Overview

Dataset statistics

Number of variables9
Number of observations210
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.1 KiB
Average record size in memory73.6 B

Variable types

Numeric1
Text4
Categorical1
DateTime3

Dataset

Description인천광역시 남동구 식품안전인증업소인 HACCP 인증업소 현황에 대한 데이터로 연번, 업체명, 적용업종, 적용품목, 주소, 인증번호, 최초인증일, 인증종료일, 데이터기준일 항목을 제공합니다.
Author인천광역시 남동구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15075401&srcSe=7661IVAWM27C61E190

Alerts

적용업종 has constant value ""Constant
데이터기준일 has constant value ""Constant
연번 has unique valuesUnique
인증번호 has unique valuesUnique

Reproduction

Analysis started2024-01-28 13:37:40.900469
Analysis finished2024-01-28 13:37:41.520948
Duration0.62 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct210
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean105.5
Minimum1
Maximum210
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-01-28T22:37:41.590788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile11.45
Q153.25
median105.5
Q3157.75
95-th percentile199.55
Maximum210
Range209
Interquartile range (IQR)104.5

Descriptive statistics

Standard deviation60.765944
Coefficient of variation (CV)0.57598052
Kurtosis-1.2
Mean105.5
Median Absolute Deviation (MAD)52.5
Skewness0
Sum22155
Variance3692.5
MonotonicityStrictly increasing
2024-01-28T22:37:42.021999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
159 1
 
0.5%
135 1
 
0.5%
136 1
 
0.5%
137 1
 
0.5%
138 1
 
0.5%
139 1
 
0.5%
140 1
 
0.5%
141 1
 
0.5%
142 1
 
0.5%
Other values (200) 200
95.2%
ValueCountFrequency (%)
1 1
0.5%
2 1
0.5%
3 1
0.5%
4 1
0.5%
5 1
0.5%
6 1
0.5%
7 1
0.5%
8 1
0.5%
9 1
0.5%
10 1
0.5%
ValueCountFrequency (%)
210 1
0.5%
209 1
0.5%
208 1
0.5%
207 1
0.5%
206 1
0.5%
205 1
0.5%
204 1
0.5%
203 1
0.5%
202 1
0.5%
201 1
0.5%

업체명
Text

Distinct101
Distinct (%)48.1%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-01-28T22:37:42.229563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length13
Mean length7.7857143
Min length3

Characters and Unicode

Total characters1635
Distinct characters198
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

Unique39 ?
Unique (%)18.6%

Sample

1st row주식회사 마띠아 남촌지점
2nd row농업회사법인 수복주식회사
3rd row농업회사법인 수복주식회사
4th row주식회사 마담티라미수
5th row고성푸드
ValueCountFrequency (%)
주식회사 50
 
18.1%
채움바이오 6
 
2.2%
더다이닝 6
 
2.2%
베지스타 6
 
2.2%
농업회사법인 5
 
1.8%
수복주식회사 5
 
1.8%
주)새롬식품 5
 
1.8%
제이에스바이오 5
 
1.8%
주식회사이호푸드 5
 
1.8%
생생찬 4
 
1.4%
Other values (100) 179
64.9%
2024-01-28T22:37:42.559071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 124
 
7.6%
식 105
 
6.4%
사 85
 
5.2%
회 84
 
5.1%
66
 
4.0%
이 58
 
3.5%
( 52
 
3.2%
드 52
 
3.2%
) 52
 
3.2%
푸 48
 
2.9%
Other values (188) 909
55.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1384
84.6%
Space Separator 66
 
4.0%
Open Punctuation 56
 
3.4%
Close Punctuation 56
 
3.4%
Other Symbol 35
 
2.1%
Uppercase Letter 17
 
1.0%
Lowercase Letter 12
 
0.7%
Other Punctuation 6
 
0.4%
Dash Punctuation 2
 
0.1%
Decimal Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 124
 
9.0%
식 105
 
7.6%
사 85
 
6.1%
회 84
 
6.1%
이 58
 
4.2%
드 52
 
3.8%
푸 48
 
3.5%
품 32
 
2.3%
스 31
 
2.2%
리 26
 
1.9%
Other values (169) 739
53.4%
Uppercase Letter
ValueCountFrequency (%)
F 7
41.2%
C 4
23.5%
B 3
17.6%
T 2
 
