Overview

Dataset statistics

Number of variables6
Number of observations791
Missing cells117
Missing cells (%)2.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory38.0 KiB
Average record size in memory49.2 B

Variable types

Numeric1
Text4
DateTime1

Dataset

Description경기도 광주시 소재 담배소매인 지정현황에 대한 데이터로 지정번호, 업소명, 업소지번주소, 도로명주소 등을 제공합니다.
Author경기도 광주시
URLhttps://www.data.go.kr/data/15021205/fileData.do

Alerts

업소지번주소 has 57 (7.2%) missing valuesMissing
업소도로명주소 has 60 (7.6%) missing valuesMissing
번호 has unique valuesUnique
지정번호 has unique valuesUnique

Reproduction

Analysis started2023-12-16 15:06:38.444218
Analysis finished2023-12-16 15:06:41.999869
Duration3.56 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct791
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean396
Minimum1
Maximum791
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.1 KiB
2023-12-16T15:06:42.375530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile40.5
Q1198.5
median396
Q3593.5
95-th percentile751.5
Maximum791
Range790
Interquartile range (IQR)395

Descriptive statistics

Standard deviation228.48632
Coefficient of variation (CV)0.57698567
Kurtosis-1.2
Mean396
Median Absolute Deviation (MAD)198
Skewness0
Sum313236
Variance52206
MonotonicityStrictly increasing
2023-12-16T15:06:42.993151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
521 1
 
0.1%
523 1
 
0.1%
524 1
 
0.1%
525 1
 
0.1%
526 1
 
0.1%
527 1
 
0.1%
528 1
 
0.1%
529 1
 
0.1%
530 1
 
0.1%
Other values (781) 781
98.7%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
791 1
0.1%
790 1
0.1%
789 1
0.1%
788 1
0.1%
787 1
0.1%
786 1
0.1%
785 1
0.1%
784 1
0.1%
783 1
0.1%
782 1
0.1%

지정번호
Text

UNIQUE 

Distinct791
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
2023-12-16T15:06:44.004599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length23
Mean length23
Min length23

Characters and Unicode

Total characters18193
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

Unique791 ?
Unique (%)100.0%

Sample

1st row2023-5540322-05-6-00092
2nd row2023-5540322-05-6-00090
3rd row2023-5540322-05-6-00091
4th row2023-5540322-05-6-00089
5th row2023-5540322-05-6-00088
ValueCountFrequency (%)
2023-5540322-05-6-00092 1
 
0.1%
2017-5540123-05-6-00024 1
 
0.1%
2016-5540123-05-6-00085 1
 
0.1%
2016-5540123-05-6-00078 1
 
0.1%
2016-5540123-05-6-00081 1
 
0.1%
2016-5540123-05-6-00079 1
 
0.1%
2016-5540123-05-6-00076 1
 
0.1%
2016-5540123-05-6-00073 1
 
0.1%
2016-5540123-05-6-00071 1
 
0.1%
2016-5540123-05-6-00065 1
 
0.1%
Other values (781) 781
98.7%
2023-12-16T15:06:45.067769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5458
30.0%
- 3164
17.4%
5 2890
15.9%
2 2356
13.0%
6 1045
 
5.7%
1 999
 
5.5%
4 992
 
5.5%
3 707
 
3.9%
9 215
 
1.2%
7 185
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15029
82.6%
Dash Punctuation 3164
 
17.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5458
36.3%
5 2890
19.2%
2 2356
15.7%
6 1045
 
7.0%
1 999
 
6.6%
4 992
 
6.6%
3 707
 
4.7%
9 215
 
1.4%
7 185
 
1.2%
8 182
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 3164
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 18193
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5458
30.0%
- 3164
17.4%
5 2890
15.9%
2 2356
13.0%
6 1045
 
5.7%
1 999
 
5.5%
4 992
 
5.5%
3 707
 
3.9%
9 215
 
1.2%
7 185
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18193
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5458
30.0%
- 3164
17.4%
5 2890
15.9%
2 2356
13.0%
6 1045
 
5.7%
1 999
 
5.5%
4 992
 
5.5%
3 707
 
3.9%
9 215
 
1.2%
7 185
 
1.0%

업소명
Text

Distinct786
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
2023-12-16T15:06:45.636133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length22
Mean length10.226296
Min length2

Characters and Unicode

Total characters8089
Distinct characters405
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

Unique781 ?
Unique (%)98.7%

Sample

1st row지에스(GS)25 초월승리점
2nd row(주)디앤오곤지암리조트 L빌리지 무인편의점(씨스페이스)
3rd row(주)디앤오곤지암리조트 EW빌리지 리테일샵(씨스페이스)
4th row주식회사 리치마트
5th row이마트24 광주타운점
ValueCountFrequency (%)
씨유 97
 
