Overview

Dataset statistics

Number of variables7
Number of observations39
Missing cells2
Missing cells (%)0.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.3 KiB
Average record size in memory61.4 B

Variable types

Numeric2
Text4
Categorical1

Dataset

Description인천광역시 남동구 착한가격업소현황에 대한 데이터로 연번, 업소명, 유형, 소재지주소, 전화번호, 대표메뉴명1, 대표메뉴1가격 항목을 제공합니다.
Author인천광역시 남동구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15067442&srcSe=7661IVAWM27C61E190

Alerts

전화번호 has 2 (5.1%) missing valuesMissing
연번 has unique valuesUnique
업소명 has unique valuesUnique
소재지주소 has unique valuesUnique

Reproduction

Analysis started2024-01-28 15:31:44.663642
Analysis finished2024-01-28 15:31:45.678349
Duration1.01 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct39
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20
Minimum1
Maximum39
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2024-01-29T00:31:45.736181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.9
Q110.5
median20
Q329.5
95-th percentile37.1
Maximum39
Range38
Interquartile range (IQR)19

Descriptive statistics

Standard deviation11.401754
Coefficient of variation (CV)0.57008771
Kurtosis-1.2
Mean20
Median Absolute Deviation (MAD)10
Skewness0
Sum780
Variance130
MonotonicityStrictly increasing
2024-01-29T00:31:45.842560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
1 1
 
2.6%
2 1
 
2.6%
23 1
 
2.6%
24 1
 
2.6%
25 1
 
2.6%
26 1
 
2.6%
27 1
 
2.6%
28 1
 
2.6%
29 1
 
2.6%
30 1
 
2.6%
Other values (29) 29
74.4%
ValueCountFrequency (%)
1 1
2.6%
2 1
2.6%
3 1
2.6%
4 1
2.6%
5 1
2.6%
6 1
2.6%
7 1
2.6%
8 1
2.6%
9 1
2.6%
10 1
2.6%
ValueCountFrequency (%)
39 1
2.6%
38 1
2.6%
37 1
2.6%
36 1
2.6%
35 1
2.6%
34 1
2.6%
33 1
2.6%
32 1
2.6%
31 1
2.6%
30 1
2.6%

업소명
Text

UNIQUE 

Distinct39
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size444.0 B
2024-01-29T00:31:46.029855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length5.3589744
Min length3

Characters and Unicode

Total characters209
Distinct characters128
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39 ?
Unique (%)100.0%

Sample

1st row화미소금구이
2nd row우돈먹는날
3rd row끼머리방
4th row행복식당
5th row소망각
ValueCountFrequency (%)
화미소금구이 1
 
2.4%
내고향만두 1
 
2.4%
국수마을 1
 
2.4%
서인반점 1
 
2.4%
고향모밀촌 1
 
2.4%
드라이119세탁 1
 
2.4%
정김밥 1
 
2.4%
델리푸드 1
 
2.4%
김밥마을 1
 
2.4%
모밀지기 1
 
2.4%
Other values (31) 31
75.6%
2024-01-29T00:31:46.317680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 7
 
3.3%
국 6
 
2.9%
리 6
 
2.9%
고 4
 
1.9%
두 4
 
1.9%
밥 4
 
1.9%
김 4
 
1.9%
손 3
 
1.4%
미 3
 
1.4%
네 3
 
1.4%
Other values (118) 165
78.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 201
96.2%
Other Punctuation 3
 
1.4%
Decimal Number 3
 
1.4%
Space Separator 2
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 7
 
3.5%
국 6
 
3.0%
리 6
 
3.0%
고 4
 
2.0%
두 4
 
2.0%
밥 4
 
2.0%
김 4
 
2.0%
손 3
 
1.5%
미 3
 
1.5%
네 3
 
1.5%
Other values (114) 157
78.1%
Decimal Number
ValueCountFrequency (%)
1 2
66.7%
9 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 201
96.2%
Common 8
 
