Overview

Dataset statistics

Number of variables7
Number of observations127
Missing cells144
Missing cells (%)16.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.3 KiB
Average record size in memory59.0 B

Variable types

Text3
DateTime2
Numeric2

Dataset

Description경상북도 예천군에 서 영업하고 있는 카페 및 식음료 업체들의 업소명, 인허가일자, 도로명줏, 지번 주소에 관련한 데이터
Author경상북도 예천군
URLhttps://www.data.go.kr/data/15127441/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
위도 is highly overall correlated with 경도High correlation
경도 is highly overall correlated with 위도High correlation
업소지번주소 has 48 (37.8%) missing valuesMissing
위도 has 48 (37.8%) missing valuesMissing
경도 has 48 (37.8%) missing valuesMissing

Reproduction

Analysis started2024-04-06 08:25:32.772921
Analysis finished2024-04-06 08:25:35.099035
Duration2.33 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

Distinct124
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-04-06T17:25:35.523474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length19
Mean length7.2677165
Min length2

Characters and Unicode

Total characters923
Distinct characters241
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

Unique122 ?
Unique (%)96.1%

Sample

1st row우정다방
2nd row유진다방
3rd row백년다방
4th row송정다방
5th row복지다방
ValueCountFrequency (%)
경북도청점 7
 
3.8%
카페 6
 
3.3%
coffee 4
 
2.2%
정다방 3
 
1.6%
커피 3
 
1.6%
예천점 3
 
1.6%
솔다방 2
 
1.1%
메가엠지씨커피 2
 
1.1%
봄봄 2
 
1.1%
cafe 2
 
1.1%
Other values (148) 148
81.3%
2024-04-06T17:25:36.297453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
55
 
6.0%
다 51
 
5.5%
방 43
 
4.7%
커 27
 
2.9%
피 26
 
2.8%
점 25
 
2.7%
도 21
 
2.3%
경 20
 
2.2%
북 20
 
2.2%
카 18
 
2.0%
Other values (231) 617
66.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 710
76.9%
Uppercase Letter 76
 
8.2%
Space Separator 55
 
6.0%
Lowercase Letter 44
 
4.8%
Close Punctuation 15
 
1.6%
Open Punctuation 15
 
1.6%
Decimal Number 7
 
0.8%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
다 51
 
7.2%
방 43
 
6.1%
커 27
 
3.8%
피 26
 
3.7%
점 25
 
3.5%
도 21
 
3.0%
경 20
 
2.8%
북 20
 
2.8%
카 18
 
2.5%
청 17
 
2.4%
Other values (190) 442
62.3%
Uppercase Letter
ValueCountFrequency (%)
E 12
15.8%
F 7
 
9.2%
A 7
 
9.2%
C 6
 
7.9%
O 5
 
6.6%
G 4
 
5.3%
T 4
 
5.3%
B 4
 
5.3%
W 3
 
3.9%
I 3
 
3.9%
Other values (11) 21
27.6%
Lowercase Letter
ValueCountFrequency (%)
e 10
22.7%
c 6
13.6%
f 6
13.6%
s 3
 
6.8%
o 3
 
6.8%
n 3
 
6.8%
k 3
 
6.8%
a 3
 
6.8%
i 3
 
6.8%
d 2
 
4.5%
Other values (2) 2
 
4.5%
Decimal Number
ValueCountFrequency (%)
8 2
28.6%
2 2
28.6%
1 2
28.6%
6 1
14.3%
Space Separator
ValueCountFrequency (%)
55
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 710
76.9%
Latin 120
 
