Overview

Dataset statistics

Number of variables7
Number of observations175
Missing cells22
Missing cells (%)1.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.9 KiB
Average record size in memory57.8 B

Variable types

Numeric1
Categorical2
Text4

Dataset

Description보령시의 음식물 쓰레기 다량 배출 사업장에 대한 정보로 업종명, 업소명, 영업장 전화번호, 소재지 도로명 주소, 소재지 지번 주소, 데이터 기준일로 구성되어 있습니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=303&beforeMenuCd=DOM_000000201001001000&publicdatapk=15094776

Alerts

데이터 기준일 has constant value ""Constant
연번 is highly overall correlated with 업종명High correlation
업종명 is highly overall correlated with 연번High correlation
영업장 전화번호 has 10 (5.7%) missing valuesMissing
소재지 도로명 주소 has 2 (1.1%) missing valuesMissing
소재지 지번 주소 has 10 (5.7%) missing valuesMissing
연번 has unique valuesUnique
업소명 has unique valuesUnique

Reproduction

Analysis started2024-01-09 20:28:25.550213
Analysis finished2024-01-09 20:28:26.248500
Duration0.7 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct175
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean88
Minimum1
Maximum175
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-01-10T05:28:26.309042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile9.7
Q144.5
median88
Q3131.5
95-th percentile166.3
Maximum175
Range174
Interquartile range (IQR)87

Descriptive statistics

Standard deviation50.662281
Coefficient of variation (CV)0.57570773
Kurtosis-1.2
Mean88
Median Absolute Deviation (MAD)44
Skewness0
Sum15400
Variance2566.6667
MonotonicityStrictly increasing
2024-01-10T05:28:26.419131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.6%
2 1
 
0.6%
113 1
 
0.6%
114 1
 
0.6%
115 1
 
0.6%
116 1
 
0.6%
117 1
 
0.6%
118 1
 
0.6%
119 1
 
0.6%
120 1
 
0.6%
Other values (165) 165
94.3%
ValueCountFrequency (%)
1 1
0.6%
2 1
0.6%
3 1
0.6%
4 1
0.6%
5 1
0.6%
6 1
0.6%
7 1
0.6%
8 1
0.6%
9 1
0.6%
10 1
0.6%
ValueCountFrequency (%)
175 1
0.6%
174 1
0.6%
173 1
0.6%
172 1
0.6%
171 1
0.6%
170 1
0.6%
169 1
0.6%
168 1
0.6%
167 1
0.6%
166 1
0.6%

업종명
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
일반음식점
130 
집단급식소
37 
휴게음식점
 
8

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 130
74.3%
집단급식소 37
 
21.1%
휴게음식점 8
 
4.6%

Length

2024-01-10T05:28:26.530337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:28:26.615774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반음식점 130
74.3%
집단급식소 37
 
21.1%
휴게음식점 8
 
4.6%

업소명
Text

UNIQUE 

Distinct175
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2024-01-10T05:28:26.814712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length18
Mean length7.1142857
Min length2

Characters and Unicode

Total characters1245
Distinct characters327
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique175 ?
Unique (%)100.0%

Sample

1st row모카브레드
2nd row장가네 태양 한우곰탕
3rd row명작숯불갈비
4th row메이찬
5th row바다횟집
ValueCountFrequency (%)
충남보령dt점 2
 
1.0%
㈜동원홈푸드(s&s 2
 
1.0%
모카브레드 1
 
0.5%
대림정 1
 
0.5%
가마솥 1
 
0.5%
명품국밥 1
 
0.5%
김가네24시해장국 1
 
0.5%
산에 1
 
0.5%
푸른바다회타운 1
 
0.5%
돌담길뜰안 1
 
0.5%
Other values (190) 190
94.1%
2024-01-10T05:28:27.387629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
대 28
 
2.2%
27
 
2.2%
교 27
 
2.2%
보 26
 
2.1%
학 25
 
2.0%
령 23
 
1.8%
이 22
 
1.8%
스 22
 
1.8%
식 22
 
1.8%
한 21
 
1.7%
Other values (317) 1002
80.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1113
89.4%
Space Separator 27
 
