Overview

Dataset statistics

Number of variables8
Number of observations110
Missing cells115
Missing cells (%)13.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.0 KiB
Average record size in memory65.2 B

Variable types

Unsupported1
Text6
Categorical1

Dataset

Description전라남도 남도음식명가 지정업소 현황(업체명, 소재지, 연락처, 주메뉴)
Author전라남도
URLhttps://www.data.go.kr/data/15050624/fileData.do

Alerts

Unnamed: 7 has constant value ""Constant
Unnamed: 7 has 109 (99.1%) missing valuesMissing
Unnamed: 0 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 10:31:48.110916
Analysis finished2023-12-12 10:31:49.163283
Duration1.05 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Unnamed: 0
Unsupported

REJECTED  UNSUPPORTED 

Missing1
Missing (%)0.9%
Memory size1012.0 B

Unnamed: 1
Text

Distinct107
Distinct (%)98.2%
Missing1
Missing (%)0.9%
Memory size1012.0 B
2023-12-12T19:31:49.360198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length5.0183486
Min length2

Characters and Unicode

Total characters547
Distinct characters189
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique105 ?
Unique (%)96.3%

Sample

1st row업체명
2nd row옥 정
3rd row영란횟집
4th row인동주마을
5th row대양
ValueCountFrequency (%)
정 3
 
2.2%
독천식당 2
 
1.5%
관 2
 
1.5%
일 2
 
1.5%
달맞이흑두부 2
 
1.5%
안성식당 1
 
0.7%
이조숯불갈비 1
 
0.7%
탐마루장흥한우 1
 
0.7%
진 1
 
0.7%
금강산횟집 1
 
0.7%
Other values (118) 118
88.1%
2023-12-12T19:31:49.784787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 21
 
3.8%
20
 
3.7%
관 17
 
3.1%
당 17
 
3.1%
한 17
 
3.1%
정 14
 
2.6%
가 10
 
1.8%
원 10
 
1.8%
회 9
 
1.6%
우 9
 
1.6%
Other values (179) 403
73.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 514
94.0%
Space Separator 20
 
3.7%
Control 7
 
1.3%
Decimal Number 4
 
0.7%
Close Punctuation 1
 
0.2%
Open Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 21
 
4.1%
관 17
 
3.3%
당 17
 
3.3%
한 17
 
3.3%
정 14
 
2.7%
가 10
 
1.9%
원 10
 
1.9%
회 9
 
1.8%
우 9
 
1.8%
집 9
 
1.8%
Other values (171) 381
74.1%
Decimal Number
ValueCountFrequency (%)
1 1
25.0%
2 1
25.0%
6 1
25.0%
0 1
25.0%
Space Separator
ValueCountFrequency (%)
20
100.0%
Control
ValueCountFrequency (%)
7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 512
93.6%
Common 33
 
6.0%
Han 2
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 21
 
4.1%
관 17
 
3.3%
당 17
 
3.3%
한 17
 
3.3%
정 14
 
2.7%
가 10
 
2.0%
원 10
 
2.0%
회 9
 
1.8%
우 9
 
1.8%
집 9
 
1.8%
Other values (169) 379
74.0%
Common
ValueCountFrequency (%)
20
60.6%
7
 
21.2%
1 1
 
3.0%
) 1
 
3.0%
2 1
 
3.0%
( 1
 
3.0%
6 1
 
3.0%
0 1
 
3.0%
Han
ValueCountFrequency (%)
愛 1
50.0%
家 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 512
93.6%
ASCII 33
 
