Overview

Dataset statistics

Number of variables8
Number of observations28
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.9 KiB
Average record size in memory69.7 B

Variable types

Numeric1
Text5
Categorical1
DateTime1

Dataset

Description인천광역시 계양구 HACCP 인증업소에 대한 데이터(업소명, 업종, 적용품목, 대표자, 주소, 인증번호, 인증일)를 제공하고 있습니다.
Author인천광역시 계양구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15062364&srcSe=7661IVAWM27C61E190

Alerts

업종 has constant value ""Constant
연번 has unique valuesUnique
인증번호 has unique valuesUnique

Reproduction

Analysis started2024-03-18 03:06:53.253066
Analysis finished2024-03-18 03:06:55.540077
Duration2.29 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.5
Minimum1
Maximum28
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2024-03-18T12:06:55.591891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.35
Q17.75
median14.5
Q321.25
95-th percentile26.65
Maximum28
Range27
Interquartile range (IQR)13.5

Descriptive statistics

Standard deviation8.2259751
Coefficient of variation (CV)0.56730863
Kurtosis-1.2
Mean14.5
Median Absolute Deviation (MAD)7
Skewness0
Sum406
Variance67.666667
MonotonicityStrictly increasing
2024-03-18T12:06:55.707286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
1 1
 
3.6%
16 1
 
3.6%
28 1
 
3.6%
27 1
 
3.6%
26 1
 
3.6%
25 1
 
3.6%
24 1
 
3.6%
23 1
 
3.6%
22 1
 
3.6%
21 1
 
3.6%
Other values (18) 18
64.3%
ValueCountFrequency (%)
1 1
3.6%
2 1
3.6%
3 1
3.6%
4 1
3.6%
5 1
3.6%
6 1
3.6%
7 1
3.6%
8 1
3.6%
9 1
3.6%
10 1
3.6%
ValueCountFrequency (%)
28 1
3.6%
27 1
3.6%
26 1
3.6%
25 1
3.6%
24 1
3.6%
23 1
3.6%
22 1
3.6%
21 1
3.6%
20 1
3.6%
19 1
3.6%

업소명
Text

Distinct19
Distinct (%)67.9%
Missing0
Missing (%)0.0%
Memory size356.0 B
2024-03-18T12:06:55.864713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length8
Mean length6.1428571
Min length3

Characters and Unicode

Total characters172
Distinct characters80
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)46.4%

Sample

1st row주식회사보릿골푸드
2nd row(주)준유통
3rd row빵부자
4th row오성협동조합
5th row㈜화인푸드
ValueCountFrequency (%)
㈜화인푸드 4
 
12.5%
주식회사 4
 
12.5%
푸드존 3
 
9.4%
㈜선도씨푸드 2
 
6.2%
산해수산 2
 
6.2%
㈜초원 2
 
6.2%
노틀담베이커리 2
 
6.2%
세현백암전통순대 1
 
3.1%
행운식품㈜ 1
 
3.1%
경인푸드 1
 
3.1%
Other values (10) 10
31.2%
2024-03-18T12:06:56.138842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
푸 12
 
7.0%
드 12
 
7.0%
㈜ 11
 
6.4%
식 9
 
5.2%
인 6
 
3.5%
주 6
 
3.5%
회 5
 
2.9%
사 5
 
2.9%
화 4
 
2.3%
산 4
 
2.3%
Other values (70) 98
57.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 155
90.1%
Other Symbol 11
 
6.4%
Space Separator 4
 
2.3%
Open Punctuation 1
 
0.6%
Close Punctuation 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
푸 12
 
7.7%
드 12
 
7.7%
식 9
 
5.8%
인 6
 
3.9%
주 6
 
3.9%
회 5
 
3.2%
사 5
 
3.2%
화 4
 
2.6%
산 4
 
2.6%
품 4
 
2.6%
Other values (66) 88
56.8%
Other Symbol
ValueCountFrequency (%)
㈜ 11
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 166
96.5%
Common 6
 
