Overview

Dataset statistics

Number of variables7
Number of observations436
Missing cells190
Missing cells (%)6.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory24.0 KiB
Average record size in memory56.3 B

Variable types

Text4
DateTime2
Categorical1

Dataset

Description영동관내의 폐업 음식점의 2012년 1월부터 2020년 10월까지의 업소명, 주소, 업소전화, 허가신고일, 폐업일자, 업종 명칭이 제공됩니다.
Author충청북도 영동군
URLhttps://www.data.go.kr/data/15052844/fileData.do

Alerts

업종 is highly imbalanced (54.3%)Imbalance
소재지 도로명주소 has 56 (12.8%) missing valuesMissing
소재지 지번주소 has 6 (1.4%) missing valuesMissing
업소전화 has 128 (29.4%) missing valuesMissing

Reproduction

Analysis started2023-12-12 21:43:18.781328
Analysis finished2023-12-12 21:43:19.401462
Duration0.62 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

Distinct417
Distinct (%)95.6%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
2023-12-13T06:43:19.645181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length15
Mean length5.1536697
Min length2

Characters and Unicode

Total characters2247
Distinct characters412
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

Unique399 ?
Unique (%)91.5%

Sample

1st row철판동태찜
2nd row박달가든
3rd row다정식당
4th row워니앤미니
5th row용산철판동태찜
ValueCountFrequency (%)
영동 5
 
0.9%
카페 5
 
0.9%
칼국수 4
 
0.7%
영동점 4
 
0.7%
호수다방 3
 
0.6%
새막골 2
 
0.4%
신날개 2
 
0.4%
가마솥 2
 
0.4%
커피나무 2
 
0.4%
호프 2
 
0.4%
Other values (481) 503
94.2%
2023-12-13T06:43:20.080831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 106
 
4.7%
98
 
4.4%
당 95
 
4.2%
다 51
 
2.3%
방 41
 
1.8%
동 41
 
1.8%
영 31
 
1.4%
가 30
 
1.3%
이 28
 
1.2%
수 26
 
1.2%
Other values (402) 1700
75.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2037
90.7%
Space Separator 98
 
4.4%
Uppercase Letter 37
 
1.6%
Decimal Number 24
 
1.1%
Lowercase Letter 18
 
0.8%
Other Punctuation 13
 
0.6%
Open Punctuation 10
 
0.4%
Close Punctuation 10
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 106
 
5.2%
당 95
 
4.7%
다 51
 
2.5%
방 41
 
2.0%
동 41
 
2.0%
영 31
 
1.5%
가 30
 
1.5%
이 28
 
1.4%
수 26
 
1.3%
마 25
 
1.2%
Other values (365) 1563
76.7%
Uppercase Letter
ValueCountFrequency (%)
S 7
18.9%
B 4
10.8%
C 4
10.8%
O 4
10.8%
G 3
8.1%
W 2
 
5.4%
I 2
 
5.4%
D 2
 
5.4%
L 2
 
5.4%
R 1
 
2.7%
Other values (6) 6
16.2%
Decimal Number
ValueCountFrequency (%)
0 6
25.0%
2 5
20.8%
3 3
12.5%
5 3
12.5%
6 3
12.5%
7 2
 
8.3%
1 1
 
4.2%
9 1
 
4.2%
Other Punctuation
ValueCountFrequency (%)
. 6
46.2%
' 3
23.1%
& 2
 
15.4%
＆ 1
 
7.7%
? 1
 
7.7%
Lowercase Letter
ValueCountFrequency (%)
e 5
27.8%
a 4
22.2%
f 4
22.2%
s 3
16.7%
o 2
 
11.1%
Space Separator
ValueCountFrequency (%)
98
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2037
90.7%
Common 155
 
