Overview

Dataset statistics

Number of variables6
Number of observations57
Missing cells30
Missing cells (%)8.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.9 KiB
Average record size in memory51.3 B

Variable types

Numeric1
Categorical1
Text4

Dataset

Description인천광역시 미추홀구 식품소분업에 대한 데이터로 업종명, 업소명, 도로명주소, 지번주소, 전화번호 등을 제공합니다.
Author인천광역시 미추홀구
URLhttps://www.data.go.kr/data/15080979/fileData.do

Alerts

업종명 has constant value ""Constant
소재지전화 has 30 (52.6%) missing valuesMissing
연번 has unique valuesUnique
업소명 has unique valuesUnique
소재지(도로명) has unique valuesUnique
소재지(지번) has unique valuesUnique

Reproduction

Analysis started2024-03-23 05:37:59.326911
Analysis finished2024-03-23 05:38:00.493213
Duration1.17 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct57
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29
Minimum1
Maximum57
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size645.0 B
2024-03-23T14:38:00.650204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.8
Q115
median29
Q343
95-th percentile54.2
Maximum57
Range56
Interquartile range (IQR)28

Descriptive statistics

Standard deviation16.598193
Coefficient of variation (CV)0.57235147
Kurtosis-1.2
Mean29
Median Absolute Deviation (MAD)14
Skewness0
Sum1653
Variance275.5
MonotonicityStrictly increasing
2024-03-23T14:38:00.975931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.8%
44 1
 
1.8%
32 1
 
1.8%
33 1
 
1.8%
34 1
 
1.8%
35 1
 
1.8%
36 1
 
1.8%
37 1
 
1.8%
38 1
 
1.8%
39 1
 
1.8%
Other values (47) 47
82.5%
ValueCountFrequency (%)
1 1
1.8%
2 1
1.8%
3 1
1.8%
4 1
1.8%
5 1
1.8%
6 1
1.8%
7 1
1.8%
8 1
1.8%
9 1
1.8%
10 1
1.8%
ValueCountFrequency (%)
57 1
1.8%
56 1
1.8%
55 1
1.8%
54 1
1.8%
53 1
1.8%
52 1
1.8%
51 1
1.8%
50 1
1.8%
49 1
1.8%
48 1
1.8%

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size588.0 B
식품소분업
57 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품소분업 57
100.0%

Length

2024-03-23T14:38:01.222935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T14:38:01.425740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품소분업 57
100.0%

업소명
Text

UNIQUE 

Distinct57
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size588.0 B
2024-03-23T14:38:01.782947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length12
Mean length5.8947368
Min length2

Characters and Unicode

Total characters336
Distinct characters156
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique57 ?
Unique (%)100.0%

Sample

1st row삼성제과
2nd row중앙상회
3rd row공주물산
4th row만물상회
5th row(주)해정원
ValueCountFrequency (%)
주식회사 3
 
4.5%
주안점 2
 
3.0%
삼성제과 1
 
1.5%
뻥튀기공작소 1
 
1.5%
삼라마트 1
 
1.5%
농업회사법인(주)청정식품 1
 
1.5%
월드헬시푸드 1
 
1.5%
야다푸드 1
 
1.5%
클림 1
 
1.5%
길`s마켓 1
 
1.5%
Other values (53) 53
80.3%
2024-03-23T14:38:02.507105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 15
 
4.5%
이 12
 
3.6%
식 9
 
2.7%
드 9
 
2.7%
9
 
2.7%
) 8
 
2.4%
( 8
 
2.4%
마 7
 
2.1%
회 7
 
2.1%
트 6
 
1.8%
Other values (146) 246
73.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 306
91.1%
Space Separator 9
 
2.7%
Close Punctuation 8
 
2.4%
Open Punctuation 8
 
2.4%
Uppercase Letter 3
 
0.9%
Modifier Symbol 1
 
0.3%
Other Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 15
 
4.9%
이 12
 
3.9%
식 9
 
2.9%
드 9
 
2.9%
마 7
 
2.3%
회 7
 
2.3%
트 6
 
2.0%
인 6
 
2.0%
푸 5
 
1.6%
사 5
 
1.6%
Other values (138) 225
73.5%
Uppercase Letter
ValueCountFrequency (%)
S 1
33.3%
K 1
33.3%
J 1
33.3%
Space Separator
ValueCountFrequency (%)
9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%
Other Punctuation
ValueCountFrequency (%)
＆ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 306
91.1%
Common 27
 
