Overview

Dataset statistics

Number of variables6
Number of observations178
Missing cells30
Missing cells (%)2.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.5 KiB
Average record size in memory48.7 B

Variable types

Categorical1
Text4
DateTime1

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
영업장 전화번호 has 18 (10.1%) missing valuesMissing
소재지 도로명 주소 has 2 (1.1%) missing valuesMissing
소재지 지번 주소 has 10 (5.6%) missing valuesMissing
업소명 has unique valuesUnique

Reproduction

Analysis started2024-01-09 20:28:30.628665
Analysis finished2024-01-09 20:28:31.201612
Duration0.57 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

Distinct3
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
일반음식점
133 
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 133
74.7%
집단급식소 37
 
20.8%
휴게음식점 8
 
4.5%

Length

2024-01-10T05:28:31.257541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:28:31.351708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반음식점 133
74.7%
집단급식소 37
 
20.8%
휴게음식점 8
 
4.5%

업소명
Text

UNIQUE 

Distinct178
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2024-01-10T05:28:31.542259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length18
Mean length7.1573034
Min length2

Characters and Unicode

Total characters1274
Distinct characters331
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

Unique178 ?
Unique (%)100.0%

Sample

1st row모카브레드
2nd row장가네 태양 한우곰탕
3rd row명작숯불갈비
4th row메이찬
5th row바다횟집
ValueCountFrequency (%)
㈜동원홈푸드(s&s 2
 
1.0%
충남보령dt점 2
 
1.0%
모카브레드 1
 
0.5%
명품국밥 1
 
0.5%
김가네24시해장국 1
 
0.5%
산에 1
 
0.5%
푸른바다회타운 1
 
0.5%
돌담길뜰안 1
 
0.5%
뜰안디저트카페 1
 
0.5%
쌍둥이쌈밥 1
 
0.5%
Other values (195) 195
94.2%
2024-01-10T05:28:31.871281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
29
 
2.3%
대 29
 
2.3%
교 27
 
2.1%
보 27
 
2.1%
학 25
 
2.0%
스 24
 
1.9%
령 24
 
1.9%
식 23
 
1.8%
이 22
 
1.7%
한 22
 
1.7%
Other values (321) 1022
80.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1138
89.3%
Space Separator 29
 
2.3%
Lowercase Letter 24
 
1.9%
Uppercase Letter 23
 
1.8%
Close Punctuation 20
 
1.6%
Open Punctuation 20
 
1.6%
Decimal Number 13
 
1.0%
Other Punctuation 5
 
0.4%
Other Symbol 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 29
 
2.5%
교 27
 
2.4%
보 27
 
2.4%
학 25
 
2.2%
스 24
 
2.1%
령 24
 
2.1%
식 23
 
2.0%
이 22
 
1.9%
한 22
 
1.9%
천 21
 
1.8%
Other values (285) 894
78.6%
Uppercase Letter
ValueCountFrequency (%)
S 4
17.4%
C 3
13.0%
T 3
13.0%
N 2
8.7%
D 2
8.7%
M 2
8.7%
G 2
8.7%
A 1
 
4.3%
L 1
 
4.3%
I 1
 
4.3%
Other values (2) 2
8.7%
Lowercase Letter
ValueCountFrequency (%)
i 5
20.8%
r 4
16.7%
e 3
12.5%
a 3
12.5%
s 3
12.5%
t 1
 
4.2%
o 1
 
4.2%
b 1
 
4.2%
l 1
 
4.2%
u 1
 
4.2%
Decimal Number
ValueCountFrequency (%)
0 3
23.1%
4 2
15.4%
2 2
15.4%
1 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 (%)
29
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1140
89.5%
Common 87
 
6.8%
Latin 47
 
3.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 29
 
2.5%
교 27
 
2.4%
보 27
 
2.4%
학 25
 
2.2%
스 24
 
2.1%
령 24
 
2.1%
식 23
 
2.0%
이 22
 
1.9%
한 22
 
1.9%
천 21
 
1.8%
Other values (286) 896
78.6%
Latin
ValueCountFrequency (%)
i 5
 
10.6%
S 4
 
8.5%
r 4
 
8.5%
e 3
 
6.4%
a 3
 
6.4%
s 3
 
6.4%
C 3
 
6.4%
T 3
 
6.4%
N 2
 
4.3%
D 2
 
4.3%
Other values (13) 15
31.9%
Common
ValueCountFrequency (%)
29
33.3%
) 20
23.0%
( 20
23.0%
& 3
 
3.4%
0 3
 
3.4%
4 2
 
2.3%
2 2
 
2.3%
1 2
 
2.3%
. 2
 
2.3%
8 2
 
2.3%
Other values (2) 2
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1138
89.3%
ASCII 134
 
