Overview

Dataset statistics

Number of variables9
Number of observations110
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.3 KiB
Average record size in memory77.2 B

Variable types

Numeric3
Categorical3
Text2
DateTime1

Dataset

Description부산광역시서구_제설함배치정보_20230413
Author부산광역시 서구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15113387

Alerts

수량 has constant value ""Constant
관리기관(부서) has constant value ""Constant
데이터기준일자 has constant value ""Constant
관리번호 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
위도 is highly overall correlated with 관리번호 and 1 other fieldsHigh correlation
경도 is highly overall correlated with 행정동명High correlation
행정동명 is highly overall correlated with 관리번호 and 2 other fieldsHigh correlation
관리번호 has unique valuesUnique
설치장소 has unique valuesUnique

Reproduction

Analysis started2023-12-10 16:33:01.595763
Analysis finished2023-12-10 16:33:03.722893
Duration2.13 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct110
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean55.5
Minimum1
Maximum110
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T01:33:03.808213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.45
Q128.25
median55.5
Q382.75
95-th percentile104.55
Maximum110
Range109
Interquartile range (IQR)54.5

Descriptive statistics

Standard deviation31.898276
Coefficient of variation (CV)0.57474371
Kurtosis-1.2
Mean55.5
Median Absolute Deviation (MAD)27.5
Skewness0
Sum6105
Variance1017.5
MonotonicityStrictly increasing
2023-12-11T01:33:04.003875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.9%
71 1
 
0.9%
82 1
 
0.9%
81 1
 
0.9%
80 1
 
0.9%
79 1
 
0.9%
78 1
 
0.9%
77 1
 
0.9%
76 1
 
0.9%
75 1
 
0.9%
Other values (100) 100
90.9%
ValueCountFrequency (%)
1 1
0.9%
2 1
0.9%
3 1
0.9%
4 1
0.9%
5 1
0.9%
6 1
0.9%
7 1
0.9%
8 1
0.9%
9 1
0.9%
10 1
0.9%
ValueCountFrequency (%)
110 1
0.9%
109 1
0.9%
108 1
0.9%
107 1
0.9%
106 1
0.9%
105 1
0.9%
104 1
0.9%
103 1
0.9%
102 1
0.9%
101 1
0.9%

행정동명
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)11.8%
Missing0
Missing (%)0.0%
Memory size1012.0 B
암남동
29 
서대신4동
19 
아미동
13 
동대신3동
11 
남부민2동
8 
Other values (8)
30 

Length

Max length5
Median length5
Mean length4.1090909
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row동대신1동
2nd row동대신1동
3rd row동대신1동
4th row동대신1동
5th row동대신1동

Common Values

ValueCountFrequency (%)
암남동 29
26.4%
서대신4동 19
17.3%
아미동 13
11.8%
동대신3동 11
 
10.0%
남부민2동 8
 
7.3%
서대신1동 7
 
6.4%
동대신1동 6
 
5.5%
동대신2동 4
 
3.6%
서대신3동 4
 
3.6%
초장동 3
 
2.7%
Other values (3) 6
 
5.5%

Length

2023-12-11T01:33:04.212368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
암남동 29
26.4%
서대신4동 19
17.3%
아미동 13
11.8%
동대신3동 11
 
10.0%
남부민2동 8
 
7.3%
서대신1동 7
 
6.4%
동대신1동 6
 
5.5%
동대신2동 4
 
3.6%
서대신3동 4
 
3.6%
초장동 3
 
2.7%
Other values (3) 6
 
5.5%

설치장소
Text

UNIQUE 

Distinct110
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1012.0 B
2023-12-11T01:33:04.565684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length22
Mean length13.736364
Min length4

Characters and Unicode

Total characters1511
Distinct characters244
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique110 ?
Unique (%)100.0%

Sample

1st row동대맨션 한양옷집 앞
2nd row보동길 178 맞은편
3rd row보동길 162-1 앞
4th row로또판매센터 맞은편
5th row옹벽 앞
ValueCountFrequency (%)
앞 48
 
