Overview

Dataset statistics

Number of variables6
Number of observations529
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory24.9 KiB
Average record size in memory48.2 B

Variable types

Categorical2
Text4

Dataset

Description충청남도 시군에 등록된 모범 음식점 현황에 대한 데이터이며 지역, 업소명, 주소, 연락처 주 메뉴 등 항목을 제공합니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=406&beforeMenuCd=DOM_000000201001001000&publicdatapk=3082706

Alerts

업종 is highly imbalanced (59.2%)Imbalance

Reproduction

Analysis started2024-01-09 20:57:19.586876
Analysis finished2024-01-09 20:57:20.238659
Duration0.65 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지역
Categorical

Distinct13
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
아산시
100 
공주시
66 
논산시
54 
서산시
46 
당진시
44 
Other values (8)
219 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
아산시 100
18.9%
공주시 66
12.5%
논산시 54
10.2%
서산시 46
8.7%
당진시 44
8.3%
천안시 40
 
7.6%
부여군 33
 
6.2%
예산군 33
 
6.2%
태안군 29
 
5.5%
홍성군 26
 
4.9%
Other values (3) 58
11.0%

Length

2024-01-10T05:57:20.285743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
아산시 100
18.9%
공주시 66
12.5%
논산시 54
10.2%
서산시 46
8.7%
당진시 44
8.3%
천안시 40
 
7.6%
부여군 33
 
6.2%
예산군 33
 
6.2%
태안군 29
 
5.5%
홍성군 26
 
4.9%
Other values (3) 58
11.0%

업소명
Text

Distinct521
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
2024-01-10T05:57:20.466062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length16
Mean length5.4933837
Min length1

Characters and Unicode

Total characters2906
Distinct characters419
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique513 ?
Unique (%)97.0%

Sample

1st row유가네장어본점
2nd row웅짬뽕
3rd row송원가든
4th row처갓집생삼겹
5th row원대구뽈탕
ValueCountFrequency (%)
본점 3
 
0.5%
아산점 3
 
0.5%
용화점 2
 
0.3%
화평동왕냉면 2
 
0.3%
등촌샤브칼국수 2
 
0.3%
육하원칙 2
 
0.3%
청지기꽃게장 2
 
0.3%
주)태경비케이 2
 
0.3%
㈜케이알산업홍성 2
 
0.3%
태평식당 2
 
0.3%
Other values (546) 554
96.2%
2024-01-10T05:57:20.827724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
가 76
 
2.6%
산 57
 
2.0%
당 55
 
1.9%
52
 
1.8%
수 50
 
1.7%
집 46
 
1.6%
식 46
 
1.6%
점 45
 
1.5%
대 43
 
1.5%
비 41
 
1.4%
Other values (409) 2395
82.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2794
96.1%
Space Separator 52
 
1.8%
Close Punctuation 20
 
0.7%
Open Punctuation 20
 
0.7%
Decimal Number 8
 
0.3%
Other Punctuation 4
 
0.1%
Lowercase Letter 4
 
0.1%
Other Symbol 3
 
0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
가 76
 
2.7%
산 57
 
2.0%
당 55
 
2.0%
수 50
 
1.8%
집 46
 
1.6%
식 46
 
1.6%
점 45
 
1.6%
대 43
 
1.5%
비 41
 
1.5%
장 40
 
1.4%
Other values (393) 2295
82.1%
Decimal Number
ValueCountFrequency (%)
1 4
50.0%
3 1
 
12.5%
5 1
 
12.5%
2 1
 
12.5%
0 1
 
12.5%
Lowercase Letter
ValueCountFrequency (%)
o 1
25.0%
u 1
25.0%
t 1
25.0%
e 1
25.0%
Other Punctuation
ValueCountFrequency (%)
& 3
75.0%
· 1
 
25.0%
Space Separator
ValueCountFrequency (%)
52
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 3
100.0%
Uppercase Letter
ValueCountFrequency (%)
R 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2796
96.2%
Common 104
 
