Overview

Dataset statistics

Number of variables8
Number of observations92
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.2 KiB
Average record size in memory69.4 B

Variable types

Text2
Numeric4
Categorical2

Dataset

Description광주광역시 서구 경로우대 이미용실 정보에 대한 데이터로 업소명, 정상가격, 우대가격 등에 대한 정보를 제공합니다.
Author광주광역시 서구
URLhttps://www.data.go.kr/data/15033517/fileData.do

Alerts

위도 is highly overall correlated with 행정동High correlation
경도 is highly overall correlated with 행정동High correlation
정상가격 is highly overall correlated with 우대가격High correlation
우대가격 is highly overall correlated with 정상가격High correlation
행정동 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
업소명 has unique valuesUnique

Reproduction

Analysis started2024-01-06 13:14:31.883420
Analysis finished2024-01-06 13:14:38.010046
Duration6.13 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

UNIQUE 

Distinct92
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size868.0 B
2024-01-06T13:14:38.555939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length4.923913
Min length1

Characters and Unicode

Total characters453
Distinct characters160
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

Unique92 ?
Unique (%)100.0%

Sample

1st row우주이발관
2nd row우영이용원
3rd row서석이발관
4th row해성이용원
5th row쌍촌이용원
ValueCountFrequency (%)
우주이발관 1
 
1.1%
원헤어아트 1
 
1.1%
박진주헤어클럽 1
 
1.1%
알파미용실 1
 
1.1%
니콜 1
 
1.1%
똘레헤어 1
 
1.1%
글로리아헤어샵 1
 
1.1%
세리박 1
 
1.1%
끌리네헤어뉴스 1
 
1.1%
헤어180 1
 
1.1%
Other values (82) 82
89.1%
2024-01-06T13:14:39.796524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
어 39
 
8.6%
헤 39
 
8.6%
용 19
 
4.2%
미 18
 
4.0%
리 16
 
3.5%
실 14
 
3.1%
샵 12
 
2.6%
스 12
 
2.6%
이 10
 
2.2%
머 7
 
1.5%
Other values (150) 267
58.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 444
98.0%
Decimal Number 6
 
1.3%
Close Punctuation 1
 
0.2%
Lowercase Letter 1
 
0.2%
Open Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
어 39
 
8.8%
헤 39
 
8.8%
용 19
 
4.3%
미 18
 
4.1%
리 16
 
3.6%
실 14
 
3.2%
샵 12
 
2.7%
스 12
 
2.7%
이 10
 
2.3%
머 7
 
1.6%
Other values (142) 258
58.1%
Decimal Number
ValueCountFrequency (%)
0 2
33.3%
1 1
16.7%
8 1
16.7%
6 1
16.7%
3 1
16.7%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 444
98.0%
Common 8
 
1.8%
Latin 1
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
어 39
 
8.8%
헤 39
 
8.8%
용 19
 
4.3%
미 18
 
4.1%
리 16
 
3.6%
실 14
 
3.2%
샵 12
 
2.7%
스 12
 
2.7%
이 10
 
2.3%
머 7
 
1.6%
Other values (142) 258
58.1%
Common
ValueCountFrequency (%)
0 2
25.0%
1 1
12.5%
8 1
12.5%
) 1
12.5%
( 1
12.5%
6 1
12.5%
3 1
12.5%
Latin
ValueCountFrequency (%)
e 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 444
98.0%
ASCII 9
 
2.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
어 39
 
8.8%
헤 39
 
8.8%
용 19
 
4.3%
미 18
 
4.1%
리 16
 
3.6%
실 14
 
3.2%
샵 12
 
2.7%
스 12
 
2.7%
이 10
 
2.3%
머 7
 
1.6%
Other values (142) 258
58.1%
ASCII
ValueCountFrequency (%)
0 2
22.2%
1 1
11.1%
8 1
11.1%
) 1
11.1%
e 1
11.1%
( 1
11.1%
6 1
11.1%
3 1
11.1%

