Overview

Dataset statistics

Number of variables7
Number of observations10000
Missing cells9034
Missing cells (%)12.9%
Duplicate rows123
Duplicate rows (%)1.2%
Total size in memory644.5 KiB
Average record size in memory66.0 B

Variable types

Text3
Categorical2
Numeric2

Dataset

Description부산광역시부산진구_U옥외광고물정보_20230905
Author부산광역시 부산진구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15066405

Alerts

시도 has constant value ""Constant
구군 has constant value ""Constant
Dataset has 123 (1.2%) duplicate rowsDuplicates
표시위치 has 271 (2.7%) missing valuesMissing
건물번호 has 271 (2.7%) missing valuesMissing
건물번호2 has 8492 (84.9%) missing valuesMissing

Reproduction

Analysis started2023-12-10 17:04:32.344277
Analysis finished2023-12-10 17:04:35.023802
Duration2.68 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

Distinct6267
Distinct (%)62.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T02:04:35.341053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length20
Mean length6.184
Min length1

Characters and Unicode

Total characters61840
Distinct characters992
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3773 ?
Unique (%)37.7%

Sample

1st row디저트39
2nd row시즈원PC
3rd row성안교회주차장
4th row해법영수과학원
5th rowThe아이스크림
ValueCountFrequency (%)
coffee 39
 
0.4%
gs25 23
 
0.2%
cu 20
 
0.2%
the 19
 
0.2%
pc 18
 
0.2%
파리바게뜨 15
 
0.1%
주)비지에프리테일 15
 
0.1%
부산본점 14
 
0.1%
초읍점 14
 
0.1%
cafe 13
 
0.1%
Other values (6507) 10646
98.2%
2023-12-11T02:04:36.067579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 1130
 
1.8%
이 944
 
1.5%
리 895
 
1.4%
어 876
 
1.4%
스 847
 
1.4%
836
 
1.4%
동 757
 
1.2%
부 722
 
1.2%
산 704
 
1.1%
점 668
 
1.1%
Other values (982) 53461
86.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 53343
86.3%
Uppercase Letter 4538
 
7.3%
Lowercase Letter 1770
 
2.9%
Space Separator 836
 
1.4%
Decimal Number 640
 
1.0%
Other Punctuation 224
 
0.4%
Close Punctuation 223
 
0.4%
Open Punctuation 221
 
0.4%
Dash Punctuation 15
 
< 0.1%
Math Symbol 13
 
< 0.1%
Other values (2) 17
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 1130
 
2.1%
이 944
 
1.8%
리 895
 
1.7%
어 876
 
1.6%
스 847
 
1.6%
동 757
 
1.4%
부 722
 
1.4%
산 704
 
1.3%
점 668
 
1.3%
가 659
 
1.2%
Other values (897) 45141
84.6%
Uppercase Letter
ValueCountFrequency (%)
E 499
 
11.0%
O 370
 
8.2%
C 311
 
6.9%
S 308
 
6.8%
A 305
 
6.7%
T 259
 
5.7%
N 240
 
5.3%
I 236
 
5.2%
L 212
 
4.7%
R 193
 
4.3%
Other values (16) 1605
35.4%
Lowercase Letter
ValueCountFrequency (%)
e 238
13.4%
o 179
 
10.1%
a 174
 
9.8%
i 121
 
6.8%
n 120
 
6.8%
c 102
 
5.8%
r 96
 
5.4%
s 95
 
5.4%
l 84
 
4.7%
t 79
 
4.5%
Other values (15) 482
27.2%
Other Punctuation
ValueCountFrequency (%)
& 81
36.2%
. 68
30.4%
, 20
 
8.9%
# 19
 
8.5%
! 8
 
3.6%
: 8
 
3.6%
/ 7
 
3.1%
% 5
 
2.2%
? 3
 
1.3%
; 2
 
0.9%
Other values (2) 3
 
1.3%
Decimal Number
ValueCountFrequency (%)
2 170
26.6%
5 95
14.8%
1 93
14.5%
0 72
11.2%
4 61
 
