Overview

Dataset statistics

Number of variables7
Number of observations2435
Missing cells3
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory133.3 KiB
Average record size in memory56.1 B

Variable types

Text3
Categorical2
DateTime2

Dataset

Description대전광역시 대덕구 일반음식점현황에 관한 데이터로 (업소명, 업종명, 업태명 소재지, 인허가일자)의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/3070166/fileData.do

Alerts

업종명 has constant value ""Constant
데이터기준일 has constant value ""Constant

Reproduction

Analysis started2023-12-12 19:53:51.645399
Analysis finished2023-12-12 19:53:52.652722
Duration1.01 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

Distinct2354
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size19.2 KiB
2023-12-13T04:53:52.878242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length19
Mean length5.8587269
Min length1

Characters and Unicode

Total characters14266
Distinct characters741
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2286 ?
Unique (%)93.9%

Sample

1st row영화반점
2nd row대덕식당
3rd row홍성식당
4th row우리식당
5th row등나무집
ValueCountFrequency (%)
김밥나라식당 6
 
0.2%
신탄진점 5
 
0.2%
전주식당 3
 
0.1%
법동점 3
 
0.1%
송촌점 3
 
0.1%
우리식당 3
 
0.1%
황금식당 3
 
0.1%
까투리식당 3
 
0.1%
김밥천국 3
 
0.1%
허갈닭강정 3
 
0.1%
Other values (2386) 2462
98.6%
2023-12-13T04:53:53.351885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 648
 
4.5%
당 608
 
4.3%
점 333
 
2.3%
이 303
 
2.1%
대 262
 
1.8%
리 245
 
1.7%
치 181
 
1.3%
가 170
 
1.2%
마 165
 
1.2%
비 156
 
1.1%
Other values (731) 11195
78.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13943
97.7%
Decimal Number 161
 
1.1%
Space Separator 62
 
0.4%
Uppercase Letter 31
 
0.2%
Lowercase Letter 21
 
0.1%
Open Punctuation 20
 
0.1%
Close Punctuation 20
 
0.1%
Other Punctuation 8
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 648
 
4.6%
당 608
 
4.4%
점 333
 
2.4%
이 303
 
2.2%
대 262
 
1.9%
리 245
 
1.8%
치 181
 
1.3%
가 170
 
1.2%
마 165
 
1.2%
비 156
 
1.1%
Other values (685) 10872
78.0%
Uppercase Letter
ValueCountFrequency (%)
A 5
16.1%
B 4
12.9%
O 3
 
9.7%
X 2
 
6.5%
G 2
 
6.5%
T 2
 
6.5%
C 2
 
6.5%
J 1
 
3.2%
Y 1
 
3.2%
M 1
 
3.2%
Other values (8) 8
25.8%
Lowercase Letter
ValueCountFrequency (%)
e 3
14.3%
a 3
14.3%
m 2
9.5%
i 2
9.5%
t 2
9.5%
h 2
9.5%
o 2
9.5%
b 1
 
4.8%
p 1
 
4.8%
n 1
 
4.8%
Other values (2) 2
9.5%
Decimal Number
ValueCountFrequency (%)
1 33
20.5%
0 30
18.6%
2 21
13.0%
5 19
11.8%
9 17
10.6%
8 15
9.3%
7 10
 
6.2%
3 8
 
5.0%
4 4
 
2.5%
6 4
 
2.5%
Other Punctuation
ValueCountFrequency (%)
. 4
50.0%
& 3
37.5%
, 1
 
12.5%
Space Separator
ValueCountFrequency (%)
62
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13943
97.7%
Common 271
 
1.9%
Latin 52
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 648
 
4.6%
당 608
 
4.4%
점 333
 
2.4%
이 303
 
2.2%
대 262
 
1.9%
리 245
 
1.8%
치 181
 
1.3%
가 170
 
1.2%
마 165
 
1.2%
비 156
 
1.1%
Other values (685) 10872
78.0%
Latin
ValueCountFrequency (%)
A 5
 
9.6%
B 4
 
7.7%
O 3
 
5.8%
e 3
 
5.8%
a 3
 
5.8%
m 2
 
3.8%
i 2
 
3.8%
t 2
 
3.8%
h 2
 
3.8%
o 2
 
3.8%
Other values (20) 24
46.2%
Common
ValueCountFrequency (%)
62
22.9%
1 33
12.2%
0 30
11.1%
2 21
 
