Overview

Dataset statistics

Number of variables8
Number of observations37
Missing cells3
Missing cells (%)1.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.5 KiB
Average record size in memory68.6 B

Variable types

Categorical3
Text4
Numeric1

Dataset

Description행정안전부 착한가격업소로 지정된 광주광역시 동구 상점에 관한 공공데이터 입니다.(업소명, 주요품목, 가격, 전화번호, 소재지도로명주소 등)
Author광주광역시 동구
URLhttps://www.data.go.kr/data/15079351/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
업종 is highly overall correlated with 기타유의사항High correlation
기타유의사항 is highly overall correlated with 가격 and 1 other fieldsHigh correlation
가격 is highly overall correlated with 기타유의사항High correlation
업종 is highly imbalanced (51.3%)Imbalance
기타유의사항 is highly imbalanced (59.4%)Imbalance
전화번호 has 3 (8.1%) missing valuesMissing
업소명 has unique valuesUnique
소재지도로명주소 has unique valuesUnique

Reproduction

Analysis started2024-03-23 05:49:49.469564
Analysis finished2024-03-23 05:49:50.472453
Duration1 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)10.8%
Missing0
Missing (%)0.0%
Memory size428.0 B
한식
30 
중식
 
3
미용업
 
3
목욕업
 
1

Length

Max length3
Median length2
Mean length2.1081081
Min length2

Unique

Unique1 ?
Unique (%)2.7%

Sample

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

Common Values

ValueCountFrequency (%)
한식 30
81.1%
중식 3
 
8.1%
미용업 3
 
8.1%
목욕업 1
 
2.7%

Length

2024-03-23T14:49:50.560336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T14:49:50.702186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한식 30
81.1%
중식 3
 
8.1%
미용업 3
 
8.1%
목욕업 1
 
2.7%

업소명
Text

UNIQUE 

Distinct37
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size428.0 B
2024-03-23T14:49:51.014596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length4.6486486
Min length2

Characters and Unicode

Total characters172
Distinct characters108
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)100.0%

Sample

1st row서석식당
2nd row산수골
3rd row명지원
4th row반디식당
5th row박순자녹두집
ValueCountFrequency (%)
서석식당 1
 
2.5%
산수골 1
 
2.5%
숯불갈비 1
 
2.5%
짜앤짬탕수육 1
 
2.5%
황후 1
 
2.5%
대왕김밥(대인동 1
 
2.5%
대왕김밥(학동 1
 
2.5%
학동김밥 1
 
2.5%
칠미 1
 
2.5%
마쏘라까망베르 1
 
2.5%
Other values (30) 30
75.0%
2024-03-23T14:49:51.589490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 6
 
3.5%
당 5
 
2.9%
미 5
 
2.9%
밥 5
 
2.9%
대 5
 
2.9%
동 4
 
2.3%
수 4
 
2.3%
김 4
 
2.3%
명 3
 
1.7%
지 3
 
1.7%
Other values (98) 128
74.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 161
93.6%
Space Separator 3
 
1.7%
Close Punctuation 2
 
1.2%
Open Punctuation 2
 
1.2%
Decimal Number 2
 
1.2%
Lowercase Letter 1
 
0.6%
Other Punctuation 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 6
 
3.7%
당 5
 
3.1%
미 5
 
3.1%
밥 5
 
3.1%
대 5
 
3.1%
동 4
 
2.5%
수 4
 
2.5%
김 4
 
2.5%
명 3
 
1.9%
지 3
 
1.9%
Other values (91) 117
72.7%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
4 1
50.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
s 1
100.0%
Other Punctuation
ValueCountFrequency (%)
' 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 161
93.6%
Common 10
 
5.8%
Latin 1
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 6
 
3.7%
당 5
 
3.1%
미 5
 
3.1%
밥 5
 
3.1%
대 5
 
3.1%
동 4
 
2.5%
수 4
 
2.5%
김 4
 
2.5%
명 3
 
1.9%
지 3
 
1.9%
Other values (91) 117
72.7%
Common
ValueCountFrequency (%)
3
30.0%
) 2
20.0%
( 2
20.0%
2 1
 