3.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
푸 12
 
7.2%
드 12
 
7.2%
㈜ 11
 
6.6%
식 9
 
5.4%
인 6
 
3.6%
주 6
 
3.6%
회 5
 
3.0%
사 5
 
3.0%
화 4
 
2.4%
산 4
 
2.4%
Other values (67) 92
55.4%
Common
ValueCountFrequency (%)
4
66.7%
( 1
 
16.7%
) 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 155
90.1%
None 11
 
6.4%
ASCII 6
 
3.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
푸 12
 
7.7%
드 12
 
7.7%
식 9
 
5.8%
인 6
 
3.9%
주 6
 
3.9%
회 5
 
3.2%
사 5
 
3.2%
화 4
 
2.6%
산 4
 
2.6%
품 4
 
2.6%
Other values (66) 88
56.8%
None
ValueCountFrequency (%)
㈜ 11
100.0%
ASCII
ValueCountFrequency (%)
4
66.7%
( 1
 
16.7%
) 1
 
16.7%

업종
Categorical

CONSTANT 

Distinct1
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size356.0 B
식품제조가공업
28 

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 28
100.0%

Length

2024-03-18T12:06:56.275645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T12:06:56.388709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 28
100.0%

적용품목
Text

Distinct22
Distinct (%)78.6%
Missing0
Missing (%)0.0%
Memory size356.0 B
2024-03-18T12:06:56.543586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length13.5
Mean length7.25
Min length2

Characters and Unicode

Total characters203
Distinct characters57
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

Unique17 ?
Unique (%)60.7%

Sample

1st row청국장
2nd row기타가공품
3rd row빵류
4th row과자
5th row기타가공품
ValueCountFrequency (%)
기타수산물가공품 5
 
12.5%
중 4
 
10.0%
빵류 3
 
7.5%
냉동어류 2
 
5.0%
즉석조리식품(순대 2
 
5.0%
기타가공품 2
 
5.0%
과자 2
 
5.0%
어류 1
 
2.5%
청국장 1
 
2.5%
국수(생면 1
 
2.5%
Other values (17) 17
42.5%
2024-03-18T12:06:56.879717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
품 17
 
8.4%
가 14
 
6.9%
공 14
 
6.9%
12
 
5.9%
기 10
 
4.9%
타 10
 
4.9%
류 9
 
4.4%
수 7
 
3.4%
) 6
 
3.0%
산 6
 
3.0%
Other values (47) 98
48.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 179
88.2%
Space Separator 12
 
5.9%
Close Punctuation 6
 
3.0%
Open Punctuation 6
 
3.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
품 17
 
9.5%
가 14
 
7.8%
공 14
 
7.8%
기 10
 
5.6%
타 10
 
5.6%
류 9
 
5.0%
수 7
 
3.9%
산 6
 
3.4%
물 6
 
3.4%
냉 5
 
2.8%
Other values (44) 81
45.3%
Space Separator
ValueCountFrequency (%)
12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 179
88.2%
Common 24
 
11.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
품 17
 
9.5%
가 14
 
7.8%
공 14
 
7.8%
기 10
 
5.6%
타 10
 
5.6%
류 9
 
5.0%
수 7
 
3.9%
산 6
 
3.4%
물 6
 
3.4%
냉 5
 
2.8%
Other values (44) 81
45.3%
Common
ValueCountFrequency (%)
12
50.0%
) 6
25.0%
( 6
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 179
88.2%
ASCII 24
 
11.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
품 17
 
9.5%
가 14
 
7.8%
공 14
 
7.8%
기 10
 
5.6%
타 10
 
5.6%
류 9
 
5.0%
수 7
 
3.9%
산 6
 
3.4%
물 6
 
3.4%
냉 5
 
2.8%
Other values (44) 81
45.3%
ASCII
ValueCountFrequency (%)
12
50.0%
) 6
25.0%
( 6
25.0%

대표자
Text

Distinct19
Distinct (%)67.9%
Missing0
Missing (%)0.0%
Memory size356.0 B
2024-03-18T12:06:57.039032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.8928571
Min length3

Characters and Unicode

Total characters109
Distinct characters47
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)46.4%

Sample

1st row김춘수
2nd row모길봉
3rd row이석규
4th row이손희
5th row임구연
ValueCountFrequency (%)
외 5
13.2%
1명 5
13.2%
임구연 4
 
10.5%
이승희 3
 
7.9%
장상훈 2
 
5.3%
장순종 2
 
5.3%
최소미 2
 
5.3%
이승찬 2
 
5.3%
김세현 1
 
2.6%
김용험 1
 
2.6%
Other values (11) 11
28.9%
2024-03-18T12:06:57.320792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10
 
