Overview

Dataset statistics

Number of variables7
Number of observations207
Missing cells74
Missing cells (%)5.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.7 KiB
Average record size in memory57.6 B

Variable types

Numeric1
Categorical3
Text3

Dataset

Description인천광역시 남동구에 위치하는 특색 음식거리 현황에 대한 데이터로 연번, 거리명, 점포명, 유형, 위치, 연락처, 데이터기준일자를 제공합니다.
URLhttps://www.data.go.kr/data/15090599/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
연번 is highly overall correlated with 거리명High correlation
거리명 is highly overall correlated with 연번High correlation
연락처 has 74 (35.7%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 07:44:36.042810
Analysis finished2023-12-12 07:44:36.728290
Duration0.69 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct207
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean104
Minimum1
Maximum207
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-12T16:44:36.838162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile11.3
Q152.5
median104
Q3155.5
95-th percentile196.7
Maximum207
Range206
Interquartile range (IQR)103

Descriptive statistics

Standard deviation59.899917
Coefficient of variation (CV)0.57596074
Kurtosis-1.2
Mean104
Median Absolute Deviation (MAD)52
Skewness0
Sum21528
Variance3588
MonotonicityStrictly increasing
2023-12-12T16:44:36.966330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
2 1
 
0.5%
133 1
 
0.5%
134 1
 
0.5%
135 1
 
0.5%
136 1
 
0.5%
137 1
 
0.5%
138 1
 
0.5%
139 1
 
0.5%
140 1
 
0.5%
Other values (197) 197
95.2%
ValueCountFrequency (%)
1 1
0.5%
2 1
0.5%
3 1
0.5%
4 1
0.5%
5 1
0.5%
6 1
0.5%
7 1
0.5%
8 1
0.5%
9 1
0.5%
10 1
0.5%
ValueCountFrequency (%)
207 1
0.5%
206 1
0.5%
205 1
0.5%
204 1
0.5%
203 1
0.5%
202 1
0.5%
201 1
0.5%
200 1
0.5%
199 1
0.5%
198 1
0.5%

거리명
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
구월로데오음식문화거리
107 
구월문예길음식문화1번가
77 
소래포구신도로횟집거리
12 
운연동 추어마을
11 

Length

Max length12
Median length11
Mean length11.21256
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row구월문예길음식문화1번가
2nd row구월문예길음식문화1번가
3rd row구월문예길음식문화1번가
4th row구월문예길음식문화1번가
5th row구월문예길음식문화1번가

Common Values

ValueCountFrequency (%)
구월로데오음식문화거리 107
51.7%
구월문예길음식문화1번가 77
37.2%
소래포구신도로횟집거리 12
 
5.8%
운연동 추어마을 11
 
5.3%

Length

2023-12-12T16:44:37.110754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:44:37.234609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
구월로데오음식문화거리 107
49.1%
구월문예길음식문화1번가 77
35.3%
소래포구신도로횟집거리 12
 
5.5%
운연동 11
 
5.0%
추어마을 11
 
5.0%

점포명
Text

Distinct204
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-12T16:44:37.465155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length14
Mean length6.9855072
Min length2

Characters and Unicode

Total characters1446
Distinct characters369
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

Unique201 ?
Unique (%)97.1%

Sample

1st row주촌
2nd row감자탕형제들
3rd row홍두깨 칼국수
4th row용궁정
5th row송원식당
ValueCountFrequency (%)
구월점 10
 
4.2%
인천구월점 5
 
2.1%
구월로데오점 3
 
1.3%
김밥천국 2
 
0.8%
본점 2
 
0.8%
육시리 2
 
0.8%
타코비 2
 
0.8%
베스킨라빈스구월점 1
 
0.4%
천유향 1
 
0.4%
황해수육구월로데오점 1
 
0.4%
Other values (209) 209
87.8%
2023-12-12T16:44:37.945772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
구 70
 