3.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 7
 
3.5%
국 6
 
3.0%
리 6
 
3.0%
고 4
 
2.0%
두 4
 
2.0%
밥 4
 
2.0%
김 4
 
2.0%
손 3
 
1.5%
미 3
 
1.5%
네 3
 
1.5%
Other values (114) 157
78.1%
Common
ValueCountFrequency (%)
, 3
37.5%
2
25.0%
1 2
25.0%
9 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 201
96.2%
ASCII 8
 
3.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 7
 
3.5%
국 6
 
3.0%
리 6
 
3.0%
고 4
 
2.0%
두 4
 
2.0%
밥 4
 
2.0%
김 4
 
2.0%
손 3
 
1.5%
미 3
 
1.5%
네 3
 
1.5%
Other values (114) 157
78.1%
ASCII
ValueCountFrequency (%)
, 3
37.5%
2
25.0%
1 2
25.0%
9 1
 
12.5%

유형
Categorical

Distinct7
Distinct (%)17.9%
Missing0
Missing (%)0.0%
Memory size444.0 B
한식_일반
15 
중식
7 
미용업
5 
한식_면류
5 
한식_육류
4 
Other values (2)
3 

Length

Max length5
Median length5
Mean length4.0512821
Min length2

Unique

Unique1 ?
Unique (%)2.6%

Sample

1st row한식_육류
2nd row한식_육류
3rd row미용업
4th row한식_일반
5th row중식

Common Values

ValueCountFrequency (%)
한식_일반 15
38.5%
중식 7
17.9%
미용업 5
 
12.8%
한식_면류 5
 
12.8%
한식_육류 4
 
10.3%
이용업 2
 
5.1%
세탁업 1
 
2.6%

Length

2024-01-29T00:31:46.425365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T00:31:46.531196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한식_일반 15
38.5%
중식 7
17.9%
미용업 5
 
12.8%
한식_면류 5
 
12.8%
한식_육류 4
 
10.3%
이용업 2
 
5.1%
세탁업 1
 
2.6%

소재지주소
Text

UNIQUE 

Distinct39
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size444.0 B
2024-01-29T00:31:46.745095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length23
Mean length20.358974
Min length15

Characters and Unicode

Total characters794
Distinct characters60
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

Unique39 ?
Unique (%)100.0%

Sample

1st row인천광역시 남동구 용천로97번길3
2nd row인천광역시 남동구 용천로 91 1층
3rd row인천광역시 남동구 용천로 104-1
4th row인천광역시 남동구 성말로 53번길 27-1
5th row인천광역시 남동구 문화서로4번길25-8
ValueCountFrequency (%)
인천광역시 39
24.8%
남동구 39
24.8%
14 3
 
1.9%
1층 3
 
1.9%
21-5 2
 
1.3%
장승로 2
 
1.3%
하촌서로 2
 
1.3%
25 2
 
1.3%
복개동로 2
 
1.3%
용천로 2
 
1.3%
Other values (61) 61
38.9%
2024-01-29T00:31:47.057293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
118
 
14.9%
구 47
 
5.9%
동 46
 
5.8%
남 45
 
5.7%
천 44
 
5.5%
인 41
 
5.2%
로 39
 
4.9%
시 39
 
4.9%
역 39
 
4.9%
광 39
 
4.9%
Other values (50) 297
37.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 502
63.2%
Decimal Number 157
 
19.8%
Space Separator 118
 
14.9%
Dash Punctuation 11
 
1.4%
Other Punctuation 3
 
0.4%
Uppercase Letter 1
 
0.1%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 47
9.4%
동 46
9.2%
남 45
9.0%
천 44
8.8%
인 41
8.2%
로 39
 
