Overview

Dataset statistics

Number of variables8
Number of observations24
Missing cells7
Missing cells (%)3.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.7 KiB
Average record size in memory70.5 B

Variable types

Categorical2
DateTime1
Text4
Numeric1

Dataset

Description남동구 패스트푸드점 현황에 대한 데이터로 업종명, 인허가일자, 업소명, 소재지(도로명주소),소재지(지번주소), 소재지전화번호, 업태명 항목을 제공합니다.
Author인천광역시 남동구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15116836&srcSe=7661IVAWM27C61E190

Alerts

업종명 has constant value ""Constant
업태명 has constant value ""Constant
소재지전화 has 7 (29.2%) missing valuesMissing
인허가일자 has unique valuesUnique
업소명 has unique valuesUnique
소재지(도로명) has unique valuesUnique
소재지(지번) has unique valuesUnique
영업장면적 has unique valuesUnique

Reproduction

Analysis started2024-01-28 07:05:47.205886
Analysis finished2024-01-28 07:05:47.711365
Duration0.51 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
일반음식점
24 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반음식점 24
100.0%

Length

2024-01-28T16:05:47.757163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T16:05:47.824477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반음식점 24
100.0%

인허가일자
Date

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
Minimum1995-09-18 00:00:00
Maximum2022-08-03 00:00:00
2024-01-28T16:05:47.887612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T16:05:47.973729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)

업소명
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2024-01-28T16:05:48.115740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length11
Mean length6.25
Min length2

Characters and Unicode

Total characters150
Distinct characters99
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

Unique24 ?
Unique (%)100.0%

Sample

1st row미선순대
2nd row광명숯불갈비
3rd row축산이야기
4th row비비큐치킨 구월점
5th row미미성
ValueCountFrequency (%)
구월점 3
 
9.7%
미선순대 1
 
3.2%
빨간장화7080 1
 
3.2%
본사직영 1
 
3.2%
신의주찹쌀순대 1
 
3.2%
f&b 1
 
3.2%
큐알에프앤비(qr 1
 
3.2%
모꼬지 1
 
3.2%
빈체로 1
 
3.2%
크라운호프서창2지구점 1
 
3.2%
Other values (19) 19
61.3%
2024-01-28T16:05:48.578132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7
 
4.7%
구 6
 
4.0%
점 6
 
4.0%
비 5
 
3.3%
스 4
 
2.7%
월 4
 
2.7%
미 4
 
2.7%
장 3
 
2.0%
이 3
 
2.0%
성 3
 
2.0%
Other values (89) 105
70.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 131
87.3%
Space Separator 7
 
4.7%
Decimal Number 5
 
3.3%
Uppercase Letter 4
 
2.7%
Close Punctuation 1
 
0.7%
Other Punctuation 1
 
0.7%
Open Punctuation 1
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 6
 
4.6%
점 6
 
4.6%
비 5
 
3.8%
스 4
 
3.1%
월 4
 
3.1%
미 4
 
3.1%
장 3
 
2.3%
이 3
 
2.3%
성 3
 
2.3%
치 3
 
2.3%
Other values (77) 90
68.7%
Decimal Number
ValueCountFrequency (%)
0 2
40.0%
2 1
20.0%
8 1
20.0%
7 1
20.0%
Uppercase Letter
ValueCountFrequency (%)
Q 1
25.0%
B 1
25.0%
F 1
25.0%
R 1
25.0%
Space Separator
ValueCountFrequency (%)
7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 131
87.3%
Common 15
 
10.0%
Latin 4
 
2.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 6
 
4.6%
점 6
 
4.6%
비 5
 
3.8%
스 4
 
3.1%
월 4
 
3.1%
미 4
 
3.1%
장 3
 
2.3%
이 3
 
2.3%
성 3
 
2.3%
치 3
 
2.3%
Other values (77) 90
68.7%
Common
ValueCountFrequency (%)
7
46.7%
0 2
 
13.3%
2 1
 
6.7%
) 1
 
6.7%
& 1
 
6.7%
( 1
 
6.7%
8 1
 
6.7%
7 1
 
6.7%
Latin
ValueCountFrequency (%)
Q 1
25.0%
B 1
25.0%
F 1
25.0%
R 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 131
87.3%
ASCII 19
 
