Overview

Dataset statistics

Number of variables8
Number of observations24
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.7 KiB
Average record size in memory71.5 B

Variable types

Numeric2
Categorical1
Text3
DateTime1
Boolean1

Dataset

Description매장면적 3,000제곱미터 이상의 상업시설을 개설하고자 하는 자는소관 지방자치단체에 대규모점포 개설등록 신청을 하고 허가를 받아야 함
Author부산광역시 해운대구
URLhttps://www.data.go.kr/data/15077764/fileData.do

Alerts

연번 is highly overall correlated with 매장면적(제곱미터) and 1 other fieldsHigh correlation
매장면적(제곱미터) is highly overall correlated with 연번High correlation
구분 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
전통상업보존구역해당여부 is highly overall correlated with 구분High correlation
연번 has unique valuesUnique
시설명 has unique valuesUnique
매장면적(제곱미터) has unique valuesUnique
연락처 has unique valuesUnique
허가일(인가-사업개시 등) has unique valuesUnique

Reproduction

Analysis started2024-03-23 06:57:29.570212
Analysis finished2024-03-23 06:57:33.179357
Duration3.61 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.5
Minimum1
Maximum24
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2024-03-23T06:57:33.480669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.15
Q16.75
median12.5
Q318.25
95-th percentile22.85
Maximum24
Range23
Interquartile range (IQR)11.5

Descriptive statistics

Standard deviation7.0710678
Coefficient of variation (CV)0.56568542
Kurtosis-1.2
Mean12.5
Median Absolute Deviation (MAD)6
Skewness0
Sum300
Variance50
MonotonicityStrictly increasing
2024-03-23T06:57:33.991524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1 1
 
4.2%
14 1
 
4.2%
24 1
 
4.2%
23 1
 
4.2%
22 1
 
4.2%
21 1
 
4.2%
20 1
 
4.2%
19 1
 
4.2%
18 1
 
4.2%
17 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
1 1
4.2%
2 1
4.2%
3 1
4.2%
4 1
4.2%
5 1
4.2%
6 1
4.2%
7 1
4.2%
8 1
4.2%
9 1
4.2%
10 1
4.2%
ValueCountFrequency (%)
24 1
4.2%
23 1
4.2%
22 1
4.2%
21 1
4.2%
20 1
4.2%
19 1
4.2%
18 1
4.2%
17 1
4.2%
16 1
4.2%
15 1
4.2%

구분
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)20.8%
Missing0
Missing (%)0.0%
Memory size324.0 B
준대규모점포
12 
그밖의 대규모점포
4 
대형마트
3 
백화점
3 
쇼핑센터
2 

Length

Max length9
Median length7.5
Mean length5.7083333
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대형마트
2nd row대형마트
3rd row대형마트
4th row백화점
5th row백화점

Common Values

ValueCountFrequency (%)
준대규모점포 12
50.0%
그밖의 대규모점포 4
 
16.7%
대형마트 3
 
12.5%
백화점 3
 
12.5%
쇼핑센터 2
 
8.3%

Length

2024-03-23T06:57:34.755122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T06:57:35.192606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
준대규모점포 12
42.9%
그밖의 4
 
14.3%
대규모점포 4
 
14.3%
대형마트 3
 
10.7%
백화점 3
 
10.7%
쇼핑센터 2
 
7.1%

시설명
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2024-03-23T06:57:35.924067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length13
Mean length11.291667
Min length5

Characters and Unicode

Total characters271
Distinct characters71
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)100.0%

Sample

1st row이마트 해운대점
2nd row홈플러스 센텀시티점
3rd row홈플러스 부산반여점
4th row롯데백화점 센텀시티점
5th row신세계백화점 센텀시티점
ValueCountFrequency (%)
the 4
 
8.0%
센텀시티점 4
 
8.0%
fresh 4
 
8.0%
gs 4
 
8.0%
해운대점 3
 
6.0%
탑마트 3
 
6.0%
홈플러스 2
 
4.0%
부산반여점 2
 
4.0%
해운대동부점 1
 
2.0%
대동점 1
 
2.0%
Other values (22) 22
44.0%
2024-03-23T06:57:37.403937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
28
 
10.3%
점 21
 
7.7%
스 16
 
5.9%
대 8
 
3.0%
H 8
 
3.0%
S 8
 
3.0%
E 8
 
3.0%
운 8
 
3.0%
해 7
 
2.6%
홈 6
 
2.2%
Other values (61) 153
56.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 199
73.4%
Uppercase Letter 42
 