7.8%
시 39
 
7.8%
역 39
 
7.8%
광 39
 
7.8%
번 22
 
4.4%
Other values (34) 101
20.1%
Decimal Number
ValueCountFrequency (%)
1 34
21.7%
2 21
13.4%
4 16
10.2%
3 16
10.2%
7 15
9.6%
5 15
9.6%
8 12
 
7.6%
0 12
 
7.6%
6 9
 
5.7%
9 7
 
4.5%
Space Separator
ValueCountFrequency (%)
118
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 502
63.2%
Common 291
36.6%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 47
9.4%
동 46
9.2%
남 45
9.0%
천 44
8.8%
인 41
8.2%
로 39
 
7.8%
시 39
 
7.8%
역 39
 
7.8%
광 39
 
7.8%
번 22
 
4.4%
Other values (34) 101
20.1%
Common
ValueCountFrequency (%)
118
40.5%
1 34
 
11.7%
2 21
 
7.2%
4 16
 
5.5%
3 16
 
5.5%
7 15
 
5.2%
5 15
 
5.2%
8 12
 
4.1%
0 12
 
4.1%
- 11
 
3.8%
Other values (5) 21
 
7.2%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 502
63.2%
ASCII 292
36.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
118
40.4%
1 34
 
11.6%
2 21
 
7.2%
4 16
 
5.5%
3 16
 
5.5%
7 15
 
5.1%
5 15
 
5.1%
8 12
 
4.1%
0 12
 
4.1%
- 11
 
3.8%
Other values (6) 22
 
7.5%
Hangul
ValueCountFrequency (%)
구 47
9.4%
동 46
9.2%
남 45
9.0%
천 44
8.8%
인 41
8.2%
로 39
 
7.8%
시 39
 
7.8%
역 39
 
7.8%
광 39
 
7.8%
번 22
 
4.4%
Other values (34) 101
20.1%

전화번호
Text

MISSING 

Distinct37
Distinct (%)100.0%
Missing2
Missing (%)5.1%
Memory size444.0 B
2024-01-29T00:31:47.237813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters444
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

Unique37 ?
Unique (%)100.0%

Sample

1st row032-473-0600
2nd row032-461-4776
3rd row032-468-8475
4th row032-441-2705
5th row032-433-8552
ValueCountFrequency (%)
032-465-8294 1
 
2.7%
032-467-7956 1
 
2.7%
032-472-3819 1
 
2.7%
032-467-3393 1
 
2.7%
032-464-5365 1
 
2.7%
032-467-0995 1
 
2.7%
032-466-6699 1
 
2.7%
032-461-3332 1
 
2.7%
032-468-2502 1
 
2.7%
032-471-8334 1
 
2.7%
Other values (27) 27
73.0%
2024-01-29T00:31:47.523044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 74
16.7%
3 67
15.1%
2 67
15.1%
4 53
11.9%
0 51
11.5%
6 37
8.3%
9 26
 
5.9%
5 24
 
5.4%
7 22
 
5.0%
1 14
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 370
83.3%
Dash Punctuation 74
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 67
18.1%
2 67
18.1%
4 53
14.3%
0 51
13.8%
6 37
10.0%
9 26
 
7.0%
5 24
 
6.5%
7 22
 
5.9%
1 14
 
3.8%
8 9
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 74
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 444
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 74
16.7%
3 67
15.1%
2 67
15.1%
4 53
11.9%
0 51
11.5%
6 37
8.3%
9 26
 
5.9%
5 24
 
5.4%
7 22
 
5.0%
1 14
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 444
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 74
16.7%
3 67
15.1%
2 67
15.1%
4 53
11.9%
0 51
11.5%
6 37
8.3%
9 26
 
5.9%
5 24
 
5.4%
7 22
 
5.0%
1 14
 
3.2%

대표메뉴명1
Text

Distinct28
Distinct (%)71.8%
Missing0
Missing (%)0.0%
Memory size444.0 B
2024-01-29T00:31:47.688191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length5.7948718
Min length4

Characters and Unicode

Total characters226
Distinct characters77
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