주소
Text

Distinct89
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size868.0 B
2024-01-06T13:14:40.816677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length21
Mean length18.673913
Min length14

Characters and Unicode

Total characters1718
Distinct characters74
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

Unique86 ?
Unique (%)93.5%

Sample

1st row광주광역시 서구 경열로146번길 1-1
2nd row광주광역시 서구 천변좌로 216-3
3rd row광주광역시 서구 대남대로461번길 11
4th row광주광역시 서구 군분로235번길 7
5th row광주광역시 서구 운천로172번길 16
ValueCountFrequency (%)
광주광역시 92
25.0%
서구 92
25.0%
화정로 5
 
1.4%
14 4
 
1.1%
화운로 4
 
1.1%
쌍학로 3
 
0.8%
쌍촌로 3
 
0.8%
11 3
 
0.8%
22 3
 
0.8%
16 3
 
0.8%
Other values (128) 156
42.4%
2024-01-06T13:14:42.322821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
276
16.1%
광 184
 
10.7%
1 99
 
5.8%
구 93
 
5.4%
주 93
 
5.4%
역 92
 
5.4%
시 92
 
5.4%
서 92
 
5.4%
로 91
 
5.3%
길 54
 
3.1%
Other values (64) 552
32.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1064
61.9%
Decimal Number 354
 
20.6%
Space Separator 276
 
16.1%
Dash Punctuation 24
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 184
17.3%
구 93
8.7%
주 93
8.7%
역 92
8.6%
시 92
8.6%
서 92
8.6%
로 91
8.6%
길 54
 
5.1%
번 53
 
5.0%
화 30
 
2.8%
Other values (52) 190
17.9%
Decimal Number
ValueCountFrequency (%)
1 99
28.0%
2 50
14.1%
3 36
 
10.2%
4 31
 
8.8%
6 27
 
7.6%
5 26
 
7.3%
9 26
 
7.3%
7 21
 
5.9%
8 20
 
5.6%
0 18
 
5.1%
Space Separator
ValueCountFrequency (%)
276
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1064
61.9%
Common 654
38.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 184
17.3%
구 93
8.7%
주 93
8.7%
역 92
8.6%
시 92
8.6%
서 92
8.6%
로 91
8.6%
길 54
 
5.1%
번 53
 
5.0%
화 30
 
2.8%
Other values (52) 190
17.9%
Common
ValueCountFrequency (%)
276
42.2%
1 99
 
15.1%
2 50
 
7.6%
3 36
 
5.5%
4 31
 
4.7%
6 27
 
4.1%
5 26
 
4.0%
9 26
 
4.0%
- 24
 
3.7%
7 21
 
3.2%
Other values (2) 38
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1064
61.9%
ASCII 654
38.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
276
42.2%
1 99
 
15.1%
2 50
 
7.6%
3 36
 
5.5%
4 31
 
4.7%
6 27
 
4.1%
5 26
 
4.0%
9 26
 
4.0%
- 24
 
3.7%
7 21
 
3.2%
Other values (2) 38
 
5.8%
Hangul
ValueCountFrequency (%)
광 184
17.3%
구 93
8.7%
주 93
8.7%
역 92
8.6%
시 92
8.6%
서 92
8.6%
로 91
8.6%
길 54
 
5.1%
번 53
 
5.0%
화 30
 
2.8%
Other values (52) 190
17.9%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct89
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.148641
Minimum35.120768
Maximum35.170215
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size960.0 B
2024-01-06T13:14:42.905802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.120768
5-th percentile35.126354
Q135.143357
median35.148494
Q335.156114
95-th percentile35.164929
Maximum35.170215
Range0.04944729
Interquartile range (IQR)0.012756315

Descriptive statistics

Standard deviation0.010788751
Coefficient of variation (CV)0.00030694647
Kurtosis0.46863949
Mean35.148641
Median Absolute Deviation (MAD)0.006974235
Skewness-0.51640744
Sum3233.675
Variance0.00011639716
MonotonicityNot monotonic
2024-01-06T13:14:43.658309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.14227435 2
 