4.8%
점 68
 
4.7%
월 59
 
4.1%
31
 
2.1%
천 25
 
1.7%
) 22
 
1.5%
오 21
 
1.5%
( 21
 
1.5%
인 21
 
1.5%
집 20
 
1.4%
Other values (359) 1088
75.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1297
89.7%
Space Separator 31
 
2.1%
Lowercase Letter 24
 
1.7%
Decimal Number 23
 
1.6%
Uppercase Letter 23
 
1.6%
Close Punctuation 22
 
1.5%
Open Punctuation 21
 
1.5%
Other Punctuation 4
 
0.3%
Modifier Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 70
 
5.4%
점 68
 
5.2%
월 59
 
4.5%
천 25
 
1.9%
오 21
 
1.6%
인 21
 
1.6%
집 20
 
1.5%
리 18
 
1.4%
스 17
 
1.3%
로 17
 
1.3%
Other values (316) 961
74.1%
Uppercase Letter
ValueCountFrequency (%)
O 4
17.4%
K 2
 
8.7%
I 2
 
8.7%
N 2
 
8.7%
R 2
 
8.7%
P 2
 
8.7%
E 1
 
4.3%
B 1
 
4.3%
J 1
 
4.3%
L 1
 
4.3%
Other values (5) 5
21.7%
Lowercase Letter
ValueCountFrequency (%)
e 5
20.8%
o 3
12.5%
t 3
12.5%
y 2
 
8.3%
b 2
 
8.3%
s 2
 
8.3%
a 1
 
4.2%
r 1
 
4.2%
m 1
 
4.2%
p 1
 
4.2%
Other values (3) 3
12.5%
Decimal Number
ValueCountFrequency (%)
0 6
26.1%
9 4
17.4%
4 3
13.0%
1 2
 
8.7%
3 2
 
8.7%
8 2
 
8.7%
2 2
 
8.7%
7 1
 
4.3%
5 1
 
4.3%
Other Punctuation
ValueCountFrequency (%)
. 2
50.0%
& 2
50.0%
Space Separator
ValueCountFrequency (%)
31
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1297
89.7%
Common 102
 
7.1%
Latin 47
 
3.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 70
 
5.4%
점 68
 
5.2%
월 59
 
4.5%
천 25
 
1.9%
오 21
 
1.6%
인 21
 
1.6%
집 20
 
1.5%
리 18
 
1.4%
스 17
 
1.3%
로 17
 
1.3%
Other values (316) 961
74.1%
Latin
ValueCountFrequency (%)
e 5
 
10.6%
O 4
 
8.5%
o 3
 
6.4%
t 3
 
6.4%
y 2
 
4.3%
K 2
 
4.3%
b 2
 
4.3%
s 2
 
4.3%
I 2
 
4.3%
N 2
 
4.3%
Other values (18) 20
42.6%
Common
ValueCountFrequency (%)
31
30.4%
) 22
21.6%
( 21
20.6%
0 6
 
5.9%
9 4
 
3.9%
4 3
 
2.9%
1 2
 
2.0%
3 2
 
2.0%
8 2
 
2.0%
. 2
 
2.0%
Other values (5) 7
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1297
89.7%
ASCII 149
 
10.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
구 70
 
5.4%
점 68
 
5.2%
월 59
 
4.5%
천 25
 
1.9%
오 21
 
1.6%
인 21
 
1.6%
집 20
 
1.5%
리 18
 
1.4%
스 17
 
1.3%
로 17
 
1.3%
Other values (316) 961
74.1%
ASCII
ValueCountFrequency (%)
31
20.8%
) 22
14.8%
( 21
14.1%
0 6
 
4.0%
e 5
 
3.4%
9 4
 
2.7%
O 4
 
2.7%
o 3
 
2.0%
4 3
 
2.0%
t 3
 
2.0%
Other values (33) 47
31.5%

유형
Categorical

Distinct19
Distinct (%)9.2%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
한식
69 
기타
25 
호프/통닭
24 
정종/대포집/소주방
19 
식육(숯불구이)
18 
Other values (14)
52 