15.5%
Space Separator 28
 
10.3%
Decimal Number 1
 
0.4%
Other Symbol 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 21
 
10.6%
스 16
 
8.0%
대 8
 
4.0%
운 8
 
4.0%
해 7
 
3.5%
홈 6
 
3.0%
플 6
 
3.0%
러 6
 
3.0%
센 6
 
3.0%
텀 6
 
3.0%
Other values (49) 109
54.8%
Uppercase Letter
ValueCountFrequency (%)
H 8
19.0%
S 8
19.0%
E 8
19.0%
F 4
9.5%
R 4
9.5%
T 4
9.5%
G 4
9.5%
N 1
 
2.4%
C 1
 
2.4%
Space Separator
ValueCountFrequency (%)
28
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 200
73.8%
Latin 42
 
15.5%
Common 29
 
10.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 21
 
10.5%
스 16
 
8.0%
대 8
 
4.0%
운 8
 
4.0%
해 7
 
3.5%
홈 6
 
3.0%
플 6
 
3.0%
러 6
 
3.0%
센 6
 
3.0%
텀 6
 
3.0%
Other values (50) 110
55.0%
Latin
ValueCountFrequency (%)
H 8
19.0%
S 8
19.0%
E 8
19.0%
F 4
9.5%
R 4
9.5%
T 4
9.5%
G 4
9.5%
N 1
 
2.4%
C 1
 
2.4%
Common
ValueCountFrequency (%)
28
96.6%
2 1
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 199
73.4%
ASCII 71
 
26.2%
None 1
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
28
39.4%
H 8
 
11.3%
S 8
 
11.3%
E 8
 
11.3%
F 4
 
5.6%
R 4
 
5.6%
T 4
 
5.6%
G 4
 
5.6%
2 1
 
1.4%
N 1
 
1.4%
Hangul
ValueCountFrequency (%)
점 21
 
10.6%
스 16
 
8.0%
대 8
 
4.0%
운 8
 
4.0%
해 7
 
3.5%
홈 6
 
3.0%
플 6
 
3.0%
러 6
 
3.0%
센 6
 
3.0%
텀 6
 
3.0%
Other values (49) 109
54.8%
None
ValueCountFrequency (%)
㈜ 1
100.0%

소재지
Text

Distinct23
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Memory size324.0 B
2024-03-23T06:57:38.283465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length28.5
Mean length24.791667
Min length17

Characters and Unicode

Total characters595
Distinct characters68
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

Unique22 ?
Unique (%)91.7%

Sample

1st row부산광역시 해운대구 좌동순환로 511(중동)
2nd row부산광역시 해운대구 센텀동로 6
3rd row부산광역시 해운대구 선수촌로21번길 37(반여동)
4th row부산광역시 해운대구 센텀남대로 59(우동)
5th row부산광역시 해운대구 센텀남대로 35(우동)
ValueCountFrequency (%)
부산광역시 24
23.8%
해운대구 14
 
13.9%
좌동순환로 5
 
5.0%
반여동 2
 
2.0%
좌동 2
 
2.0%
센텀중앙로 2
 
2.0%
145 2
 
2.0%
세실로 2
 
2.0%
선수촌로 2
 
2.0%
1층 2
 
2.0%
Other values (42) 44
43.6%
2024-03-23T06:57:39.676197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
77
 
12.9%
동 33
 
5.5%
시 25
 
4.2%
부 24
 
4.0%
광 24
 
4.0%
역 24
 
4.0%
산 24
 
4.0%
로 23
 
3.9%
( 22
 
3.7%
) 22
 
3.7%
Other values (58) 297
49.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 375
63.0%
Decimal Number 86
 
14.5%
Space Separator 77
 
12.9%
Open Punctuation 22
 
3.7%
Close Punctuation 22
 
3.7%
Other Punctuation 12
 
2.0%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 33
 
8.8%
시 25
 
6.7%
부 24
 
6.4%
광 24
 
6.4%
역 24
 
6.4%
산 24
 
6.4%
로 23
 
6.1%
대 19
 
5.1%
운 16
 
4.3%
구 15
 
4.0%
Other values (43) 148
39.5%
Decimal Number
ValueCountFrequency (%)
1 21
24.4%
3 16
18.6%
2 9
10.5%
5 8
 
9.3%
0 8
 
9.3%
7 6
 
7.0%
8 5
 
5.8%
9 5
 
5.8%
4 5
 
5.8%
6 3
 
3.5%
Space Separator
ValueCountFrequency (%)
77
100.0%
Open Punctuation
ValueCountFrequency (%)
( 22
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%
Other Punctuation
ValueCountFrequency (%)
, 12
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 375
63.0%
Common 220
37.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 33
 