3.6%
Latin 5
 
0.2%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
가 76
 
2.7%
산 57
 
2.0%
당 55
 
2.0%
수 50
 
1.8%
집 46
 
1.6%
식 46
 
1.6%
점 45
 
1.6%
대 43
 
1.5%
비 41
 
1.5%
장 40
 
1.4%
Other values (393) 2297
82.2%
Common
ValueCountFrequency (%)
52
50.0%
) 20
 
19.2%
( 20
 
19.2%
1 4
 
3.8%
& 3
 
2.9%
· 1
 
1.0%
3 1
 
1.0%
5 1
 
1.0%
2 1
 
1.0%
0 1
 
1.0%
Latin
ValueCountFrequency (%)
R 1
20.0%
o 1
20.0%
u 1
20.0%
t 1
20.0%
e 1
20.0%
Han
ValueCountFrequency (%)
本 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2793
96.1%
ASCII 108
 
3.7%
None 4
 
0.1%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
가 76
 
2.7%
산 57
 
2.0%
당 55
 
2.0%
수 50
 
1.8%
집 46
 
1.6%
식 46
 
1.6%
점 45
 
1.6%
대 43
 
1.5%
비 41
 
1.5%
장 40
 
1.4%
Other values (392) 2294
82.1%
ASCII
ValueCountFrequency (%)
52
48.1%
) 20
 
18.5%
( 20
 
18.5%
1 4
 
3.7%
& 3
 
2.8%
3 1
 
0.9%
5 1
 
0.9%
2 1
 
0.9%
0 1
 
0.9%
R 1
 
0.9%
Other values (4) 4
 
3.7%
None
ValueCountFrequency (%)
㈜ 3
75.0%
· 1
 
25.0%
CJK
ValueCountFrequency (%)
本 1
100.0%

주소
Text

Distinct527
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
2024-01-10T05:57:21.121725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length37
Mean length23.964083
Min length16

Characters and Unicode

Total characters12677
Distinct characters266
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

Unique525 ?
Unique (%)99.2%

Sample

1st row충청남도 천안시 동남구 청수13로 20(청당동)
2nd row충청남도 천안시 동남구 청수6로 35-80(청당동)
3rd row충청남도 천안시 동남구 북면 충철로 1358-6
4th row충청남도 천안시 서북구 원두정4길2, 1층(두정동)
5th row충청남도 천안시 서북구 오성4길 10,1층(두정동)
ValueCountFrequency (%)
충청남도 529
 
19.0%
아산시 100
 
3.6%
1층 82
 
2.9%
공주시 66
 
2.4%
논산시 54
 
1.9%
서산시 46
 
1.7%
당진시 44
 
1.6%
천안시 40
 
1.4%
부여군 33
 
1.2%
예산군 33
 
1.2%
Other values (936) 1758
63.1%
2024-01-10T05:57:21.528383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2323
 
18.3%
남 569
 
4.5%
청 554
 
4.4%
충 545
 
4.3%
1 540
 
4.3%
도 538
 
4.2%
시 400
 
3.2%
로 387
 
3.1%
산 330
 
2.6%
동 313
 
2.5%
Other values (256) 6178
48.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7608
60.0%
Space Separator 2323
 
18.3%
Decimal Number 1970
 
15.5%
Open Punctuation 234
 
1.8%
Close Punctuation 234
 
1.8%
Other Punctuation 150
 
1.2%
Dash Punctuation 149
 
1.2%
Uppercase Letter 5
 
< 0.1%
Math Symbol 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 569
 
7.5%
청 554
 
7.3%
충 545
 
7.2%
도 538
 
7.1%
시 400
 
5.3%
로 387
 
5.1%
산 330
 
4.3%
동 313
 
4.1%
길 216
 
2.8%
읍 169
 
2.2%
Other values (235) 3587
47.1%
Decimal Number
ValueCountFrequency (%)
1 540
27.4%
2 280
14.2%
3 200
 
