Overview

Dataset statistics

Number of variables8
Number of observations815
Missing cells6
Missing cells (%)0.1%
Duplicate rows1
Duplicate rows (%)0.1%
Total size in memory51.1 KiB
Average record size in memory64.2 B

Variable types

Categorical2
Text3
DateTime3

Dataset

Description인천광역시 계양구 휴게음식점 현황입니다. 업종명, 업태명, 업소명, 소재지, 인허가일자 등을 포함하는 파일입니다.
Author인천광역시 계양구
URLhttps://www.data.go.kr/data/15062375/fileData.do

Alerts

업종명 has constant value ""Constant
데이터기준일 has constant value ""Constant
Dataset has 1 (0.1%) duplicate rowsDuplicates

Reproduction

Analysis started2024-03-14 10:04:13.805572
Analysis finished2024-03-14 10:04:15.790514
Duration1.98 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
휴게음식점
815 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
휴게음식점 815
100.0%

Length

2024-03-14T19:04:15.991475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T19:04:16.299118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
휴게음식점 815
100.0%

업태명
Categorical

Distinct11
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
커피숍
309 
편의점
163 
일반조리판매
141 
기타 휴게음식점
107 
패스트푸드
39 
Other values (6)
56 

Length

Max length8
Median length3
Mean length4.2625767
Min length2

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
커피숍 309
37.9%
편의점 163
20.0%
일반조리판매 141
17.3%
기타 휴게음식점 107
 
13.1%
패스트푸드 39
 
4.8%
다방 36
 
4.4%
아이스크림 7
 
0.9%
푸드트럭 5
 
0.6%
키즈카페 4
 
0.5%
철도역구내 3
 
0.4%

Length

2024-03-14T19:04:16.659359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
커피숍 309
33.5%
편의점 163
17.7%
일반조리판매 141
15.3%
기타 107
 
11.6%
휴게음식점 107
 
11.6%
패스트푸드 39
 
4.2%
다방 36
 
3.9%
아이스크림 7
 
0.8%
푸드트럭 5
 
0.5%
키즈카페 4
 
0.4%
Other values (2) 4
 
0.4%

업소명
Text

Distinct808
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
2024-03-14T19:04:17.524528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length24
Mean length8.5214724
Min length2

Characters and Unicode

Total characters6945
Distinct characters537
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique801 ?
Unique (%)98.3%

Sample

1st row성다방
2nd row원다방
3rd row대왕다방
4th row금당다방
5th row천궁다방
ValueCountFrequency (%)
세븐일레븐 23
 
2.3%
씨유 11
 
1.1%
계양구청점 9
 
0.9%
이디야 7
 
0.7%
계산역점 7
 
0.7%
인천계양구청점 5
 
0.5%
인천동양점 5
 
0.5%
계산점 4
 
0.4%
빽다방 4
 
0.4%
효성점 4
 
0.4%
Other values (855) 921
92.1%
2024-03-14T19:04:18.853926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 425
 
6.1%
계 216
 
3.1%
185
 
2.7%
인 158
 
2.3%
스 158
 
2.3%
양 150
 
2.2%
이 145
 
2.1%
피 138
 
2.0%
천 128
 
1.8%
븐 120
 
1.7%
Other values (527) 5122
73.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5789
83.4%
Uppercase Letter 322
 
4.6%
Lowercase Letter 213
 
3.1%
Decimal Number 202
 
2.9%
Space Separator 185
 
2.7%
Close Punctuation 105
 
1.5%
Open Punctuation 104
 
1.5%
Other Punctuation 23
 
0.3%
Math Symbol 1
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 425
 
7.3%
계 216
 
3.7%
인 158
 
2.7%
스 158
 
2.7%
양 150
 
2.6%
이 145
 
2.5%
피 138
 
2.4%
천 128
 
2.2%
븐 120
 
2.1%
커 103
 
1.8%
Other values (458) 4048
69.9%
Uppercase Letter
ValueCountFrequency (%)
C 58
18.0%
S 35
10.9%
P 31
9.6%
G 29
 