13.0%
Common 93
 
10.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
다 51
 
7.2%
방 43
 
6.1%
커 27
 
3.8%
피 26
 
3.7%
점 25
 
3.5%
도 21
 
3.0%
경 20
 
2.8%
북 20
 
2.8%
카 18
 
2.5%
청 17
 
2.4%
Other values (190) 442
62.3%
Latin
ValueCountFrequency (%)
E 12
 
10.0%
e 10
 
8.3%
F 7
 
5.8%
A 7
 
5.8%
C 6
 
5.0%
c 6
 
5.0%
f 6
 
5.0%
O 5
 
4.2%
G 4
 
3.3%
T 4
 
3.3%
Other values (23) 53
44.2%
Common
ValueCountFrequency (%)
55
59.1%
) 15
 
16.1%
( 15
 
16.1%
8 2
 
2.2%
2 2
 
2.2%
1 2
 
2.2%
& 1
 
1.1%
6 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 710
76.9%
ASCII 213
 
23.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
55
25.8%
) 15
 
7.0%
( 15
 
7.0%
E 12
 
5.6%
e 10
 
4.7%
F 7
 
3.3%
A 7
 
3.3%
C 6
 
2.8%
c 6
 
2.8%
f 6
 
2.8%
Other values (31) 74
34.7%
Hangul
ValueCountFrequency (%)
다 51
 
7.2%
방 43
 
6.1%
커 27
 
3.8%
피 26
 
3.7%
점 25
 
3.5%
도 21
 
3.0%
경 20
 
2.8%
북 20
 
2.8%
카 18
 
2.5%
청 17
 
2.4%
Other values (190) 442
62.3%

인허가일자
Date

Distinct121
Distinct (%)95.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum1979-08-04 00:00:00
Maximum2024-02-23 00:00:00
2024-04-06T17:25:36.634004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:36.896796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업소도로명주소
Text

Distinct124
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-04-06T17:25:37.512516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length47
Mean length25
Min length19

Characters and Unicode

Total characters3175
Distinct characters153
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

Unique121 ?
Unique (%)95.3%

Sample

1st row경상북도 예천군 풍양면 낙상2길 8
2nd row경상북도 예천군 풍양면 낙상2길 45
3rd row경상북도 예천군 예천읍 효자로 97
4th row경상북도 예천군 감천면 충효로 1400
5th row경상북도 예천군 지보면 지보로 177
ValueCountFrequency (%)
예천군 128
17.7%
경상북도 127
17.5%
호명읍 46
 
6.4%
예천읍 32
 
4.4%
새움3로 20
 
2.8%
풍양면 17
 
2.3%
낙상2길 11
 
1.5%
용궁면 9
 
1.2%
효자로 9
 
1.2%
지보면 9
 
1.2%
Other values (205) 316
43.6%
2024-04-06T17:25:38.491606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
599
18.9%
천 166
 
5.2%
예 161
 
5.1%
상 152
 
4.8%
도 139
 
4.4%
경 133
 
4.2%
1 132
 
4.2%
북 132
 
4.2%
군 130
 
4.1%
호 83
 
2.6%
Other values (143) 1348
42.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1959
61.7%
Space Separator 599
 
18.9%
Decimal Number 506
 
15.9%
Other Punctuation 47
 
1.5%
Dash Punctuation 33
 
1.0%
Uppercase Letter 14
 
0.4%
Close Punctuation 8
 
0.3%
Open Punctuation 8
 
0.3%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 166
 
8.5%
예 161
 
8.2%
상 152
 
7.8%
도 139
 
7.1%
경 133
 
6.8%
북 132
 
6.7%
군 130
 
6.6%
호 83
 
4.2%
읍 78
 
4.0%
로 77
 
3.9%
Other values (120) 708
36.1%
Decimal Number
ValueCountFrequency (%)
1 132
26.1%
2 74
14.6%
3 66
13.0%
0 58
11.5%
4 37
 
7.3%
7 33
 
6.5%
6 31
 
6.1%
9 27
 
5.3%
8 25
 
4.9%
5 23
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
M 4
28.6%
J 4
28.6%
W 3
21.4%
N 1
 
7.1%
K 1
 
7.1%
H 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
, 46
97.9%
. 1
 
2.1%
Space Separator
ValueCountFrequency (%)
599
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 33
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1959
61.7%
Common 1201
37.8%
Latin 15
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 166
 
8.5%
예 161
 
8.2%
상 152
 
7.8%
도 139
 
7.1%
경 133
 
6.8%
북 132
 
6.7%
군 130
 
6.6%
호 83
 
4.2%
읍 78
 
4.0%
로 77
 
3.9%
Other values (120) 708
36.1%
Common
ValueCountFrequency (%)
599
49.9%
1 132
 
11.0%
2 74
 
6.2%
3 66
 
5.5%
0 58
 
4.8%
, 46
 
3.8%
4 37
 
3.1%
- 33
 
2.7%
7 33
 
2.7%
6 31
 
2.6%
Other values (6) 92
 
7.7%
Latin
ValueCountFrequency (%)
M 4
26.7%
J 4
26.7%
W 3
20.0%
N 1
 
6.7%
o 1
 
6.7%
K 1
 
6.7%
H 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1959
61.7%
ASCII 1216
38.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
599
49.3%
1 132
 
