Overview

Dataset statistics

Number of variables7
Number of observations98
Missing cells28
Missing cells (%)4.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.6 KiB
Average record size in memory58.3 B

Variable types

Numeric1
Categorical1
Text4
DateTime1

Dataset

Description인천광역시 서구의 집단급식소 식품판매업의 현황(업종명, 업소명, 소재지, 전화번호 등) 에 관하여 데이터를 제공합니다.
Author인천광역시 서구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15089504&srcSe=7661IVAWM27C61E190

Alerts

업종명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
소재지(지번) has 1 (1.0%) missing valuesMissing
전화번호 has 27 (27.6%) missing valuesMissing
연번 has unique valuesUnique
업소명 has unique valuesUnique

Reproduction

Analysis started2024-03-18 02:51:40.807684
Analysis finished2024-03-18 02:51:41.910816
Duration1.1 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct98
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49.5
Minimum1
Maximum98
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1014.0 B
2024-03-18T11:51:41.980659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.85
Q125.25
median49.5
Q373.75
95-th percentile93.15
Maximum98
Range97
Interquartile range (IQR)48.5

Descriptive statistics

Standard deviation28.434134
Coefficient of variation (CV)0.57442696
Kurtosis-1.2
Mean49.5
Median Absolute Deviation (MAD)24.5
Skewness0
Sum4851
Variance808.5
MonotonicityStrictly increasing
2024-03-18T11:51:42.108376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.0%
75 1
 
1.0%
73 1
 
1.0%
72 1
 
1.0%
71 1
 
1.0%
70 1
 
1.0%
69 1
 
1.0%
68 1
 
1.0%
67 1
 
1.0%
66 1
 
1.0%
Other values (88) 88
89.8%
ValueCountFrequency (%)
1 1
1.0%
2 1
1.0%
3 1
1.0%
4 1
1.0%
5 1
1.0%
6 1
1.0%
7 1
1.0%
8 1
1.0%
9 1
1.0%
10 1
1.0%
ValueCountFrequency (%)
98 1
1.0%
97 1
1.0%
96 1
1.0%
95 1
1.0%
94 1
1.0%
93 1
1.0%
92 1
1.0%
91 1
1.0%
90 1
1.0%
89 1
1.0%

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size916.0 B
집단급식소 식품판매업
98 

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 98
100.0%

Length

2024-03-18T11:51:42.220544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T11:51:42.294997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
집단급식소 98
50.0%
식품판매업 98
50.0%

업소명
Text

UNIQUE 

Distinct98
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size916.0 B
2024-03-18T11:51:42.463184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length15
Mean length6.8163265
Min length2

Characters and Unicode

Total characters668
Distinct characters157
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

Unique98 ?
Unique (%)100.0%

Sample

1st row(주)기린푸드시스템
2nd row(주)하나로푸드시스템
3rd row초원푸드
4th row검단농협
5th row다우리유통
ValueCountFrequency (%)
주식회사 4
 
3.7%
농업회사법인 3
 
2.8%
주)기린푸드시스템 1
 
0.9%
미추홀식품 1
 
0.9%
주)럭키마트 1
 
0.9%
다해에프앤비 1
 
0.9%
에이비씨푸드 1
 
0.9%
고도푸드 1
 
0.9%
주)란꾸이팡 1
 
0.9%
세명푸드 1
 
0.9%
Other values (92) 92
86.0%
2024-03-18T11:51:42.771230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
드 44
 
6.6%
주 43
 
6.4%
푸 43
 
6.4%
( 40
 
6.0%
) 40
 
6.0%
에 23
 
3.4%
이 18
 
2.7%
스 16
 
2.4%
식 15
 
2.2%
사 14
 
2.1%
Other values (147) 372
55.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 553
82.8%
Open Punctuation 41
 
6.1%
Close Punctuation 41
 
6.1%
Uppercase Letter 22
 
3.3%
Space Separator 9
 
1.3%
Dash Punctuation 1
 
0.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
드 44
 
8.0%
주 43
 
7.8%
푸 43
 
7.8%
에 23
 
4.2%
이 18
 
3.3%
스 16
 
2.9%
식 15
 
2.7%
사 14
 
2.5%
회 12
 
2.2%
씨 12
 
2.2%
Other values (129) 313
56.6%
Uppercase Letter
ValueCountFrequency (%)
F 3
13.6%
O 3
13.6%
S 3
13.6%
D 3
13.6%
Y 2
9.1%
J 2
9.1%
E 2
9.1%
K 1
 
