Overview

Dataset statistics

Number of variables7
Number of observations10000
Missing cells9025
Missing cells (%)12.9%
Duplicate rows115
Duplicate rows (%)1.1%
Total size in memory644.5 KiB
Average record size in memory66.0 B

Variable types

Text3
Categorical2
Numeric2

Dataset

Description부산광역시 부산진구 관내 옥외광고물로 등록된 정보(업소명, 규격, 위치정보 등)가 등록된 자료를 제공하고자 합니다.
Author부산광역시 부산진구
URLhttps://www.data.go.kr/data/15066405/fileData.do

Alerts

시도 has constant value ""Constant
구군 has constant value ""Constant
Dataset has 115 (1.1%) duplicate rowsDuplicates
표시위치 has 288 (2.9%) missing valuesMissing
건물번호 has 288 (2.9%) missing valuesMissing
건물번호2 has 8449 (84.5%) missing valuesMissing

Reproduction

Analysis started2023-12-12 11:53:08.364440
Analysis finished2023-12-12 11:53:10.247858
Duration1.88 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

Distinct6274
Distinct (%)62.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T20:53:10.492525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length20
Mean length6.1988
Min length1

Characters and Unicode

Total characters61988
Distinct characters991
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3761 ?
Unique (%)37.6%

Sample

1st row천수자연건강
2nd row그때그집
3rd rowAngel in uscoffee
4th row미화해장국.생고기
5th row고려불교예술원
ValueCountFrequency (%)
coffee 35
 
0.3%
gs25 23
 
0.2%
the 22
 
0.2%
cu 19
 
0.2%
pc 16
 
0.1%
씨유 16
 
0.1%
cafe 14
 
0.1%
크린토피아 14
 
0.1%
초읍점 13
 
0.1%
세븐일레븐 13
 
0.1%
Other values (6521) 10661
98.3%
2023-12-12T20:53:11.096983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 1158
 
1.9%
이 932
 
1.5%
스 899
 
1.5%
어 887
 
1.4%
리 870
 
1.4%
846
 
1.4%
동 778
 
1.3%
부 749
 
1.2%
산 711
 
1.1%
가 687
 
1.1%
Other values (981) 53471
86.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 53407
86.2%
Uppercase Letter 4485
 
7.2%
Lowercase Letter 1835
 
3.0%
Space Separator 846
 
1.4%
Decimal Number 665
 
1.1%
Other Punctuation 236
 
0.4%
Close Punctuation 234
 
0.4%
Open Punctuation 231
 
0.4%
Dash Punctuation 17
 
< 0.1%
Math Symbol 16
 
< 0.1%
Other values (2) 16
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 1158
 
2.2%
이 932
 
1.7%
스 899
 
1.7%
어 887
 
1.7%
리 870
 
1.6%
동 778
 
1.5%
부 749
 
1.4%
산 711
 
1.3%
가 687
 
1.3%
점 686
 
1.3%
Other values (896) 45050
84.4%
Uppercase Letter
ValueCountFrequency (%)
E 486
 
10.8%
S 342
 
7.6%
O 333
 
7.4%
A 297
 
6.6%
C 279
 
6.2%
T 258
 
5.8%
I 241
 
5.4%
N 234
 
5.2%
R 209
 
4.7%
L 203
 
4.5%
Other values (16) 1603
35.7%
Lowercase Letter
ValueCountFrequency (%)
e 265
14.4%
a 180
 
9.8%
o 169
 
9.2%
i 135
 
7.4%
n 130
 
7.1%
r 105
 
5.7%
c 104
 
5.7%
s 94
 
5.1%
t 91
 
5.0%
l 79
 
4.3%
Other values (15) 483
26.3%
Other Punctuation
ValueCountFrequency (%)
& 85
36.0%
. 68
28.8%
, 19
 
8.1%
# 18
 
7.6%
! 10
 
4.2%
% 9
 
3.8%
/ 8
 
3.4%
: 6
 
2.5%
? 5
 
2.1%
; 4
 
1.7%
Other values (2) 4
 
1.7%
Decimal Number
ValueCountFrequency (%)
2 183
27.5%
1 102
15.3%
5 101
15.2%
4 69
 