9.0%
E 21
 
6.5%
A 19
 
5.9%
U 17
 
5.3%
D 14
 
4.3%
R 13
 
4.0%
F 11
 
3.4%
Other values (15) 74
23.0%
Lowercase Letter
ValueCountFrequency (%)
e 35
16.4%
a 25
11.7%
s 17
 
8.0%
r 15
 
7.0%
f 14
 
6.6%
l 12
 
5.6%
t 12
 
5.6%
o 12
 
5.6%
c 11
 
5.2%
i 10
 
4.7%
Other values (12) 50
23.5%
Decimal Number
ValueCountFrequency (%)
2 75
37.1%
5 50
24.8%
4 18
 
8.9%
1 15
 
7.4%
3 15
 
7.4%
9 13
 
6.4%
0 6
 
3.0%
8 5
 
2.5%
7 4
 
2.0%
6 1
 
0.5%
Other Punctuation
ValueCountFrequency (%)
& 7
30.4%
. 6
26.1%
, 5
21.7%
: 2
 
8.7%
/ 1
 
4.3%
# 1
 
4.3%
' 1
 
4.3%
Space Separator
ValueCountFrequency (%)
185
100.0%
Close Punctuation
ValueCountFrequency (%)
) 105
100.0%
Open Punctuation
ValueCountFrequency (%)
( 104
100.0%
Math Symbol
ValueCountFrequency (%)
＋ 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5789
83.4%
Common 621
 
8.9%
Latin 535
 
7.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 425
 
7.3%
계 216
 
3.7%
인 158
 
2.7%
스 158
 
2.7%
양 150
 
2.6%
이 145
 
2.5%
피 138
 
2.4%
천 128
 
2.2%
븐 120
 
2.1%
커 103
 
1.8%
Other values (458) 4048
69.9%
Latin
ValueCountFrequency (%)
C 58
 
10.8%
S 35
 
6.5%
e 35
 
6.5%
P 31
 
5.8%
G 29
 
5.4%
a 25
 
4.7%
E 21
 
3.9%
A 19
 
3.6%
U 17
 
3.2%
s 17
 
3.2%
Other values (37) 248
46.4%
Common
ValueCountFrequency (%)
185
29.8%
) 105
16.9%
( 104
16.7%
2 75
12.1%
5 50
 
8.1%
4 18
 
2.9%
1 15
 
2.4%
3 15
 
2.4%
9 13
 
2.1%
& 7
 
1.1%
Other values (12) 34
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5789
83.4%
ASCII 1155
 
16.6%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 425
 
7.3%
계 216
 
3.7%
인 158
 
2.7%
스 158
 
2.7%
양 150
 
2.6%
이 145
 
2.5%
피 138
 
2.4%
천 128
 
2.2%
븐 120
 
2.1%
커 103
 
1.8%
Other values (458) 4048
69.9%
ASCII
ValueCountFrequency (%)
185
16.0%
) 105
 
9.1%
( 104
 
9.0%
2 75
 
6.5%
C 58
 
5.0%
5 50
 
4.3%
S 35
 
3.0%
e 35
 
3.0%
P 31
 
2.7%
G 29
 
2.5%
Other values (58) 448
38.8%
None
ValueCountFrequency (%)
＋ 1
100.0%

소재지(도로명)
Text

Distinct781
Distinct (%)96.4%
Missing5
Missing (%)0.6%
Memory size6.5 KiB
2024-03-14T19:04:19.942852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length54
Mean length35.97037
Min length21

Characters and Unicode

Total characters29136
Distinct characters298
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique762 ?
Unique (%)94.1%

