Overview

Dataset statistics

Number of variables10
Number of observations249
Missing cells129
Missing cells (%)5.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory19.6 KiB
Average record size in memory80.5 B

Variable types

Categorical5
Text4
DateTime1

Dataset

Description경상남도 창녕군 관내 담배소매인 지정 현황 정보(시군명, 소매인구분, 업소명, 지번주소, 도로명주소, 영업상태, 지정일자, 데이터기준일자)
Author경상남도 창녕군
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15035661

Alerts

시군명 has constant value ""Constant
민원구분(구내/일반) has constant value ""Constant
소매인구분 has constant value ""Constant
영업상태(정사영업/폐업처리) has constant value ""Constant
데이터기준일자 has constant value ""Constant
전화번호 has 129 (51.8%) missing valuesMissing

Reproduction

Analysis started2023-12-11 00:17:42.768924
Analysis finished2023-12-11 00:17:43.311207
Duration0.54 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
경상남도 창녕군
249 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경상남도 창녕군
2nd row경상남도 창녕군
3rd row경상남도 창녕군
4th row경상남도 창녕군
5th row경상남도 창녕군

Common Values

ValueCountFrequency (%)
경상남도 창녕군 249
100.0%

Length

2023-12-11T09:17:43.369021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:17:43.453242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상남도 249
50.0%
창녕군 249
50.0%

민원구분(구내/일반)
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
일반
249 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반 249
100.0%

Length

2023-12-11T09:17:43.547246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:17:43.644995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반 249
100.0%

업소명
Text

Distinct217
Distinct (%)87.1%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2023-12-11T09:17:43.838781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length16
Mean length6.184739
Min length2

Characters and Unicode

Total characters1540
Distinct characters273
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique208 ?
Unique (%)83.5%

Sample

1st row마마치
2nd row맘편한 그린DC마트
3rd row홈마트
4th row인교슈퍼
5th row풍년슈퍼
ValueCountFrequency (%)
일용잡화 17
 
5.7%
잡화 10
 
3.3%
세븐일레븐 9
 
3.0%
gs25 9
 
3.0%
씨유 9
 
3.0%
창녕점 5
 
1.7%
남지상회 2
 
0.7%
아이마트 2
 
0.7%
영마트 2
 
0.7%
진마트 2
 
0.7%
Other values (227) 233
77.7%
2023-12-11T09:17:44.281003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 71
 
4.6%
52
 
3.4%
창 47
 
3.1%
녕 44
 
2.9%
마 42
 
2.7%
일 36
 
2.3%
트 35
 
2.3%
지 34
 
2.2%
화 31
 
2.0%
잡 28
 
1.8%
Other values (263) 1120
72.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1392
90.4%
Space Separator 52
 
3.4%
Uppercase Letter 42
 
2.7%
Decimal Number 36
 
2.3%
Open Punctuation 9
 
0.6%
Close Punctuation 9
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 71
 
5.1%
창 47
 
3.4%
녕 44
 
3.2%
마 42
 
3.0%
일 36
 
2.6%
트 35
 
2.5%
지 34
 
2.4%
화 31
 
2.2%
잡 28
 
2.0%
븐 27
 
1.9%
Other values (246) 997
71.6%
Uppercase Letter
ValueCountFrequency (%)
S 13
31.0%
G 13
31.0%
C 7
16.7%
U 4
 
9.5%
B 1
 
2.4%
A 1
 
2.4%
I 1
 
2.4%
O 1
 
2.4%
D 1
 
2.4%
Decimal Number
ValueCountFrequency (%)
2 17
47.2%
5 15
41.7%
4 2
 
5.6%
9 1
 
2.8%
3 1
 
2.8%
Space Separator
ValueCountFrequency (%)
52
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1392
90.4%
Common 106
 
6.9%
Latin 42
 
2.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 71
 
5.1%
창 47
 
3.4%
녕 44
 
3.2%
마 42
 
3.0%
일 36
 
2.6%
트 35
 
2.5%
지 34
 
2.4%
화 31
 
2.2%
잡 28
 
2.0%
븐 27
 
1.9%
Other values (246) 997
71.6%
Latin
ValueCountFrequency (%)
S 13
31.0%
G 13
31.0%
C 7
16.7%
U 4
 