6.9%
Latin 55
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 106
 
5.2%
당 95
 
4.7%
다 51
 
2.5%
방 41
 
2.0%
동 41
 
2.0%
영 31
 
1.5%
가 30
 
1.5%
이 28
 
1.4%
수 26
 
1.3%
마 25
 
1.2%
Other values (365) 1563
76.7%
Latin
ValueCountFrequency (%)
S 7
12.7%
e 5
 
9.1%
B 4
 
7.3%
a 4
 
7.3%
C 4
 
7.3%
O 4
 
7.3%
f 4
 
7.3%
s 3
 
5.5%
G 3
 
5.5%
W 2
 
3.6%
Other values (11) 15
27.3%
Common
ValueCountFrequency (%)
98
63.2%
( 10
 
6.5%
) 10
 
6.5%
. 6
 
3.9%
0 6
 
3.9%
2 5
 
3.2%
3 3
 
1.9%
5 3
 
1.9%
6 3
 
1.9%
' 3
 
1.9%
Other values (6) 8
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2037
90.7%
ASCII 209
 
9.3%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 106
 
5.2%
당 95
 
4.7%
다 51
 
2.5%
방 41
 
2.0%
동 41
 
2.0%
영 31
 
1.5%
가 30
 
1.5%
이 28
 
1.4%
수 26
 
1.3%
마 25
 
1.2%
Other values (365) 1563
76.7%
ASCII
ValueCountFrequency (%)
98
46.9%
( 10
 
4.8%
) 10
 
4.8%
S 7
 
3.3%
. 6
 
2.9%
0 6
 
2.9%
2 5
 
2.4%
e 5
 
2.4%
B 4
 
1.9%
a 4
 
1.9%
Other values (26) 54
25.8%
None
ValueCountFrequency (%)
＆ 1
100.0%

소재지 도로명주소
Text

MISSING 

Distinct339
Distinct (%)89.2%
Missing56
Missing (%)12.8%
Memory size3.5 KiB
2023-12-13T06:43:20.294882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length38
Mean length22.036842
Min length18

Characters and Unicode

Total characters8374
Distinct characters155
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique306 ?
Unique (%)80.5%

Sample

1st row충청북도 영동군 용산면 빙벽장길?15
2nd row충청북도 영동군 영동읍 중앙로 49
3rd row충청북도 영동군 매곡면 괘방령로?577
4th row충청북도 영동군 영동읍 영동황간로?31
5th row충청북도 영동군 영동읍 영산로3길 8-1
ValueCountFrequency (%)
충청북도 380
19.9%
영동군 380
19.9%
영동읍 224
 
11.7%
황간면 43
 
2.3%
계산로 38
 
2.0%
용산면 28
 
1.5%
황간로 19
 
1.0%
민주지산로 19
 
1.0%
5 18
 
0.9%
추풍령면 18
 
0.9%
Other values (357) 743
38.9%
2023-12-13T06:43:20.623492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1606
19.2%
영 704
 
8.4%
동 685
 
8.2%
도 383
 
4.6%
군 381
 
4.5%
충 380
 
4.5%
청 380
 
4.5%
북 380
 
4.5%
로 310
 
3.7%
1 271
 
3.2%
Other values (145) 2894
34.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5434
64.9%
Space Separator 1606
 
19.2%
Decimal Number 1128
 
13.5%
Dash Punctuation 103
 
1.2%
Other Punctuation 63
 
0.8%
Open Punctuation 20
 
0.2%
Close Punctuation 20
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 704
13.0%
동 685
12.6%
도 383
 
7.0%
군 381
 
7.0%
충 380
 
7.0%
청 380
 
7.0%
북 380
 
7.0%
로 310
 
5.7%
읍 224
 
4.1%
산 224
 
4.1%
Other values (129) 1383
25.5%
Decimal Number
ValueCountFrequency (%)
1 271
24.0%
3 161
14.3%
2 149
13.2%
5 105
 
9.3%
4 99
 
8.8%
6 83
 
7.4%
9 78
 
6.9%
0 70
 
6.2%
7 58
 
5.1%
8 54
 
4.8%
Other Punctuation
ValueCountFrequency (%)
? 37
58.7%
, 26
41.3%
Space Separator
ValueCountFrequency (%)
1606
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 103
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5434
64.9%
Common 2940
35.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 704
13.0%
동 685
12.6%
도 383
 
