Overview

Dataset statistics

Number of variables6
Number of observations75
Missing cells28
Missing cells (%)6.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.7 KiB
Average record size in memory50.8 B

Variable types

Numeric1
Categorical1
Text4

Dataset

Description인천광역시 남동구 집단급식소 식품판매업에 관한 데이터로 업종명, 업소명, 소재지(도로명, 지번주소), 위경도 좌표, 소재지전화번호 등을 제공합니다.
Author인천광역시 남동구
URLhttps://www.data.go.kr/data/15113511/fileData.do

Alerts

업종명 has constant value ""Constant
소재지전화 has 28 (37.3%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-04-21 02:22:36.802173
Analysis finished2024-04-21 02:22:39.048729
Duration2.25 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct75
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38
Minimum1
Maximum75
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size807.0 B
2024-04-21T11:22:39.151721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.7
Q119.5
median38
Q356.5
95-th percentile71.3
Maximum75
Range74
Interquartile range (IQR)37

Descriptive statistics

Standard deviation21.794495
Coefficient of variation (CV)0.57353933
Kurtosis-1.2
Mean38
Median Absolute Deviation (MAD)19
Skewness0
Sum2850
Variance475
MonotonicityStrictly increasing
2024-04-21T11:22:39.300252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.3%
49 1
 
1.3%
56 1
 
1.3%
55 1
 
1.3%
54 1
 
1.3%
53 1
 
1.3%
52 1
 
1.3%
51 1
 
1.3%
50 1
 
1.3%
48 1
 
1.3%
Other values (65) 65
86.7%
ValueCountFrequency (%)
1 1
1.3%
2 1
1.3%
3 1
1.3%
4 1
1.3%
5 1
1.3%
6 1
1.3%
7 1
1.3%
8 1
1.3%
9 1
1.3%
10 1
1.3%
ValueCountFrequency (%)
75 1
1.3%
74 1
1.3%
73 1
1.3%
72 1
1.3%
71 1
1.3%
70 1
1.3%
69 1
1.3%
68 1
1.3%
67 1
1.3%
66 1
1.3%

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size732.0 B
집단급식소 식품판매업
75 

Length

Max length11
Median length11
Mean length11
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row집단급식소 식품판매업
2nd row집단급식소 식품판매업
3rd row집단급식소 식품판매업
4th row집단급식소 식품판매업
5th row집단급식소 식품판매업

Common Values

ValueCountFrequency (%)
집단급식소 식품판매업 75
100.0%

Length

2024-04-21T11:22:39.436893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T11:22:39.534322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
집단급식소 75
50.0%
식품판매업 75
50.0%

업소명
Text

Distinct74
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size732.0 B
2024-04-21T11:22:39.722228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11
Mean length5.8666667
Min length2

Characters and Unicode

Total characters440
Distinct characters141
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique73 ?
Unique (%)97.3%

Sample

1st row대광푸드
2nd row힘찬푸드
3rd row한별급식
4th row오성푸드시스템
5th row(주)이프유캔
ValueCountFrequency (%)
주식회사 6
 
7.1%
금란 2
 
2.4%
홍익식품 2
 
2.4%
대광푸드 1
 
1.2%
안양상회(인농303 1
 
1.2%
더푸드팜 1
 
1.2%
주)남영씨푸드 1
 
1.2%
제일종합물류 1
 
1.2%
주)그린푸드 1
 
1.2%
엔에이치푸드 1
 
1.2%
Other values (68) 68
80.0%
2024-04-21T11:22:40.085538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
드 31
 
7.0%
푸 31
 
7.0%
주 23
 
5.2%
) 17
 
3.9%
식 17
 
3.9%
( 17
 
3.9%
회 12
 
2.7%
이 12
 
2.7%
스 12
 
2.7%
10
 
2.3%
Other values (131) 258
58.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 388
88.2%
Close Punctuation 17
 
3.9%
Open Punctuation 17
 
3.9%
Space Separator 10
 
2.3%
Decimal Number 6
 
1.4%
Uppercase Letter 2
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
드 31
 