Length

Max length10
Median length2
Mean length3.9323671
Min length2

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st row식육(숯불구이)
2nd row한식
3rd row한식
4th row한식
5th row한식

Common Values

ValueCountFrequency (%)
한식 69
33.3%
기타 25
 
12.1%
호프/통닭 24
 
11.6%
정종/대포집/소주방 19
 
9.2%
식육(숯불구이) 18
 
8.7%
횟집 15
 
7.2%
커피숍 8
 
3.9%
분식 5
 
2.4%
<NA> 3
 
1.4%
일식 3
 
1.4%
Other values (9) 18
 
8.7%

Length

2023-12-12T16:44:38.134900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 69
33.0%
기타 27
 
12.9%
호프/통닭 24
 
11.5%
정종/대포집/소주방 19
 
9.1%
식육(숯불구이 18
 
8.6%
횟집 15
 
7.2%
커피숍 8
 
3.8%
분식 5
 
2.4%
중국식 3
 
1.4%
일식 3
 
1.4%
Other values (9) 18
 
8.6%

위치
Text

Distinct204
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-12T16:44:38.415094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length47
Mean length36.898551
Min length22

Characters and Unicode

Total characters7638
Distinct characters103
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

Unique201 ?
Unique (%)97.1%

Sample

1st row인천광역시 남동구 문화서로4번길 41-42 (구월동,(문화서로4번길 41-42) 1층일부)
2nd row인천광역시 남동구 문화서로4번길 65 (구월동, 1층)
3rd row인천광역시 남동구 문화서로4번길 61-34 (구월동,(문화서로4번길61-34))
4th row인천광역시 남동구 문화서로4번길 61-36, 1층 (구월동)
5th row인천광역시 남동구 문화서로4번길 61-14 (구월동)
ValueCountFrequency (%)
남동구 207
 
14.7%
인천광역시 201
 
14.3%
구월동 149
 
10.6%
1층 88
 
6.3%
문화서로4번길 53
 
3.8%
인하로 34
 
2.4%
성말로 32
 
2.3%
10 29
 
2.1%
인하로489번길 28
 
2.0%
2층 16
 
1.1%
Other values (237) 569
40.5%
2023-12-12T16:44:38.904872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1206
 
15.8%
1 423
 
5.5%
동 419
 
5.5%
구 400
 
5.2%
인 289
 
3.8%
, 268
 
3.5%
로 237
 
3.1%
) 228
 
3.0%
( 228
 
3.0%
남 209
 
2.7%
Other values (93) 3731
48.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4109
53.8%
Decimal Number 1491
 
19.5%
Space Separator 1206
 
15.8%
Other Punctuation 268
 
3.5%
Close Punctuation 228
 
3.0%
Open Punctuation 228
 
3.0%
Dash Punctuation 99
 
1.3%
Math Symbol 5
 
0.1%
Uppercase Letter 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 419
 
10.2%
구 400
 
9.7%
인 289
 
7.0%
로 237
 
5.8%
남 209
 
5.1%
시 205
 
5.0%
역 201
 
4.9%
광 201
 
4.9%
천 201
 
4.9%
월 183
 
4.5%
Other values (75) 1564
38.1%
Decimal Number
ValueCountFrequency (%)
1 423
28.4%
4 209
14.0%
2 182
12.2%
0 177
11.9%
3 100
 
6.7%
8 87
 
5.8%
9 85
 
5.7%
6 84
 
5.6%
7 79
 
5.3%
5 65
 
4.4%
Uppercase Letter
ValueCountFrequency (%)
B 3
75.0%
A 1
 
25.0%
Space Separator
ValueCountFrequency (%)
1206
100.0%
Other Punctuation
ValueCountFrequency (%)
, 268
100.0%
Close Punctuation
ValueCountFrequency (%)
) 228
100.0%
Open Punctuation
ValueCountFrequency (%)
( 228
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 99
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4109
53.8%
Common 3525
46.2%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 419
 