9.5%
3 46
 
7.2%
8 32
 
5.0%
9 27
 
4.2%
6 22
 
3.4%
7 22
 
3.4%
Math Symbol
ValueCountFrequency (%)
+ 10
76.9%
| 2
 
15.4%
~ 1
 
7.7%
Close Punctuation
ValueCountFrequency (%)
) 216
96.9%
] 7
 
3.1%
Open Punctuation
ValueCountFrequency (%)
( 214
96.8%
[ 7
 
3.2%
Other Symbol
ValueCountFrequency (%)
● 6
60.0%
㈜ 4
40.0%
Space Separator
ValueCountFrequency (%)
836
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 53259
86.1%
Latin 6308
 
10.2%
Common 2185
 
3.5%
Han 88
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 1130
 
2.1%
이 944
 
1.8%
리 895
 
1.7%
어 876
 
1.6%
스 847
 
1.6%
동 757
 
1.4%
부 722
 
1.4%
산 704
 
1.3%
점 668
 
1.3%
가 659
 
1.2%
Other values (865) 45057
84.6%
Latin
ValueCountFrequency (%)
E 499
 
7.9%
O 370
 
5.9%
C 311
 
4.9%
S 308
 
4.9%
A 305
 
4.8%
T 259
 
4.1%
N 240
 
3.8%
e 238
 
3.8%
I 236
 
3.7%
L 212
 
3.4%
Other values (41) 3330
52.8%
Common
ValueCountFrequency (%)
836
38.3%
) 216
 
9.9%
( 214
 
9.8%
2 170
 
7.8%
5 95
 
4.3%
1 93
 
4.3%
& 81
 
3.7%
0 72
 
3.3%
. 68
 
3.1%
4 61
 
2.8%
Other values (23) 279
 
12.8%
Han
ValueCountFrequency (%)
家 15
17.0%
美 9
 
10.2%
生 6
 
6.8%
秀 6
 
6.8%
大 6
 
6.8%
水 4
 
4.5%
人 4
 
4.5%
眞 3
 
3.4%
本 3
 
3.4%
酒 3
 
3.4%
Other values (23) 29
33.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 53243
86.1%
ASCII 8487
 
13.7%
CJK 87
 
0.1%
Compat Jamo 12
 
< 0.1%
Geometric Shapes 6
 
< 0.1%
None 4
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 1130
 
2.1%
이 944
 
1.8%
리 895
 
1.7%
어 876
 
1.6%
스 847
 
1.6%
동 757
 
1.4%
부 722
 
1.4%
산 704
 
1.3%
점 668
 
1.3%
가 659
 
1.2%
Other values (859) 45041
84.6%
ASCII
ValueCountFrequency (%)
836
 
9.9%
E 499
 
5.9%
O 370
 
4.4%
C 311
 
3.7%
S 308
 
3.6%
A 305
 
3.6%
T 259
 
3.1%
N 240
 
2.8%
e 238
 
2.8%
I 236
 
2.8%
Other values (73) 4885
57.6%
CJK
ValueCountFrequency (%)
家 15
17.2%
美 9
 
10.3%
生 6
 
6.9%
秀 6
 
6.9%
大 6
 
6.9%
水 4
 
4.6%
人 4
 
4.6%
眞 3
 
3.4%
本 3
 
3.4%
酒 3
 
3.4%
Other values (22) 28
32.2%
Geometric Shapes
ValueCountFrequency (%)
● 6
100.0%
None
ValueCountFrequency (%)
㈜ 4
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅇ 4
33.3%
ㅅ 2
16.7%
ㅋ 2
16.7%
ㄹ 2
16.7%
ㅡ 2
16.7%
CJK Compat Ideographs
ValueCountFrequency (%)
龍 1
100.0%

규격2
Text

Distinct2654
Distinct (%)26.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T02:04:36.604891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length24
Mean length6.6865
Min length3

Characters and Unicode

Total characters66865
Distinct characters24
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1568 ?
Unique (%)15.7%

Sample

1st row3*0.7
2nd row0.8*1.3*5.6
3rd row0.8*0.8*4
4th row1.90*0.8
5th row7.2*1.2
ValueCountFrequency (%)
0.8*3 149
 