Unique23 ?
Unique (%)59.0%

Sample

1st row 고추장불고기
2nd row 삼겹살무한
3rd row 컷트
4th row 백반
5th row 자장면
ValueCountFrequency (%)
자장면 6
 
15.0%
컷트 3
 
7.5%
김밥 3
 
7.5%
잔치국수 2
 
5.0%
온모밀 2
 
5.0%
한식부페 1
 
2.5%
고추장불고기 1
 
2.5%
짜장면 1
 
2.5%
떡볶이 1
 
2.5%
왕돈까스 1
 
2.5%
Other values (19) 19
47.5%
2024-01-29T00:31:47.952076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
77
34.1%
장 13
 
5.8%
면 7
 
3.1%
자 6
 
2.7%
트 6
 
2.7%
컷 5
 
2.2%
국 5
 
2.2%
밥 4
 
1.8%
김 4
 
1.8%
식 4
 
1.8%
Other values (67) 95
42.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 137
60.6%
Space Separator 77
34.1%
Other Punctuation 4
 
1.8%
Open Punctuation 3
 
1.3%
Close Punctuation 3
 
1.3%
Uppercase Letter 1
 
0.4%
Decimal Number 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 13
 
9.5%
면 7
 
5.1%
자 6
 
4.4%
트 6
 
4.4%
컷 5
 
3.6%
국 5
 
3.6%
밥 4
 
2.9%
김 4
 
2.9%
식 4
 
2.9%
한 3
 
2.2%
Other values (61) 80
58.4%
Space Separator
ValueCountFrequency (%)
77
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Uppercase Letter
ValueCountFrequency (%)
Y 1
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 137
60.6%
Common 88
38.9%
Latin 1
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 13
 
9.5%
면 7
 
5.1%
자 6
 
4.4%
트 6
 
4.4%
컷 5
 
3.6%
국 5
 
3.6%
밥 4
 
2.9%
김 4
 
2.9%
식 4
 
2.9%
한 3
 
2.2%
Other values (61) 80
58.4%
Common
ValueCountFrequency (%)
77
87.5%
, 4
 
4.5%
( 3
 
3.4%
) 3
 
3.4%
2 1
 
1.1%
Latin
ValueCountFrequency (%)
Y 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 137
60.6%
ASCII 89
39.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
77
86.5%
, 4
 
4.5%
( 3
 
3.4%
) 3
 
3.4%
Y 1
 
1.1%
2 1
 
1.1%
Hangul
ValueCountFrequency (%)
장 13
 
9.5%
면 7
 
5.1%
자 6
 
4.4%
트 6
 
4.4%
컷 5
 
3.6%
국 5
 
3.6%
밥 4
 
2.9%
김 4
 
2.9%
식 4
 
2.9%
한 3
 
2.2%
Other values (61) 80
58.4%

대표메뉴1가격
Real number (ℝ)

Distinct16
Distinct (%)41.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6176.9231
Minimum1000
Maximum25000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2024-01-29T00:31:48.065036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1000
5-th percentile2400
Q14750
median5500
Q37000
95-th percentile10010
Maximum25000
Range24000
Interquartile range (IQR)2250

Descriptive statistics

Standard deviation3800.9321
Coefficient of variation (CV)0.61534393
Kurtosis15.693475
Mean6176.9231
Median Absolute Deviation (MAD)1500
Skewness3.2271753
Sum240900
Variance14447085
MonotonicityNot monotonic
2024-01-29T00:31:48.193856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
5000 8
20.5%
7000 7
17.9%
8000 6
15.4%
3000 3
 