7.3%
세븐일레븐 66
 
4.9%
이마트24 53
 
4.0%
지에스25 51
 
3.8%
지에스(gs)25 46
 
3.4%
주식회사 28
 
2.1%
gs25 28
 
2.1%
주)코리아세븐 26
 
1.9%
지에스25(gs25 11
 
0.8%
경기광주 8
 
0.6%
Other values (814) 922
69.0%
2023-12-16T15:06:46.888422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
546
 
6.7%
점 520
 
6.4%
주 448
 
5.5%
광 364
 
4.5%
2 250
 
3.1%
지 219
 
2.7%
5 190
 
2.3%
스 182
 
2.2%
마 179
 
2.2%
븐 172
 
2.1%
Other values (395) 5019
62.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6358
78.6%
Space Separator 546
 
6.7%
Decimal Number 518
 
6.4%
Uppercase Letter 320
 
4.0%
Close Punctuation 161
 
2.0%
Open Punctuation 161
 
2.0%
Lowercase Letter 20
 
0.2%
Other Punctuation 3
 
< 0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 520
 
8.2%
주 448
 
7.0%
광 364
 
5.7%
지 219
 
3.4%
스 182
 
2.9%
마 179
 
2.8%
븐 172
 
2.7%
트 164
 
2.6%
유 153
 
2.4%
에 145
 
2.3%
Other values (347) 3812
60.0%
Uppercase Letter
ValueCountFrequency (%)
G 115
35.9%
S 113
35.3%
C 18
 
5.6%
U 13
 
4.1%
R 11
 
3.4%
A 8
 
2.5%
M 6
 
1.9%
D 5
 
1.6%
T 5
 
1.6%
I 5
 
1.6%
Other values (10) 21
 
6.6%
Lowercase Letter
ValueCountFrequency (%)
s 4
20.0%
e 3
15.0%
g 2
10.0%
i 2
10.0%
l 2
10.0%
n 2
10.0%
o 1
 
5.0%
w 1
 
5.0%
r 1
 
5.0%
u 1
 
5.0%
Decimal Number
ValueCountFrequency (%)
2 250
48.3%
5 190
36.7%
4 57
 
11.0%
1 12
 
2.3%
3 3
 
0.6%
0 3
 
0.6%
7 2
 
0.4%
8 1
 
0.2%
Other Punctuation
ValueCountFrequency (%)
. 1
33.3%
& 1
33.3%
' 1
33.3%
Close Punctuation
ValueCountFrequency (%)
) 160
99.4%
] 1
 
0.6%
Open Punctuation
ValueCountFrequency (%)
( 160
99.4%
[ 1
 
0.6%
Space Separator
ValueCountFrequency (%)
546
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6358
78.6%
Common 1391
 
17.2%
Latin 340
 
4.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 520
 
8.2%
주 448
 
7.0%
광 364
 
5.7%
지 219
 
3.4%
스 182
 
2.9%
마 179
 
2.8%
븐 172
 
2.7%
트 164
 
2.6%
유 153
 
2.4%
에 145
 
2.3%
Other values (347) 3812
60.0%
Latin
ValueCountFrequency (%)
G 115
33.8%
S 113
33.2%
C 18
 
5.3%
U 13
 
3.8%
R 11
 
3.2%
A 8
 
2.4%
M 6
 
1.8%
D 5
 
1.5%
T 5
 
1.5%
I 5
 
1.5%
Other values (21) 41
 
12.1%
Common
ValueCountFrequency (%)
546
39.3%
2 250
18.0%
5 190
 
13.7%
) 160
 
11.5%
( 160
 
11.5%
4 57
 
4.1%
1 12
 
0.9%
3 3
 
0.2%
0 3
 
0.2%
- 2
 
0.1%
Other values (7) 8
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6358
78.6%
ASCII 1731
 
21.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
546
31.5%
2 250
14.4%
5 190
 
11.0%
) 160
 
9.2%
( 160
 
9.2%
G 115
 
6.6%
S 113
 
6.5%
4 57
 
3.3%
C 18
 
1.0%
U 13
 
0.8%
Other values (38) 109
 
6.3%
Hangul
ValueCountFrequency (%)
점 520
 
8.2%
주 448
 
7.0%
광 364
 
5.7%
지 219
 
3.4%
스 182
 
2.9%
마 179
 
2.8%
븐 172
 
2.7%
트 164
 
2.6%
유 153
 
2.4%
에 145
 
2.3%
Other values (347) 3812
60.0%

업소지번주소
Text

MISSING 

Distinct730
Distinct (%)99.5%
Missing57
Missing (%)7.2%
Memory size6.3 KiB
2023-12-16T15:06:47.919937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length42.5
Mean length23.125341
Min length14

