Overview

Dataset statistics

Number of variables11
Number of observations60
Missing cells1
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.4 KiB
Average record size in memory92.2 B

Variable types

Numeric1
Categorical6
Text4

Alerts

자료출처 has constant value ""Constant
공개여부 has constant value ""Constant
갱신주기 has constant value ""Constant
작성일 is highly overall correlated with 비고High correlation
비고 is highly overall correlated with 작성일High correlation
순번 is highly overall correlated with 시군명High correlation
시군명 is highly overall correlated with 순번High correlation
비고 is highly imbalanced (84.6%)Imbalance
작성일 is highly imbalanced (87.8%)Imbalance
대표자 has 1 (1.7%) missing valuesMissing
순번 has unique valuesUnique

Reproduction

Analysis started2024-03-14 00:35:28.841637
Analysis finished2024-03-14 00:35:29.856290
Duration1.01 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30.5
Minimum1
Maximum60
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2024-03-14T09:35:29.932338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.95
Q115.75
median30.5
Q345.25
95-th percentile57.05
Maximum60
Range59
Interquartile range (IQR)29.5

Descriptive statistics

Standard deviation17.464249
Coefficient of variation (CV)0.57259833
Kurtosis-1.2
Mean30.5
Median Absolute Deviation (MAD)15
Skewness0
Sum1830
Variance305
MonotonicityStrictly increasing
2024-03-14T09:35:30.063930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.7%
32 1
 
1.7%
34 1
 
1.7%
35 1
 
1.7%
36 1
 
1.7%
37 1
 
1.7%
38 1
 
1.7%
39 1
 
1.7%
40 1
 
1.7%
41 1
 
1.7%
Other values (50) 50
83.3%
ValueCountFrequency (%)
1 1
1.7%
2 1
1.7%
3 1
1.7%
4 1
1.7%
5 1
1.7%
6 1
1.7%
7 1
1.7%
8 1
1.7%
9 1
1.7%
10 1
1.7%
ValueCountFrequency (%)
60 1
1.7%
59 1
1.7%
58 1
1.7%
57 1
1.7%
56 1
1.7%
55 1
1.7%
54 1
1.7%
53 1
1.7%
52 1
1.7%
51 1
1.7%

시군명
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
전주시
28 
군산시
11 
부안군
4 
익산시
3 
남원시
3 
Other values (7)
11 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique4 ?
Unique (%)6.7%

Sample

1st row완주군
2nd row익산시
3rd row익산시
4th row익산시
5th row부안군

Common Values

ValueCountFrequency (%)
전주시 28
46.7%
군산시 11
 
18.3%
부안군 4
 
6.7%
익산시 3
 
5.0%
남원시 3
 
5.0%
김제시 3
 
5.0%
진안군 2
 
3.3%
임실군 2
 
3.3%
완주군 1
 
1.7%
무주군 1
 
1.7%
Other values (2) 2
 
3.3%

Length

2024-03-14T09:35:30.172819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전주시 28
46.7%
군산시 11
 
18.3%
부안군 4
 
6.7%
익산시 3
 
5.0%
남원시 3
 
5.0%
김제시 3
 
5.0%
진안군 2
 
3.3%
임실군 2
 
3.3%
완주군 1
 
1.7%
무주군 1
 
1.7%
Other values (2) 2
 
3.3%

업체명
Text

Distinct59
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
2024-03-14T09:35:30.350261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length4.5333333
Min length2

Characters and Unicode

Total characters272
Distinct characters139
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

Unique58 ?
Unique (%)96.7%

Sample

1st row그랑삐아또
2nd row화원반점
3rd row아리산
4th row동보성
5th row격포항횟집
ValueCountFrequency (%)
일품향 2
 
3.2%
그랑삐아또 1
 
1.6%
아리랑하우스 1
 
1.6%
우리밀 1
 
1.6%
동우 1
 
1.6%
전라도음식이야기 1
 
1.6%
유)송천이중본 1
 
1.6%
백리향 1
 
1.6%
유)몽중원 1
 
1.6%
북경루 1
 
1.6%
Other values (51) 51
82.3%
2024-03-14T09:35:30.635543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
중 8
 
2.9%
아 8
 
2.9%
집 7
 
2.6%
이 7
 
2.6%
리 6
 
2.2%
우 5
 
1.8%
횟 5
 
1.8%
스 5
 
1.8%
가 4
 
1.5%
성 4
 
1.5%
Other values (129) 213
78.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 266
97.8%
Open Punctuation 2
 
0.7%
Space Separator 2
 
0.7%
Close Punctuation 2
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
중 8
 
