Overview

Dataset statistics

Number of variables8
Number of observations203
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.2 KiB
Average record size in memory66.7 B

Variable types

Categorical4
Text2
Numeric2

Dataset

Description우리구 관내 실내공기질 관리 시설(불특정다수가 이용하는 시설)에대한 정보(대상시설 구분,시설명,위도, 경도)를 제공합니다
Author부산광역시 부산진구
URLhttps://www.data.go.kr/data/15037964/fileData.do

Alerts

관리기관명 has constant value ""Constant
구군명 has constant value ""Constant
데이터기준일자 has constant value ""Constant

Reproduction

Analysis started2023-12-16 15:37:09.888625
Analysis finished2023-12-16 15:37:20.944047
Duration11.06 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대상시설구분
Categorical

Distinct15
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
실내주차장
53 
의료기관
39 
대규모점포
28 
어린이집
21 
PC영업시설
17 
Other values (10)
45 

Length

Max length7
Median length6
Mean length4.6059113
Min length2

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
실내주차장 53
26.1%
의료기관 39
19.2%
대규모점포 28
13.8%
어린이집 21
 
10.3%
PC영업시설 17
 
8.4%
지하역사 10
 
4.9%
목욕장 9
 
4.4%
노인요양시설 5
 
2.5%
영화상영관 5
 
2.5%
장례식장 4
 
2.0%
Other values (5) 12
 
5.9%

Length

2023-12-16T15:37:21.395023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
실내주차장 53
26.1%
의료기관 39
19.2%
대규모점포 28
13.8%
어린이집 21
 
10.3%
pc영업시설 17
 
8.4%
지하역사 10
 
4.9%
목욕장 9
 
4.4%
노인요양시설 5
 
2.5%
영화상영관 5
 
2.5%
장례식장 4
 
2.0%
Other values (5) 12
 
5.9%

시설명
Text

Distinct191
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-16T15:37:22.756048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length21
Mean length9.0295567
Min length3

Characters and Unicode

Total characters1833
Distinct characters307
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique179 ?
Unique (%)88.2%

Sample

1st row양정역
2nd row부전역
3rd row서면역(1호선)
4th row범내골역
5th row개금역
ValueCountFrequency (%)
서면점 5
 
1.7%
의료법인 5
 
1.7%
pc 5
 
1.7%
삼정타워 3
 
1.0%
범내골역 2
 
0.7%
서면본점 2
 
0.7%
부산 2
 
0.7%
pc토랑 2
 
0.7%
오피스텔 2
 
0.7%
롯데시네마 2
 
0.7%
Other values (240) 256
89.5%
2023-12-16T15:37:24.644927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
88
 
4.8%
원 59
 
3.2%
부 49
 
2.7%
산 47
 
2.6%
병 39
 
2.1%
이 38
 
2.1%
의 34
 
1.9%
양 33
 
1.8%
스 30
 
1.6%
시 30
 
1.6%
Other values (297) 1386
75.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1559
85.1%
Uppercase Letter 102
 
5.6%
Space Separator 88
 
4.8%
Decimal Number 22
 
1.2%
Close Punctuation 21
 
1.1%
Open Punctuation 21
 
1.1%
Other Symbol 9
 
0.5%
Other Punctuation 6
 
0.3%
Dash Punctuation 2
 
0.1%
Lowercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 59
 
3.8%
부 49
 
3.1%
산 47
 
3.0%
병 39
 
2.5%
이 38
 
2.4%
의 34
 
2.2%
양 33
 
2.1%
스 30
 
1.9%
시 30
 
1.9%
어 29
 
1.9%
Other values (258) 1171
75.1%
Uppercase Letter
ValueCountFrequency (%)
C 23
22.5%
P 18
17.6%
O 9
 