2.2%
Lowercase Letter 24
 
1.9%
Uppercase Letter 23
 
1.8%
Open Punctuation 19
 
1.5%
Close Punctuation 19
 
1.5%
Decimal Number 13
 
1.0%
Other Punctuation 5
 
0.4%
Other Symbol 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 28
 
2.5%
교 27
 
2.4%
보 26
 
2.3%
학 25
 
2.2%
령 23
 
2.1%
이 22
 
2.0%
스 22
 
2.0%
식 22
 
2.0%
한 21
 
1.9%
천 20
 
1.8%
Other values (281) 877
78.8%
Uppercase Letter
ValueCountFrequency (%)
S 4
17.4%
C 3
13.0%
T 3
13.0%
N 2
8.7%
D 2
8.7%
G 2
8.7%
M 2
8.7%
L 1
 
4.3%
I 1
 
4.3%
H 1
 
4.3%
Other values (2) 2
8.7%
Lowercase Letter
ValueCountFrequency (%)
i 5
20.8%
r 4
16.7%
s 3
12.5%
e 3
12.5%
a 3
12.5%
o 1
 
4.2%
t 1
 
4.2%
f 1
 
4.2%
b 1
 
4.2%
l 1
 
4.2%
Decimal Number
ValueCountFrequency (%)
0 3
23.1%
1 2
15.4%
4 2
15.4%
2 2
15.4%
8 2
15.4%
3 1
 
7.7%
7 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
& 3
60.0%
. 2
40.0%
Space Separator
ValueCountFrequency (%)
27
100.0%
Open Punctuation
ValueCountFrequency (%)
( 19
100.0%
Close Punctuation
ValueCountFrequency (%)
) 19
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1115
89.6%
Common 83
 
6.7%
Latin 47
 
3.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 28
 
2.5%
교 27
 
2.4%
보 26
 
2.3%
학 25
 
2.2%
령 23
 
2.1%
이 22
 
2.0%
스 22
 
2.0%
식 22
 
2.0%
한 21
 
1.9%
천 20
 
1.8%
Other values (282) 879
78.8%
Latin
ValueCountFrequency (%)
i 5
 
10.6%
S 4
 
8.5%
r 4
 
8.5%
s 3
 
6.4%
e 3
 
6.4%
C 3
 
6.4%
T 3
 
6.4%
a 3
 
6.4%
N 2
 
4.3%
D 2
 
4.3%
Other values (13) 15
31.9%
Common
ValueCountFrequency (%)
27
32.5%
( 19
22.9%
) 19
22.9%
& 3
 
3.6%
0 3
 
3.6%
1 2
 
2.4%
4 2
 
2.4%
2 2
 
2.4%
. 2
 
2.4%
8 2
 
2.4%
Other values (2) 2
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1113
89.4%
ASCII 130
 
10.4%
None 2
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
대 28
 
2.5%
교 27
 
2.4%
보 26
 
2.3%
학 25
 
2.2%
령 23
 
2.1%
이 22
 
2.0%
스 22
 
2.0%
식 22
 
2.0%
한 21
 
1.9%
천 20
 
1.8%
Other values (281) 877
78.8%
ASCII
ValueCountFrequency (%)
27
20.8%
( 19
14.6%
) 19
14.6%
i 5
 
3.8%
S 4
 
3.1%
r 4
 
3.1%
s 3
 
2.3%
& 3
 
2.3%
e 3
 
2.3%
C 3
 
2.3%
Other values (25) 40
30.8%
None
ValueCountFrequency (%)
㈜ 2
100.0%

영업장 전화번호
Text

MISSING 

Distinct159
Distinct (%)96.4%
Missing10
Missing (%)5.7%
Memory size1.5 KiB
2024-01-10T05:28:27.620141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.115152
Min length12

Characters and Unicode

Total characters1999
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

Unique155 ?
Unique (%)93.9%

Sample

1st row041-931-1356
2nd row041-933-0099
3rd row041-934-1800
4th row041-931-4211
5th row041-641-2372
ValueCountFrequency (%)
041-931-5500 4
 
2.4%
041-933-3323 2
 
1.2%
041-939-5532 2
 
1.2%
041-939-3630 2
 
1.2%
041-935-6800 1
 
0.6%
041-933-9289 1
 
0.6%
041-932-4004 1
 
0.6%
041-935-7800 1
 
0.6%
0507-1308-7864 1
 
0.6%
041-933-4288 1
 
0.6%
Other values (149) 149
90.3%
2024-01-10T05:28:27.965623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 330
16.5%
0 295
14.8%
1 292
14.6%
3 262
13.1%
4 238
11.9%
9 212
10.6%
2 86
 
