Overview

Dataset statistics

Number of variables7
Number of observations62
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.6 KiB
Average record size in memory59.1 B

Variable types

Numeric1
Text4
Categorical2

Dataset

Description부천시 관내의 모범음식점 지정현황으로 업종, 업소명, 소재지(도로명,지번), 우편번호, 연락처, 유형, 주요메뉴 등의 정보를 제공합니다.
URLhttps://www.data.go.kr/data/3039577/fileData.do

Alerts

연번 has unique valuesUnique
업소명 has unique valuesUnique
소재지(도로명) has unique valuesUnique
소재지전화번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 09:07:51.714056
Analysis finished2023-12-12 09:07:52.657617
Duration0.94 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct62
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31.5
Minimum1
Maximum62
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size690.0 B
2023-12-12T18:07:52.753447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.05
Q116.25
median31.5
Q346.75
95-th percentile58.95
Maximum62
Range61
Interquartile range (IQR)30.5

Descriptive statistics

Standard deviation18.041619
Coefficient of variation (CV)0.5727498
Kurtosis-1.2
Mean31.5
Median Absolute Deviation (MAD)15.5
Skewness0
Sum1953
Variance325.5
MonotonicityStrictly increasing
2023-12-12T18:07:52.969102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.6%
48 1
 
1.6%
35 1
 
1.6%
36 1
 
1.6%
37 1
 
1.6%
38 1
 
1.6%
39 1
 
1.6%
40 1
 
1.6%
41 1
 
1.6%
42 1
 
1.6%
Other values (52) 52
83.9%
ValueCountFrequency (%)
1 1
1.6%
2 1
1.6%
3 1
1.6%
4 1
1.6%
5 1
1.6%
6 1
1.6%
7 1
1.6%
8 1
1.6%
9 1
1.6%
10 1
1.6%
ValueCountFrequency (%)
62 1
1.6%
61 1
1.6%
60 1
1.6%
59 1
1.6%
58 1
1.6%
57 1
1.6%
56 1
1.6%
55 1
1.6%
54 1
1.6%
53 1
1.6%

업소명
Text

UNIQUE 

Distinct62
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size628.0 B
2023-12-12T18:07:53.305263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length11
Mean length6.8548387
Min length2

Characters and Unicode

Total characters425
Distinct characters196
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

Unique62 ?
Unique (%)100.0%

Sample

1st row강원토종삼계탕
2nd row강화토종웅추삼계탕
3rd row개성손만두
4th row김포한탄강부천점
5th row꽃마름
ValueCountFrequency (%)
강원토종삼계탕 1
 
1.4%
정가네생선구이전문 1
 
1.4%
참맛진숯불갈비 1
 
1.4%
차이나몽 1
 
1.4%
질마재양대창 1
 
1.4%
중경홍중샤브뷔페 1
 
1.4%
조박사아구까치복 1
 
1.4%
조마루감자탕중동남부점 1
 
1.4%
정가네만두샤브 1
 
1.4%
외길수산 1
 
1.4%
Other values (59) 59
85.5%
2023-12-12T18:07:53.802261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 13
 
3.1%
점 12
 
2.8%
부 9
 
2.1%
천 8
 
1.9%
대 8
 
1.9%
7
 
1.6%
중 6
 
1.4%
탕 6
 
1.4%
동 6
 
1.4%
마 6
 
1.4%
Other values (186) 344
80.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 394
92.7%
Lowercase Letter 10
 
2.4%
Space Separator 7
 
1.6%
Uppercase Letter 5
 
1.2%
Open Punctuation 4
 
0.9%
Close Punctuation 4
 
0.9%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 13
 
3.3%
점 12
 
3.0%
부 9
 
2.3%
천 8
 
2.0%
대 8
 
2.0%
중 6
 
1.5%
탕 6
 
1.5%
동 6
 
1.5%
마 6
 
1.5%
가 6
 
1.5%
Other values (170) 314
79.7%
Lowercase Letter
ValueCountFrequency (%)
e 2
20.0%
h 2
20.0%
i 1
10.0%
t 1
10.0%
c 1
10.0%
n 1
10.0%
o 1
10.0%
x 1
10.0%
Uppercase Letter
ValueCountFrequency (%)
K 2
40.0%
J 1
20.0%
B 1
20.0%
T 1
20.0%
Space Separator
ValueCountFrequency (%)
7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 394
92.7%
Common 16
 