8.0%
Latin 3
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 15
 
4.9%
이 12
 
3.9%
식 9
 
2.9%
드 9
 
2.9%
마 7
 
2.3%
회 7
 
2.3%
트 6
 
2.0%
인 6
 
2.0%
푸 5
 
1.6%
사 5
 
1.6%
Other values (138) 225
73.5%
Common
ValueCountFrequency (%)
9
33.3%
) 8
29.6%
( 8
29.6%
` 1
 
3.7%
＆ 1
 
3.7%
Latin
ValueCountFrequency (%)
S 1
33.3%
K 1
33.3%
J 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 306
91.1%
ASCII 29
 
8.6%
None 1
 
0.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 15
 
4.9%
이 12
 
3.9%
식 9
 
2.9%
드 9
 
2.9%
마 7
 
2.3%
회 7
 
2.3%
트 6
 
2.0%
인 6
 
2.0%
푸 5
 
1.6%
사 5
 
1.6%
Other values (138) 225
73.5%
ASCII
ValueCountFrequency (%)
9
31.0%
) 8
27.6%
( 8
27.6%
` 1
 
3.4%
S 1
 
3.4%
K 1
 
3.4%
J 1
 
3.4%
None
ValueCountFrequency (%)
＆ 1
100.0%

소재지(도로명)
Text

UNIQUE 

Distinct57
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size588.0 B
2024-03-23T14:38:02.979754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length40
Mean length31.807018
Min length22

Characters and Unicode

Total characters1813
Distinct characters118
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

Unique57 ?
Unique (%)100.0%

Sample

1st row인천광역시 미추홀구 경원대로781번길 63 (주안동)
2nd row인천광역시 미추홀구 경인로471번길 7 (주안동)
3rd row인천광역시 미추홀구 인주대로137번길 23-16 (용현동)
4th row인천광역시 미추홀구 인주대로238번길 36 (용현동)
5th row인천광역시 미추홀구 염전로165번길 52-45 (도화동)
ValueCountFrequency (%)
인천광역시 57
 
16.2%
미추홀구 57
 
16.2%
주안동 26
 
7.4%
2층 11
 
3.1%
도화동 10
 
2.8%
1층 9
 
2.6%
용현동 7
 
2.0%
숭의동 6
 
1.7%
학익동 5
 
1.4%
방축로 4
 
1.1%
Other values (133) 159
45.3%
2024-03-23T14:38:03.783059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
295
 
16.3%
인 73
 
4.0%
1 63
 
3.5%
동 62
 
3.4%
홀 61
 
3.4%
미 60
 
3.3%
추 60
 
3.3%
역 59
 
3.3%
천 58
 
3.2%
) 57
 
3.1%
Other values (108) 965
53.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1061
58.5%
Space Separator 295
 
16.3%
Decimal Number 278
 
15.3%
Close Punctuation 57
 
3.1%
Open Punctuation 57
 
3.1%
Other Punctuation 39
 
2.2%
Dash Punctuation 13
 
0.7%
Lowercase Letter 7
 
0.4%
Uppercase Letter 6
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 73
 
6.9%
동 62
 
5.8%
홀 61
 
5.7%
미 60
 
5.7%
추 60
 
5.7%
역 59
 
5.6%
천 58
 
5.5%
구 57
 
5.4%
광 57
 
5.4%
시 57
 
5.4%
Other values (82) 457
43.1%
Decimal Number
ValueCountFrequency (%)
1 63
22.7%
2 50
18.0%
3 47
16.9%
6 23
 