7.7%
( 20
 
7.4%
) 20
 
7.4%
5 19
 
7.0%
9 17
 
6.3%
8 15
 
5.5%
7 10
 
3.7%
Other values (6) 24
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13942
97.7%
ASCII 323
 
2.3%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 648
 
4.6%
당 608
 
4.4%
점 333
 
2.4%
이 303
 
2.2%
대 262
 
1.9%
리 245
 
1.8%
치 181
 
1.3%
가 170
 
1.2%
마 165
 
1.2%
비 156
 
1.1%
Other values (684) 10871
78.0%
ASCII
ValueCountFrequency (%)
62
19.2%
1 33
10.2%
0 30
 
9.3%
2 21
 
6.5%
( 20
 
6.2%
) 20
 
6.2%
5 19
 
5.9%
9 17
 
5.3%
8 15
 
4.6%
7 10
 
3.1%
Other values (36) 76
23.5%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size19.2 KiB
일반음식점
2435 

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 2435
100.0%

Length

2023-12-13T04:53:53.520945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:53:53.643834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반음식점 2435
100.0%

업태명
Categorical

Distinct22
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size19.2 KiB
한식
1410 
호프/통닭
258 
기타
185 
분식
153 
통닭(치킨)
 
77
Other values (17)
352 

Length

Max length15
Median length2
Mean length2.8180698
Min length2

Unique

Unique3 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
한식 1410
57.9%
호프/통닭 258
 
10.6%
기타 185
 
7.6%
분식 153
 
6.3%
통닭(치킨) 77
 
3.2%
중국식 65
 
2.7%
식육(숯불구이) 57
 
2.3%
경양식 50
 
2.1%
까페 42
 
1.7%
횟집 34
 
1.4%
Other values (12) 104
 
4.3%

Length

2023-12-13T04:53:53.893414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 1410
57.9%
호프/통닭 258
 
10.6%
기타 185
 
7.6%
분식 153
 
6.3%
통닭(치킨 77
 
3.2%
중국식 65
 
2.7%
식육(숯불구이 57
 
2.3%
경양식 50
 
2.1%
까페 42
 
1.7%
횟집 34
 
1.4%
Other values (12) 104
 
4.3%

소재지(도로명)
Text

Distinct2235
Distinct (%)91.9%
Missing3
Missing (%)0.1%
Memory size19.2 KiB
2023-12-13T04:53:54.323065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length51
Mean length29.850329
Min length21

Characters and Unicode

Total characters72596
Distinct characters212
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

Unique2058 ?
Unique (%)84.6%

Sample

1st row대전광역시 대덕구 신탄진동로23번길 46 (신탄진동,(1층))
2nd row대전광역시 대덕구 신탄진로738번길 1 (신탄진동)
3rd row대전광역시 대덕구 신탄진로839번길 10, 1층 (신탄진동)
4th row대전광역시 대덕구 대화15길 118, 1층 (대화동)
5th row대전광역시 대덕구 대화로 53 (대화동)
ValueCountFrequency (%)
대전광역시 2432
 
17.3%
대덕구 2432
 
17.3%
1층 1334
 
9.5%
중리동 449
 
3.2%
송촌동 353
 
2.5%
오정동 267
 
1.9%
신탄진동 239
 
1.7%
석봉동 181
 
1.3%
비래동 166
 
1.2%
법동 112
 
0.8%
Other values (1218) 6105
43.4%
2023-12-13T04:53:54.954085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11638
 
16.0%
대 5622
 
7.7%
1 3833
 
5.3%
동 2909
 
4.0%
덕 2844
 
3.9%
) 2540
 
3.5%
( 2540
 
3.5%
전 2506
 
3.5%
시 2438
 
3.4%
구 2433
 
3.4%
Other values (202) 33293
45.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 42020
57.9%
Space Separator 11638
 
