Overview

Dataset statistics

Number of variables7
Number of observations2514
Missing cells588
Missing cells (%)3.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory140.1 KiB
Average record size in memory57.1 B

Variable types

Categorical2
Text3
Numeric1
DateTime1

Dataset

Description서산시에서 인허가된 일반음식점, 휴게음식점 현황에 대한 데이터입니다. 업종명, 업소명, 소재지, 영업장면적, 전화번호, 업태명, 데이터기준일의 항목명을 가지고 있습니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=447&beforeMenuCd=DOM_000000201001001000&publicdatapk=15000815

Alerts

업종명 has constant value ""Constant
데이터기준일 has constant value ""Constant
소재지전화 has 587 (23.3%) missing valuesMissing
영업장면적 has 121 (4.8%) zerosZeros

Reproduction

Analysis started2024-01-09 21:07:05.009184
Analysis finished2024-01-09 21:07:06.306460
Duration1.3 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size19.8 KiB
일반음식점
2514 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반음식점 2514
100.0%

Length

2024-01-10T06:07:06.363025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:07:06.443715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반음식점 2514
100.0%

업소명
Text

Distinct2457
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size19.8 KiB
2024-01-10T06:07:06.654458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length19
Mean length5.5310263
Min length1

Characters and Unicode

Total characters13905
Distinct characters705
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2409 ?
Unique (%)95.8%

Sample

1st row행복한쌈밥
2nd row송남회관
3rd row영성각
4th row버드내식당
5th row태광식당
ValueCountFrequency (%)
서산점 33
 
1.1%
호수공원점 19
 
0.7%
대산점 11
 
0.4%
서산호수공원점 10
 
0.3%
예천점 8
 
0.3%
동문점 8
 
0.3%
칼국수 7
 
0.2%
읍내점 6
 
0.2%
대성식당 5
 
0.2%
치킨 5
 
0.2%
Other values (2602) 2785
96.1%
2024-01-10T06:07:07.064903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 390
 
2.8%
383
 
2.8%
점 354
 
2.5%
당 322
 
2.3%
산 282
 
2.0%
이 257
 
1.8%
서 222
 
1.6%
리 210
 
1.5%
대 206
 
1.5%
가 202
 
1.5%
Other values (695) 11077
79.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13133
94.4%
Space Separator 383
 
2.8%
Close Punctuation 140
 
1.0%
Open Punctuation 140
 
1.0%
Decimal Number 70
 
0.5%
Other Punctuation 25
 
0.2%
Uppercase Letter 12
 
0.1%
Lowercase Letter 1
 
< 0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 390
 
3.0%
점 354
 
2.7%
당 322
 
2.5%
산 282
 
2.1%
이 257
 
2.0%
서 222
 
1.7%
리 210
 
1.6%
대 206
 
1.6%
가 202
 
1.5%
수 192
 
1.5%
Other values (668) 10496
79.9%
Decimal Number
ValueCountFrequency (%)
2 22
31.4%
1 13
18.6%
0 8
 
11.4%
4 7
 
10.0%
5 5
 
7.1%
7 4
 
5.7%
8 3
 
4.3%
9 3
 
4.3%
3 3
 
4.3%
6 2
 
2.9%
Other Punctuation
ValueCountFrequency (%)
. 13
52.0%
· 4
 
16.0%
& 4
 
16.0%
, 2
 
8.0%
' 1
 
4.0%
＆ 1
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
C 3
25.0%
H 3
25.0%
B 3
25.0%
K 1
 
8.3%
M 1
 
8.3%
W 1
 
8.3%
Space Separator
ValueCountFrequency (%)
383
100.0%
Close Punctuation
ValueCountFrequency (%)
) 140
100.0%
Open Punctuation
ValueCountFrequency (%)
( 140
100.0%
Lowercase Letter
ValueCountFrequency (%)
s 1
100.0%
Other Symbol
ValueCountFrequency (%)
○ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13131
94.4%
Common 759
 
