Overview

Dataset statistics

Number of variables7
Number of observations60
Missing cells8
Missing cells (%)1.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.5 KiB
Average record size in memory60.2 B

Variable types

Text4
Numeric2
DateTime1

Dataset

Description전라북도 무주군의 공중위생업에 관한 데이터로써 업소명, 소재지도로명주소, 소재지지번주소, 위도, 경도, 전화번호, 데이터기준일자 항목으로 구성
Author전라북도 무주군
URLhttps://www.data.go.kr/data/15007409/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
위도 is highly overall correlated with 경도High correlation
경도 is highly overall correlated with 위도High correlation
전화번호 has 8 (13.3%) missing valuesMissing

Reproduction

Analysis started2023-12-12 23:52:30.414999
Analysis finished2023-12-12 23:52:31.322684
Duration0.91 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

Distinct58
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size612.0 B
2023-12-13T08:52:31.503660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length5.4666667
Min length2

Characters and Unicode

Total characters328
Distinct characters141
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique56 ?
Unique (%)93.3%

Sample

1st row살롱드'S
2nd row무주왁싱 속눈썹 윙크샵
3rd row이미지미용실
4th row염색 이야기
5th row유알헤어
ValueCountFrequency (%)
윤미용실 2
 
2.7%
쌩얼 2
 
2.7%
미용실 2
 
2.7%
현미용실 2
 
2.7%
미인 1
 
1.4%
오샤레헤어 1
 
1.4%
경아미용실 1
 
1.4%
미다스피부삽 1
 
1.4%
영미용실 1
 
1.4%
살롱드's 1
 
1.4%
Other values (59) 59
80.8%
2023-12-13T08:52:31.875467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
미 32
 
9.8%
용 28
 
8.5%
실 27
 
8.2%
헤 13
 
4.0%
13
 
4.0%
어 13
 
4.0%
리 6
 
1.8%
이 6
 
1.8%
샵 5
 
1.5%
아 5
 
1.5%
Other values (131) 180
54.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 305
93.0%
Space Separator 13
 
4.0%
Uppercase Letter 8
 
2.4%
Decimal Number 1
 
0.3%
Other Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
미 32
 
10.5%
용 28
 
9.2%
실 27
 
8.9%
헤 13
 
4.3%
어 13
 
4.3%
리 6
 
2.0%
이 6
 
2.0%
샵 5
 
1.6%
아 5
 
1.6%
머 4
 
1.3%
Other values (122) 166
54.4%
Uppercase Letter
ValueCountFrequency (%)
S 2
25.0%
E 2
25.0%
Y 1
12.5%
L 1
12.5%
A 1
12.5%
H 1
12.5%
Space Separator
ValueCountFrequency (%)
13
100.0%
Decimal Number
ValueCountFrequency (%)
5 1
100.0%
Other Punctuation
ValueCountFrequency (%)
' 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 305
93.0%
Common 15
 
4.6%
Latin 8
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
미 32
 
10.5%
용 28
 
9.2%
실 27
 
8.9%
헤 13
 
4.3%
어 13
 
4.3%
리 6
 
2.0%
이 6
 
2.0%
샵 5
 
1.6%
아 5
 
1.6%
머 4
 
1.3%
Other values (122) 166
54.4%
Latin
ValueCountFrequency (%)
S 2
25.0%
E 2
25.0%
Y 1
12.5%
L 1
12.5%
A 1
12.5%
H 1
12.5%
Common
ValueCountFrequency (%)
13
86.7%
5 1
 
6.7%
' 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 305
93.0%
ASCII 23
 
7.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
미 32
 
10.5%
용 28
 
9.2%
실 27
 
8.9%
헤 13
 
4.3%
어 13
 
4.3%
리 6
 
2.0%
이 6
 
2.0%
샵 5
 
1.6%
아 5
 
1.6%
머 4
 
1.3%
Other values (122) 166
54.4%
ASCII
ValueCountFrequency (%)
13
56.5%
S 2
 
8.7%
E 2
 
8.7%
5 1
 
4.3%
' 1
 
4.3%
Y 1
 
4.3%
L 1
 
4.3%
A 1
 
4.3%
H 1
 
4.3%

소재지도로명주소
Text

Distinct57
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
2023-12-13T08:52:32.335369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length35
Mean length22.4
Min length18