10.4%
0 64
 
9.6%
3 39
 
5.9%
8 32
 
4.8%
7 28
 
4.2%
9 24
 
3.6%
6 23
 
3.5%
Math Symbol
ValueCountFrequency (%)
+ 12
75.0%
~ 2
 
12.5%
| 2
 
12.5%
Close Punctuation
ValueCountFrequency (%)
) 226
96.6%
] 8
 
3.4%
Open Punctuation
ValueCountFrequency (%)
( 223
96.5%
[ 8
 
3.5%
Other Symbol
ValueCountFrequency (%)
● 6
75.0%
㈜ 2
 
25.0%
Space Separator
ValueCountFrequency (%)
846
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 53337
86.0%
Latin 6320
 
10.2%
Common 2259
 
3.6%
Han 72
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 1158
 
2.2%
이 932
 
1.7%
스 899
 
1.7%
어 887
 
1.7%
리 870
 
1.6%
동 778
 
1.5%
부 749
 
1.4%
산 711
 
1.3%
가 687
 
1.3%
점 686
 
1.3%
Other values (874) 44980
84.3%
Latin
ValueCountFrequency (%)
E 486
 
7.7%
S 342
 
5.4%
O 333
 
5.3%
A 297
 
4.7%
C 279
 
4.4%
e 265
 
4.2%
T 258
 
4.1%
I 241
 
3.8%
N 234
 
3.7%
R 209
 
3.3%
Other values (41) 3376
53.4%
Common
ValueCountFrequency (%)
846
37.5%
) 226
 
10.0%
( 223
 
9.9%
2 183
 
8.1%
1 102
 
4.5%
5 101
 
4.5%
& 85
 
3.8%
4 69
 
3.1%
. 68
 
3.0%
0 64
 
2.8%
Other values (23) 292
 
12.9%
Han
ValueCountFrequency (%)
家 15
20.8%
美 7
 
9.7%
大 6
 
8.3%
秀 5
 
6.9%
酒 4
 
5.6%
生 4
 
5.6%
人 4
 
5.6%
本 3
 
4.2%
宇 3
 
4.2%
水 2
 
2.8%
Other values (13) 19
26.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 53326
86.0%
ASCII 8573
 
13.8%
CJK 72
 
0.1%
Compat Jamo 9
 
< 0.1%
Geometric Shapes 6
 
< 0.1%
None 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 1158
 
2.2%
이 932
 
1.7%
스 899
 
1.7%
어 887
 
1.7%
리 870
 
1.6%
동 778
 
1.5%
부 749
 
1.4%
산 711
 
1.3%
가 687
 
1.3%
점 686
 
1.3%
Other values (868) 44969
84.3%
ASCII
ValueCountFrequency (%)
846
 
9.9%
E 486
 
5.7%
S 342
 
4.0%
O 333
 
3.9%
A 297
 
3.5%
C 279
 
3.3%
e 265
 
3.1%
T 258
 
3.0%
I 241
 
2.8%
N 234
 
2.7%
Other values (73) 4992
58.2%
CJK
ValueCountFrequency (%)
家 15
20.8%
美 7
 
9.7%
大 6
 
8.3%
秀 5
 
6.9%
酒 4
 
5.6%
生 4
 
5.6%
人 4
 
5.6%
本 3
 
4.2%
宇 3
 
4.2%
水 2
 
2.8%
Other values (13) 19
26.4%
Geometric Shapes
ValueCountFrequency (%)
● 6
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅡ 4
44.4%
ㅇ 2
22.2%
ㄹ 1
 
11.1%
ㅋ 1
 
11.1%
ㅅ 1
 
11.1%
None
ValueCountFrequency (%)
㈜ 2
100.0%

규격2
Text

Distinct2628
Distinct (%)26.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T20:53:11.519793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length24
Mean length6.689
Min length3

Characters and Unicode

Total characters66890
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

Unique1534 ?
Unique (%)15.3%

Sample

1st row4.2*0.8
2nd row0.6*0.6*3
3rd row3*0.5
4th row4*0.8
5th row8*0.7
ValueCountFrequency (%)
0.8*3 146
 
