Overview

Dataset statistics

Number of variables5
Number of observations1245
Missing cells915
Missing cells (%)14.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory50.0 KiB
Average record size in memory41.1 B

Variable types

Numeric1
Text4

Dataset

Description인천광역시 부평구 건강기능식품일반팜매업소의 업소명, 소재지(도로명, 지번), 영업장 면적, 소재지 전화번호에 대한 데이터를 제공합니다.
Author인천광역시 부평구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15102443&srcSe=7661IVAWM27C61E190

Alerts

소재지전화 has 903 (72.5%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-01-28 14:17:17.569389
Analysis finished2024-01-28 14:17:18.511092
Duration0.94 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct1245
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean623
Minimum1
Maximum1245
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.1 KiB
2024-01-28T23:17:18.577075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile63.2
Q1312
median623
Q3934
95-th percentile1182.8
Maximum1245
Range1244
Interquartile range (IQR)622

Descriptive statistics

Standard deviation359.54485
Coefficient of variation (CV)0.57711854
Kurtosis-1.2
Mean623
Median Absolute Deviation (MAD)311
Skewness0
Sum775635
Variance129272.5
MonotonicityStrictly increasing
2024-01-28T23:17:18.703075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
829 1
 
0.1%
836 1
 
0.1%
835 1
 
0.1%
834 1
 
0.1%
833 1
 
0.1%
832 1
 
0.1%
831 1
 
0.1%
830 1
 
0.1%
828 1
 
0.1%
Other values (1235) 1235
99.2%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
1245 1
0.1%
1244 1
0.1%
1243 1
0.1%
1242 1
0.1%
1241 1
0.1%
1240 1
0.1%
1239 1
0.1%
1238 1
0.1%
1237 1
0.1%
1236 1
0.1%

업소명
Text

Distinct1227
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
2024-01-28T23:17:18.976625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length22
Mean length6.5100402
Min length1

Characters and Unicode

Total characters8105
Distinct characters622
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1213 ?
Unique (%)97.4%

Sample

1st row아모레부평특약점
2nd row비타민뱅크(주)
3rd row이든네이처 부평총국
4th row정관장부개전시판매장
5th row롯데쇼핑(주)롯데마트 부평역점
ValueCountFrequency (%)
주식회사 44
 
2.9%
인셀덤 38
 
2.5%
세븐일레븐 14
 
0.9%
부평점 10
 
0.7%
애터미 8
 
0.5%
씨제이올리브영(주 7
 
0.5%
롱제비티 7
 
0.5%
에치와이 7
 
0.5%
정관장 5
 
0.3%
삼산점 5
 
0.3%
Other values (1328) 1391
90.6%
2024-01-28T23:17:19.366132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 303
 
3.7%
291
 
3.6%
스 229
 
2.8%
인 201
 
2.5%
점 171
 
2.1%
리 153
 
1.9%
부 146
 
1.8%
( 124
 
1.5%
) 124
 
1.5%
평 115
 
1.4%
Other values (612) 6248
77.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7126
87.9%
Space Separator 291
 
3.6%
Uppercase Letter 191
 
2.4%
Lowercase Letter 150
 
1.9%
Open Punctuation 124
 
1.5%
Close Punctuation 124
 
1.5%
Decimal Number 85
 
1.0%
Other Punctuation 13
 
0.2%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 303
 
4.3%
스 229
 
3.2%
인 201
 
2.8%
점 171
 
2.4%
리 153
 
2.1%
부 146
 
2.0%
평 115
 
1.6%
주 112
 
1.6%
셀 110
 
1.5%
덤 105
 
1.5%
Other values (546) 5481
76.9%
Uppercase Letter
ValueCountFrequency (%)
G 17
 
8.9%
M 16
 
8.4%
O 14
 
7.3%
R 13
 
6.8%
S 12
 
6.3%
A 12
 
6.3%
N 11
 
5.8%
L 10
 
5.2%
H 10
 
5.2%
D 8
 
4.2%
Other values (16) 68
35.6%
Lowercase Letter
ValueCountFrequency (%)
a 21
14.0%
e 17
11.3%
l 16
10.7%
o 14
 
9.3%
n 10
 
6.7%
i 9
 
6.0%
r 7
 
4.7%
s 6
 
4.0%
y 6
 
4.0%
g 5
 
3.3%
Other values (12) 39
26.0%
Decimal Number
ValueCountFrequency (%)
2 22
25.9%
1 19
22.4%
0 18
21.2%
3 7
 
