Overview

Dataset statistics

Number of variables8
Number of observations32
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.2 KiB
Average record size in memory71.1 B

Variable types

Numeric3
Categorical1
Text3
DateTime1

Dataset

Description광주광역시 광산구 내 가격안정 모범업소 현황 정보(업종, 업체명, 주소, 전화번호, 위도, 경도, 데이터기준일자 등)를 제공합니다.
URLhttps://www.data.go.kr/data/15005640/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
위도 is highly overall correlated with 경도High correlation
경도 is highly overall correlated with 위도High correlation
연번 has unique valuesUnique
업체명 has unique valuesUnique
도로명주소 has unique valuesUnique
전화번호 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique

Reproduction

Analysis started2023-12-12 21:36:13.629273
Analysis finished2023-12-12 21:36:14.995677
Duration1.37 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.5
Minimum1
Maximum32
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-13T06:36:15.068749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.55
Q18.75
median16.5
Q324.25
95-th percentile30.45
Maximum32
Range31
Interquartile range (IQR)15.5

Descriptive statistics

Standard deviation9.3808315
Coefficient of variation (CV)0.56853524
Kurtosis-1.2
Mean16.5
Median Absolute Deviation (MAD)8
Skewness0
Sum528
Variance88
MonotonicityStrictly increasing
2023-12-13T06:36:15.215394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
1 1
 
3.1%
18 1
 
3.1%
32 1
 
3.1%
31 1
 
3.1%
30 1
 
3.1%
29 1
 
3.1%
28 1
 
3.1%
27 1
 
3.1%
26 1
 
3.1%
25 1
 
3.1%
Other values (22) 22
68.8%
ValueCountFrequency (%)
1 1
3.1%
2 1
3.1%
3 1
3.1%
4 1
3.1%
5 1
3.1%
6 1
3.1%
7 1
3.1%
8 1
3.1%
9 1
3.1%
10 1
3.1%
ValueCountFrequency (%)
32 1
3.1%
31 1
3.1%
30 1
3.1%
29 1
3.1%
28 1
3.1%
27 1
3.1%
26 1
3.1%
25 1
3.1%
24 1
3.1%
23 1
3.1%

업종
Categorical

Distinct10
Distinct (%)31.2%
Missing0
Missing (%)0.0%
Memory size388.0 B
한식_육류
9 
이미용업
4 
한식_분식
4 
한식_찌개류
4 
목욕업
2 
Other values (5)
9 

Length

Max length6
Median length5
Mean length4.34375
Min length2

Unique

Unique1 ?
Unique (%)3.1%

Sample

1st row목욕업
2nd row목욕업
3rd row세탁업
4th row이미용업
5th row이미용업

Common Values

ValueCountFrequency (%)
한식_육류 9
28.1%
이미용업 4
12.5%
한식_분식 4
12.5%
한식_찌개류 4
12.5%
목욕업 2
 
6.2%
세탁업 2
 
6.2%
중식 2
 
6.2%
한식_일반 2
 
6.2%
일식 2
 
6.2%
기타양식 1
 
3.1%

Length

2023-12-13T06:36:15.399525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:36:15.551704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한식_육류 9
28.1%
이미용업 4
12.5%
한식_분식 4
12.5%
한식_찌개류 4
12.5%
목욕업 2
 
6.2%
세탁업 2
 
6.2%
중식 2
 
6.2%
한식_일반 2
 
6.2%
일식 2
 
6.2%
기타양식 1
 
3.1%

업체명
Text

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-12-13T06:36:15.772410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length8
Mean length5.65625
Min length3

Characters and Unicode

Total characters181
Distinct characters113
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)100.0%

Sample

1st row은성목욕탕
2nd row하남민속대중탕
3rd row명성세탁소
4th row머리하는날
5th row중앙미용실
ValueCountFrequency (%)
은성목욕탕 1
 
2.9%
화천추어탕 1
 
2.9%
어머니가마솥추어탕 1
 
2.9%
시골추어탕 1
 
2.9%
옛날짜장 1
 
2.9%
케익하우스 1
 
2.9%
미엘 1
 
2.9%
소망분식 1
 
2.9%
악떡분식 1
 
2.9%
떡갈비 1
 
2.9%
Other values (25) 25
71.4%
2023-12-13T06:36:16.160429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 8
 
4.4%
탕 5
 
2.8%
어 5
 
2.8%
당 4
 
2.2%
리 3
 
1.7%
추 3
 
1.7%
성 3
 
1.7%
고 3
 
1.7%
스 3
 
1.7%
실 3
 
1.7%
Other values (103) 141
77.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 175
96.7%
Space Separator 3
 