1.5%
4*1 122
 
1.2%
3*1 97
 
1.0%
3.5*1 81
 
0.8%
5*1 79
 
0.8%
6*1 72
 
0.7%
4.5*1 67
 
0.7%
0.6*0.6*2 63
 
0.6%
3*0.8 61
 
0.6%
4*0.8 57
 
0.6%
Other values (2647) 9175
91.5%
2023-12-11T02:04:37.367036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 15611
23.3%
* 12331
18.4%
0 7379
11.0%
1 5826
 
8.7%
5 4734
 
7.1%
2 4500
 
6.7%
8 4097
 
6.1%
3 3706
 
5.5%
4 3171
 
4.7%
6 2526
 
3.8%
Other values (14) 2984
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 38792
58.0%
Other Punctuation 27982
41.8%
Other Letter 47
 
0.1%
Space Separator 40
 
0.1%
Open Punctuation 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7379
19.0%
1 5826
15.0%
5 4734
12.2%
2 4500
11.6%
8 4097
10.6%
3 3706
9.6%
4 3171
8.2%
6 2526
 
6.5%
7 1814
 
4.7%
9 1039
 
2.7%
Other Letter
ValueCountFrequency (%)
이 17
36.2%
높 17
36.2%
양 3
 
6.4%
성 3
 
6.4%
화 3
 
6.4%
추 2
 
4.3%
진 2
 
4.3%
Other Punctuation
ValueCountFrequency (%)
. 15611
55.8%
* 12331
44.1%
: 20
 
0.1%
, 20
 
0.1%
Space Separator
ValueCountFrequency (%)
40
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 66818
99.9%
Hangul 47
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 15611
23.4%
* 12331
18.5%
0 7379
11.0%
1 5826
 
8.7%
5 4734
 
7.1%
2 4500
 
6.7%
8 4097
 
6.1%
3 3706
 
5.5%
4 3171
 
4.7%
6 2526
 
3.8%
Other values (7) 2937
 
4.4%
Hangul
ValueCountFrequency (%)
이 17
36.2%
높 17
36.2%
양 3
 
6.4%
성 3
 
6.4%
화 3
 
6.4%
추 2
 
4.3%
진 2
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 66818
99.9%
Hangul 47
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 15611
23.4%
* 12331
18.5%
0 7379
11.0%
1 5826
 
8.7%
5 4734
 
7.1%
2 4500
 
6.7%
8 4097
 
6.1%
3 3706
 
5.5%
4 3171
 
4.7%
6 2526
 
3.8%
Other values (7) 2937
 
4.4%
Hangul
ValueCountFrequency (%)
이 17
36.2%
높 17
36.2%
양 3
 
6.4%
성 3
 
6.4%
화 3
 
6.4%
추 2
 
4.3%
진 2
 
4.3%

표시위치
Text

MISSING 

Distinct250
Distinct (%)2.6%
Missing271
Missing (%)2.7%
Memory size156.2 KiB
2023-12-11T02:04:37.804030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length5.2458629
Min length3

Characters and Unicode

Total characters51037
Distinct characters65
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)0.2%

Sample

1st row새싹로
2nd row당감로64번길
3rd row가야대로507번길
4th row가야대로
5th row백양산로53번길
ValueCountFrequency (%)
가야대로 929
 
9.5%
새싹로 669
 
6.9%
동평로 609
 
6.3%
엄광로 510
 
5.2%
성지로 457
 
4.7%
백양대로 337
 
3.5%
당감로 329
 
3.4%
백양순환로 298
 
3.1%
대학로 296
 
3.0%
당감서로 288
 
3.0%
Other values (240) 5007
51.5%
2023-12-11T02:04:38.534077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 9729
19.1%
길 3508
 
6.9%
번 3508
 
6.9%
대 2822
 
5.5%
가 2003
 
3.9%
야 1938
 
3.8%
백 1498
 
2.9%
양 1498
 
2.9%
지 1310
 
2.6%
1 1296
 
2.5%
Other values (55) 21927
43.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 42284
82.8%
Decimal Number 8753
 
17.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 9729
23.0%
길 3508
 
8.3%
번 3508
 
8.3%
대 2822
 
6.7%
가 2003
 
4.7%
야 1938
 
4.6%
백 1498
 
3.5%
양 1498
 
3.5%
지 1310
 
3.1%
동 1292
 
3.1%
Other values (45) 13178
31.2%
Decimal Number
ValueCountFrequency (%)
1 1296
14.8%
4 1130
12.9%
3 1102
12.6%
2 1065
12.2%
5 911
10.4%
8 821
9.4%
7 799
9.1%
0 684
7.8%
6 530
6.1%
9 415
 