9.2%
이 7
 
6.4%
승 6
 
5.5%
1 5
 
4.6%
명 5
 
4.6%
외 5
 
4.6%
구 4
 
3.7%
장 4
 
3.7%
임 4
 
3.7%
희 4
 
3.7%
Other values (37) 55
50.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 94
86.2%
Space Separator 10
 
9.2%
Decimal Number 5
 
4.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 7
 
7.4%
승 6
 
6.4%
명 5
 
5.3%
외 5
 
5.3%
구 4
 
4.3%
장 4
 
4.3%
임 4
 
4.3%
희 4
 
4.3%
연 4
 
4.3%
김 3
 
3.2%
Other values (35) 48
51.1%
Space Separator
ValueCountFrequency (%)
10
100.0%
Decimal Number
ValueCountFrequency (%)
1 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 94
86.2%
Common 15
 
13.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 7
 
7.4%
승 6
 
6.4%
명 5
 
5.3%
외 5
 
5.3%
구 4
 
4.3%
장 4
 
4.3%
임 4
 
4.3%
희 4
 
4.3%
연 4
 
4.3%
김 3
 
3.2%
Other values (35) 48
51.1%
Common
ValueCountFrequency (%)
10
66.7%
1 5
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 94
86.2%
ASCII 15
 
13.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10
66.7%
1 5
33.3%
Hangul
ValueCountFrequency (%)
이 7
 
7.4%
승 6
 
6.4%
명 5
 
5.3%
외 5
 
5.3%
구 4
 
4.3%
장 4
 
4.3%
임 4
 
4.3%
희 4
 
4.3%
연 4
 
4.3%
김 3
 
3.2%
Other values (35) 48
51.1%

주소
Text

Distinct19
Distinct (%)67.9%
Missing0
Missing (%)0.0%
Memory size356.0 B
2024-03-18T12:06:57.529801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length36.5
Mean length33.642857
Min length22

Characters and Unicode

Total characters942
Distinct characters87
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

Unique13 ?
Unique (%)46.4%

Sample

1st row인천광역시 계양구 경명대로 977, 나동 지하1층 (계산동)
2nd row인천광역시 계양구 봉오대로 468, JJJ빌딩 2층 일부호 (효성동)
3rd row인천광역시 계양구 안남로573번길 9, 효성빌딩 2층 (효성동)
4th row인천광역시 계양구 병방시장로 69(신명진달래아파트 지하층 일부호 병방동)
5th row인천광역시 계양구 안남로 457번길 16
ValueCountFrequency (%)
인천광역시 28
 
16.0%
계양구 28
 
16.0%
2층 6
 
3.4%
서운동 6
 
3.4%
계산동 5
 
2.9%
1,2층 4
 
2.3%
일부호 4
 
2.3%
안남로 4
 
2.3%
457번길 4
 
2.3%
16 4
 
2.3%
Other values (53) 82
46.9%
2024-03-18T12:06:57.869761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
147
 
15.6%
계 35
 
3.7%
1 34
 
3.6%
시 31
 
3.3%
양 30
 
3.2%
) 29
 
3.1%
, 29
 
3.1%
( 29
 
3.1%
인 28
 
3.0%
광 28
 
3.0%
Other values (77) 522
55.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 554
58.8%
Space Separator 147
 
15.6%
Decimal Number 143
 
15.2%
Close Punctuation 29
 
3.1%
Other Punctuation 29
 
3.1%
Open Punctuation 29
 
3.1%
Dash Punctuation 5
 
0.5%
Uppercase Letter 5
 
0.5%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
계 35
 
6.3%
시 31
 
5.6%
양 30
 
5.4%
인 28
 
5.1%
광 28
 
5.1%
역 28
 
5.1%
구 28
 
5.1%
동 28
 
5.1%
천 28
 
5.1%
층 28
 
5.1%
Other values (59) 262
47.3%
Decimal Number
ValueCountFrequency (%)
1 34
23.8%
2 26
18.2%
4 18
12.6%
5 13
 