12.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7
36.8%
0 2
 
10.5%
2 1
 
5.3%
Q 1
 
5.3%
) 1
 
5.3%
B 1
 
5.3%
& 1
 
5.3%
F 1
 
5.3%
R 1
 
5.3%
( 1
 
5.3%
Other values (2) 2
 
10.5%
Hangul
ValueCountFrequency (%)
구 6
 
4.6%
점 6
 
4.6%
비 5
 
3.8%
스 4
 
3.1%
월 4
 
3.1%
미 4
 
3.1%
장 3
 
2.3%
이 3
 
2.3%
성 3
 
2.3%
치 3
 
2.3%
Other values (77) 90
68.7%

소재지(도로명)
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2024-01-28T16:05:48.791836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length42
Mean length37.333333
Min length27

Characters and Unicode

Total characters896
Distinct characters102
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

Unique24 ?
Unique (%)100.0%

Sample

1st row인천광역시 남동구 만수로37번길 8-13, 1층 7호 (만수동)
2nd row인천광역시 남동구 문화로89번길 45, 1층 (구월동)
3rd row인천광역시 남동구 담방로47번길 8-16, 1층 (만수동)
4th row인천광역시 남동구 성리로35번길 20-1 (구월동, 1층 2호 일부)
5th row인천광역시 남동구 용천로 140, 1층 (간석동)
ValueCountFrequency (%)
인천광역시 24
 
14.2%
남동구 24
 
14.2%
1층 15
 
8.9%
구월동 11
 
6.5%
만수동 5
 
3.0%
51 3
 
1.8%
2층 3
 
1.8%
전부호 2
 
1.2%
102호 2
 
1.2%
103호 2
 
1.2%
Other values (77) 78
46.2%
2024-01-28T16:05:49.123325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
145
 
16.2%
동 52
 
5.8%
1 52
 
5.8%
구 43
 
4.8%
인 28
 
3.1%
( 27
 
3.0%
, 27
 
3.0%
) 27
 
3.0%
역 27
 
3.0%
남 26
 
2.9%
Other values (92) 442
49.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 501
55.9%
Decimal Number 159
 
17.7%
Space Separator 145
 
16.2%
Open Punctuation 27
 
3.0%
Other Punctuation 27
 
3.0%
Close Punctuation 27
 
3.0%
Dash Punctuation 6
 
0.7%
Uppercase Letter 4
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 52
 
10.4%
구 43
 
8.6%
인 28
 
5.6%
역 27
 
5.4%
남 26
 
5.2%
로 26
 
5.2%
시 26
 
5.2%
천 25
 
5.0%
광 24
 
4.8%
층 21
 
4.2%
Other values (73) 203
40.5%
Decimal Number
ValueCountFrequency (%)
1 52
32.7%
2 22
13.8%
0 16
 
10.1%
7 14
 
8.8%
3 13
 
8.2%
5 12
 
7.5%
8 10
 
6.3%
6 8
 
5.0%
9 7
 
4.4%
4 5
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
C 1
25.0%
P 1
25.0%
I 1
25.0%
V 1
25.0%
Space Separator
ValueCountFrequency (%)
145
100.0%
Open Punctuation
ValueCountFrequency (%)
( 27
100.0%
Other Punctuation
ValueCountFrequency (%)
, 27
100.0%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 501
55.9%
Common 391
43.6%
Latin 4
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 52
 
10.4%
구 43
 
8.6%
인 28
 
5.6%
역 27
 
5.4%
남 26
 
5.2%
로 26
 
5.2%
시 26
 
5.2%
천 25
 
5.0%
광 24
 
4.8%
층 21
 
4.2%
Other values (73) 203
40.5%
Common
ValueCountFrequency (%)
145
37.1%
1 52
 
13.3%
( 27
 
6.9%
, 27
 
6.9%
) 27
 
6.9%
2 22
 
5.6%
0 16
 
4.1%
7 14
 
3.6%
3 13
 
3.3%
5 12
 
3.1%
Other values (5) 36
 
9.2%
Latin
ValueCountFrequency (%)
C 1
25.0%
P 1
25.0%
I 1
25.0%
V 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 501
55.9%
ASCII 395
44.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
145
36.7%
1 52
 
13.2%
( 27
 
6.8%
, 27
 
6.8%
) 27
 
6.8%
2 22
 
5.6%
0 16
 
4.1%
7 14
 
3.5%
3 13
 
3.3%
5 12
 
3.0%
Other values (9) 40
 
10.1%
Hangul
ValueCountFrequency (%)
동 52
 
10.4%
구 43
 
8.6%
인 28
 
5.6%
역 27
 
5.4%
남 26
 
5.2%
로 26
 
5.2%
시 26
 
5.2%
천 25
 
5.0%
광 24
 
4.8%
층 21
 
4.2%
Other values (73) 203
40.5%

소재지(지번)
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2024-01-28T16:05:49.313614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length35.5
Mean length29.625
Min length20