4.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 42284
82.8%
Common 8753
 
17.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 9729
23.0%
길 3508
 
8.3%
번 3508
 
8.3%
대 2822
 
6.7%
가 2003
 
4.7%
야 1938
 
4.6%
백 1498
 
3.5%
양 1498
 
3.5%
지 1310
 
3.1%
동 1292
 
3.1%
Other values (45) 13178
31.2%
Common
ValueCountFrequency (%)
1 1296
14.8%
4 1130
12.9%
3 1102
12.6%
2 1065
12.2%
5 911
10.4%
8 821
9.4%
7 799
9.1%
0 684
7.8%
6 530
6.1%
9 415
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 42284
82.8%
ASCII 8753
 
17.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 9729
23.0%
길 3508
 
8.3%
번 3508
 
8.3%
대 2822
 
6.7%
가 2003
 
4.7%
야 1938
 
4.6%
백 1498
 
3.5%
양 1498
 
3.5%
지 1310
 
3.1%
동 1292
 
3.1%
Other values (45) 13178
31.2%
ASCII
ValueCountFrequency (%)
1 1296
14.8%
4 1130
12.9%
3 1102
12.6%
2 1065
12.2%
5 911
10.4%
8 821
9.4%
7 799
9.1%
0 684
7.8%
6 530
6.1%
9 415
 
4.7%

시도
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
부산광역시
10000 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부산광역시 10000
100.0%

Length

2023-12-11T02:04:38.805431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:04:38.983539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 10000
100.0%

구군
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
부산진구
10000 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부산진구 10000
100.0%

Length

2023-12-11T02:04:39.157351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:04:39.350729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산진구 10000
100.0%

건물번호
Real number (ℝ)

MISSING 

Distinct448
Distinct (%)4.6%
Missing271
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean127.81519
Minimum1
Maximum735
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T02:04:39.572375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5
Q124
median65
Q3160
95-th percentile557.2
Maximum735
Range734
Interquartile range (IQR)136

Descriptive statistics

Standard deviation162.12818
Coefficient of variation (CV)1.2684578
Kurtosis3.2961702
Mean127.81519
Median Absolute Deviation (MAD)47
Skewness1.984923
Sum1243514
Variance26285.546
MonotonicityNot monotonic
2023-12-11T02:04:39.839792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 224
 
2.2%
11 153
 
1.5%
5 141
 
1.4%
4 129
 
1.3%
29 126
 
1.3%
19 125
 
1.2%
21 124
 
1.2%
8 123
 
1.2%
30 122
 
1.2%
10 110
 
1.1%
Other values (438) 8352
83.5%
(Missing) 271
 
2.7%
ValueCountFrequency (%)
1 28
 
0.3%
2 40
 
0.4%
3 224
2.2%
4 129
1.3%
5 141
1.4%
6 103
1.0%
7 91
0.9%
8 123
1.2%
9 100
1.0%
10 110
1.1%
ValueCountFrequency (%)
735 1
 
< 0.1%
733 2
 
< 0.1%
731 1
 
< 0.1%
729 5
 
0.1%
727 2
 
< 0.1%
725 6
 
0.1%
721 18
0.2%
715 16
0.2%
713 12
0.1%
709 7
 
0.1%

건물번호2
Real number (ℝ)

MISSING 

Distinct25
Distinct (%)1.7%
Missing8492
Missing (%)84.9%
Infinite0
Infinite (%)0.0%
Mean4.1366048
Minimum0
Maximum33
Zeros25
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T02:04:40.104845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q36
95-th percentile14
Maximum33
Range33
Interquartile range (IQR)5

Descriptive statistics

Standard deviation5.5625692
Coefficient of variation (CV)1.3447186
Kurtosis8.3610831
Mean4.1366048
Median Absolute Deviation (MAD)0
Skewness2.605699
Sum6238
Variance30.942176
MonotonicityNot monotonic
2023-12-11T02:04:40.340346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
1 813
 
