Overview

Dataset statistics

Number of variables6
Number of observations622
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory29.9 KiB
Average record size in memory49.2 B

Variable types

Numeric1
Text4
DateTime1

Dataset

Description울산광역시 중구 담배소매인 지정 현황에 대한 데이터로 업소명, 업소 지번주소, 업소 도로명주소, 지정일자 등의 정보를 제공합니다.
Author울산광역시 중구
URLhttps://www.data.go.kr/data/15035619/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
순번 has unique valuesUnique

Reproduction

Analysis started2024-03-16 04:25:16.876351
Analysis finished2024-03-16 04:25:17.485760
Duration0.61 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct622
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean312.39068
Minimum1
Maximum632
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2024-03-16T13:25:17.539289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile32.05
Q1156.25
median311.5
Q3466.75
95-th percentile594.95
Maximum632
Range631
Interquartile range (IQR)310.5

Descriptive statistics

Standard deviation181.0486
Coefficient of variation (CV)0.57955828
Kurtosis-1.1828334
Mean312.39068
Median Absolute Deviation (MAD)155.5
Skewness0.019412317
Sum194307
Variance32778.596
MonotonicityNot monotonic
2024-03-16T13:25:17.643398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126 1
 
0.2%
35 1
 
0.2%
543 1
 
0.2%
453 1
 
0.2%
316 1
 
0.2%
450 1
 
0.2%
305 1
 
0.2%
280 1
 
0.2%
122 1
 
0.2%
105 1
 
0.2%
Other values (612) 612
98.4%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
632 1
0.2%
631 1
0.2%
630 1
0.2%
629 1
0.2%
628 1
0.2%
627 1
0.2%
626 1
0.2%
625 1
0.2%
624 1
0.2%
623 1
0.2%

업소명
Text

Distinct598
Distinct (%)96.1%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2024-03-16T13:25:17.892715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length17
Mean length7.255627
Min length1

Characters and Unicode

Total characters4513
Distinct characters410
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

Unique581 ?
Unique (%)93.4%

Sample

1st row(주) 한솔푸드
2nd row(주)애니원에프앤씨 굿모닝카페점
3rd row(주)코리아세븐 울산병영드림점
4th row(주)코리아세븐 울산해오름점
5th row24시간 편의점
ValueCountFrequency (%)
씨유 35
 
4.2%
세븐일레븐 26
 
3.2%
이마트24 22
 
2.7%
지에스(gs)25 20
 
2.4%
gs25 13
 
1.6%
현대홈마트 6
 
0.7%
주식회사 6
 
0.7%
미니스톱 4
 
0.5%
썬빌리지 4
 
0.5%
지에스25 4
 
0.5%
Other values (632) 684
83.0%
2024-03-16T13:25:18.279730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 222
 
4.9%
202
 
4.5%
마 155
 
3.4%
산 145
 
3.2%
트 144
 
3.2%
울 125
 
2.8%
유 92
 
2.0%
슈 92
 
2.0%
퍼 92
 
2.0%
스 91
 
2.0%
Other values (400) 3153
69.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3853
85.4%
Space Separator 202
 
4.5%
Decimal Number 190
 
4.2%
Uppercase Letter 147
 
3.3%
Close Punctuation 53
 
1.2%
Open Punctuation 53
 
1.2%
Other Punctuation 7
 
0.2%
Lowercase Letter 6
 
0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 222
 
5.8%
마 155
 
4.0%
산 145
 
3.8%
트 144
 
3.7%
울 125
 
3.2%
유 92
 
2.4%
슈 92
 
2.4%
퍼 92
 
2.4%
스 91
 
2.4%
성 79
 
2.1%
Other values (364) 2616
67.9%
Uppercase Letter
ValueCountFrequency (%)
S 50
34.0%
G 50
34.0%
C 10
 