3.8%
Latin 15
 
3.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 13
 
3.3%
점 12
 
3.0%
부 9
 
2.3%
천 8
 
2.0%
대 8
 
2.0%
중 6
 
1.5%
탕 6
 
1.5%
동 6
 
1.5%
마 6
 
1.5%
가 6
 
1.5%
Other values (170) 314
79.7%
Latin
ValueCountFrequency (%)
K 2
13.3%
e 2
13.3%
h 2
13.3%
J 1
6.7%
i 1
6.7%
t 1
6.7%
c 1
6.7%
n 1
6.7%
B 1
6.7%
o 1
6.7%
Other values (2) 2
13.3%
Common
ValueCountFrequency (%)
7
43.8%
( 4
25.0%
) 4
25.0%
. 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 394
92.7%
ASCII 31
 
7.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 13
 
3.3%
점 12
 
3.0%
부 9
 
2.3%
천 8
 
2.0%
대 8
 
2.0%
중 6
 
1.5%
탕 6
 
1.5%
동 6
 
1.5%
마 6
 
1.5%
가 6
 
1.5%
Other values (170) 314
79.7%
ASCII
ValueCountFrequency (%)
7
22.6%
( 4
12.9%
) 4
12.9%
K 2
 
6.5%
e 2
 
6.5%
h 2
 
6.5%
. 1
 
3.2%
J 1
 
3.2%
i 1
 
3.2%
t 1
 
3.2%
Other values (6) 6
19.4%

소재지(도로명)
Text

UNIQUE 

Distinct62
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size628.0 B
2023-12-12T18:07:54.100166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length43.5
Mean length33.33871
Min length20

Characters and Unicode

Total characters2067
Distinct characters135
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

Unique62 ?
Unique (%)100.0%

Sample

1st row경기도 부천시 부일로237번길 23 (상동,테마프라자 2층)
2nd row경기도 부천시 중동로 65 (송내동,대지빌딩)
3rd row경기도 부천시 석천로 95 (중동,, 1층)
4th row경기도 부천시 소사로 851 (원종동, 현대빌딩1층 1,2호)
5th row경기도 부천시 소사로 680 (작동, 주건축물제1동 5층)
ValueCountFrequency (%)
경기도 62
 
15.2%
부천시 62
 
15.2%
1층 11
 
2.7%
2층 10
 
2.4%
중동 9
 
2.2%
길주로 6
 
1.5%
신흥로 5
 
1.2%
일부 5
 
1.2%
상동 5
 
1.2%
경인로 5
 
1.2%
Other values (181) 229
56.0%
2023-12-12T18:07:54.577740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
347
 
16.8%
, 107
 
5.2%
1 87
 
4.2%
부 84
 
4.1%
2 81
 
3.9%
동 76
 
3.7%
경 67
 
3.2%
) 66
 
3.2%
천 66
 
3.2%
( 66
 
3.2%
Other values (125) 1020
49.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1050
50.8%
Decimal Number 421
20.4%
Space Separator 347
 
16.8%
Other Punctuation 107
 
5.2%
Close Punctuation 66
 
3.2%
Open Punctuation 66
 
3.2%
Math Symbol 5
 
0.2%
Dash Punctuation 3
 
0.1%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 84
 
8.0%
동 76
 
7.2%
경 67
 
6.4%
천 66
 
6.3%
도 64
 
6.1%
시 62
 
5.9%
기 62
 
5.9%
로 62
 
5.9%
층 44
 
4.2%
길 32
 
3.0%
Other values (107) 431
41.0%
Decimal Number
ValueCountFrequency (%)
1 87
20.7%
2 81
19.2%
0 51
12.1%
4 42
10.0%
5 42
10.0%
3 39
9.3%
6 25
 
5.9%
7 20
 
4.8%
8 18
 
4.3%
9 16
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
M 1
50.0%
J 1
50.0%
Space Separator
ValueCountFrequency (%)
347
100.0%
Other Punctuation
ValueCountFrequency (%)
, 107
100.0%
Close Punctuation
ValueCountFrequency (%)
) 66
100.0%
Open Punctuation
ValueCountFrequency (%)
( 66
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1050
50.8%
Common 1015
49.1%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 84
 
