Overview

Dataset statistics

Number of variables5
Number of observations1114
Missing cells653
Missing cells (%)11.7%
Duplicate rows1
Duplicate rows (%)0.1%
Total size in memory43.6 KiB
Average record size in memory40.1 B

Variable types

Categorical1
Text4

Dataset

Description인천광역시 부평구 식품위생업 현황입니다.(업종명,업소명,소재지(도로명),소재지(지번),소재지전화)ex) 식품제조가공업,프리노을 주식회사,인천광역시 부평구 열우물로 149 (십정동 1층),인천광역시 부평구 십정동 118-5 1층,032-578-0109
Author인천광역시 부평구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15017393&srcSe=7661IVAWM27C61E190

Alerts

Dataset has 1 (0.1%) duplicate rowsDuplicates
소재지전화 has 653 (58.6%) missing valuesMissing

Reproduction

Analysis started2024-01-28 08:55:56.287569
Analysis finished2024-01-28 08:55:56.960211
Duration0.67 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

Distinct8
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size8.8 KiB
즉석판매제조가공업
526 
식품자동판매기영업
209 
식품제조가공업
135 
식품소분업
86 
유통전문판매업
79 
Other values (3)
79 

Length

Max length11
Median length9
Mean length8.2962298
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
즉석판매제조가공업 526
47.2%
식품자동판매기영업 209
 
18.8%
식품제조가공업 135
 
12.1%
식품소분업 86
 
7.7%
유통전문판매업 79
 
7.1%
기타식품판매업 39
 
3.5%
집단급식소 식품판매업 33
 
3.0%
용기.포장지제조업 7
 
0.6%

Length

2024-01-28T17:55:57.011627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T17:55:57.096719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
즉석판매제조가공업 526
45.9%
식품자동판매기영업 209
 
18.2%
식품제조가공업 135
 
11.8%
식품소분업 86
 
7.5%
유통전문판매업 79
 
6.9%
기타식품판매업 39
 
3.4%
집단급식소 33
 
2.9%
식품판매업 33
 
2.9%
용기.포장지제조업 7
 
0.6%

업소명
Text

Distinct1019
Distinct (%)91.5%
Missing0
Missing (%)0.0%
Memory size8.8 KiB
2024-01-28T17:55:57.302504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length22
Mean length7.0664273
Min length2

Characters and Unicode

Total characters7872
Distinct characters581
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique947 ?
Unique (%)85.0%

Sample

1st row부원식품
2nd row경인식품
3rd row미래식품
4th row영동식품
5th row대진농산
ValueCountFrequency (%)
주식회사 52
 
3.7%
세븐일레븐 15
 
1.1%
씨유 14
 
1.0%
지에스25 12
 
0.8%
이마트24 9
 
0.6%
나우커피 9
 
0.6%
무인카페 8
 
0.6%
부평점 7
 
0.5%
동서식품(주 7
 
0.5%
농업회사법인 6
 
0.4%
Other values (1122) 1273
90.2%
2024-01-28T17:55:57.607549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
299
 
3.8%
주 193
 
2.5%
점 190
 
2.4%
부 183
 
2.3%
) 170
 
2.2%
( 169
 
2.1%
스 156
 
2.0%
이 154
 
2.0%
식 143
 
1.8%
평 120
 
1.5%
Other values (571) 6095
77.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6798
86.4%
Space Separator 299
 
3.8%
Uppercase Letter 209
 
2.7%
Close Punctuation 170
 
2.2%
Open Punctuation 169
 
2.1%
Decimal Number 147
 
1.9%
Lowercase Letter 67
 
0.9%
Other Punctuation 11
 
0.1%
Modifier Symbol 1
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 193
 
2.8%
점 190
 
2.8%
부 183
 
2.7%
스 156
 
2.3%
이 154
 
2.3%
식 143
 
2.1%
평 120
 
1.8%
마 109
 
1.6%
산 105
 
1.5%
회 103
 
1.5%
Other values (512) 5342
78.6%
Uppercase Letter
ValueCountFrequency (%)
S 36
17.2%
G 22
 