6.8%
N 5
 
3.4%
T 4
 
2.7%
U 3
 
2.0%
B 3
 
2.0%
M 3
 
2.0%
L 3
 
2.0%
D 3
 
2.0%
Other values (9) 13
 
8.8%
Decimal Number
ValueCountFrequency (%)
2 90
47.4%
5 58
30.5%
4 31
 
16.3%
1 4
 
2.1%
0 4
 
2.1%
8 2
 
1.1%
3 1
 
0.5%
Lowercase Letter
ValueCountFrequency (%)
h 2
33.3%
e 2
33.3%
s 1
16.7%
r 1
16.7%
Other Punctuation
ValueCountFrequency (%)
& 4
57.1%
. 3
42.9%
Space Separator
ValueCountFrequency (%)
202
100.0%
Close Punctuation
ValueCountFrequency (%)
) 53
100.0%
Open Punctuation
ValueCountFrequency (%)
( 53
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3853
85.4%
Common 507
 
11.2%
Latin 153
 
3.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 222
 
5.8%
마 155
 
4.0%
산 145
 
3.8%
트 144
 
3.7%
울 125
 
3.2%
유 92
 
2.4%
슈 92
 
2.4%
퍼 92
 
2.4%
스 91
 
2.4%
성 79
 
2.1%
Other values (364) 2616
67.9%
Latin
ValueCountFrequency (%)
S 50
32.7%
G 50
32.7%
C 10
 
6.5%
N 5
 
3.3%
T 4
 
2.6%
U 3
 
2.0%
B 3
 
2.0%
M 3
 
2.0%
L 3
 
2.0%
D 3
 
2.0%
Other values (13) 19
 
12.4%
Common
ValueCountFrequency (%)
202
39.8%
2 90
17.8%
5 58
 
11.4%
) 53
 
10.5%
( 53
 
10.5%
4 31
 
6.1%
& 4
 
0.8%
1 4
 
0.8%
0 4
 
0.8%
. 3
 
0.6%
Other values (3) 5
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3853
85.4%
ASCII 660
 
14.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 222
 
5.8%
마 155
 
4.0%
산 145
 
3.8%
트 144
 
3.7%
울 125
 
3.2%
유 92
 
2.4%
슈 92
 
2.4%
퍼 92
 
2.4%
스 91
 
2.4%
성 79
 
2.1%
Other values (364) 2616
67.9%
ASCII
ValueCountFrequency (%)
202
30.6%
2 90
13.6%
5 58
 
8.8%
) 53
 
8.0%
( 53
 
8.0%
S 50
 
7.6%
G 50
 
7.6%
4 31
 
4.7%
C 10
 
1.5%
N 5
 
0.8%
Other values (26) 58
 
8.8%

업소지번주소
Text

Distinct519
Distinct (%)83.4%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2024-03-16T13:25:18.682300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length38
Mean length18.681672
Min length1

Characters and Unicode

Total characters11620
Distinct characters168
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique516 ?
Unique (%)83.0%

Sample

1st row울산광역시 중구 우정동 528번지 1호
2nd row
3rd row울산광역시 중구 남외동 346
4th row울산광역시 중구 남외동 1008-7
5th row울산광역시 중구 복산동 456-9호
ValueCountFrequency (%)
울산광역시 520
20.5%
중구 519
20.5%
반구동 74
 
2.9%
호 70
 
2.8%
태화동 65
 
2.6%
남외동 48
 
1.9%
학성동 41
 
1.6%
1호 39
 
1.5%
복산동 38
 
1.5%
성안동 37
 
1.5%
Other values (650) 1080
42.7%
2024-03-16T13:25:19.035816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2626
22.6%
구 601
 
5.2%
산 587
 
5.1%
동 550
 
4.7%
중 537
 
4.6%
울 526
 
4.5%
시 522
 
4.5%
광 520
 
4.5%
역 520
 
4.5%
1 454
 
3.9%
Other values (158) 4177
35.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6507
56.0%
Space Separator 2626
22.6%
Decimal Number 2227
 