3.0%
아 8
 
3.0%
집 7
 
2.6%
이 7
 
2.6%
리 6
 
2.3%
우 5
 
1.9%
횟 5
 
1.9%
스 5
 
1.9%
가 4
 
1.5%
성 4
 
1.5%
Other values (126) 207
77.8%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 266
97.8%
Common 6
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
중 8
 
3.0%
아 8
 
3.0%
집 7
 
2.6%
이 7
 
2.6%
리 6
 
2.3%
우 5
 
1.9%
횟 5
 
1.9%
스 5
 
1.9%
가 4
 
1.5%
성 4
 
1.5%
Other values (126) 207
77.8%
Common
ValueCountFrequency (%)
( 2
33.3%
2
33.3%
) 2
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 266
97.8%
ASCII 6
 
2.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
중 8
 
3.0%
아 8
 
3.0%
집 7
 
2.6%
이 7
 
2.6%
리 6
 
2.3%
우 5
 
1.9%
횟 5
 
1.9%
스 5
 
1.9%
가 4
 
1.5%
성 4
 
1.5%
Other values (126) 207
77.8%
ASCII
ValueCountFrequency (%)
( 2
33.3%
2
33.3%
) 2
33.3%

대표자
Text

MISSING 

Distinct58
Distinct (%)98.3%
Missing1
Missing (%)1.7%
Memory size612.0 B
2024-03-14T09:35:30.822453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.0169492
Min length3

Characters and Unicode

Total characters178
Distinct characters86
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

Unique57 ?
Unique (%)96.6%

Sample

1st row지진산
2nd row허숭희
3rd row성복방
4th row주유진
5th row임영신
ValueCountFrequency (%)
박순자 2
 
3.3%
정점순 1
 
1.7%
이점란 1
 
1.7%
장용운 1
 
1.7%
소우현 1
 
1.7%
이정애 1
 
1.7%
정정기 1
 
1.7%
김호영 1
 
1.7%
이철준 1
 
1.7%
이명희 1
 
1.7%
Other values (49) 49
81.7%
2024-03-14T09:35:31.141579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 11
 
6.2%
김 9
 
5.1%
박 7
 
3.9%
순 7
 
3.9%
정 7
 
3.9%
희 6
 
3.4%
영 6
 
3.4%
성 4
 
2.2%
현 4
 
2.2%
자 4
 
2.2%
Other values (76) 113
63.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 176
98.9%
Space Separator 2
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 11
 
6.2%
김 9
 
5.1%
박 7
 
4.0%
순 7
 
4.0%
정 7
 
4.0%
희 6
 
3.4%
영 6
 
3.4%
성 4
 
2.3%
현 4
 
2.3%
자 4
 
2.3%
Other values (75) 111
63.1%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 176
98.9%
Common 2
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 11
 
6.2%
김 9
 
5.1%
박 7
 
4.0%
순 7
 
4.0%
정 7
 
4.0%
희 6
 
3.4%
영 6
 
3.4%
성 4
 
2.3%
현 4
 
2.3%
자 4
 
2.3%
Other values (75) 111
63.1%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 176
98.9%
ASCII 2
 
1.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 11
 
6.2%
김 9
 
5.1%
박 7
 
4.0%
순 7
 
4.0%
정 7
 
4.0%
희 6
 
3.4%
영 6
 
3.4%
성 4
 
2.3%
현 4
 
2.3%
자 4
 
2.3%
Other values (75) 111
63.1%
ASCII
ValueCountFrequency (%)
2
100.0%

도로명주소
Text

Distinct59
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
2024-03-14T09:35:31.407903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length16
Mean length14.533333
Min length9

Characters and Unicode

Total characters872
Distinct characters119
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

Unique58 ?
Unique (%)96.7%

Sample

1st row완주군 구이면 두방길 28
2nd row익산시 목천로7길 24-1
3rd row익산시 인북로 323
4th row익산시 하나로 437
5th row부안군 변산면 방파제길 39
ValueCountFrequency (%)
전주시 27
 
12.2%
완산구 18
 
8.1%
군산시 12
 
5.4%
덕진구 9
 
4.1%
부안군 4
 
1.8%
35 3
 
1.4%
김제시 3
 
1.4%
익산시 3
 
1.4%
남원시 3
 
1.4%
변산면 3
 
1.4%
Other values (127) 137
61.7%
2024-03-14T09:35:31.816497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
162
18.6%
시 49
 
5.6%
산 42
 
4.8%
3 34
 
3.9%
전 34
 
3.9%
주 33
 
3.8%
로 32
 
3.7%
길 28
 
3.2%
구 28
 
3.2%
1 26
 
3.0%
Other values (109) 404
46.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 523
60.0%
Decimal Number 173
 
19.8%
Space Separator 162
 
18.6%
Dash Punctuation 14
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 49
 