Characters and Unicode

Total characters711
Distinct characters90
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

Unique24 ?
Unique (%)100.0%

Sample

1st row인천광역시 남동구 만수동 73-1 1층 7호
2nd row인천광역시 남동구 구월동 1370-3
3rd row인천광역시 남동구 만수동 1023-14 1층
4th row인천광역시 남동구 구월동 1186-3 1층 2호일부
5th row인천광역시 남동구 간석동 34-20 외 2필지 1층 일부
ValueCountFrequency (%)
인천광역시 24
17.3%
남동구 24
17.3%
구월동 12
 
8.6%
1층 9
 
6.5%
만수동 6
 
4.3%
간석동 2
 
1.4%
2층 2
 
1.4%
논현동 2
 
1.4%
102호 2
 
1.4%
1층일부 2
 
1.4%
Other values (53) 54
38.8%
2024-01-28T16:05:49.607348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
137
19.3%
1 56
 
7.9%
동 49
 
6.9%
구 39
 
5.5%
시 26
 
3.7%
인 25
 
3.5%
역 25
 
3.5%
광 24
 
3.4%
남 24
 
3.4%
천 24
 
3.4%
Other values (80) 282
39.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 371
52.2%
Decimal Number 168
23.6%
Space Separator 137
 
19.3%
Dash Punctuation 22
 
3.1%
Uppercase Letter 4
 
0.6%
Close Punctuation 3
 
0.4%
Other Punctuation 3
 
0.4%
Open Punctuation 3
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 49
13.2%
구 39
 
10.5%
시 26
 
7.0%
인 25
 
6.7%
역 25
 
6.7%
광 24
 
6.5%
남 24
 
6.5%
천 24
 
6.5%
층 14
 
3.8%
월 13
 
3.5%
Other values (61) 108
29.1%
Decimal Number
ValueCountFrequency (%)
1 56
33.3%
0 20
 
11.9%
2 20
 
11.9%
3 16
 
9.5%
4 14
 
8.3%
8 11
 
6.5%
6 10
 
6.0%
7 8
 
4.8%
9 7
 
4.2%
5 6
 
3.6%
Uppercase Letter
ValueCountFrequency (%)
P 1
25.0%
C 1
25.0%
V 1
25.0%
I 1
25.0%
Space Separator
ValueCountFrequency (%)
137
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 371
52.2%
Common 336
47.3%
Latin 4
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 49
13.2%
구 39
 
10.5%
시 26
 
7.0%
인 25
 
6.7%
역 25
 
6.7%
광 24
 
6.5%
남 24
 
6.5%
천 24
 
6.5%
층 14
 
3.8%
월 13
 
3.5%
Other values (61) 108
29.1%
Common
ValueCountFrequency (%)
137
40.8%
1 56
16.7%
- 22
 
6.5%
0 20
 
6.0%
2 20
 
6.0%
3 16
 
4.8%
4 14
 
4.2%
8 11
 
3.3%
6 10
 
3.0%
7 8
 
2.4%
Other values (5) 22
 
6.5%
Latin
ValueCountFrequency (%)
P 1
25.0%
C 1
25.0%
V 1
25.0%
I 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 371
52.2%
ASCII 340
47.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
137
40.3%
1 56
16.5%
- 22
 
6.5%
0 20
 
5.9%
2 20
 
5.9%
3 16
 
4.7%
4 14
 
4.1%
8 11
 
3.2%
6 10
 
2.9%
7 8
 
2.4%
Other values (9) 26
 
7.6%
Hangul
ValueCountFrequency (%)
동 49
13.2%
구 39
 
10.5%
시 26
 
7.0%
인 25
 
6.7%
역 25
 
6.7%
광 24
 
6.5%
남 24
 
6.5%
천 24
 
6.5%
층 14
 
3.8%
월 13
 
3.5%
Other values (61) 108
29.1%

영업장면적
Real number (ℝ)

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean65.411667
Minimum12.08
Maximum116.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2024-01-28T16:05:49.711260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12.08
5-th percentile19.4395
Q134.4675
median60.84
Q396.66
95-th percentile116.4105
Maximum116.8
Range104.72
Interquartile range (IQR)62.1925