Characters and Unicode

Total characters1344
Distinct characters71
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique54 ?
Unique (%)90.0%

Sample

1st row전라북도 무주군 무주읍 단천로 103
2nd row전라북도 무주군 무주읍 단천로 106 1층
3rd row전라북도 무주군 무주읍 단천로 109
4th row전라북도 무주군 무주읍 단천로 110-1 1층
5th row전라북도 무주군 무주읍 단천로 110-1 1층
ValueCountFrequency (%)
전라북도 60
18.5%
무주군 60
18.5%
무주읍 41
12.7%
주계로 19
 
5.9%
1층 15
 
4.6%
안성면 10
 
3.1%
단천로 9
 
2.8%
설천면 5
 
1.5%
안성로 5
 
1.5%
주계로8길 5
 
1.5%
Other values (81) 95
29.3%
2023-12-13T08:52:32.676694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
279
20.8%
주 126
 
9.4%
무 107
 
8.0%
1 73
 
5.4%
도 61
 
4.5%
라 61
 
4.5%
전 60
 
4.5%
북 60
 
4.5%
군 60
 
4.5%
로 55
 
4.1%
Other values (61) 402
29.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 842
62.6%
Space Separator 279
 
20.8%
Decimal Number 193
 
14.4%
Dash Punctuation 18
 
1.3%
Open Punctuation 6
 
0.4%
Close Punctuation 6
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 126
15.0%
무 107
12.7%
도 61
 
7.2%
라 61
 
7.2%
전 60
 
7.1%
북 60
 
7.1%
군 60
 
7.1%
로 55
 
6.5%
읍 41
 
4.9%
계 24
 
2.9%
Other values (47) 187
22.2%
Decimal Number
ValueCountFrequency (%)
1 73
37.8%
8 22
 
11.4%
2 17
 
8.8%
3 15
 
7.8%
0 13
 
6.7%
7 13
 
6.7%
5 13
 
6.7%
9 10
 
5.2%
4 9
 
4.7%
6 8
 
4.1%
Space Separator
ValueCountFrequency (%)
279
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 842
62.6%
Common 502
37.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 126
15.0%
무 107
12.7%
도 61
 
7.2%
라 61
 
7.2%
전 60
 
7.1%
북 60
 
7.1%
군 60
 
7.1%
로 55
 
6.5%
읍 41
 
4.9%
계 24
 
2.9%
Other values (47) 187
22.2%
Common
ValueCountFrequency (%)
279
55.6%
1 73
 
14.5%
8 22
 
4.4%
- 18
 
3.6%
2 17
 
3.4%
3 15
 
3.0%
0 13
 
2.6%
7 13
 
2.6%
5 13
 
2.6%
9 10
 
2.0%
Other values (4) 29
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 842
62.6%
ASCII 502
37.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
279
55.6%
1 73
 
14.5%
8 22
 
4.4%
- 18
 
3.6%
2 17
 
3.4%
3 15
 
3.0%
0 13
 
2.6%
7 13
 
2.6%
5 13
 
2.6%
9 10
 
2.0%
Other values (4) 29
 
5.8%
Hangul
ValueCountFrequency (%)
주 126
15.0%
무 107
12.7%
도 61
 
7.2%
라 61
 
7.2%
전 60
 
7.1%
북 60
 
7.1%
군 60
 
7.1%
로 55
 
6.5%
읍 41
 
4.9%
계 24
 
2.9%
Other values (47) 187
22.2%

소재지지번주소
Text

Distinct57
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
2023-12-13T08:52:32.929486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length33
Mean length24.333333
Min length21

Characters and Unicode

Total characters1460
Distinct characters67
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique54 ?
Unique (%)90.0%

Sample

1st row전라북도 무주군 무주읍 읍내리 301
2nd row전라북도 무주군 무주읍 읍내리 186-10
3rd row전라북도 무주군 무주읍 읍내리 249-4
4th row전라북도 무주군 무주읍 읍내리 185
5th row전라북도 무주군 무주읍 읍내리 185
ValueCountFrequency (%)
전라북도 60
19.2%
무주군 60
19.2%
무주읍 41
13.1%
읍내리 39
12.5%
장기리 10
 