8.8%
A 8
 
7.8%
G 7
 
6.9%
S 6
 
5.9%
E 5
 
4.9%
T 4
 
3.9%
K 3
 
2.9%
N 3
 
2.9%
Other values (11) 16
15.7%
Decimal Number
ValueCountFrequency (%)
2 11
50.0%
1 5
22.7%
4 3
 
13.6%
3 1
 
4.5%
0 1
 
4.5%
5 1
 
4.5%
Other Punctuation
ValueCountFrequency (%)
. 2
33.3%
, 2
33.3%
& 1
16.7%
? 1
16.7%
Lowercase Letter
ValueCountFrequency (%)
f 1
50.0%
a 1
50.0%
Space Separator
ValueCountFrequency (%)
88
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 9
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Math Symbol
ValueCountFrequency (%)
→ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1568
85.5%
Common 161
 
8.8%
Latin 104
 
5.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 59
 
3.8%
부 49
 
3.1%
산 47
 
3.0%
병 39
 
2.5%
이 38
 
2.4%
의 34
 
2.2%
양 33
 
2.1%
스 30
 
1.9%
시 30
 
1.9%
어 29
 
1.8%
Other values (259) 1180
75.3%
Latin
ValueCountFrequency (%)
C 23
22.1%
P 18
17.3%
O 9
 
8.7%
A 8
 
7.7%
G 7
 
6.7%
S 6
 
5.8%
E 5
 
4.8%
T 4
 
3.8%
K 3
 
2.9%
N 3
 
2.9%
Other values (13) 18
17.3%
Common
ValueCountFrequency (%)
88
54.7%
) 21
 
13.0%
( 21
 
13.0%
2 11
 
6.8%
1 5
 
3.1%
4 3
 
1.9%
. 2
 
1.2%
- 2
 
1.2%
, 2
 
1.2%
3 1
 
0.6%
Other values (5) 5
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1559
85.1%
ASCII 264
 
14.4%
None 9
 
0.5%
Arrows 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
88
33.3%
C 23
 
8.7%
) 21
 
8.0%
( 21
 
8.0%
P 18
 
6.8%
2 11
 
4.2%
O 9
 
3.4%
A 8
 
3.0%
G 7
 
2.7%
S 6
 
2.3%
Other values (27) 52
19.7%
Hangul
ValueCountFrequency (%)
원 59
 
3.8%
부 49
 
3.1%
산 47
 
3.0%
병 39
 
2.5%
이 38
 
2.4%
의 34
 
2.2%
양 33
 
2.1%
스 30
 
1.9%
시 30
 
1.9%
어 29
 
1.9%
Other values (258) 1171
75.1%
None
ValueCountFrequency (%)
㈜ 9
100.0%
Arrows
ValueCountFrequency (%)
→ 1
100.0%

소재지
Text

Distinct188
Distinct (%)92.6%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-16T15:37:25.904532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length69
Median length41
Mean length26.221675
Min length16

Characters and Unicode

Total characters5323
Distinct characters145
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

Unique175 ?
Unique (%)86.2%

Sample

1st row부산광역시 부산진구 중앙대로 지하 930
2nd row부산광역시 부산진구 중앙대로 지하 786
3rd row부산광역시 부산진구 중앙대로 지하 730
4th row부산광역시 부산진구 중앙대로 지하 612
5th row부산광역시 부산진구 가야대로 지하 442
ValueCountFrequency (%)
부산광역시 203
19.5%
부산진구 203
19.5%
중앙대로 42
 
4.0%
가야대로 29
 
2.8%
부전동 18
 
1.7%
관리사무소 15
 
1.4%
2층 11
 
1.1%
지하 11
 
1.1%
서면로 8
 
0.8%
신천대로 8
 
0.8%
Other values (328) 491
47.3%
2023-12-16T15:37:28.698838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
837
 
15.7%
부 453
 
8.5%
산 414
 
7.8%
시 214
 
4.0%
진 209
 
3.9%
광 206
 
3.9%
구 205
 
3.9%
로 204
 
3.8%
역 203
 
3.8%
1 156
 
2.9%
Other values (135) 2222
41.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3383
63.6%
Space Separator 837
 