5.5%
Latin 13
 
0.1%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 390
 
3.0%
점 354
 
2.7%
당 322
 
2.5%
산 282
 
2.1%
이 257
 
2.0%
서 222
 
1.7%
리 210
 
1.6%
대 206
 
1.6%
가 202
 
1.5%
수 192
 
1.5%
Other values (666) 10494
79.9%
Common
ValueCountFrequency (%)
383
50.5%
) 140
 
18.4%
( 140
 
18.4%
2 22
 
2.9%
1 13
 
1.7%
. 13
 
1.7%
0 8
 
1.1%
4 7
 
0.9%
5 5
 
0.7%
7 4
 
0.5%
Other values (10) 24
 
3.2%
Latin
ValueCountFrequency (%)
C 3
23.1%
H 3
23.1%
B 3
23.1%
s 1
 
7.7%
K 1
 
7.7%
M 1
 
7.7%
W 1
 
7.7%
Han
ValueCountFrequency (%)
足 1
50.0%
心 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13131
94.4%
ASCII 766
 
5.5%
None 5
 
< 0.1%
CJK 2
 
< 0.1%
Geometric Shapes 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 390
 
3.0%
점 354
 
2.7%
당 322
 
2.5%
산 282
 
2.1%
이 257
 
2.0%
서 222
 
1.7%
리 210
 
1.6%
대 206
 
1.6%
가 202
 
1.5%
수 192
 
1.5%
Other values (666) 10494
79.9%
ASCII
ValueCountFrequency (%)
383
50.0%
) 140
 
18.3%
( 140
 
18.3%
2 22
 
2.9%
1 13
 
1.7%
. 13
 
1.7%
0 8
 
1.0%
4 7
 
0.9%
5 5
 
0.7%
7 4
 
0.5%
Other values (14) 31
 
4.0%
None
ValueCountFrequency (%)
· 4
80.0%
＆ 1
 
20.0%
CJK
ValueCountFrequency (%)
足 1
50.0%
心 1
50.0%
Geometric Shapes
ValueCountFrequency (%)
○ 1
100.0%

소재지(도로명)
Text

Distinct2224
Distinct (%)88.5%
Missing1
Missing (%)< 0.1%
Memory size19.8 KiB
2024-01-10T06:07:07.314303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length51
Mean length26.057302
Min length18

Characters and Unicode

Total characters65482
Distinct characters266
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2003 ?
Unique (%)79.7%

Sample

1st row충청남도 서산시 번화1로 15 (읍내동)
2nd row충청남도 서산시 음암면 도당큰말길 6-4
3rd row충청남도 서산시 해미면 남문1로 40-1
4th row충청남도 서산시 운산면 해운로 1205-1
5th row충청남도 서산시 해미면 읍성마을4길 17-8
ValueCountFrequency (%)
충청남도 2513
 
17.5%
서산시 2513
 
17.5%
1층 948
 
6.6%
동문동 475
 
3.3%
읍내동 385
 
2.7%
대산읍 362
 
2.5%
해미면 224
 
1.6%
예천동 166
 
1.2%
2층 119
 
0.8%
석림동 119
 
0.8%
Other values (1591) 6513
45.4%
2024-01-10T06:07:07.709909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12077
18.4%
1 3532
 
5.4%
산 3063
 
4.7%
남 2684
 
4.1%
서 2670
 
4.1%
시 2656
 
4.1%
충 2613
 
4.0%
도 2566
 
3.9%
청 2515
 
3.8%
동 2364
 
3.6%
Other values (256) 28742
43.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 37006
56.5%
Space Separator 12077
 
18.4%
Decimal Number 10501
 
16.0%
Close Punctuation 1835
 
2.8%
Open Punctuation 1835
 
2.8%
Other Punctuation 1521
 
2.3%
Dash Punctuation 632
 
1.0%
Uppercase Letter 61
 
0.1%
Math Symbol 12
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 3063
 
8.3%
남 2684
 
7.3%
서 2670
 
7.2%
시 2656
 
7.2%
충 2613
 
7.1%
도 2566
 
6.9%
청 2515
 
6.8%
동 2364
 
6.4%
로 1943
 
5.3%
층 1295
 
3.5%
Other values (227) 12637
34.1%
Decimal Number
ValueCountFrequency (%)
1 3532
33.6%
2 1527
14.5%
3 1083
 