10.0%
4 1
 
10.0%
' 1
 
10.0%
Latin
ValueCountFrequency (%)
s 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 161
93.6%
ASCII 11
 
6.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 6
 
3.7%
당 5
 
3.1%
미 5
 
3.1%
밥 5
 
3.1%
대 5
 
3.1%
동 4
 
2.5%
수 4
 
2.5%
김 4
 
2.5%
명 3
 
1.9%
지 3
 
1.9%
Other values (91) 117
72.7%
ASCII
ValueCountFrequency (%)
3
27.3%
) 2
18.2%
( 2
18.2%
2 1
 
9.1%
4 1
 
9.1%
s 1
 
9.1%
' 1
 
9.1%

주요품목
Text

Distinct25
Distinct (%)67.6%
Missing0
Missing (%)0.0%
Memory size428.0 B
2024-03-23T14:49:51.860988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length11
Mean length6
Min length2

Characters and Unicode

Total characters222
Distinct characters76
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)51.4%

Sample

1st row낚지비빔밥
2nd row병어조림(2인)
3rd row생삼겹(200g)
4th row백반
5th row수제비
ValueCountFrequency (%)
김밥 6
 
15.8%
백반 3
 
7.9%
짜장면 3
 
7.9%
성인남녀컷트 2
 
5.3%
돼지갈비(250g 2
 
5.3%
삼겹살(200g 2
 
5.3%
생선구이(모듬 1
 
2.6%
낚지비빔밥 1
 
2.6%
수제돈가스 1
 
2.6%
찌개(김치,참치,순두부,부대 1
 
2.6%
Other values (16) 16
42.1%
2024-03-23T14:49:52.354520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 14
 
6.3%
( 14
 
6.3%
0 11
 
5.0%
김 9
 
4.1%
밥 8
 
3.6%
g 8
 
3.6%
, 7
 
3.2%
2 7
 
3.2%
장 6
 
2.7%
비 5
 
2.3%
Other values (66) 133
59.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 150
67.6%
Decimal Number 26
 
11.7%
Close Punctuation 14
 
6.3%
Open Punctuation 14
 
6.3%
Lowercase Letter 8
 
3.6%
Other Punctuation 7
 
3.2%
Space Separator 1
 
0.5%
Dash Punctuation 1
 
0.5%
Uppercase Letter 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 9
 
6.0%
밥 8
 
5.3%
장 6
 
4.0%
비 5
 
3.3%
겹 5
 
3.3%
삼 5
 
3.3%
인 5
 
3.3%
스 4
 
2.7%
지 4
 
2.7%
짜 4
 
2.7%
Other values (53) 95
63.3%
Decimal Number
ValueCountFrequency (%)
0 11
42.3%
2 7
26.9%
5 3
 
11.5%
8 2
 
7.7%
1 2
 
7.7%
3 1
 
3.8%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Lowercase Letter
ValueCountFrequency (%)
g 8
100.0%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
L 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 150
67.6%
Common 63
28.4%
Latin 9
 
4.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 9
 
6.0%
밥 8
 
5.3%
장 6
 
4.0%
비 5
 
3.3%
겹 5
 
3.3%
삼 5
 
3.3%
인 5
 
3.3%
스 4
 
2.7%
지 4
 
2.7%
짜 4
 
2.7%
Other values (53) 95
63.3%
Common
ValueCountFrequency (%)
) 14
22.2%
( 14
22.2%
0 11
17.5%
, 7
11.1%
2 7
11.1%
5 3
 
4.8%
8 2
 
3.2%
1 2
 
3.2%
1
 
1.6%
- 1
 
1.6%
Latin
ValueCountFrequency (%)
g 8
88.9%
L 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 150
67.6%
ASCII 72
32.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 14
19.4%
( 14
19.4%
0 11
15.3%
g 8
11.1%
, 7
9.7%
2 7
9.7%
5 3
 
4.2%
8 2
 
2.8%
1 2
 
2.8%
1
 
1.4%
Other values (3) 3
 
4.2%
Hangul
ValueCountFrequency (%)
김 9
 
6.0%
밥 8
 
5.3%
장 6
 
4.0%
비 5
 
3.3%
겹 5
 
3.3%
삼 5
 
3.3%
인 5
 
3.3%
스 4
 
2.7%
지 4
 
2.7%
짜 4
 
2.7%
Other values (53) 95
63.3%

가격
Real number (ℝ)