10.2%
4 172
 
8.7%
6 146
 
7.4%
5 139
 
7.1%
0 132
 
6.7%
7 126
 
6.4%
9 118
 
6.0%
8 117
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 148
98.7%
. 1
 
0.7%
& 1
 
0.7%
Uppercase Letter
ValueCountFrequency (%)
J 2
40.0%
A 2
40.0%
B 1
20.0%
Space Separator
ValueCountFrequency (%)
2323
100.0%
Open Punctuation
ValueCountFrequency (%)
( 234
100.0%
Close Punctuation
ValueCountFrequency (%)
) 234
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 149
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7608
60.0%
Common 5064
39.9%
Latin 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 569
 
7.5%
청 554
 
7.3%
충 545
 
7.2%
도 538
 
7.1%
시 400
 
5.3%
로 387
 
5.1%
산 330
 
4.3%
동 313
 
4.1%
길 216
 
2.8%
읍 169
 
2.2%
Other values (235) 3587
47.1%
Common
ValueCountFrequency (%)
2323
45.9%
1 540
 
10.7%
2 280
 
5.5%
( 234
 
4.6%
) 234
 
4.6%
3 200
 
3.9%
4 172
 
3.4%
- 149
 
2.9%
, 148
 
2.9%
6 146
 
2.9%
Other values (8) 638
 
12.6%
Latin
ValueCountFrequency (%)
J 2
40.0%
A 2
40.0%
B 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7608
60.0%
ASCII 5069
40.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2323
45.8%
1 540
 
10.7%
2 280
 
5.5%
( 234
 
4.6%
) 234
 
4.6%
3 200
 
3.9%
4 172
 
3.4%
- 149
 
2.9%
, 148
 
2.9%
6 146
 
2.9%
Other values (11) 643
 
12.7%
Hangul
ValueCountFrequency (%)
남 569
 
7.5%
청 554
 
7.3%
충 545
 
7.2%
도 538
 
7.1%
시 400
 
5.3%
로 387
 
5.1%
산 330
 
4.3%
동 313
 
4.1%
길 216
 
2.8%
읍 169
 
2.2%
Other values (235) 3587
47.1%

전화번호
Text

Distinct528
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
2024-01-10T05:57:21.751439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length12
Mean length12.877127
Min length12

Characters and Unicode

Total characters6812
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique527 ?
Unique (%)99.6%

Sample

1st row041-565-1092
2nd row041-555-7522
3rd row041-566-3336
4th row041-622-9295
5th row041-567-1780
ValueCountFrequency (%)
041 198
 
23.9%
543 10
 
1.2%
042 8
 
1.0%
546 5
 
0.6%
545 5
 
0.6%
532 5
 
0.6%
858 4
 
0.5%
534 4
 
0.5%
547 4
 
0.5%
675 4
 
0.5%
Other values (558) 580
70.1%
2024-01-10T05:57:22.067576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1058
15.5%
0 839
12.3%
4 798
11.7%
1 782
11.5%
3 583
8.6%
5 570
8.4%
436
6.4%
6 397
 
5.8%
8 360
 
5.3%
7 352
 
5.2%
Other values (2) 637
9.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5318
78.1%
Dash Punctuation 1058
 
15.5%
Space Separator 436
 
6.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 839
15.8%
4 798
15.0%
1 782
14.7%
3 583
11.0%
5 570
10.7%
6 397
7.5%
8 360
6.8%
7 352
6.6%
2 346
6.5%
9 291
 
5.5%
Dash Punctuation
ValueCountFrequency (%)
- 1058
100.0%
Space Separator
ValueCountFrequency (%)
436
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6812
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 1058
15.5%
0 839
12.3%
4 798
11.7%
1 782
11.5%
3 583
8.6%
5 570
8.4%
436
6.4%
6 397
 
5.8%
8 360
 
5.3%
7 352
 
5.2%
Other values (2) 637
9.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6812
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1058
15.5%
0 839
12.3%
4 798
11.7%
1 782
11.5%
3 583
8.6%
5 570
8.4%
436
6.4%
6 397
 