10.3%
4 819
 
7.8%
5 726
 
6.9%
6 646
 
6.2%
7 585
 
5.6%
9 538
 
5.1%
0 523
 
5.0%
8 522
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
D 21
34.4%
B 15
24.6%
A 13
21.3%
C 7
 
11.5%
F 1
 
1.6%
K 1
 
1.6%
J 1
 
1.6%
P 1
 
1.6%
T 1
 
1.6%
Other Punctuation
ValueCountFrequency (%)
, 1485
97.6%
@ 26
 
1.7%
/ 8
 
0.5%
. 2
 
0.1%
Space Separator
ValueCountFrequency (%)
12077
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1835
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1835
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 632
100.0%
Math Symbol
ValueCountFrequency (%)
~ 12
100.0%
Lowercase Letter
ValueCountFrequency (%)
c 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 37006
56.5%
Common 28413
43.4%
Latin 63
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 3063
 
8.3%
남 2684
 
7.3%
서 2670
 
7.2%
시 2656
 
7.2%
충 2613
 
7.1%
도 2566
 
6.9%
청 2515
 
6.8%
동 2364
 
6.4%
로 1943
 
5.3%
층 1295
 
3.5%
Other values (227) 12637
34.1%
Common
ValueCountFrequency (%)
12077
42.5%
1 3532
 
12.4%
) 1835
 
6.5%
( 1835
 
6.5%
2 1527
 
5.4%
, 1485
 
5.2%
3 1083
 
3.8%
4 819
 
2.9%
5 726
 
2.6%
6 646
 
2.3%
Other values (9) 2848
 
10.0%
Latin
ValueCountFrequency (%)
D 21
33.3%
B 15
23.8%
A 13
20.6%
C 7
 
11.1%
c 2
 
3.2%
F 1
 
1.6%
K 1
 
1.6%
J 1
 
1.6%
P 1
 
1.6%
T 1
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 37005
56.5%
ASCII 28476
43.5%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12077
42.4%
1 3532
 
12.4%
) 1835
 
6.4%
( 1835
 
6.4%
2 1527
 
5.4%
, 1485
 
5.2%
3 1083
 
3.8%
4 819
 
2.9%
5 726
 
2.5%
6 646
 
2.3%
Other values (19) 2911
 
10.2%
Hangul
ValueCountFrequency (%)
산 3063
 
8.3%
남 2684
 
7.3%
서 2670
 
7.2%
시 2656
 
7.2%
충 2613
 
7.1%
도 2566
 
6.9%
청 2515
 
6.8%
동 2364
 
6.4%
로 1943
 
5.3%
층 1295
 
3.5%
Other values (226) 12636
34.1%
Compat Jamo
ValueCountFrequency (%)
ㅣ 1
100.0%

영업장면적
Real number (ℝ)

ZEROS 

Distinct1970
Distinct (%)78.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean97.422259
Minimum0
Maximum3149.1
Zeros121
Zeros (%)4.8%
Negative0
Negative (%)0.0%
Memory size22.2 KiB
2024-01-10T06:07:07.845974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile8.065
Q137.5
median67.72
Q3121.615
95-th percentile246.984
Maximum3149.1
Range3149.1
Interquartile range (IQR)84.115

Descriptive statistics

Standard deviation142.06661
Coefficient of variation (CV)1.4582561
Kurtosis222.63264
Mean97.422259
Median Absolute Deviation (MAD)35.32
Skewness12.217205
Sum244919.56
Variance20182.921
MonotonicityNot monotonic
2024-01-10T06:07:07.981917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 121
 