10.9%
2 74
 
6.1%
3 66
 
5.4%
0 58
 
4.8%
, 46
 
3.8%
4 37
 
3.0%
- 33
 
2.7%
7 33
 
2.7%
6 31
 
2.5%
Other values (13) 107
 
8.8%
Hangul
ValueCountFrequency (%)
천 166
 
8.5%
예 161
 
8.2%
상 152
 
7.8%
도 139
 
7.1%
경 133
 
6.8%
북 132
 
6.7%
군 130
 
6.6%
호 83
 
4.2%
읍 78
 
4.0%
로 77
 
3.9%
Other values (120) 708
36.1%

업소지번주소
Text

MISSING 

Distinct76
Distinct (%)96.2%
Missing48
Missing (%)37.8%
Memory size1.1 KiB
2024-04-06T17:25:39.115521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length23
Mean length21.620253
Min length19

Characters and Unicode

Total characters1708
Distinct characters58
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

Unique73 ?
Unique (%)92.4%

Sample

1st row경상북도 예천군 풍양면 낙상리 71
2nd row경상북도 예천군 풍양면 낙상리 163-14
3rd row경상북도 예천군 예천읍 노하리 73-51
4th row경상북도 예천군 감천면 포리 385-18
5th row경상북도 예천군 지보면 마전리 174-1
ValueCountFrequency (%)
경상북도 79
20.0%
예천군 79
20.0%
예천읍 31
 
7.8%
풍양면 17
 
4.3%
낙상리 15
 
3.8%
지보면 9
 
2.3%
남본리 9
 
2.3%
용궁면 9
 
2.3%
읍부리 8
 
2.0%
노하리 8
 
2.0%
Other values (96) 131
33.2%
2024-04-06T17:25:39.965309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
316
18.5%
천 117
 
6.9%
예 110
 
6.4%
상 99
 
5.8%
경 79
 
4.6%
북 79
 
4.6%
도 79
 
4.6%
군 79
 
4.6%
리 79
 
4.6%
1 62
 
3.6%
Other values (48) 609
35.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1028
60.2%
Space Separator 316
 
18.5%
Decimal Number 303
 
17.7%
Dash Punctuation 61
 
3.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 117
11.4%
예 110
10.7%
상 99
9.6%
경 79
 
7.7%
북 79
 
7.7%
도 79
 
7.7%
군 79
 
7.7%
리 79
 
7.7%
면 48
 
4.7%
읍 39
 
3.8%
Other values (36) 220
21.4%
Decimal Number
ValueCountFrequency (%)
1 62
20.5%
2 48
15.8%
4 34
11.2%
5 31
10.2%
3 28
9.2%
6 27
8.9%
7 24
 
7.9%
8 18
 
5.9%
9 16
 
5.3%
0 15
 
5.0%
Space Separator
ValueCountFrequency (%)
316
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 61
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1028
60.2%
Common 680
39.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 117
11.4%
예 110
10.7%
상 99
9.6%
경 79
 
7.7%
북 79
 
7.7%
도 79
 
7.7%
군 79
 
7.7%
리 79
 
7.7%
면 48
 
4.7%
읍 39
 
3.8%
Other values (36) 220
21.4%
Common
ValueCountFrequency (%)
316
46.5%
1 62
 
9.1%
- 61
 
9.0%
2 48
 
7.1%
4 34
 
5.0%
5 31
 
4.6%
3 28
 
4.1%
6 27
 
4.0%
7 24
 
3.5%
8 18
 
2.6%
Other values (2) 31
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1028
60.2%
ASCII 680
39.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
316
46.5%
1 62
 