Sample

1st row인천광역시 계양구 주부토로 565 (계산동)
2nd row인천광역시 계양구 주부토로 395, 지하1층 (작전동)
3rd row인천광역시 계양구 안남로 467 (효성동)
4th row인천광역시 계양구 주부토로 388, 1층 (작전동)
5th row인천광역시 계양구 계양대로89번길 1 (작전동)
ValueCountFrequency (%)
인천광역시 810
 
13.6%
계양구 810
 
13.6%
1층 535
 
9.0%
일부호 349
 
5.9%
계산동 244
 
4.1%
작전동 171
 
2.9%
효성동 98
 
1.6%
장제로 71
 
1.2%
계양대로 62
 
1.0%
2층 46
 
0.8%
Other values (974) 2754
46.3%
2024-03-14T19:04:21.474718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5143
 
17.7%
1 1613
 
5.5%
계 1343
 
4.6%
양 1050
 
3.6%
동 980
 
3.4%
, 977
 
3.4%
) 837
 
2.9%
( 837
 
2.9%
천 833
 
2.9%
역 829
 
2.8%
Other values (288) 14694
50.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16838
57.8%
Space Separator 5143
 
17.7%
Decimal Number 4309
 
14.8%
Other Punctuation 987
 
3.4%
Close Punctuation 837
 
2.9%
Open Punctuation 837
 
2.9%
Uppercase Letter 114
 
0.4%
Dash Punctuation 57
 
0.2%
Lowercase Letter 12
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
계 1343
 
8.0%
양 1050
 
6.2%
동 980
 
5.8%
천 833
 
4.9%
역 829
 
4.9%
시 828
 
4.9%
인 825
 
4.9%
광 812
 
4.8%
구 812
 
4.8%
로 775
 
4.6%
Other values (246) 7751
46.0%
Uppercase Letter
ValueCountFrequency (%)
B 19
16.7%
A 11
9.6%
S 10
8.8%
E 9
 
7.9%
O 9
 
7.9%
P 8
 
7.0%
M 7
 
6.1%
L 6
 
5.3%
C 6
 
5.3%
U 5
 
4.4%
Other values (7) 24
21.1%
Decimal Number
ValueCountFrequency (%)
1 1613
37.4%
2 462
 
10.7%
0 430
 
10.0%
3 334
 
7.8%
5 298
 
6.9%
4 261
 
6.1%
7 259
 
6.0%
8 237
 
5.5%
9 222
 
5.2%
6 193
 
4.5%
Lowercase Letter
ValueCountFrequency (%)
e 5
41.7%
b 1
 
8.3%
c 1
 
8.3%
l 1
 
8.3%
d 1
 
8.3%
i 1
 
8.3%
x 1
 
8.3%
p 1
 
8.3%
Other Punctuation
ValueCountFrequency (%)
, 977
99.0%
. 10
 
1.0%
Space Separator
ValueCountFrequency (%)
5143
100.0%
Close Punctuation
ValueCountFrequency (%)
) 837
100.0%
Open Punctuation
ValueCountFrequency (%)
( 837
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 57
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16838
57.8%
Common 12172
41.8%
Latin 126
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
계 1343
 
8.0%
양 1050
 
6.2%
동 980
 
5.8%
천 833
 
4.9%
역 829
 
4.9%
시 828
 
4.9%
인 825
 
4.9%
광 812
 
4.8%
구 812
 
4.8%
로 775
 
4.6%
Other values (246) 7751
46.0%
Latin
ValueCountFrequency (%)
B 19
15.1%
A 11
 
8.7%
S 10
 
7.9%
E 9
 
7.1%
O 9
 
7.1%
P 8
 
6.3%
M 7
 
5.6%
L 6
 
4.8%
C 6
 
4.8%
e 5
 
4.0%
Other values (15) 36
28.6%
Common
ValueCountFrequency (%)
5143
42.3%
1 1613
 
13.3%
, 977
 
8.0%
) 837
 
6.9%
( 837
 
6.9%
2 462
 
3.8%
0 430
 
3.5%
3 334
 
2.7%
5 298
 
2.4%
4 261
 
2.1%
Other values (7) 980
 
8.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16838
57.8%
ASCII 12298
42.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5143
41.8%
1 1613
 