10.2%
구 400
 
9.7%
인 289
 
7.0%
로 237
 
5.8%
남 209
 
5.1%
시 205
 
5.0%
역 201
 
4.9%
광 201
 
4.9%
천 201
 
4.9%
월 183
 
4.5%
Other values (75) 1564
38.1%
Common
ValueCountFrequency (%)
1206
34.2%
1 423
 
12.0%
, 268
 
7.6%
) 228
 
6.5%
( 228
 
6.5%
4 209
 
5.9%
2 182
 
5.2%
0 177
 
5.0%
3 100
 
2.8%
- 99
 
2.8%
Other values (6) 405
 
11.5%
Latin
ValueCountFrequency (%)
B 3
75.0%
A 1
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4109
53.8%
ASCII 3529
46.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1206
34.2%
1 423
 
12.0%
, 268
 
7.6%
) 228
 
6.5%
( 228
 
6.5%
4 209
 
5.9%
2 182
 
5.2%
0 177
 
5.0%
3 100
 
2.8%
- 99
 
2.8%
Other values (8) 409
 
11.6%
Hangul
ValueCountFrequency (%)
동 419
 
10.2%
구 400
 
9.7%
인 289
 
7.0%
로 237
 
5.8%
남 209
 
5.1%
시 205
 
5.0%
역 201
 
4.9%
광 201
 
4.9%
천 201
 
4.9%
월 183
 
4.5%
Other values (75) 1564
38.1%

연락처
Text

MISSING 

Distinct132
Distinct (%)99.2%
Missing74
Missing (%)35.7%
Memory size1.7 KiB
2023-12-12T16:44:39.189597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters1596
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

Unique131 ?
Unique (%)98.5%

Sample

1st row032-427-9279
2nd row032-438-4400
3rd row032-424-8256
4th row032-438-0500
5th row032-432-6948
ValueCountFrequency (%)
032-422-6446 2
 
1.5%
032-423-8839 1
 
0.8%
032-427-9279 1
 
0.8%
032-424-2202 1
 
0.8%
032-427-2217 1
 
0.8%
032-442-3550 1
 
0.8%
032-421-3558 1
 
0.8%
032-433-4984 1
 
0.8%
032-439-4392 1
 
0.8%
032-421-4351 1
 
0.8%
Other values (122) 122
91.7%
2023-12-12T16:44:39.601145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 282
17.7%
- 266
16.7%
3 258
16.2%
4 202
12.7%
0 199
12.5%
6 79
 
4.9%
1 78
 
4.9%
8 61
 
3.8%
9 60
 
3.8%
7 56
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1330
83.3%
Dash Punctuation 266
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 282
21.2%
3 258
19.4%
4 202
15.2%
0 199
15.0%
6 79
 
5.9%
1 78
 
5.9%
8 61
 
4.6%
9 60
 
4.5%
7 56
 
4.2%
5 55
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 266
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1596
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 282
17.7%
- 266
16.7%
3 258
16.2%
4 202
12.7%
0 199
12.5%
6 79
 
4.9%
1 78
 
4.9%
8 61
 
3.8%
9 60
 
3.8%
7 56
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1596
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 282
17.7%
- 266
16.7%
3 258
16.2%
4 202
12.7%
0 199
12.5%
6 79
 
4.9%
1 78
 
4.9%
8 61
 
3.8%
9 60
 
3.8%
7 56
 
3.5%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-06-07
207 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-06-07
2nd row2023-06-07
3rd row2023-06-07
4th row2023-06-07
5th row2023-06-07

Common Values

ValueCountFrequency (%)
2023-06-07 207
100.0%

Length

2023-12-12T16:44:39.763479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:44:39.882500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-06-07 207
100.0%