8.0%
동 76
 
7.2%
경 67
 
6.4%
천 66
 
6.3%
도 64
 
6.1%
시 62
 
5.9%
기 62
 
5.9%
로 62
 
5.9%
층 44
 
4.2%
길 32
 
3.0%
Other values (107) 431
41.0%
Common
ValueCountFrequency (%)
347
34.2%
, 107
 
10.5%
1 87
 
8.6%
2 81
 
8.0%
) 66
 
6.5%
( 66
 
6.5%
0 51
 
5.0%
4 42
 
4.1%
5 42
 
4.1%
3 39
 
3.8%
Other values (6) 87
 
8.6%
Latin
ValueCountFrequency (%)
M 1
50.0%
J 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1050
50.8%
ASCII 1017
49.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
347
34.1%
, 107
 
10.5%
1 87
 
8.6%
2 81
 
8.0%
) 66
 
6.5%
( 66
 
6.5%
0 51
 
5.0%
4 42
 
4.1%
5 42
 
4.1%
3 39
 
3.8%
Other values (8) 89
 
8.8%
Hangul
ValueCountFrequency (%)
부 84
 
8.0%
동 76
 
7.2%
경 67
 
6.4%
천 66
 
6.3%
도 64
 
6.1%
시 62
 
5.9%
기 62
 
5.9%
로 62
 
5.9%
층 44
 
4.2%
길 32
 
3.0%
Other values (107) 431
41.0%

소재지전화번호
Text

UNIQUE 

Distinct62
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size628.0 B
2023-12-12T18:07:54.924139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters744
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 row032-325-9119
2nd row032-652-5288
3rd row032-611-7393
4th row032-682-1121
5th row032-677-3977
ValueCountFrequency (%)
032-325-9119 1
 
1.6%
032-228-8000 1
 
1.6%
032-672-5509 1
 
1.6%
032-345-0114 1
 
1.6%
032-611-2095 1
 
1.6%
032-681-5292 1
 
1.6%
032-671-0715 1
 
1.6%
032-678-2518 1
 
1.6%
032-342-2454 1
 
1.6%
032-612-5953 1
 
1.6%
Other values (52) 52
83.9%
2023-12-12T18:07:55.421907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 129
17.3%
3 124
16.7%
- 124
16.7%
0 107
14.4%
6 56
7.5%
5 47
 
6.3%
8 45
 
6.0%
1 35
 
4.7%
7 33
 
4.4%
4 28
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 620
83.3%
Dash Punctuation 124
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 129
20.8%
3 124
20.0%
0 107
17.3%
6 56
9.0%
5 47
 
7.6%
8 45
 
7.3%
1 35
 
5.6%
7 33
 
5.3%
4 28
 
4.5%
9 16
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 124
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 744
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 129
17.3%
3 124
16.7%
- 124
16.7%
0 107
14.4%
6 56
7.5%
5 47
 
6.3%
8 45
 
6.0%
1 35
 
4.7%
7 33
 
4.4%
4 28
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 744
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 129
17.3%
3 124
16.7%
- 124
16.7%
0 107
14.4%
6 56
7.5%
5 47
 
6.3%
8 45
 
6.0%
1 35
 
4.7%
7 33
 
4.4%
4 28
 
3.8%

음식의유형
Categorical

Distinct11
Distinct (%)17.7%
Missing0
Missing (%)0.0%
Memory size628.0 B
한식
44 
뷔페식
 
4
중국식
 
3
일식
 
3
경양식
 
2
Other values (6)
6 

Length

Max length5
Median length2
Mean length2.2580645
Min length2

Unique

Unique6 ?
Unique (%)9.7%

Sample

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

Common Values

ValueCountFrequency (%)
한식 44
71.0%
뷔페식 4
 
6.5%
중국식 3
 
4.8%
일식 3
 
4.8%
경양식 2
 
3.2%
뷔페 1
 
1.6%
양식 1
 
1.6%
복어취급 1
 
1.6%
식육취급 1
 
1.6%
중식 1
 
1.6%

Length

2023-12-12T18:07:55.608800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 44
71.0%
뷔페식 4
 