19.2%
Dash Punctuation 207
 
1.8%
Uppercase Letter 46
 
0.4%
Other Punctuation 3
 
< 0.1%
Letter Number 1
 
< 0.1%
Lowercase Letter 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 601
9.2%
산 587
9.0%
동 550
 
8.5%
중 537
 
8.3%
울 526
 
8.1%
시 522
 
8.0%
광 520
 
8.0%
역 520
 
8.0%
호 399
 
6.1%
지 296
 
4.5%
Other values (129) 1449
22.3%
Uppercase Letter
ValueCountFrequency (%)
B 18
39.1%
N 15
32.6%
P 2
 
4.3%
A 2
 
4.3%
L 2
 
4.3%
R 1
 
2.2%
H 1
 
2.2%
I 1
 
2.2%
M 1
 
2.2%
K 1
 
2.2%
Other values (2) 2
 
4.3%
Decimal Number
ValueCountFrequency (%)
1 454
20.4%
2 273
12.3%
4 249
11.2%
3 227
10.2%
5 213
9.6%
6 179
 
8.0%
0 171
 
7.7%
7 161
 
7.2%
8 156
 
7.0%
9 144
 
6.5%
Space Separator
ValueCountFrequency (%)
2626
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 207
100.0%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6507
56.0%
Common 5065
43.6%
Latin 48
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 601
9.2%
산 587
9.0%
동 550
 
8.5%
중 537
 
8.3%
울 526
 
8.1%
시 522
 
8.0%
광 520
 
8.0%
역 520
 
8.0%
호 399
 
6.1%
지 296
 
4.5%
Other values (129) 1449
22.3%
Common
ValueCountFrequency (%)
2626
51.8%
1 454
 
9.0%
2 273
 
5.4%
4 249
 
4.9%
3 227
 
4.5%
5 213
 
4.2%
- 207
 
4.1%
6 179
 
3.5%
0 171
 
3.4%
7 161
 
3.2%
Other values (5) 305
 
6.0%
Latin
ValueCountFrequency (%)
B 18
37.5%
N 15
31.2%
P 2
 
4.2%
A 2
 
4.2%
L 2
 
4.2%
R 1
 
2.1%
Ⅱ 1
 
2.1%
H 1
 
2.1%
I 1
 
2.1%
M 1
 
2.1%
Other values (4) 4
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6507
56.0%
ASCII 5112
44.0%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2626
51.4%
1 454
 
8.9%
2 273
 
5.3%
4 249
 
4.9%
3 227
 
4.4%
5 213
 
4.2%
- 207
 
4.0%
6 179
 
3.5%
0 171
 
3.3%
7 161
 
3.1%
Other values (18) 352
 
6.9%
Hangul
ValueCountFrequency (%)
구 601
9.2%
산 587
9.0%
동 550
 
8.5%
중 537
 
8.3%
울 526
 
8.1%
시 522
 
8.0%
광 520
 
8.0%
역 520
 
8.0%
호 399
 
6.1%
지 296
 
4.5%
Other values (129) 1449
22.3%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

업소도로명주소
Text

Distinct525
Distinct (%)84.4%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2024-03-16T13:25:19.290809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length52
Mean length21.946945
Min length1

Characters and Unicode

Total characters13651
Distinct characters238
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique524 ?
Unique (%)84.2%

Sample

1st row울산광역시 중구 종가로 323. 한국에너지공단 지하1층 (우정동)
2nd row울산광역시 중구 종가로 345. 1층 (교동)
3rd row울산광역시 중구 곽남14길 19 (남외동)
4th row울산광역시 중구 해오름15길 53. 1층 (남외동)
5th row
ValueCountFrequency (%)
울산광역시 524
 