16.0%
Decimal Number 11578
 
15.9%
Close Punctuation 2540
 
3.5%
Open Punctuation 2540
 
3.5%
Other Punctuation 1946
 
2.7%
Dash Punctuation 296
 
0.4%
Uppercase Letter 36
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 5622
 
13.4%
동 2909
 
6.9%
덕 2844
 
6.8%
전 2506
 
6.0%
시 2438
 
5.8%
구 2433
 
5.8%
역 2432
 
5.8%
광 2432
 
5.8%
로 2377
 
5.7%
층 1632
 
3.9%
Other values (176) 14395
34.3%
Decimal Number
ValueCountFrequency (%)
1 3833
33.1%
2 1349
 
11.7%
3 1060
 
9.2%
4 960
 
8.3%
5 884
 
7.6%
7 818
 
7.1%
0 785
 
6.8%
6 722
 
6.2%
8 695
 
6.0%
9 472
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
B 20
55.6%
A 8
 
22.2%
C 3
 
8.3%
S 2
 
5.6%
F 1
 
2.8%
Q 1
 
2.8%
E 1
 
2.8%
Other Punctuation
ValueCountFrequency (%)
, 1944
99.9%
/ 1
 
0.1%
. 1
 
0.1%
Lowercase Letter
ValueCountFrequency (%)
e 1
50.0%
s 1
50.0%
Space Separator
ValueCountFrequency (%)
11638
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2540
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2540
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 296
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 42020
57.9%
Common 30538
42.1%
Latin 38
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 5622
 
13.4%
동 2909
 
6.9%
덕 2844
 
6.8%
전 2506
 
6.0%
시 2438
 
5.8%
구 2433
 
5.8%
역 2432
 
5.8%
광 2432
 
5.8%
로 2377
 
5.7%
층 1632
 
3.9%
Other values (176) 14395
34.3%
Common
ValueCountFrequency (%)
11638
38.1%
1 3833
 
12.6%
) 2540
 
8.3%
( 2540
 
8.3%
, 1944
 
6.4%
2 1349
 
4.4%
3 1060
 
3.5%
4 960
 
3.1%
5 884
 
2.9%
7 818
 
2.7%
Other values (7) 2972
 
9.7%
Latin
ValueCountFrequency (%)
B 20
52.6%
A 8
 
21.1%
C 3
 
7.9%
S 2
 
5.3%
e 1
 
2.6%
F 1
 
2.6%
Q 1
 
2.6%
E 1
 
2.6%
s 1
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 42020
57.9%
ASCII 30576
42.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11638
38.1%
1 3833
 
12.5%
) 2540
 
8.3%
( 2540
 
8.3%
, 1944
 
6.4%
2 1349
 
4.4%
3 1060
 
3.5%
4 960
 
3.1%
5 884
 
2.9%
7 818
 
2.7%
Other values (16) 3010
 
9.8%
Hangul
ValueCountFrequency (%)
대 5622
 
13.4%
동 2909
 
6.9%
덕 2844
 
6.8%
전 2506
 
6.0%
시 2438
 
5.8%
구 2433
 
5.8%
역 2432
 
5.8%
광 2432
 
5.8%
로 2377
 
5.7%
층 1632
 
3.9%
Other values (176) 14395
34.3%

소재지(지번)
Text

Distinct2276
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Memory size19.2 KiB
2023-12-13T04:53:55.440233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length43
Mean length23.397536
Min length17

Characters and Unicode

Total characters56973
Distinct characters191
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

Unique2134 ?
Unique (%)87.6%

Sample

1st row대전광역시 대덕구 신탄진동 139-17 (1층)
2nd row대전광역시 대덕구 신탄진동 295-14
3rd row대전광역시 대덕구 신탄진동 114-14 1층
4th row대전광역시 대덕구 대화동 35-883
5th row대전광역시 대덕구 대화동 40-67
ValueCountFrequency (%)
대전광역시 2435
21.5%
대덕구 2435
21.5%
1층 998
 