4.3%
5 84
 
4.2%
8 76
 
3.8%
6 64
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1669
83.5%
Dash Punctuation 330
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 295
17.7%
1 292
17.5%
3 262
15.7%
4 238
14.3%
9 212
12.7%
2 86
 
5.2%
5 84
 
5.0%
8 76
 
4.6%
6 64
 
3.8%
7 60
 
3.6%
Dash Punctuation
ValueCountFrequency (%)
- 330
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1999
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 330
16.5%
0 295
14.8%
1 292
14.6%
3 262
13.1%
4 238
11.9%
9 212
10.6%
2 86
 
4.3%
5 84
 
4.2%
8 76
 
3.8%
6 64
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1999
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 330
16.5%
0 295
14.8%
1 292
14.6%
3 262
13.1%
4 238
11.9%
9 212
10.6%
2 86
 
4.3%
5 84
 
4.2%
8 76
 
3.8%
6 64
 
3.2%

소재지 도로명 주소
Text

MISSING 

Distinct165
Distinct (%)95.4%
Missing2
Missing (%)1.1%
Memory size1.5 KiB
2024-01-10T05:28:28.291609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length31
Mean length23.549133
Min length18

Characters and Unicode

Total characters4074
Distinct characters137
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

Unique159 ?
Unique (%)91.9%

Sample

1st row충청남도 보령시 해수욕장4길 84 (신흑동)
2nd row충청남도 보령시 청소면 충서로 4063
3rd row충청남도 보령시 작은오랏5길 13 (동대동)
4th row충청남도 보령시 큰오랏1길 60 (동대동)
5th row충청남도 보령시 천북면 학성염전길 94-26
ValueCountFrequency (%)
충청남도 173
19.3%
보령시 173
19.3%
신흑동 42
 
4.7%
동대동 29
 
3.2%
명천동 18
 
2.0%
대천동 17
 
1.9%
웅천읍 13
 
1.5%
2층 12
 
1.3%
해수욕장4길 10
 
1.1%
대해로 10
 
1.1%
Other values (224) 399
44.5%
2024-01-10T05:28:28.742802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
723
17.7%
남 195
 
4.8%
보 189
 
4.6%
령 187
 
4.6%
청 177
 
4.3%
충 176
 
4.3%
도 175
 
4.3%
시 173
 
4.2%
동 163
 
4.0%
) 135
 
3.3%
Other values (127) 1781
43.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2470
60.6%
Space Separator 723
 
17.7%
Decimal Number 549
 
13.5%
Close Punctuation 135
 
3.3%
Open Punctuation 135
 
3.3%
Other Punctuation 31
 
0.8%
Dash Punctuation 31
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 195
 
7.9%
보 189
 
7.7%
령 187
 
7.6%
청 177
 
7.2%
충 176
 
7.1%
도 175
 
7.1%
시 173
 
7.0%
동 163
 
6.6%
로 89
 
3.6%
길 87
 
3.5%
Other values (112) 859
34.8%
Decimal Number
ValueCountFrequency (%)
1 120
21.9%
2 70
12.8%
3 59
10.7%
8 57
10.4%
4 56
10.2%
0 43
 
7.8%
7 42
 
7.7%
6 39
 
7.1%
5 36
 
6.6%
9 27
 
4.9%
Space Separator
ValueCountFrequency (%)
723
100.0%
Close Punctuation
ValueCountFrequency (%)
) 135
100.0%
Open Punctuation
ValueCountFrequency (%)
( 135
100.0%
Other Punctuation
ValueCountFrequency (%)
, 31
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2470
60.6%
Common 1604
39.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 195
 
7.9%
보 189
 
7.7%
령 187
 
7.6%
청 177
 
7.2%
충 176
 
7.1%
도 175
 
7.1%
시 173
 
7.0%
동 163
 
6.6%
로 89
 
3.6%
길 87
 
3.5%
Other values (112) 859
34.8%
Common
ValueCountFrequency (%)
723
45.1%
) 135
 
8.4%
( 135
 
8.4%
1 120
 
7.5%
2 70
 
4.4%
3 59
 
3.7%
8 57
 
3.6%
4 56
 
3.5%
0 43
 
2.7%
7 42
 
2.6%
Other values (5) 164
 
10.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2470
60.6%
ASCII 1604
39.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
723
45.1%
) 135
 