9.5%
B 1
 
2.4%
A 1
 
2.4%
I 1
 
2.4%
O 1
 
2.4%
D 1
 
2.4%
Common
ValueCountFrequency (%)
52
49.1%
2 17
 
16.0%
5 15
 
14.2%
( 9
 
8.5%
) 9
 
8.5%
4 2
 
1.9%
9 1
 
0.9%
3 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1392
90.4%
ASCII 148
 
9.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 71
 
5.1%
창 47
 
3.4%
녕 44
 
3.2%
마 42
 
3.0%
일 36
 
2.6%
트 35
 
2.5%
지 34
 
2.4%
화 31
 
2.2%
잡 28
 
2.0%
븐 27
 
1.9%
Other values (246) 997
71.6%
ASCII
ValueCountFrequency (%)
52
35.1%
2 17
 
11.5%
5 15
 
10.1%
S 13
 
8.8%
G 13
 
8.8%
( 9
 
6.1%
) 9
 
6.1%
C 7
 
4.7%
U 4
 
2.7%
4 2
 
1.4%
Other values (7) 7
 
4.7%

소재지지번주소
Text

Distinct245
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2023-12-11T09:17:44.627373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length23
Mean length21.710843
Min length19

Characters and Unicode

Total characters5406
Distinct characters105
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

Unique241 ?
Unique (%)96.8%

Sample

1st row경상남도 창녕군 부곡면 구산리 295-3
2nd row경상남도 창녕군 남지읍 남지리 609-47
3rd row경상남도 창녕군 남지읍 남지리 981-1
4th row경상남도 창녕군 부곡면 수다리 5-13
5th row경상남도 창녕군 도천면 송진리 205-8
ValueCountFrequency (%)
창녕군 249
20.0%
경상남도 248
19.9%
창녕읍 64
 
5.1%
남지읍 46
 
3.7%
부곡면 37
 
3.0%
남지리 35
 
2.8%
영산면 27
 
2.2%
거문리 26
 
2.1%
대합면 17
 
1.4%
술정리 13
 
1.0%
Other values (322) 483
38.8%
2023-12-11T09:17:45.135607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1039
19.2%
남 332
 
6.1%
창 318
 
5.9%
녕 317
 
5.9%
도 263
 
4.9%
상 250
 
4.6%
군 249
 
4.6%
경 248
 
4.6%
리 240
 
4.4%
- 197
 
3.6%
Other values (95) 1953
36.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3191
59.0%
Space Separator 1039
 
19.2%
Decimal Number 979
 
18.1%
Dash Punctuation 197
 
3.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 332
10.4%
창 318
10.0%
녕 317
9.9%
도 263
 
8.2%
상 250
 
7.8%
군 249
 
7.8%
경 248
 
7.8%
리 240
 
7.5%
면 139
 
4.4%
읍 110
 
3.4%
Other values (83) 725
22.7%
Decimal Number
ValueCountFrequency (%)
1 190
19.4%
2 164
16.8%
3 126
12.9%
5 96
9.8%
6 75
 
7.7%
7 71
 
7.3%
4 69
 
7.0%
9 67
 
6.8%
8 61
 
6.2%
0 60
 
6.1%
Space Separator
ValueCountFrequency (%)
1039
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 197
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3191
59.0%
Common 2215
41.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 332
10.4%
창 318
10.0%
녕 317
9.9%
도 263
 
8.2%
상 250
 
7.8%
군 249
 
7.8%
경 248
 
7.8%
리 240
 
7.5%
면 139
 
4.4%
읍 110
 
3.4%
Other values (83) 725
22.7%
Common
ValueCountFrequency (%)
1039
46.9%
- 197
 
8.9%
1 190
 
8.6%
2 164
 
7.4%
3 126
 
5.7%
5 96
 
4.3%
6 75
 
3.4%
7 71
 
3.2%
4 69
 
3.1%
9 67
 
3.0%
Other values (2) 121
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3191
59.0%
ASCII 2215
41.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1039
46.9%
- 197
 