8.2%
5 5
 
5.9%
7 5
 
5.9%
9 3
 
3.5%
6 3
 
3.5%
4 2
 
2.4%
8 1
 
1.2%
Other Punctuation
ValueCountFrequency (%)
. 9
69.2%
& 2
 
15.4%
: 1
 
7.7%
' 1
 
7.7%
Space Separator
ValueCountFrequency (%)
291
100.0%
Open Punctuation
ValueCountFrequency (%)
( 124
100.0%
Close Punctuation
ValueCountFrequency (%)
) 124
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7125
87.9%
Common 638
 
7.9%
Latin 341
 
4.2%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 303
 
4.3%
스 229
 
3.2%
인 201
 
2.8%
점 171
 
2.4%
리 153
 
2.1%
부 146
 
2.0%
평 115
 
1.6%
주 112
 
1.6%
셀 110
 
1.5%
덤 105
 
1.5%
Other values (545) 5480
76.9%
Latin
ValueCountFrequency (%)
a 21
 
6.2%
G 17
 
5.0%
e 17
 
5.0%
l 16
 
4.7%
M 16
 
4.7%
O 14
 
4.1%
o 14
 
4.1%
R 13
 
3.8%
S 12
 
3.5%
A 12
 
3.5%
Other values (38) 189
55.4%
Common
ValueCountFrequency (%)
291
45.6%
( 124
19.4%
) 124
19.4%
2 22
 
3.4%
1 19
 
3.0%
0 18
 
2.8%
. 9
 
1.4%
3 7
 
1.1%
5 5
 
0.8%
7 5
 
0.8%
Other values (8) 14
 
2.2%
Han
ValueCountFrequency (%)
美 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7125
87.9%
ASCII 979
 
12.1%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 303
 
4.3%
스 229
 
3.2%
인 201
 
2.8%
점 171
 
2.4%
리 153
 
2.1%
부 146
 
2.0%
평 115
 
1.6%
주 112
 
1.6%
셀 110
 
1.5%
덤 105
 
1.5%
Other values (545) 5480
76.9%
ASCII
ValueCountFrequency (%)
291
29.7%
( 124
 
12.7%
) 124
 
12.7%
2 22
 
2.2%
a 21
 
2.1%
1 19
 
1.9%
0 18
 
1.8%
G 17
 
1.7%
e 17
 
1.7%
l 16
 
1.6%
Other values (56) 310
31.7%
CJK
ValueCountFrequency (%)
美 1
100.0%

소재지(도로명)
Text

Distinct1128
Distinct (%)91.5%
Missing12
Missing (%)1.0%
Memory size9.9 KiB
2024-01-28T23:17:19.702640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length72
Median length56
Mean length39.712895
Min length22

Characters and Unicode

Total characters48966
Distinct characters359
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1089 ?
Unique (%)88.3%

Sample

1st row인천광역시 부평구 대정로 66, 다운타운일레븐 4층 405호 (부평동)
2nd row인천광역시 부평구 부평문화로 35 (부평동)
3rd row인천광역시 부평구 부흥로294번길 4 (부평동,추인타워 303)
4th row인천광역시 부평구 부흥로 393 (부개동)
5th row인천광역시 부평구 광장로 16 (부평동, 롯데마트 부평역점 )
ValueCountFrequency (%)
인천광역시 1233
 
13.1%
부평구 1233
 
13.1%
부평동 457
 
4.8%
일부호 266
 
2.8%
1층 158
 
1.7%
삼산동 158
 
1.7%
산곡동 146
 
1.5%
십정동 116
 
1.2%
2층 115
 
1.2%
청천동 113
 
1.2%
Other values (1604) 5430
57.6%
2024-01-28T23:17:20.156690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8195
 
16.7%
부 2624
 
5.4%
1 2115
 
4.3%
평 2025
 
4.1%
동 1810
 
3.7%
, 1755
 
3.6%
천 1421
 
2.9%
0 1398
 
2.9%
인 1295
 
2.6%
시 1287
 
2.6%
Other values (349) 25041
51.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 27166
55.5%
Decimal Number 8881
 
18.1%
Space Separator 8195
 
16.7%
Other Punctuation 1756
 
3.6%
Close Punctuation 1282
 
2.6%
Open Punctuation 1282
 
2.6%
Uppercase Letter 212
 
0.4%
Dash Punctuation 185
 
0.4%
Math Symbol 4
 
< 0.1%
Lowercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 2624
 
9.7%
평 2025
 
7.5%
동 1810
 
6.7%
천 1421
 
5.2%
인 1295
 
4.8%
시 1287
 
4.7%
광 1277
 
4.7%
로 1258
 
4.6%
역 1258
 
4.6%
호 1252
 
4.6%
Other values (304) 11659
42.9%
Uppercase Letter
ValueCountFrequency (%)
B 32
15.1%
A 29
13.7%
M 27
12.7%
S 23
10.8%
C 13
 