9.1%
9 11
 
7.7%
7 11
 
7.7%
3 9
 
6.3%
6 8
 
5.6%
8 8
 
5.6%
0 5
 
3.5%
Uppercase Letter
ValueCountFrequency (%)
J 3
60.0%
B 2
40.0%
Space Separator
ValueCountFrequency (%)
147
100.0%
Close Punctuation
ValueCountFrequency (%)
) 29
100.0%
Other Punctuation
ValueCountFrequency (%)
, 29
100.0%
Open Punctuation
ValueCountFrequency (%)
( 29
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 554
58.8%
Common 383
40.7%
Latin 5
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
계 35
 
6.3%
시 31
 
5.6%
양 30
 
5.4%
인 28
 
5.1%
광 28
 
5.1%
역 28
 
5.1%
구 28
 
5.1%
동 28
 
5.1%
천 28
 
5.1%
층 28
 
5.1%
Other values (59) 262
47.3%
Common
ValueCountFrequency (%)
147
38.4%
1 34
 
8.9%
) 29
 
7.6%
, 29
 
7.6%
( 29
 
7.6%
2 26
 
6.8%
4 18
 
4.7%
5 13
 
3.4%
9 11
 
2.9%
7 11
 
2.9%
Other values (6) 36
 
9.4%
Latin
ValueCountFrequency (%)
J 3
60.0%
B 2
40.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 554
58.8%
ASCII 388
41.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
147
37.9%
1 34
 
8.8%
) 29
 
7.5%
, 29
 
7.5%
( 29
 
7.5%
2 26
 
6.7%
4 18
 
4.6%
5 13
 
3.4%
9 11
 
2.8%
7 11
 
2.8%
Other values (8) 41
 
10.6%
Hangul
ValueCountFrequency (%)
계 35
 
6.3%
시 31
 
5.6%
양 30
 
5.4%
인 28
 
5.1%
광 28
 
5.1%
역 28
 
5.1%
구 28
 
5.1%
동 28
 
5.1%
천 28
 
5.1%
층 28
 
5.1%
Other values (59) 262
47.3%

인증번호
Text

UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size356.0 B
2024-03-18T12:06:58.048276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters308
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

Unique28 ?
Unique (%)100.0%

Sample

1st row2022-3-1058
2nd row2022-3-0993
3rd row2021-3-1499
4th row2021-3-1462
5th row2020-3-0701
ValueCountFrequency (%)
2022-3-1058 1
 
3.6%
2022-3-0993 1
 
3.6%
2012-3-8263 1
 
3.6%
2015-3-8288 1
 
3.6%
2015-3-8289 1
 
3.6%
2015-3-8380 1
 
3.6%
2016-3-8402 1
 
3.6%
2016-3-8403 1
 
3.6%
2017-3-9026 1
 
3.6%
2017-3-9367 1
 
3.6%
Other values (18) 18
64.3%
2024-03-18T12:06:58.325063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 59
19.2%
- 56
18.2%
0 49
15.9%
3 43
14.0%
1 31
10.1%
9 22
 
7.1%
8 17
 
5.5%
6 11
 
3.6%
5 9
 
2.9%
4 6
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 252
81.8%
Dash Punctuation 56
 
18.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 59
23.4%
0 49
19.4%
3 43
17.1%
1 31
12.3%
9 22
 
8.7%
8 17
 
6.7%
6 11
 
4.4%
5 9
 
3.6%
4 6
 
2.4%
7 5
 
2.0%
Dash Punctuation
ValueCountFrequency (%)
- 56
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 308
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 59
19.2%
- 56
18.2%
0 49
15.9%
3 43
14.0%
1 31
10.1%
9 22
 
7.1%
8 17
 
5.5%
6 11
 
3.6%
5 9
 
2.9%
4 6
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 308
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 59
19.2%
- 56
18.2%
0 49
15.9%
3 43
14.0%
1 31
10.1%
9 22
 
7.1%
8 17
 
5.5%
6 11
 
3.6%
5 9
 
2.9%
4 6
 
1.9%

인증일
Date

Distinct20
Distinct (%)71.4%
Missing0
Missing (%)0.0%
Memory size356.0 B
Minimum2012-01-31 00:00:00
Maximum2022-11-11 00:00:00
2024-03-18T12:06:58.425129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:06:58.520140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)