11.8%
N 1
 
5.9%
Lowercase Letter
ValueCountFrequency (%)
e 4
33.3%
k 2
16.7%
a 2
16.7%
c 2
16.7%
h 2
16.7%
Open Punctuation
ValueCountFrequency (%)
( 52
92.9%
[ 4
 
7.1%
Close Punctuation
ValueCountFrequency (%)
) 52
92.9%
] 4
 
7.1%
Space Separator
ValueCountFrequency (%)
66
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 35
100.0%
Other Punctuation
ValueCountFrequency (%)
& 6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1419
86.8%
Common 187
 
11.4%
Latin 29
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 124
 
8.7%
식 105
 
7.4%
사 85
 
6.0%
회 84
 
5.9%
이 58
 
4.1%
드 52
 
3.7%
푸 48
 
3.4%
㈜ 35
 
2.5%
품 32
 
2.3%
스 31
 
2.2%
Other values (170) 765
53.9%
Latin
ValueCountFrequency (%)
F 7
24.1%
e 4
13.8%
C 4
13.8%
B 3
10.3%
k 2
 
6.9%
a 2
 
6.9%
c 2
 
6.9%
T 2
 
6.9%
h 2
 
6.9%
N 1
 
3.4%
Common
ValueCountFrequency (%)
66
35.3%
( 52
27.8%
) 52
27.8%
& 6
 
3.2%
[ 4
 
2.1%
] 4
 
2.1%
- 2
 
1.1%
2 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1384
84.6%
ASCII 216
 
13.2%
None 35
 
2.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 124
 
9.0%
식 105
 
7.6%
사 85
 
6.1%
회 84
 
6.1%
이 58
 
4.2%
드 52
 
3.8%
푸 48
 
3.5%
품 32
 
2.3%
스 31
 
2.2%
리 26
 
1.9%
Other values (169) 739
53.4%
ASCII
ValueCountFrequency (%)
66
30.6%
( 52
24.1%
) 52
24.1%
F 7
 
3.2%
& 6
 
2.8%
e 4
 
1.9%
C 4
 
1.9%
[ 4
 
1.9%
] 4
 
1.9%
B 3
 
1.4%
Other values (8) 14
 
6.5%
None
ValueCountFrequency (%)
㈜ 35
100.0%

적용업종
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
식품제조가공업
210 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 210
100.0%

Length

2024-01-28T22:37:42.670667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T22:37:42.746845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 210
100.0%

적용품목
Text

Distinct56
Distinct (%)26.7%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-01-28T22:37:42.937698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length6.2952381
Min length1

Characters and Unicode

Total characters1322
Distinct characters105
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)12.4%

Sample

1st row빵류
2nd row액상차
3rd row침출차
4th row빵류
5th row기타수산물가공품 중 냉동연체류
ValueCountFrequency (%)
중 38
 
13.0%
기타수산물가공품 36
 
12.3%
빵류 23
 
7.9%
냉동어류 17
 
5.8%
과자 13
 
4.5%
냉동연체류 13
 
4.5%
기타가공품 11
 
3.8%
즉석조리식품 10
 
3.4%
소스 10
 
3.4%
절임식품 7
 
2.4%
Other values (52) 114
39.0%
2024-01-28T22:37:43.266356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
품 107
 
8.1%
82
 
6.2%
류 81
 
6.1%
가 70
 
5.3%
공 70
 
5.3%
기 56
 
4.2%
타 56
 
4.2%
식 42
 
3.2%
중 39
 
3.0%
냉 39
 
3.0%
Other values (95) 680
51.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1201
90.8%
Space Separator 82
 
6.2%
Close Punctuation 19
 
1.4%
Open Punctuation 19
 
1.4%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
품 107
 
8.9%
류 81
 
6.7%
가 70
 
5.8%
공 70
 
5.8%
기 56
 
4.7%
타 56
 
4.7%
식 42
 
3.5%
중 39
 
3.2%
냉 39
 
3.2%
동 39
 
3.2%
Other values (91) 602
50.1%
Space Separator
ValueCountFrequency (%)
82
100.0%
Close Punctuation
ValueCountFrequency (%)
) 19
100.0%
Open Punctuation
ValueCountFrequency (%)
( 19
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1201
90.8%
Common 121
 