13.3%
맞은편 19
 
5.3%
입구 18
 
5.0%
옆 15
 
4.2%
밑 11
 
3.0%
게시판 5
 
1.4%
구덕기상관측소 4
 
1.1%
화단 4
 
1.1%
횡단보도 4
 
1.1%
아래 3
 
0.8%
Other values (198) 230
63.7%
2023-12-11T01:33:05.121116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
252
 
16.7%
앞 50
 
3.3%
로 36
 
2.4%
구 34
 
2.3%
1 27
 
1.8%
입 24
 
1.6%
장 22
 
1.5%
대 21
 
1.4%
편 21
 
1.4%
은 20
 
1.3%
Other values (234) 1004
66.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1093
72.3%
Space Separator 252
 
16.7%
Decimal Number 106
 
7.0%
Open Punctuation 15
 
1.0%
Close Punctuation 15
 
1.0%
Dash Punctuation 15
 
1.0%
Uppercase Letter 12
 
0.8%
Math Symbol 1
 
0.1%
Lowercase Letter 1
 
0.1%
Other Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
앞 50
 
4.6%
로 36
 
3.3%
구 34
 
3.1%
입 24
 
2.2%
장 22
 
2.0%
대 21
 
1.9%
편 21
 
1.9%
은 20
 
1.8%
맞 20
 
1.8%
동 18
 
1.6%
Other values (209) 827
75.7%
Decimal Number
ValueCountFrequency (%)
1 27
25.5%
2 15
14.2%
8 14
13.2%
3 11
10.4%
5 9
 
8.5%
0 8
 
7.5%
9 8
 
7.5%
7 6
 
5.7%
4 4
 
3.8%
6 4
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
A 3
25.0%
P 2
16.7%
T 2
16.7%
U 1
 
8.3%
C 1
 
8.3%
B 1
 
8.3%
G 1
 
8.3%
S 1
 
8.3%
Space Separator
ValueCountFrequency (%)
252
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
m 1
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1094
72.4%
Common 404
 
26.7%
Latin 13
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
앞 50
 
4.6%
로 36
 
3.3%
구 34
 
3.1%
입 24
 
2.2%
장 22
 
2.0%
대 21
 
1.9%
편 21
 
1.9%
은 20
 
1.8%
맞 20
 
1.8%
동 18
 
1.6%
Other values (210) 828
75.7%
Common
ValueCountFrequency (%)
252
62.4%
1 27
 
6.7%
( 15
 
3.7%
) 15
 
3.7%
- 15
 
3.7%
2 15
 
3.7%
8 14
 
3.5%
3 11
 
2.7%
5 9
 
2.2%
0 8
 
2.0%
Other values (5) 23
 
5.7%
Latin
ValueCountFrequency (%)
A 3
23.1%
P 2
15.4%
T 2
15.4%
U 1
 
7.7%
C 1
 
7.7%
m 1
 
7.7%
B 1
 
7.7%
G 1
 
7.7%
S 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1093
72.3%
ASCII 417
 
27.6%
None 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
252
60.4%
1 27
 
6.5%
( 15
 
3.6%
) 15
 
3.6%
- 15
 
3.6%
2 15
 
3.6%
8 14
 
3.4%
3 11
 
2.6%
5 9
 
2.2%
0 8
 
1.9%
Other values (14) 36
 
8.6%
Hangul
ValueCountFrequency (%)
앞 50
 
4.6%
로 36
 
3.3%
구 34
 
3.1%
입 24
 
2.2%
장 22
 
2.0%
대 21
 
1.9%
편 21
 
1.9%
은 20
 
1.8%
맞 20
 
1.8%
동 18
 
1.6%
Other values (209) 827
75.7%
None
ValueCountFrequency (%)
㈜ 1
100.0%

소재지도로명주소
Text

Distinct95
Distinct (%)86.4%
Missing0
Missing (%)0.0%
Memory size1012.0 B
2023-12-11T01:33:05.545700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length23
Mean length16.890909
Min length13