3.2%
안성면 10
 
3.2%
설천면 5
 
1.6%
소천리 4
 
1.3%
854-3 2
 
0.6%
당산리 2
 
0.6%
Other values (75) 80
25.6%
2023-12-13T08:52:33.240464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
307
21.0%
무 104
 
7.1%
주 103
 
7.1%
읍 80
 
5.5%
1 74
 
5.1%
라 61
 
4.2%
전 60
 
4.1%
북 60
 
4.1%
도 60
 
4.1%
군 60
 
4.1%
Other values (57) 491
33.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 826
56.6%
Space Separator 307
 
21.0%
Decimal Number 273
 
18.7%
Dash Punctuation 48
 
3.3%
Open Punctuation 3
 
0.2%
Close Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
무 104
12.6%
주 103
12.5%
읍 80
9.7%
라 61
7.4%
전 60
7.3%
북 60
7.3%
도 60
7.3%
군 60
7.3%
리 60
7.3%
내 41
 
5.0%
Other values (43) 137
16.6%
Decimal Number
ValueCountFrequency (%)
1 74
27.1%
2 40
14.7%
3 29
 
10.6%
0 28
 
10.3%
4 23
 
8.4%
5 22
 
8.1%
9 15
 
5.5%
6 15
 
5.5%
8 14
 
5.1%
7 13
 
4.8%
Space Separator
ValueCountFrequency (%)
307
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 48
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 826
56.6%
Common 634
43.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
무 104
12.6%
주 103
12.5%
읍 80
9.7%
라 61
7.4%
전 60
7.3%
북 60
7.3%
도 60
7.3%
군 60
7.3%
리 60
7.3%
내 41
 
5.0%
Other values (43) 137
16.6%
Common
ValueCountFrequency (%)
307
48.4%
1 74
 
11.7%
- 48
 
7.6%
2 40
 
6.3%
3 29
 
4.6%
0 28
 
4.4%
4 23
 
3.6%
5 22
 
3.5%
9 15
 
2.4%
6 15
 
2.4%
Other values (4) 33
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 826
56.6%
ASCII 634
43.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
307
48.4%
1 74
 
11.7%
- 48
 
7.6%
2 40
 
6.3%
3 29
 
4.6%
0 28
 
4.4%
4 23
 
3.6%
5 22
 
3.5%
9 15
 
2.4%
6 15
 
2.4%
Other values (4) 33
 
5.2%
Hangul
ValueCountFrequency (%)
무 104
12.6%
주 103
12.5%
읍 80
9.7%
라 61
7.4%
전 60
7.3%
북 60
7.3%
도 60
7.3%
군 60
7.3%
리 60
7.3%
내 41
 
5.0%
Other values (43) 137
16.6%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct57
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.97908
Minimum35.864645
Maximum36.009904
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-13T08:52:33.354685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.864645
5-th percentile35.866117
Q135.996942
median36.006474
Q336.007489
95-th percentile36.008699
Maximum36.009904
Range0.145259
Interquartile range (IQR)0.010547

Descriptive statistics

Standard deviation0.05352506
Coefficient of variation (CV)0.0014876717
Kurtosis0.65957985
Mean35.97908
Median Absolute Deviation (MAD)0.001089155
Skewness-1.572302
Sum2158.7448
Variance0.002864932
MonotonicityNot monotonic
2023-12-13T08:52:33.459680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.007484 2
 
3.3%
36.007563 2
 
3.3%
36.006361 2
 
3.3%
36.007793 1
 
1.7%
36.008453 1
 
1.7%
36.007505 1
 
1.7%
36.006767 1
 
1.7%
36.007271 1
 
1.7%
36.004672 1
 
1.7%
36.005654 1
 
1.7%
Other values (47) 47
78.3%
ValueCountFrequency (%)
35.864645 1
1.7%
35.864997 1
1.7%
35.86605 1
1.7%
35.866121 1
1.7%
35.86638253 1
1.7%
35.866449 1
1.7%
35.86706 1
1.7%
35.867296 1
1.7%
35.86748 1
1.7%
35.867636 1
1.7%
ValueCountFrequency (%)
36.009904 1
1.7%
36.009895 1
1.7%
36.00983798 1
1.7%
36.008639 1
1.7%
36.008615 1
1.7%
36.008453 1
1.7%
36.007962 1
1.7%
36.007911 1
1.7%
36.007793 1
1.7%
36.00776 1
1.7%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct57
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.6748
Minimum127.55934
Maximum127.85211
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-13T08:52:33.573944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.55934
5-th percentile127.65339
Q1127.65646
median127.66158
Q3127.66315
95-th percentile127.78812
Maximum127.85211
Range0.292773
Interquartile range (IQR)0.006691