6.1%
I 12
 
5.7%
E 8
 
3.8%
T 7
 
3.3%
P 7
 
3.3%
R 6
 
2.8%
Other values (15) 48
22.6%
Decimal Number
ValueCountFrequency (%)
1 2115
23.8%
0 1398
15.7%
2 1252
14.1%
3 935
10.5%
4 890
10.0%
5 563
 
6.3%
6 549
 
6.2%
7 457
 
5.1%
8 395
 
4.4%
9 327
 
3.7%
Lowercase Letter
ValueCountFrequency (%)
i 1
33.3%
t 1
33.3%
y 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 1755
99.9%
. 1
 
0.1%
Space Separator
ValueCountFrequency (%)
8195
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1282
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1282
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 185
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 27166
55.5%
Common 21585
44.1%
Latin 215
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 2624
 
9.7%
평 2025
 
7.5%
동 1810
 
6.7%
천 1421
 
5.2%
인 1295
 
4.8%
시 1287
 
4.7%
광 1277
 
4.7%
로 1258
 
4.6%
역 1258
 
4.6%
호 1252
 
4.6%
Other values (304) 11659
42.9%
Latin
ValueCountFrequency (%)
B 32
14.9%
A 29
13.5%
M 27
12.6%
S 23
10.7%
C 13
 
6.0%
I 12
 
5.6%
E 8
 
3.7%
T 7
 
3.3%
P 7
 
3.3%
R 6
 
2.8%
Other values (18) 51
23.7%
Common
ValueCountFrequency (%)
8195
38.0%
1 2115
 
9.8%
, 1755
 
8.1%
0 1398
 
6.5%
) 1282
 
5.9%
( 1282
 
5.9%
2 1252
 
5.8%
3 935
 
4.3%
4 890
 
4.1%
5 563
 
2.6%
Other values (7) 1918
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 27166
55.5%
ASCII 21800
44.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8195
37.6%
1 2115
 
9.7%
, 1755
 
8.1%
0 1398
 
6.4%
) 1282
 
5.9%
( 1282
 
5.9%
2 1252
 
5.7%
3 935
 
4.3%
4 890
 
4.1%
5 563
 
2.6%
Other values (35) 2133
 
9.8%
Hangul
ValueCountFrequency (%)
부 2624
 
9.7%
평 2025
 
7.5%
동 1810
 
6.7%
천 1421
 
5.2%
인 1295
 
4.8%
시 1287
 
4.7%
광 1277
 
4.7%
로 1258
 
4.6%
역 1258
 
4.6%
호 1252
 
4.6%
Other values (304) 11659
42.9%

소재지(지번)
Text

Distinct1167
Distinct (%)93.7%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
2024-01-28T23:17:20.427446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length44
Mean length31.737349
Min length17

Characters and Unicode

Total characters39513
Distinct characters335
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1120 ?
Unique (%)90.0%

Sample

1st row인천광역시 부평구 부평동 152-1 다운타운일레븐 405호
2nd row인천광역시 부평구 부평동 70-127
3rd row인천광역시 부평구 부평동 373-26 추인타워 303
4th row인천광역시 부평구 부개동 67-10
5th row인천광역시 부평구 부평동 738-21 롯데마트 부평역점
ValueCountFrequency (%)
인천광역시 1245
 
15.9%
부평구 1245
 
15.9%
부평동 472
 
6.0%
삼산동 161
 
2.1%
산곡동 155
 
2.0%
일부 125
 
1.6%
십정동 119
 
1.5%
1층 117
 
1.5%
청천동 116
 
1.5%
부개동 98
 
1.3%
Other values (1631) 3973
50.8%
2024-01-28T23:17:20.888528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7264
18.4%
부 2262
 
5.7%
1 2031
 
5.1%
평 1858
 
4.7%
동 1683
 
4.3%
천 1386
 
3.5%
0 1364
 
3.5%
시 1279
 
3.2%
광 1269
 
3.2%
역 1266
 
3.2%
Other values (325) 17851
45.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 21360
54.1%
Decimal Number 9322
23.6%
Space Separator 7264
 