1.5%
4*1 127
 
1.3%
3*1 86
 
0.9%
5*1 77
 
0.8%
3.5*1 77
 
0.8%
3*0.8 65
 
0.6%
0.6*0.6*2 64
 
0.6%
4.5*1 64
 
0.6%
0.8*3*4 61
 
0.6%
6*1 59
 
0.6%
Other values (2617) 9201
91.8%
2023-12-12T20:53:12.106884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 15648
23.4%
* 12316
18.4%
0 7512
11.2%
1 5729
 
8.6%
5 4839
 
7.2%
2 4431
 
6.6%
8 4043
 
6.0%
3 3670
 
5.5%
4 3131
 
4.7%
6 2489
 
3.7%
Other values (14) 3082
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 38779
58.0%
Other Punctuation 28007
41.9%
Other Letter 54
 
0.1%
Space Separator 46
 
0.1%
Open Punctuation 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7512
19.4%
1 5729
14.8%
5 4839
12.5%
2 4431
11.4%
8 4043
10.4%
3 3670
9.5%
4 3131
8.1%
6 2489
 
6.4%
7 1803
 
4.6%
9 1132
 
2.9%
Other Letter
ValueCountFrequency (%)
이 19
35.2%
높 19
35.2%
양 4
 
7.4%
성 4
 
7.4%
화 4
 
7.4%
추 2
 
3.7%
진 2
 
3.7%
Other Punctuation
ValueCountFrequency (%)
. 15648
55.9%
* 12316
44.0%
: 23
 
0.1%
, 20
 
0.1%
Space Separator
ValueCountFrequency (%)
46
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 66836
99.9%
Hangul 54
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 15648
23.4%
* 12316
18.4%
0 7512
11.2%
1 5729
 
8.6%
5 4839
 
7.2%
2 4431
 
6.6%
8 4043
 
6.0%
3 3670
 
5.5%
4 3131
 
4.7%
6 2489
 
3.7%
Other values (7) 3028
 
4.5%
Hangul
ValueCountFrequency (%)
이 19
35.2%
높 19
35.2%
양 4
 
7.4%
성 4
 
7.4%
화 4
 
7.4%
추 2
 
3.7%
진 2
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 66836
99.9%
Hangul 54
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 15648
23.4%
* 12316
18.4%
0 7512
11.2%
1 5729
 
8.6%
5 4839
 
7.2%
2 4431
 
6.6%
8 4043
 
6.0%
3 3670
 
5.5%
4 3131
 
4.7%
6 2489
 
3.7%
Other values (7) 3028
 
4.5%
Hangul
ValueCountFrequency (%)
이 19
35.2%
높 19
35.2%
양 4
 
7.4%
성 4
 
7.4%
화 4
 
7.4%
추 2
 
3.7%
진 2
 
3.7%

표시위치
Text

MISSING 

Distinct249
Distinct (%)2.6%
Missing288
Missing (%)2.9%
Memory size156.2 KiB
2023-12-12T20:53:12.787144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length5.1989292
Min length3

Characters and Unicode

Total characters50492
Distinct characters63
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

Unique29 ?
Unique (%)0.3%

Sample

1st row성지로
2nd row새싹로
3rd row엄광로
4th row동평로116번길
5th row동평로
ValueCountFrequency (%)
가야대로 948
 
9.8%
새싹로 674
 
6.9%
동평로 622
 
6.4%
엄광로 504
 
5.2%
성지로 459
 
4.7%
당감로 340
 
3.5%
백양대로 329
 
3.4%
대학로 324
 
3.3%
백양순환로 303
 
3.1%
당감서로 274
 
2.8%
Other values (239) 4935
50.8%
2023-12-12T20:53:13.287900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 9712
19.2%
번 3418
 
6.8%
길 3418
 
6.8%
대 2815
 
5.6%
가 1988
 
3.9%
야 1930
 
3.8%
백 1463
 
2.9%
양 1463
 
2.9%
지 1321
 
2.6%
동 1279
 
2.5%
Other values (53) 21685
42.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 42016
83.2%
Decimal Number 8476
 
16.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 9712
23.1%
번 3418
 
8.1%
길 3418
 
8.1%
대 2815
 
6.7%
가 1988
 
4.7%
야 1930
 
4.6%
백 1463
 
3.5%
양 1463
 
3.5%
지 1321
 
3.1%
동 1279
 
3.0%
Other values (43) 13209
31.4%
Decimal Number
ValueCountFrequency (%)
1 1238
14.6%
4 1126
13.3%
2 1045
12.3%
3 1029
12.1%
5 860
10.1%
7 801
9.5%
8 754
8.9%
0 686
8.1%
6 523
6.2%
9 414
 