8.3%
5 19
 
6.8%
8 18
 
6.5%
0 17
 
6.1%
4 16
 
5.8%
7 13
 
4.7%
9 12
 
4.3%
Lowercase Letter
ValueCountFrequency (%)
o 1
14.3%
w 1
14.3%
e 1
14.3%
r 1
14.3%
v 1
14.3%
c 1
14.3%
g 1
14.3%
Uppercase Letter
ValueCountFrequency (%)
A 2
33.3%
B 2
33.3%
J 1
16.7%
T 1
16.7%
Space Separator
ValueCountFrequency (%)
295
100.0%
Close Punctuation
ValueCountFrequency (%)
) 57
100.0%
Open Punctuation
ValueCountFrequency (%)
( 57
100.0%
Other Punctuation
ValueCountFrequency (%)
, 39
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1061
58.5%
Common 739
40.8%
Latin 13
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 73
 
6.9%
동 62
 
5.8%
홀 61
 
5.7%
미 60
 
5.7%
추 60
 
5.7%
역 59
 
5.6%
천 58
 
5.5%
구 57
 
5.4%
광 57
 
5.4%
시 57
 
5.4%
Other values (82) 457
43.1%
Common
ValueCountFrequency (%)
295
39.9%
1 63
 
8.5%
) 57
 
7.7%
( 57
 
7.7%
2 50
 
6.8%
3 47
 
6.4%
, 39
 
5.3%
6 23
 
3.1%
5 19
 
2.6%
8 18
 
2.4%
Other values (5) 71
 
9.6%
Latin
ValueCountFrequency (%)
A 2
15.4%
B 2
15.4%
o 1
7.7%
w 1
7.7%
e 1
7.7%
r 1
7.7%
v 1
7.7%
c 1
7.7%
g 1
7.7%
J 1
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1061
58.5%
ASCII 752
41.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
295
39.2%
1 63
 
8.4%
) 57
 
7.6%
( 57
 
7.6%
2 50
 
6.6%
3 47
 
6.2%
, 39
 
5.2%
6 23
 
3.1%
5 19
 
2.5%
8 18
 
2.4%
Other values (16) 84
 
11.2%
Hangul
ValueCountFrequency (%)
인 73
 
6.9%
동 62
 
5.8%
홀 61
 
5.7%
미 60
 
5.7%
추 60
 
5.7%
역 59
 
5.6%
천 58
 
5.5%
구 57
 
5.4%
광 57
 
5.4%
시 57
 
5.4%
Other values (82) 457
43.1%

소재지(지번)
Text

UNIQUE 

Distinct57
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size588.0 B
2024-03-23T14:38:04.269164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length32
Mean length24.754386
Min length17

Characters and Unicode

Total characters1411
Distinct characters90
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique57 ?
Unique (%)100.0%

Sample

1st row인천광역시 미추홀구 주안동 1508-11 9통1반
2nd row인천광역시 미추홀구 주안동 953-2
3rd row인천광역시 미추홀구 용현동 453-12
4th row인천광역시 미추홀구 용현동 98-1
5th row인천광역시 미추홀구 도화동 822-7
ValueCountFrequency (%)
인천광역시 57
20.8%
미추홀구 57
20.8%
주안동 26
 
9.5%
도화동 10
 
3.6%
용현동 7
 
2.6%
숭의동 6
 
2.2%
2층 5
 
1.8%
학익동 5
 
1.8%
1385-10 3
 
1.1%
2
 
0.7%
Other values (92) 96
35.0%
2024-03-23T14:38:05.233510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
269
19.1%
1 67
 
4.7%
인 60
 
4.3%
동 60
 
4.3%
천 58
 
4.1%
역 58
 
4.1%
시 57
 
4.0%
추 57
 
4.0%
홀 57
 
4.0%
구 57
 
4.0%
Other values (80) 611
43.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 791
56.1%
Decimal Number 287
 
20.3%
Space Separator 269
 
19.1%
Dash Punctuation 50
 
3.5%
Lowercase Letter 7
 
0.5%
Uppercase Letter 4
 
0.3%
Other Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 60
 
7.6%
동 60
 
7.6%
천 58
 
7.3%
역 58
 
7.3%
시 57
 
7.2%
추 57
 
7.2%
홀 57
 
7.2%
구 57
 
7.2%
미 57
 
7.2%
광 57
 
7.2%
Other values (57) 213
26.9%
Decimal Number
ValueCountFrequency (%)
1 67
23.3%
2 34
11.8%
4 32
11.1%
3 32
11.1%
8 27
9.4%
0 24
 