8.8%
중리동 482
 
4.3%
송촌동 375
 
3.3%
오정동 293
 
2.6%
신탄진동 261
 
2.3%
석봉동 188
 
1.7%
비래동 182
 
1.6%
법동 130
 
1.1%
Other values (2057) 3552
31.3%
2023-12-13T04:53:56.153925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11272
19.8%
대 4991
 
8.8%
1 3643
 
6.4%
덕 2540
 
4.5%
동 2538
 
4.5%
전 2443
 
4.3%
시 2440
 
4.3%
구 2436
 
4.3%
광 2435
 
4.3%
역 2435
 
4.3%
Other values (181) 19800
34.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 29446
51.7%
Decimal Number 12277
21.5%
Space Separator 11272
 
19.8%
Dash Punctuation 2368
 
4.2%
Close Punctuation 734
 
1.3%
Open Punctuation 734
 
1.3%
Other Punctuation 113
 
0.2%
Uppercase Letter 28
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 4991
16.9%
덕 2540
8.6%
동 2538
8.6%
전 2443
8.3%
시 2440
8.3%
구 2436
8.3%
광 2435
8.3%
역 2435
8.3%
층 1192
 
4.0%
리 487
 
1.7%
Other values (158) 5509
18.7%
Decimal Number
ValueCountFrequency (%)
1 3643
29.7%
2 1552
12.6%
4 1330
 
10.8%
3 1180
 
9.6%
5 921
 
7.5%
6 852
 
6.9%
7 754
 
6.1%
0 733
 
6.0%
9 662
 
5.4%
8 650
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
B 16
57.1%
A 6
 
21.4%
C 3
 
10.7%
S 2
 
7.1%
Q 1
 
3.6%
Other Punctuation
ValueCountFrequency (%)
, 110
97.3%
/ 2
 
1.8%
! 1
 
0.9%
Space Separator
ValueCountFrequency (%)
11272
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2368
100.0%
Close Punctuation
ValueCountFrequency (%)
) 734
100.0%
Open Punctuation
ValueCountFrequency (%)
( 734
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 29446
51.7%
Common 27498
48.3%
Latin 29
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 4991
16.9%
덕 2540
8.6%
동 2538
8.6%
전 2443
8.3%
시 2440
8.3%
구 2436
8.3%
광 2435
8.3%
역 2435
8.3%
층 1192
 
4.0%
리 487
 
1.7%
Other values (158) 5509
18.7%
Common
ValueCountFrequency (%)
11272
41.0%
1 3643
 
13.2%
- 2368
 
8.6%
2 1552
 
5.6%
4 1330
 
4.8%
3 1180
 
4.3%
5 921
 
3.3%
6 852
 
3.1%
7 754
 
2.7%
) 734
 
2.7%
Other values (7) 2892
 
10.5%
Latin
ValueCountFrequency (%)
B 16
55.2%
A 6
 
20.7%
C 3
 
10.3%
S 2
 
6.9%
Q 1
 
3.4%
e 1
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 29446
51.7%
ASCII 27527
48.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11272
40.9%
1 3643
 
13.2%
- 2368
 
8.6%
2 1552
 
5.6%
4 1330
 
4.8%
3 1180
 
4.3%
5 921
 
3.3%
6 852
 
3.1%
7 754
 
2.7%
) 734
 
2.7%
Other values (13) 2921
 
10.6%
Hangul
ValueCountFrequency (%)
대 4991
16.9%
덕 2540
8.6%
동 2538
8.6%
전 2443
8.3%
시 2440
8.3%
구 2436
8.3%
광 2435
8.3%
역 2435
8.3%
층 1192
 
4.0%
리 487
 
1.7%
Other values (158) 5509
18.7%

인허가일자
Date

Distinct1953
Distinct (%)80.2%
Missing0
Missing (%)0.0%
Memory size19.2 KiB
Minimum1969-07-15 00:00:00
Maximum2022-03-04 00:00:00
2023-12-13T04:53:56.342378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:53:56.508930image/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 size19.2 KiB
Minimum2023-05-22 00:00:00
Maximum2023-05-22 00:00:00
2023-12-13T04:53:56.666880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:53:56.811114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Missing values

2023-12-13T04:53:52.454787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T04:53:52.600363image/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

