Overview

Dataset statistics

Number of variables10
Number of observations30
Missing cells30
Missing cells (%)10.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.6 KiB
Average record size in memory88.4 B

Variable types

Categorical4
Text2
Unsupported1
Numeric2
DateTime1

Dataset

Description부산광역시 수영구 인명구조함 정보로 인명구조함의 위치, 구성품, 개수, 주소, 위도, 경도, 관리부서, 데이터기준일자 정보를 제공하고 있습니다.
Author공공데이터포털
URLhttps://www.data.go.kr/data/15117178/fileData.do

Alerts

구군명 has constant value ""Constant
개수 has constant value ""Constant
관리부서 has constant value ""Constant
데이터기준일자 has constant value ""Constant
위도 is highly overall correlated with 경도High correlation
경도 is highly overall correlated with 위도High correlation
도로명주소 has 30 (100.0%) missing valuesMissing
위치 has unique valuesUnique
도로명주소 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-17 18:10:06.304406
Analysis finished2024-04-17 18:10:06.980447
Duration0.68 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구군명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
부산광역시 수영구
30 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부산광역시 수영구 30
100.0%

Length

2024-04-18T03:10:07.040198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:10:07.108849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 30
50.0%
수영구 30
50.0%

위치
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-04-18T03:10:07.246471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length19
Mean length15.566667
Min length7

Characters and Unicode

Total characters467
Distinct characters135
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

Unique30 ?
Unique (%)100.0%

Sample

1st row광안대교 옆 분포교 앞
2nd row광안대교 옆 방파제 앞
3rd row광안대교 하부
4th row메가마트 남천점 앞 곡각지점
5th row남천항 방파제 끝
ValueCountFrequency (%)
앞 20
 
17.5%
방파제 6
 
5.3%
하부 6
 
5.3%
갈맷길 5
 
4.4%
삼익비치 4
 
3.5%
수변공원 4
 
3.5%
옆 3
 
2.6%
과정교 3
 
2.6%
광안대교 3
 
2.6%
민락항 3
 
2.6%
Other values (49) 57
50.0%
2024-04-18T03:10:07.737479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
84
 
18.0%
앞 20
 
4.3%
광 10
 
2.1%
동 10
 
2.1%
변 10
 
2.1%
1 10
 
2.1%
교 10
 
2.1%
수 9
 
1.9%
안 8
 
1.7%
부 8
 
1.7%
Other values (125) 288
61.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 327
70.0%
Space Separator 84
 
18.0%
Decimal Number 31
 
6.6%
Close Punctuation 7
 
1.5%
Open Punctuation 7
 
1.5%
Uppercase Letter 6
 
1.3%
Lowercase Letter 2
 
0.4%
Dash Punctuation 2
 
0.4%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
앞 20
 
6.1%
광 10
 
3.1%
동 10
 
3.1%
변 10
 
3.1%
교 10
 
3.1%
수 9
 
2.8%
안 8
 
2.4%
부 8
 
2.4%
길 7
 
2.1%
방 7
 
2.1%
Other values (105) 228
69.7%
Decimal Number
ValueCountFrequency (%)
1 10
32.3%
2 6
19.4%
0 6
19.4%
3 3
 
9.7%
5 2
 
6.5%
9 1
 
3.2%
8 1
 
3.2%
6 1
 
3.2%
7 1
 
3.2%
Uppercase Letter
ValueCountFrequency (%)
S 2
33.3%
K 1
16.7%
C 1
16.7%
U 1
16.7%
G 1
16.7%
Space Separator
ValueCountFrequency (%)
84
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 327
70.0%
Common 132
28.3%
Latin 8
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
앞 20
 