18.4%
Dash Punctuation 1088
 
2.8%
Uppercase Letter 233
 
0.6%
Open Punctuation 86
 
0.2%
Close Punctuation 86
 
0.2%
Other Punctuation 68
 
0.2%
Math Symbol 3
 
< 0.1%
Lowercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 2262
 
10.6%
평 1858
 
8.7%
동 1683
 
7.9%
천 1386
 
6.5%
시 1279
 
6.0%
광 1269
 
5.9%
역 1266
 
5.9%
인 1263
 
5.9%
구 1255
 
5.9%
호 965
 
4.5%
Other values (280) 6874
32.2%
Uppercase Letter
ValueCountFrequency (%)
A 49
21.0%
B 28
12.0%
M 27
11.6%
S 23
9.9%
I 12
 
5.2%
C 12
 
5.2%
P 9
 
3.9%
E 8
 
3.4%
K 8
 
3.4%
T 7
 
3.0%
Other values (15) 50
21.5%
Decimal Number
ValueCountFrequency (%)
1 2031
21.8%
0 1364
14.6%
2 1172
12.6%
4 1138
12.2%
3 946
10.1%
5 709
 
7.6%
6 561
 
6.0%
7 527
 
5.7%
9 467
 
5.0%
8 407
 
4.4%
Lowercase Letter
ValueCountFrequency (%)
y 1
33.3%
i 1
33.3%
t 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 67
98.5%
. 1
 
1.5%
Space Separator
ValueCountFrequency (%)
7264
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1088
100.0%
Open Punctuation
ValueCountFrequency (%)
( 86
100.0%
Close Punctuation
ValueCountFrequency (%)
) 86
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 21360
54.1%
Common 17917
45.3%
Latin 236
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 2262
 
10.6%
평 1858
 
8.7%
동 1683
 
7.9%
천 1386
 
6.5%
시 1279
 
6.0%
광 1269
 
5.9%
역 1266
 
5.9%
인 1263
 
5.9%
구 1255
 
5.9%
호 965
 
4.5%
Other values (280) 6874
32.2%
Latin
ValueCountFrequency (%)
A 49
20.8%
B 28
11.9%
M 27
11.4%
S 23
9.7%
I 12
 
5.1%
C 12
 
5.1%
P 9
 
3.8%
E 8
 
3.4%
K 8
 
3.4%
T 7
 
3.0%
Other values (18) 53
22.5%
Common
ValueCountFrequency (%)
7264
40.5%
1 2031
 
11.3%
0 1364
 
7.6%
2 1172
 
6.5%
4 1138
 
6.4%
- 1088
 
6.1%
3 946
 
5.3%
5 709
 
4.0%
6 561
 
3.1%
7 527
 
2.9%
Other values (7) 1117
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 21360
54.1%
ASCII 18153
45.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7264
40.0%
1 2031
 
11.2%
0 1364
 
7.5%
2 1172
 
6.5%
4 1138
 
6.3%
- 1088
 
6.0%
3 946
 
5.2%
5 709
 
3.9%
6 561
 
3.1%
7 527
 
2.9%
Other values (35) 1353
 
7.5%
Hangul
ValueCountFrequency (%)
부 2262
 
10.6%
평 1858
 
8.7%
동 1683
 
7.9%
천 1386
 
6.5%
시 1279
 
6.0%
광 1269
 
5.9%
역 1266
 
5.9%
인 1263
 
5.9%
구 1255
 
5.9%
호 965
 
4.5%
Other values (280) 6874
32.2%

소재지전화
Text

MISSING 

Distinct325
Distinct (%)95.0%
Missing903
Missing (%)72.5%
Memory size9.9 KiB
2024-01-28T23:17:21.102906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.093567
Min length11

Characters and Unicode

Total characters4136
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

Unique317 ?
Unique (%)92.7%

Sample

1st row032-517-7925
2nd row02-508-5700
3rd row032-517-0902
4th row032-524-2303
5th row032-454-2500
ValueCountFrequency (%)
02-504-2425 9
 
2.6%
02-3284-8129 4
 
1.2%
032-874-2532 2
 
0.6%
032-517-9116 2
 
0.6%
032-500-2557 2
 
0.6%
02-6970-8518 2
 
0.6%
032-512-9413 2
 
0.6%
032-503-4472 2
 
0.6%
032-473-2888 1
 
0.3%
032-330-3511 1
 
0.3%
Other values (315) 315
92.1%
2024-01-28T23:17:21.451744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 684
16.5%
- 684
16.5%
2 590
14.3%
3 525
12.7%
5 428
10.3%
1 250
 
6.0%
7 242
 
5.9%
4 218
 
5.3%
8 197
 
4.8%
6 169
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3452
83.5%
Dash Punctuation 684
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 684
19.8%
2 590
17.1%
3 525
15.2%
5 428
12.4%
1 250
 