13.1%
, 977
 
7.9%
) 837
 
6.8%
( 837
 
6.8%
2 462
 
3.8%
0 430
 
3.5%
3 334
 
2.7%
5 298
 
2.4%
4 261
 
2.1%
Other values (32) 1106
 
9.0%
Hangul
ValueCountFrequency (%)
계 1343
 
8.0%
양 1050
 
6.2%
동 980
 
5.8%
천 833
 
4.9%
역 829
 
4.9%
시 828
 
4.9%
인 825
 
4.9%
광 812
 
4.8%
구 812
 
4.8%
로 775
 
4.6%
Other values (246) 7751
46.0%

소재지(지번)
Text

Distinct772
Distinct (%)94.8%
Missing1
Missing (%)0.1%
Memory size6.5 KiB
2024-03-14T19:04:22.666228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length43
Mean length26.251843
Min length16

Characters and Unicode

Total characters21369
Distinct characters286
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique742 ?
Unique (%)91.2%

Sample

1st row인천광역시 계양구 계산동 922-13
2nd row인천광역시 계양구 작전동 871-24
3rd row인천광역시 계양구 효성동 331-6
4th row인천광역시 계양구 작전동 197-1
5th row인천광역시 계양구 작전동 864-28
ValueCountFrequency (%)
인천광역시 814
18.7%
계양구 814
18.7%
계산동 263
 
6.1%
작전동 191
 
4.4%
1층 141
 
3.2%
효성동 104
 
2.4%
1층일부호 63
 
1.5%
일부호 57
 
1.3%
일부 56
 
1.3%
임학동 51
 
1.2%
Other values (999) 1789
41.2%
2024-03-14T19:04:24.348142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4071
19.1%
1 1165
 
5.5%
계 1140
 
5.3%
동 922
 
4.3%
양 899
 
4.2%
역 831
 
3.9%
인 828
 
3.9%
천 823
 
3.9%
광 816
 
3.8%
구 816
 
3.8%
Other values (276) 9058
42.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12100
56.6%
Decimal Number 4293
 
20.1%
Space Separator 4071
 
19.1%
Dash Punctuation 699
 
3.3%
Uppercase Letter 101
 
0.5%
Other Punctuation 41
 
0.2%
Open Punctuation 23
 
0.1%
Close Punctuation 23
 
0.1%
Lowercase Letter 12
 
0.1%
Other Number 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
계 1140
 
9.4%
동 922
 
7.6%
양 899
 
7.4%
역 831
 
6.9%
인 828
 
6.8%
천 823
 
6.8%
광 816
 
6.7%
구 816
 
6.7%
시 814
 
6.7%
호 330
 
2.7%
Other values (230) 3881
32.1%
Uppercase Letter
ValueCountFrequency (%)
B 11
10.9%
S 10
9.9%
E 9
 
8.9%
O 9
 
8.9%
A 8
 
7.9%
P 7
 
6.9%
M 7
 
6.9%
L 6
 
5.9%
H 5
 
5.0%
C 5
 
5.0%
Other values (7) 24
23.8%
Decimal Number
ValueCountFrequency (%)
1 1165
27.1%
2 489
11.4%
0 423
 
9.9%
3 368
 
8.6%
6 353
 
8.2%
9 351
 
8.2%
4 328
 
7.6%
8 319
 
7.4%
5 289
 
6.7%
7 208
 
4.8%
Lowercase Letter
ValueCountFrequency (%)
e 5
41.7%
b 2
 
16.7%
i 1
 
8.3%
d 1
 
8.3%
p 1
 
8.3%
l 1
 
8.3%
x 1
 
8.3%
Other Number
ValueCountFrequency (%)
④ 1
25.0%
③ 1
25.0%
② 1
25.0%
① 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 35
85.4%
. 6
 