2.2%
35.14654499 2
 
2.2%
35.13401723 2
 
2.2%
35.15382979 1
 
1.1%
35.14975322 1
 
1.1%
35.13656786 1
 
1.1%
35.14342054 1
 
1.1%
35.1414726 1
 
1.1%
35.1410891 1
 
1.1%
35.13807676 1
 
1.1%
Other values (79) 79
85.9%
ValueCountFrequency (%)
35.12076805 1
1.1%
35.12129116 1
1.1%
35.12169714 1
1.1%
35.12368417 1
1.1%
35.12626909 1
1.1%
35.12642329 1
1.1%
35.12956421 1
1.1%
35.13121232 1
1.1%
35.13401723 2
2.2%
35.13656786 1
1.1%
ValueCountFrequency (%)
35.17021534 1
1.1%
35.17003562 1
1.1%
35.16990083 1
1.1%
35.16536487 1
1.1%
35.16496975 1
1.1%
35.16489642 1
1.1%
35.16456528 1
1.1%
35.16435049 1
1.1%
35.16238756 1
1.1%
35.16011554 1
1.1%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct89
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.87351
Minimum126.84319
Maximum126.90654
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size960.0 B
2024-01-06T13:14:44.239992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.84319
5-th percentile126.85656
Q1126.86291
median126.87315
Q3126.88274
95-th percentile126.89499
Maximum126.90654
Range0.063353
Interquartile range (IQR)0.019832825

Descriptive statistics

Standard deviation0.01304787
Coefficient of variation (CV)0.00010284157
Kurtosis-0.23923
Mean126.87351
Median Absolute Deviation (MAD)0.0098938
Skewness0.32544855
Sum11672.363
Variance0.00017024692
MonotonicityNot monotonic
2024-01-06T13:14:44.788404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.8836736 2
 
2.2%
126.850108 2
 
2.2%
126.8613852 2
 
2.2%
126.9012361 1
 
1.1%
126.8591386 1
 
1.1%
126.8586115 1
 
1.1%
126.8583696 1
 
1.1%
126.8586786 1
 
1.1%
126.8597046 1
 
1.1%
126.8609694 1
 
1.1%
Other values (79) 79
85.9%
ValueCountFrequency (%)
126.8431866 1
1.1%
126.850108 2
2.2%
126.8548984 1
1.1%
126.8554062 1
1.1%
126.8575057 1
1.1%
126.8582598 1
1.1%
126.8583696 1
1.1%
126.8586115 1
1.1%
126.8586786 1
1.1%
126.8591386 1
1.1%
ValueCountFrequency (%)
126.9065396 1
1.1%
126.9058958 1
1.1%
126.9012361 1
1.1%
126.9006112 1
1.1%
126.8951692 1
1.1%
126.8948414 1
1.1%
126.8946924 1
1.1%
126.8943106 1
1.1%
126.8908724 1
1.1%
126.8883861 1
1.1%

행정동
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)19.6%
Missing0
Missing (%)0.0%
Memory size868.0 B
상무2동
17 
화정3동
7 
화정1동
7 
화정2동
7 
농성1동
6 
Other values (13)
48 

Length

Max length4
Median length4
Mean length3.6956522
Min length2

Unique

Unique1 ?
Unique (%)1.1%

Sample

1st row양동
2nd row양동
3rd row농성2동
4th row농성2동
5th row상무2동

Common Values

ValueCountFrequency (%)
상무2동 17
18.5%
화정3동 7
 
7.6%
화정1동 7
 
7.6%
화정2동 7
 
7.6%
농성1동 6
 
6.5%
농성2동 6
 
6.5%
상무1동 6
 
6.5%
화정4동 5
 
5.4%
풍암동 5
 
5.4%
양동 4
 
4.3%
Other values (8) 22
23.9%

Length

2024-01-06T13:14:45.410599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
상무2동 17
18.5%
화정1동 7
 