Characters and Unicode

Total characters16974
Distinct characters272
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

Unique726 ?
Unique (%)98.9%

Sample

1st row경기도 광주시 초월읍 산이리 181-1 티아모
2nd row경기도 광주시 도척면 도웅리 533 L빌리지
3rd row경기도 광주시 도척면 도웅리 533 EW빌리지
4th row경기도 광주시 양벌동 308-10
5th row경기도 광주시 신현동 860-1 1층
ValueCountFrequency (%)
경기도 734
 
18.0%
광주시 731
 
17.9%
오포읍 133
 
3.3%
초월읍 102
 
2.5%
곤지암읍 81
 
2.0%
1층 73
 
1.8%
1호 64
 
1.6%
경안동 47
 
1.2%
태전동 44
 
1.1%
퇴촌면 40
 
1.0%
Other values (969) 2024
49.7%
2023-12-16T15:06:49.749783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3367
19.8%
도 800
 
4.7%
경 792
 
4.7%
광 771
 
4.5%
주 758
 
4.5%
기 739
 
4.4%
1 737
 
4.3%
시 737
 
4.3%
지 563
 
3.3%
2 451
 
2.7%
Other values (262) 7259
42.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10088
59.4%
Space Separator 3367
 
19.8%
Decimal Number 3179
 
18.7%
Dash Punctuation 269
 
1.6%
Uppercase Letter 41
 
0.2%
Other Punctuation 28
 
0.2%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 800
 
7.9%
경 792
 
7.9%
광 771
 
7.6%
주 758
 
7.5%
기 739
 
7.3%
시 737
 
7.3%
지 563
 
5.6%
리 425
 
4.2%
호 416
 
4.1%
동 401
 
4.0%
Other values (229) 3686
36.5%
Uppercase Letter
ValueCountFrequency (%)
B 11
26.8%
A 10
24.4%
E 4
 
9.8%
L 2
 
4.9%
Z 2
 
4.9%
H 2
 
4.9%
O 2
 
4.9%
W 1
 
2.4%
N 1
 
2.4%
C 1
 
2.4%
Other values (5) 5
12.2%
Decimal Number
ValueCountFrequency (%)
1 737
23.2%
2 451
14.2%
3 371
11.7%
4 297
9.3%
0 259
 
8.1%
5 254
 
8.0%
6 247
 
7.8%
7 204
 
6.4%
8 186
 
5.9%
9 173
 
5.4%
Other Punctuation
ValueCountFrequency (%)
, 25
89.3%
/ 1
 
3.6%
@ 1
 
3.6%
. 1
 
3.6%
Space Separator
ValueCountFrequency (%)
3367
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 269
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10088
59.4%
Common 6845
40.3%
Latin 41
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 800
 
7.9%
경 792
 
7.9%
광 771
 
7.6%
주 758
 
7.5%
기 739
 
7.3%
시 737
 
7.3%
지 563
 
5.6%
리 425
 
4.2%
호 416
 
4.1%
동 401
 
4.0%
Other values (229) 3686
36.5%
Common
ValueCountFrequency (%)
3367
49.2%
1 737
 
10.8%
2 451
 
6.6%
3 371
 
5.4%
4 297
 
4.3%
- 269
 
3.9%
0 259
 
3.8%
5 254
 
3.7%
6 247
 
3.6%
7 204
 
3.0%
Other values (8) 389
 
5.7%
Latin
ValueCountFrequency (%)
B 11
26.8%
A 10
24.4%
E 4
 
9.8%
L 2
 
4.9%
Z 2
 
4.9%
H 2
 
4.9%
O 2
 
4.9%
W 1
 
2.4%
N 1
 
2.4%
C 1
 
2.4%
Other values (5) 5
12.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10088
59.4%
ASCII 6886
40.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3367
48.9%
1 737
 
10.7%
2 451
 
6.5%
3 371
 
5.4%
4 297
 
4.3%
- 269
 
3.9%
0 259
 
3.8%
5 254
 
3.7%
6 247
 
3.6%
7 204
 
3.0%
Other values (23) 430
 
6.2%
Hangul
ValueCountFrequency (%)
도 800
 
7.9%
경 792
 
7.9%
광 771
 
7.6%
주 758
 
7.5%
기 739
 
7.3%
시 737
 
7.3%
지 563
 
5.6%
리 425
 
4.2%
호 416
 
4.1%
동 401
 
4.0%
Other values (229) 3686
36.5%

업소도로명주소
Text

MISSING 

Distinct729
Distinct (%)99.7%
Missing60
Missing (%)7.6%
Memory size6.3 KiB
2023-12-16T15:06:51.891686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length51
Mean length26.597811
Min length17