9.1%
- 61
 
9.0%
2 48
 
7.1%
4 34
 
5.0%
5 31
 
4.6%
3 28
 
4.1%
6 27
 
4.0%
7 24
 
3.5%
8 18
 
2.6%
Other values (2) 31
 
4.6%
Hangul
ValueCountFrequency (%)
천 117
11.4%
예 110
10.7%
상 99
9.6%
경 79
 
7.7%
북 79
 
7.7%
도 79
 
7.7%
군 79
 
7.7%
리 79
 
7.7%
면 48
 
4.7%
읍 39
 
3.8%
Other values (36) 220
21.4%

위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct76
Distinct (%)96.2%
Missing48
Missing (%)37.8%
Infinite0
Infinite (%)0.0%
Mean36.612798
Minimum36.507888
Maximum36.744658
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-04-06T17:25:40.281390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.507888
5-th percentile36.508831
Q136.543464
median36.6493
Q336.657095
95-th percentile36.702183
Maximum36.744658
Range0.23676979
Interquartile range (IQR)0.11363034

Descriptive statistics

Standard deviation0.068462756
Coefficient of variation (CV)0.0018699132
Kurtosis-1.1907295
Mean36.612798
Median Absolute Deviation (MAD)0.0414885
Skewness-0.32798135
Sum2892.411
Variance0.0046871489
MonotonicityNot monotonic
2024-04-06T17:25:40.683830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.54346421 2
 
1.6%
36.6493003 2
 
1.6%
36.50788841 2
 
1.6%
36.54371451 1
 
0.8%
36.60795884 1
 
0.8%
36.65598835 1
 
0.8%
36.54063793 1
 
0.8%
36.54298905 1
 
0.8%
36.56378393 1
 
0.8%
36.7001577 1
 
0.8%
Other values (66) 66
52.0%
(Missing) 48
37.8%
ValueCountFrequency (%)
36.50788841 2
1.6%
36.50864959 1
0.8%
36.50870243 1
0.8%
36.50884548 1
0.8%
36.50891833 1
0.8%
36.50901925 1
0.8%
36.50941797 1
0.8%
36.50943027 1
0.8%
36.50945913 1
0.8%
36.50950393 1
0.8%
ValueCountFrequency (%)
36.7446582 1
0.8%
36.72165845 1
0.8%
36.72148401 1
0.8%
36.72041568 1
0.8%
36.7001577 1
0.8%
36.69351772 1
0.8%
36.69061245 1
0.8%
36.68985022 1
0.8%
36.68947899 1
0.8%
36.68893423 1
0.8%

경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct76
Distinct (%)96.2%
Missing48
Missing (%)37.8%
Infinite0
Infinite (%)0.0%
Mean128.39671
Minimum128.27184
Maximum128.57679
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-04-06T17:25:40.986394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.27184
5-th percentile128.27757
Q1128.30082
median128.43838
Q3128.45349
95-th percentile128.5155
Maximum128.57679
Range0.3049523
Interquartile range (IQR)0.15267265

Descriptive statistics

Standard deviation0.079551527
Coefficient of variation (CV)0.00061957604
Kurtosis-1.156043
Mean128.39671
Median Absolute Deviation (MAD)0.0312919
Skewness-0.20443747
Sum10143.34
Variance0.0063284455
MonotonicityNot monotonic
2024-04-06T17:25:41.281707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.386278 2
 
1.6%
128.4383764 2
 
1.6%
128.3026708 2
 
1.6%
128.3871087 1
 
0.8%
128.2821138 1
 
0.8%
128.4525195 1
 
0.8%
128.4614574 1
 
0.8%
128.3865205 1
 
0.8%
128.304509 1
 
0.8%
128.5142311 1
 
0.8%
Other values (66) 66
52.0%
(Missing) 48
37.8%
ValueCountFrequency (%)
128.2718394 1
0.8%
128.2758683 1
0.8%
128.2772161 1
0.8%
128.2772243 1
0.8%
128.2776133 1
0.8%
128.2782969 1
0.8%
128.2821045 1
0.8%
128.2821138 1
0.8%
128.2988261 1
0.8%
128.2990806 1
0.8%
ValueCountFrequency (%)
128.5767917 1
0.8%
128.5274037 1
0.8%
128.5269964 1
0.8%
128.5269529 1
0.8%
128.5142311 1
0.8%
128.5035043 1
0.8%
128.464234 1
0.8%
128.4615022 1
0.8%
128.4614574 1
0.8%
128.4605199 1
0.8%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2024-04-01 00:00:00
Maximum2024-04-01 00:00:00
2024-04-06T17:25:41.513247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:41.707462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-04-06T17:25:33.989628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:33.479030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:34.183442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:25:33.722407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:25:41.848171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소지번주소위도경도
업소지번주소1.0001.0001.000
위도1.0001.0000.878
경도1.0000.8781.000
2024-04-06T17:25:42.442799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.685
경도0.6851.000