10.5%
None 2
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
29
21.6%
) 20
14.9%
( 20
14.9%
i 5
 
3.7%
S 4
 
3.0%
r 4
 
3.0%
& 3
 
2.2%
e 3
 
2.2%
a 3
 
2.2%
s 3
 
2.2%
Other values (25) 40
29.9%
Hangul
ValueCountFrequency (%)
대 29
 
2.5%
교 27
 
2.4%
보 27
 
2.4%
학 25
 
2.2%
스 24
 
2.1%
령 24
 
2.1%
식 23
 
2.0%
이 22
 
1.9%
한 22
 
1.9%
천 21
 
1.8%
Other values (285) 894
78.6%
None
ValueCountFrequency (%)
㈜ 2
100.0%

영업장 전화번호
Text

MISSING 

Distinct154
Distinct (%)96.2%
Missing18
Missing (%)10.1%
Memory size1.5 KiB
2024-01-10T05:28:32.102184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.1125
Min length12

Characters and Unicode

Total characters1938
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

Unique150 ?
Unique (%)93.8%

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
 
2.5%
041-939-5532 2
 
1.2%
041-939-3630 2
 
1.2%
041-933-3323 2
 
1.2%
0507-1324-0843 1
 
0.6%
041-931-1356 1
 
0.6%
041-935-6800 1
 
0.6%
0507-1308-7864 1
 
0.6%
041-933-4288 1
 
0.6%
041-931-7890 1
 
0.6%
Other values (144) 144
90.0%
2024-01-10T05:28:32.453812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 320
16.5%
0 287
14.8%
1 281
14.5%
3 254
13.1%
4 234
12.1%
9 207
10.7%
2 83
 
4.3%
5 82
 
4.2%
8 71
 
3.7%
6 63
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1618
83.5%
Dash Punctuation 320
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 287
17.7%
1 281
17.4%
3 254
15.7%
4 234
14.5%
9 207
12.8%
2 83
 
5.1%
5 82
 
5.1%
8 71
 
4.4%
6 63
 
3.9%
7 56
 
3.5%
Dash Punctuation
ValueCountFrequency (%)
- 320
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1938
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 320
16.5%
0 287
14.8%
1 281
14.5%
3 254
13.1%
4 234
12.1%
9 207
10.7%
2 83
 
4.3%
5 82
 
4.2%
8 71
 
3.7%
6 63
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1938
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 320
16.5%
0 287
14.8%
1 281
14.5%
3 254
13.1%
4 234
12.1%
9 207
10.7%
2 83
 
4.3%
5 82
 
4.2%
8 71
 
3.7%
6 63
 
3.3%

소재지 도로명 주소
Text

MISSING 

Distinct168
Distinct (%)95.5%
Missing2
Missing (%)1.1%
Memory size1.5 KiB
2024-01-10T05:28:32.641567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length31
Mean length23.4375
Min length9

Characters and Unicode

Total characters4125
Distinct characters145
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

Unique162 ?
Unique (%)92.0%

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 175
19.3%
보령시 175
19.3%
신흑동 42
 
4.6%
동대동 31
 
3.4%
명천동 18
 
2.0%
대천동 17
 
1.9%
웅천읍 13
 
1.4%
2층 12
 
1.3%
대해로 10
 
1.1%
해수욕장4길 10
 
1.1%
Other values (226) 404
44.5%
2024-01-10T05:28:32.927019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
731
17.7%
남 197
 
4.8%
보 191
 
4.6%
령 189
 
4.6%
청 179
 
4.3%
충 178
 
4.3%
도 177
 
4.3%
시 175
 
4.2%
동 167
 
4.0%
) 137
 
3.3%
Other values (135) 1804
43.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2496
60.5%
Space Separator 731
 
17.7%
Decimal Number 553
 
13.4%
Close Punctuation 137
 
3.3%
Open Punctuation 137
 
3.3%
Dash Punctuation 31
 
0.8%
Other Punctuation 31
 
0.8%
Uppercase Letter 7
 
0.2%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 197
 
7.9%
보 191
 
7.7%
령 189
 
7.6%
청 179
 
7.2%
충 178
 
7.1%
도 177
 
7.1%
시 175
 
7.0%
동 167
 
6.7%
로 90
 
3.6%
길 88
 
3.5%
Other values (112) 865
34.7%
Decimal Number
ValueCountFrequency (%)
1 120
21.7%
2 71
12.8%
3 59
10.7%
8 57
10.3%
4 56
10.1%
0 43
 