6.0%
CJK 2
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 21
 
4.1%
관 17
 
3.3%
당 17
 
3.3%
한 17
 
3.3%
정 14
 
2.7%
가 10
 
2.0%
원 10
 
2.0%
회 9
 
1.8%
우 9
 
1.8%
집 9
 
1.8%
Other values (169) 379
74.0%
ASCII
ValueCountFrequency (%)
20
60.6%
7
 
21.2%
1 1
 
3.0%
) 1
 
3.0%
2 1
 
3.0%
( 1
 
3.0%
6 1
 
3.0%
0 1
 
3.0%
CJK
ValueCountFrequency (%)
愛 1
50.0%
家 1
50.0%

Unnamed: 2
Categorical

Distinct24
Distinct (%)21.8%
Missing0
Missing (%)0.0%
Memory size1012.0 B
목포시
10 
순천시
8 
광양시
 
7
담양군
 
7
해남군
 
7
Other values (19)
71 

Length

Max length4
Median length3
Mean length3
Min length2

Unique

Unique2 ?
Unique (%)1.8%

Sample

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

Common Values

ValueCountFrequency (%)
목포시 10
 
9.1%
순천시 8
 
7.3%
광양시 7
 
6.4%
담양군 7
 
6.4%
해남군 7
 
6.4%
화순군 6
 
5.5%
여수시 6
 
5.5%
나주시 6
 
5.5%
영광군 5
 
4.5%
완도군 5
 
4.5%
Other values (14) 43
39.1%

Length

2023-12-12T19:31:49.944001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
목포시 10
 
9.1%
순천시 8
 
7.3%
광양시 7
 
6.4%
담양군 7
 
6.4%
해남군 7
 
6.4%
화순군 6
 
5.5%
여수시 6
 
5.5%
나주시 6
 
5.5%
영광군 5
 
4.5%
완도군 5
 
4.5%
Other values (14) 43
39.1%

남도음식명가 지정 업소 명단(108개소)
Text

Distinct109
Distinct (%)100.0%
Missing1
Missing (%)0.9%
Memory size1012.0 B
2023-12-12T19:31:50.297605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length21
Mean length16.394495
Min length3

Characters and Unicode

Total characters1787
Distinct characters154
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique109 ?
Unique (%)100.0%

Sample

1st row소재지
2nd row목포시 미항로 8(상동)
3rd row목포시 번화로 47(중앙동 1가)
4th row목포시 복산길 12번길 5(옥암동)
5th row목포시 해안로 173번길 45(중앙동)
ValueCountFrequency (%)
목포시 10
 
2.4%
순천시 8
 
1.9%
해남군 7
 
1.7%
담양군 7
 
1.7%
광양시 7
 
1.7%
여수시 6
 
1.5%
나주시 6
 
1.5%
화순군 6
 
1.5%
중앙로 6
 
1.5%
완도군 5
 
1.2%
Other values (267) 345
83.5%
2023-12-12T19:31:50.824188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
307
 
17.2%
1 85
 
4.8%
군 73
 
4.1%
로 66
 
3.7%
길 58
 
3.2%
2 49
 
2.7%
3 44
 
2.5%
읍 42
 
2.4%
시 41
 
2.3%
동 39
 
2.2%
Other values (144) 983
55.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1041
58.3%
Decimal Number 340
 
19.0%
Space Separator 307
 
17.2%
Dash Punctuation 34
 
1.9%
Open Punctuation 32
 
1.8%
Close Punctuation 32
 
1.8%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
군 73
 
7.0%
로 66
 
6.3%
길 58
 
5.6%
읍 42
 
4.0%
시 41
 
3.9%
동 39
 
3.7%
면 38
 
3.7%
성 25
 
2.4%
광 24
 
2.3%
양 22
 
2.1%
Other values (129) 613
58.9%
Decimal Number
ValueCountFrequency (%)
1 85
25.0%
2 49
14.4%
3 44
12.9%
4 31
 
9.1%
5 28
 
8.2%
9 23
 
6.8%
8 23
 
6.8%
0 21
 
6.2%
6 18
 
5.3%
7 18
 
5.3%
Space Separator
ValueCountFrequency (%)
307
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 34
100.0%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%
Other Punctuation
ValueCountFrequency (%)
․ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1041
58.3%
Common 746
41.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
군 73
 