5.8%
8 360
 
5.3%
7 352
 
5.2%
Other values (2) 637
9.4%

주메뉴
Text

Distinct396
Distinct (%)74.9%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
2024-01-10T05:57:22.316810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length37
Mean length7.905482
Min length2

Characters and Unicode

Total characters4182
Distinct characters299
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique339 ?
Unique (%)64.1%

Sample

1st row민물장어
2nd row짬뽕
3rd row소머리국밥,염소탕
4th row갈비류
5th row대구뽈찜, 대구탕(지리)
ValueCountFrequency (%)
삼겹살 19
 
2.4%
돼지갈비 17
 
2.1%
한정식 15
 
1.9%
칼국수 14
 
1.8%
갈비 13
 
1.6%
생선회 13
 
1.6%
등 12
 
1.5%
삼계탕 11
 
1.4%
장어구이 10
 
1.3%
갈비탕 10
 
1.3%
Other values (444) 661
83.1%
2024-01-10T05:57:22.692197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 382
 
9.1%
272
 
6.5%
탕 130
 
3.1%
비 117
 
2.8%
갈 103
 
2.5%
식 100
 
2.4%
정 79
 
1.9%
한 75
 
1.8%
장 74
 
1.8%
국 73
 
1.7%
Other values (289) 2777
66.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3478
83.2%
Other Punctuation 388
 
9.3%
Space Separator 272
 
6.5%
Close Punctuation 18
 
0.4%
Open Punctuation 18
 
0.4%
Decimal Number 4
 
0.1%
Math Symbol 2
 
< 0.1%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
탕 130
 
3.7%
비 117
 
3.4%
갈 103
 
3.0%
식 100
 
2.9%
정 79
 
2.3%
한 75
 
2.2%
장 74
 
2.1%
국 73
 
2.1%
기 66
 
1.9%
밥 65
 
1.9%
Other values (278) 2596
74.6%
Decimal Number
ValueCountFrequency (%)
4 2
50.0%
3 1
25.0%
2 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 382
98.5%
. 6
 
1.5%
Uppercase Letter
ValueCountFrequency (%)
L 1
50.0%
A 1
50.0%
Space Separator
ValueCountFrequency (%)
272
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3478
83.2%
Common 702
 
16.8%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
탕 130
 
3.7%
비 117
 
3.4%
갈 103
 
3.0%
식 100
 
2.9%
정 79
 
2.3%
한 75
 
2.2%
장 74
 
2.1%
국 73
 
2.1%
기 66
 
1.9%
밥 65
 
1.9%
Other values (278) 2596
74.6%
Common
ValueCountFrequency (%)
, 382
54.4%
272
38.7%
) 18
 
2.6%
( 18
 
2.6%
. 6
 
0.9%
+ 2
 
0.3%
4 2
 
0.3%
3 1
 
0.1%
2 1
 
0.1%
Latin
ValueCountFrequency (%)
L 1
50.0%
A 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3478
83.2%
ASCII 704
 
16.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 382
54.3%
272
38.6%
) 18
 
2.6%
( 18
 
2.6%
. 6
 
0.9%
+ 2
 
0.3%
4 2
 
0.3%
L 1
 
0.1%
A 1
 
0.1%
3 1
 
0.1%
Hangul
ValueCountFrequency (%)
탕 130
 
3.7%
비 117
 
3.4%
갈 103
 
3.0%
식 100
 
2.9%
정 79
 
2.3%
한 75
 
2.2%
장 74
 
2.1%
국 73
 
2.1%
기 66
 
1.9%
밥 65
 
1.9%
Other values (278) 2596
74.6%

업종
Categorical

IMBALANCE 

Distinct11
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
한식
415 
식육(숯불구이)
 
25
일식
 
20
분식
 
18
중식
 
11
Other values (6)
 
40

Length

Max length8
Median length2
Mean length2.3270321
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
한식 415
78.4%
식육(숯불구이) 25
 