6.1%
광 10
 
3.1%
동 10
 
3.1%
변 10
 
3.1%
교 10
 
3.1%
수 9
 
2.8%
안 8
 
2.4%
부 8
 
2.4%
길 7
 
2.1%
방 7
 
2.1%
Other values (105) 228
69.7%
Common
ValueCountFrequency (%)
84
63.6%
1 10
 
7.6%
) 7
 
5.3%
( 7
 
5.3%
2 6
 
4.5%
0 6
 
4.5%
3 3
 
2.3%
- 2
 
1.5%
5 2
 
1.5%
9 1
 
0.8%
Other values (4) 4
 
3.0%
Latin
ValueCountFrequency (%)
S 2
25.0%
e 2
25.0%
K 1
12.5%
C 1
12.5%
U 1
12.5%
G 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 327
70.0%
ASCII 140
30.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
84
60.0%
1 10
 
7.1%
) 7
 
5.0%
( 7
 
5.0%
2 6
 
4.3%
0 6
 
4.3%
3 3
 
2.1%
S 2
 
1.4%
e 2
 
1.4%
- 2
 
1.4%
Other values (10) 11
 
7.9%
Hangul
ValueCountFrequency (%)
앞 20
 
6.1%
광 10
 
3.1%
동 10
 
3.1%
변 10
 
3.1%
교 10
 
3.1%
수 9
 
2.8%
안 8
 
2.4%
부 8
 
2.4%
길 7
 
2.1%
방 7
 
2.1%
Other values (105) 228
69.7%

구성품
Categorical

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
보관함+ 구명환+ 구명로프+ 구명조끼
21 
거치대+ 구명환+ 구명로프
5 
보관함+ 구명환+ 구명로프+ 구명조끼+ 구급함
4 

Length

Max length25
Median length20
Mean length19.666667
Min length14

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row보관함+ 구명환+ 구명로프+ 구명조끼
2nd row보관함+ 구명환+ 구명로프+ 구명조끼
3rd row보관함+ 구명환+ 구명로프+ 구명조끼
4th row보관함+ 구명환+ 구명로프+ 구명조끼
5th row보관함+ 구명환+ 구명로프+ 구명조끼

Common Values

ValueCountFrequency (%)
보관함+ 구명환+ 구명로프+ 구명조끼 21
70.0%
거치대+ 구명환+ 구명로프 5
 
16.7%
보관함+ 구명환+ 구명로프+ 구명조끼+ 구급함 4
 
13.3%

Length

2024-04-18T03:10:07.836635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:10:07.911429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
구명환 30
25.2%
구명로프 30
25.2%
보관함 25
21.0%
구명조끼 25
21.0%
거치대 5
 
4.2%
구급함 4
 
3.4%

개수
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
1
30 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 30
100.0%

Length

2024-04-18T03:10:07.994936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:10:08.079352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 30
100.0%

도로명주소
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

지번주소
Text

Distinct23
Distinct (%)76.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-04-18T03:10:08.197529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length24
Mean length19.633333
Min length17

Characters and Unicode

Total characters589
Distinct characters39
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)66.7%

Sample

1st row부산광역시 남구 대연3동 광안대교 옆 분포교 앞
2nd row부산광역시 남구 대연3동 광안대교 옆 방파제
3rd row부산광역시 남구 대연3동 광안대교 하부
4th row부산광역시 수영구 남천동 564
5th row부산광역시 수영구 남천동 148-93
ValueCountFrequency (%)
부산광역시 30
23.8%
수영구 27
21.4%
민락동 11
 
8.7%
남천동 7
 
5.6%
망미동 5
 
4.0%
110-19 4
 
3.2%
113-52 3
 
2.4%
148-93 3
 
2.4%
남구 3
 
2.4%
대연3동 3
 
2.4%
Other values (25) 30
23.8%
2024-04-18T03:10:08.475340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
97
16.5%
1 38
 
6.5%
광 35
 
5.9%
부 31
 
5.3%
구 30
 
5.1%
동 30
 
5.1%
산 30
 
5.1%
시 30
 
5.1%
역 30
 
5.1%
영 29
 
4.9%
Other values (29) 209
35.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 350
59.4%
Decimal Number 121
 