17.8%
중구 524
 
17.8%
1층 105
 
3.6%
반구동 80
 
2.7%
태화동 65
 
2.2%
남외동 42
 
1.4%
성안동 40
 
1.4%
학성동 37
 
1.3%
우정동 36
 
1.2%
성남동 33
 
1.1%
Other values (621) 1465
49.6%
2024-03-16T13:25:19.693065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2639
19.3%
구 667
 
4.9%
산 620
 
4.5%
1 617
 
4.5%
동 604
 
4.4%
중 544
 
4.0%
시 534
 
3.9%
울 532
 
3.9%
역 531
 
3.9%
) 527
 
3.9%
Other values (228) 5836
42.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7705
56.4%
Space Separator 2639
 
19.3%
Decimal Number 1933
 
14.2%
Close Punctuation 527
 
3.9%
Open Punctuation 527
 
3.9%
Other Punctuation 250
 
1.8%
Dash Punctuation 45
 
0.3%
Uppercase Letter 19
 
0.1%
Lowercase Letter 4
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 667
 
8.7%
산 620
 
8.0%
동 604
 
7.8%
중 544
 
7.1%
시 534
 
6.9%
울 532
 
6.9%
역 531
 
6.9%
광 524
 
6.8%
길 311
 
4.0%
로 198
 
2.6%
Other values (194) 2640
34.3%
Uppercase Letter
ValueCountFrequency (%)
A 3
15.8%
P 2
10.5%
B 2
10.5%
I 2
10.5%
H 2
10.5%
L 2
10.5%
M 1
 
5.3%
K 1
 
5.3%
S 1
 
5.3%
R 1
 
5.3%
Other values (2) 2
10.5%
Decimal Number
ValueCountFrequency (%)
1 617
31.9%
2 245
 
12.7%
0 193
 
10.0%
3 191
 
9.9%
4 150
 
7.8%
5 145
 
7.5%
6 121
 
6.3%
7 97
 
5.0%
8 88
 
4.6%
9 86
 
4.4%
Lowercase Letter
ValueCountFrequency (%)
v 1
25.0%
g 1
25.0%
c 1
25.0%
e 1
25.0%
Other Punctuation
ValueCountFrequency (%)
. 249
99.6%
/ 1
 
0.4%
Space Separator
ValueCountFrequency (%)
2639
100.0%
Close Punctuation
ValueCountFrequency (%)
) 527
100.0%
Open Punctuation
ValueCountFrequency (%)
( 527
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 45
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7705
56.4%
Common 5922
43.4%
Latin 24
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 667
 
8.7%
산 620
 
8.0%
동 604
 
7.8%
중 544
 
7.1%
시 534
 
6.9%
울 532
 
6.9%
역 531
 
6.9%
광 524
 
6.8%
길 311
 
4.0%
로 198
 
2.6%
Other values (194) 2640
34.3%
Common
ValueCountFrequency (%)
2639
44.6%
1 617
 
10.4%
) 527
 
8.9%
( 527
 
8.9%
. 249
 
4.2%
2 245
 
4.1%
0 193
 
3.3%
3 191
 
3.2%
4 150
 
2.5%
5 145
 
2.4%
Other values (7) 439
 
7.4%
Latin
ValueCountFrequency (%)
A 3
12.5%
P 2
 
8.3%
B 2
 
8.3%
I 2
 
8.3%
H 2
 
8.3%
L 2
 
8.3%
M 1
 
4.2%
v 1
 
4.2%
g 1
 
4.2%
c 1
 
4.2%
Other values (7) 7
29.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7705
56.4%
ASCII 5945
43.5%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2639
44.4%
1 617
 
10.4%
) 527
 
8.9%
( 527
 
8.9%
. 249
 
4.2%
2 245
 
4.1%
0 193
 
3.2%
3 191
 
3.2%
4 150
 
2.5%
5 145
 
2.4%
Other values (23) 462
 
7.8%
Hangul
ValueCountFrequency (%)
구 667
 
8.7%
산 620
 
8.0%
동 604
 
7.8%
중 544
 
7.1%
시 534
 
6.9%
울 532
 
6.9%
역 531
 
6.9%
광 524
 
6.8%
길 311
 
4.0%
로 198
 
2.6%
Other values (194) 2640
34.3%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