4.5%
M 1
 
4.5%
T 1
 
4.5%
Open Punctuation
ValueCountFrequency (%)
( 40
97.6%
[ 1
 
2.4%
Close Punctuation
ValueCountFrequency (%)
) 40
97.6%
] 1
 
2.4%
Space Separator
ValueCountFrequency (%)
9
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 553
82.8%
Common 93
 
13.9%
Latin 22
 
3.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
드 44
 
8.0%
주 43
 
7.8%
푸 43
 
7.8%
에 23
 
4.2%
이 18
 
3.3%
스 16
 
2.9%
식 15
 
2.7%
사 14
 
2.5%
회 12
 
2.2%
씨 12
 
2.2%
Other values (129) 313
56.6%
Latin
ValueCountFrequency (%)
F 3
13.6%
O 3
13.6%
S 3
13.6%
D 3
13.6%
Y 2
9.1%
J 2
9.1%
E 2
9.1%
K 1
 
4.5%
M 1
 
4.5%
T 1
 
4.5%
Common
ValueCountFrequency (%)
( 40
43.0%
) 40
43.0%
9
 
9.7%
- 1
 
1.1%
& 1
 
1.1%
] 1
 
1.1%
[ 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 553
82.8%
ASCII 115
 
17.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
드 44
 
8.0%
주 43
 
7.8%
푸 43
 
7.8%
에 23
 
4.2%
이 18
 
3.3%
스 16
 
2.9%
식 15
 
2.7%
사 14
 
2.5%
회 12
 
2.2%
씨 12
 
2.2%
Other values (129) 313
56.6%
ASCII
ValueCountFrequency (%)
( 40
34.8%
) 40
34.8%
9
 
7.8%
F 3
 
2.6%
O 3
 
2.6%
S 3
 
2.6%
D 3
 
2.6%
Y 2
 
1.7%
J 2
 
1.7%
E 2
 
1.7%
Other values (8) 8
 
7.0%

소재지(도로명)
Text

Distinct97
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size916.0 B
2024-03-18T11:51:43.063745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length41.5
Mean length32.255102
Min length15

Characters and Unicode

Total characters3161
Distinct characters126
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

Unique96 ?
Unique (%)98.0%

Sample

1st row인천광역시 서구 장고개로238번길 33-1 (가좌동)
2nd row인천광역시 서구 경서로45번길 8-10 (경서동, 744-10)
3rd row인천광역시 서구 승학로402번길 29-5 (검암동)
4th row인천광역시 서구 대곡로 71
5th row인천광역시 서구 봉수대로501번길 21, 1층 (원창동)
ValueCountFrequency (%)
인천광역시 98
 
15.9%
서구 98
 
15.9%
가좌동 34
 
5.5%
1층 28
 
4.5%
검암동 11
 
1.8%
2층 10
 
1.6%
석남동 9
 
1.5%
36 7
 
1.1%
원창동 6
 
1.0%
일부 6
 
1.0%
Other values (197) 310
50.2%
2024-03-18T11:51:43.408486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
519
 
16.4%
1 162
 
5.1%
동 116
 
3.7%
서 111
 
3.5%
) 107
 
3.4%
( 106
 
3.4%
, 102
 
3.2%
천 102
 
3.2%
인 100
 
3.2%
광 98
 
3.1%
Other values (116) 1638
51.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1688
53.4%
Decimal Number 594
 
18.8%
Space Separator 519
 
16.4%
Close Punctuation 107
 
3.4%
Open Punctuation 106
 
3.4%
Other Punctuation 102
 
3.2%
Dash Punctuation 36
 
1.1%
Uppercase Letter 8
 
0.3%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 116
 
6.9%
서 111
 
6.6%
천 102
 
6.0%
인 100
 
5.9%
광 98
 
5.8%
역 98
 
5.8%
시 98
 
5.8%
구 98
 
5.8%
로 98
 
5.8%
길 73
 
4.3%
Other values (95) 696
41.2%
Decimal Number
ValueCountFrequency (%)
1 162
27.3%
2 84
14.1%
3 71
12.0%
0 65
10.9%
6 40
 
