Overview

Dataset statistics

Number of variables6
Number of observations129
Missing cells67
Missing cells (%)8.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.3 KiB
Average record size in memory50.0 B

Variable types

Numeric1
Categorical1
Text4

Dataset

Description인천광역시 부평구 제과점 현황입니다.(업종명,업소명,소재지(도로명),소재지(지번),소재지전화)ex) 제과점영업,빵터,인천광역시 부평구 부일로 16 1층 101호 (부평동 헤르메스아파트2동),인천광역시 부평구 부평동 495-10 헤르메스아파트2동 101호,032-330-0010
Author인천광역시 부평구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=3078621&srcSe=7661IVAWM27C61E190

Alerts

업종명 has constant value ""Constant
소재지전화 has 67 (51.9%) missing valuesMissing
연번 has unique valuesUnique
소재지(도로명) has unique valuesUnique
소재지(지번) has unique valuesUnique

Reproduction

Analysis started2024-01-28 13:44:36.166351
Analysis finished2024-01-28 13:44:36.751231
Duration0.58 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct129
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean65
Minimum1
Maximum129
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-01-28T22:44:36.817825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7.4
Q133
median65
Q397
95-th percentile122.6
Maximum129
Range128
Interquartile range (IQR)64

Descriptive statistics

Standard deviation37.383151
Coefficient of variation (CV)0.5751254
Kurtosis-1.2
Mean65
Median Absolute Deviation (MAD)32
Skewness0
Sum8385
Variance1397.5
MonotonicityStrictly increasing
2024-01-28T22:44:36.935058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.8%
98 1
 
0.8%
96 1
 
0.8%
95 1
 
0.8%
94 1
 
0.8%
93 1
 
0.8%
92 1
 
0.8%
91 1
 
0.8%
90 1
 
0.8%
89 1
 
0.8%
Other values (119) 119
92.2%
ValueCountFrequency (%)
1 1
0.8%
2 1
0.8%
3 1
0.8%
4 1
0.8%
5 1
0.8%
6 1
0.8%
7 1
0.8%
8 1
0.8%
9 1
0.8%
10 1
0.8%
ValueCountFrequency (%)
129 1
0.8%
128 1
0.8%
127 1
0.8%
126 1
0.8%
125 1
0.8%
124 1
0.8%
123 1
0.8%
122 1
0.8%
121 1
0.8%
120 1
0.8%

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
제과점영업
129 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제과점영업 129
100.0%

Length

2024-01-28T22:44:37.045550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T22:44:37.120874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제과점영업 129
100.0%

업소명
Text

Distinct121
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-01-28T22:44:37.310692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length15
Mean length7.9069767
Min length2

Characters and Unicode

Total characters1020
Distinct characters228
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

Unique119 ?
Unique (%)92.2%

Sample

1st row어거스트101
2nd row빵아저씨쿠키아줌마
3rd row쉐라메르과자점
4th row파리바게뜨(부평역점)
5th row마망
ValueCountFrequency (%)
파리바게뜨 10
 
6.5%
파리바게트 9
 
5.8%
뚜레쥬르 5
 
3.2%
던킨도너츠 2
 
1.3%
과자점 2
 
1.3%
삼산점 2
 
1.3%
명인빵지순례1984 2
 
1.3%
차츰차츰 1
 
0.6%
조아베이커리 1
 
0.6%
바이올렛 1
 
0.6%
Other values (120) 120
77.4%
2024-01-28T22:44:37.626835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 60
 
5.9%
점 48
 
4.7%
파 41
 
4.0%
바 40
 
3.9%
게 37
 
3.6%
이 34
 
3.3%
부 33
 
3.2%
뜨 27
 
2.6%
트 26
 
2.5%
26
 
2.5%
Other values (218) 648
63.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 931
91.3%
Space Separator 26
 
2.5%
Lowercase Letter 22
 
2.2%
Decimal Number 17
 
1.7%
Open Punctuation 10
 
1.0%
Close Punctuation 10
 
1.0%
Uppercase Letter 3
 
0.3%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 60
 
6.4%
점 48
 
5.2%
파 41
 
4.4%
바 40
 
4.3%
게 37
 
4.0%
이 34
 
3.7%
부 33
 
3.5%
뜨 27
 
2.9%
트 26
 
2.8%
평 23
 
2.5%
Other values (194) 562
60.4%
Lowercase Letter
ValueCountFrequency (%)
e 5
22.7%
a 4
18.2%
r 3
13.6%
k 2
 