10.5%
E 16
 
7.7%
A 14
 
6.7%
C 14
 
6.7%
O 14
 
6.7%
F 12
 
5.7%
B 8
 
3.8%
I 8
 
3.8%
R 8
 
3.8%
Other values (12) 57
27.3%
Lowercase Letter
ValueCountFrequency (%)
e 12
17.9%
o 8
11.9%
a 6
9.0%
s 5
 
7.5%
n 5
 
7.5%
i 4
 
6.0%
m 4
 
6.0%
l 3
 
4.5%
c 3
 
4.5%
r 3
 
4.5%
Other values (9) 14
20.9%
Decimal Number
ValueCountFrequency (%)
2 62
42.2%
5 41
27.9%
4 16
 
10.9%
1 10
 
6.8%
0 5
 
3.4%
3 5
 
3.4%
7 4
 
2.7%
6 2
 
1.4%
8 2
 
1.4%
Other Punctuation
ValueCountFrequency (%)
. 4
36.4%
& 3
27.3%
: 2
18.2%
, 2
18.2%
Space Separator
ValueCountFrequency (%)
299
100.0%
Close Punctuation
ValueCountFrequency (%)
) 170
100.0%
Open Punctuation
ValueCountFrequency (%)
( 169
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6797
86.3%
Common 798
 
10.1%
Latin 276
 
3.5%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 193
 
2.8%
점 190
 
2.8%
부 183
 
2.7%
스 156
 
2.3%
이 154
 
2.3%
식 143
 
2.1%
평 120
 
1.8%
마 109
 
1.6%
산 105
 
1.5%
회 103
 
1.5%
Other values (511) 5341
78.6%
Latin
ValueCountFrequency (%)
S 36
 
13.0%
G 22
 
8.0%
E 16
 
5.8%
A 14
 
5.1%
C 14
 
5.1%
O 14
 
5.1%
e 12
 
4.3%
F 12
 
4.3%
o 8
 
2.9%
B 8
 
2.9%
Other values (31) 120
43.5%
Common
ValueCountFrequency (%)
299
37.5%
) 170
21.3%
( 169
21.2%
2 62
 
7.8%
5 41
 
5.1%
4 16
 
2.0%
1 10
 
1.3%
0 5
 
0.6%
3 5
 
0.6%
. 4
 
0.5%
Other values (8) 17
 
2.1%
Han
ValueCountFrequency (%)
貞 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6797
86.3%
ASCII 1074
 
13.6%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
299
27.8%
) 170
15.8%
( 169
15.7%
2 62
 
5.8%
5 41
 
3.8%
S 36
 
3.4%
G 22
 
2.0%
4 16
 
1.5%
E 16
 
1.5%
A 14
 
1.3%
Other values (49) 229
21.3%
Hangul
ValueCountFrequency (%)
주 193
 
2.8%
점 190
 
2.8%
부 183
 
2.7%
스 156
 
2.3%
이 154
 
2.3%
식 143
 
2.1%
평 120
 
1.8%
마 109
 
1.6%
산 105
 
1.5%
회 103
 
1.5%
Other values (511) 5341
78.6%
CJK
ValueCountFrequency (%)
貞 1
100.0%

소재지(도로명)
Text

Distinct1034
Distinct (%)92.8%
Missing0
Missing (%)0.0%
Memory size8.8 KiB
2024-01-28T17:55:57.829417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length55
Mean length34.931777
Min length9

Characters and Unicode

Total characters38914
Distinct characters328
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique983 ?
Unique (%)88.2%

Sample

1st row인천광역시 부평구 정석로 10 (십정동)
2nd row인천광역시 부평구 수변로85번길 22-3 (부개동)
3rd row인천광역시 부평구 부흥북로58번길 23 (부평동)
4th row인천광역시 부평구 세월천로 216-11 (청천동,1층)
5th row인천광역시 부평구 원적로421번길 12 (산곡동)
ValueCountFrequency (%)
인천광역시 1094
 