15.7%
Decimal Number 817
 
15.3%
Other Punctuation 99
 
1.9%
Close Punctuation 67
 
1.3%
Open Punctuation 67
 
1.3%
Math Symbol 30
 
0.6%
Dash Punctuation 17
 
0.3%
Uppercase Letter 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 453
13.4%
산 414
 
12.2%
시 214
 
6.3%
진 209
 
6.2%
광 206
 
6.1%
구 205
 
6.1%
로 204
 
6.0%
역 203
 
6.0%
대 110
 
3.3%
층 90
 
2.7%
Other values (113) 1075
31.8%
Decimal Number
ValueCountFrequency (%)
1 156
19.1%
2 107
13.1%
7 100
12.2%
6 91
11.1%
4 73
8.9%
3 70
8.6%
5 63
7.7%
0 60
 
7.3%
8 51
 
6.2%
9 46
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
D 2
33.3%
R 1
16.7%
C 1
16.7%
G 1
16.7%
V 1
16.7%
Other Punctuation
ValueCountFrequency (%)
, 98
99.0%
* 1
 
1.0%
Space Separator
ValueCountFrequency (%)
837
100.0%
Close Punctuation
ValueCountFrequency (%)
) 67
100.0%
Open Punctuation
ValueCountFrequency (%)
( 67
100.0%
Math Symbol
ValueCountFrequency (%)
~ 30
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3383
63.6%
Common 1934
36.3%
Latin 6
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 453
13.4%
산 414
 
12.2%
시 214
 
6.3%
진 209
 
6.2%
광 206
 
6.1%
구 205
 
6.1%
로 204
 
6.0%
역 203
 
6.0%
대 110
 
3.3%
층 90
 
2.7%
Other values (113) 1075
31.8%
Common
ValueCountFrequency (%)
837
43.3%
1 156
 
8.1%
2 107
 
5.5%
7 100
 
5.2%
, 98
 
5.1%
6 91
 
4.7%
4 73
 
3.8%
3 70
 
3.6%
) 67
 
3.5%
( 67
 
3.5%
Other values (7) 268
 
13.9%
Latin
ValueCountFrequency (%)
D 2
33.3%
R 1
16.7%
C 1
16.7%
G 1
16.7%
V 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3383
63.6%
ASCII 1940
36.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
837
43.1%
1 156
 
8.0%
2 107
 
5.5%
7 100
 
5.2%
, 98
 
5.1%
6 91
 
4.7%
4 73
 
3.8%
3 70
 
3.6%
) 67
 
3.5%
( 67
 
3.5%
Other values (12) 274
 
14.1%
Hangul
ValueCountFrequency (%)
부 453
13.4%
산 414
 
12.2%
시 214
 
6.3%
진 209
 
6.2%
광 206
 
6.1%
구 205
 
6.1%
로 204
 
6.0%
역 203
 
6.0%
대 110
 
3.3%
층 90
 
2.7%
Other values (113) 1075
31.8%

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
부산광역시 부산진구청
203 

Length

Max length11
Median length11
Mean length11
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부산광역시 부산진구청 203
100.0%

Length

2023-12-16T15:37:29.211845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T15:37:30.102116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 203
50.0%
부산진구청 203
50.0%

구군명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
부산진구
203 

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 203
100.0%

Length

2023-12-16T15:37:30.964354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T15:37:31.420182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산진구 203
100.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-01
203 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-12-01
2nd row2023-12-01
3rd row2023-12-01
4th row2023-12-01
5th row2023-12-01

Common Values

ValueCountFrequency (%)
2023-12-01 203
100.0%

Length

2023-12-16T15:37:32.362574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T15:37:32.743318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-12-01 203
100.0%

위도
Real number (ℝ)