9.1%
h 1
 
4.5%
n 1
 
4.5%
t 1
 
4.5%
s 1
 
4.5%
c 1
 
4.5%
b 1
 
4.5%
Other values (2) 2
 
9.1%
Decimal Number
ValueCountFrequency (%)
8 4
23.5%
1 4
23.5%
0 3
17.6%
9 2
11.8%
4 2
11.8%
3 2
11.8%
Uppercase Letter
ValueCountFrequency (%)
C 2
66.7%
B 1
33.3%
Space Separator
ValueCountFrequency (%)
26
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 931
91.3%
Common 64
 
6.3%
Latin 25
 
2.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 60
 
6.4%
점 48
 
5.2%
파 41
 
4.4%
바 40
 
4.3%
게 37
 
4.0%
이 34
 
3.7%
부 33
 
3.5%
뜨 27
 
2.9%
트 26
 
2.8%
평 23
 
2.5%
Other values (194) 562
60.4%
Latin
ValueCountFrequency (%)
e 5
20.0%
a 4
16.0%
r 3
12.0%
k 2
 
8.0%
C 2
 
8.0%
h 1
 
4.0%
n 1
 
4.0%
t 1
 
4.0%
s 1
 
4.0%
c 1
 
4.0%
Other values (4) 4
16.0%
Common
ValueCountFrequency (%)
26
40.6%
( 10
 
15.6%
) 10
 
15.6%
8 4
 
6.2%
1 4
 
6.2%
0 3
 
4.7%
9 2
 
3.1%
4 2
 
3.1%
3 2
 
3.1%
& 1
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 931
91.3%
ASCII 89
 
8.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 60
 
6.4%
점 48
 
5.2%
파 41
 
4.4%
바 40
 
4.3%
게 37
 
4.0%
이 34
 
3.7%
부 33
 
3.5%
뜨 27
 
2.9%
트 26
 
2.8%
평 23
 
2.5%
Other values (194) 562
60.4%
ASCII
ValueCountFrequency (%)
26
29.2%
( 10
 
11.2%
) 10
 
11.2%
e 5
 
5.6%
8 4
 
4.5%
a 4
 
4.5%
1 4
 
4.5%
r 3
 
3.4%
0 3
 
3.4%
k 2
 
2.2%
Other values (14) 18
20.2%

소재지(도로명)
Text

UNIQUE 

Distinct129
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-01-28T22:44:37.886279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length46
Mean length35.317829
Min length21

Characters and Unicode

Total characters4556
Distinct characters186
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

Unique129 ?
Unique (%)100.0%

Sample

1st row인천광역시 부평구 부평문화로141번길 3, 굿플러스 1층 101호 (부평동)
2nd row인천광역시 부평구 마장로 72 (십정동)
3rd row인천광역시 부평구 안남로222번길 30 (산곡동, 경남아파트2차상가동 나동 1층2호~4호, 지하1호, 지하12호)
4th row인천광역시 부평구 시장로 12 (부평동)
5th row인천광역시 부평구 부평문화로 37 (부평동,동아2차 상가 107호)
ValueCountFrequency (%)
인천광역시 129
 
14.4%
부평구 129
 
14.4%
1층 70
 
7.8%
부평동 36
 
4.0%
일부호 20
 
2.2%
산곡동 13
 
1.4%
일부 11
 
1.2%
십정동 10
 
1.1%
부개동 10
 
1.1%
청천동 9
 
1.0%
Other values (296) 461
51.3%
2024-01-28T22:44:38.265018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
770
 
16.9%
1 272
 
6.0%
부 269
 
5.9%
평 205
 
4.5%
동 154
 
3.4%
, 151
 
3.3%
천 146
 
3.2%
인 139
 
3.1%
광 137
 
3.0%
역 136
 
3.0%
Other values (176) 2177
47.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2603
57.1%
Space Separator 770
 
16.9%
Decimal Number 736
 
16.2%
Other Punctuation 152
 
3.3%
Close Punctuation 132
 
2.9%
Open Punctuation 132
 
2.9%
Uppercase Letter 17
 
0.4%
Dash Punctuation 11
 
0.2%
Math Symbol 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 269
 
10.3%
평 205
 
7.9%
동 154
 
5.9%
천 146
 
5.6%
인 139
 
5.3%
광 137
 
5.3%
역 136
 
5.2%
시 134
 
5.1%
로 131
 
5.0%
구 131
 
5.0%
Other values (144) 1021
39.2%
Uppercase Letter
ValueCountFrequency (%)
E 2
 
11.8%
I 2
 
11.8%
B 1
 
5.9%
F 1
 
5.9%
H 1
 
5.9%
A 1
 
5.9%
M 1
 
5.9%
P 1
 
5.9%
O 1
 
5.9%
G 1
 
5.9%
Other values (5) 5
29.4%
Decimal Number
ValueCountFrequency (%)
1 272
37.0%
2 92
 