14.1%
부평구 1094
 
14.1%
1층 520
 
6.7%
일부호 359
 
4.6%
부평동 311
 
4.0%
청천동 145
 
1.9%
십정동 137
 
1.8%
삼산동 115
 
1.5%
부개동 103
 
1.3%
산곡동 93
 
1.2%
Other values (1239) 3766
48.7%
2024-01-28T17:55:58.180038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6629
 
17.0%
부 2382
 
6.1%
1 1901
 
4.9%
평 1668
 
4.3%
동 1381
 
3.5%
천 1341
 
3.4%
인 1189
 
3.1%
시 1134
 
2.9%
( 1130
 
2.9%
) 1130
 
2.9%
Other values (318) 19029
48.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22216
57.1%
Space Separator 6629
 
17.0%
Decimal Number 6058
 
15.6%
Open Punctuation 1132
 
2.9%
Close Punctuation 1132
 
2.9%
Other Punctuation 1128
 
2.9%
Uppercase Letter 381
 
1.0%
Dash Punctuation 184
 
0.5%
Math Symbol 53
 
0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 2382
 
10.7%
평 1668
 
7.5%
동 1381
 
6.2%
천 1341
 
6.0%
인 1189
 
5.4%
시 1134
 
5.1%
광 1129
 
5.1%
역 1114
 
5.0%
로 1110
 
5.0%
구 1106
 
5.0%
Other values (273) 8662
39.0%
Uppercase Letter
ValueCountFrequency (%)
E 69
18.1%
A 49
12.9%
C 45
11.8%
B 38
10.0%
R 36
9.4%
P 26
 
6.8%
L 20
 
5.2%
U 19
 
5.0%
T 17
 
4.5%
N 15
 
3.9%
Other values (11) 47
12.3%
Decimal Number
ValueCountFrequency (%)
1 1901
31.4%
2 812
13.4%
3 681
 
11.2%
0 557
 
9.2%
4 487
 
8.0%
5 399
 
6.6%
7 342
 
5.6%
6 341
 
5.6%
8 295
 
4.9%
9 243
 
4.0%
Other Punctuation
ValueCountFrequency (%)
, 1124
99.6%
& 2
 
0.2%
/ 1
 
0.1%
@ 1
 
0.1%
Math Symbol
ValueCountFrequency (%)
< 20
37.7%
> 20
37.7%
~ 13
24.5%
Open Punctuation
ValueCountFrequency (%)
( 1130
99.8%
[ 2
 
0.2%
Close Punctuation
ValueCountFrequency (%)
) 1130
99.8%
] 2
 
0.2%
Space Separator
ValueCountFrequency (%)
6629
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 184
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 22214
57.1%
Common 16316
41.9%
Latin 382
 
1.0%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 2382
 
10.7%
평 1668
 
7.5%
동 1381
 
6.2%
천 1341
 
6.0%
인 1189
 
5.4%
시 1134
 
5.1%
광 1129
 
5.1%
역 1114
 
5.0%
로 1110
 
5.0%
구 1106
 
5.0%
Other values (271) 8660
39.0%
Common
ValueCountFrequency (%)
6629
40.6%
1 1901
 
11.7%
( 1130
 
6.9%
) 1130
 
6.9%
, 1124
 
6.9%
2 812
 
5.0%
3 681
 
4.2%
0 557
 
3.4%
4 487
 
3.0%
5 399
 
2.4%
Other values (13) 1466
 
9.0%
Latin
ValueCountFrequency (%)
E 69
18.1%
A 49
12.8%
C 45
11.8%
B 38
9.9%
R 36
9.4%
P 26
 
6.8%
L 20
 
5.2%
U 19
 
5.0%
T 17
 
4.5%
N 15
 
3.9%
Other values (12) 48
12.6%
Han
ValueCountFrequency (%)
德 1
50.0%
美 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22214
57.1%
ASCII 16698
42.9%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6629
39.7%
1 1901
 