HIGH CORRELATION 

Distinct19
Distinct (%)51.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8472.973
Minimum1000
Maximum30000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2024-03-23T14:49:52.513966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1000
5-th percentile2900
Q15000
median7000
Q312000
95-th percentile15200
Maximum30000
Range29000
Interquartile range (IQR)7000

Descriptive statistics

Standard deviation5460.6496
Coefficient of variation (CV)0.64447858
Kurtosis5.3556314
Mean8472.973
Median Absolute Deviation (MAD)4000
Skewness1.751945
Sum313500
Variance29818694
MonotonicityNot monotonic
2024-03-23T14:49:52.674668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
6000 7
18.9%
3000 5
13.5%
12000 4
10.8%
14000 3
 
8.1%
7000 3
 
8.1%
9000 2
 
5.4%
13000 1
 
2.7%
10000 1
 
2.7%
2500 1
 
2.7%
8000 1
 
2.7%
Other values (9) 9
24.3%
ValueCountFrequency (%)
1000 1
 
2.7%
2500 1
 
2.7%
3000 5
13.5%
4000 1
 
2.7%
4500 1
 
2.7%
5000 1
 
2.7%
6000 7
18.9%
7000 3
8.1%
7500 1
 
2.7%
8000 1
 
2.7%
ValueCountFrequency (%)
30000 1
 
2.7%
16000 1
 
2.7%
15000 1
 
2.7%
14000 3
8.1%
13000 1
 
2.7%
12000 4
10.8%
11000 1
 
2.7%
10000 1
 
2.7%
9000 2
5.4%
8000 1
 
2.7%

전화번호
Text

MISSING 

Distinct34
Distinct (%)100.0%
Missing3
Missing (%)8.1%
Memory size428.0 B
2024-03-23T14:49:53.027570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters408
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

Unique34 ?
Unique (%)100.0%

Sample

1st row062-223-9009
2nd row062-233-3318
3rd row062-227-3565
4th row062-222-0809
5th row062-223-8694
ValueCountFrequency (%)
062-236-2879 1
 
2.9%
062-224-5004 1
 
2.9%
062-236-2465 1
 
2.9%
062-234-0052 1
 
2.9%
062-234-0097 1
 
2.9%
062-529-3363 1
 
2.9%
062-223-0868 1
 
2.9%
062-225-3248 1
 
2.9%
062-523-1269 1
 
2.9%
062-675-9944 1
 
2.9%
Other values (24) 24
70.6%
2024-03-23T14:49:53.570647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 105
25.7%
- 68
16.7%
0 55
13.5%
6 54
13.2%
3 32
 
7.8%
8 22
 
5.4%
4 21
 
5.1%
9 17
 
4.2%
7 14
 
3.4%
5 13
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 340
83.3%
Dash Punctuation 68
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 105
30.9%
0 55
16.2%
6 54
15.9%
3 32
 
9.4%
8 22
 
6.5%
4 21
 
6.2%
9 17
 
5.0%
7 14
 
4.1%
5 13
 
3.8%
1 7
 
2.1%
Dash Punctuation
ValueCountFrequency (%)
- 68
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 408
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 105
25.7%
- 68
16.7%
0 55
13.5%
6 54
13.2%
3 32
 
7.8%
8 22
 
5.4%
4 21
 
5.1%
9 17
 
4.2%
7 14
 
3.4%
5 13
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 408
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 105
25.7%
- 68
16.7%
0 55
13.5%
6 54
13.2%
3 32
 
7.8%
8 22
 
5.4%
4 21
 
5.1%
9 17
 
4.2%
7 14
 
3.4%
5 13
 
3.2%

소재지도로명주소
Text

UNIQUE 

Distinct37
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size428.0 B
2024-03-23T14:49:53.931114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length29
Mean length25.108108
Min length19

Characters and Unicode

Total characters929
Distinct characters63
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