Interactions

2023-12-12T16:44:36.400168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T16:44:39.952464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번거리명유형
연번1.0000.8880.440
거리명0.8881.0000.483
유형0.4400.4831.000
2023-12-12T16:44:40.063488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
유형거리명
유형1.0000.273
거리명0.2731.000
2023-12-12T16:44:40.191640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번거리명유형
연번1.0000.7400.177
거리명0.7401.0000.273
유형0.1770.2731.000

Missing values

2023-12-12T16:44:36.501450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:44:36.670065image/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

연번거리명점포명유형위치연락처데이터기준일자
01구월문예길음식문화1번가주촌식육(숯불구이)인천광역시 남동구 문화서로4번길 41-42 (구월동,(문화서로4번길 41-42) 1층일부)032-427-92792023-06-07
12구월문예길음식문화1번가감자탕형제들한식인천광역시 남동구 문화서로4번길 65 (구월동, 1층)032-438-44002023-06-07
23구월문예길음식문화1번가홍두깨 칼국수한식인천광역시 남동구 문화서로4번길 61-34 (구월동,(문화서로4번길61-34))032-424-82562023-06-07
34구월문예길음식문화1번가용궁정한식인천광역시 남동구 문화서로4번길 61-36, 1층 (구월동)032-438-05002023-06-07
45구월문예길음식문화1번가송원식당한식인천광역시 남동구 문화서로4번길 61-14 (구월동)032-432-69482023-06-07
56구월문예길음식문화1번가(닭치고)춘천전통닭갈비한식인천광역시 남동구 문화서로4번길 61-24 (구월동, 1층)032-423-03302023-06-07
67구월문예길음식문화1번가미소식당횟집인천광역시 남동구 문화서로4번길 61-47 (구월동)032-421-11072023-06-07
78구월문예길음식문화1번가연안식당한식인천광역시 남동구 문화서로4번길 61-1 (구월동)032-437-94662023-06-07
89구월문예길음식문화1번가화미원중국식인천광역시 남동구 문화서로4번길 47-1 (구월동, 1층일부)032-432-00702023-06-07
910구월문예길음식문화1번가참치다미시일식인천광역시 남동구 문화서로4번길 61-3, 1층 (구월동)032-423-99962023-06-07
연번거리명점포명유형위치연락처데이터기준일자
197198구월로데오음식문화거리카페204기타인천광역시 남동구 인하로507번길 21-1, 지하1층 일부호 (구월동)<NA>2023-06-07
198199구월로데오음식문화거리앰비언트정종/대포집/소주방인천광역시 남동구 인하로507번길 21, 승관빌딩 2층 일부호 (구월동)<NA>2023-06-07
199200구월로데오음식문화거리잇츠(Eat`s)기타인천광역시 남동구 인하로507번길 9, 4층 401호 (구월동, 하나빌딩)032-432-75002023-06-07
200201구월로데오음식문화거리더종로빈대떡분식인천광역시 남동구 인하로507번길 9, 1층 105호 (구월동, 하나빌딩)<NA>2023-06-07
201202구월로데오음식문화거리새마을식당육 인천구월점식육(숯불구이)인천광역시 남동구 인하로507번길 9, 하나빌딩 1층 103호,104호 (구월동)<NA>2023-06-07
202203구월로데오음식문화거리베스킨라빈스구월점아이스크림남동구 인하로489번길 16 (구월동,(인하로489번길16) 세동네오스빌딩101호)<NA>2023-06-07
203204구월로데오음식문화거리제줏간 인천구월점기타남동구 인하로 497-28, 노빌리안 1 1층 116호 (구월동)<NA>2023-06-07
204205구월로데오음식문화거리리파인 구월점기타남동구 인하로 497-28, 노빌리안 1 2층 206호 (구월동)<NA>2023-06-07
205206구월로데오음식문화거리빨라쪼인천구월로데오점커피숍남동구 인하로489번길 16, 세동네오스 1층 105호 (구월동)<NA>2023-06-07
206207구월로데오음식문화거리천유향 마라샹궈 (구월점)기타남동구 인하로489번길 16, 세동네오스 1층 106호 (구월동)<NA>2023-06-07