8.4%
( 135
 
8.4%
1 120
 
7.5%
2 70
 
4.4%
3 59
 
3.7%
8 57
 
3.6%
4 56
 
3.5%
0 43
 
2.7%
7 42
 
2.6%
Other values (5) 164
 
10.2%
Hangul
ValueCountFrequency (%)
남 195
 
7.9%
보 189
 
7.7%
령 187
 
7.6%
청 177
 
7.2%
충 176
 
7.1%
도 175
 
7.1%
시 173
 
7.0%
동 163
 
6.6%
로 89
 
3.6%
길 87
 
3.5%
Other values (112) 859
34.8%

소재지 지번 주소
Text

MISSING 

Distinct157
Distinct (%)95.2%
Missing10
Missing (%)5.7%
Memory size1.5 KiB
2024-01-10T05:28:29.075997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length27
Mean length20.121212
Min length15

Characters and Unicode

Total characters3320
Distinct characters87
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

Unique151 ?
Unique (%)91.5%

Sample

1st row충청남도 보령시 신흑동 1917
2nd row충청남도 보령시 청소면 재정리 668-5
3rd row충청남도 보령시 동대동 1765
4th row충청남도 보령시 동대동 1395
5th row충청남도 보령시 천북면 학성리 255
ValueCountFrequency (%)
충청남도 165
23.2%
보령시 165
23.2%
신흑동 40
 
5.6%
동대동 28
 
3.9%
명천동 19
 
2.7%
대천동 16
 
2.2%
웅천읍 13
 
1.8%
주교면 7
 
1.0%
궁촌동 7
 
1.0%
내항동 6
 
0.8%
Other values (198) 246
34.6%
2024-01-10T05:28:29.556075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
712
21.4%
남 172
 
5.2%
청 168
 
5.1%
보 167
 
5.0%
도 166
 
5.0%
령 166
 
5.0%
시 166
 
5.0%
충 165
 
5.0%
동 157
 
4.7%
1 137
 
4.1%
Other values (77) 1144
34.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1805
54.4%
Space Separator 712
 
21.4%
Decimal Number 687
 
20.7%
Dash Punctuation 109
 
3.3%
Open Punctuation 3
 
0.1%
Close Punctuation 3
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 172
9.5%
청 168
9.3%
보 167
9.3%
도 166
9.2%
령 166
9.2%
시 166
9.2%
충 165
9.1%
동 157
8.7%
천 55
 
3.0%
대 47
 
2.6%
Other values (62) 376
20.8%
Decimal Number
ValueCountFrequency (%)
1 137
19.9%
2 95
13.8%
4 72
10.5%
7 64
9.3%
3 64
9.3%
8 60
8.7%
5 55
8.0%
0 52
 
7.6%
9 47
 
6.8%
6 41
 
6.0%
Space Separator
ValueCountFrequency (%)
712
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 109
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1805
54.4%
Common 1515
45.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 172
9.5%
청 168
9.3%
보 167
9.3%
도 166
9.2%
령 166
9.2%
시 166
9.2%
충 165
9.1%
동 157
8.7%
천 55
 
3.0%
대 47
 
2.6%
Other values (62) 376
20.8%
Common
ValueCountFrequency (%)
712
47.0%
1 137
 
9.0%
- 109
 
7.2%
2 95
 
6.3%
4 72
 
4.8%
7 64
 
4.2%
3 64
 
4.2%
8 60
 
4.0%
5 55
 
3.6%
0 52
 
3.4%
Other values (5) 95
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1805
54.4%
ASCII 1515
45.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
712
47.0%
1 137
 
9.0%
- 109
 
7.2%
2 95
 
6.3%
4 72
 
4.8%
7 64
 
4.2%
3 64
 
4.2%
8 60
 
4.0%
5 55
 
3.6%
0 52
 
3.4%
Other values (5) 95
 
6.3%
Hangul
ValueCountFrequency (%)
남 172
9.5%
청 168
9.3%
보 167
9.3%
도 166
9.2%
령 166
9.2%
시 166
9.2%
충 165
9.1%
동 157
8.7%
천 55
 