11.4%
( 1130
 
6.8%
) 1130
 
6.8%
, 1124
 
6.7%
2 812
 
4.9%
3 681
 
4.1%
0 557
 
3.3%
4 487
 
2.9%
5 399
 
2.4%
Other values (35) 1848
 
11.1%
Hangul
ValueCountFrequency (%)
부 2382
 
10.7%
평 1668
 
7.5%
동 1381
 
6.2%
천 1341
 
6.0%
인 1189
 
5.4%
시 1134
 
5.1%
광 1129
 
5.1%
역 1114
 
5.0%
로 1110
 
5.0%
구 1106
 
5.0%
Other values (271) 8660
39.0%
CJK
ValueCountFrequency (%)
德 1
50.0%
美 1
50.0%

소재지(지번)
Text

Distinct1049
Distinct (%)94.2%
Missing0
Missing (%)0.0%
Memory size8.8 KiB
2024-01-28T17:55:58.615661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length45
Mean length27.492819
Min length18

Characters and Unicode

Total characters30627
Distinct characters299
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique997 ?
Unique (%)89.5%

Sample

1st row인천광역시 부평구 십정동 360-28
2nd row인천광역시 부평구 부개동 120-72
3rd row인천광역시 부평구 부평동 396-7
4th row인천광역시 부평구 청천동 68-110 1층
5th row인천광역시 부평구 산곡동 412-30
ValueCountFrequency (%)
인천광역시 1114
17.8%
부평구 1114
17.8%
부평동 340
 
5.4%
1층 308
 
4.9%
일부 174
 
2.8%
청천동 155
 
2.5%
십정동 142
 
2.3%
삼산동 128
 
2.0%
일부호 112
 
1.8%
산곡동 110
 
1.8%
Other values (1342) 2574
41.0%
2024-01-28T17:55:58.958319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6046
19.7%
부 1962
 
6.4%
1 1610
 
5.3%
평 1528
 
5.0%
천 1302
 
4.3%
동 1290
 
4.2%
인 1150
 
3.8%
역 1133
 
3.7%
시 1131
 
3.7%
광 1129
 
3.7%
Other values (289) 12346
40.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16761
54.7%
Decimal Number 6408
 
20.9%
Space Separator 6046
 
19.7%
Dash Punctuation 1007
 
3.3%
Uppercase Letter 211
 
0.7%
Other Punctuation 101
 
0.3%
Open Punctuation 40
 
0.1%
Close Punctuation 40
 
0.1%
Math Symbol 12
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 1962
11.7%
평 1528
 
9.1%
천 1302
 
7.8%
동 1290
 
7.7%
인 1150
 
6.9%
역 1133
 
6.8%
시 1131
 
6.7%
광 1129
 
6.7%
구 1126
 
6.7%
층 470
 
2.8%
Other values (247) 4540
27.1%
Uppercase Letter
ValueCountFrequency (%)
B 31
14.7%
E 27
12.8%
C 23
10.9%
A 22
10.4%
U 18
8.5%
T 16
7.6%
R 15
7.1%
N 14
6.6%
M 8
 
3.8%
S 7
 
3.3%
Other values (10) 30
14.2%
Decimal Number
ValueCountFrequency (%)
1 1610
25.1%
2 876
13.7%
3 663
10.3%
4 633
 
9.9%
0 612
 
9.6%
5 515
 
8.0%
6 416
 
6.5%
7 396
 
6.2%
9 356
 
5.6%
8 331
 
5.2%
Other Punctuation
ValueCountFrequency (%)
, 97
96.0%
& 2
 
2.0%
@ 1
 
1.0%
/ 1
 
1.0%
Open Punctuation
ValueCountFrequency (%)
( 38
95.0%
[ 2
 
5.0%
Close Punctuation
ValueCountFrequency (%)
) 38
95.0%
] 2
 
5.0%
Space Separator
ValueCountFrequency (%)
6046
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1007
100.0%
Math Symbol
ValueCountFrequency (%)
~ 12
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16759
54.7%
Common 13654
44.6%
Latin 212
 