20.5%
Space Separator 97
 
16.5%
Dash Punctuation 21
 
3.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 35
10.0%
부 31
8.9%
구 30
8.6%
동 30
8.6%
산 30
8.6%
시 30
8.6%
역 30
8.6%
영 29
8.3%
수 29
8.3%
락 11
 
3.1%
Other values (17) 65
18.6%
Decimal Number
ValueCountFrequency (%)
1 38
31.4%
3 16
13.2%
8 14
 
11.6%
4 11
 
9.1%
2 10
 
8.3%
5 9
 
7.4%
9 8
 
6.6%
0 8
 
6.6%
6 4
 
3.3%
7 3
 
2.5%
Space Separator
ValueCountFrequency (%)
97
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 350
59.4%
Common 239
40.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 35
10.0%
부 31
8.9%
구 30
8.6%
동 30
8.6%
산 30
8.6%
시 30
8.6%
역 30
8.6%
영 29
8.3%
수 29
8.3%
락 11
 
3.1%
Other values (17) 65
18.6%
Common
ValueCountFrequency (%)
97
40.6%
1 38
 
15.9%
- 21
 
8.8%
3 16
 
6.7%
8 14
 
5.9%
4 11
 
4.6%
2 10
 
4.2%
5 9
 
3.8%
9 8
 
3.3%
0 8
 
3.3%
Other values (2) 7
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 350
59.4%
ASCII 239
40.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
97
40.6%
1 38
 
15.9%
- 21
 
8.8%
3 16
 
6.7%
8 14
 
5.9%
4 11
 
4.6%
2 10
 
4.2%
5 9
 
3.8%
9 8
 
3.3%
0 8
 
3.3%
Other values (2) 7
 
2.9%
Hangul
ValueCountFrequency (%)
광 35
10.0%
부 31
8.9%
구 30
8.6%
동 30
8.6%
산 30
8.6%
시 30
8.6%
역 30
8.6%
영 29
8.3%
수 29
8.3%
락 11
 
3.1%
Other values (17) 65
18.6%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct23
Distinct (%)76.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.154635
Minimum35.133012
Maximum35.185632
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-04-18T03:10:08.571997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.133012
5-th percentile35.136503
Q135.142735
median35.153449
Q335.160141
95-th percentile35.179325
Maximum35.185632
Range0.05262037
Interquartile range (IQR)0.017406235

Descriptive statistics

Standard deviation0.013939316
Coefficient of variation (CV)0.00039651432
Kurtosis-0.29427361
Mean35.154635
Median Absolute Deviation (MAD)0.010588775
Skewness0.61410119
Sum1054.6391
Variance0.00019430454
MonotonicityNot monotonic
2024-04-18T03:10:08.679903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
35.15562196 4
 
13.3%
35.14261019 3
 
10.0%
35.15282 3
 
10.0%
35.133012 1
 
3.3%
35.16725861 1
 
3.3%
35.15342773 1
 
3.3%
35.14713109 1
 
3.3%
35.14614438 1
 
3.3%
35.18563237 1
 
3.3%
35.18140109 1
 
3.3%
Other values (13) 13
43.3%
ValueCountFrequency (%)
35.133012 1
 
3.3%
35.135814 1
 
3.3%
35.13734425 1
 
3.3%
35.137881 1
 
3.3%
35.14233192 1
 
3.3%
35.14261019 3
10.0%
35.14310934 1
 
3.3%
35.14614438 1
 
3.3%
35.14713109 1
 
3.3%
35.15282 3
10.0%
ValueCountFrequency (%)
35.18563237 1
 
3.3%
35.18140109 1
 
3.3%
35.17678863 1
 
3.3%
35.17623621 1
 
3.3%
35.17388246 1
 
3.3%
35.16725861 1
 
3.3%
35.16717453 1
 
3.3%
35.16130799 1
 
3.3%
35.15664088 1
 
3.3%
35.15562196 4
13.3%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct23
Distinct (%)76.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.12249
Minimum129.11285
Maximum129.13482
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-04-18T03:10:08.768725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum129.11285
5-th percentile129.11323
Q1129.11647
median129.1189
Q3129.12815
95-th percentile129.13482
Maximum129.13482
Range0.0219737
Interquartile range (IQR)0.0116756