8.1%
2 125
 
1.2%
6 65
 
0.7%
12 61
 
0.6%
9 58
 
0.6%
4 54
 
0.5%
3 53
 
0.5%
5 49
 
0.5%
8 36
 
0.4%
14 31
 
0.3%
Other values (15) 163
 
1.6%
(Missing) 8492
84.9%
ValueCountFrequency (%)
0 25
 
0.2%
1 813
8.1%
2 125
 
1.2%
3 53
 
0.5%
4 54
 
0.5%
5 49
 
0.5%
6 65
 
0.7%
7 24
 
0.2%
8 36
 
0.4%
9 58
 
0.6%
ValueCountFrequency (%)
33 4
 
< 0.1%
32 13
0.1%
29 9
0.1%
22 4
 
< 0.1%
21 3
 
< 0.1%
20 4
 
< 0.1%
18 2
 
< 0.1%
17 14
0.1%
16 4
 
< 0.1%
15 2
 
< 0.1%

Interactions

2023-12-11T02:04:34.045042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:04:33.657335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:04:34.253363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:04:33.860032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T02:04:40.512054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
건물번호건물번호2
건물번호1.0000.398
건물번호20.3981.000
2023-12-11T02:04:40.708026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
건물번호건물번호2
건물번호1.000-0.160
건물번호2-0.1601.000

Missing values

2023-12-11T02:04:34.487278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T02:04:34.697678image/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.
2023-12-11T02:04:34.915359image/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

업소명규격2표시위치시도구군건물번호건물번호2
15213디저트393*0.7새싹로부산광역시부산진구832
15602시즈원PC0.8*1.3*5.6당감로64번길부산광역시부산진구21<NA>
12253성안교회주차장0.8*0.8*4가야대로507번길부산광역시부산진구156<NA>
13609해법영수과학원1.90*0.8가야대로부산광역시부산진구63512
309The아이스크림7.2*1.2백양산로53번길부산광역시부산진구103<NA>
1738따봉로또복권0.5*0.5*3연지로부산광역시부산진구8<NA>
6191과탐원과학탐구전문교습소6*1.4백양대로부산광역시부산진구243<NA>
2430하늘부동산3.8*1.2당감서로부산광역시부산진구11<NA>
14245창조헤어공간3.6*1.2엄광로부산광역시부산진구271<NA>
1853하나투어1.4*1.2새싹로부산광역시부산진구143<NA>
업소명규격2표시위치시도구군건물번호건물번호2
14913대성냉동설비4.3*1백양순환로부산광역시부산진구152<NA>
492참숯한우공장0.8*2.8*4성지로부산광역시부산진구181
13354시골추어탕2.8*0.8대학로15번길부산광역시부산진구6<NA>
12389대풍자동차수리4.5*0.3가야대로588번길부산광역시부산진구16<NA>
10562수입나라0.8*2*3가야대로482번길부산광역시부산진구53<NA>
10134EDIYA COFFEE1.30*1.3<NA>부산광역시부산진구<NA><NA>
9497조은성모안과3*1가야대로부산광역시부산진구4761
11782원조가야돼지국밥0.7*2.6엄광로부산광역시부산진구1361
331왕수학교실4.2*0.8백양산로53번길부산광역시부산진구103<NA>
13487진지한쌈4.2*1대학로부산광역시부산진구67<NA>

Duplicate rows

Most frequently occurring

업소명규격2표시위치시도구군건물번호건물번호2# duplicates
97초석학원1.4*4동평로291번길부산광역시부산진구30174
5LG전자4.86*0.7가야대로부산광역시부산진구512<NA>3
27농심가3.5*0.7가야대로679번길부산광역시부산진구148<NA>3
71아트스시0.2*0.6*1.8동평로부산광역시부산진구23313
0(주)21세기인테리어3*0.8대학로45번길부산광역시부산진구25<NA>2
1ADOLPH FITNESS2.4*0.7엄광로부산광역시부산진구35<NA>2
2B&J고시텔3.8*1.5엄광로부산광역시부산진구17652
3GS25 부산개금점5.8*0.7냉정로부산광역시부산진구214<NA>2
4HEIMISH BEAUTY1.6*0.1가야대로부산광역시부산진구587<NA>2
6LLOYDBOMB4.5*0.8당감로부산광역시부산진구62<NA>2