8.0%
푸 31
 
8.0%
주 23
 
5.9%
식 17
 
4.4%
회 12
 
3.1%
이 12
 
3.1%
스 12
 
3.1%
에 9
 
2.3%
사 9
 
2.3%
농 6
 
1.5%
Other values (122) 226
58.2%
Decimal Number
ValueCountFrequency (%)
3 3
50.0%
0 1
 
16.7%
2 1
 
16.7%
7 1
 
16.7%
Uppercase Letter
ValueCountFrequency (%)
F 1
50.0%
S 1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%
Space Separator
ValueCountFrequency (%)
10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 388
88.2%
Common 50
 
11.4%
Latin 2
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
드 31
 
8.0%
푸 31
 
8.0%
주 23
 
5.9%
식 17
 
4.4%
회 12
 
3.1%
이 12
 
3.1%
스 12
 
3.1%
에 9
 
2.3%
사 9
 
2.3%
농 6
 
1.5%
Other values (122) 226
58.2%
Common
ValueCountFrequency (%)
) 17
34.0%
( 17
34.0%
10
20.0%
3 3
 
6.0%
0 1
 
2.0%
2 1
 
2.0%
7 1
 
2.0%
Latin
ValueCountFrequency (%)
F 1
50.0%
S 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 388
88.2%
ASCII 52
 
11.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
드 31
 
8.0%
푸 31
 
8.0%
주 23
 
5.9%
식 17
 
4.4%
회 12
 
3.1%
이 12
 
3.1%
스 12
 
3.1%
에 9
 
2.3%
사 9
 
2.3%
농 6
 
1.5%
Other values (122) 226
58.2%
ASCII
ValueCountFrequency (%)
) 17
32.7%
( 17
32.7%
10
19.2%
3 3
 
5.8%
0 1
 
1.9%
F 1
 
1.9%
2 1
 
1.9%
7 1
 
1.9%
S 1
 
1.9%

소재지(도로명)
Text

Distinct72
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Memory size732.0 B
2024-04-21T11:22:40.365292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length42
Mean length36.466667
Min length27

Characters and Unicode

Total characters2735
Distinct characters128
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

Unique70 ?
Unique (%)93.3%

Sample

1st row인천광역시 남동구 장자로6번길 83, 1층 (장수동)
2nd row인천광역시 남동구 함박뫼로377번길 68, 부1동 2층 일부호 (남촌동)
3rd row인천광역시 남동구 배려터로 54, 1층 일부,2층 일부호 (수산동)
4th row인천광역시 남동구 인하로521번길 10-5, 1층 전부호 (구월동)
5th row인천광역시 남동구 논고개로 403, 1층일부 (도림동)
ValueCountFrequency (%)
인천광역시 75
 
13.3%
남동구 75
 
13.3%
1층 55
 
9.8%
일부호 30
 
5.3%
고잔동 13
 
2.3%
남촌동 10
 
1.8%
만수동 9
 
1.6%
도림동 9
 
1.6%
수산동 8
 
1.4%
2층 8
 
1.4%
Other values (169) 271
48.1%
2024-04-21T11:22:40.781727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
488
 
17.8%
동 182
 
6.7%
1 129
 
4.7%
남 107
 
3.9%
구 87
 
3.2%
시 85
 
3.1%
, 82
 
3.0%
인 78
 
2.9%
층 78
 
2.9%
) 76
 
2.8%
Other values (118) 1343
49.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1561
57.1%
Space Separator 488
 
17.8%
Decimal Number 421
 
15.4%
Other Punctuation 82
 
3.0%
Close Punctuation 76
 
2.8%
Open Punctuation 76
 
2.8%
Dash Punctuation 21
 
0.8%
Uppercase Letter 10
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 182
 
11.7%
남 107
 
6.9%
구 87
 
5.6%
시 85
 
5.4%
인 78
 
5.0%
층 78
 
5.0%
로 75
 
4.8%
역 75
 
4.8%
천 75
 
4.8%
광 75
 
4.8%
Other values (100) 644
41.3%
Decimal Number
ValueCountFrequency (%)
1 129
30.6%
2 64
15.2%
3 48
 