4.7%
일식 20
 
3.8%
분식 18
 
3.4%
중식 11
 
2.1%
중국식 9
 
1.7%
횟집 9
 
1.7%
경양식 8
 
1.5%
양식 6
 
1.1%
뷔페식 6
 
1.1%

Length

2024-01-10T05:57:22.808343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 415
78.4%
식육(숯불구이 25
 
4.7%
일식 20
 
3.8%
분식 18
 
3.4%
중식 11
 
2.1%
중국식 9
 
1.7%
횟집 9
 
1.7%
경양식 8
 
1.5%
양식 6
 
1.1%
뷔페식 6
 
1.1%

Correlations

2024-01-10T05:57:22.882097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역업종
지역1.0000.454
업종0.4541.000
2024-01-10T05:57:22.951859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종지역
업종1.0000.200
지역0.2001.000
2024-01-10T05:57:23.034154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역업종
지역1.0000.200
업종0.2001.000

Missing values

2024-01-10T05:57:20.126842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T05:57:20.206681image/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

지역업소명주소전화번호주메뉴업종
0천안시유가네장어본점충청남도 천안시 동남구 청수13로 20(청당동)041-565-1092민물장어한식
1천안시웅짬뽕충청남도 천안시 동남구 청수6로 35-80(청당동)041-555-7522짬뽕중식
2천안시송원가든충청남도 천안시 동남구 북면 충철로 1358-6041-566-3336소머리국밥,염소탕한식
3천안시처갓집생삼겹충청남도 천안시 서북구 원두정4길2, 1층(두정동)041-622-9295갈비류한식
4천안시원대구뽈탕충청남도 천안시 서북구 오성4길 10,1층(두정동)041-567-1780대구뽈찜, 대구탕(지리)한식
5천안시온누리쭈꾸미 천안성정점충청남도 천안시 서북구 백석로 203(성정동)041-572-9292철판쭈꾸미한식
6천안시라온흑염소삼계탕전문충청남도 천안시 서북구 미라11길 26(쌍용동)0507-1388-9233흑염소탕,삼계탕한식
7천안시황금돼지충청남도 천안시 서북구 불당25로 192, 113호(불당동, 골든프라자2)0507-1345-0773삼겹살한식
8천안시김씨네부대찌개충청남도 천안시 서북구 직산읍 직산로 43041-583-5566부대찌개한식
9천안시불당시티 울엄마김밥충청남도 천안시 서북구 공원로 176, 지하2 B214호(시티프라디움3차, 불당동)041-533-6800김밥, 쫄면분식
지역업소명주소전화번호주메뉴업종
519태안군인평장어메기집충청남도 태안군 태안읍 강경벌로 739041- 674-4660장어구이한식
520태안군정일품충청남도 태안군 태안읍 동문5길 5-1041- 674-0505갈비, 돌솥밥한식
521태안군통나무집사람들충청남도 태안군 원북면 원이로 447-15041- 672-1600마늘갈비,게국지,간장게장한식
522태안군한국관충청남도 태안군 태안읍 독샘로 100041- 675-2415한정식한식
523태안군한아구충청남도 태안군 태안읍 중앙로 133-8041- 674-3800아구탕한식
524태안군항구회관충청남도 태안군 근흥면 신진부두길 134041- 675-3330회, 매운탕횟집
525태안군항아리보쌈태안점충청남도 태안군 태안읍 군청8길 19041 -675 -0023보쌈, 쟁반구수, 육개장한식
526태안군향토꽃게장충청남도 태안군 태안읍 능샘1길 44041- 674-5591게장, 우럭젓국한식
527태안군홍두깨칼국수충청남도 태안군 태안읍 정주내2길 1041- 672-7379칼국수, 만두전골분식
528태안군황소왕갈비충청남도 태안군 안면읍 장터로 172041- 673-4130한식(갈비)식육(숯불구이)