1.7%
Decimal Number 1
 
0.6%
Close Punctuation 1
 
0.6%
Open Punctuation 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 8
 
4.6%
탕 5
 
2.9%
어 5
 
2.9%
당 4
 
2.3%
리 3
 
1.7%
추 3
 
1.7%
성 3
 
1.7%
고 3
 
1.7%
스 3
 
1.7%
실 3
 
1.7%
Other values (99) 135
77.1%
Space Separator
ValueCountFrequency (%)
3
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 175
96.7%
Common 6
 
3.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 8
 
4.6%
탕 5
 
2.9%
어 5
 
2.9%
당 4
 
2.3%
리 3
 
1.7%
추 3
 
1.7%
성 3
 
1.7%
고 3
 
1.7%
스 3
 
1.7%
실 3
 
1.7%
Other values (99) 135
77.1%
Common
ValueCountFrequency (%)
3
50.0%
1 1
 
16.7%
) 1
 
16.7%
( 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 175
96.7%
ASCII 6
 
3.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 8
 
4.6%
탕 5
 
2.9%
어 5
 
2.9%
당 4
 
2.3%
리 3
 
1.7%
추 3
 
1.7%
성 3
 
1.7%
고 3
 
1.7%
스 3
 
1.7%
실 3
 
1.7%
Other values (99) 135
77.1%
ASCII
ValueCountFrequency (%)
3
50.0%
1 1
 
16.7%
) 1
 
16.7%
( 1
 
16.7%

도로명주소
Text

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-12-13T06:36:16.425382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length28.5
Mean length24.625
Min length16

Characters and Unicode

Total characters788
Distinct characters61
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)100.0%

Sample

1st row광주광역시 광산구 월곡로 39
2nd row광주광역시 광산구 월곡산정로 96-21
3rd row광주광역시 광산구 목련로153번길 56
4th row광주광역시 광산구 송도로 322
5th row광주광역시 광산구 광산로30번길 5-1
ValueCountFrequency (%)
광주광역시 32
20.8%
광산구 32
20.8%
송정동 6
 
3.9%
수완동 5
 
3.2%
광산로30번길 4
 
2.6%
월곡동 3
 
1.9%
14 2
 
1.3%
도산동 2
 
1.3%
13 2
 
1.3%
수완로 2
 
1.3%
Other values (64) 64
41.6%
2023-12-13T06:36:17.112298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
122
15.5%
광 102
 
12.9%
산 45
 
5.7%
1 37
 
4.7%
역 32
 
4.1%
시 32
 
4.1%
구 32
 
4.1%
주 32
 
4.1%
로 30
 
3.8%
동 27
 
3.4%
Other values (51) 297
37.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 479
60.8%
Decimal Number 125
 
15.9%
Space Separator 122
 
15.5%
Close Punctuation 23
 
2.9%
Open Punctuation 23
 
2.9%
Dash Punctuation 11
 
1.4%
Other Punctuation 5
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 102
21.3%
산 45
9.4%
역 32
 
6.7%
시 32
 
6.7%
구 32
 
6.7%
주 32
 
6.7%
로 30
 
6.3%
동 27
 
5.6%
길 20
 
4.2%
번 18
 
3.8%
Other values (36) 109
22.8%
Decimal Number
ValueCountFrequency (%)
1 37
29.6%
3 18
14.4%
2 14
 
11.2%
5 12
 
9.6%
4 9
 
7.2%
0 9
 
7.2%
7 8
 
6.4%
8 7
 
5.6%
6 6
 
4.8%
9 5
 
4.0%
Space Separator
ValueCountFrequency (%)
122
100.0%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 479
60.8%
Common 309
39.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 102
21.3%
산 45
9.4%
역 32
 
6.7%
시 32
 
6.7%
구 32
 
6.7%
주 32
 
6.7%
로 30
 
6.3%
동 27
 
5.6%
길 20
 
4.2%
번 18
 
3.8%
Other values (36) 109
22.8%
Common
ValueCountFrequency (%)
122
39.5%
1 37
 
12.0%
) 23
 
7.4%
( 23
 
7.4%
3 18
 
5.8%
2 14
 
4.5%
5 12
 
3.9%
- 11
 
3.6%
4 9
 
2.9%
0 9
 
2.9%
Other values (5) 31
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 479
60.8%
ASCII 309
39.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
122
39.5%
1 37
 
12.0%
) 23
 
7.4%
( 23
 
7.4%
3 18
 
5.8%
2 14
 
4.5%
5 12
 
3.9%
- 11
 
3.6%
4 9
 
2.9%
0 9
 
2.9%
Other values (5) 31
 
10.0%
Hangul
ValueCountFrequency (%)
광 102
21.3%
산 45
9.4%
역 32
 
6.7%
시 32
 
6.7%
구 32
 
6.7%
주 32
 
6.7%
로 30
 
6.3%
동 27
 
5.6%
길 20
 
4.2%
번 18
 
3.8%
Other values (36) 109
22.8%

전화번호
Text

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-12-13T06:36:17.338948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters384
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