Descriptive statistics

Standard deviation0.0075918647
Coefficient of variation (CV)5.8795835 × 10-5
Kurtosis-1.3007924
Mean129.12249
Median Absolute Deviation (MAD)0.005455
Skewness0.46051668
Sum3873.6747
Variance5.7636409 × 10-5
MonotonicityNot monotonic
2024-04-18T03:10:08.863790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
129.1348192 4
 
13.3%
129.1176435 3
 
10.0%
129.1281466 3
 
10.0%
129.1161 1
 
3.3%
129.124338 1
 
3.3%
129.1186916 1
 
3.3%
129.1144878 1
 
3.3%
129.1153256 1
 
3.3%
129.1158107 1
 
3.3%
129.1177131 1
 
3.3%
Other values (13) 13
43.3%
ValueCountFrequency (%)
129.1128455 1
 
3.3%
129.113072 1
 
3.3%
129.113428 1
 
3.3%
129.1144878 1
 
3.3%
129.1150407 1
 
3.3%
129.1153256 1
 
3.3%
129.1158107 1
 
3.3%
129.1161 1
 
3.3%
129.117584 1
 
3.3%
129.1176435 3
10.0%
ValueCountFrequency (%)
129.1348192 4
13.3%
129.1334716 1
 
3.3%
129.1307332 1
 
3.3%
129.1305897 1
 
3.3%
129.1281466 3
10.0%
129.1265677 1
 
3.3%
129.1248562 1
 
3.3%
129.124338 1
 
3.3%
129.1201542 1
 
3.3%
129.1191169 1
 
3.3%

관리부서
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
안전관리과
30 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
안전관리과 30
100.0%

Length

2024-04-18T03:10:08.960128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:10:09.030350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
안전관리과 30
100.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2023-07-20 00:00:00
Maximum2023-07-20 00:00:00
2024-04-18T03:10:09.094392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T03:10:09.160182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-04-18T03:10:06.684361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T03:10:06.537121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T03:10:06.745748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T03:10:06.608451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-18T03:10:09.214934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위치구성품지번주소위도경도
위치1.0001.0001.0001.0001.000
구성품1.0001.0000.9000.6470.352
지번주소1.0000.9001.0001.0001.000
위도1.0000.6471.0001.0000.894
경도1.0000.3521.0000.8941.000
2024-04-18T03:10:09.285465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도구성품
위도1.0000.5350.416
경도0.5351.0000.229
구성품0.4160.2291.000

Missing values

2024-04-18T03:10:06.837364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-18T03:10:06.940458image/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