7.6%
화정2동 7
 
7.6%
화정3동 7
 
7.6%
농성1동 6
 
6.5%
농성2동 6
 
6.5%
상무1동 6
 
6.5%
화정4동 5
 
5.4%
풍암동 5
 
5.4%
금호1동 4
 
4.3%
Other values (8) 22
23.9%

품목
Categorical

Distinct3
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size868.0 B
컷트
72 
이발
10 
컷트
10 

Length

Max length4
Median length4
Mean length3.7826087
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row 이발
2nd row 이발
3rd row 이발
4th row 이발
5th row 이발

Common Values

ValueCountFrequency (%)
컷트 72
78.3%
이발 10
 
10.9%
컷트 10
 
10.9%

Length

2024-01-06T13:14:46.042241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-06T13:14:46.571570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
컷트 82
89.1%
이발 10
 
10.9%

정상가격
Real number (ℝ)

HIGH CORRELATION 

Distinct16
Distinct (%)17.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10239.13
Minimum5000
Maximum30000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size960.0 B
2024-01-06T13:14:46.915702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5000
5-th percentile6000
Q17000
median10000
Q312000
95-th percentile16900
Maximum30000
Range25000
Interquartile range (IQR)5000

Descriptive statistics

Standard deviation4114.7538
Coefficient of variation (CV)0.40186556
Kurtosis5.5202556
Mean10239.13
Median Absolute Deviation (MAD)2000
Skewness1.8673877
Sum942000
Variance16931199
MonotonicityNot monotonic
2024-01-06T13:14:47.416766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
10000 21
22.8%
7000 18
19.6%
8000 13
14.1%
12000 10
10.9%
15000 10
10.9%
6000 6
 
6.5%
5000 3
 
3.3%
9000 2
 
2.2%
13000 2
 
2.2%
18000 1
 
1.1%
Other values (6) 6
 
6.5%
ValueCountFrequency (%)
5000 3
 
3.3%
6000 6
 
6.5%
7000 18
19.6%
8000 13
14.1%
9000 2
 
2.2%
10000 21
22.8%
11000 1
 
1.1%
12000 10
10.9%
13000 2
 
2.2%
15000 10
10.9%
ValueCountFrequency (%)
30000 1
 
1.1%
23000 1
 
1.1%
20000 1
 
1.1%
19000 1
 
1.1%
18000 1
 
1.1%
16000 1
 
1.1%
15000 10
10.9%
13000 2
 
2.2%
12000 10
10.9%
11000 1
 
1.1%

우대가격
Real number (ℝ)

HIGH CORRELATION 

Distinct15
Distinct (%)16.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6783.6957
Minimum2000
Maximum25000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size960.0 B
2024-01-06T13:14:47.871473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2000
5-th percentile3000
Q15000
median5000
Q38000
95-th percentile13000
Maximum25000
Range23000
Interquartile range (IQR)3000

Descriptive statistics

Standard deviation3664.06
Coefficient of variation (CV)0.54012741
Kurtosis6.2368234
Mean6783.6957
Median Absolute Deviation (MAD)1000
Skewness2.0428934
Sum624100
Variance13425336
MonotonicityNot monotonic
2024-01-06T13:14:48.447946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
5000 33
35.9%
4000 10
 