업소명업종명업태명소재지(도로명)소재지(지번)인허가일자데이터기준일
0영화반점일반음식점중국식대전광역시 대덕구 신탄진동로23번길 46 (신탄진동,(1층))대전광역시 대덕구 신탄진동 139-17 (1층)1971-03-292023-05-22
1대덕식당일반음식점한식대전광역시 대덕구 신탄진로738번길 1 (신탄진동)대전광역시 대덕구 신탄진동 295-141976-11-152023-05-22
2홍성식당일반음식점한식대전광역시 대덕구 신탄진로839번길 10, 1층 (신탄진동)대전광역시 대덕구 신탄진동 114-14 1층1977-01-312023-05-22
3우리식당일반음식점한식대전광역시 대덕구 대화15길 118, 1층 (대화동)대전광역시 대덕구 대화동 35-8831977-06-212023-05-22
4등나무집일반음식점한식대전광역시 대덕구 대화로 53 (대화동)대전광역시 대덕구 대화동 40-671978-11-242023-05-22
5계룡식당일반음식점한식대전광역시 대덕구 대전로 1371, 1층 (읍내동)대전광역시 대덕구 읍내동 244-251979-01-242023-05-22
6정다운보리밥일반음식점한식대전광역시 대덕구 신탄진동로7번길 74, 1층 (신탄진동)대전광역시 대덕구 신탄진동 121-25 (1층)1979-05-152023-05-22
7신천지식당일반음식점한식대전광역시 대덕구 대청로 508-8 (미호동)대전광역시 대덕구 미호동 270-51982-06-022023-05-22
8고관가든일반음식점한식대전광역시 대덕구 대청로 508 (미호동)대전광역시 대덕구 미호동 270-71982-06-192023-05-22
9대마성일반음식점한식대전광역시 대덕구 대화로 119 (대화동)대전광역시 대덕구 대화동 316-31982-07-012023-05-22
업소명업종명업태명소재지(도로명)소재지(지번)인허가일자데이터기준일
2425동근이 숯불 두마리치킨일반음식점호프/통닭대전광역시 대덕구 중리북로 9, 1층 (중리동)대전광역시 대덕구 중리동 131-62022-01-112023-05-22
2426호랑이초밥일반음식점일식대전광역시 대덕구 송촌북로36번길 17, 1층 102호 (송촌동)대전광역시 대덕구 송촌동 449-5 ,1층 102호2022-01-172023-05-22
2427엄마김밥사랑일반음식점분식대전광역시 대덕구 대청로 55, 1층 (신탄진동)대전광역시 대덕구 신탄진동 91-5 ,1층2022-01-252023-05-22
2428병팔이치킨포차일반음식점호프/통닭대전광역시 대덕구 덕암북로10번길 44, 1층 (덕암동)대전광역시 대덕구 덕암동 5-7 ,1층2022-02-142023-05-22
2429함돈스일반음식점경양식대전광역시 대덕구 대덕대로1458번길 3, 2층 (목상동)대전광역시 대덕구 목상동 148-1 ,2층2022-02-172023-05-22
2430오빠곱창송강신탄점일반음식점한식대전광역시 대덕구 대덕대로1448번길 53, 1층 (목상동)대전광역시 대덕구 목상동 145-11 ,1층2022-02-172023-05-22
2431아싸대패삼겹살일반음식점한식대전광역시 대덕구 대덕대로1448번길 17, 1층 (목상동)대전광역시 대덕구 목상동 146-12 ,1층2022-02-182023-05-22
2432시골옛날시장장터통닭일반음식점호프/통닭대전광역시 대덕구 대덕대로1486번길 53, 1층 (목상동)대전광역시 대덕구 목상동 201 ,1층2022-03-022023-05-22
2433호돈일반음식점식육(숯불구이)대전광역시 대덕구 대청로 54, 1층 (신탄진동)대전광역시 대덕구 신탄진동 126-212022-03-022023-05-22
2434모모김밥일반음식점분식대전광역시 대덕구 신탄진로 803, 1층 (신탄진동)대전광역시 대덕구 신탄진동 147-22022-03-042023-05-22