7.8%
7 42
 
7.6%
6 40
 
7.2%
5 37
 
6.7%
9 28
 
5.1%
Uppercase Letter
ValueCountFrequency (%)
E 2
28.6%
C 1
14.3%
A 1
14.3%
L 1
14.3%
P 1
14.3%
R 1
14.3%
Math Symbol
ValueCountFrequency (%)
> 1
50.0%
< 1
50.0%
Space Separator
ValueCountFrequency (%)
731
100.0%
Close Punctuation
ValueCountFrequency (%)
) 137
100.0%
Open Punctuation
ValueCountFrequency (%)
( 137
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%
Other Punctuation
ValueCountFrequency (%)
, 31
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2496
60.5%
Common 1622
39.3%
Latin 7
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 197
 
7.9%
보 191
 
7.7%
령 189
 
7.6%
청 179
 
7.2%
충 178
 
7.1%
도 177
 
7.1%
시 175
 
7.0%
동 167
 
6.7%
로 90
 
3.6%
길 88
 
3.5%
Other values (112) 865
34.7%
Common
ValueCountFrequency (%)
731
45.1%
) 137
 
8.4%
( 137
 
8.4%
1 120
 
7.4%
2 71
 
4.4%
3 59
 
3.6%
8 57
 
3.5%
4 56
 
3.5%
0 43
 
2.7%
7 42
 
2.6%
Other values (7) 169
 
10.4%
Latin
ValueCountFrequency (%)
E 2
28.6%
C 1
14.3%
A 1
14.3%
L 1
14.3%
P 1
14.3%
R 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2496
60.5%
ASCII 1629
39.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
731
44.9%
) 137
 
8.4%
( 137
 
8.4%
1 120
 
7.4%
2 71
 
4.4%
3 59
 
3.6%
8 57
 
3.5%
4 56
 
3.4%
0 43
 
2.6%
7 42
 
2.6%
Other values (13) 176
 
10.8%
Hangul
ValueCountFrequency (%)
남 197
 
7.9%
보 191
 
7.7%
령 189
 
7.6%
청 179
 
7.2%
충 178
 
7.1%
도 177
 
7.1%
시 175
 
7.0%
동 167
 
6.7%
로 90
 
3.6%
길 88
 
3.5%
Other values (112) 865
34.7%

소재지 지번 주소
Text

MISSING 

Distinct160
Distinct (%)95.2%
Missing10
Missing (%)5.6%
Memory size1.5 KiB
2024-01-10T05:28:33.250270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length28
Mean length20.202381
Min length15

Characters and Unicode

Total characters3394
Distinct characters98
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

Unique154 ?
Unique (%)91.7%

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 168
23.1%
보령시 168
23.1%
신흑동 40
 
5.5%
동대동 30
 
4.1%
명천동 20
 
2.7%
대천동 16
 
2.2%
웅천읍 13
 
1.8%
궁촌동 7
 
1.0%
주교면 7
 
1.0%
남포면 6
 
0.8%
Other values (205) 253
34.8%
2024-01-10T05:28:33.668295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
728
21.4%
남 175
 
5.2%
보 171
 
5.0%
청 171
 
5.0%
령 170
 
5.0%
도 169
 
5.0%
시 169
 
5.0%
충 168
 
4.9%
동 162
 
4.8%
1 141
 
4.2%
Other values (88) 1170
34.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1851
54.5%
Space Separator 728
 
21.4%
Decimal Number 695
 
20.5%
Dash Punctuation 110
 
3.2%
Open Punctuation 3
 
0.1%
Close Punctuation 3
 
0.1%
Uppercase Letter 3
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 175
9.5%
보 171
9.2%
청 171
9.2%
령 170
9.2%
도 169
9.1%
시 169
9.1%
충 168
9.1%
동 162
8.8%
천 57
 
3.1%
대 49
 
2.6%
Other values (70) 390
21.1%
Decimal Number
ValueCountFrequency (%)
1 141
20.3%
2 95
13.7%
4 73
10.5%
3 65
9.4%
7 65
9.4%
8 60
8.6%
5 55
 
7.9%
0 52
 
7.5%
9 47
 
6.8%
6 42
 
6.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
33.3%
B 1
33.3%
L 1
33.3%
Space Separator
ValueCountFrequency (%)
728
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 110
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 1851
54.5%
Common 1540
45.4%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 175
9.5%
보 171
9.2%
청 171
9.2%
령 170
9.2%
도 169
9.1%
시 169
9.1%
충 168
9.1%
동 162
8.8%
천 57
 