Unique37 ?
Unique (%)100.0%

Sample

1st row광주광역시 동구 백서로 171-3, 1층(서석동)
2nd row광주광역시 동구 경양로 340(산수동)
3rd row광주광역시 동구 구성로 252(계림동)
4th row광주광역시 동구 구성로 258(계림동)
5th row광주광역시 동구 구성로204번길 26(대인동)
ValueCountFrequency (%)
광주광역시 37
22.0%
동구 37
22.0%
백서로 4
 
2.4%
1층 3
 
1.8%
지산로 3
 
1.8%
남문로 3
 
1.8%
1층(대인동 3
 
1.8%
학소로 3
 
1.8%
필문대로287번길 2
 
1.2%
천변좌로 2
 
1.2%
Other values (65) 71
42.3%
2024-03-23T14:49:54.542884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
131
 
14.1%
동 76
 
8.2%
광 75
 
8.1%
1 44
 
4.7%
구 41
 
4.4%
로 38
 
4.1%
시 37
 
4.0%
주 37
 
4.0%
) 37
 
4.0%
역 37
 
4.0%
Other values (53) 376
40.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 530
57.1%
Decimal Number 161
 
17.3%
Space Separator 131
 
14.1%
Close Punctuation 37
 
4.0%
Open Punctuation 37
 
4.0%
Other Punctuation 19
 
2.0%
Dash Punctuation 14
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 76
14.3%
광 75
14.2%
구 41
 
7.7%
로 38
 
7.2%
시 37
 
7.0%
주 37
 
7.0%
역 37
 
7.0%
층 18
 
3.4%
길 13
 
2.5%
산 13
 
2.5%
Other values (38) 145
27.4%
Decimal Number
ValueCountFrequency (%)
1 44
27.3%
2 31
19.3%
3 14
 
8.7%
7 12
 
7.5%
5 11
 
6.8%
8 11
 
6.8%
6 11
 
6.8%
9 10
 
6.2%
4 9
 
5.6%
0 8
 
5.0%
Space Separator
ValueCountFrequency (%)
131
100.0%
Close Punctuation
ValueCountFrequency (%)
) 37
100.0%
Open Punctuation
ValueCountFrequency (%)
( 37
100.0%
Other Punctuation
ValueCountFrequency (%)
, 19
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 530
57.1%
Common 399
42.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 76
14.3%
광 75
14.2%
구 41
 
7.7%
로 38
 
7.2%
시 37
 
7.0%
주 37
 
7.0%
역 37
 
7.0%
층 18
 
3.4%
길 13
 
2.5%
산 13
 
2.5%
Other values (38) 145
27.4%
Common
ValueCountFrequency (%)
131
32.8%
1 44
 
11.0%
) 37
 
9.3%
( 37
 
9.3%
2 31
 
7.8%
, 19
 
4.8%
- 14
 
3.5%
3 14
 
3.5%
7 12
 
3.0%
5 11
 
2.8%
Other values (5) 49
 
12.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 530
57.1%
ASCII 399
42.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
131
32.8%
1 44
 
11.0%
) 37
 
9.3%
( 37
 
9.3%
2 31
 
7.8%
, 19
 
4.8%
- 14
 
3.5%
3 14
 
3.5%
7 12
 
3.0%
5 11
 
2.8%
Other values (5) 49
 
12.3%
Hangul
ValueCountFrequency (%)
동 76
14.3%
광 75
14.2%
구 41
 
7.7%
로 38
 
7.2%
시 37
 
7.0%
주 37
 
7.0%
역 37
 
7.0%
층 18
 
3.4%
길 13
 
2.5%
산 13
 
2.5%
Other values (38) 145
27.4%

기타유의사항
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size428.0 B
<NA>
34 
개인정보로 인해 전화번호 미등록
 
3

Length

Max length17
Median length4
Mean length5.0540541
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 34
91.9%
개인정보로 인해 전화번호 미등록 3
 
8.1%

Length

2024-03-23T14:49:54.786916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T14:49:54.959622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 34
73.9%
개인정보로 3
 
6.5%
인해 3
 
6.5%
전화번호 3
 
6.5%
미등록 3
 
6.5%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size428.0 B
2024-03-06
37 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-03-06
2nd row2024-03-06
3rd row2024-03-06
4th row2024-03-06
5th row2024-03-06