7.0%
로 66
 
6.3%
길 58
 
5.6%
읍 42
 
4.0%
시 41
 
3.9%
동 39
 
3.7%
면 38
 
3.7%
성 25
 
2.4%
광 24
 
2.3%
양 22
 
2.1%
Other values (129) 613
58.9%
Common
ValueCountFrequency (%)
307
41.2%
1 85
 
11.4%
2 49
 
6.6%
3 44
 
5.9%
- 34
 
4.6%
( 32
 
4.3%
) 32
 
4.3%
4 31
 
4.2%
5 28
 
3.8%
9 23
 
3.1%
Other values (5) 81
 
10.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1041
58.3%
ASCII 745
41.7%
Punctuation 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
307
41.2%
1 85
 
11.4%
2 49
 
6.6%
3 44
 
5.9%
- 34
 
4.6%
( 32
 
4.3%
) 32
 
4.3%
4 31
 
4.2%
5 28
 
3.8%
9 23
 
3.1%
Other values (4) 80
 
10.7%
Hangul
ValueCountFrequency (%)
군 73
 
7.0%
로 66
 
6.3%
길 58
 
5.6%
읍 42
 
4.0%
시 41
 
3.9%
동 39
 
3.7%
면 38
 
3.7%
성 25
 
2.4%
광 24
 
2.3%
양 22
 
2.1%
Other values (129) 613
58.9%
Punctuation
ValueCountFrequency (%)
․ 1
100.0%

Unnamed: 4
Text

Distinct108
Distinct (%)99.1%
Missing1
Missing (%)0.9%
Memory size1012.0 B
2023-12-12T19:31:51.185282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length3.0366972
Min length2

Characters and Unicode

Total characters331
Distinct characters102
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique107 ?
Unique (%)98.2%

Sample

1st row대표자
2nd row이경하
3rd row조형숙
4th row우정단
5th row강옥희
ValueCountFrequency (%)
박수영 2
 
1.8%
조경순 1
 
0.9%
천현석 1
 
0.9%
김진규 1
 
0.9%
김애순 1
 
0.9%
이병규 1
 
0.9%
한성엽 1
 
0.9%
오현화 1
 
0.9%
정명승 1
 
0.9%
송영진 1
 
0.9%
Other values (99) 99
90.0%
2023-12-12T19:31:51.640194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 26
 
7.9%
이 19
 
5.7%
정 16
 
4.8%
박 10
 
3.0%
영 10
 
3.0%
순 10
 
3.0%
숙 10
 
3.0%
주 9
 
2.7%
희 8
 
2.4%
은 7
 
2.1%
Other values (92) 206
62.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 329
99.4%
Space Separator 2
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 26
 
7.9%
이 19
 
5.8%
정 16
 
4.9%
박 10
 
3.0%
영 10
 
3.0%
순 10
 
3.0%
숙 10
 
3.0%
주 9
 
2.7%
희 8
 
2.4%
은 7
 
2.1%
Other values (91) 204
62.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 329
99.4%
Common 2
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 26
 
7.9%
이 19
 
5.8%
정 16
 
4.9%
박 10
 
3.0%
영 10
 
3.0%
순 10
 
3.0%
숙 10
 
3.0%
주 9
 
2.7%
희 8
 
2.4%
은 7
 
2.1%
Other values (91) 204
62.0%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 329
99.4%
ASCII 2
 
0.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 26
 
7.9%
이 19
 
5.8%
정 16
 
4.9%
박 10
 
3.0%
영 10
 
3.0%
순 10
 
3.0%
숙 10
 
3.0%
주 9
 
2.7%
희 8
 
2.4%
은 7
 
2.1%
Other values (91) 204
62.0%
ASCII
ValueCountFrequency (%)
2
100.0%

Unnamed: 5
Text

Distinct109
Distinct (%)100.0%
Missing1
Missing (%)0.9%
Memory size1012.0 B
2023-12-12T19:31:52.035964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.9541284
Min length3

Characters and Unicode

Total characters867
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique109 ?
Unique (%)100.0%