4.9%

Most occurring scripts

ValueCountFrequency (%)
Hangul 42016
83.2%
Common 8476
 
16.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 9712
23.1%
번 3418
 
8.1%
길 3418
 
8.1%
대 2815
 
6.7%
가 1988
 
4.7%
야 1930
 
4.6%
백 1463
 
3.5%
양 1463
 
3.5%
지 1321
 
3.1%
동 1279
 
3.0%
Other values (43) 13209
31.4%
Common
ValueCountFrequency (%)
1 1238
14.6%
4 1126
13.3%
2 1045
12.3%
3 1029
12.1%
5 860
10.1%
7 801
9.5%
8 754
8.9%
0 686
8.1%
6 523
6.2%
9 414
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 42016
83.2%
ASCII 8476
 
16.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 9712
23.1%
번 3418
 
8.1%
길 3418
 
8.1%
대 2815
 
6.7%
가 1988
 
4.7%
야 1930
 
4.6%
백 1463
 
3.5%
양 1463
 
3.5%
지 1321
 
3.1%
동 1279
 
3.0%
Other values (43) 13209
31.4%
ASCII
ValueCountFrequency (%)
1 1238
14.6%
4 1126
13.3%
2 1045
12.3%
3 1029
12.1%
5 860
10.1%
7 801
9.5%
8 754
8.9%
0 686
8.1%
6 523
6.2%
9 414
 
4.9%

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

2023-12-12T20:53:13.494823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:53:13.646172image/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

2023-12-12T20:53:13.801322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:53:13.951457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산진구 10000
100.0%

건물번호
Real number (ℝ)

MISSING 

Distinct449
Distinct (%)4.6%
Missing288
Missing (%)2.9%
Infinite0
Infinite (%)0.0%
Mean129.6665
Minimum1
Maximum733
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T20:53:14.105905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5
Q124
median66
Q3164
95-th percentile560
Maximum733
Range732
Interquartile range (IQR)140

Descriptive statistics

Standard deviation163.24352
Coefficient of variation (CV)1.2589491
Kurtosis3.1245901
Mean129.6665
Median Absolute Deviation (MAD)48
Skewness1.9474448
Sum1259321
Variance26648.447
MonotonicityNot monotonic
2023-12-12T20:53:14.332857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 202
 
2.0%
5 149
 
1.5%
11 141
 
1.4%
4 134
 
1.3%
30 131
 
1.3%
29 124
 
1.2%
21 124
 
1.2%
14 124
 
1.2%
10 122
 
1.2%
19 114
 
1.1%
Other values (439) 8347
83.5%
(Missing) 288
 
2.9%
ValueCountFrequency (%)
1 24
 
0.2%
2 31
 
0.3%
3 202
2.0%
4 134
1.3%
5 149
1.5%
6 110
1.1%
7 98
1.0%
8 104
1.0%
9 110
1.1%
10 122
1.2%
ValueCountFrequency (%)
733 2
 
< 0.1%
731 1
 
< 0.1%
729 4
 
< 0.1%
727 1
 
< 0.1%
725 6
 
0.1%
721 15
0.1%
715 14
0.1%
713 11
0.1%
709 6
 
0.1%
707 3
 
< 0.1%

건물번호2
Real number (ℝ)

MISSING 

Distinct26
Distinct (%)1.7%
Missing8449
Missing (%)84.5%
Infinite0
Infinite (%)0.0%
Mean4.005158
Minimum0
Maximum33
Zeros28
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T20:53:14.605062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q35
95-th percentile14
Maximum33
Range33
Interquartile range (IQR)4

Descriptive statistics

Standard deviation5.5327738
Coefficient of variation (CV)1.3814121
Kurtosis9.3300568
Mean4.005158
Median Absolute Deviation (MAD)0
Skewness2.7583528
Sum6212
Variance30.611586
MonotonicityNot monotonic
2023-12-12T20:53:14.797386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
1 856
 