Common Values

ValueCountFrequency (%)
2024-03-06 37
100.0%

Length

2024-03-23T14:49:55.135602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T14:49:55.278100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-03-06 37
100.0%

Interactions

2024-03-23T14:49:49.988093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T14:49:55.408635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종업소명주요품목가격전화번호소재지도로명주소
업종1.0001.0001.0000.4511.0001.000
업소명1.0001.0001.0001.0001.0001.000
주요품목1.0001.0001.0000.9621.0001.000
가격0.4511.0000.9621.0001.0001.000
전화번호1.0001.0001.0001.0001.0001.000
소재지도로명주소1.0001.0001.0001.0001.0001.000
2024-03-23T14:49:55.948181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종기타유의사항
업종1.0001.000
기타유의사항1.0001.000
2024-03-23T14:49:56.091336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
가격업종기타유의사항
가격1.0000.3131.000
업종0.3131.0001.000
기타유의사항1.0001.0001.000

Missing values

2024-03-23T14:49:50.183180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T14:49:50.396346image/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

업종업소명주요품목가격전화번호소재지도로명주소기타유의사항데이터기준일자
0한식서석식당낚지비빔밥9000062-223-9009광주광역시 동구 백서로 171-3, 1층(서석동)<NA>2024-03-06
1한식산수골병어조림(2인)30000062-233-3318광주광역시 동구 경양로 340(산수동)<NA>2024-03-06
2한식명지원생삼겹(200g)14000062-227-3565광주광역시 동구 구성로 252(계림동)<NA>2024-03-06
3한식반디식당백반6000062-222-0809광주광역시 동구 구성로 258(계림동)<NA>2024-03-06
4한식박순자녹두집수제비6000062-223-8694광주광역시 동구 구성로204번길 26(대인동)<NA>2024-03-06
5한식우리뷔페백반6000062-364-3816광주광역시 동구 금남로 181, 1층 102호(금남로5가)<NA>2024-03-06
6한식제주덕구 동명점김치찌개7000062-226-1020광주광역시 동구 동명로 4, 1층(장동)<NA>2024-03-06
7한식장독대주물럭쌈밥(2인이상)12000062-223-5630광주광역시 동구 문화전당로 43, 3층(광산동)<NA>2024-03-06
8한식화롯불돼지갈비(250g)16000062-224-6119광주광역시 동구 백서로 168(서석동)<NA>2024-03-06
9한식미미상회생삼겹(180g)11000062-236-2879광주광역시 동구 백서로 182, 1층(서석동)<NA>2024-03-06
업종업소명주요품목가격전화번호소재지도로명주소기타유의사항데이터기준일자
27한식마쏘라까망베르돈가스(L)8000062-224-5004광주광역시 동구 필문대로205번길 19(지산동)<NA>2024-03-06
28한식죽사랑김밥사랑김밥3000062-227-0988광주광역시 동구 필문대로287번길 23-17(지산동)<NA>2024-03-06
29미용업헤어디자이너 수빈성인여자컷트12000062-463-6402광주광역시 동구 의재로26번길 4-2, 1층(학동)<NA>2024-03-06
30한식장터삼겹살(180g)12000062-228-0252광주광역시 동구 백서로 180(서석동)<NA>2024-03-06
31한식삼미식당간짜장7000062-227-0391광주광역시 동구 백서로189번길 14-32(서석동)<NA>2024-03-06
32한식참스민김밥2500062-232-3883광주광역시 동구 남문로 752-3(학동, 1층)<NA>2024-03-06
33한식종합분식찌개(김치,참치,순두부,부대)7000062-225-4928광주광역시 동구 장동로 23-3(장동)<NA>2024-03-06
34미용업교대헤어매직성인남녀컷트12000062-523-1269광주광역시 동구 무등로375번길 24, 1층(계림동)<NA>2024-03-06
35미용업주영미용실성인남녀컷트10000<NA>광주광역시 동구 무등로375번길 27-1, 1층(계림동)개인정보로 인해 전화번호 미등록2024-03-06
36목욕업명문목욕탕목욕6000062-227-2459광주광역시 동구 지원로 5(소태동)<NA>2024-03-06