8.8%
시 25
 
6.7%
부 24
 
6.4%
광 24
 
6.4%
역 24
 
6.4%
산 24
 
6.4%
로 23
 
6.1%
대 19
 
5.1%
운 16
 
4.3%
구 15
 
4.0%
Other values (43) 148
39.5%
Common
ValueCountFrequency (%)
77
35.0%
( 22
 
10.0%
) 22
 
10.0%
1 21
 
9.5%
3 16
 
7.3%
, 12
 
5.5%
2 9
 
4.1%
5 8
 
3.6%
0 8
 
3.6%
7 6
 
2.7%
Other values (5) 19
 
8.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 375
63.0%
ASCII 220
37.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
77
35.0%
( 22
 
10.0%
) 22
 
10.0%
1 21
 
9.5%
3 16
 
7.3%
, 12
 
5.5%
2 9
 
4.1%
5 8
 
3.6%
0 8
 
3.6%
7 6
 
2.7%
Other values (5) 19
 
8.6%
Hangul
ValueCountFrequency (%)
동 33
 
8.8%
시 25
 
6.7%
부 24
 
6.4%
광 24
 
6.4%
역 24
 
6.4%
산 24
 
6.4%
로 23
 
6.1%
대 19
 
5.1%
운 16
 
4.3%
구 15
 
4.0%
Other values (43) 148
39.5%

매장면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13933.05
Minimum177.21
Maximum139892
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2024-03-23T06:57:40.268178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum177.21
5-th percentile191.8
Q1384.75
median3056.5
Q316736
95-th percentile33178.65
Maximum139892
Range139714.79
Interquartile range (IQR)16351.25

Descriptive statistics

Standard deviation28804.115
Coefficient of variation (CV)2.067323
Kurtosis17.266967
Mean13933.05
Median Absolute Deviation (MAD)2860.5
Skewness3.9370497
Sum334393.21
Variance8.2967705 × 108
MonotonicityNot monotonic
2024-03-23T06:57:41.036802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
11193.0 1
 
4.2%
360.0 1
 
4.2%
1954.0 1
 
4.2%
1524.0 1
 
4.2%
1498.0 1
 
4.2%
990.0 1
 
4.2%
393.0 1
 
4.2%
209.0 1
 
4.2%
202.0 1
 
4.2%
190.0 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
177.21 1
4.2%
190.0 1
4.2%
202.0 1
4.2%
209.0 1
4.2%
212.0 1
4.2%
360.0 1
4.2%
393.0 1
4.2%
541.0 1
4.2%
990.0 1
4.2%
1498.0 1
4.2%
ValueCountFrequency (%)
139892.0 1
4.2%
33738.0 1
4.2%
30009.0 1
4.2%
28555.0 1
4.2%
17827.0 1
4.2%
17471.0 1
4.2%
16491.0 1
4.2%
11992.0 1
4.2%
11193.0 1
4.2%
10277.0 1
4.2%

연락처
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2024-03-23T06:57:41.678495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.875
Min length9

Characters and Unicode

Total characters285
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

Unique24 ?
Unique (%)100.0%

Sample

1st row051-608-1052
2nd row051-709-8123
3rd row051-509-8124
4th row051-730-2220
5th row1588-1234
ValueCountFrequency (%)
051-608-1052 1
 
4.2%
051-709-8123 1
 
4.2%
051-525-0422 1
 
4.2%
051-704-9009 1
 
4.2%
051-710-2533 1
 
4.2%
051-746-8547 1
 
4.2%
051-702-8540 1
 
4.2%
051-701-8545 1
 
4.2%
051-747-8365 1
 
4.2%
051-703-7666 1
 
4.2%
Other values (14) 14
58.3%
2024-03-23T06:57:42.742834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 54
18.9%
- 47
16.5%
5 39
13.7%
1 38
13.3%
7 27
9.5%
4 22
7.7%
2 17
 
6.0%
3 13
 
4.6%
8 12
 
4.2%
6 8
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 238
83.5%
Dash Punctuation 47
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 54
22.7%
5 39
16.4%
1 38
16.0%
7 27
11.3%
4 22
9.2%
2 17
 
7.1%
3 13
 
5.5%
8 12
 
5.0%
6 8
 
3.4%
9 8
 
3.4%
Dash Punctuation
ValueCountFrequency (%)
- 47
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 285
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 54
18.9%
- 47
16.5%
5 39
13.7%
1 38
13.3%
7 27
9.5%
4 22
7.7%
2 17
 
6.0%
3 13
 
4.6%
8 12
 
4.2%
6 8
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 285
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 54
18.9%
- 47
16.5%
5 39
13.7%
1 38
13.3%
7 27
9.5%
4 22
7.7%
2 17
 
6.0%
3 13
 
4.6%
8 12
 
4.2%
6 8
 
2.8%

허가일(인가-사업개시 등)
Date

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
Minimum1994-04-26 00:00:00
Maximum2023-12-09 00:00:00
2024-03-23T06:57:43.363626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:57:43.886065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)

전통상업보존구역해당여부
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size156.0 B
True
20 
False
4 
ValueCountFrequency (%)
True 20
83.3%
False 4
 