Characters and Unicode

Total characters19443
Distinct characters302
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

Unique727 ?
Unique (%)99.5%

Sample

1st row경기도 광주시 초월읍 산이길 44-6 (티아모)
2nd row경기도 광주시 양벌로 200 (양벌동)
3rd row경기도 광주시 상태길 71, 1층 (신현동)
4th row경기도 광주시 초월읍 설월길23번길 20-2
5th row경기도 광주시 퇴촌면 천진암로 591, 1층
ValueCountFrequency (%)
경기도 731
 
16.5%
광주시 731
 
16.5%
1층 228
 
5.1%
오포읍 132
 
3.0%
초월읍 102
 
2.3%
곤지암읍 84
 
1.9%
101호 48
 
1.1%
경안동 47
 
1.1%
경충대로 46
 
1.0%
태전동 43
 
1.0%
Other values (974) 2240
50.5%
2023-12-16T15:06:54.192769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3703
19.0%
1 1043
 
5.4%
경 888
 
4.6%
도 806
 
4.1%
광 804
 
4.1%
주 776
 
4.0%
시 738
 
3.8%
기 736
 
3.8%
로 553
 
2.8%
, 484
 
2.5%
Other values (292) 8912
45.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11007
56.6%
Space Separator 3703
 
19.0%
Decimal Number 3302
 
17.0%
Other Punctuation 486
 
2.5%
Close Punctuation 363
 
1.9%
Open Punctuation 363
 
1.9%
Dash Punctuation 153
 
0.8%
Uppercase Letter 63
 
0.3%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 888
 
8.1%
도 806
 
7.3%
광 804
 
7.3%
주 776
 
7.1%
시 738
 
6.7%
기 736
 
6.7%
로 553
 
5.0%
동 441
 
4.0%
읍 318
 
2.9%
길 298
 
2.7%
Other values (259) 4649
42.2%
Uppercase Letter
ValueCountFrequency (%)
B 29
46.0%
A 15
23.8%
E 3
 
4.8%
Z 2
 
3.2%
C 2
 
3.2%
H 2
 
3.2%
O 2
 
3.2%
U 1
 
1.6%
S 1
 
1.6%
T 1
 
1.6%
Other values (5) 5
 
7.9%
Decimal Number
ValueCountFrequency (%)
1 1043
31.6%
2 402
 
12.2%
0 364
 
11.0%
3 306
 
9.3%
4 260
 
7.9%
6 212
 
6.4%
5 211
 
6.4%
7 200
 
6.1%
8 160
 
4.8%
9 144
 
4.4%
Other Punctuation
ValueCountFrequency (%)
, 484
99.6%
. 1
 
0.2%
/ 1
 
0.2%
Space Separator
ValueCountFrequency (%)
3703
100.0%
Close Punctuation
ValueCountFrequency (%)
) 363
100.0%
Open Punctuation
ValueCountFrequency (%)
( 363
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 153
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11007
56.6%
Common 8373
43.1%
Latin 63
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 888
 
8.1%
도 806
 
7.3%
광 804
 
7.3%
주 776
 
7.1%
시 738
 
6.7%
기 736
 
6.7%
로 553
 
5.0%
동 441
 
4.0%
읍 318
 
2.9%
길 298
 
2.7%
Other values (259) 4649
42.2%
Common
ValueCountFrequency (%)
3703
44.2%
1 1043
 
12.5%
, 484
 
5.8%
2 402
 
4.8%
0 364
 
4.3%
) 363
 
4.3%
( 363
 
4.3%
3 306
 
3.7%
4 260
 
3.1%
6 212
 
2.5%
Other values (8) 873
 
10.4%
Latin
ValueCountFrequency (%)
B 29
46.0%
A 15
23.8%
E 3
 
4.8%
Z 2
 
3.2%
C 2
 
3.2%
H 2
 
3.2%
O 2
 
3.2%
U 1
 
1.6%
S 1
 
1.6%
T 1
 
1.6%
Other values (5) 5
 
7.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11007
56.6%
ASCII 8436
43.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3703
43.9%
1 1043
 