10.9%
10000 10
 
10.9%
7000 8
 
8.7%
3000 8
 
8.7%
8000 6
 
6.5%
6000 4
 
4.3%
12000 4
 
4.3%
9000 2
 
2.2%
13000 2
 
2.2%
Other values (5) 5
 
5.4%
ValueCountFrequency (%)
2000 1
 
1.1%
3000 8
 
8.7%
4000 10
 
10.9%
5000 33
35.9%
6000 4
 
4.3%
7000 8
 
8.7%
8000 6
 
6.5%
9000 2
 
2.2%
10000 10
 
10.9%
12000 4
 
4.3%
ValueCountFrequency (%)
25000 1
 
1.1%
17100 1
 
1.1%
16000 1
 
1.1%
15000 1
 
1.1%
13000 2
 
2.2%
12000 4
 
4.3%
10000 10
10.9%
9000 2
 
2.2%
8000 6
6.5%
7000 8
8.7%

Interactions

2024-01-06T13:14:36.163896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:14:33.276267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:14:34.267114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:14:35.212309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:14:36.379988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:14:33.535573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:14:34.527477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:14:35.455889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:14:36.630701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:14:33.784314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:14:34.776604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:14:35.715235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:14:36.880130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:14:34.027830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:14:34.978616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:14:35.938803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-06T13:14:48.812803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소명주소위도경도행정동품목정상가격우대가격
업소명1.0001.0001.0001.0001.0001.0001.0001.000
주소1.0001.0001.0001.0001.0000.8180.9780.988
위도1.0001.0001.0000.5450.9200.0000.5510.379
경도1.0001.0000.5451.0000.9350.3310.1810.161
행정동1.0001.0000.9200.9351.0000.5140.5450.462
품목1.0000.8180.0000.3310.5141.0000.3930.000
정상가격1.0000.9780.5510.1810.5450.3931.0000.954
우대가격1.0000.9880.3790.1610.4620.0000.9541.000
2024-01-06T13:14:49.437804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동품목
행정동1.0000.249
품목0.2491.000
2024-01-06T13:14:49.742538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도정상가격우대가격행정동품목
위도1.0000.316-0.0040.0480.6500.000
경도0.3161.000-0.297-0.1760.6900.199
정상가격-0.004-0.2971.0000.8720.2120.271
우대가격0.048-0.1760.8721.0000.1900.003
행정동0.6500.6900.2120.1901.0000.249
품목0.0000.1990.2710.0030.2491.000

Missing values

2024-01-06T13:14:37.392671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-06T13:14:37.881742image/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

업소명주소위도경도행정동품목정상가격우대가격
0우주이발관광주광역시 서구 경열로146번길 1-135.15383126.901236양동이발80005000
1우영이용원광주광역시 서구 천변좌로 216-335.155437126.900611양동이발80005000
2서석이발관광주광역시 서구 대남대로461번길 1135.15052126.884917농성2동이발100005000
3해성이용원광주광역시 서구 군분로235번길 735.151388126.88091농성2동이발100008000
4쌍촌이용원광주광역시 서구 운천로172번길 1635.147981126.85826상무2동이발120009000
5우등이용원광주광역시 서구 금화로393번길 2335.144125126.887162화정2동이발80006000
6동보이발관광주광역시 서구 화정로161번길 2735.147481126.87596화정3동이발100008000
7성원이용원광주광역시 서구 마륵복개로 10835.146545126.850108서창동이발120008000
8신광성광주광역시 서구 죽봉대로119번길 2435.16497126.881322광천동이발100007000
9뉴시티광주광역시 서구 상무공원로 12635.155582126.843187치평동이발120009000
업소명주소위도경도행정동품목정상가격우대가격
82광명헤어광주광역시 서구 내방로251번길 935.159278126.867183상무1동컷트1500010000
83티지헤어광주광역시 서구 월산로 269-235.159871126.888202농성1동컷트1500013000
84까망머리광주광역시 서구 쌍학로 1135.146476126.866243상무2동컷트110008000
85영미용실광주광역시 서구 내방로 430-135.15977126.886502농성1동컷트70005000
86머리마을광주광역시 서구 대남대로487번길 2035.151219126.884205농성2동컷트70005000
87엔젤뷰티샵광주광역시 서구 쌍촌로 1935.146647126.864886상무2동컷트1500012000
88라로헤어광주광역시 서구 화정로 135.144514126.857506상무2동컷트1500010000
89소망미용실광주광역시 서구 월산로267번길 2635.158026126.886513농성1동컷트1500010000
90머리하기좋은날광주광역시 서구 마재로 5935.131212126.864935금호2동컷트100007000
91블루밍헤어광주광역시 서구 화개1로 6335.129564126.854898금호2동컷트1600012000