11.4%
5 38
 
9.0%
0 36
 
8.6%
4 27
 
6.4%
6 23
 
5.5%
7 23
 
5.5%
8 20
 
4.8%
9 13
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
B 7
70.0%
A 2
 
20.0%
C 1
 
10.0%
Space Separator
ValueCountFrequency (%)
488
100.0%
Other Punctuation
ValueCountFrequency (%)
, 82
100.0%
Close Punctuation
ValueCountFrequency (%)
) 76
100.0%
Open Punctuation
ValueCountFrequency (%)
( 76
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1561
57.1%
Common 1164
42.6%
Latin 10
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 182
 
11.7%
남 107
 
6.9%
구 87
 
5.6%
시 85
 
5.4%
인 78
 
5.0%
층 78
 
5.0%
로 75
 
4.8%
역 75
 
4.8%
천 75
 
4.8%
광 75
 
4.8%
Other values (100) 644
41.3%
Common
ValueCountFrequency (%)
488
41.9%
1 129
 
11.1%
, 82
 
7.0%
) 76
 
6.5%
( 76
 
6.5%
2 64
 
5.5%
3 48
 
4.1%
5 38
 
3.3%
0 36
 
3.1%
4 27
 
2.3%
Other values (5) 100
 
8.6%
Latin
ValueCountFrequency (%)
B 7
70.0%
A 2
 
20.0%
C 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1561
57.1%
ASCII 1174
42.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
488
41.6%
1 129
 
11.0%
, 82
 
7.0%
) 76
 
6.5%
( 76
 
6.5%
2 64
 
5.5%
3 48
 
4.1%
5 38
 
3.2%
0 36
 
3.1%
4 27
 
2.3%
Other values (8) 110
 
9.4%
Hangul
ValueCountFrequency (%)
동 182
 
11.7%
남 107
 
6.9%
구 87
 
5.6%
시 85
 
5.4%
인 78
 
5.0%
층 78
 
5.0%
로 75
 
4.8%
역 75
 
4.8%
천 75
 
4.8%
광 75
 
4.8%
Other values (100) 644
41.3%

소재지(지번)
Text

Distinct74
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size732.0 B
2024-04-21T11:22:41.080656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length41
Mean length30.106667
Min length19

Characters and Unicode

Total characters2258
Distinct characters110
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

Unique73 ?
Unique (%)97.3%

Sample

1st row인천광역시 남동구 장수동 788-16 1층
2nd row인천광역시 남동구 남촌동 626-1 부속1동 2층일부
3rd row인천광역시 남동구 수산동 323 1층 일부, 2층 일부
4th row인천광역시 남동구 구월동 1170-11 ,1층전부호
5th row인천광역시 남동구 도림동 96-9
ValueCountFrequency (%)
인천광역시 75
 
16.3%
남동구 75
 
16.3%
1층 31
 
6.8%
고잔동 13
 
2.8%
일부호 12
 
2.6%
남촌동 10
 
2.2%
일부 10
 
2.2%
만수동 9
 
2.0%
도림동 9
 
2.0%
1층일부 8
 
1.7%
Other values (133) 207
45.1%
2024-04-21T11:22:41.494470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
449
19.9%
동 173
 
7.7%
1 150
 
6.6%
남 92
 
4.1%
구 83
 
3.7%
시 80
 
3.5%
인 77
 
3.4%
역 75
 
3.3%
광 75
 
3.3%
천 75
 
3.3%
Other values (100) 929
41.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1227
54.3%
Decimal Number 473
 
20.9%
Space Separator 449
 
19.9%
Dash Punctuation 70
 
3.1%
Open Punctuation 11
 
0.5%
Close Punctuation 11
 
0.5%
Other Punctuation 10
 
0.4%
Uppercase Letter 7
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 173
14.1%
남 92
 
7.5%
구 83
 
6.8%
시 80
 
6.5%
인 77
 
6.3%
역 75
 
6.1%
광 75
 
6.1%
천 75
 
6.1%
층 64
 
5.2%
부 52
 
4.2%
Other values (83) 381
31.1%
Decimal Number
ValueCountFrequency (%)
1 150
31.7%
2 53
 
11.2%
3 44
 
9.3%
6 42
 
8.9%
0 40
 
8.5%
7 39
 
8.2%
5 30
 
6.3%
4 27
 
5.7%
8 27
 
5.7%
9 21
 
4.4%
Uppercase Letter
ValueCountFrequency (%)
B 5
71.4%
A 2
 
28.6%
Space Separator
ValueCountFrequency (%)
449
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 70
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Other Punctuation
ValueCountFrequency (%)
, 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1227
54.3%
Common 1024
45.3%
Latin 7
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 173
14.1%
남 92
 