Descriptive statistics

Standard deviation35.945034
Coefficient of variation (CV)0.54952022
Kurtosis-1.4739764
Mean65.411667
Median Absolute Deviation (MAD)31.37
Skewness0.12966127
Sum1569.88
Variance1292.0454
MonotonicityNot monotonic
2024-01-28T16:05:49.805490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
21.42 1
 
4.2%
116.7 1
 
4.2%
12.08 1
 
4.2%
116.8 1
 
4.2%
46.77 1
 
4.2%
90.09 1
 
4.2%
113.82 1
 
4.2%
61.2 1
 
4.2%
35.0 1
 
4.2%
37.05 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
12.08 1
4.2%
19.09 1
4.2%
21.42 1
4.2%
21.69 1
4.2%
29.7 1
4.2%
32.87 1
4.2%
35.0 1
4.2%
37.05 1
4.2%
38.22 1
4.2%
46.77 1
4.2%
ValueCountFrequency (%)
116.8 1
4.2%
116.7 1
4.2%
114.77 1
4.2%
113.82 1
4.2%
112.0 1
4.2%
97.98 1
4.2%
96.22 1
4.2%
92.44 1
4.2%
90.09 1
4.2%
73.68 1
4.2%

소재지전화
Text

MISSING 

Distinct17
Distinct (%)100.0%
Missing7
Missing (%)29.2%
Memory size324.0 B
2024-01-28T16:05:49.947897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters204
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

Unique17 ?
Unique (%)100.0%

Sample

1st row032-464-0365
2nd row032-435-2433
3rd row032-471-6671
4th row032-428-1471
5th row032-421-8666
ValueCountFrequency (%)
032-464-0365 1
 
5.9%
032-433-7474 1
 
5.9%
032-435-2433 1
 
5.9%
032-437-7727 1
 
5.9%
032-719-2237 1
 
5.9%
032-446-3447 1
 
5.9%
032-425-6721 1
 
5.9%
032-471-9339 1
 
5.9%
032-435-8488 1
 
5.9%
032-471-6671 1
 
5.9%
Other values (7) 7
41.2%
2024-01-28T16:05:50.204455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 38
18.6%
- 34
16.7%
2 29
14.2%
4 25
12.3%
0 21
10.3%
7 18
8.8%
6 15
 
7.4%
1 10
 
4.9%
8 5
 
2.5%
9 5
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 170
83.3%
Dash Punctuation 34
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 38
22.4%
2 29
17.1%
4 25
14.7%
0 21
12.4%
7 18
10.6%
6 15
 
8.8%
1 10
 
5.9%
8 5
 
2.9%
9 5
 
2.9%
5 4
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 34
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 204
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 38
18.6%
- 34
16.7%
2 29
14.2%
4 25
12.3%
0 21
10.3%
7 18
8.8%
6 15
 
7.4%
1 10
 
4.9%
8 5
 
2.5%
9 5
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 204
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 38
18.6%
- 34
16.7%
2 29
14.2%
4 25
12.3%
0 21
10.3%
7 18
8.8%
6 15
 
7.4%
1 10
 
4.9%
8 5
 
2.5%
9 5
 
2.5%

업태명
Categorical

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
패스트푸드
24 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
패스트푸드 24
100.0%

Length

2024-01-28T16:05:50.319114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T16:05:50.386114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
패스트푸드 24
100.0%

Interactions

2024-01-28T16:05:47.499361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T16:05:50.431520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인허가일자업소명소재지(도로명)소재지(지번)영업장면적소재지전화
인허가일자1.0001.0001.0001.0001.0001.000
업소명1.0001.0001.0001.0001.0001.000
소재지(도로명)1.0001.0001.0001.0001.0001.000
소재지(지번)1.0001.0001.0001.0001.0001.000
영업장면적1.0001.0001.0001.0001.0001.000
소재지전화1.0001.0001.0001.0001.0001.000

Missing values

2024-01-28T16:05:47.586478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T16:05:47.675058image/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