8.6%
2 126
 
1.3%
6 68
 
0.7%
9 58
 
0.6%
3 56
 
0.6%
4 52
 
0.5%
5 51
 
0.5%
12 44
 
0.4%
8 41
 
0.4%
14 31
 
0.3%
Other values (16) 168
 
1.7%
(Missing) 8449
84.5%
ValueCountFrequency (%)
0 28
 
0.3%
1 856
8.6%
2 126
 
1.3%
3 56
 
0.6%
4 52
 
0.5%
5 51
 
0.5%
6 68
 
0.7%
7 20
 
0.2%
8 41
 
0.4%
9 58
 
0.6%
ValueCountFrequency (%)
33 5
 
0.1%
32 14
0.1%
30 1
 
< 0.1%
29 8
0.1%
22 4
 
< 0.1%
21 2
 
< 0.1%
20 3
 
< 0.1%
18 1
 
< 0.1%
17 12
0.1%
16 5
 
0.1%

Interactions

2023-12-12T20:53:09.554690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:53:09.235514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:53:09.701187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:53:09.388155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T20:53:14.948755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
건물번호건물번호2
건물번호1.0000.342
건물번호20.3421.000
2023-12-12T20:53:15.094808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
건물번호건물번호2
건물번호1.000-0.171
건물번호2-0.1711.000

Missing values

2023-12-12T20:53:09.900237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T20:53:10.043371image/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.
2023-12-12T20:53:10.168819image/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
793천수자연건강4.2*0.8성지로부산광역시부산진구221
4277그때그집0.6*0.6*3새싹로부산광역시부산진구280<NA>
8437Angel in uscoffee3*0.5엄광로부산광역시부산진구30<NA>
7216미화해장국.생고기4*0.8동평로116번길부산광역시부산진구8<NA>
760고려불교예술원8*0.7동평로부산광역시부산진구261<NA>
8844코렘노부영LITERACY14.5*1.8가야대로부산광역시부산진구458<NA>
8719뽑기싸롱0.5*0.5*3복지로부산광역시부산진구411
7701보원사0.8*0.4당감로10번길부산광역시부산진구96
6145주공셀프주유소7.41*1백양대로부산광역시부산진구231<NA>
15232FLOWER POEM0.4*0.4*3신천대로220번길부산광역시부산진구92<NA>
업소명규격2표시위치시도구군건물번호건물번호2
10586새송이아구찜5.4*0.6냉정로233번길부산광역시부산진구205
3420브랜드신발0.8*1.4*3.5성지로137번길부산광역시부산진구108<NA>
2130한신태권도0.8*4*5새싹로부산광역시부산진구189<NA>
8089서민치킨포차4*0.9복지로부산광역시부산진구70<NA>
11674가야중앙체육관1.2*2.2가야공원로부산광역시부산진구44<NA>
10122TheGaGaCoffee0.7*0.6*2가야대로703번길부산광역시부산진구26<NA>
10550동아씽크인테리어3.8*1.2가야대로482번길부산광역시부산진구69<NA>
4884한양왕족발3.5*0.6새싹로부산광역시부산진구2711
10282한성종합공사5.2*1신천대로197번길부산광역시부산진구501
1099로이만어학원3.8*1백양관문로부산광역시부산진구103<NA>

Duplicate rows

Most frequently occurring

업소명규격2표시위치시도구군건물번호건물번호2# duplicates
40로타리노인복지센터4.8*0.6동평로부산광역시부산진구245<NA>3
81이튼치과의원6*1.2당감서로부산광역시부산진구88<NA>3
85진가네추어탕1.4*1.1백양순환로부산광역시부산진구9<NA>3
109헤어토크1.5*0.5엄광로부산광역시부산진구18013
0(주) 이마트트레이더스 서면점9.8*12.5시민공원로부산광역시부산진구31<NA>2
17ELEVEN 부산초읍하늘채점5*0.7성지로부산광역시부산진구123<NA>2
2ADOLPH FITNESS2.4*0.7엄광로부산광역시부산진구35<NA>2
3ARITAUM3*0.5동평로부산광역시부산진구112<NA>2
4Any time의료기3.5*0.6가야대로부산광역시부산진구459<NA>2
5B&J고시텔3.8*1.5엄광로부산광역시부산진구17652