7.5%
구 83
 
6.8%
시 80
 
6.5%
인 77
 
6.3%
역 75
 
6.1%
광 75
 
6.1%
천 75
 
6.1%
층 64
 
5.2%
부 52
 
4.2%
Other values (83) 381
31.1%
Common
ValueCountFrequency (%)
449
43.8%
1 150
 
14.6%
- 70
 
6.8%
2 53
 
5.2%
3 44
 
4.3%
6 42
 
4.1%
0 40
 
3.9%
7 39
 
3.8%
5 30
 
2.9%
4 27
 
2.6%
Other values (5) 80
 
7.8%
Latin
ValueCountFrequency (%)
B 5
71.4%
A 2
 
28.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1227
54.3%
ASCII 1031
45.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
449
43.5%
1 150
 
14.5%
- 70
 
6.8%
2 53
 
5.1%
3 44
 
4.3%
6 42
 
4.1%
0 40
 
3.9%
7 39
 
3.8%
5 30
 
2.9%
4 27
 
2.6%
Other values (7) 87
 
8.4%
Hangul
ValueCountFrequency (%)
동 173
14.1%
남 92
 
7.5%
구 83
 
6.8%
시 80
 
6.5%
인 77
 
6.3%
역 75
 
6.1%
광 75
 
6.1%
천 75
 
6.1%
층 64
 
5.2%
부 52
 
4.2%
Other values (83) 381
31.1%

소재지전화
Text

MISSING 

Distinct47
Distinct (%)100.0%
Missing28
Missing (%)37.3%
Memory size732.0 B
2024-04-21T11:22:41.727161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.148936
Min length12

Characters and Unicode

Total characters571
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

Unique47 ?
Unique (%)100.0%

Sample

1st row032-469-1457
2nd row070-4406-7915
3rd row032-424-0140
4th row070-8990-5022
5th row032-822-0503
ValueCountFrequency (%)
032-469-1457 1
 
2.1%
070-7005-5222 1
 
2.1%
070-4647-2280 1
 
2.1%
032-428-6008 1
 
2.1%
032-422-0434 1
 
2.1%
070-8688-0636 1
 
2.1%
032-425-2702 1
 
2.1%
032-471-1144 1
 
2.1%
070-4334-5840 1
 
2.1%
070-4114-1510 1
 
2.1%
Other values (37) 37
78.7%
2024-04-21T11:22:42.097973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 94
16.5%
0 87
15.2%
2 81
14.2%
3 72
12.6%
4 47
8.2%
5 42
7.4%
7 38
6.7%
1 37
 
6.5%
8 32
 
5.6%
6 22
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 477
83.5%
Dash Punctuation 94
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 87
18.2%
2 81
17.0%
3 72
15.1%
4 47
9.9%
5 42
8.8%
7 38
8.0%
1 37
7.8%
8 32
 
6.7%
6 22
 
4.6%
9 19
 
4.0%
Dash Punctuation
ValueCountFrequency (%)
- 94
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 571
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 94
16.5%
0 87
15.2%
2 81
14.2%
3 72
12.6%
4 47
8.2%
5 42
7.4%
7 38
6.7%
1 37
 
6.5%
8 32
 
5.6%
6 22
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 571
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 94
16.5%
0 87
15.2%
2 81
14.2%
3 72
12.6%
4 47
8.2%
5 42
7.4%
7 38
6.7%
1 37
 
6.5%
8 32
 
5.6%
6 22
 
3.9%

Interactions

2024-04-21T11:22:38.728512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T11:22:42.229662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업소명소재지(도로명)소재지(지번)소재지전화
연번1.0000.9270.9010.9271.000
업소명0.9271.0001.0001.0001.000
소재지(도로명)0.9011.0001.0001.0001.000
소재지(지번)0.9271.0001.0001.0001.000
소재지전화1.0001.0001.0001.0001.000