Sample

1st row연락처
2nd row243-0012
3rd row243-7311
4th row284-4068
5th row244-8308
ValueCountFrequency (%)
653-9500 1
 
0.9%
461-2021 1
 
0.9%
532-9932 1
 
0.9%
535-5114 1
 
0.9%
535-1005 1
 
0.9%
535-4751 1
 
0.9%
535-1001 1
 
0.9%
534-7770 1
 
0.9%
434-2486 1
 
0.9%
432-1027 1
 
0.9%
Other values (99) 99
90.8%
2023-12-12T19:31:52.548325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 113
13.0%
- 108
12.5%
3 104
12.0%
5 98
11.3%
8 82
9.5%
4 69
8.0%
1 66
7.6%
7 65
7.5%
0 63
7.3%
6 56
6.5%
Other values (4) 43
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 756
87.2%
Dash Punctuation 108
 
12.5%
Other Letter 3
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 113
14.9%
3 104
13.8%
5 98
13.0%
8 82
10.8%
4 69
9.1%
1 66
8.7%
7 65
8.6%
0 63
8.3%
6 56
7.4%
9 40
 
5.3%
Other Letter
ValueCountFrequency (%)
연 1
33.3%
락 1
33.3%
처 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 108
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 864
99.7%
Hangul 3
 
0.3%

Most frequent character per script

Common
ValueCountFrequency (%)
2 113
13.1%
- 108
12.5%
3 104
12.0%
5 98
11.3%
8 82
9.5%
4 69
8.0%
1 66
7.6%
7 65
7.5%
0 63
7.3%
6 56
6.5%
Hangul
ValueCountFrequency (%)
연 1
33.3%
락 1
33.3%
처 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 864
99.7%
Hangul 3
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 113
13.1%
- 108
12.5%
3 104
12.0%
5 98
11.3%
8 82
9.5%
4 69
8.0%
1 66
7.6%
7 65
7.5%
0 63
7.3%
6 56
6.5%
Hangul
ValueCountFrequency (%)
연 1
33.3%
락 1
33.3%
처 1
33.3%

Unnamed: 6
Text

Distinct73
Distinct (%)67.0%
Missing1
Missing (%)0.9%
Memory size1012.0 B
2023-12-12T19:31:52.819610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length10
Mean length4.6238532
Min length2

Characters and Unicode

Total characters504
Distinct characters116
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

Unique60 ?
Unique (%)55.0%

Sample

1st row주메뉴
2nd row한정식
3rd row민어회
4th row홍어삼합
5th row꼬리곰탕
ValueCountFrequency (%)
한정식 17
 
15.0%
숯불고기 7
 
6.2%
생선회 4
 
3.5%
회정식 3
 
2.7%
참게탕 2
 
1.8%
곰탕 2
 
1.8%
삼합애국 2
 
1.8%
서대회 2
 
1.8%
회 2
 
1.8%
굴비정식 2
 
1.8%
Other values (65) 70
61.9%
2023-12-12T19:31:53.183900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 42
 
8.3%
한 38
 
7.5%
정 34
 
6.7%
비 20
 
4.0%
회 15
 
3.0%
갈 13
 
2.6%
탕 13
 
2.6%
( 12
 
2.4%
불 12
 
2.4%
) 12
 
2.4%
Other values (106) 293
58.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 469
93.1%
Open Punctuation 12
 
2.4%
Close Punctuation 12
 
2.4%
Other Punctuation 6
 
1.2%
Space Separator 5
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 42
 
9.0%
한 38
 
8.1%
정 34
 
7.2%
비 20
 
4.3%
회 15
 
3.2%
갈 13
 
2.8%
탕 13
 
2.8%
불 12
 
2.6%
기 11
 
2.3%
고 10
 
2.1%
Other values (102) 261
55.7%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 469
93.1%
Common 35
 