12.5%
0 82
 
11.1%
4 64
 
8.7%
3 60
 
8.2%
5 53
 
7.2%
6 40
 
5.4%
9 25
 
3.4%
8 24
 
3.3%
7 24
 
3.3%
Other Punctuation
ValueCountFrequency (%)
, 151
99.3%
@ 1
 
0.7%
Space Separator
ValueCountFrequency (%)
770
100.0%
Close Punctuation
ValueCountFrequency (%)
) 132
100.0%
Open Punctuation
ValueCountFrequency (%)
( 132
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2603
57.1%
Common 1936
42.5%
Latin 17
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 269
 
10.3%
평 205
 
7.9%
동 154
 
5.9%
천 146
 
5.6%
인 139
 
5.3%
광 137
 
5.3%
역 136
 
5.2%
시 134
 
5.1%
로 131
 
5.0%
구 131
 
5.0%
Other values (144) 1021
39.2%
Common
ValueCountFrequency (%)
770
39.8%
1 272
 
14.0%
, 151
 
7.8%
) 132
 
6.8%
( 132
 
6.8%
2 92
 
4.8%
0 82
 
4.2%
4 64
 
3.3%
3 60
 
3.1%
5 53
 
2.7%
Other values (7) 128
 
6.6%
Latin
ValueCountFrequency (%)
E 2
 
11.8%
I 2
 
11.8%
B 1
 
5.9%
F 1
 
5.9%
H 1
 
5.9%
A 1
 
5.9%
M 1
 
5.9%
P 1
 
5.9%
O 1
 
5.9%
G 1
 
5.9%
Other values (5) 5
29.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2603
57.1%
ASCII 1953
42.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
770
39.4%
1 272
 
13.9%
, 151
 
7.7%
) 132
 
6.8%
( 132
 
6.8%
2 92
 
4.7%
0 82
 
4.2%
4 64
 
3.3%
3 60
 
3.1%
5 53
 
2.7%
Other values (22) 145
 
7.4%
Hangul
ValueCountFrequency (%)
부 269
 
10.3%
평 205
 
7.9%
동 154
 
5.9%
천 146
 
5.6%
인 139
 
5.3%
광 137
 
5.3%
역 136
 
5.2%
시 134
 
5.1%
로 131
 
5.0%
구 131
 
5.0%
Other values (144) 1021
39.2%

소재지(지번)
Text

UNIQUE 

Distinct129
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-01-28T22:44:38.545268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length42
Mean length29.310078
Min length19

Characters and Unicode

Total characters3781
Distinct characters162
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

Unique129 ?
Unique (%)100.0%

Sample

1st row인천광역시 부평구 부평동 364-19 외2필지, 굿플러스 101호
2nd row인천광역시 부평구 십정동 174-13
3rd row인천광역시 부평구 산곡동 274 경남아파트2차상가동 나동 1층2호~4호, 지하1호, 지하12호
4th row인천광역시 부평구 부평동 153-21
5th row인천광역시 부평구 부평동 70-5 동아2차 상가 107호
ValueCountFrequency (%)
인천광역시 129
16.9%
부평구 129
16.9%
1층 58
 
7.6%
부평동 43
 
5.6%
산곡동 21
 
2.7%
일부 20
 
2.6%
삼산동 17
 
2.2%
십정동 13
 
1.7%
갈산동 12
 
1.6%
부개동 12
 
1.6%
Other values (233) 311
40.7%
2024-01-28T22:44:39.215021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
755
20.0%
1 261
 
6.9%
부 223
 
5.9%
평 183
 
4.8%
동 147
 
3.9%
천 140
 
3.7%
역 136
 
3.6%
인 132
 
3.5%
시 132
 
3.5%
구 131
 
3.5%
Other values (152) 1541
40.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2011
53.2%
Decimal Number 839
22.2%
Space Separator 755
 
20.0%
Dash Punctuation 119
 
3.1%
Other Punctuation 32
 
0.8%
Uppercase Letter 16
 
0.4%
Math Symbol 3
 
0.1%
Close Punctuation 3
 
0.1%
Open Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 223
 
11.1%
평 183
 
9.1%
동 147
 
7.3%
천 140
 
7.0%
역 136
 
6.8%
인 132
 
6.6%
시 132
 
6.6%
구 131
 
6.5%
광 129
 
6.4%
층 76
 
3.8%
Other values (121) 582
28.9%
Uppercase Letter
ValueCountFrequency (%)
E 2
12.5%
I 2
12.5%
F 1
 