Missing values

2024-04-21T11:22:38.901686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T11:22:39.005292image/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
01집단급식소 식품판매업대광푸드인천광역시 남동구 장자로6번길 83, 1층 (장수동)인천광역시 남동구 장수동 788-16 1층032-469-1457
12집단급식소 식품판매업힘찬푸드인천광역시 남동구 함박뫼로377번길 68, 부1동 2층 일부호 (남촌동)인천광역시 남동구 남촌동 626-1 부속1동 2층일부070-4406-7915
23집단급식소 식품판매업한별급식인천광역시 남동구 배려터로 54, 1층 일부,2층 일부호 (수산동)인천광역시 남동구 수산동 323 1층 일부, 2층 일부<NA>
34집단급식소 식품판매업오성푸드시스템인천광역시 남동구 인하로521번길 10-5, 1층 전부호 (구월동)인천광역시 남동구 구월동 1170-11 ,1층전부호032-424-0140
45집단급식소 식품판매업(주)이프유캔인천광역시 남동구 논고개로 403, 1층일부 (도림동)인천광역시 남동구 도림동 96-9070-8990-5022
56집단급식소 식품판매업미래농산인천광역시 남동구 논곡로85번길 5-4, 1층 (논현동)인천광역시 남동구 논현동 560-3 1층<NA>
67집단급식소 식품판매업주식회사 효찬인천광역시 남동구 능허대로 755, 1층 일부호 (고잔동)인천광역시 남동구 고잔동 729-6 1층 일부호032-822-0503
78집단급식소 식품판매업(주)루시키즈인천광역시 남동구 은청로 4-7, 남동공단산업용품상가 B동 3층 306호 (고잔동)인천광역시 남동구 고잔동 630 남동공단산업용품상가 B동 3층 306호032-579-1388
89집단급식소 식품판매업정훈상회인천광역시 남동구 남촌시장로 6, 남촌 농산물 도매시장 채소2동 1층 161호 (남촌동)인천광역시 남동구 남촌동 652 남촌 농산물 도매시장 채소2동-상1-7-73<NA>
910집단급식소 식품판매업금란인천광역시 남동구 덕골로 78-1, 1층 일부호 (도림동)인천광역시 남동구 도림동 526-3 1층 일부호<NA>
연번업종명업소명소재지(도로명)소재지(지번)소재지전화
6566집단급식소 식품판매업빛담은인천광역시 남동구 서판로 35, 지하1층 비01호 일부호 (만수동)인천광역시 남동구 만수동 1114 지하1층 비01호 일부호(빛담은 내)<NA>
6667집단급식소 식품판매업금란인천광역시 남동구 덕골로 78-1, 1층 일부호 (도림동)인천광역시 남동구 도림동 526-3 1층 일부호<NA>
6768집단급식소 식품판매업승리농산인천광역시 남동구 남촌로122번길 62-10, 1층 일부호 (남촌동)인천광역시 남동구 남촌동 352-18 1층 일부호<NA>
6869집단급식소 식품판매업학교급식전문인천광역시 남동구 장자로 13-1, 2층 일부호 (장수동)인천광역시 남동구 장수동 780-14 2층 일부호031-923-3043
6970집단급식소 식품판매업경성유통인천광역시 남동구 구월남로260번길 20, 1층 일부(2)호 (구월동)인천광역시 남동구 구월동 1239-17 1층 일부(2호)<NA>
7071집단급식소 식품판매업아이누리 남동인천광역시 남동구 도림로12번길 27, 1층 일부호 (도림동)인천광역시 남동구 도림동 661-12 1층 일부호(101호)<NA>
7172집단급식소 식품판매업영푸드인천광역시 남동구 만수서로37번길 56, 1층 일부호 (만수동)인천광역시 남동구 만수동 865-8 1층 일부호<NA>
7273집단급식소 식품판매업고래인천광역시 남동구 남촌로 108, 2층 (남촌동)인천광역시 남동구 남촌동 488-5 2층 전체<NA>
7374집단급식소 식품판매업현푸드인천광역시 남동구 만수서로29번길 5-6, 1층 일부호 (만수동)인천광역시 남동구 만수동 109-210 1층 일부<NA>
7475집단급식소 식품판매업다성에프에스(FS)인천광역시 남동구 백범로247번길 93-20, 1층 (만수동)인천광역시 남동구 만수동 906-11 1층<NA>