14.6%
Math Symbol
ValueCountFrequency (%)
+ 1
50.0%
~ 1
50.0%
Space Separator
ValueCountFrequency (%)
4071
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 699
100.0%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12100
56.6%
Common 9156
42.8%
Latin 113
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
계 1140
 
9.4%
동 922
 
7.6%
양 899
 
7.4%
역 831
 
6.9%
인 828
 
6.8%
천 823
 
6.8%
광 816
 
6.7%
구 816
 
6.7%
시 814
 
6.7%
호 330
 
2.7%
Other values (230) 3881
32.1%
Latin
ValueCountFrequency (%)
B 11
 
9.7%
S 10
 
8.8%
E 9
 
8.0%
O 9
 
8.0%
A 8
 
7.1%
P 7
 
6.2%
M 7
 
6.2%
L 6
 
5.3%
e 5
 
4.4%
H 5
 
4.4%
Other values (14) 36
31.9%
Common
ValueCountFrequency (%)
4071
44.5%
1 1165
 
12.7%
- 699
 
7.6%
2 489
 
5.3%
0 423
 
4.6%
3 368
 
4.0%
6 353
 
3.9%
9 351
 
3.8%
4 328
 
3.6%
8 319
 
3.5%
Other values (12) 590
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12100
56.6%
ASCII 9265
43.4%
Enclosed Alphanum 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4071
43.9%
1 1165
 
12.6%
- 699
 
7.5%
2 489
 
5.3%
0 423
 
4.6%
3 368
 
4.0%
6 353
 
3.8%
9 351
 
3.8%
4 328
 
3.5%
8 319
 
3.4%
Other values (32) 699
 
7.5%
Hangul
ValueCountFrequency (%)
계 1140
 
9.4%
동 922
 
7.6%
양 899
 
7.4%
역 831
 
6.9%
인 828
 
6.8%
천 823
 
6.8%
광 816
 
6.7%
구 816
 
6.7%
시 814
 
6.7%
호 330
 
2.7%
Other values (230) 3881
32.1%
Enclosed Alphanum
ValueCountFrequency (%)
④ 1
25.0%
③ 1
25.0%
② 1
25.0%
① 1
25.0%

영업자시작일
Date

Distinct644
Distinct (%)79.0%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
Minimum1999-12-30 00:00:00
Maximum2024-02-22 00:00:00
2024-03-14T19:04:24.749084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:04:25.189597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가일자
Date

Distinct713
Distinct (%)87.5%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
Minimum1979-08-10 00:00:00
Maximum2024-02-19 00:00:00
2024-03-14T19:04:25.585556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:04:26.003361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
Minimum2024-03-07 00:00:00
Maximum2024-03-07 00:00:00
2024-03-14T19:04:26.357938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:04:26.652841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Missing values

2024-03-14T19:04:14.926913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T19:04:15.351366image/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.
2024-03-14T19:04:15.655165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