9.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
품 107
 
8.9%
류 81
 
6.7%
가 70
 
5.8%
공 70
 
5.8%
기 56
 
4.7%
타 56
 
4.7%
식 42
 
3.5%
중 39
 
3.2%
냉 39
 
3.2%
동 39
 
3.2%
Other values (91) 602
50.1%
Common
ValueCountFrequency (%)
82
67.8%
) 19
 
15.7%
( 19
 
15.7%
, 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1201
90.8%
ASCII 121
 
9.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
품 107
 
8.9%
류 81
 
6.7%
가 70
 
5.8%
공 70
 
5.8%
기 56
 
4.7%
타 56
 
4.7%
식 42
 
3.5%
중 39
 
3.2%
냉 39
 
3.2%
동 39
 
3.2%
Other values (91) 602
50.1%
ASCII
ValueCountFrequency (%)
82
67.8%
) 19
 
15.7%
( 19
 
15.7%
, 1
 
0.8%

주소
Text

Distinct99
Distinct (%)47.1%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-01-28T22:37:43.523446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length46
Mean length38.695238
Min length25

Characters and Unicode

Total characters8126
Distinct characters129
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

Unique39 ?
Unique (%)18.6%

Sample

1st row인천광역시 남동구 함박뫼로377번길 24-33 (남촌동)
2nd row인천광역시 남동구 호구포로 183, 후이즈스마트타워 2층 209호 (고잔동)
3rd row인천광역시 남동구 호구포로 183, 후이즈스마트타워 2층 209호 (고잔동)
4th row인천광역시 남동구 인하로543번길 12, 2층 일부호 (구월동)
5th row인천광역시 남동구 서판로 35, 지하1층 비01호 일부호 (만수동)
ValueCountFrequency (%)
인천광역시 210
 
13.7%
남동구 210
 
13.7%
고잔동 104
 
6.8%
일부호 61
 
4.0%
2층 55
 
3.6%
1층 42
 
2.7%
남촌동 28
 
1.8%
호구포로 21
 
1.4%
가동 20
 
1.3%
3층 18
 
1.2%
Other values (244) 768
50.0%
2024-01-28T22:37:43.896623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1327
 
16.3%
동 589
 
7.2%
1 342
 
4.2%
남 311
 
3.8%
층 304
 
3.7%
, 281
 
3.5%
구 243
 
3.0%
) 230
 
2.8%
( 230
 
2.8%
로 223
 
2.7%
Other values (119) 4046
49.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4583
56.4%
Decimal Number 1400
 
17.2%
Space Separator 1327
 
16.3%
Other Punctuation 281
 
3.5%
Close Punctuation 230
 
2.8%
Open Punctuation 230
 
2.8%
Uppercase Letter 35
 
0.4%
Math Symbol 26
 
0.3%
Dash Punctuation 14
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 589
 
12.9%
남 311
 
6.8%
층 304
 
6.6%
구 243
 
5.3%
로 223
 
4.9%
천 221
 
4.8%
인 214
 
4.7%
역 210
 
4.6%
시 210
 
4.6%
광 210
 
4.6%
Other values (97) 1848
40.3%
Decimal Number
ValueCountFrequency (%)
1 342
24.4%
2 216
15.4%
3 195
13.9%
5 150
10.7%
4 139
9.9%
0 96
 
6.9%
6 75
 
5.4%
8 67
 
4.8%
9 60
 
4.3%
7 60
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
B 14
40.0%
A 9
25.7%
C 8
22.9%
H 2
 
5.7%
I 1
 
2.9%
N 1
 
2.9%
Space Separator
ValueCountFrequency (%)
1327
100.0%
Other Punctuation
ValueCountFrequency (%)
, 281
100.0%
Close Punctuation
ValueCountFrequency (%)
) 230
100.0%
Open Punctuation
ValueCountFrequency (%)
( 230
100.0%
Math Symbol
ValueCountFrequency (%)
~ 26
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4583
56.4%
Common 3508
43.2%
Latin 35
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 589
 