9.4%
산 42
 
8.0%
전 34
 
6.5%
주 33
 
6.3%
로 32
 
6.1%
길 28
 
5.4%
구 28
 
5.4%
군 23
 
4.4%
완 19
 
3.6%
진 12
 
2.3%
Other values (97) 223
42.6%
Decimal Number
ValueCountFrequency (%)
3 34
19.7%
1 26
15.0%
2 24
13.9%
5 19
11.0%
9 16
9.2%
6 13
 
7.5%
4 12
 
6.9%
0 12
 
6.9%
7 12
 
6.9%
8 5
 
2.9%
Space Separator
ValueCountFrequency (%)
162
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 523
60.0%
Common 349
40.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 49
 
9.4%
산 42
 
8.0%
전 34
 
6.5%
주 33
 
6.3%
로 32
 
6.1%
길 28
 
5.4%
구 28
 
5.4%
군 23
 
4.4%
완 19
 
3.6%
진 12
 
2.3%
Other values (97) 223
42.6%
Common
ValueCountFrequency (%)
162
46.4%
3 34
 
9.7%
1 26
 
7.4%
2 24
 
6.9%
5 19
 
5.4%
9 16
 
4.6%
- 14
 
4.0%
6 13
 
3.7%
4 12
 
3.4%
0 12
 
3.4%
Other values (2) 17
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 523
60.0%
ASCII 349
40.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
162
46.4%
3 34
 
9.7%
1 26
 
7.4%
2 24
 
6.9%
5 19
 
5.4%
9 16
 
4.6%
- 14
 
4.0%
6 13
 
3.7%
4 12
 
3.4%
0 12
 
3.4%
Other values (2) 17
 
4.9%
Hangul
ValueCountFrequency (%)
시 49
 
9.4%
산 42
 
8.0%
전 34
 
6.5%
주 33
 
6.3%
로 32
 
6.1%
길 28
 
5.4%
구 28
 
5.4%
군 23
 
4.4%
완 19
 
3.6%
진 12
 
2.3%
Other values (97) 223
42.6%

전화번호
Text

Distinct59
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
2024-03-14T09:35:32.081209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters720
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

Unique58 ?
Unique (%)96.7%

Sample

1st row063-221-0601
2nd row063-855-2608
3rd row063-851-5265
4th row063-838-2888
5th row063-584-8833
ValueCountFrequency (%)
063-464-4489 2
 
3.3%
063-468-5300 1
 
1.7%
063-453-8883 1
 
1.7%
063-254-1336 1
 
1.7%
063-241-1819 1
 
1.7%
063-244-4477 1
 
1.7%
063-255-7738 1
 
1.7%
063-274-8801 1
 
1.7%
063-284-1900 1
 
1.7%
063-276-5252 1
 
1.7%
Other values (49) 49
81.7%
2024-03-14T09:35:32.377215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 120
16.7%
0 99
13.8%
3 97
13.5%
6 92
12.8%
2 65
9.0%
4 60
8.3%
8 57
7.9%
5 46
 
6.4%
1 43
 
6.0%
7 21
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 600
83.3%
Dash Punctuation 120
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 99
16.5%
3 97
16.2%
6 92
15.3%
2 65
10.8%
4 60
10.0%
8 57
9.5%
5 46
7.7%
1 43
7.2%
7 21
 
3.5%
9 20
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 120
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 720
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 120
16.7%
0 99
13.8%
3 97
13.5%
6 92
12.8%
2 65
9.0%
4 60
8.3%
8 57
7.9%
5 46
 
6.4%
1 43
 
6.0%
7 21
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 720
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 120
16.7%
0 99
13.8%
3 97
13.5%
6 92
12.8%
2 65
9.0%
4 60
8.3%
8 57
7.9%
5 46
 
6.4%
1 43
 
6.0%
7 21
 
2.9%

비고
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
-
58 
터존부페
 
1
<NA>
 
1

Length

Max length4
Median length1
Mean length1.1
Min length1

Unique

Unique2 ?
Unique (%)3.3%

Sample

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

Common Values

ValueCountFrequency (%)
- 58
96.7%
터존부페 1
 
1.7%
<NA> 1
 
1.7%

Length

2024-03-14T09:35:32.490775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:35:32.574975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
58
96.7%
터존부페 1
 
1.7%
na 1
 
1.7%

자료출처
Categorical

CONSTANT 

Distinct1
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size612.0 B
관광총괄과
60 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
관광총괄과 60
100.0%

Length

2024-03-14T09:35:32.859666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:35:32.926756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
관광총괄과 60
100.0%

공개여부
Categorical

CONSTANT 

Distinct1
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size612.0 B
공개
60 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공개 60
100.0%