0.7%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 1962
11.7%
평 1528
 
9.1%
천 1302
 
7.8%
동 1290
 
7.7%
인 1150
 
6.9%
역 1133
 
6.8%
시 1131
 
6.7%
광 1129
 
6.7%
구 1126
 
6.7%
층 470
 
2.8%
Other values (245) 4538
27.1%
Common
ValueCountFrequency (%)
6046
44.3%
1 1610
 
11.8%
- 1007
 
7.4%
2 876
 
6.4%
3 663
 
4.9%
4 633
 
4.6%
0 612
 
4.5%
5 515
 
3.8%
6 416
 
3.0%
7 396
 
2.9%
Other values (11) 880
 
6.4%
Latin
ValueCountFrequency (%)
B 31
14.6%
E 27
12.7%
C 23
10.8%
A 22
10.4%
U 18
8.5%
T 16
7.5%
R 15
7.1%
N 14
6.6%
M 8
 
3.8%
S 7
 
3.3%
Other values (11) 31
14.6%
Han
ValueCountFrequency (%)
美 1
50.0%
德 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16759
54.7%
ASCII 13866
45.3%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6046
43.6%
1 1610
 
11.6%
- 1007
 
7.3%
2 876
 
6.3%
3 663
 
4.8%
4 633
 
4.6%
0 612
 
4.4%
5 515
 
3.7%
6 416
 
3.0%
7 396
 
2.9%
Other values (32) 1092
 
7.9%
Hangul
ValueCountFrequency (%)
부 1962
11.7%
평 1528
 
9.1%
천 1302
 
7.8%
동 1290
 
7.7%
인 1150
 
6.9%
역 1133
 
6.8%
시 1131
 
6.7%
광 1129
 
6.7%
구 1126
 
6.7%
층 470
 
2.8%
Other values (245) 4538
27.1%
CJK
ValueCountFrequency (%)
美 1
50.0%
德 1
50.0%

소재지전화
Text

MISSING 

Distinct435
Distinct (%)94.4%
Missing653
Missing (%)58.6%
Memory size8.8 KiB
2024-01-28T17:55:59.152299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.002169
Min length12

Characters and Unicode

Total characters5533
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

Unique414 ?
Unique (%)89.8%

Sample

1st row032-428-8801
2nd row032-503-1267
3rd row032-527-7900
4th row032-554-2622
5th row032-526-8886
ValueCountFrequency (%)
032-500-3228 4
 
0.9%
032-516-9934 3
 
0.7%
032-564-2691 3
 
0.7%
032-503-6700 3
 
0.7%
032-506-2004 2
 
0.4%
032-501-8888 2
 
0.4%
032-454-2500 2
 
0.4%
032-522-7361 2
 
0.4%
032-573-2001 2
 
0.4%
032-655-8484 2
 
0.4%
Other values (425) 436
94.6%
2024-01-28T17:55:59.448729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 922
16.7%
2 898
16.2%
0 828
15.0%
3 792
14.3%
5 616
11.1%
1 340
 
6.1%
4 261
 
4.7%
6 245
 
4.4%
7 230
 
4.2%
8 220
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4611
83.3%
Dash Punctuation 922
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 898
19.5%
0 828
18.0%
3 792
17.2%
5 616
13.4%
1 340
 
7.4%
4 261
 
5.7%
6 245
 
5.3%
7 230
 
5.0%
8 220
 
4.8%
9 181
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 922
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5533
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 922
16.7%
2 898
16.2%
0 828
15.0%
3 792
14.3%
5 616
11.1%
1 340
 
6.1%
4 261
 
4.7%
6 245
 
4.4%
7 230
 
4.2%
8 220
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5533
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 922
16.7%
2 898
16.2%
0 828
15.0%
3 792
14.3%
5 616
11.1%
1 340
 
6.1%
4 261
 
4.7%
6 245
 
4.4%
7 230
 
4.2%
8 220
 
4.0%

Missing values

2024-01-28T17:55:56.863743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T17:55:56.931920image/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