12.9%
남 311
 
6.8%
층 304
 
6.6%
구 243
 
5.3%
로 223
 
4.9%
천 221
 
4.8%
인 214
 
4.7%
역 210
 
4.6%
시 210
 
4.6%
광 210
 
4.6%
Other values (97) 1848
40.3%
Common
ValueCountFrequency (%)
1327
37.8%
1 342
 
9.7%
, 281
 
8.0%
) 230
 
6.6%
( 230
 
6.6%
2 216
 
6.2%
3 195
 
5.6%
5 150
 
4.3%
4 139
 
4.0%
0 96
 
2.7%
Other values (6) 302
 
8.6%
Latin
ValueCountFrequency (%)
B 14
40.0%
A 9
25.7%
C 8
22.9%
H 2
 
5.7%
I 1
 
2.9%
N 1
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4583
56.4%
ASCII 3543
43.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1327
37.5%
1 342
 
9.7%
, 281
 
7.9%
) 230
 
6.5%
( 230
 
6.5%
2 216
 
6.1%
3 195
 
5.5%
5 150
 
4.2%
4 139
 
3.9%
0 96
 
2.7%
Other values (12) 337
 
9.5%
Hangul
ValueCountFrequency (%)
동 589
 
12.9%
남 311
 
6.8%
층 304
 
6.6%
구 243
 
5.3%
로 223
 
4.9%
천 221
 
4.8%
인 214
 
4.7%
역 210
 
4.6%
시 210
 
4.6%
광 210
 
4.6%
Other values (97) 1848
40.3%

인증번호
Text

UNIQUE 

Distinct210
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-01-28T22:37:44.161390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters2310
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

Unique210 ?
Unique (%)100.0%

Sample

1st row2023-3-0728
2nd row2023-3-0689
3rd row2023-3-0688
4th row2023-3-0659
5th row2023-3-0633
ValueCountFrequency (%)
2023-3-0728 1
 
0.5%
2018-3-9130 1
 
0.5%
2020-3-9037 1
 
0.5%
2019-3-9078 1
 
0.5%
2020-3-9036 1
 
0.5%
2019-3-9439 1
 
0.5%
2019-3-9440 1
 
0.5%
2019-3-9349 1
 
0.5%
2019-3-9242 1
 
0.5%
2019-3-9234 1
 
0.5%
Other values (200) 200
95.2%
2024-01-28T22:37:44.506643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 457
19.8%
- 420
18.2%
0 387
16.8%
3 321
13.9%
1 252
10.9%
8 106
 
4.6%
9 98
 
4.2%
4 72
 
3.1%
6 70
 
3.0%
5 69
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1890
81.8%
Dash Punctuation 420
 
18.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 457
24.2%
0 387
20.5%
3 321
17.0%
1 252
13.3%
8 106
 
5.6%
9 98
 
5.2%
4 72
 
3.8%
6 70
 
3.7%
5 69
 
3.7%
7 58
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 420
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2310
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 457
19.8%
- 420
18.2%
0 387
16.8%
3 321
13.9%
1 252
10.9%
8 106
 
4.6%
9 98
 
4.2%
4 72
 
3.1%
6 70
 
3.0%
5 69
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2310
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 457
19.8%
- 420
18.2%
0 387
16.8%
3 321
13.9%
1 252
10.9%
8 106
 
4.6%
9 98
 
4.2%
4 72
 
3.1%
6 70
 
3.0%
5 69
 
3.0%

최초인증일
Date

Distinct124
Distinct (%)59.0%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
Minimum2007-05-11 00:00:00
Maximum2023-09-14 00:00:00
2024-01-28T22:37:44.639512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T22:37:44.761010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인증종료일
Date

Distinct109
Distinct (%)51.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
Minimum2023-11-16 00:00:00
Maximum2026-11-25 00:00:00
2024-01-28T22:37:44.868669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T22:37:44.989409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
Minimum2023-11-10 00:00:00
Maximum2023-11-10 00:00:00
2024-01-28T22:37:45.074520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T22:37:45.152121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-01-28T22:37:41.284153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T22:37:45.211184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번적용품목주소
연번1.0000.4990.973
적용품목0.4991.0000.000
주소0.9730.0001.000

Missing values

2024-01-28T22:37:41.374488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T22:37:41.477343image/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