Length

2024-03-14T09:35:32.998896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:35:33.068477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공개 60
100.0%

작성일
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
2015.1
59 
2016.07
 
1

Length

Max length7
Median length6
Mean length6.0166667
Min length6

Unique

Unique1 ?
Unique (%)1.7%

Sample

1st row2015.1
2nd row2015.1
3rd row2015.1
4th row2015.1
5th row2015.1

Common Values

ValueCountFrequency (%)
2015.1 59
98.3%
2016.07 1
 
1.7%

Length

2024-03-14T09:35:33.154614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:35:33.258729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2015.1 59
98.3%
2016.07 1
 
1.7%

갱신주기
Categorical

CONSTANT 

Distinct1
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size612.0 B
1년
60 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1년
2nd row1년
3rd row1년
4th row1년
5th row1년

Common Values

ValueCountFrequency (%)
1년 60
100.0%

Length

2024-03-14T09:35:33.343631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:35:33.422738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1년 60
100.0%

Interactions

2024-03-14T09:35:29.420226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T09:35:33.476475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시군명업체명대표자도로명주소전화번호비고작성일
순번1.0000.8120.9360.9381.0001.0000.0000.071
시군명0.8121.0000.9560.0001.0001.0000.0000.000
업체명0.9360.9561.0000.9970.9970.9971.0001.000
대표자0.9380.0000.9971.0000.9970.9971.000NaN
도로명주소1.0001.0000.9970.9971.0001.0001.0001.000
전화번호1.0001.0000.9970.9971.0001.0001.0001.000
비고0.0000.0001.0001.0001.0001.0001.000NaN
작성일0.0710.0001.000NaN1.0001.000NaN1.000
2024-03-14T09:35:33.576913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명작성일비고
시군명1.0000.0000.000
작성일0.0001.0001.000
비고0.0001.0001.000
2024-03-14T09:35:33.646076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시군명비고작성일
순번1.0000.5020.0000.000
시군명0.5021.0000.0000.000
비고0.0000.0001.0001.000
작성일0.0000.0001.0001.000

Missing values

2024-03-14T09:35:29.553559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T09:35:29.794348image/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

순번시군명업체명대표자도로명주소전화번호비고자료출처공개여부작성일갱신주기
01완주군그랑삐아또지진산완주군 구이면 두방길 28063-221-0601-관광총괄과공개2015.11년
12익산시화원반점허숭희익산시 목천로7길 24-1063-855-2608-관광총괄과공개2015.11년
23익산시아리산성복방익산시 인북로 323063-851-5265-관광총괄과공개2015.11년
34익산시동보성주유진익산시 하나로 437063-838-2888-관광총괄과공개2015.11년
45부안군격포항횟집임영신부안군 변산면 방파제길 39063-584-8833-관광총괄과공개2015.11년
56부안군서해바다횟집김용특부안군 변산면 채석강길 27063-584-8811-관광총괄과공개2015.11년
67부안군테라스가든장정숙부안군 변산면 채석강길 33063-581-9933-관광총괄과공개2015.11년
78부안군해물짬뽕이선희부안군 부안읍 부풍로 131063-584-1253-관광총괄과공개2015.11년
89무주군천지가든박순자무주군 무주읍 괴목로 1313063-322-3456-관광총괄과공개2015.11년
910진안군마이담서수원진안군 부귀면 전진로 1947063-433-5535-관광총괄과공개2015.11년
순번시군명업체명대표자도로명주소전화번호비고자료출처공개여부작성일갱신주기
5051군산시정선손성남군산시 나운안1길 33063-464-2500-관광총괄과공개2015.11년
5152군산시등대횟집백정희군산시 비응로 35063-464-4489-관광총괄과공개2015.11년
5253군산시등대가식당김성규군산시 비응로 35063-464-4489-관광총괄과공개2015.11년
5354군산시만다린장준상군산시 공단대로 449063-468-0054-관광총괄과공개2015.11년
5455군산시아리울해물짬뽕나상두군산시 비응동로 65063-462-4646-관광총괄과공개2015.11년
5556군산시새만금횟집김부영군산시 비응안7길 13063-464-1001-관광총괄과공개2015.11년
5657고창군중앙식당고보준고창군 고창읍 모양성로 27063-564-2107-관광총괄과공개2015.11년
5758임실군옛날짜장박한순임실군 임실읍 춘향로 2933063-644-2929-관광총괄과공개2015.11년
5859임실군전주샹그릴라컨트리클럽최현범임실군 신덕면 수지로 559-90063-643-1000-관광총괄과공개2015.11년
5960전주시아웃백스테이크하우스<NA>전북 전주시 완산구 고사동 90-1063-285-0581<NA>관광총괄과공개2016.071년