구군명위치구성품개수도로명주소지번주소위도경도관리부서데이터기준일자
0부산광역시 수영구광안대교 옆 분포교 앞보관함+ 구명환+ 구명로프+ 구명조끼1<NA>부산광역시 남구 대연3동 광안대교 옆 분포교 앞35.133012129.1161안전관리과2023-07-20
1부산광역시 수영구광안대교 옆 방파제 앞보관함+ 구명환+ 구명로프+ 구명조끼1<NA>부산광역시 남구 대연3동 광안대교 옆 방파제35.137881129.113428안전관리과2023-07-20
2부산광역시 수영구광안대교 하부보관함+ 구명환+ 구명로프+ 구명조끼1<NA>부산광역시 남구 대연3동 광안대교 하부35.135814129.113072안전관리과2023-07-20
3부산광역시 수영구메가마트 남천점 앞 곡각지점보관함+ 구명환+ 구명로프+ 구명조끼1<NA>부산광역시 수영구 남천동 56435.137344129.112845안전관리과2023-07-20
4부산광역시 수영구남천항 방파제 끝보관함+ 구명환+ 구명로프+ 구명조끼1<NA>부산광역시 수영구 남천동 148-9335.14261129.117644안전관리과2023-07-20
5부산광역시 수영구남천항 방파제 시작부보관함+ 구명환+ 구명로프+ 구명조끼1<NA>부산광역시 수영구 남천동 148-9335.14261129.117644안전관리과2023-07-20
6부산광역시 수영구삼익비치 216동 앞보관함+ 구명환+ 구명로프+ 구명조끼1<NA>부산광역시 수영구 남천동 148-835.142332129.115041안전관리과2023-07-20
7부산광역시 수영구삼익비치 308동 앞보관함+ 구명환+ 구명로프+ 구명조끼+ 구급함1<NA>부산광역시 수영구 남천동 148-1335.143109129.117584안전관리과2023-07-20
8부산광역시 수영구삼익비치 301동 앞 방파제보관함+ 구명환+ 구명로프+ 구명조끼1<NA>부산광역시 수영구 남천동 148-9335.14261129.117644안전관리과2023-07-20
9부산광역시 수영구부산횟집 앞 방파제보관함+ 구명환+ 구명로프+ 구명조끼+ 구급함1<NA>부산광역시 수영구 민락동 181-7835.154284129.126568안전관리과2023-07-20
구군명위치구성품개수도로명주소지번주소위도경도관리부서데이터기준일자
20부산광역시 수영구좌수영교 인근 광장데크(중간지역) 하부 갈맷길거치대+ 구명환+ 구명로프1<NA>부산광역시 수영구 수영동 54635.167259129.124338안전관리과2023-07-20
21부산광역시 수영구좌수영교 인근 갈맷길보관함+ 구명환+ 구명로프+ 구명조끼1<NA>부산광역시 수영구 망미동 238-535.173882129.120154안전관리과2023-07-20
22부산광역시 수영구SK주유소 길건너 데크 광장 옆보관함+ 구명환+ 구명로프+ 구명조끼1<NA>부산광역시 수영구 망미동 68-235.176789129.118144안전관리과2023-07-20
23부산광역시 수영구과정교 하부 갈맷길 (수영강변 1차 e-편한세상 101동 앞)거치대+ 구명환+ 구명로프1<NA>부산광역시 수영구 망미동 98535.176236129.119117안전관리과2023-07-20
24부산광역시 수영구과정교 하부 갈맷길 (수영강변 2차 e-편한세상 201동 앞)보관함+ 구명환+ 구명로프+ 구명조끼1<NA>부산광역시 수영구 망미동 114135.181401129.117713안전관리과2023-07-20
25부산광역시 수영구과정교 하부 갈맷길(망미동 방재창고 앞)거치대+ 구명환+ 구명로프1<NA>부산광역시 수영구 망미동 108235.185632129.115811안전관리과2023-07-20
26부산광역시 수영구삼익비치 301동 앞 남천해변공원보관함+ 구명환+ 구명로프+ 구명조끼1<NA>부산광역시 수영구 남천동 148-10335.146144129.115326안전관리과2023-07-20
27부산광역시 수영구광안해변로CU광안오션점 맞은편 데크보관함+ 구명환+ 구명로프+ 구명조끼1<NA>부산광역시 수영구 민락동 113-5235.15282129.128147안전관리과2023-07-20
28부산광역시 수영구광안동GS25(광안해변로159) 앞보관함+ 구명환+ 구명로프+ 구명조끼1<NA>부산광역시 수영구 광안동 282-335.147131129.114488안전관리과2023-07-20
29부산광역시 수영구호메르스호텔(광안해변로 217) 앞보관함+ 구명환+ 구명로프+ 구명조끼1<NA>부산광역시 수영구 광안동 1306-235.153428129.118692안전관리과2023-07-20