7.7%
6000 2
 
5.1%
2500 2
 
5.1%
5500 2
 
5.1%
6500 1
 
2.6%
1000 1
 
2.6%
4000 1
 
2.6%
Other values (6) 6
15.4%
ValueCountFrequency (%)
1000 1
 
2.6%
1500 1
 
2.6%
2500 2
 
5.1%
3000 3
 
7.7%
3500 1
 
2.6%
4000 1
 
2.6%
4500 1
 
2.6%
5000 8
20.5%
5500 2
 
5.1%
6000 2
 
5.1%
ValueCountFrequency (%)
25000 1
 
2.6%
11000 1
 
2.6%
9900 1
 
2.6%
8000 6
15.4%
7000 7
17.9%
6500 1
 
2.6%
6000 2
 
5.1%
5500 2
 
5.1%
5000 8
20.5%
4500 1
 
2.6%

Interactions

2024-01-29T00:31:45.382043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:31:45.008451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:31:45.459751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:31:45.315440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-29T00:31:48.291693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업소명유형소재지주소전화번호대표메뉴명1대표메뉴1가격
연번1.0001.0000.3411.0001.0000.6700.000
업소명1.0001.0001.0001.0001.0001.0001.000
유형0.3411.0001.0001.0001.0000.9910.716
소재지주소1.0001.0001.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.0001.0001.000
대표메뉴명10.6701.0000.9911.0001.0001.0000.996
대표메뉴1가격0.0001.0000.7161.0001.0000.9961.000
2024-01-29T00:31:48.403402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번대표메뉴1가격유형
연번1.000-0.1680.149
대표메뉴1가격-0.1681.0000.320
유형0.1490.3201.000

Missing values

2024-01-29T00:31:45.550527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-29T00:31:45.643371image/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

연번업소명유형소재지주소전화번호대표메뉴명1대표메뉴1가격
01화미소금구이한식_육류인천광역시 남동구 용천로97번길3032-473-0600고추장불고기8000
12우돈먹는날한식_육류인천광역시 남동구 용천로 91 1층032-461-4776삼겹살무한11000
23끼머리방미용업인천광역시 남동구 용천로 104-1032-468-8475컷트7000
34행복식당한식_일반인천광역시 남동구 성말로 53번길 27-1032-441-2705백반7000
45소망각중식인천광역시 남동구 문화서로4번길25-8032-433-8552자장면3500
56중국성중식인천광역시 남동구 남동대로747번길51032-426-7979자장면4500
67남도추어탕한식_일반인천광역시 남동구 구월로266번길10032-473-0022추어탕8000
78큰집손칼국수한식_면류인천광역시 남동구 호구포로790번길 21-5032-469-4125잔치국수3000
89착한탕,국한식_일반인천광역시 남동구 호구포로800번길 17(구월동)032-465-8294선지해장국 ,2인분5000
910보람미용실미용업인천광역시 남동구 호구포로 790번길 21-5 A동12호032-469-2393일반펌25000
연번업소명유형소재지주소전화번호대표메뉴명1대표메뉴1가격
2930내고향만두한식_일반인천광역시 남동구 인주대로 888번길 27032-471-8334고기만두5000
3031유진헤어미용업인천광역시 남동구 담방서로 17번길 25032-462-3955컷트,(학생,경로)7000
3132큰손의정부,부대찌개한식_일반인천광역시 남동구 장승로 5032-467-6701부대찌개8000
3233항아리필한식_일반인천광역시 남동구 인주대로888번길 35<NA>한식뷔페7000
3334여명차이나중식인천광역시 남동구 장승로 49-1, 1층032-465-5522자장면5000
3435두리왕돈까스한식_일반인천광역시 남동구 장승남로 42, 105호032-467-5522왕돈까스6500
3536남촌컷트클럽이용업인천광역시 남동구 남촌동로35번길 3032-463-9923컷트8000
3637중국관중식인천광역시 남동구 은봉로 312번길 23 1층032-441-0644자장면5000
3738에바다떡볶이한식_일반인천광역시 남동구 장도로 4-2032-423-7494떡볶이3000
3839박가네삼감포한식_일반인천광역시 남동구 논현로46번길 14032-422-5449장어탕7000