6.7%
4 39
 
6.6%
7 39
 
6.6%
5 36
 
6.1%
9 31
 
5.2%
8 27
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
A 4
50.0%
B 1
 
12.5%
G 1
 
12.5%
J 1
 
12.5%
C 1
 
12.5%
Space Separator
ValueCountFrequency (%)
519
100.0%
Close Punctuation
ValueCountFrequency (%)
) 107
100.0%
Open Punctuation
ValueCountFrequency (%)
( 106
100.0%
Other Punctuation
ValueCountFrequency (%)
, 102
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 36
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1688
53.4%
Common 1465
46.3%
Latin 8
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 116
 
6.9%
서 111
 
6.6%
천 102
 
6.0%
인 100
 
5.9%
광 98
 
5.8%
역 98
 
5.8%
시 98
 
5.8%
구 98
 
5.8%
로 98
 
5.8%
길 73
 
4.3%
Other values (95) 696
41.2%
Common
ValueCountFrequency (%)
519
35.4%
1 162
 
11.1%
) 107
 
7.3%
( 106
 
7.2%
, 102
 
7.0%
2 84
 
5.7%
3 71
 
4.8%
0 65
 
4.4%
6 40
 
2.7%
4 39
 
2.7%
Other values (6) 170
 
11.6%
Latin
ValueCountFrequency (%)
A 4
50.0%
B 1
 
12.5%
G 1
 
12.5%
J 1
 
12.5%
C 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1688
53.4%
ASCII 1473
46.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
519
35.2%
1 162
 
11.0%
) 107
 
7.3%
( 106
 
7.2%
, 102
 
6.9%
2 84
 
5.7%
3 71
 
4.8%
0 65
 
4.4%
6 40
 
2.7%
4 39
 
2.6%
Other values (11) 178
 
12.1%
Hangul
ValueCountFrequency (%)
동 116
 
6.9%
서 111
 
6.6%
천 102
 
6.0%
인 100
 
5.9%
광 98
 
5.8%
역 98
 
5.8%
시 98
 
5.8%
구 98
 
5.8%
로 98
 
5.8%
길 73
 
4.3%
Other values (95) 696
41.2%

소재지(지번)
Text

MISSING 

Distinct96
Distinct (%)99.0%
Missing1
Missing (%)1.0%
Memory size916.0 B
2024-03-18T11:51:43.703826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length32
Mean length24.298969
Min length17

Characters and Unicode

Total characters2357
Distinct characters104
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

Unique95 ?
Unique (%)97.9%

Sample

1st row인천광역시 서구 가좌동 289-25
2nd row인천광역시 서구 경서동 744-10
3rd row인천광역시 서구 검암동 654-12
4th row인천광역시 서구 대곡동 679 외 1필지
5th row인천광역시 서구 원창동 42-6 1층
ValueCountFrequency (%)
인천광역시 97
19.7%
서구 97
19.7%
가좌동 35
 
7.1%
1층 20
 
4.1%
검암동 12
 
2.4%
2층 9
 
1.8%
석남동 9
 
1.8%
경서동 6
 
1.2%
일부 6
 
1.2%
심곡동 6
 
1.2%
Other values (134) 195
39.6%
2024-03-18T11:51:44.146299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
479
20.3%
1 116
 
4.9%
동 110
 
4.7%
서 103
 
4.4%
천 100
 
4.2%
인 99
 
4.2%
2 99
 
4.2%
광 97
 
4.1%
역 97
 
4.1%
시 97
 
4.1%
Other values (94) 960
40.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1187
50.4%
Decimal Number 562
23.8%
Space Separator 479
20.3%
Dash Punctuation 88
 
3.7%
Close Punctuation 13
 
0.6%
Open Punctuation 11
 
0.5%
Other Punctuation 9
 
0.4%
Uppercase Letter 7
 
0.3%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 110
 
9.3%
서 103
 
8.7%
천 100
 
8.4%
인 99
 
8.3%
광 97
 
8.2%
역 97
 
8.2%
시 97
 
8.2%
구 97
 
8.2%
층 47
 
4.0%
가 38
 
3.2%
Other values (73) 302
25.4%
Decimal Number
ValueCountFrequency (%)
1 116
20.6%
2 99
17.6%
3 69
12.3%
4 50
8.9%
5 43
 