8.4%
6 23
 
8.0%
5 20
 
7.0%
7 14
 
4.9%
9 14
 
4.9%
Lowercase Letter
ValueCountFrequency (%)
e 1
14.3%
o 1
14.3%
w 1
14.3%
r 1
14.3%
c 1
14.3%
g 1
14.3%
v 1
14.3%
Uppercase Letter
ValueCountFrequency (%)
B 2
50.0%
J 1
25.0%
T 1
25.0%
Space Separator
ValueCountFrequency (%)
269
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 50
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 791
56.1%
Common 609
43.2%
Latin 11
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 60
 
7.6%
동 60
 
7.6%
천 58
 
7.3%
역 58
 
7.3%
시 57
 
7.2%
추 57
 
7.2%
홀 57
 
7.2%
구 57
 
7.2%
미 57
 
7.2%
광 57
 
7.2%
Other values (57) 213
26.9%
Common
ValueCountFrequency (%)
269
44.2%
1 67
 
11.0%
- 50
 
8.2%
2 34
 
5.6%
4 32
 
5.3%
3 32
 
5.3%
8 27
 
4.4%
0 24
 
3.9%
6 23
 
3.8%
5 20
 
3.3%
Other values (3) 31
 
5.1%
Latin
ValueCountFrequency (%)
B 2
18.2%
e 1
9.1%
J 1
9.1%
T 1
9.1%
o 1
9.1%
w 1
9.1%
r 1
9.1%
c 1
9.1%
g 1
9.1%
v 1
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 791
56.1%
ASCII 620
43.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
269
43.4%
1 67
 
10.8%
- 50
 
8.1%
2 34
 
5.5%
4 32
 
5.2%
3 32
 
5.2%
8 27
 
4.4%
0 24
 
3.9%
6 23
 
3.7%
5 20
 
3.2%
Other values (13) 42
 
6.8%
Hangul
ValueCountFrequency (%)
인 60
 
7.6%
동 60
 
7.6%
천 58
 
7.3%
역 58
 
7.3%
시 57
 
7.2%
추 57
 
7.2%
홀 57
 
7.2%
구 57
 
7.2%
미 57
 
7.2%
광 57
 
7.2%
Other values (57) 213
26.9%

소재지전화
Text

MISSING 

Distinct27
Distinct (%)100.0%
Missing30
Missing (%)52.6%
Memory size588.0 B
2024-03-23T14:38:05.626088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.962963
Min length9

Characters and Unicode

Total characters323
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

Unique27 ?
Unique (%)100.0%

Sample

1st row032-422-5387
2nd row032-425-4438
3rd row032-883-0101
4th row032-873-4668
5th row032-875-6166
ValueCountFrequency (%)
032-422-5387 1
 
3.7%
032-8722-720 1
 
3.7%
032-865-5008 1
 
3.7%
1688-7602 1
 
3.7%
070-8654-1225 1
 
3.7%
070-4062-4344 1
 
3.7%
032-873-5858 1
 
3.7%
032-864-9100 1
 
3.7%
032-862-8988 1
 
3.7%
032-873-4959 1
 
3.7%
Other values (17) 17
63.0%
2024-03-23T14:38:06.184335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 53
16.4%
3 45
13.9%
0 44
13.6%
8 39
12.1%
2 36
11.1%
6 28
8.7%
7 22
6.8%
4 18
 
5.6%
5 15
 
4.6%
1 14
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 270
83.6%
Dash Punctuation 53
 
16.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 45
16.7%
0 44
16.3%
8 39
14.4%
2 36
13.3%
6 28
10.4%
7 22
8.1%
4 18
 
6.7%
5 15
 
5.6%
1 14
 
5.2%
9 9
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 53
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 323
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 53
16.4%
3 45
13.9%
0 44
13.6%
8 39
12.1%
2 36
11.1%
6 28
8.7%
7 22
6.8%
4 18
 
5.6%
5 15
 
4.6%
1 14
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 323
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 53
16.4%
3 45
13.9%
0 44
13.6%
8 39
12.1%
2 36
11.1%
6 28
8.7%
7 22
6.8%
4 18
 