Distinct159
Distinct (%)78.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.157952
Minimum35.141609
Maximum35.182807
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-16T15:37:33.263907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.141609
5-th percentile35.145681
Q135.15287
median35.156326
Q335.162833
95-th percentile35.174268
Maximum35.182807
Range0.04119787
Interquartile range (IQR)0.0099634

Descriptive statistics

Standard deviation0.0090357664
Coefficient of variation (CV)0.00025700492
Kurtosis-0.096387451
Mean35.157952
Median Absolute Deviation (MAD)0.00487792
Skewness0.59625981
Sum7137.0642
Variance8.1645075 × 10-5
MonotonicityNot monotonic
2023-12-16T15:37:33.819822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.15679253 5
 
2.5%
35.15784866 5
 
2.5%
35.14943396 4
 
2.0%
35.15300583 4
 
2.0%
35.15511752 4
 
2.0%
35.15364928 3
 
1.5%
35.15703218 3
 
1.5%
35.15426987 3
 
1.5%
35.15472749 3
 
1.5%
35.14722597 2
 
1.0%
Other values (149) 167
82.3%
ValueCountFrequency (%)
35.14160936 2
1.0%
35.14169296 1
0.5%
35.14174242 2
1.0%
35.14182847 1
0.5%
35.141866 1
0.5%
35.14205888 1
0.5%
35.14260918 1
0.5%
35.14431978 1
0.5%
35.14566778 1
0.5%
35.14579707 1
0.5%
ValueCountFrequency (%)
35.18280723 1
0.5%
35.18166912 1
0.5%
35.18047218 1
0.5%
35.17922004 1
0.5%
35.1780131 1
0.5%
35.17738668 1
0.5%
35.17577108 1
0.5%
35.17544132 1
0.5%
35.17480321 1
0.5%
35.17465827 1
0.5%

경도
Real number (ℝ)

Distinct159
Distinct (%)78.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.05383
Minimum129.01786
Maximum129.07593
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-16T15:37:34.248570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum129.01786
5-th percentile129.02314
Q1129.04998
median129.05884
Q3129.06236
95-th percentile129.07041
Maximum129.07593
Range0.058067
Interquartile range (IQR)0.0123787

Descriptive statistics

Standard deviation0.014196313
Coefficient of variation (CV)0.00011000304
Kurtosis0.29450867
Mean129.05383
Median Absolute Deviation (MAD)0.0049153
Skewness-1.1028409
Sum26197.927
Variance0.00020153531
MonotonicityNot monotonic
2023-12-16T15:37:34.955143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
129.0564133 5
 
2.5%
129.050028 5
 
2.5%
129.0639784 4
 
2.0%
129.0596019 4
 
2.0%
129.0603537 4
 
2.0%
129.0540458 3
 
1.5%
129.0630128 3
 
1.5%
129.0573026 3
 
1.5%
129.0596024 3
 
1.5%
129.045315 2
 
1.0%
Other values (149) 167
82.3%
ValueCountFrequency (%)
129.017859 1
0.5%
129.0194524 1
0.5%
129.0197657 1
0.5%
129.0201588 1
0.5%
129.0204117 1
0.5%
129.020569 2
1.0%
129.0215908 1
0.5%
129.0223596 2
1.0%
129.0231314 1
0.5%
129.0232287 1
0.5%
ValueCountFrequency (%)
129.075926 1
0.5%
129.0746271 1
0.5%
129.0741138 1
0.5%
129.0740734 1
0.5%
129.0737175 1
0.5%
129.0732114 1
0.5%
129.0729135 1
0.5%
129.0726998 1
0.5%
129.0720525 1
0.5%
129.0712233 1
0.5%

Interactions

2023-12-16T15:37:19.140137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:37:18.215191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:37:19.584140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:37:18.654406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-16T15:37:35.312604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대상시설구분위도경도
대상시설구분1.0000.3130.371
위도0.3131.0000.734
경도0.3710.7341.000
2023-12-16T15:37:35.621565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도대상시설구분
위도1.0000.1280.119
경도0.1281.0000.141
대상시설구분0.1190.1411.000