업종명업태명업소명소재지(도로명)소재지(지번)영업자시작일인허가일자데이터기준일
0휴게음식점다방성다방인천광역시 계양구 주부토로 565 (계산동)인천광역시 계양구 계산동 922-132007-07-061979-08-102024-03-07
1휴게음식점다방원다방인천광역시 계양구 주부토로 395, 지하1층 (작전동)인천광역시 계양구 작전동 871-242017-04-211980-12-242024-03-07
2휴게음식점다방대왕다방인천광역시 계양구 안남로 467 (효성동)인천광역시 계양구 효성동 331-62014-02-251981-07-252024-03-07
3휴게음식점다방금당다방인천광역시 계양구 주부토로 388, 1층 (작전동)인천광역시 계양구 작전동 197-12012-05-181982-04-022024-03-07
4휴게음식점다방천궁다방인천광역시 계양구 계양대로89번길 1 (작전동)인천광역시 계양구 작전동 864-282013-07-291983-01-262024-03-07
5휴게음식점다방한성커피숍인천광역시 계양구 계양대로 64, 지층 (작전동, 지하1층 )인천광역시 계양구 작전동 866-12011-11-031984-11-272024-03-07
6휴게음식점다방영다방인천광역시 계양구 효서로 299, 지하1층 (작전동)인천광역시 계양구 작전동 871-78 지하1층2019-11-181986-04-182024-03-07
7휴게음식점다방정다방인천광역시 계양구 안남로 496 (효성동)인천광역시 계양구 효성동 272-122016-11-211988-06-142024-03-07
8휴게음식점다방명보다방인천광역시 계양구 주부토로 478 (계산동,지하1층)인천광역시 계양구 계산동 305-2 지하1층2013-09-051990-02-262024-03-07
9휴게음식점다방석다방인천광역시 계양구 계산시장길 11, 지하1층 (계산동)인천광역시 계양구 계산동 958-192011-11-281990-02-152024-03-07
업종명업태명업소명소재지(도로명)소재지(지번)영업자시작일인허가일자데이터기준일
805휴게음식점커피숍1009인천광역시 계양구 계양대로 28 (주)호텔카리스 지하1층 일부호 (작전동)인천광역시 계양구 작전동 428-2 (주)호텔카리스2024-01-022024-01-022024-03-07
806휴게음식점커피숍발도스커피계산역점인천광역시 계양구 경명대로 1085, 조흥프라자텔 1층 104호 (계산동)인천광역시 계양구 계산동 920-9 조흥프라자텔 104호2024-01-082024-01-082024-03-07
807휴게음식점일반조리판매넘버원 페스츄리 붕어인천광역시 계양구 계양대로 지하 73, 작전역 지하층 3호 (작전동)인천광역시 계양구 작전동 878 작전역 3호2024-01-082024-01-082024-03-07
808휴게음식점커피숍컴포즈커피인천성지초등학교점인천광역시 계양구 아나지로247번길 11, 모닝프라자 1층 108호 (효성동)인천광역시 계양구 효성동 200-4 모닝프라자2024-01-102024-01-102024-03-07
809휴게음식점기타 휴게음식점밥마리김밥인천광역시 계양구 효서로 287, 1층 일부호 (작전동)인천광역시 계양구 작전동 871-602024-01-112024-01-112024-03-07
810휴게음식점편의점세븐일레븐계산센터점인천광역시 계양구 경명대로1045번길 5, 1층 일부호 (계산동)인천광역시 계양구 계산동 931-382024-01-232024-01-232024-03-07
811휴게음식점편의점세븐일레븐동양제일점인천광역시 계양구 당미길 4, 1층 일부호 (동양동)인천광역시 계양구 동양동 6412024-01-252024-01-252024-03-07
812휴게음식점일반조리판매장손족발(계양점)인천광역시 계양구 장제로 822, 롯데마트 계양점 2층 일부호 (계산동)인천광역시 계양구 계산동 1059-1 롯데마트 계양점2024-02-012024-02-012024-03-07
813휴게음식점편의점세븐일레븐효성사랑점인천광역시 계양구 효서로145번길 7, 1층 일부호 (효성동)인천광역시 계양구 효성동 249-82024-02-132024-02-132024-03-07
814휴게음식점기타 휴게음식점쭈니네꽈배기인천광역시 계양구 임학안로 1, 1층 일부호 (임학동)인천광역시 계양구 임학동 63-662024-02-192024-02-192024-03-07

Duplicate rows

Most frequently occurring

업종명업태명업소명소재지(도로명)소재지(지번)영업자시작일인허가일자데이터기준일# duplicates
0휴게음식점기타 휴게음식점(주)이마트계양점인천광역시 계양구 봉오대로 785 (작전동,지하2층)인천광역시 계양구 작전동 911-1 지하2층2020-04-232002-04-302024-03-072