7.7%
0 42
 
7.5%
7 42
 
7.5%
6 39
 
6.9%
9 32
 
5.7%
8 30
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
A 3
42.9%
J 1
 
14.3%
B 1
 
14.3%
G 1
 
14.3%
C 1
 
14.3%
Space Separator
ValueCountFrequency (%)
479
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 88
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Other Punctuation
ValueCountFrequency (%)
, 9
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1187
50.4%
Common 1163
49.3%
Latin 7
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 110
 
9.3%
서 103
 
8.7%
천 100
 
8.4%
인 99
 
8.3%
광 97
 
8.2%
역 97
 
8.2%
시 97
 
8.2%
구 97
 
8.2%
층 47
 
4.0%
가 38
 
3.2%
Other values (73) 302
25.4%
Common
ValueCountFrequency (%)
479
41.2%
1 116
 
10.0%
2 99
 
8.5%
- 88
 
7.6%
3 69
 
5.9%
4 50
 
4.3%
5 43
 
3.7%
0 42
 
3.6%
7 42
 
3.6%
6 39
 
3.4%
Other values (6) 96
 
8.3%
Latin
ValueCountFrequency (%)
A 3
42.9%
J 1
 
14.3%
B 1
 
14.3%
G 1
 
14.3%
C 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1187
50.4%
ASCII 1170
49.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
479
40.9%
1 116
 
9.9%
2 99
 
8.5%
- 88
 
7.5%
3 69
 
5.9%
4 50
 
4.3%
5 43
 
3.7%
0 42
 
3.6%
7 42
 
3.6%
6 39
 
3.3%
Other values (11) 103
 
8.8%
Hangul
ValueCountFrequency (%)
동 110
 
9.3%
서 103
 
8.7%
천 100
 
8.4%
인 99
 
8.3%
광 97
 
8.2%
역 97
 
8.2%
시 97
 
8.2%
구 97
 
8.2%
층 47
 
4.0%
가 38
 
3.2%
Other values (73) 302
25.4%

전화번호
Text

MISSING 

Distinct71
Distinct (%)100.0%
Missing27
Missing (%)27.6%
Memory size916.0 B
2024-03-18T11:51:44.378779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.056338
Min length12

Characters and Unicode

Total characters856
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

Unique71 ?
Unique (%)100.0%

Sample

1st row032-584-7979
2nd row032-424-0251
3rd row032-564-6351
4th row032-565-5176
5th row032-507-1418
ValueCountFrequency (%)
032-584-7979 1
 
1.4%
031-983-4342 1
 
1.4%
032-574-8767 1
 
1.4%
032-277-7790 1
 
1.4%
032-577-1028 1
 
1.4%
032-575-7817 1
 
1.4%
032-891-5424 1
 
1.4%
032-937-7805 1
 
1.4%
032-584-7150 1
 
1.4%
032-573-6256 1
 
1.4%
Other values (61) 61
85.9%
2024-03-18T11:51:44.699672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 142
16.6%
0 117
13.7%
3 106
12.4%
2 105
12.3%
5 84
9.8%
7 68
7.9%
6 61
7.1%
8 53
 
6.2%
4 47
 
5.5%
1 43
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 714
83.4%
Dash Punctuation 142
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 117
16.4%
3 106
14.8%
2 105
14.7%
5 84
11.8%
7 68
9.5%
6 61
8.5%
8 53
7.4%
4 47
6.6%
1 43
 
6.0%
9 30
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 142
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 856
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 142
16.6%
0 117
13.7%
3 106
12.4%
2 105
12.3%
5 84
9.8%
7 68
7.9%
6 61
7.1%
8 53
 
6.2%
4 47
 
5.5%
1 43
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 856
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 142
16.6%
0 117
13.7%
3 106
12.4%
2 105
12.3%
5 84
9.8%
7 68
7.9%
6 61
7.1%
8 53
 
6.2%
4 47
 
5.5%
1 43
 
5.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size916.0 B
Minimum2022-09-06 00:00:00
Maximum2022-09-06 00:00:00
2024-03-18T11:51:44.796942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:51:44.872358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-03-18T11:51:41.358357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-18T11:51:44.927906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업소명소재지(도로명)소재지(지번)전화번호
연번1.0001.0000.9340.9251.000
업소명1.0001.0001.0001.0001.000
소재지(도로명)0.9341.0001.0001.0001.000
소재지(지번)0.9251.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.000

