도전화번호기준일자
122차차네일(CHACHANAIL)경기도 연천군 전곡읍 평화로673번길 45경기도 연천군 전곡읍 은대리 640-1238.030519127.062337<NA>2023-07-03
123강스네일경기도 연천군 전곡읍 전곡로 187-1경기도 연천군 전곡읍 은대리 859-2838.028198127.066281<NA>2023-07-03
124쏘블리네일경기도 연천군 전곡읍 은전로78번길 5경기도 연천군 전곡읍 전곡리 459-2038.028126127.06858031-528-55672023-07-03
125토탈 뷰티경기도 연천군 전곡읍 전곡로196번길 19경기도 연천군 전곡읍 은대리 541-1438.029835127.067459<NA>2023-07-03
126제이엠뷰티경기도 연천군 전곡읍 온골로53번길 16-1경기도 연천군 전곡읍 전곡리 483-4338.025424127.066936<NA>2023-07-03
127샬롬네일경기도 연천군 전곡읍 은전로 104경기도 연천군 전곡읍 전곡리 353-3938.0285127.071072<NA>2023-07-03
128뷰티 메이즈퀸경기도 연천군 전곡읍 은전로78번길 61경기도 연천군 전곡읍 전곡리 333-3238.025544127.069808<NA>2023-07-03
129시크헤어경기도 연천군 전곡읍 전곡로 168-3경기도 연천군 전곡읍 전곡리 479-4838.027161127.067874<NA>2023-07-03
130라인 더하기경기도 연천군 전곡읍 전곡역로93번길 60경기도 연천군 전곡읍 전곡리 332-12338.026417127.07123<NA><NA>
131헤어살롱 라움경기도 연천군 전곡읍 은전로 75경기도 연천군 전곡읍 전곡리 455-6238.028353127.068033<NA><NA>