8.9%
1 190
 
8.6%
2 164
 
7.4%
3 126
 
5.7%
5 96
 
4.3%
6 75
 
3.4%
7 71
 
3.2%
4 69
 
3.1%
9 67
 
3.0%
Other values (2) 121
 
5.5%
Hangul
ValueCountFrequency (%)
남 332
10.4%
창 318
10.0%
녕 317
9.9%
도 263
 
8.2%
상 250
 
7.8%
군 249
 
7.8%
경 248
 
7.8%
리 240
 
7.5%
면 139
 
4.4%
읍 110
 
3.4%
Other values (83) 725
22.7%

소재지도로명주소
Text

Distinct242
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2023-12-11T09:17:45.546129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length38
Mean length21.297189
Min length18

Characters and Unicode

Total characters5303
Distinct characters153
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

Unique236 ?
Unique (%)94.8%

Sample

1st row경상남도 창녕군 부곡면 구산학포로 283
2nd row경상남도 창녕군 남지읍 낙동로 514
3rd row경상남도 창녕군 남지읍 남지중앙로 66
4th row경상남도 창녕군 부곡면 온천로 1183
5th row경상남도 창녕군 도천면 영산도천로 1
ValueCountFrequency (%)
경상남도 249
19.6%
창녕군 249
19.6%
창녕읍 64
 
5.0%
남지읍 46
 
3.6%
부곡면 37
 
2.9%
영산면 27
 
2.1%
대합면 17
 
1.3%
명덕로 11
 
0.9%
낙동로 11
 
0.9%
계성면 10
 
0.8%
Other values (305) 548
43.2%
2023-12-11T09:17:45.855153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1020
19.2%
창 337
 
6.4%
녕 327
 
6.2%
남 312
 
5.9%
도 265
 
5.0%
상 254
 
4.8%
경 252
 
4.8%
군 252
 
4.8%
1 186
 
3.5%
로 140
 
2.6%
Other values (143) 1958
36.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3502
66.0%
Space Separator 1020
 
19.2%
Decimal Number 712
 
13.4%
Dash Punctuation 40
 
0.8%
Other Punctuation 13
 
0.2%
Open Punctuation 8
 
0.2%
Close Punctuation 8
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
창 337
 
9.6%
녕 327
 
9.3%
남 312
 
8.9%
도 265
 
7.6%
상 254
 
7.3%
경 252
 
7.2%
군 252
 
7.2%
로 140
 
4.0%
면 139
 
4.0%
길 116
 
3.3%
Other values (128) 1108
31.6%
Decimal Number
ValueCountFrequency (%)
1 186
26.1%
2 97
13.6%
4 74
 
10.4%
3 63
 
8.8%
9 59
 
8.3%
5 56
 
7.9%
0 52
 
7.3%
7 49
 
6.9%
6 43
 
6.0%
8 33
 
4.6%
Space Separator
ValueCountFrequency (%)
1020
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 40
100.0%
Other Punctuation
ValueCountFrequency (%)
. 13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3502
66.0%
Common 1801
34.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
창 337
 
9.6%
녕 327
 
9.3%
남 312
 
8.9%
도 265
 
7.6%
상 254
 
7.3%
경 252
 
7.2%
군 252
 
7.2%
로 140
 
4.0%
면 139
 
4.0%
길 116
 
3.3%
Other values (128) 1108
31.6%
Common
ValueCountFrequency (%)
1020
56.6%
1 186
 
10.3%
2 97
 
5.4%
4 74
 
4.1%
3 63
 
3.5%
9 59
 
3.3%
5 56
 
3.1%
0 52
 
2.9%
7 49
 
2.7%
6 43
 
2.4%
Other values (5) 102
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3502
66.0%
ASCII 1801
34.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1020
56.6%
1 186
 
10.3%
2 97
 
5.4%
4 74
 
4.1%
3 63
 
3.5%
9 59
 
3.3%
5 56
 
3.1%
0 52
 
2.9%
7 49
 
2.7%
6 43
 
2.4%
Other values (5) 102
 
5.7%
Hangul
ValueCountFrequency (%)
창 337
 
9.6%
녕 327
 
9.3%
남 312
 
8.9%
도 265
 
7.6%
상 254
 
7.3%
경 252
 
7.2%
군 252
 
7.2%
로 140
 
4.0%
면 139
 
4.0%
길 116
 
3.3%
Other values (128) 1108
31.6%

소매인구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
일반소매인
249 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반소매인 249
100.0%