7.0%
군 381
 
7.0%
충 380
 
7.0%
청 380
 
7.0%
북 380
 
7.0%
로 310
 
5.7%
읍 224
 
4.1%
산 224
 
4.1%
Other values (129) 1383
25.5%
Common
ValueCountFrequency (%)
1606
54.6%
1 271
 
9.2%
3 161
 
5.5%
2 149
 
5.1%
5 105
 
3.6%
- 103
 
3.5%
4 99
 
3.4%
6 83
 
2.8%
9 78
 
2.7%
0 70
 
2.4%
Other values (6) 215
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5434
64.9%
ASCII 2940
35.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1606
54.6%
1 271
 
9.2%
3 161
 
5.5%
2 149
 
5.1%
5 105
 
3.6%
- 103
 
3.5%
4 99
 
3.4%
6 83
 
2.8%
9 78
 
2.7%
0 70
 
2.4%
Other values (6) 215
 
7.3%
Hangul
ValueCountFrequency (%)
영 704
13.0%
동 685
12.6%
도 383
 
7.0%
군 381
 
7.0%
충 380
 
7.0%
청 380
 
7.0%
북 380
 
7.0%
로 310
 
5.7%
읍 224
 
4.1%
산 224
 
4.1%
Other values (129) 1383
25.5%

소재지 지번주소
Text

MISSING 

Distinct390
Distinct (%)90.7%
Missing6
Missing (%)1.4%
Memory size3.5 KiB
2023-12-13T06:43:20.920142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length38
Mean length24.716279
Min length20

Characters and Unicode

Total characters10628
Distinct characters142
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

Unique356 ?
Unique (%)82.8%

Sample

1st row충청북도 영동군 영동읍 계산리 261-1번지
2nd row충청북도 영동군 용산면 율리 694-6번지
3rd row충청북도 영동군 심천면 심천리 204번지
4th row충청북도 영동군 영동읍 계산리 698-1번지
5th row충청북도 영동군 용산면 구촌리 393-4번지
ValueCountFrequency (%)
충청북도 430
19.6%
영동군 430
19.6%
영동읍 246
 
11.2%
계산리 199
 
9.1%
황간면 49
 
2.2%
용산면 34
 
1.5%
남성리 28
 
1.3%
구촌리 27
 
1.2%
추풍령면 23
 
1.0%
추풍령리 20
 
0.9%
Other values (467) 710
32.3%
2023-12-13T06:43:21.309139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2192
20.6%
동 692
 
6.5%
영 683
 
6.4%
도 433
 
4.1%
군 431
 
4.1%
충 430
 
4.0%
북 430
 
4.0%
청 430
 
4.0%
리 429
 
4.0%
- 395
 
3.7%
Other values (132) 4083
38.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6201
58.3%
Space Separator 2192
 
20.6%
Decimal Number 1822
 
17.1%
Dash Punctuation 395
 
3.7%
Close Punctuation 6
 
0.1%
Open Punctuation 6
 
0.1%
Other Punctuation 3
 
< 0.1%
Uppercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 692
11.2%
영 683
11.0%
도 433
 
7.0%
군 431
 
7.0%
충 430
 
6.9%
북 430
 
6.9%
청 430
 
6.9%
리 429
 
6.9%
산 310
 
5.0%
읍 246
 
4.0%
Other values (114) 1687
27.2%
Decimal Number
ValueCountFrequency (%)
1 269
14.8%
6 254
13.9%
2 218
12.0%
5 205
11.3%
8 185
10.2%
3 182
10.0%
4 150
8.2%
9 138
7.6%
7 128
7.0%
0 93
 
5.1%
Uppercase Letter
ValueCountFrequency (%)
T 1
33.3%
P 1
33.3%
A 1
33.3%
Space Separator
ValueCountFrequency (%)
2192
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 395
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6201
58.3%
Common 4424
41.6%
Latin 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 692
11.2%
영 683
11.0%
도 433
 