Unique32 ?
Unique (%)100.0%

Sample

1st row062-951-5884
2nd row062-951-5662
3rd row062-961-1591
4th row062-944-3695
5th row062-944-1190
ValueCountFrequency (%)
062-951-5884 1
 
3.1%
062-951-5662 1
 
3.1%
062-955-9560 1
 
3.1%
062-959-0192 1
 
3.1%
062-952-5582 1
 
3.1%
062-716-7771 1
 
3.1%
062-953-5252 1
 
3.1%
062-942-8991 1
 
3.1%
062-944-1198 1
 
3.1%
062-943-5486 1
 
3.1%
Other values (22) 22
68.8%
2023-12-13T06:36:17.658932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 64
16.7%
2 49
12.8%
9 47
12.2%
6 46
12.0%
0 40
10.4%
5 36
9.4%
4 30
7.8%
1 23
 
6.0%
3 19
 
4.9%
8 18
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 320
83.3%
Dash Punctuation 64
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 49
15.3%
9 47
14.7%
6 46
14.4%
0 40
12.5%
5 36
11.2%
4 30
9.4%
1 23
7.2%
3 19
 
5.9%
8 18
 
5.6%
7 12
 
3.8%
Dash Punctuation
ValueCountFrequency (%)
- 64
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 384
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 64
16.7%
2 49
12.8%
9 47
12.2%
6 46
12.0%
0 40
10.4%
5 36
9.4%
4 30
7.8%
1 23
 
6.0%
3 19
 
4.9%
8 18
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 384
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 64
16.7%
2 49
12.8%
9 47
12.2%
6 46
12.0%
0 40
10.4%
5 36
9.4%
4 30
7.8%
1 23
 
6.0%
3 19
 
4.9%
8 18
 
4.7%

위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.163075
Minimum35.125744
Maximum35.213072
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-13T06:36:17.808068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.125744
5-th percentile35.129305
Q135.138504
median35.168036
Q335.18666
95-th percentile35.196533
Maximum35.213072
Range0.087327995
Interquartile range (IQR)0.04815615

Descriptive statistics

Standard deviation0.025708608
Coefficient of variation (CV)0.00073112515
Kurtosis-1.3647383
Mean35.163075
Median Absolute Deviation (MAD)0.025429686
Skewness0.04744391
Sum1125.2184
Variance0.00066093254
MonotonicityNot monotonic
2023-12-13T06:36:17.950258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
35.1688917594183 1
 
3.1%
35.1399081897768 1
 
3.1%
35.1922623055682 1
 
3.1%
35.190447851531 1
 
3.1%
35.1916287901724 1
 
3.1%
35.1902130028356 1
 
3.1%
35.1863500645558 1
 
3.1%
35.1747278954448 1
 
3.1%
35.125743819225 1
 
3.1%
35.1385387068919 1
 
3.1%
Other values (22) 22
68.8%
ValueCountFrequency (%)
35.125743819225 1
3.1%
35.1289248814847 1
3.1%
35.1296158593232 1
3.1%
35.1302353544128 1
3.1%
35.130476555594 1
3.1%
35.1380570413211 1
3.1%
35.138331092448 1
3.1%
35.1384002972371 1
3.1%
35.1385387068919 1
3.1%
35.1386313874337 1
3.1%
ValueCountFrequency (%)
35.2130718139132 1
3.1%
35.1976289284711 1
3.1%
35.1956370516498 1
3.1%
35.1922623055682 1
3.1%
35.1916287901724 1
3.1%
35.190447851531 1
3.1%
35.1902130028356 1
3.1%
35.1875908241816 1
3.1%
35.1863500645558 1
3.1%
35.1853879465972 1
3.1%

경도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.80965
Minimum126.75706
Maximum126.84046
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-13T06:36:18.100017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.75706
5-th percentile126.78953
Q1126.79532
median126.80869
Q3126.82907
95-th percentile126.83581
Maximum126.84046
Range0.08339689
Interquartile range (IQR)0.033745587

Descriptive statistics

Standard deviation0.018799421
Coefficient of variation (CV)0.00014824914
Kurtosis0.28052048
Mean126.80965
Median Absolute Deviation (MAD)0.014190207
Skewness-0.35691981
Sum4057.9087
Variance0.00035341822
MonotonicityNot monotonic
2023-12-13T06:36:18.287604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
126.813382411143 1
 