Characters and Unicode

Total characters1858
Distinct characters67
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

Unique86 ?
Unique (%)78.2%

Sample

1st row부산광역시 서구 대영로 78
2nd row부산광역시 서구 보동길 178
3rd row부산광역시 서구 보동길 162-1
4th row부산광역시 서구 대영로 94-1
5th row부산광역시 서구 보동길 236
ValueCountFrequency (%)
부산광역시 110
25.8%
서구 110
25.8%
해돋이로 11
 
2.6%
꽃마을로 8
 
1.9%
감천로 7
 
1.6%
암남공원로 5
 
1.2%
충무대로 5
 
1.2%
망양로 5
 
1.2%
보동길 5
 
1.2%
꽃마을로163번길 5
 
1.2%
Other values (118) 156
36.5%
2023-12-11T01:33:06.043936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
317
17.1%
산 117
 
6.3%
시 114
 
6.1%
부 112
 
6.0%
광 112
 
6.0%
구 111
 
6.0%
역 110
 
5.9%
서 110
 
5.9%
로 105
 
5.7%
1 76
 
4.1%
Other values (57) 574
30.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1223
65.8%
Space Separator 317
 
17.1%
Decimal Number 302
 
16.3%
Dash Punctuation 16
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 117
9.6%
시 114
9.3%
부 112
 
9.2%
광 112
 
9.2%
구 111
 
9.1%
역 110
 
9.0%
서 110
 
9.0%
로 105
 
8.6%
길 27
 
2.2%
번 22
 
1.8%
Other values (45) 283
23.1%
Decimal Number
ValueCountFrequency (%)
1 76
25.2%
2 43
14.2%
3 31
10.3%
7 26
 
8.6%
8 26
 
8.6%
6 24
 
7.9%
5 23
 
7.6%
9 19
 
6.3%
0 18
 
6.0%
4 16
 
5.3%
Space Separator
ValueCountFrequency (%)
317
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1223
65.8%
Common 635
34.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 117
9.6%
시 114
9.3%
부 112
 
9.2%
광 112
 
9.2%
구 111
 
9.1%
역 110
 
9.0%
서 110
 
9.0%
로 105
 
8.6%
길 27
 
2.2%
번 22
 
1.8%
Other values (45) 283
23.1%
Common
ValueCountFrequency (%)
317
49.9%
1 76
 
12.0%
2 43
 
6.8%
3 31
 
4.9%
7 26
 
4.1%
8 26
 
4.1%
6 24
 
3.8%
5 23
 
3.6%
9 19
 
3.0%
0 18
 
2.8%
Other values (2) 32
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1223
65.8%
ASCII 635
34.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
317
49.9%
1 76
 
12.0%
2 43
 
6.8%
3 31
 
4.9%
7 26
 
4.1%
8 26
 
4.1%
6 24
 
3.8%
5 23
 
3.6%
9 19
 
3.0%
0 18
 
2.8%
Other values (2) 32
 
5.0%
Hangul
ValueCountFrequency (%)
산 117
9.6%
시 114
9.3%
부 112
 
9.2%
광 112
 
9.2%
구 111
 
9.1%
역 110
 
9.0%
서 110
 
9.0%
로 105
 
8.6%
길 27
 
2.2%
번 22
 
1.8%
Other values (45) 283
23.1%

수량
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1012.0 B
1
110 

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 (%)
1 110
100.0%

Length

2023-12-11T01:33:06.171360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:33:06.266093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 110
100.0%

관리기관(부서)
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1012.0 B
서구청(구민안전과)
110 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서구청(구민안전과)
2nd row서구청(구민안전과)
3rd row서구청(구민안전과)
4th row서구청(구민안전과)
5th row서구청(구민안전과)