7.0%
군 431
 
7.0%
충 430
 
6.9%
북 430
 
6.9%
청 430
 
6.9%
리 429
 
6.9%
산 310
 
5.0%
읍 246
 
4.0%
Other values (114) 1687
27.2%
Common
ValueCountFrequency (%)
2192
49.5%
- 395
 
8.9%
1 269
 
6.1%
6 254
 
5.7%
2 218
 
4.9%
5 205
 
4.6%
8 185
 
4.2%
3 182
 
4.1%
4 150
 
3.4%
9 138
 
3.1%
Other values (5) 236
 
5.3%
Latin
ValueCountFrequency (%)
T 1
33.3%
P 1
33.3%
A 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6201
58.3%
ASCII 4427
41.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2192
49.5%
- 395
 
8.9%
1 269
 
6.1%
6 254
 
5.7%
2 218
 
4.9%
5 205
 
4.6%
8 185
 
4.2%
3 182
 
4.1%
4 150
 
3.4%
9 138
 
3.1%
Other values (8) 239
 
5.4%
Hangul
ValueCountFrequency (%)
동 692
11.2%
영 683
11.0%
도 433
 
7.0%
군 431
 
7.0%
충 430
 
6.9%
북 430
 
6.9%
청 430
 
6.9%
리 429
 
6.9%
산 310
 
5.0%
읍 246
 
4.0%
Other values (114) 1687
27.2%

업소전화
Text

MISSING 

Distinct297
Distinct (%)96.4%
Missing128
Missing (%)29.4%
Memory size3.5 KiB
2023-12-13T06:43:21.565327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.00974
Min length12

Characters and Unicode

Total characters3699
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

Unique286 ?
Unique (%)92.9%

Sample

1st row043-742-9900
2nd row043-742-6103
3rd row043-744-7731
4th row043-743-2603
5th row043-742-2436
ValueCountFrequency (%)
043-742-2536 2
 
0.6%
043-742-9742 2
 
0.6%
043-743-1811 2
 
0.6%
043-745-0050 2
 
0.6%
043-744-1551 2
 
0.6%
043-743-0470 2
 
0.6%
043-744-9191 2
 
0.6%
043-744-2558 2
 
0.6%
043-742-1213 2
 
0.6%
043-745-5382 2
 
0.6%
Other values (287) 288
93.5%
2023-12-13T06:43:21.961721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 803
21.7%
- 616
16.7%
3 512
13.8%
0 469
12.7%
7 433
11.7%
2 229
 
6.2%
5 191
 
5.2%
1 133
 
3.6%
9 128
 
3.5%
8 98
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3083
83.3%
Dash Punctuation 616
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 803
26.0%
3 512
16.6%
0 469
15.2%
7 433
14.0%
2 229
 
7.4%
5 191
 
6.2%
1 133
 
4.3%
9 128
 
4.2%
8 98
 
3.2%
6 87
 
2.8%
Dash Punctuation
ValueCountFrequency (%)
- 616
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3699
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 803
21.7%
- 616
16.7%
3 512
13.8%
0 469
12.7%
7 433
11.7%
2 229
 
6.2%
5 191
 
5.2%
1 133
 
3.6%
9 128
 
3.5%
8 98
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3699
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 803
21.7%
- 616
16.7%
3 512
13.8%
0 469
12.7%
7 433
11.7%
2 229
 
6.2%
5 191
 
5.2%
1 133
 
3.6%
9 128
 
3.5%
8 98
 
2.6%

허가신고일
Date

Distinct418
Distinct (%)95.9%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
Minimum1967-10-16 00:00:00
Maximum2020-11-10 00:00:00
2023-12-13T06:43:22.111436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:43:22.296651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

폐업일자
Date

Distinct364
Distinct (%)83.5%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
Minimum2012-01-11 00:00:00
Maximum2021-10-21 00:00:00
2023-12-13T06:43:22.471291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:43:22.598020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업종
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
일반음식점
357 
휴게음식점
76 
제과점영업
 