6.2%
M 1
 
6.2%
R 1
 
6.2%
K 1
 
6.2%
G 1
 
6.2%
A 1
 
6.2%
P 1
 
6.2%
O 1
 
6.2%
Other values (4) 4
25.0%
Decimal Number
ValueCountFrequency (%)
1 261
31.1%
2 94
 
11.2%
0 84
 
10.0%
4 83
 
9.9%
5 75
 
8.9%
3 73
 
8.7%
9 48
 
5.7%
6 42
 
5.0%
8 41
 
4.9%
7 38
 
4.5%
Other Punctuation
ValueCountFrequency (%)
, 31
96.9%
@ 1
 
3.1%
Space Separator
ValueCountFrequency (%)
755
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 119
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2011
53.2%
Common 1754
46.4%
Latin 16
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 223
 
11.1%
평 183
 
9.1%
동 147
 
7.3%
천 140
 
7.0%
역 136
 
6.8%
인 132
 
6.6%
시 132
 
6.6%
구 131
 
6.5%
광 129
 
6.4%
층 76
 
3.8%
Other values (121) 582
28.9%
Common
ValueCountFrequency (%)
755
43.0%
1 261
 
14.9%
- 119
 
6.8%
2 94
 
5.4%
0 84
 
4.8%
4 83
 
4.7%
5 75
 
4.3%
3 73
 
4.2%
9 48
 
2.7%
6 42
 
2.4%
Other values (7) 120
 
6.8%
Latin
ValueCountFrequency (%)
E 2
12.5%
I 2
12.5%
F 1
 
6.2%
M 1
 
6.2%
R 1
 
6.2%
K 1
 
6.2%
G 1
 
6.2%
A 1
 
6.2%
P 1
 
6.2%
O 1
 
6.2%
Other values (4) 4
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2011
53.2%
ASCII 1770
46.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
755
42.7%
1 261
 
14.7%
- 119
 
6.7%
2 94
 
5.3%
0 84
 
4.7%
4 83
 
4.7%
5 75
 
4.2%
3 73
 
4.1%
9 48
 
2.7%
6 42
 
2.4%
Other values (21) 136
 
7.7%
Hangul
ValueCountFrequency (%)
부 223
 
11.1%
평 183
 
9.1%
동 147
 
7.3%
천 140
 
7.0%
역 136
 
6.8%
인 132
 
6.6%
시 132
 
6.6%
구 131
 
6.5%
광 129
 
6.4%
층 76
 
3.8%
Other values (121) 582
28.9%

소재지전화
Text

MISSING 

Distinct62
Distinct (%)100.0%
Missing67
Missing (%)51.9%
Memory size1.1 KiB
2024-01-28T22:44:39.429797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.048387
Min length12

Characters and Unicode

Total characters747
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

Unique62 ?
Unique (%)100.0%

Sample

1st row032-361-9376
2nd row070-8138-7499
3rd row032-523-0404
4th row032-515-7007
5th row032-522-0450
ValueCountFrequency (%)
032-425-5590 1
 
1.6%
032-524-9289 1
 
1.6%
032-529-5350 1
 
1.6%
032-330-8060 1
 
1.6%
032-502-8203 1
 
1.6%
032-512-8204 1
 
1.6%
032-528-8253 1
 
1.6%
032-513-8204 1
 
1.6%
032-512-8203 1
 
1.6%
070-4254-0022 1
 
1.6%
Other values (52) 52
83.9%
2024-01-28T22:44:39.743800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 137
18.3%
- 124
16.6%
2 123
16.5%
3 94
12.6%
5 76
10.2%
4 39
 
5.2%
1 38
 
5.1%
8 38
 
5.1%
9 30
 
4.0%
7 24
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 623
83.4%
Dash Punctuation 124
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 137
22.0%
2 123
19.7%
3 94
15.1%
5 76
12.2%
4 39
 
6.3%
1 38
 
6.1%
8 38
 
6.1%
9 30
 
4.8%
7 24
 
3.9%
6 24
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 124
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 747
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 137
18.3%
- 124
16.6%
2 123
16.5%
3 94
12.6%
5 76
10.2%
4 39
 
5.2%
1 38
 
5.1%
8 38
 
5.1%
9 30
 
4.0%
7 24
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 747
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 137
18.3%
- 124
16.6%
2 123
16.5%
3 94
12.6%
5 76
10.2%
4 39
 