Common Values

ValueCountFrequency (%)
서구청(구민안전과) 110
100.0%

Length

2023-12-11T01:33:06.368593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:33:06.458974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서구청(구민안전과 110
100.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1012.0 B
Minimum2023-04-13 00:00:00
Maximum2023-04-13 00:00:00
2023-12-11T01:33:06.540392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:33:06.631577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct101
Distinct (%)91.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.101176
Minimum35.062505
Maximum35.193908
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T01:33:06.764471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.062505
5-th percentile35.06317
Q135.083007
median35.10175
Q335.11668
95-th percentile35.127837
Maximum35.193908
Range0.1314031
Interquartile range (IQR)0.033673675

Descriptive statistics

Standard deviation0.020725735
Coefficient of variation (CV)0.00059045699
Kurtosis2.2636684
Mean35.101176
Median Absolute Deviation (MAD)0.0172565
Skewness0.48185356
Sum3861.1294
Variance0.00042955609
MonotonicityNot monotonic
2023-12-11T01:33:06.918101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.08 3
 
2.7%
35.10175 2
 
1.8%
35.0807796 2
 
1.8%
35.1278372 2
 
1.8%
35.0627028 2
 
1.8%
35.0625049 2
 
1.8%
35.0629 2
 
1.8%
35.12 2
 
1.8%
35.099659 1
 
0.9%
35.0842811 1
 
0.9%
Other values (91) 91
82.7%
ValueCountFrequency (%)
35.0625049 2
1.8%
35.0627028 2
1.8%
35.0629 2
1.8%
35.0635 1
0.9%
35.0723995 1
0.9%
35.0756964 1
0.9%
35.0779059 1
0.9%
35.078607 1
0.9%
35.078617 1
0.9%
35.0788688 1
0.9%
ValueCountFrequency (%)
35.193908 1
0.9%
35.131002 1
0.9%
35.1298372 1
0.9%
35.1288372 1
0.9%
35.1286303 1
0.9%
35.1278372 2
1.8%
35.126161 1
0.9%
35.1253387 1
0.9%
35.1223372 1
0.9%
35.1219026 1
0.9%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct102
Distinct (%)92.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.01647
Minimum129.00488
Maximum129.0933
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T01:33:07.059802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum129.00488
5-th percentile129.00841
Q1129.01176
median129.01544
Q3129.01974
95-th percentile129.02413
Maximum129.0933
Range0.0884234
Interquartile range (IQR)0.007982425

Descriptive statistics

Standard deviation0.009031109
Coefficient of variation (CV)6.9999661 × 10-5
Kurtosis48.023312
Mean129.01647
Median Absolute Deviation (MAD)0.0040866
Skewness5.7262496
Sum14191.811
Variance8.1560931 × 10-5
MonotonicityNot monotonic
2023-12-11T01:33:07.509700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
129.0152358 4
 
3.6%
129.0058161 3
 
2.7%
129.0111538 2
 
1.8%
129.014416 2
 
1.8%
129.0196969 2
 
1.8%
129.018635 1
 
0.9%
129.0176505 1
 
0.9%
129.0169497 1
 
0.9%
129.0206904 1
 
0.9%
129.0189031 1
 
0.9%
Other values (92) 92
83.6%
ValueCountFrequency (%)
129.0048766 1
 
0.9%
129.0058161 3
2.7%
129.0068161 1
 
0.9%
129.00826 1
 
0.9%
129.0085938 1
 
0.9%
129.0091847 1
 
0.9%
129.0093067 1
 
0.9%
129.009397 1
 
0.9%
129.0094225 1
 
0.9%
129.009452 1
 
0.9%
ValueCountFrequency (%)
129.0933 1
0.9%
129.0329 1
0.9%
129.026252 1
0.9%
129.0251 1
0.9%
129.024887 1
0.9%
129.0241526 1
0.9%
129.0241 1
0.9%
129.0238 1
0.9%
129.0232161 1
0.9%
129.023054 1
0.9%