Descriptive statistics

Standard deviation0.050416188
Coefficient of variation (CV)0.0003948797
Kurtosis5.137759
Mean127.6748
Median Absolute Deviation (MAD)0.002833
Skewness2.1885735
Sum7660.4882
Variance0.002541792
MonotonicityNot monotonic
2023-12-13T08:52:33.679861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.66159 2
 
3.3%
127.663114 2
 
3.3%
127.659508 2
 
3.3%
127.662342 1
 
1.7%
127.788087 1
 
1.7%
127.661572 1
 
1.7%
127.661907 1
 
1.7%
127.661583 1
 
1.7%
127.664375 1
 
1.7%
127.668107 1
 
1.7%
Other values (47) 47
78.3%
ValueCountFrequency (%)
127.559338 1
1.7%
127.652856 1
1.7%
127.653366 1
1.7%
127.6533879 1
1.7%
127.653557 1
1.7%
127.653688 1
1.7%
127.653769 1
1.7%
127.65385 1
1.7%
127.65404 1
1.7%
127.654185 1
1.7%
ValueCountFrequency (%)
127.852111 1
1.7%
127.8485938 1
1.7%
127.788821 1
1.7%
127.788087 1
1.7%
127.787667 1
1.7%
127.786625 1
1.7%
127.779904 1
1.7%
127.668107 1
1.7%
127.6647895 1
1.7%
127.664446 1
1.7%

전화번호
Text

MISSING 

Distinct52
Distinct (%)100.0%
Missing8
Missing (%)13.3%
Memory size612.0 B
2023-12-13T08:52:33.876196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.230769
Min length12

Characters and Unicode

Total characters636
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

Unique52 ?
Unique (%)100.0%

Sample

1st row0507-1370-1752
2nd row063-323-8009
3rd row063-324-7570
4th row063-322-8416
5th row0507-1306-7207
ValueCountFrequency (%)
063-322-2672 1
 
1.9%
0507-1313-8404 1
 
1.9%
063-324-7020 1
 
1.9%
063-322-2716 1
 
1.9%
063-324-1980 1
 
1.9%
0507-1387-5895 1
 
1.9%
063-322-5559 1
 
1.9%
063-322-4161 1
 
1.9%
063-3243-433 1
 
1.9%
063-322-5741 1
 
1.9%
Other values (42) 42
80.8%
2023-12-13T08:52:34.182786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 126
19.8%
- 104
16.4%
2 89
14.0%
0 82
12.9%
6 61
9.6%
4 46
 
7.2%
1 34
 
5.3%
5 32
 
5.0%
7 25
 
3.9%
9 19
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 532
83.6%
Dash Punctuation 104
 
16.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 126
23.7%
2 89
16.7%
0 82
15.4%
6 61
11.5%
4 46
 
8.6%
1 34
 
6.4%
5 32
 
6.0%
7 25
 
4.7%
9 19
 
3.6%
8 18
 
3.4%
Dash Punctuation
ValueCountFrequency (%)
- 104
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 636
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 126
19.8%
- 104
16.4%
2 89
14.0%
0 82
12.9%
6 61
9.6%
4 46
 
7.2%
1 34
 
5.3%
5 32
 
5.0%
7 25
 
3.9%
9 19
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 636
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 126
19.8%
- 104
16.4%
2 89
14.0%
0 82
12.9%
6 61
9.6%
4 46
 
7.2%
1 34
 
5.3%
5 32
 
5.0%
7 25
 
3.9%
9 19
 
3.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size612.0 B
Minimum2021-12-15 00:00:00
Maximum2021-12-15 00:00:00
2023-12-13T08:52:34.273234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:52:34.342427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T08:52:30.973825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:52:30.810017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:52:31.050894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:52:30.898867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:52:34.395874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소명소재지도로명주소소재지지번주소위도경도전화번호
업소명1.0000.9780.9780.6150.0001.000
소재지도로명주소0.9781.0001.0001.0001.0001.000
소재지지번주소0.9781.0001.0001.0001.0001.000
위도0.6151.0001.0001.0000.6661.000
경도0.0001.0001.0000.6661.0001.000
전화번호1.0001.0001.0001.0001.0001.000
2023-12-13T08:52:34.475531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.595
경도0.5951.000