5.6%
5 15
 
4.6%
1 14
 
4.3%

Interactions

2024-03-23T14:37:59.913736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T14:38:06.337694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업소명소재지(도로명)소재지(지번)소재지전화
연번1.0001.0001.0001.0001.000
업소명1.0001.0001.0001.0001.000
소재지(도로명)1.0001.0001.0001.0001.000
소재지(지번)1.0001.0001.0001.0001.000
소재지전화1.0001.0001.0001.0001.000

Missing values

2024-03-23T14:38:00.180137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T14:38:00.415512image/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

연번업종명업소명소재지(도로명)소재지(지번)소재지전화
01식품소분업삼성제과인천광역시 미추홀구 경원대로781번길 63 (주안동)인천광역시 미추홀구 주안동 1508-11 9통1반032-422-5387
12식품소분업중앙상회인천광역시 미추홀구 경인로471번길 7 (주안동)인천광역시 미추홀구 주안동 953-2032-425-4438
23식품소분업공주물산인천광역시 미추홀구 인주대로137번길 23-16 (용현동)인천광역시 미추홀구 용현동 453-12032-883-0101
34식품소분업만물상회인천광역시 미추홀구 인주대로238번길 36 (용현동)인천광역시 미추홀구 용현동 98-1032-873-4668
45식품소분업(주)해정원인천광역시 미추홀구 염전로165번길 52-45 (도화동)인천광역시 미추홀구 도화동 822-7032-875-6166
56식품소분업떡보의하루 주안점인천광역시 미추홀구 경인로 424-1 (주안동)인천광역시 미추홀구 주안동 302-9<NA>
67식품소분업롯데쇼핑(주) 롯데슈퍼 인천문학점인천광역시 미추홀구 소성로 335 (문학동)인천광역시 미추홀구 문학동 385-3032-471-7660
78식품소분업빅토리할인마트인천광역시 미추홀구 매소홀로 355 (학익동)인천광역시 미추홀구 학익동 209-3032-863-9393
89식품소분업중앙유통인천광역시 미추홀구 경인로42번길 4 (숭의동)인천광역시 미추홀구 숭의동 182-1032-886-5396
910식품소분업재원꽃게인천광역시 미추홀구 주승로 160, B01호 (주안동)인천광역시 미추홀구 주안동 1600 B01호<NA>
연번업종명업소명소재지(도로명)소재지(지번)소재지전화
4748식품소분업에스제이마켓인천광역시 미추홀구 송림로 181-2, 제1층 제1호 (도화동)인천광역시 미추홀구 도화동 24-64 제1층 제1호<NA>
4849식품소분업유벨리타인천광역시 미추홀구 염전로 330, 주안 J Tower 1차 지식산업센터 1211호 (주안동)인천광역시 미추홀구 주안동 5-2 주안 J Tower 1차 지식산업센터 1211호<NA>
4950식품소분업주식회사 에스엔비인천광역시 미추홀구 염창로 58, 주안cgv A동 지하1층 38호 (주안동)인천광역시 미추홀구 주안동 30-1 주안cgv<NA>
5051식품소분업(주)이플푸드인천광역시 미추홀구 방축로 312, 8층 11,12호 (주안동)인천광역시 미추홀구 주안동 1385-101688-7602
5152식품소분업이지누들인천광역시 미추홀구 방축로 312, 820호 (주안동)인천광역시 미추홀구 주안동 1385-10 820호<NA>
5253식품소분업제이앤케이(J＆K)컴퍼니인천광역시 미추홀구 연송로 38, 2층 2호 (도화동)인천광역시 미추홀구 도화동 24-7070-4156-3339
5354식품소분업소금창고인천광역시 미추홀구 주승로 22, 정진프라자 101-5호 (학익동)인천광역시 미추홀구 학익동 649 정진프라자 101-5호<NA>
5455식품소분업호랑인천광역시 미추홀구 인주대로320번길 21-34, 1층 우측호 (주안동)인천광역시 미추홀구 주안동 1418-83<NA>
5556식품소분업나눔기획인천광역시 미추홀구 염창로 109, 1층 102호 좌측호 (주안동)인천광역시 미추홀구 주안동 22-42<NA>
5657식품소분업라피네플레르인천광역시 미추홀구 미추홀대로 647, 2층 (주안동)인천광역시 미추홀구 주안동 481-36<NA>