4.8%
33.0 9
 
0.4%
30.0 9
 
0.4%
39.6 9
 
0.4%
36.0 8
 
0.3%
60.0 7
 
0.3%
34.0 7
 
0.3%
66.0 7
 
0.3%
132.0 6
 
0.2%
42.12 6
 
0.2%
Other values (1960) 2325
92.5%
ValueCountFrequency (%)
0.0 121
4.8%
6.8 1
 
< 0.1%
7.5 2
 
0.1%
7.9 1
 
< 0.1%
8.0 1
 
< 0.1%
8.1 1
 
< 0.1%
9.72 1
 
< 0.1%
9.9 1
 
< 0.1%
10.26 1
 
< 0.1%
10.5 1
 
< 0.1%
ValueCountFrequency (%)
3149.1 2
0.1%
2291.42 1
< 0.1%
2238.19 1
< 0.1%
1856.19 1
< 0.1%
1083.25 1
< 0.1%
856.46 1
< 0.1%
801.14 1
< 0.1%
769.15 1
< 0.1%
763.92 1
< 0.1%
739.27 1
< 0.1%

소재지전화
Text

MISSING 

Distinct1869
Distinct (%)97.0%
Missing587
Missing (%)23.3%
Memory size19.8 KiB
2024-01-10T06:07:08.217255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.966269
Min length2

Characters and Unicode

Total characters23059
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

Unique1817 ?
Unique (%)94.3%

Sample

1st row041-663-6019
2nd row041-660-4071
3rd row041-688-0468
4th row041-663-3643
5th row041-665-3271
ValueCountFrequency (%)
7
 
0.4%
041-665-8844 3
 
0.2%
041-666-8400 2
 
0.1%
041-667-8488 2
 
0.1%
041-667-4545 2
 
0.1%
041-667-1959 2
 
0.1%
041-663-7490 2
 
0.1%
041-664-5557 2
 
0.1%
041-681-8892 2
 
0.1%
041-668-3392 2
 
0.1%
Other values (1859) 1901
98.7%
2024-01-10T06:07:08.581038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 4299
18.6%
- 3853
16.7%
1 2850
12.4%
0 2800
12.1%
4 2797
12.1%
8 1479
 
6.4%
2 1058
 
4.6%
5 1014
 
4.4%
7 990
 
4.3%
9 980
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 19206
83.3%
Dash Punctuation 3853
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 4299
22.4%
1 2850
14.8%
0 2800
14.6%
4 2797
14.6%
8 1479
 
7.7%
2 1058
 
5.5%
5 1014
 
5.3%
7 990
 
5.2%
9 980
 
5.1%
3 939
 
4.9%
Dash Punctuation
ValueCountFrequency (%)
- 3853
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 23059
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 4299
18.6%
- 3853
16.7%
1 2850
12.4%
0 2800
12.1%
4 2797
12.1%
8 1479
 
6.4%
2 1058
 
4.6%
5 1014
 
4.4%
7 990
 
4.3%
9 980
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23059
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 4299
18.6%
- 3853
16.7%
1 2850
12.4%
0 2800
12.1%
4 2797
12.1%
8 1479
 
6.4%
2 1058
 
4.6%
5 1014
 
4.4%
7 990
 
4.3%
9 980
 
4.2%

업태명
Categorical

Distinct18
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size19.8 KiB
한식
1172 
호프/통닭
329 
식육(숯불구이)
291 
분식
186 
패스트푸드
 
95
Other values (13)
441 

Length

Max length10
Median length2
Mean length3.4928401
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row한식
2nd row식육(숯불구이)
3rd row중국식
4th row식육(숯불구이)
5th row한식

Common Values

ValueCountFrequency (%)
한식 1172
46.6%
호프/통닭 329
 
13.1%
식육(숯불구이) 291
 
11.6%
분식 186
 
7.4%
패스트푸드 95
 
3.8%
기타 91
 
3.6%
통닭(치킨) 77
 
3.1%
중국식 71
 
2.8%
경양식 52
 
2.1%
일식 46
 
1.8%
Other values (8) 104
 
4.1%

Length

2024-01-10T06:07:08.739053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 1172
46.6%
호프/통닭 329
 