Interactions

2023-12-11T01:33:03.036603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:33:02.247044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:33:02.645313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:33:03.134739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:33:02.370530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:33:02.776340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:33:03.267895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:33:02.518009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:33:02.913388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:33:07.617279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호행정동명소재지도로명주소위도경도
관리번호1.0000.9270.9540.8010.827
행정동명0.9271.0001.0000.8950.743
소재지도로명주소0.9541.0001.0000.9731.000
위도0.8010.8950.9731.0000.373
경도0.8270.7431.0000.3731.000
2023-12-11T01:33:07.711418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호위도경도행정동명
관리번호1.000-0.7960.0260.729
위도-0.7961.000-0.3050.677
경도0.026-0.3051.0000.504
행정동명0.7290.6770.5041.000

Missing values

2023-12-11T01:33:03.438372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:33:03.648349image/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

관리번호행정동명설치장소소재지도로명주소수량관리기관(부서)데이터기준일자위도경도
01동대신1동동대맨션 한양옷집 앞부산광역시 서구 대영로 781서구청(구민안전과)2023-04-1335.11033129.019719
12동대신1동보동길 178 맞은편부산광역시 서구 보동길 1781서구청(구민안전과)2023-04-1335.10999129.0329
23동대신1동보동길 162-1 앞부산광역시 서구 보동길 162-11서구청(구민안전과)2023-04-1335.10944129.0238
34동대신1동로또판매센터 맞은편부산광역시 서구 대영로 94-11서구청(구민안전과)2023-04-1335.11122129.0214
45동대신1동옹벽 앞부산광역시 서구 보동길 2361서구청(구민안전과)2023-04-1335.11247129.0251
56동대신1동아리랑빌라 앞부산광역시 서구 보동길 1911서구청(구민안전과)2023-04-1335.11072129.0241
67동대신2동전원빌라 맞은편 북산경로당 앞부산광역시 서구 중앙공원로 241서구청(구민안전과)2023-04-1335.115978129.024153
78동대신2동신익빌라 맞은편부산광역시 서구 보수대로 201번길 411서구청(구민안전과)2023-04-1335.113008129.024887
89동대신2동닥밭골 입구부산광역시 서구 보동길 2961서구청(구민안전과)2023-04-1335.11409129.023054
910동대신2동대청맨션부산광역시 서구 망양로193번길 101서구청(구민안전과)2023-04-1335.113393129.026252
관리번호행정동명설치장소소재지도로명주소수량관리기관(부서)데이터기준일자위도경도
100101암남동암남공원 진입로 시계탑 옆부산광역시 서구 암남공원로1서구청(구민안전과)2023-04-1335.062703129.019697
101102암남동예비군 교육장 중간(가로등 81-9)부산광역시 서구 장군산로1서구청(구민안전과)2023-04-1335.0629129.015236
102103암남동송도태경시티빌 앞부산광역시 서구 충무대로 761서구청(구민안전과)2023-04-1335.078927129.02082
103104암남동삼경빌라 앞부산광역시 서구 감천로 2771서구청(구민안전과)2023-04-1335.08129.018201
104105암남동암남동주민센터 앞 버스정류장부산광역시 서구 충무대로831서구청(구민안전과)2023-04-1335.08129.021136
105106암남동고신대병원 교직원주차장 앞부산광역시 서구 감천로 2621서구청(구민안전과)2023-04-1335.080874129.014335
106107암남동암남로78번길 31 사거리 반사경 밑부산광역시 서구 암남로78번길 311서구청(구민안전과)2023-04-1335.078617129.012404
107108암남동삼정하이빌 맞은편부산광역시 서구 암남로78번길 461서구청(구민안전과)2023-04-1335.079129.012001
108109암남동암남로58번길 20-1 맞은편 전신주 아래부산광역시 서구 암남로58번길 20-11서구청(구민안전과)2023-04-1335.078607129.012758
109110암남동충무대로83번길 59 골목길 모퉁이부산광역시 서구 충무대로83번길 591서구청(구민안전과)2023-04-1335.081358129.023026