Length

2023-12-11T09:17:45.958968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:17:46.034536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반소매인 249
100.0%

영업상태(정사영업/폐업처리)
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
정상영업
249 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정상영업 249
100.0%

Length

2023-12-11T09:17:46.109908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:17:46.181865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상영업 249
100.0%

지정일자
Date

Distinct203
Distinct (%)81.5%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
Minimum1985-06-30 00:00:00
Maximum2020-02-27 00:00:00
2023-12-11T09:17:46.269480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:17:46.393643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

전화번호
Text

MISSING 

Distinct103
Distinct (%)85.8%
Missing129
Missing (%)51.8%
Memory size2.1 KiB
2023-12-11T09:17:46.603328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length10.625
Min length1

Characters and Unicode

Total characters1275
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique99 ?
Unique (%)82.5%

Sample

1st row055-521-5077
2nd row055-526-2580
3rd row055-370-5023
4th row055-536-9870
5th row055-532-1253
ValueCountFrequency (%)
055-533-0065 2
 
1.9%
055-526-3981 2
 
1.9%
055-532-6641 2
 
1.9%
055-526-1329 1
 
1.0%
055-536-5521 1
 
1.0%
055-521-0667 1
 
1.0%
055-521-5151 1
 
1.0%
055-533-1669 1
 
1.0%
055-536-2956 1
 
1.0%
055-533-1599 1
 
1.0%
Other values (92) 92
87.6%
2023-12-11T09:17:46.913280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 356
27.9%
- 210
16.5%
0 160
12.5%
3 136
 
10.7%
2 102
 
8.0%
6 84
 
6.6%
1 67
 
5.3%
8 44
 
3.5%
7 37
 
2.9%
9 35
 
2.7%
Other values (2) 44
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1050
82.4%
Dash Punctuation 210
 
16.5%
Space Separator 15
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 356
33.9%
0 160
15.2%
3 136
 
13.0%
2 102
 
9.7%
6 84
 
8.0%
1 67
 
6.4%
8 44
 
4.2%
7 37
 
3.5%
9 35
 
3.3%
4 29
 
2.8%
Dash Punctuation
ValueCountFrequency (%)
- 210
100.0%
Space Separator
ValueCountFrequency (%)
15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1275
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 356
27.9%
- 210
16.5%
0 160
12.5%
3 136
 
10.7%
2 102
 
8.0%
6 84
 
6.6%
1 67
 
5.3%
8 44
 
3.5%
7 37
 
2.9%
9 35
 
2.7%
Other values (2) 44
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1275
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 356
27.9%
- 210
16.5%
0 160
12.5%
3 136
 
10.7%
2 102
 
8.0%
6 84
 
6.6%
1 67
 
5.3%
8 44
 
3.5%
7 37
 
2.9%
9 35
 
2.7%
Other values (2) 44
 
3.5%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2020-04-08
249 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-04-08
2nd row2020-04-08
3rd row2020-04-08
4th row2020-04-08
5th row2020-04-08

Common Values

ValueCountFrequency (%)
2020-04-08 249
100.0%

Length

2023-12-11T09:17:47.024276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:17:47.114252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-04-08 249
100.0%

Missing values

2023-12-11T09:17:43.109593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:17:43.255251image/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