7.2%
7 242
 
7.0%
4 218
 
6.3%
8 197
 
5.7%
6 169
 
4.9%
9 149
 
4.3%
Dash Punctuation
ValueCountFrequency (%)
- 684
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4136
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 684
16.5%
- 684
16.5%
2 590
14.3%
3 525
12.7%
5 428
10.3%
1 250
 
6.0%
7 242
 
5.9%
4 218
 
5.3%
8 197
 
4.8%
6 169
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4136
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 684
16.5%
- 684
16.5%
2 590
14.3%
3 525
12.7%
5 428
10.3%
1 250
 
6.0%
7 242
 
5.9%
4 218
 
5.3%
8 197
 
4.8%
6 169
 
4.1%

Interactions

2024-01-28T23:17:18.219504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2024-01-28T23:17:18.315740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T23:17:18.398319image/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.
2024-01-28T23:17:18.473358image/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

연번업소명소재지(도로명)소재지(지번)소재지전화
01아모레부평특약점인천광역시 부평구 대정로 66, 다운타운일레븐 4층 405호 (부평동)인천광역시 부평구 부평동 152-1 다운타운일레븐 405호032-517-7925
12비타민뱅크(주)인천광역시 부평구 부평문화로 35 (부평동)인천광역시 부평구 부평동 70-12702-508-5700
23이든네이처 부평총국인천광역시 부평구 부흥로294번길 4 (부평동,추인타워 303)인천광역시 부평구 부평동 373-26 추인타워 303032-517-0902
34정관장부개전시판매장인천광역시 부평구 부흥로 393 (부개동)인천광역시 부평구 부개동 67-10032-524-2303
45롯데쇼핑(주)롯데마트 부평역점인천광역시 부평구 광장로 16 (부평동, 롯데마트 부평역점 )인천광역시 부평구 부평동 738-21 롯데마트 부평역점032-454-2500
56유니베라인천백운대리점인천광역시 부평구 마장로324번길 8-19 (산곡동,마동 301호)인천광역시 부평구 산곡동 100-98 마동 301호032-513-8812
67녹십초인천광역시 부평구 마장로 369, 2층 (산곡동)인천광역시 부평구 산곡동 7-4032-508-1120
78마임부개지사인천광역시 부평구 동수로 174-1, 2층 (부개동)인천광역시 부평구 부개동 174-1 2층032-521-5109
89정관장홍삼부평시장역점인천광역시 부평구 부평대로 132, 105호 (부평동, 헤리움노블레스)인천광역시 부평구 부평동 431-15 헤리움노블레스 105호032-515-2304
910한양재활의학과인천광역시 부평구 경인로 1076 (부개동)인천광역시 부평구 부개동 317032-501-2190
연번업소명소재지(도로명)소재지(지번)소재지전화
12351236썬글로벌인천광역시 부평구 부평북로 463, 306동 503호 (삼산동, 주공미래타운3단지)인천광역시 부평구 삼산동 390-6 주공미래타운3단지 306동 503호<NA>
12361237영진미래인천광역시 부평구 부일로19번길 10, 하비스트3 1303호 (부평동)인천광역시 부평구 부평동 491-1 하비스트3 1303호<NA>
12371238피데스21인천광역시 부평구 부평대로 163, 쌍용플래티넘 913호 (부평동)인천광역시 부평구 부평동 54-3 쌍용플래티넘 913호070-8751-0493
12381239이랑클인천광역시 부평구 동암남로8번길 43, 2층 (십정동)인천광역시 부평구 십정동 521-27 2층<NA>
12391240팅커벨인천광역시 부평구 영성중로 16, 501동 201호 (삼산동, 삼산주공미래타운아파트)인천광역시 부평구 삼산동 393-4 삼산주공미래타운아파트 501동 201호<NA>
12401241주식회사명성로지스틱인천광역시 부평구 평천로 396, 601호 (삼산동)인천광역시 부평구 삼산동 426-8 601호070-8806-5482
12411242소울온인천광역시 부평구 갈월동로 45, 104동 1106호 (갈산동, 두산아파트)인천광역시 부평구 갈산동 368 두산아파트 104동 1106호<NA>
12421243고라몰인천광역시 부평구 남부역로17번길 6-3, 1층 일부 (부평동)인천광역시 부평구 부평동 744-12 1층 일부<NA>
12431244디스띵트인천광역시 부평구 체육관로 18, 대경프라자 5층 501호 일부호 (삼산동)인천광역시 부평구 삼산동 462-3 대경프라자 5층 501호 일부호(9050)<NA>
12441245금복건강인천광역시 부평구 주부토로66번길 62, 501호 (부평동, 다온아파트)인천광역시 부평구 부평동 379-13 다온아파트 501호<NA>