3

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 357
81.9%
휴게음식점 76
 
17.4%
제과점영업 3
 
0.7%

Length

2023-12-13T06:43:22.722144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:43:22.828170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반음식점 357
81.9%
휴게음식점 76
 
17.4%
제과점영업 3
 
0.7%

Missing values

2023-12-13T06:43:19.167925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:43:19.266103image/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.
2023-12-13T06:43:19.355329image/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

업소명소재지 도로명주소소재지 지번주소업소전화허가신고일폐업일자업종
0철판동태찜<NA>충청북도 영동군 영동읍 계산리 261-1번지<NA>2009-08-132012-01-11일반음식점
1박달가든충청북도 영동군 용산면 빙벽장길?15충청북도 영동군 용산면 율리 694-6번지043-742-99001995-09-262012-01-19일반음식점
2다정식당<NA>충청북도 영동군 심천면 심천리 204번지043-742-61031973-11-222012-01-25일반음식점
3워니앤미니충청북도 영동군 영동읍 중앙로 49충청북도 영동군 영동읍 계산리 698-1번지043-744-77312000-01-192012-01-27일반음식점
4용산철판동태찜<NA>충청북도 영동군 용산면 구촌리 393-4번지<NA>2011-01-102012-01-30일반음식점
5천덕식당충청북도 영동군 매곡면 괘방령로?577충청북도 영동군 매곡면 어촌리 509-24번지043-743-26031996-11-302012-01-30일반음식점
6마진식당충청북도 영동군 영동읍 영동황간로?31충청북도 영동군 영동읍 매천리 405-3번지043-742-24361995-09-042012-01-31일반음식점
7흑돼지 마을충청북도 영동군 영동읍 영산로3길 8-1충청북도 영동군 영동읍 계산리 554-9번지043-745-73662010-10-202012-02-07일반음식점
8아구랑갈비마을충청북도 영동군 심천면 양산심천로 1183충청북도 영동군 심천면 고당리 564-3번지043-742-01871995-07-082012-02-13일반음식점
9용산반점<NA>충청북도 영동군 용산면 구촌리 148-4번지043-742-70712004-03-302012-02-20일반음식점
업소명소재지 도로명주소소재지 지번주소업소전화허가신고일폐업일자업종
426황리단길충청북도 영동군 황간면 영동황간로 1690충청북도 영동군 황간면 마산리 20-12<NA>2019-04-252020-09-07휴게음식점
427투썸플레이스 영동군청점충청북도 영동군 영동읍 동정로 30 (골든렉시움 오피스텔)충청북도 영동군 영동읍 동정리 97<NA>2020-04-032020-09-08휴게음식점
428오늘도 맛카롱충청북도 영동군 영동읍 계산로5길 2충청북도 영동군 영동읍 계산리 662-7<NA>2019-08-062020-11-23휴게음식점
429까페 남성대충청북도 영동군 양강면 양정죽촌로 70충청북도 영동군 양강면 양정리 595042-581-47322018-01-052021-01-06휴게음식점
430봉구스밥버거충청북도 영동군 영동읍 계산로 18충청북도 영동군 영동읍 계산리 682-7043-744-07082013-11-082021-04-02휴게음식점
431카페 아프리카충청북도 영동군 영동읍 눈어치중2길 17-1충청북도 영동군 영동읍 설계리 697-2<NA>2012-11-262021-06-03휴게음식점
432수련다방충청북도 영동군 황간면 황간로 39-5충청북도 영동군 황간면 남성리 583-2043-744-28971997-07-242021-06-15휴게음식점
433태양다방충청북도 영동군 영동읍 중앙로1길 5충청북도 영동군 영동읍 계산리 688-15043-742-92332020-02-192021-08-02휴게음식점
434베러댄와플 영동점충청북도 영동군 영동읍 계산로 108충청북도 영동군 영동읍 계산리 81-20043-744-75442017-01-172021-09-13휴게음식점
435다온충청북도 영동군 영동읍 학산영동로 1173, 은파피아노충청북도 영동군 영동읍 부용리 87-8 은파피아노<NA>2020-09-242021-10-05휴게음식점