6.5%
중국식 3
 
4.8%
일식 3
 
4.8%
경양식 2
 
3.2%
뷔페 1
 
1.6%
양식 1
 
1.6%
복어취급 1
 
1.6%
식육취급 1
 
1.6%
중식 1
 
1.6%

주된음식
Text

Distinct53
Distinct (%)85.5%
Missing0
Missing (%)0.0%
Memory size628.0 B
2023-12-12T18:07:55.861651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length4.2419355
Min length1

Characters and Unicode

Total characters263
Distinct characters105
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)75.8%

Sample

1st row삼계탕
2nd row삼계탕
3rd row만두전골
4th row민물매운탕
5th row샤브샤브
ValueCountFrequency (%)
뷔페 4
 
5.9%
감자탕 3
 
4.4%
갈비 2
 
2.9%
막국수 2
 
2.9%
피자 2
 
2.9%
부대찌개 2
 
2.9%
삼계탕 2
 
2.9%
샤브샤브 2
 
2.9%
꽃게.아구탕 1
 
1.5%
한우생등심 1
 
1.5%
Other values (47) 47
69.1%
2023-12-12T18:07:56.240738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
탕 15
 
5.7%
, 9
 
3.4%
샤 8
 
3.0%
브 8
 
3.0%
국 8
 
3.0%
비 7
 
2.7%
수 7
 
2.7%
자 6
 
2.3%
6
 
2.3%
물 6
 
2.3%
Other values (95) 183
69.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 245
93.2%
Other Punctuation 10
 
3.8%
Space Separator 6
 
2.3%
Open Punctuation 1
 
0.4%
Close Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
탕 15
 
6.1%
샤 8
 
3.3%
브 8
 
3.3%
국 8
 
3.3%
비 7
 
2.9%
수 7
 
2.9%
자 6
 
2.4%
물 6
 
2.4%
리 6
 
2.4%
갈 6
 
2.4%
Other values (90) 168
68.6%
Other Punctuation
ValueCountFrequency (%)
, 9
90.0%
. 1
 
10.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 245
93.2%
Common 18
 
6.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
탕 15
 
6.1%
샤 8
 
3.3%
브 8
 
3.3%
국 8
 
3.3%
비 7
 
2.9%
수 7
 
2.9%
자 6
 
2.4%
물 6
 
2.4%
리 6
 
2.4%
갈 6
 
2.4%
Other values (90) 168
68.6%
Common
ValueCountFrequency (%)
, 9
50.0%
6
33.3%
( 1
 
5.6%
. 1
 
5.6%
) 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 245
93.2%
ASCII 18
 
6.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
탕 15
 
6.1%
샤 8
 
3.3%
브 8
 
3.3%
국 8
 
3.3%
비 7
 
2.9%
수 7
 
2.9%
자 6
 
2.4%
물 6
 
2.4%
리 6
 
2.4%
갈 6
 
2.4%
Other values (90) 168
68.6%
ASCII
ValueCountFrequency (%)
, 9
50.0%
6
33.3%
( 1
 
5.6%
. 1
 
5.6%
) 1
 
5.6%

행정동
Categorical

Distinct10
Distinct (%)16.1%
Missing0
Missing (%)0.0%
Memory size628.0 B
신중동
17 
심곡동
7 
상동
7 
중동
6 
성곡동
6 
Other values (5)
19 

Length

Max length4
Median length3
Mean length2.8064516
Min length2

Unique

Unique1 ?
Unique (%)1.6%

Sample

1st row중동
2nd row대산동
3rd row중동
4th row오정동
5th row성곡동

Common Values

ValueCountFrequency (%)
신중동 17
27.4%
심곡동 7
11.3%
상동 7
11.3%
중동 6
 
9.7%
성곡동 6
 
9.7%
대산동 5
 
8.1%
범안동 5
 
8.1%
오정동 4
 
6.5%
부천동 4
 
6.5%
소사본동 1
 
1.6%

Length

2023-12-12T18:07:56.384220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:07:56.502043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신중동 17
27.4%
심곡동 7
11.3%
상동 7
11.3%
중동 6
 