지정일자
Text

Distinct531
Distinct (%)85.4%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2024-03-16T13:25:19.910043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters6220
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

Unique490 ?
Unique (%)78.8%

Sample

1st row2020-03-05
2nd row2014-06-13
3rd row2021-02-09
4th row2023-01-16
5th row1994-06-23
ValueCountFrequency (%)
1994-06-23 46
 
7.4%
2017-04-14 4
 
0.6%
2017-06-12 3
 
0.5%
2019-04-09 3
 
0.5%
2021-05-04 3
 
0.5%
2020-03-05 3
 
0.5%
2019-10-02 2
 
0.3%
2001-07-23 2
 
0.3%
2020-01-02 2
 
0.3%
2009-05-25 2
 
0.3%
Other values (521) 552
88.7%
2024-03-16T13:25:20.229500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1464
23.5%
- 1244
20.0%
2 1091
17.5%
1 946
15.2%
9 352
 
5.7%
4 222
 
3.6%
3 213
 
3.4%
6 203
 
3.3%
8 180
 
2.9%
7 155
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4976
80.0%
Dash Punctuation 1244
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1464
29.4%
2 1091
21.9%
1 946
19.0%
9 352
 
7.1%
4 222
 
4.5%
3 213
 
4.3%
6 203
 
4.1%
8 180
 
3.6%
7 155
 
3.1%
5 150
 
3.0%
Dash Punctuation
ValueCountFrequency (%)
- 1244
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6220
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1464
23.5%
- 1244
20.0%
2 1091
17.5%
1 946
15.2%
9 352
 
5.7%
4 222
 
3.6%
3 213
 
3.4%
6 203
 
3.3%
8 180
 
2.9%
7 155
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6220
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1464
23.5%
- 1244
20.0%
2 1091
17.5%
1 946
15.2%
9 352
 
5.7%
4 222
 
3.6%
3 213
 
3.4%
6 203
 
3.3%
8 180
 
2.9%
7 155
 
2.5%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
Minimum2024-03-11 00:00:00
Maximum2024-03-11 00:00:00
2024-03-16T13:25:20.344388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:25:20.427352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-03-16T13:25:17.243541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2024-03-16T13:25:17.360144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-16T13:25:17.454119image/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

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0126(주) 한솔푸드울산광역시 중구 우정동 528번지 1호울산광역시 중구 종가로 323. 한국에너지공단 지하1층 (우정동)2020-03-052024-03-11
1313(주)애니원에프앤씨 굿모닝카페점울산광역시 중구 종가로 345. 1층 (교동)2014-06-132024-03-11
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32(주)코리아세븐 울산해오름점울산광역시 중구 남외동 1008-7울산광역시 중구 해오름15길 53. 1층 (남외동)2023-01-162024-03-11
461624시간 편의점울산광역시 중구 복산동 456-9호1994-06-232024-03-11
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618488통신울산광역시 중구 성남동 226번지 19호울산광역시 중구 학성로 68. 1층 (성남동)2018-09-202024-03-11
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612334홍일할인마트울산광역시 중구 동동 116번지 9호울산광역시 중구 산전5길 17 (동동)2013-05-022024-03-11
613510화수분슈퍼울산광역시 중구 동동 65-20번지울산광역시 중구 병영16길 30 (동동)2000-02-032024-03-11
614428화인유통울산광역시 중구 학성동 156번지 21 호울산광역시 중구 옥교14길 24 (학성동)2006-05-192024-03-11
615530활주로낚시울산광역시 중구 서동 55-1호1998-08-072024-03-11
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619620효동상회울산광역시 중구 복산동 311-6호1994-06-232024-03-11
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