Missing values

2023-12-16T15:37:20.043901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-16T15:37:20.758517image/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

대상시설구분시설명소재지관리기관명구군명데이터기준일자위도경도
0지하역사양정역부산광역시 부산진구 중앙대로 지하 930부산광역시 부산진구청부산진구2023-12-0135.172968129.071223
1지하역사부전역부산광역시 부산진구 중앙대로 지하 786부산광역시 부산진구청부산진구2023-12-0135.162639129.063009
2지하역사서면역(1호선)부산광역시 부산진구 중앙대로 지하 730부산광역시 부산진구청부산진구2023-12-0135.157766129.058445
3지하역사범내골역부산광역시 부산진구 중앙대로 지하 612부산광역시 부산진구청부산진구2023-12-0135.147357129.059232
4지하역사개금역부산광역시 부산진구 가야대로 지하 442부산광역시 부산진구청부산진구2023-12-0135.153189129.020412
5지하역사동의대역부산광역시 부산진구 가야대로 지하 554부산광역시 부산진구청부산진구2023-12-0135.154042129.03255
6지하역사가야역부산광역시 부산진구 가야대로 지하 650부산광역시 부산진구청부산진구2023-12-0135.155874129.042825
7지하역사부암역부산광역시 부산진구 가야대로 지하 719부산광역시 부산진구청부산진구2023-12-0135.157444129.049935
8지하역사서면역(2호선)부산광역시 부산진구 중앙대로 지하 730부산광역시 부산진구청부산진구2023-12-0135.157766129.058445
9지하역사전포역부산광역시 부산진구 전포대로 지하 181부산광역시 부산진구청부산진구2023-12-0135.152838129.065362
대상시설구분시설명소재지관리기관명구군명데이터기준일자위도경도
193실내주차장주식회사 씨제이헬로비전부산광역시 부산진구 서전로46번길 48(전포동)부산광역시 부산진구청부산진구2023-12-0135.155585129.064629
194실내주차장한라시그마타워부산광역시 부산진구 황령대로 13(범천동), 1층 관리사무소부산광역시 부산진구청부산진구2023-12-0135.148353129.060826
195실내주차장시청역 롯데골드로즈부산광역시 부산진구 중앙대로 993(양정동), 지하1층 관리사무소부산광역시 부산진구청부산진구2023-12-0135.178013129.074627
196실내주차장더블루 오피스텔부산광역시 부산진구 전포대로171번길 26(전포동) 관리사무소부산광역시 부산진구청부산진구2023-12-0135.151771129.063647
197실내주차장범내골역 한라비발디 STUDIO 422부산광역시 부산진구 범천로 22(범천동), 301호 관리사무소부산광역시 부산진구청부산진구2023-12-0135.148772129.056222
198실내주차장더블루2부산광역시 부산진구 서전로38번길 65(전포동) 관리사무소부산광역시 부산진구청부산진구2023-12-0135.154751129.064146
199실내주차장시청센트빌부산광역시 부산진구 중앙대로 981(양정동) 관리사무소부산광역시 부산진구청부산진구2023-12-0135.177387129.074114
200실내주차장부산 범일 로얄팰리스 2차부산광역시 부산진구 범일로 176(범천동), 2층 관리사무소부산광역시 부산진구청부산진구2023-12-0135.145668129.059682
201실내주차장주례초등학교 지하공영주차장부산광역시 부산진구 진사로61번길 28-7(개금동) 관리사무소부산광역시 부산진구청부산진구2023-12-0135.145797129.019452
202PC영업시설로떼PC부산광역시 부산진구 중앙대로 694, 쥬디스태화 401호부산광역시 부산진구청부산진구2023-12-0135.154727129.059602