Missing values

2024-03-18T11:51:41.687334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T11:51:41.788181image/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.
2024-03-18T11:51:41.871166image/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

연번업종명업소명소재지(도로명)소재지(지번)전화번호데이터기준일자
01집단급식소 식품판매업(주)기린푸드시스템인천광역시 서구 장고개로238번길 33-1 (가좌동)인천광역시 서구 가좌동 289-25032-584-79792022-09-06
12집단급식소 식품판매업(주)하나로푸드시스템인천광역시 서구 경서로45번길 8-10 (경서동, 744-10)인천광역시 서구 경서동 744-10032-424-02512022-09-06
23집단급식소 식품판매업초원푸드인천광역시 서구 승학로402번길 29-5 (검암동)인천광역시 서구 검암동 654-12032-564-63512022-09-06
34집단급식소 식품판매업검단농협인천광역시 서구 대곡로 71인천광역시 서구 대곡동 679 외 1필지032-565-51762022-09-06
45집단급식소 식품판매업다우리유통인천광역시 서구 봉수대로501번길 21, 1층 (원창동)인천광역시 서구 원창동 42-6 1층032-507-14182022-09-06
56집단급식소 식품판매업(주)혜진수산인천광역시 서구 소담2로 36, 1동 1층 (금곡동)인천광역시 서구 금곡동 0 주식회사혜진수산032-556-34562022-09-06
67집단급식소 식품판매업푸른유통인천광역시 서구 원적로124번길 33인천광역시 서구 가좌동 81-59 범양상가 116호<NA>2022-09-06
78집단급식소 식품판매업다온푸드인천광역시 서구 도요지로227번길 4-13 (검암동)인천광역시 서구 검암동 664-6032-565-75862022-09-06
89집단급식소 식품판매업(주)우일푸드인천광역시 서구 장고개로238번길 33 (가좌동)인천광역시 서구 가좌동 289-27032-438-80772022-09-06
910집단급식소 식품판매업(주)에스알씨인천광역시 서구 원적로7번길 40 (가좌동)인천광역시 서구 가좌동 263-6032-575-14512022-09-06
연번업종명업소명소재지(도로명)소재지(지번)전화번호데이터기준일자
8889집단급식소 식품판매업농업회사법인주식회사성현친환경인천광역시 서구 북항로177번길 26, A동 (원창동)인천광역시 서구 원창동 393-242<NA>2022-09-06
8990집단급식소 식품판매업(주)위드식품인천광역시 서구 가정로68번길 6, 1층 (가좌동)인천광역시 서구 가좌동 159-13032-573-24062022-09-06
9091집단급식소 식품판매업오렌지에프에스인천광역시 서구 원당대로301번길 2, 103,104호 (왕길동)인천광역시 서구 왕길동 596-1032-568-41492022-09-06
9192집단급식소 식품판매업주식회사팜푸드인천광역시 서구 심곡로8번길 3-3, 1층 (심곡동)인천광역시 서구 심곡동 339-2 1층032-562-27902022-09-06
9293집단급식소 식품판매업최가인천광역시 서구 건지로 120-10, 2층 A호 (가좌동)인천광역시 서구 가좌동 173-459 2층 A호<NA>2022-09-06
9394집단급식소 식품판매업동호유통인천광역시 서구 건지로 120-10, 2층 B호 (가좌동)인천광역시 서구 가좌동 173-459 2층 B호<NA>2022-09-06
9495집단급식소 식품판매업이석푸드인천광역시 서구 건지로 120-10, 2층 C호 (가좌동)인천광역시 서구 가좌동 173-459 2층 C호<NA>2022-09-06
9596집단급식소 식품판매업다온인천광역시 서구 백범로934번길 30-12, 1동 2층 (가좌동)인천광역시 서구 가좌동 178-460<NA>2022-09-06
9697집단급식소 식품판매업정운에프에스(FS)인천광역시 서구 봉수대로182번길 15, 2층 (가좌동)인천광역시 서구 가좌동 178-425 2층<NA>2022-09-06
9798집단급식소 식품판매업푸드존인천광역시 서구 봉수대로182번길 15, 2층 일부호 (가좌동)인천광역시 서구 가좌동 178-425 2층 일부호<NA>2022-09-06