9.7%
성곡동 6
 
9.7%
대산동 5
 
8.1%
범안동 5
 
8.1%
오정동 4
 
6.5%
부천동 4
 
6.5%
소사본동 1
 
1.6%

Interactions

2023-12-12T18:07:52.184289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:07:56.596360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업소명소재지(도로명)소재지전화번호음식의유형주된음식행정동
연번1.0001.0001.0001.0000.0000.8250.394
업소명1.0001.0001.0001.0001.0001.0001.000
소재지(도로명)1.0001.0001.0001.0001.0001.0001.000
소재지전화번호1.0001.0001.0001.0001.0001.0001.000
음식의유형0.0001.0001.0001.0001.0000.9060.062
주된음식0.8251.0001.0001.0000.9061.0000.000
행정동0.3941.0001.0001.0000.0620.0001.000
2023-12-12T18:07:56.696632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
음식의유형행정동
음식의유형1.0000.000
행정동0.0001.000
2023-12-12T18:07:56.774261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번음식의유형행정동
연번1.0000.0000.119
음식의유형0.0001.0000.000
행정동0.1190.0001.000

Missing values

2023-12-12T18:07:52.410820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:07:52.591843image/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

연번업소명소재지(도로명)소재지전화번호음식의유형주된음식행정동
01강원토종삼계탕경기도 부천시 부일로237번길 23 (상동,테마프라자 2층)032-325-9119한식삼계탕중동
12강화토종웅추삼계탕경기도 부천시 중동로 65 (송내동,대지빌딩)032-652-5288한식삼계탕대산동
23개성손만두경기도 부천시 석천로 95 (중동,, 1층)032-611-7393한식만두전골중동
34김포한탄강부천점경기도 부천시 소사로 851 (원종동, 현대빌딩1층 1,2호)032-682-1121한식민물매운탕오정동
45꽃마름경기도 부천시 소사로 680 (작동, 주건축물제1동 5층)032-677-3977한식샤브샤브성곡동
56다온경기도 부천시 소향로 233 (중동,2층)032-322-1199한식쭈꾸미, 해물찜신중동
67닭이봉춘천닭갈비경기도 부천시 중동로254번길 53 (중동, 세종프라자 102호, 103호, 104호)032-321-4452한식닭갈비, 막국수신중동
78당아래비빔국수경기도 부천시 부흥로 424 (심곡동,하나리아빌106)032-667-7550한식비빔국수심곡동
89대청천가남가마루경기도 부천시 중동로 358, 1층 일부호 (약대동, 수향빌딩)032-684-0412한식감자탕신중동
910대추골경기도 부천시 성골로 65 (여월동, 2층전체)032-684-8855한식보리밥성곡동
연번업소명소재지(도로명)소재지전화번호음식의유형주된음식행정동
5253털보꽃게아구경기도 부천시 부일로 495 (심곡동, 1층)032-661-0231한식꽃게.아구탕심곡동
5354털보해물탕경기도 부천시 경인로 65 (송내동)032-662-6848한식해물탕, 간장게장대산동
5455하남돼지집경기도 부천시 부일로 697 (역곡동, 1층 일부)032-347-8389한식고기류부천동
5556한촌경기도 부천시 경인로 92, 1,2,3층 (송내동)032-668-2566한식설렁탕대산동
5657현대백화점중동점경기도 부천시 길주로 180 (중동, 현대백화점중동점 백화점동 10층 일부)032-623-3231집단급식소급식소신중동
5758현대옥 부천중동점경기도 부천시 중동로248번길 105 (중동,,2,3 조이럭타운 109,110호)032-322-2060한식콩나물국밥신중동
5859화로구이경기도 부천시 부일로 265 (상동,(1층,2층))032-325-5915한식돼지갈비중동
5960황고집바지락칼국수경기도 부천시 상동로 90 (상동,메가플러스 108호)032-327-3387한식바지락칼국수상동
6061황해도만두전골경기도 부천시 원종로51번길 64, 부곡빌딩 1,2층 (원종동)032-672-5509한식만두오정동
6162회랑경기도 부천시 소향로253번길 25, 2층 (중동, 정석프라자)032-322-3532일식회신중동