16.7%
2024-03-23T06:57:44.413578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Interactions

2024-03-23T06:57:31.369912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:57:30.616083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:57:31.719941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:57:30.980714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T06:57:44.660276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구분시설명소재지매장면적(제곱미터)연락처허가일(인가-사업개시 등)전통상업보존구역해당여부
연번1.0000.9791.0000.9190.3781.0001.0000.451
구분0.9791.0001.0001.0000.5501.0001.0000.522
시설명1.0001.0001.0001.0001.0001.0001.0001.000
소재지0.9191.0001.0001.0001.0001.0001.0001.000
매장면적(제곱미터)0.3780.5501.0001.0001.0001.0001.0000.000
연락처1.0001.0001.0001.0001.0001.0001.0001.000
허가일(인가-사업개시 등)1.0001.0001.0001.0001.0001.0001.0001.000
전통상업보존구역해당여부0.4510.5221.0001.0000.0001.0001.0001.000
2024-03-23T06:57:45.116854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분전통상업보존구역해당여부
구분1.0000.584
전통상업보존구역해당여부0.5841.000
2024-03-23T06:57:45.483878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번매장면적(제곱미터)구분전통상업보존구역해당여부
연번1.000-0.6850.6780.248
매장면적(제곱미터)-0.6851.0000.4690.000
구분0.6780.4691.0000.584
전통상업보존구역해당여부0.2480.0000.5841.000

Missing values

2024-03-23T06:57:32.350156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T06:57:32.981082image/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

연번구분시설명소재지매장면적(제곱미터)연락처허가일(인가-사업개시 등)전통상업보존구역해당여부
01대형마트이마트 해운대점부산광역시 해운대구 좌동순환로 511(중동)11193.0051-608-10522000-03-08Y
12대형마트홈플러스 센텀시티점부산광역시 해운대구 센텀동로 617827.0051-709-81232002-04-12Y
23대형마트홈플러스 부산반여점부산광역시 해운대구 선수촌로21번길 37(반여동)10277.0051-509-81242012-03-16Y
34백화점롯데백화점 센텀시티점부산광역시 해운대구 센텀남대로 59(우동)33738.0051-730-22202007-10-31Y
45백화점신세계백화점 센텀시티점부산광역시 해운대구 센텀남대로 35(우동)139892.01588-12342009-02-28Y
56백화점NC백화점 해운대점부산광역시 해운대구 해운대로 813(좌동)30009.0051-709-56072006-01-23Y
67쇼핑센터㈜세이브존 리베라부산광역시 해운대구 구남로 29번길 21(중동)16491.0051-740-90001994-04-26Y
78쇼핑센터화목데파트부산광역시 해운대구 세실로 64(좌동)4159.0051-702-37031999-03-02Y
89그밖의 대규모점포제니스스퀘어부산광역시 해운대구 마린시티2로 33(우동)17471.0051-747-76232012-03-21N
910그밖의 대규모점포해운대로데오아울렛부산광역시 해운대구 좌동순환로 473(중동)4539.0051-743-22342002-06-14N
연번구분시설명소재지매장면적(제곱미터)연락처허가일(인가-사업개시 등)전통상업보존구역해당여부
1415준대규모점포GS THE FRESH 센텀시티점부산광역시 해운대구 센텀2로19, 센텀코아102호(우동,센텀코아)177.21051-744-59472022-05-22Y
1516준대규모점포GS THE FRESH 해운대동부점부산광역시 해운대구 세실로158,상가동103호212.0051-703-76662023-12-09Y
1617준대규모점포홈플러스익스프레스좌동점부산광역시 좌동순환로 78, 1층 (좌동,건우빌딩)190.0051-747-83652006-11-27Y
1718준대규모점포홈플러스익스프레스좌동2점부산광역시 세실로 33, 1층 (좌동)202.0051-701-85452009-02-02Y
1819준대규모점포홈플러스익스프레스부산좌산점부산광역시 좌동순환로 303 (좌동)209.0051-702-85402010-11-03Y
1920준대규모점포홈플러스익스프레스부산센텀점부산광역시 센텀중앙로 145, 제상가7동 101호 (재송동,센텀파크1차)393.0051-746-85472010-09-15Y
2021준대규모점포이마트에브리데이 부산반여점부산광역시 선수촌로 65-7 (반여동)990.0051-710-25332008-12-29Y
2122준대규모점포탑마트 해운대점부산광역시 좌동로 38 (중동)1498.0051-704-90092008-06-20Y
2223준대규모점포탑마트 반여점부산광역시 선수촌로 119 (반여동)1524.0051-525-04221998-11-27N
2324준대규모점포탑마트 반송점부산광역시 윗반송로 8 (반송동)1954.0051-545-32002004-09-16Y