13.1%
식육(숯불구이 291
 
11.6%
분식 186
 
7.4%
패스트푸드 95
 
3.8%
기타 91
 
3.6%
통닭(치킨 77
 
3.1%
중국식 71
 
2.8%
경양식 52
 
2.1%
일식 46
 
1.8%
Other values (8) 104
 
4.1%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size19.8 KiB
Minimum2016-05-16 00:00:00
Maximum2016-05-16 00:00:00
2024-01-10T06:07:08.846289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:07:08.936532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-01-10T06:07:05.548031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T06:07:09.006506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
영업장면적업태명
영업장면적1.0000.408
업태명0.4081.000
2024-01-10T06:07:09.109001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
영업장면적업태명
영업장면적1.0000.195
업태명0.1951.000

Missing values

2024-01-10T06:07:05.654206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T06:07:06.138179image/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.
2024-01-10T06:07:06.261801image/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

업종명업소명소재지(도로명)영업장면적소재지전화업태명데이터기준일
0일반음식점행복한쌈밥충청남도 서산시 번화1로 15 (읍내동)0.0<NA>한식2016-05-16
1일반음식점송남회관충청남도 서산시 음암면 도당큰말길 6-40.0041-663-6019식육(숯불구이)2016-05-16
2일반음식점영성각충청남도 서산시 해미면 남문1로 40-1126.6<NA>중국식2016-05-16
3일반음식점버드내식당충청남도 서산시 운산면 해운로 1205-10.0041-660-4071식육(숯불구이)2016-05-16
4일반음식점태광식당충청남도 서산시 해미면 읍성마을4길 17-80.0041-688-0468한식2016-05-16
5일반음식점서산식당충청남도 서산시 운산면 용장리 406번지0.0041-663-3643식육(숯불구이)2016-05-16
6일반음식점현대한우촌충청남도 서산시 율지17로 21 (동문동)288.02041-665-3271식육(숯불구이)2016-05-16
7일반음식점부자집충청남도 서산시 안견로 181 (동문동)0.0<NA>한식2016-05-16
8일반음식점팔봉반점충청남도 서산시 읍내동 148번지0.0041-664-0521중국식2016-05-16
9일반음식점인지반점충청남도 서산시 인지면 무학로 16930.0041-667-7373중국식2016-05-16
업종명업소명소재지(도로명)영업장면적소재지전화업태명데이터기준일
2504일반음식점전주명가콩나물국밥 (호수공원점)충청남도 서산시 호수공원2로 27, 1층 (읍내동)205.4041-663-3275한식2016-05-16
2505일반음식점도성리산마루충청남도 서산시 지곡면 도성로 259, 1층97.02<NA>한식2016-05-16
2506일반음식점한식부페식객충청남도 서산시 지곡면 무장산업로 147-46, 1층201.89<NA>뷔페식2016-05-16
2507일반음식점마시짱충청남도 서산시 중앙로 94, 1층 (동문동, 하트리움)48.02041-666-2066분식2016-05-16
2508일반음식점김추일수제돈까스충청남도 서산시 해미면 해운로 17, 1층107.31041-688-8879경양식2016-05-16
2509일반음식점권가국수충청남도 서산시 율지6로 30, 1층 6-1호 (동문동)40.32<NA>분식2016-05-16
2510일반음식점나능이 대산점충청남도 서산시 대산읍 구진로 40-9, 2층142.02<NA>한식2016-05-16
2511일반음식점박가네마포숯불갈비충청남도 서산시 대산읍 삼길포1로 23, 1층131.4<NA>식육(숯불구이)2016-05-16
2512일반음식점대곡리식당충청남도 서산시 해미면 한티로 336, 1층70.35<NA>한식2016-05-16
2513일반음식점아이러브친킨호프충청남도 서산시 한마음16로 30, 1층 (석림동)61.72<NA>호프/통닭2016-05-16