업종명인허가일자업소명소재지(도로명)소재지(지번)영업장면적소재지전화업태명
0일반음식점1995-09-18미선순대인천광역시 남동구 만수로37번길 8-13, 1층 7호 (만수동)인천광역시 남동구 만수동 73-1 1층 7호21.42032-464-0365패스트푸드
1일반음식점1996-03-12광명숯불갈비인천광역시 남동구 문화로89번길 45, 1층 (구월동)인천광역시 남동구 구월동 1370-373.68032-435-2433패스트푸드
2일반음식점1997-07-29축산이야기인천광역시 남동구 담방로47번길 8-16, 1층 (만수동)인천광역시 남동구 만수동 1023-14 1층97.98032-471-6671패스트푸드
3일반음식점1997-10-25비비큐치킨 구월점인천광역시 남동구 성리로35번길 20-1 (구월동, 1층 2호 일부)인천광역시 남동구 구월동 1186-3 1층 2호일부29.7032-428-1471패스트푸드
4일반음식점1998-06-29미미성인천광역시 남동구 용천로 140, 1층 (간석동)인천광역시 남동구 간석동 34-20 외 2필지 1층 일부19.09032-421-8666패스트푸드
5일반음식점1999-06-12교촌치킨인천광역시 남동구 담방로21번길 3, 한국아파트상가 1층 103호 (만수동)인천광역시 남동구 만수동 1045 한국아파트상가 103호32.87032-461-7600패스트푸드
6일반음식점1999-08-12정성식당인천광역시 남동구 구월말로 113 (만수동,(백구로 79) 1층일부)인천광역시 남동구 만수동 899-43 (백구로 79) 1층일부38.22032-461-3306패스트푸드
7일반음식점2000-11-25춘천명동 닭갈비인천광역시 남동구 호구포로790번길 5-17 (구월동, 1층)인천광역시 남동구 구월동 1265-2 1층60.0032-472-3273패스트푸드
8일반음식점2000-12-02제주덕구구월점인천광역시 남동구 남동대로765번길 39 (구월동)인천광역시 남동구 구월동 1146-1114.77032-427-3636패스트푸드
9일반음식점2000-12-22만리성인천광역시 남동구 인주대로 600-1 (구월동, 1층)인천광역시 남동구 구월동 1126-9 1층96.22032-435-8488패스트푸드
업종명인허가일자업소명소재지(도로명)소재지(지번)영업장면적소재지전화업태명
14일반음식점2011-10-27우정이네인천광역시 남동구 소래역로 12, 소래포구 종합어시장 2층 237호 (논현동)인천광역시 남동구 논현동 680-1 소래포구 종합어시장 2층 237호112.0032-719-2237패스트푸드
15일반음식점2014-08-28미스터피자 만수점인천광역시 남동구 구월로 337, 1층 101, 102호 (만수동)인천광역시 남동구 만수동 888-4 1층 101, 102호69.81<NA>패스트푸드
16일반음식점2016-10-21육개장인인천광역시 남동구 미래로 13, 1층 106호 (구월동, 노빌리안명품)인천광역시 남동구 구월동 1129-22 노빌리안명품 1층 106호37.05032-437-7727패스트푸드
17일반음식점2018-07-13소담김치찌개인천광역시 남동구 구월말로16번길 7, 1층 일부호 (구월동)인천광역시 남동구 구월동 1309-2635.0<NA>패스트푸드
18일반음식점2018-08-21크라운호프서창2지구점인천광역시 남동구 서창방산로 51, 1층 115호 (서창동)인천광역시 남동구 서창동 708-461.2<NA>패스트푸드
19일반음식점2018-09-20빈체로인천광역시 남동구 오봉동로4번길 20, 1층 전부호 (도림동)인천광역시 남동구 도림동 634-7113.82032-439-9233패스트푸드
20일반음식점2021-05-06모꼬지인천광역시 남동구 인주대로522번길 61, 1층 전부호 (구월동)인천광역시 남동구 구월동 1354-20 ,1층전부90.09<NA>패스트푸드
21일반음식점2022-06-23큐알에프앤비(QR F&B)인천광역시 남동구 남동대로799번길 34, C동 2층 217호 (구월동, 신영구월지웰시티푸르지오)인천광역시 남동구 구월동 1608 신영구월지웰시티푸르지오 C동 217호46.77<NA>패스트푸드
22일반음식점2022-07-21신의주찹쌀순대 본사직영 구월점인천광역시 남동구 인하로507번길 88, 뉴다인오피스텔 1층 102호 (구월동)인천광역시 남동구 구월동 1451-1 뉴다인오피스텔 1층 102호116.8<NA>패스트푸드
23일반음식점2022-08-03버텍스 구월점인천광역시 남동구 예술로226번길 18, VIP오피스텔 지하1층 제비01호, 제비02호 일부(주방8호)호 (구월동)인천광역시 남동구 구월동 1134-10 VIP오피스텔 제비01호, 제비02호 일부(주방8호)12.08<NA>패스트푸드