5.2%
1 38
 
5.1%
8 38
 
5.1%
9 30
 
4.0%
7 24
 
3.2%

Interactions

2024-01-28T22:44:36.528806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T22:44:39.832924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번소재지전화
연번1.0001.000
소재지전화1.0001.000

Missing values

2024-01-28T22:44:36.622430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T22:44:36.713578image/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
01제과점영업어거스트101인천광역시 부평구 부평문화로141번길 3, 굿플러스 1층 101호 (부평동)인천광역시 부평구 부평동 364-19 외2필지, 굿플러스 101호032-361-9376
12제과점영업빵아저씨쿠키아줌마인천광역시 부평구 마장로 72 (십정동)인천광역시 부평구 십정동 174-13070-8138-7499
23제과점영업쉐라메르과자점인천광역시 부평구 안남로222번길 30 (산곡동, 경남아파트2차상가동 나동 1층2호~4호, 지하1호, 지하12호)인천광역시 부평구 산곡동 274 경남아파트2차상가동 나동 1층2호~4호, 지하1호, 지하12호032-523-0404
34제과점영업파리바게뜨(부평역점)인천광역시 부평구 시장로 12 (부평동)인천광역시 부평구 부평동 153-21032-515-7007
45제과점영업마망인천광역시 부평구 부평문화로 37 (부평동,동아2차 상가 107호)인천광역시 부평구 부평동 70-5 동아2차 상가 107호032-522-0450
56제과점영업뚜레쥬르부평중앙점인천광역시 부평구 부흥로 283, 1층 (부평동)인천광역시 부평구 부평동 442-8 1층032-667-7549
67제과점영업파리바게뜨부개부일점인천광역시 부평구 동수로126번길 3 (부개동, 1층일부)인천광역시 부평구 부개동 444-1 1층일부032-528-2947
78제과점영업빨간풍차과자점인천광역시 부평구 길주남로125번길 24 (부개동)인천광역시 부평구 부개동 12-89032-521-4591
89제과점영업파리바게트인천광역시 부평구 부평문화로 50 (부평동,101호)인천광역시 부평구 부평동 546-76 101호032-525-0089
910제과점영업빵장수야곱인천광역시 부평구 후정동로 43 (삼산동,삼보@상가1층1호)인천광역시 부평구 삼산동 57 삼보@상가1층1호032-524-0904
연번업종명업소명소재지(도로명)소재지(지번)소재지전화
119120제과점영업고망고인천광역시 부평구 광장로30번길 37, 1층 (부평동)인천광역시 부평구 부평동 182-79 1층<NA>
120121제과점영업향이케이크인천광역시 부평구 길주남로77번길 19, 1층 일부호 (부평동)인천광역시 부평구 부평동 10-585<NA>
121122제과점영업하트도씨인천광역시 부평구 장제로 224-1, 1층 (부개동)인천광역시 부평구 부개동 478-2 1<NA>
122123제과점영업베아또 과자점인천광역시 부평구 부흥북로6번길 5, 센트럴아파트 1층 105호 (부평동)인천광역시 부평구 부평동 436-15 센트럴아파트 105호<NA>
123124제과점영업조아베이커리인천광역시 부평구 화랑남로5번길 7, 1층 일부호 (산곡동)인천광역시 부평구 산곡동 311-67 1층 일부<NA>
124125제과점영업명인빵지순례1984 삼산점인천광역시 부평구 영성중로 50, 미래타워 109호 일부호 (삼산동)인천광역시 부평구 삼산동 391-3 미래타워 109호 일부<NA>
125126제과점영업차츰차츰인천광역시 부평구 영성중로36번길 3, 1층 일부호 (삼산동)인천광역시 부평구 삼산동 117-25 1층 일부<NA>
126127제과점영업뚜레쥬르 신일해피트리점인천광역시 부평구 원적로 295, 더루츠스퀘어 1층 111, 112호 (산곡동)인천광역시 부평구 산곡동 180-104 더루츠스퀘어 1층 111, 112호032-522-2115
127128제과점영업주제인천광역시 부평구 신트리로22번길 6, 1층 일부호 (부평동)인천광역시 부평구 부평동 882-8 1층 일부호<NA>
128129제과점영업베이커리코너 부평점인천광역시 부평구 마장로 296, 롯데마트 부평점 지하1층 일부 (산곡동)인천광역시 부평구 산곡동 159-52 롯데마트 부평점 지하1층 일부<NA>