Missing values

2024-04-06T17:25:34.497762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:25:34.777162image/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.
2024-04-06T17:25:34.988980image/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

업소명인허가일자업소도로명주소업소지번주소위도경도데이터기준일자
0우정다방1979-08-04경상북도 예천군 풍양면 낙상2길 8경상북도 예천군 풍양면 낙상리 7136.507888128.3026712024-04-01
1유진다방1979-09-21경상북도 예천군 풍양면 낙상2길 45경상북도 예천군 풍양면 낙상리 163-1436.510073128.2992822024-04-01
2백년다방1981-09-21경상북도 예천군 예천읍 효자로 97경상북도 예천군 예천읍 노하리 73-5136.657245128.4542612024-04-01
3송정다방1981-11-03경상북도 예천군 감천면 충효로 1400경상북도 예천군 감천면 포리 385-1836.721658128.5274042024-04-01
4복지다방1981-06-30경상북도 예천군 지보면 지보로 177경상북도 예천군 지보면 마전리 174-136.543715128.3871092024-04-01
5아리수다방1982-04-12경상북도 예천군 예천읍 시장로 82-1경상북도 예천군 예천읍 남본리 222-3536.655392128.4533312024-04-01
6용궁다방1982-09-29경상북도 예천군 용궁면 용궁로 98경상북도 예천군 용궁면 읍부리 316-2036.607231128.2758682024-04-01
7정다방1983-12-08경상북도 예천군 용궁면 용궁로 121-3경상북도 예천군 용궁면 읍부리 295-636.607812128.2782972024-04-01
8솔다방1984-03-20경상북도 예천군 용문면 상금시장길 15-24경상북도 예천군 용문면 상금곡리 617-136.68985128.4070842024-04-01
9늘봄다방1985-08-03경상북도 예천군 예천읍 시장로 74-1경상북도 예천군 예천읍 남본리 222-4536.655062128.4526172024-04-01
업소명인허가일자업소도로명주소업소지번주소위도경도데이터기준일자
117기남이네2023-07-21경상북도 예천군 호명읍 한어길 86-16, 2층<NA><NA><NA>2024-04-01
118은행다방2023-07-26경상북도 예천군 풍양면 낙상2길 33경상북도 예천군 풍양면 낙상리 159-636.509459128.3003882024-04-01
119카페 용궁역2023-09-11경상북도 예천군 용궁면 용궁로 64경상북도 예천군 용궁면 읍부리 39436.607569128.2718392024-04-01
120벤티프레소 경북도청점2023-09-18경상북도 예천군 호명읍 행복로 229, 상가동 114호 (경북도청신도시우방아이유쉘센트럴)<NA><NA><NA>2024-04-01
121송암카페2023-11-02경상북도 예천군 풍양면 삼강리길 41경상북도 예천군 풍양면 삼강리 14236.563268128.3002742024-04-01
122천씨씨커피 경북도청안동점2023-12-06경상북도 예천군 호명읍 새움2로 18, JM스퀘어빌딩 101호<NA><NA><NA>2024-04-01
123핫 플레이스2023-12-08경상북도 예천군 예천읍 효자로 64경상북도 예천군 예천읍 남본리 233-336.655584128.4510482024-04-01
124클라우드2023-06-01경상북도 예천군 호명읍 행복로 229, 상가동 1층 120호 (경북도청신도시우방아이유쉘센트럴)<NA><NA><NA>2024-04-01
125송학다방2024-01-26경상북도 예천군 지보면 지보로 184경상북도 예천군 지보면 소화리 912-1236.543464128.3862782024-04-01
12688다방2024-02-23경상북도 예천군 예천읍 상설시장2길 9경상북도 예천군 예천읍 동본리 55336.656002128.4566832024-04-01