업종명업소명소재지(도로명)소재지(지번)소재지전화
0식품제조가공업부원식품인천광역시 부평구 정석로 10 (십정동)인천광역시 부평구 십정동 360-28032-428-8801
1식품제조가공업경인식품인천광역시 부평구 수변로85번길 22-3 (부개동)인천광역시 부평구 부개동 120-72032-503-1267
2식품제조가공업미래식품인천광역시 부평구 부흥북로58번길 23 (부평동)인천광역시 부평구 부평동 396-7032-527-7900
3식품제조가공업영동식품인천광역시 부평구 세월천로 216-11 (청천동,1층)인천광역시 부평구 청천동 68-110 1층032-554-2622
4식품제조가공업대진농산인천광역시 부평구 원적로421번길 12 (산곡동)인천광역시 부평구 산곡동 412-30032-526-8886
5식품제조가공업백송식품인천광역시 부평구 열우물로150번길 100 (십정동)인천광역시 부평구 십정동 67-1032-424-5497
6식품제조가공업농업회사법인 이정 주식회사인천광역시 부평구 부평북로 374-1 (삼산동,1층)인천광역시 부평구 삼산동 382 1층032-523-0023
7식품제조가공업푸디안인천광역시 부평구 부평대로98번길 35 (부평동)인천광역시 부평구 부평동 438-1032-361-2311
8식품제조가공업시루방아인천광역시 부평구 부평대로 301, 남광센트렉스 218호 일부호 (청천동)인천광역시 부평구 청천동 440-4 남광센트렉스 218호 일부<NA>
9식품제조가공업(주)성민에프에스인천광역시 부평구 평천로199번길 56 (청천동, 제1동 3층 일부)인천광역시 부평구 청천동 419-8 제1동 3층 일부<NA>
업종명업소명소재지(도로명)소재지(지번)소재지전화
1104기타식품판매업부평농업협동조합인천광역시 부평구 길주로 597 (갈산동)인천광역시 부평구 갈산동 396032-500-2557
1105기타식품판매업주식회사 뉴송도마트인천광역시 부평구 마장로 178, 1~2층 (산곡동, 형제빌딩)인천광역시 부평구 산곡동 369-15 형제빌딩 1~2층032-546-1234
1106기타식품판매업한샘마트인천광역시 부평구 부평북로 345, 1층 일부호 (갈산동)인천광역시 부평구 갈산동 450-5 1층 일부호<NA>
1107기타식품판매업세계로마트 간석점인천광역시 부평구 방축로 429, 1층 일부호 (십정동)인천광역시 부평구 십정동 558-29<NA>
1108용기.포장지제조업대원산업(주)인천광역시 부평구 부평대로329번길 80 (청천동)인천광역시 부평구 청천동 412-1032-516-2211
1109집단급식소 식품판매업유푸드인천광역시 부평구 여우재로26번길 31, 나동 1~2층 (십정동)인천광역시 부평구 십정동 96-1 외 1필지, 나동 1~2층032-462-6545
1110집단급식소 식품판매업제이키즈푸드인천광역시 부평구 부평대로 283, 부평우림라이온스밸리 A동 지하1층 B115-9(12호실)호 (청천동)인천광역시 부평구 청천동 425 부평우림라이온스밸리 A동 B115-9(12호실)<NA>
1111집단급식소 식품판매업프레시포유인천광역시 부평구 원적로300번길 36, 1층 일부호 (산곡동)인천광역시 부평구 산곡동 180-421<NA>
1112집단급식소 식품판매업삼성푸드인천광역시 부평구 부흥로 395, 지하1층 일부호 (부개동)인천광역시 부평구 부개동 66-3<NA>
1113집단급식소 식품판매업대동유통인천광역시 부평구 영성중로37번길 8, 1층 (삼산동)인천광역시 부평구 삼산동 117-14 1층<NA>

Duplicate rows

Most frequently occurring

업종명업소명소재지(도로명)소재지(지번)소재지전화# duplicates
0즉석판매제조가공업주식회사 월드푸드인천광역시 부평구 영성중로15번길 12, GS더프레시 1층 일부호 (삼산동)인천광역시 부평구 삼산동 121-5<NA>2