Interactions

2024-03-18T12:06:55.173625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-18T12:06:58.628822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업소명적용품목대표자주소인증번호인증일
연번1.0000.8630.3950.8630.8631.0000.927
업소명0.8631.0000.0001.0001.0001.0001.000
적용품목0.3950.0001.0000.0000.0001.0000.000
대표자0.8631.0000.0001.0001.0001.0001.000
주소0.8631.0000.0001.0001.0001.0001.000
인증번호1.0001.0001.0001.0001.0001.0001.000
인증일0.9271.0000.0001.0001.0001.0001.000

Missing values

2024-03-18T12:06:55.352830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T12:06:55.492814image/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

연번업소명업종적용품목대표자주소인증번호인증일
01주식회사보릿골푸드식품제조가공업청국장김춘수인천광역시 계양구 경명대로 977, 나동 지하1층 (계산동)2022-3-10582022-11-11
12(주)준유통식품제조가공업기타가공품모길봉인천광역시 계양구 봉오대로 468, JJJ빌딩 2층 일부호 (효성동)2022-3-09932022-10-21
23빵부자식품제조가공업빵류이석규인천광역시 계양구 안남로573번길 9, 효성빌딩 2층 (효성동)2021-3-14992021-11-30
34오성협동조합식품제조가공업과자이손희인천광역시 계양구 병방시장로 69(신명진달래아파트 지하층 일부호 병방동)2021-3-14622021-11-26
45㈜화인푸드식품제조가공업기타가공품임구연인천광역시 계양구 안남로 457번길 162020-3-07012020-07-09
56주식회사 푸드존식품제조가공업땅콩 또는 견과류가공품이승희 외 1명인천광역시 계양구 서운산단로4길 19 1,2층 (서운동)2020-3-02122020-03-31
67주식회사 푸드존식품제조가공업초콜릿가공품이승희 외 1명인천광역시 계양구 서운산단로4길 19 1,2층 (서운동)2020-3-02112020-03-31
78주식회사 푸드존식품제조가공업기타 코코아가공품이승희 외 1명인천광역시 계양구 서운산단로4길 19 1,2층 (서운동)2020-3-02102020-03-31
89주식회사 정다함식품제조가공업기타수산물가공품 중 냉동조미가공품정석동인천광역시 계양구 봉오대로894번길 39, 2층 일부호 (서운동)2020-3-00452020-02-14
910오룡식품식품제조가공업빵류남정주인천광역시 계양구 서운산업로47번길 24-1, 1,2층 (서운동)2019-3-93962019-11-04
연번업소명업종적용품목대표자주소인증번호인증일
1819세현백암전통순대식품제조가공업즉석조리식품(순대)김세현 외 1명인천광역시 계양구 서운산업로47번길 22, 2층 (서운동)2017-3-95052017-11-30
1920모닝에버식품식품제조가공업즉석조리식품심용수 외 1명인천광역시 계양구 장제로863번길 9 (임학동)2017-3-93672017-09-29
2021경인푸드식품제조가공업즉석조리식품(순대)박승옥인천광역시 계양구 까치말로5번길 13, 지하1층,1층,2층 (작전동)2017-3-90262017-03-08
2122노틀담베이커리식품제조가공업빵류이승찬인천광역시 계양구 계양산로35번길 12-37, B동 지하층 (계산동, 계산동 40 종교시설(노틀담수녀회))2016-3-84032016-11-25
2223노틀담베이커리식품제조가공업과자이승찬인천광역시 계양구 계양산로35번길 12-37, B동 지하층 (계산동, 계산동 40 종교시설(노틀담수녀회))2016-3-84022016-11-25
2324행운식품㈜식품제조가공업떡류김용험인천광역시 계양구 안남로458번길 11-1, 2층2015-3-83802015-12-02
2425㈜초원식품제조가공업김치(기타김치)최소미인천광역시 계양구 용마루5길 8, 1층(용종동)2015-3-82892015-08-07
2526㈜초원식품제조가공업김치(배추김치)최소미인천광역시 계양구 용마루5길 8, 1층(용종동)2015-3-82882015-08-07
2627㈜진성종합식품식품제조가공업국수(생면)신중현인천광역시 계양구 아나지로 428-11(작전동, 지하1층~지상3층)2012-3-82632012-10-05
2728㈜화인푸드식품제조가공업식육함유가공품임구연인천광역시 계양구 안남로 457번길 162012-3-80382012-01-31