3.1%
대 49
 
2.6%
Other values (70) 390
21.1%
Common
ValueCountFrequency (%)
728
47.3%
1 141
 
9.2%
- 110
 
7.1%
2 95
 
6.2%
4 73
 
4.7%
3 65
 
4.2%
7 65
 
4.2%
8 60
 
3.9%
5 55
 
3.6%
0 52
 
3.4%
Other values (5) 96
 
6.2%
Latin
ValueCountFrequency (%)
A 1
33.3%
B 1
33.3%
L 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1851
54.5%
ASCII 1543
45.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
728
47.2%
1 141
 
9.1%
- 110
 
7.1%
2 95
 
6.2%
4 73
 
4.7%
3 65
 
4.2%
7 65
 
4.2%
8 60
 
3.9%
5 55
 
3.6%
0 52
 
3.4%
Other values (8) 99
 
6.4%
Hangul
ValueCountFrequency (%)
남 175
9.5%
보 171
9.2%
청 171
9.2%
령 170
9.2%
도 169
9.1%
시 169
9.1%
충 168
9.1%
동 162
8.8%
천 57
 
3.1%
대 49
 
2.6%
Other values (70) 390
21.1%

데이터 기준일
Date

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
Minimum2021-11-16 00:00:00
Maximum2021-11-16 00:00:00
2024-01-10T05:28:33.768804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:28:33.849184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Missing values

2024-01-10T05:28:30.952960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T05:28:31.048119image/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.
2024-01-10T05:28:31.152143image/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

업종명업소명영업장 전화번호소재지 도로명 주소소재지 지번 주소데이터 기준일
0일반음식점모카브레드041-931-1356충청남도 보령시 해수욕장4길 84 (신흑동)충청남도 보령시 신흑동 19172021-11-16
1일반음식점장가네 태양 한우곰탕041-933-0099충청남도 보령시 청소면 충서로 4063충청남도 보령시 청소면 재정리 668-52021-11-16
2일반음식점명작숯불갈비041-934-1800충청남도 보령시 작은오랏5길 13 (동대동)충청남도 보령시 동대동 17652021-11-16
3일반음식점메이찬041-931-4211충청남도 보령시 큰오랏1길 60 (동대동)충청남도 보령시 동대동 13952021-11-16
4일반음식점바다횟집041-641-2372충청남도 보령시 천북면 학성염전길 94-26충청남도 보령시 천북면 학성리 2552021-11-16
5일반음식점홍성한우타운041-935-9360충청남도 보령시 대해로 420, 1,2층 (요암동)충청남도 보령시 요암동 76-4 1,2층2021-11-16
6일반음식점천지횟집041-933-8833충청남도 보령시 해수욕장4길 42 (신흑동)충청남도 보령시 신흑동 19272021-11-16
7일반음식점동우회센타041-931-2220충청남도 보령시 해수욕장4길 10 (신흑동)충청남도 보령시 신흑동 19802021-11-16
8일반음식점대해로횟집041-936-3394충청남도 보령시 웅천읍 열린바다로 334-15충청남도 보령시 웅천읍 관당리 818-162021-11-16
9일반음식점삼오정041-933-3131충청남도 보령시 신설2길 80 (동대동)충청남도 보령시 동대동 10512021-11-16
업종명업소명영업장 전화번호소재지 도로명 주소소재지 지번 주소데이터 기준일
168집단급식소웅천고등학교041-931-7463충청남도 보령시 웅천읍 방축길 87충청남도 보령시 웅천읍 대창리 449-12021-11-16
169집단급식소대천여자중학교급식실041-934-6177충청남도 보령시 옥갓티1길 31 (대천동)충청남도 보령시 대천동 453-12021-11-16
170집단급식소대천중학교041-934-2602충청남도 보령시 보령남로 23 (명천동)충청남도 보령시 명천동 430-42021-11-16
171집단급식소대천동대초등학교041-931-7932충청남도 보령시 한내로터리길 137-12 (동대동)충청남도 보령시 동대동 319-1182021-11-16
172집단급식소아주자동차대학041-939-3006충청남도 보령시 주포면 대학길 106충청남도 보령시 주포면 관산리 301-22021-11-16
173집단급식소명천초등학교041-931-7188충청남도 보령시 주공로 119 (명천동)충청남도 보령시 명천동 325-12021-11-16
174집단급식소미산초.중학교041-931-0163충청남도 보령시 미산면 판미로 1462-7충청남도 보령시 미산면 도화담리 942021-11-16
175집단급식소대명중학교041-932-3031충청남도 보령시 한내로 155 (명천동)충청남도 보령시 명천동 69-82021-11-16
176집단급식소보령중학교041-932-7008충청남도 보령시 주포면 보령읍성길 87-37충청남도 보령시 주포면 보령리 266-12021-11-16
177집단급식소한내여자중학교041-936-6992충청남도 보령시 옥마로 200 (동대동)충청남도 보령시 동대동 4-12021-11-16