연번업체명적용업종적용품목주소인증번호최초인증일인증종료일데이터기준일
01주식회사 마띠아 남촌지점식품제조가공업빵류인천광역시 남동구 함박뫼로377번길 24-33 (남촌동)2023-3-07282023-09-142026-09-132023-11-10
12농업회사법인 수복주식회사식품제조가공업액상차인천광역시 남동구 호구포로 183, 후이즈스마트타워 2층 209호 (고잔동)2023-3-06892023-08-312026-08-302023-11-10
23농업회사법인 수복주식회사식품제조가공업침출차인천광역시 남동구 호구포로 183, 후이즈스마트타워 2층 209호 (고잔동)2023-3-06882023-08-312026-08-302023-11-10
34주식회사 마담티라미수식품제조가공업빵류인천광역시 남동구 인하로543번길 12, 2층 일부호 (구월동)2023-3-06592023-08-222026-08-212023-11-10
45고성푸드식품제조가공업기타수산물가공품 중 냉동연체류인천광역시 남동구 서판로 35, 지하1층 비01호 일부호 (만수동)2023-3-06332023-08-112026-08-102023-11-10
56고성푸드식품제조가공업기타수산물가공품 중 냉동어류인천광역시 남동구 서판로 35, 지하1층 비01호 일부호 (만수동)2023-3-06322023-08-112026-08-102023-11-10
67빛담은식품제조가공업기타수산물가공품 중 냉동연체류인천광역시 남동구 서판로 35, 지하1층 비01호 일부호 (만수동)2023-3-06312023-08-112026-08-102023-11-10
78빛담은식품제조가공업기타수산물가공품 중 냉동어류인천광역시 남동구 서판로 35, 지하1층 비01호 일부호 (만수동)2023-3-06302023-08-112026-08-102023-11-10
89남동푸드식품제조가공업기타수산물가공품 중 냉동연체류인천광역시 남동구 서판로 35, 지하1층 비01호 일부호 (만수동)2023-3-06292023-08-112026-08-102023-11-10
910남동푸드식품제조가공업기타수산물가공품 중 냉동어류인천광역시 남동구 서판로 35, 지하1층 비01호 일부호 (만수동)2023-3-06282023-08-112026-08-102023-11-10
연번업체명적용업종적용품목주소인증번호최초인증일인증종료일데이터기준일
200201㈜피자코리아식품제조가공업냉동식품 중 피자류인천광역시 남동구 호구포로 111 (고잔동, 101블록 14로트 1층일부, 2층전부)2012-3-81162012-04-122025-11-132023-11-10
201202건영식품식품제조가공업어묵인천광역시 남동구 남동동로33번길 13, 1층(일부),2층(고잔동)2012-3-80982012-03-162026-05-142023-11-10
202203생생찬식품제조가공업절임식품(식염절임)인천광역시 남동구 남동대로410번길 40, 1층전부, 2층일부호 (남촌동)2011-3-81632011-11-072026-06-072023-11-10
203204생생찬식품제조가공업김치(기타김치)인천광역시 남동구 남동대로410번길 40, 1층전부, 2층일부호 (남촌동)2011-3-81622011-11-072026-06-072023-11-10
204205생생찬식품제조가공업김치(배추김치)인천광역시 남동구 남동대로410번길 40, 1층전부, 2층일부호 (남촌동)2011-3-81612011-11-072026-06-072023-11-10
205206현대식품식품제조가공업냉동식품 중 면류(숙면)인천광역시 남동구 남동서로143번길 37 (고잔동, 81블록 3로트)2011-3-80482011-04-252026-06-252023-11-10
206207일미식품식품제조가공업김치(기타김치)인천광역시 남동구 남촌로67번길 28(남촌동)2011-3-80312011-04-062026-01-182023-11-10
207208일미식품식품제조가공업김치(배추김치)인천광역시 남동구 남촌로67번길 28(남촌동)2011-3-80302011-04-062026-01-182023-11-10
208209(주)새롬식품식품제조가공업어묵인천광역시 남동구 능허대로 558, 1층,2층,3층,4층 (고잔동)2010-3-81042010-12-232025-11-152023-11-10
209210천일식품㈜식품제조가공업기타가공품(냉동)인천광역시 남동구 앵고개로 426 (고잔동, 119블록 3로트)2007-3-80192007-05-112025-09-252023-11-10