Missing values

2023-12-13T08:52:31.175113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:52:31.275670image/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

업소명소재지도로명주소소재지지번주소위도경도전화번호데이터기준일자
0살롱드'S전라북도 무주군 무주읍 단천로 103전라북도 무주군 무주읍 읍내리 30136.007793127.6623420507-1370-17522021-12-15
1무주왁싱 속눈썹 윙크샵전라북도 무주군 무주읍 단천로 106 1층전라북도 무주군 무주읍 읍내리 186-1036.007553127.662811063-323-80092021-12-15
2이미지미용실전라북도 무주군 무주읍 단천로 109전라북도 무주군 무주읍 읍내리 249-436.00776127.663021063-324-75702021-12-15
3염색 이야기전라북도 무주군 무주읍 단천로 110-1 1층전라북도 무주군 무주읍 읍내리 18536.007563127.663114063-322-84162021-12-15
4유알헤어전라북도 무주군 무주읍 단천로 110-1 1층전라북도 무주군 무주읍 읍내리 18536.007563127.6631140507-1306-72072021-12-15
5이례미용실전라북도 무주군 무주읍 단천로 75-6전라북도 무주군 무주읍 읍내리 80536.007962127.65924063-322-82222021-12-15
6쌩얼 EYE LASH전라북도 무주군 무주읍 단천로 79전라북도 무주군 무주읍 읍내리 854-336.006361127.659508<NA>2021-12-15
7쌩얼 네일아트전라북도 무주군 무주읍 단천로 79전라북도 무주군 무주읍 읍내리 854-336.007911127.659788<NA>2021-12-15
8제이헤어전라북도 무주군 무주읍 단천로 84전라북도 무주군 무주읍 읍내리 876-1036.007687127.660263<NA>2021-12-15
9호박미용실전라북도 무주군 무주읍 단천로5길 8-2전라북도 무주군 무주읍 읍내리 31236.008639127.661667063-322-31532021-12-15
업소명소재지도로명주소소재지지번주소위도경도전화번호데이터기준일자
50김도연헤어컬렉션전라북도 무주군 안성면 시장윗길 7전라북도 무주군 안성면 장기리 1506-135.867296127.654223063-323-19112021-12-15
51신세계미용실전라북도 무주군 안성면 신촌길 8전라북도 무주군 안성면 장기리 1553-135.864645127.65404063-324-11552021-12-15
52요술가위전라북도 무주군 안성면 안성로 264-1전라북도 무주군 안성면 장기리 1552-8 외 1필지35.864997127.653688063-323-34682021-12-15
53소명전라북도 무주군 안성면 안성로 275-8 1층전라북도 무주군 안성면 장기리 1511-4735.86605127.653769<NA>2021-12-15
54소라미용실전라북도 무주군 안성면 안성로 281전라북도 무주군 안성면 장기리 1511-1735.866449127.654185063-323-00292021-12-15
55미인 미용실전라북도 무주군 안성면 안성로 287 ((1층))전라북도 무주군 안성면 장기리 1330-13 (1층)35.86706127.654423063-323-29922021-12-15
56작품하나머리방전라북도 무주군 안성면 안성로 293-1전라북도 무주군 안성면 장기리 1333-235.867636127.654588063-323-04442021-12-15
57이쁠래미용실전라북도 무주군 안성면 칠연로 38 덕유산장터 장옥동 1층 8호전라북도 무주군 안성면 장기리 1511-6 덕유산장터35.866121127.653557063-323-15552021-12-15
58영미용실전라북도 무주군 안성면 칠연로 38-4 1층전라북도 무주군 안성면 장기리 1511-6035.866383127.653388063-323-11462021-12-15
59벧엘미용실전라북도 무주군 적상면 성내길 18전라북도 무주군 적상면 사천리 324-235.944379127.659058063-324-64222021-12-15