12.4%
, 484
 
5.7%
2 402
 
4.8%
0 364
 
4.3%
) 363
 
4.3%
( 363
 
4.3%
3 306
 
3.6%
4 260
 
3.1%
6 212
 
2.5%
Other values (23) 936
 
11.1%
Hangul
ValueCountFrequency (%)
경 888
 
8.1%
도 806
 
7.3%
광 804
 
7.3%
주 776
 
7.1%
시 738
 
6.7%
기 736
 
6.7%
로 553
 
5.0%
동 441
 
4.0%
읍 318
 
2.9%
길 298
 
2.7%
Other values (259) 4649
42.2%

지정일자
Date

Distinct634
Distinct (%)80.2%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
Minimum1985-01-25 00:00:00
Maximum2023-12-08 00:00:00
2023-12-16T15:06:55.312364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:06:57.205575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2023-12-16T15:06:40.192547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-16T15:06:41.057268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-16T15:06:41.400942image/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.
2023-12-16T15:06:41.690597image/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

번호지정번호업소명업소지번주소업소도로명주소지정일자
012023-5540322-05-6-00092지에스(GS)25 초월승리점경기도 광주시 초월읍 산이리 181-1 티아모경기도 광주시 초월읍 산이길 44-6 (티아모)2023-12-08
122023-5540322-05-6-00090(주)디앤오곤지암리조트 L빌리지 무인편의점(씨스페이스)경기도 광주시 도척면 도웅리 533 L빌리지<NA>2023-12-07
232023-5540322-05-6-00091(주)디앤오곤지암리조트 EW빌리지 리테일샵(씨스페이스)경기도 광주시 도척면 도웅리 533 EW빌리지<NA>2023-12-07
342023-5540322-05-6-00089주식회사 리치마트경기도 광주시 양벌동 308-10경기도 광주시 양벌로 200 (양벌동)2023-11-30
452023-5540322-05-6-00088이마트24 광주타운점경기도 광주시 신현동 860-1 1층경기도 광주시 상태길 71, 1층 (신현동)2023-11-20
562023-5540322-05-6-00087지에스(GS)25 광주지월점경기도 광주시 초월읍 지월리 753-2경기도 광주시 초월읍 설월길23번길 20-22023-11-17
672023-5540322-05-6-00086지에스(GS)25 뉴광주천진암점경기도 광주시 퇴촌면 관음리 504-6 1층경기도 광주시 퇴촌면 천진암로 591, 1층2023-11-16
782023-5540322-05-6-00085지에스(GS)25 오포행복점경기도 광주시 양벌동 704-3경기도 광주시 양촌안길 35-4 (양벌동)2023-11-13
892023-5540322-05-6-00083씨유 광주태전점경기도 광주시 중대동 17-7 1층경기도 광주시 고불로 60, 1층 (중대동)2023-11-03
9102023-5540322-05-6-00084(주)코리아세븐 경기광주초월점경기도 광주시 초월읍 신월리 472경기도 광주시 초월읍 산수로 5002023-11-03
번호지정번호업소명업소지번주소업소도로명주소지정일자
7817822000-4130000-05-6-00490대성낚시경기도 광주시 곤지암읍 삼리 94번지경기도 광주시 곤지암읍 경충대로 7011998-05-08
7827832000-4130000-05-6-00016광주열쇠경기도 광주군 광주읍 경안리 54번지 1호경기도 광주시 중앙로 124 (경안동)1997-12-24
7837842000-4130000-05-6-00320고산구판장경기도 광주시 오포읍 고산리 299번지 2호경기도 광주시 오포읍 고산길 631997-11-05
7847852000-4130000-05-6-00462곤지암농업협동조합만선지점경기도 광주시 곤지암읍 만선리 208번지 2호경기도 광주시 곤지암읍 신만로 5061996-03-08
7857862000-4130000-05-6-00118경동상회경기도 광주시 역동 61번지 6호<NA>1991-04-08
7867872000-4130000-05-6-00614경안상회경기도 광주시 남한산성면 상번천리 545번지경기도 광주시 중부면 해공로 661990-11-16
7877882000-4130000-05-6-00527도척농업협동조합경기도 광주시 도척면 노곡리 58번지 23호경기도 광주시 도척면 노곡로 121989-07-03
7887892000-4130000-05-6-00576강촌식당경기도 광주시 남종면 분원리 91번지경기도 광주시 남종면 산수로 16331987-08-02
7897902000-4130000-05-6-00057코사마트(골목점)경기도 광주시 역동 139번지 15호경기도 광주시 역동로81번길 9 (역동)1986-08-28
7907912000-4130000-05-6-00059광명상회경기도 광주시 송정동 101번지 46호경기도 광주시 통미로16번길 5-7 (송정동)1985-01-25