3.1%
126.794380563248 1
 
3.1%
126.829483272454 1
 
3.1%
126.829334553884 1
 
3.1%
126.828494532658 1
 
3.1%
126.829301886048 1
 
3.1%
126.829042619585 1
 
3.1%
126.814049582357 1
 
3.1%
126.757060988657 1
 
3.1%
126.795418853922 1
 
3.1%
Other values (22) 22
68.8%
ValueCountFrequency (%)
126.757060988657 1
3.1%
126.78853968988 1
3.1%
126.790347363341 1
3.1%
126.793412592573 1
3.1%
126.793562598451 1
3.1%
126.794380563248 1
3.1%
126.794613343438 1
3.1%
126.795151154805 1
3.1%
126.795377693372 1
3.1%
126.795418853922 1
3.1%
ValueCountFrequency (%)
126.840457878318 1
3.1%
126.8364016252 1
3.1%
126.835320637274 1
3.1%
126.833301570992 1
3.1%
126.829483272454 1
3.1%
126.829334553884 1
3.1%
126.829301886048 1
3.1%
126.829138725944 1
3.1%
126.829042619585 1
3.1%
126.828494532658 1
3.1%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size388.0 B
Minimum2022-12-31 00:00:00
Maximum2022-12-31 00:00:00
2023-12-13T06:36:18.413148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:36:18.530156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T06:36:14.456059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:36:13.951710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:36:14.212777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:36:14.562618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:36:14.034010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:36:14.292211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:36:14.664240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:36:14.131594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:36:14.371666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:36:18.621981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종업체명도로명주소전화번호위도경도
연번1.0000.8371.0001.0001.0000.6030.567
업종0.8371.0001.0001.0001.0000.6320.482
업체명1.0001.0001.0001.0001.0001.0001.000
도로명주소1.0001.0001.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.0001.0001.000
위도0.6030.6321.0001.0001.0001.0000.916
경도0.5670.4821.0001.0001.0000.9161.000
2023-12-13T06:36:18.724941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도업종
연번1.0000.1230.0410.391
위도0.1231.0000.9550.335
경도0.0410.9551.0000.220
업종0.3910.3350.2201.000

Missing values

2023-12-13T06:36:14.807034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:36:14.936570image/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

연번업종업체명도로명주소전화번호위도경도데이터기준일자
01목욕업은성목욕탕광주광역시 광산구 월곡로 39062-951-588435.168892126.8133822022-12-31
12목욕업하남민속대중탕광주광역시 광산구 월곡산정로 96-21062-951-566235.164395126.8131142022-12-31
23세탁업명성세탁소광주광역시 광산구 목련로153번길 56062-961-159135.174448126.8166992022-12-31
34이미용업머리하는날광주광역시 광산구 송도로 322062-944-369535.141403126.8022992022-12-31
45이미용업중앙미용실광주광역시 광산구 광산로30번길 5-1062-944-119035.138631126.7953782022-12-31
56이미용업청실미용실광주광역시 광산구 월곡중앙로1번길 13062-955-437935.166416126.8093452022-12-31
67이미용업초이스헤어샵광주광역시 광산구 월곡반월로 58 (월곡동)062-431-393935.169937126.8130172022-12-31
78중식진고개반점광주광역시 광산구 신창로105번길 34-14062-955-447735.195637126.8364022022-12-31
89한식_분식깨비분식광주광역시 광산구 광산로30번길 11 (송정동)062-942-732435.1384126.7955492022-12-31
910한식_분식유건모밀광주광역시 광산구 광산로 13 (송정동, 1층)062-945-165135.138057126.7934132022-12-31
연번업종업체명도로명주소전화번호위도경도데이터기준일자
2223기타양식케익하우스 미엘광주광역시 광산구 송도로182번길 12 (도산동)062-943-353435.130235126.7946132022-12-31
2324한식_분식소망분식광주광역시 광산구 남동길 30 (도산동)062-943-548635.129616126.788542022-12-31
2425한식_찌개류화천추어탕광주광역시 광산구 광산로30번길 7-1 (송정동)062-944-119835.138539126.7954192022-12-31
2526한식_분식악떡분식광주광역시 광산구 평동로 754, 1층(옥동)062-942-899135.125744126.7570612022-12-31
2627한식_육류운남골 생오리광주광역시 광산구 목련로153번안길 54-6 (운남동)062-953-525235.174728126.814052022-12-31
2728일식스시빈광주광역시 광산구 수완로 14, 2층 (수완동)062-716-777135.18635126.8290432022-12-31
2829한식_육류해남한우집광주광역시 광산구 수완로52번길 1-18 (수완동)062-952-558235.190213126.8293022022-12-31
2930한식_육류광주1번정육식당광주광역시 광산구 수완로73번길 3 (수완동)062-959-019235.191629126.8284952022-12-31
3031일식다담초밥광주광역시 광산구 장신로 176 (수완동)062-955-956035.190448126.8293352022-12-31
3132한식_육류팔팔참숯구이광주광역시 광산구 수완로74번길 11-13 (수완동)062-962-883935.192262126.8294832022-12-31