시군명민원구분(구내/일반)업소명소재지지번주소소재지도로명주소소매인구분영업상태(정사영업/폐업처리)지정일자전화번호데이터기준일자
0경상남도 창녕군일반마마치경상남도 창녕군 부곡면 구산리 295-3경상남도 창녕군 부곡면 구산학포로 283일반소매인정상영업2019-03-13<NA>2020-04-08
1경상남도 창녕군일반맘편한 그린DC마트경상남도 창녕군 남지읍 남지리 609-47경상남도 창녕군 남지읍 낙동로 514일반소매인정상영업2019-02-26<NA>2020-04-08
2경상남도 창녕군일반홈마트경상남도 창녕군 남지읍 남지리 981-1경상남도 창녕군 남지읍 남지중앙로 66일반소매인정상영업2019-02-26<NA>2020-04-08
3경상남도 창녕군일반인교슈퍼경상남도 창녕군 부곡면 수다리 5-13경상남도 창녕군 부곡면 온천로 1183일반소매인정상영업2019-01-28055-521-50772020-04-08
4경상남도 창녕군일반풍년슈퍼경상남도 창녕군 도천면 송진리 205-8경상남도 창녕군 도천면 영산도천로 1일반소매인정상영업2018-12-07<NA>2020-04-08
5경상남도 창녕군일반지에스25창녕부곡점경상남도 창녕군 부곡면 부곡리 283-4경상남도 창녕군 부곡면 새동네1길 1일반소매인정상영업2018-12-07<NA>2020-04-08
6경상남도 창녕군일반폰앤픽스경상남도 창녕군 남지읍 남지리 29432경상남도 창녕군 남지읍 동포옛길 21-46. 101호일반소매인정상영업2018-11-26<NA>2020-04-08
7경상남도 창녕군일반이마트24 창녕남지중앙로점경상남도 창녕군 남지읍 남지리 167-1경상남도 창녕군 남지읍 남지중앙로 128일반소매인정상영업2018-10-01<NA>2020-04-08
8경상남도 창녕군일반아시아마트경상남도 창녕군 영산면 서리 116-22경상남도 창녕군 영산면 연지길 37일반소매인정상영업2018-08-03<NA>2020-04-08
9경상남도 창녕군일반빨간파라솔슈퍼경상남도 창녕군 남지읍 대곡리 525경상남도 창녕군 남지읍 박진로 430일반소매인정상영업2018-07-03<NA>2020-04-08
시군명민원구분(구내/일반)업소명소재지지번주소소재지도로명주소소매인구분영업상태(정사영업/폐업처리)지정일자전화번호데이터기준일자
239경상남도 창녕군일반부자식육식당경상남도 창녕군 남지읍 남지리 991-5경상남도 창녕군 남지읍 남지중앙1길 91-4일반소매인정상영업2019-11-06055-526-13292020-04-08
240경상남도 창녕군일반우리인력경상남도 창녕군 창녕읍 술정리 177-5경상남도 창녕군 창녕읍 창녕대로 99-1. 102호일반소매인정상영업2019-11-06<NA>2020-04-08
241경상남도 창녕군일반먹거리분식슈퍼경상남도 창녕군 남지읍 마산리 905-20경상남도 창녕군 남지읍 낙동로 395일반소매인정상영업2019-10-17<NA>2020-04-08
242경상남도 창녕군일반세븐일레븐 창녕도천점경상남도 창녕군 도천면 도천리 1030-1경상남도 창녕군 도천면 도천중앙로 5일반소매인정상영업2019-09-25<NA>2020-04-08
243경상남도 창녕군일반뭉치네가든경상남도 창녕군 고암면 우천리 1087-95경상남도 창녕군 고암면 창밀로 346일반소매인정상영업2019-08-23055-533-69492020-04-08
244경상남도 창녕군일반세븐일레븐 창녕영산센터점경상남도 창녕군 영산면 서리 134-11경상남도 창녕군 영산면 연지길 23일반소매인정상영업2019-08-08<NA>2020-04-08
245경상남도 창녕군일반사료할인마트경상남도 창녕군 창녕읍 교하리 222-10경상남도 창녕군 창녕읍 창녕시장길 9일반소매인정상영업2019-08-08<NA>2020-04-08
246경상남도 창녕군일반(주)아워홈 하이에어코리아 창녕점경상남도 창녕군 도천면 송진리 323경상남도 창녕군 도천면 적말길 50일반소매인정상영업2019-07-15<NA>2020-04-08
247경상남도 창녕군일반CU창녕대합공단점경상남도 창녕군 대합면 합리 1324경상남도 창녕군 대합면 대합산업단지로 107-12일반소매인정상영업2019-07-08<NA>2020-04-08
248경상남도 창녕군일반동해분식휴게소경상남도 창녕군 이방면 현창리 71-3경상남도 창녕군 이방면 우포1대로 72일반소매인정상영업2019-06-04<NA>2020-04-08