6.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 42
 
9.0%
한 38
 
8.1%
정 34
 
7.2%
비 20
 
4.3%
회 15
 
3.2%
갈 13
 
2.8%
탕 13
 
2.8%
불 12
 
2.6%
기 11
 
2.3%
고 10
 
2.1%
Other values (102) 261
55.7%
Common
ValueCountFrequency (%)
( 12
34.3%
) 12
34.3%
, 6
17.1%
5
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 469
93.1%
ASCII 35
 
6.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 42
 
9.0%
한 38
 
8.1%
정 34
 
7.2%
비 20
 
4.3%
회 15
 
3.2%
갈 13
 
2.8%
탕 13
 
2.8%
불 12
 
2.6%
기 11
 
2.3%
고 10
 
2.1%
Other values (102) 261
55.7%
ASCII
ValueCountFrequency (%)
( 12
34.3%
) 12
34.3%
, 6
17.1%
5
14.3%

Unnamed: 7
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing109
Missing (%)99.1%
Memory size1012.0 B
2023-12-12T19:31:53.288770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row비고
ValueCountFrequency (%)
비고 1
100.0%
2023-12-12T19:31:53.544309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
비 1
50.0%
고 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
비 1
50.0%
고 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
비 1
50.0%
고 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
비 1
50.0%
고 1
50.0%

Correlations

2023-12-12T19:31:53.644393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 2Unnamed: 6
Unnamed: 21.0000.985
Unnamed: 60.9851.000

Missing values

2023-12-12T19:31:48.741586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:31:48.894661image/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.
2023-12-12T19:31:49.042059image/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

Unnamed: 0Unnamed: 1Unnamed: 2남도음식명가 지정 업소 명단(108개소)Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7
0NaN<NA><NA><NA><NA><NA><NA><NA>
1연번업체명시군소재지대표자연락처주메뉴비고
21옥 정목포시목포시 미항로 8(상동)이경하243-0012한정식<NA>
32영란횟집목포시목포시 번화로 47(중앙동 1가)조형숙243-7311민어회<NA>
43인동주마을목포시목포시 복산길 12번길 5(옥암동)우정단284-4068홍어삼합<NA>
54대양목포시목포시 해안로 173번길 45(중앙동)강옥희244-8308꼬리곰탕<NA>
65한국추어탕목포시목포시 하당로 241번길 11(상동)임성희282-5080추어탕<NA>
76황금어장목포시목포시 미항로 89(상동)김경수281-3772회정식<NA>
87독천식당목포시목포시 호남로 64번길 3-1(호남동)최순희244-8622낙지비빔밥<NA>
98인도양일식회목포시목포시 해안로 47(온금동)허순243-6888회정식<NA>
Unnamed: 0Unnamed: 1Unnamed: 2남도음식명가 지정 업소 명단(108개소)Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7
10099해운대횟집완도군완도군 완도읍 해변공원로 124번길 11한기덕554-0059한식(생선회)<NA>
101100대복횟집완도군완도군 완도읍 해변공원로 109-1마권일554-3341한식(전복)<NA>
102101새천년횟집완도군완도군 완도읍 해변공원로 124번길 19박수영554-0704한식(생선회)<NA>
103102가든한국관완도군완도군 ․읍 군내3번길 24-6정광필552-1215한식(해물한정식)<NA>
104103바위섬완도군완도군 보길면 보길동로 19번길 28신순애555-5612한식(전복)<NA>
105104나주곰탕진도군진도군 진도읍 남동1길 32황기선542-0825곰탕, 갈비탕<NA>
106105이조숯불갈비진도군진도군 진도읍 남문길 12-1고종철544-8183소등심,돼지갈비<NA>
107106안성식당신안군신안군 증도면 증도중앙길 43박윤희271-7998한식(짱뚱어탕)<NA>
108107솔트레스토랑신안군신안군 증도면 지도증도로 1053-11손일선261-2277레스토랑(생선구이)<NA>
109108꽃피는무화家신안군신안군 압해읍 압해로 393-2김선주271-5552한식(영양밥)<NA>