3.0%
대 47
 
2.6%
Other values (62) 376
20.8%

데이터 기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-11-17
175 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-11-17
2nd row2023-11-17
3rd row2023-11-17
4th row2023-11-17
5th row2023-11-17

Common Values

ValueCountFrequency (%)
2023-11-17 175
100.0%

Length

2024-01-10T05:28:29.692688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:28:29.789193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-11-17 175
100.0%

Interactions

2024-01-10T05:28:25.913803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T05:28:29.841189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종명
연번1.0000.878
업종명0.8781.000
2024-01-10T05:28:29.915352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종명
연번1.0000.798
업종명0.7981.000

Missing values

2024-01-10T05:28:26.020416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T05:28:26.112510image/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.
2024-01-10T05:28:26.201057image/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

연번업종명업소명영업장 전화번호소재지 도로명 주소소재지 지번 주소데이터 기준일
01일반음식점모카브레드041-931-1356충청남도 보령시 해수욕장4길 84 (신흑동)충청남도 보령시 신흑동 19172023-11-17
12일반음식점장가네 태양 한우곰탕041-933-0099충청남도 보령시 청소면 충서로 4063충청남도 보령시 청소면 재정리 668-52023-11-17
23일반음식점명작숯불갈비041-934-1800충청남도 보령시 작은오랏5길 13 (동대동)충청남도 보령시 동대동 17652023-11-17
34일반음식점메이찬041-931-4211충청남도 보령시 큰오랏1길 60 (동대동)충청남도 보령시 동대동 13952023-11-17
45일반음식점바다횟집041-641-2372충청남도 보령시 천북면 학성염전길 94-26충청남도 보령시 천북면 학성리 2552023-11-17
56일반음식점홍성한우타운041-935-9360충청남도 보령시 대해로 420, 1,2층 (요암동)충청남도 보령시 요암동 76-4 1,2층2023-11-17
67일반음식점천지횟집041-933-8833충청남도 보령시 해수욕장4길 42 (신흑동)충청남도 보령시 신흑동 19272023-11-17
78일반음식점동우회센타041-931-2220충청남도 보령시 해수욕장4길 10 (신흑동)충청남도 보령시 신흑동 19802023-11-17
89일반음식점대해로횟집041-936-3394충청남도 보령시 웅천읍 열린바다로 334-15충청남도 보령시 웅천읍 관당리 818-162023-11-17
910일반음식점삼오정041-933-3131충청남도 보령시 신설2길 80 (동대동)충청남도 보령시 동대동 10512023-11-17
연번업종명업소명영업장 전화번호소재지 도로명 주소소재지 지번 주소데이터 기준일
165166집단급식소웅천고등학교041-931-7463충청남도 보령시 웅천읍 방축길 87충청남도 보령시 웅천읍 대창리 449-12023-11-17
166167집단급식소대천여자중학교급식실041-934-6177충청남도 보령시 옥갓티1길 31 (대천동)충청남도 보령시 대천동 453-12023-11-17
167168집단급식소대천중학교041-934-2602충청남도 보령시 보령남로 23 (명천동)충청남도 보령시 명천동 430-42023-11-17
168169집단급식소대천동대초등학교041-931-7932충청남도 보령시 한내로터리길 137-12 (동대동)충청남도 보령시 동대동 319-1182023-11-17
169170집단급식소아주자동차대학041-939-3006충청남도 보령시 주포면 대학길 106충청남도 보령시 주포면 관산리 301-22023-11-17
170171집단급식소명천초등학교041-931-7188충청남도 보령시 주공로 119 (명천동)충청남도 보령시 명천동 325-12023-11-17
171172집단급식소미산초.중학교041-931-0163충청남도 보령시 미산면 판미로 1462-7충청남도 보령시 미산면 도화담리 942023-11-17
172173집단급식소대명중학교041-932-3031충청남도 보령시 한내로 155 (명천동)충청남도 보령시 명천동 69-82023-11-17
173174집단급식소보령중학교041-932-7008충청남도 보령시 주포면 보령읍성길 87-37충청남도 보령시 주포면 보령리 266-12023-11-17
174175집단급식소한내여자중학교041-936-6992충청남도 보령시 옥마로 200 (동대동)충청남도 보령시 동대동 4-12023-11-17