Overview

Dataset statistics

Number of variables12
Number of observations980
Missing cells70
Missing cells (%)0.6%
Duplicate rows5
Duplicate rows (%)0.5%
Total size in memory96.8 KiB
Average record size in memory101.1 B

Variable types

Categorical7
Text2
Numeric3

Dataset

Description부산광역시 부산진구 관내에 설치된 방범용 CCTV 카메라 현황데이터이며, 소재지 주소, 위도, 경도, 설치목적, 영상보관일수 등의 데이터입니다.
Author부산광역시 부산진구
URLhttps://www.data.go.kr/data/15092265/fileData.do

Alerts

관리기관명 has constant value ""Constant
설치목적구분 has constant value ""Constant
카메라화소수 has constant value ""Constant
촬영방면정보 has constant value ""Constant
보관일수 has constant value ""Constant
관리기관전화번호 has constant value ""Constant
데이터기준일자 has constant value ""Constant
Dataset has 5 (0.5%) duplicate rowsDuplicates
소재지도로명주소 has 65 (6.6%) missing valuesMissing
위도 is highly skewed (γ1 = 29.87518313)Skewed
경도 is highly skewed (γ1 = -27.80141312)Skewed

Reproduction

Analysis started2023-12-12 04:38:45.503368
Analysis finished2023-12-12 04:38:47.609002
Duration2.11 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.8 KiB
부산광역시 부산진구청
980 

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 980
100.0%

Length

2023-12-12T13:38:47.672344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:38:47.778617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 980
50.0%
부산진구청 980
50.0%

소재지도로명주소
Text

MISSING 

Distinct885
Distinct (%)96.7%
Missing65
Missing (%)6.6%
Memory size7.8 KiB
2023-12-12T13:38:48.085502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length25
Mean length21.382514
Min length16

Characters and Unicode

Total characters19565
Distinct characters102
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

Unique871 ?
Unique (%)95.2%

Sample

1st row부산광역시 부산진구 신암로83번길 13
2nd row부산광역시 부산진구 동평로127번길 52
3rd row부산광역시 부산진구 동평로131번길 48
4th row부산광역시 부산진구 개금본동로66번길 11
5th row부산광역시 부산진구 가야대로703번길 16
ValueCountFrequency (%)
부산광역시 915
25.1%
부산진구 915
25.1%
엄광로 24
 
0.7%
15 18
 
0.5%
30 17
 
0.5%
14 17
 
0.5%
23 17
 
0.5%
16 16
 
0.4%
19 15
 
0.4%
7 15
 
0.4%
Other values (774) 1678
46.0%
2023-12-12T13:38:48.804651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2732
14.0%
부 1845
 
9.4%
산 1845
 
9.4%
진 982
 
5.0%
광 977
 
5.0%
시 923
 
4.7%
역 915
 
4.7%
구 915
 
4.7%
로 906
 
4.6%
1 698
 
3.6%
Other values (92) 6827
34.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12921
66.0%
Decimal Number 3762
 
19.2%
Space Separator 2732
 
14.0%
Dash Punctuation 150
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 1845
14.3%
산 1845
14.3%
진 982
7.6%
광 977
7.6%
시 923
7.1%
역 915
7.1%
구 915
7.1%
로 906
7.0%
번 693
 
5.4%
길 691
 
5.3%
Other values (80) 2229
17.3%
Decimal Number
ValueCountFrequency (%)
1 698
18.6%
2 484
12.9%
3 412
11.0%
4 368
9.8%
5 358
9.5%
7 328
8.7%
6 324
8.6%
8 281
7.5%
0 260
 
6.9%
9 249
 
6.6%
Space Separator
ValueCountFrequency (%)
2732
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 150
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12921
66.0%
Common 6644
34.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 1845
14.3%
산 1845
14.3%
진 982
7.6%
광 977
7.6%
시 923
7.1%
역 915
7.1%
구 915
7.1%
로 906
7.0%
번 693
 
5.4%
길 691
 
5.3%
Other values (80) 2229
17.3%
Common
ValueCountFrequency (%)
2732
41.1%
1 698
 
10.5%
2 484
 
7.3%
3 412
 
6.2%
4 368
 
5.5%
5 358
 
5.4%
7 328
 
4.9%
6 324
 
4.9%
8 281
 
4.2%
0 260
 
3.9%
Other values (2) 399
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12921
66.0%
ASCII 6644
34.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2732
41.1%
1 698
 
10.5%
2 484
 
7.3%
3 412
 
6.2%
4 368
 
5.5%
5 358
 
5.4%
7 328
 
4.9%
6 324
 
4.9%
8 281
 
4.2%
0 260
 
3.9%
Other values (2) 399
 
6.0%
Hangul
ValueCountFrequency (%)
부 1845
14.3%
산 1845
14.3%
진 982
7.6%
광 977
7.6%
시 923
7.1%
역 915
7.1%
구 915
7.1%
로 906
7.0%
번 693
 
5.4%
길 691
 
5.3%
Other values (80) 2229
17.3%

소재지지번주소
Text

Distinct927
Distinct (%)95.1%
Missing5
Missing (%)0.5%
Memory size7.8 KiB
2023-12-12T13:38:49.020910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length23
Mean length20.404103
Min length16

Characters and Unicode

Total characters19894
Distinct characters50
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique898 ?
Unique (%)92.1%

Sample

1st row부산광역시 부산진구 범천동 1252-70
2nd row부산광역시 부산진구 부암동 365-1
3rd row부산광역시 부산진구 부암동 320-143
4th row부산광역시 부산진구 개금동 412-13
5th row부산광역시 부산진구 당감동 71-8
ValueCountFrequency (%)
부산진구 974
24.8%
부산광역시 973
24.8%
전포동 133
 
3.4%
개금동 123
 
3.1%
당감동 118
 
3.0%
범천동 112
 
2.9%
가야동 105
 
2.7%
부암동 82
 
2.1%
양정동 78
 
2.0%
부전동 67
 
1.7%
Other values (936) 1162
29.6%
2023-12-12T13:38:49.379875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2953
14.8%
부 2103
 
10.6%
산 1997
 
10.0%
광 978
 
4.9%
역 975
 
4.9%
시 975
 
4.9%
진 975
 
4.9%
구 975
 
4.9%
동 969
 
4.9%
- 872
 
4.4%
Other values (40) 6122
30.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11761
59.1%
Decimal Number 4307
 
21.6%
Space Separator 2953
 
14.8%
Dash Punctuation 872
 
4.4%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 2103
17.9%
산 1997
17.0%
광 978
8.3%
역 975
8.3%
시 975
8.3%
진 975
8.3%
구 975
8.3%
동 969
8.2%
전 229
 
1.9%
범 140
 
1.2%
Other values (27) 1445
12.3%
Decimal Number
ValueCountFrequency (%)
1 744
17.3%
3 564
13.1%
2 550
12.8%
4 446
10.4%
6 415
9.6%
5 386
9.0%
7 348
8.1%
8 333
7.7%
9 267
 
6.2%
0 254
 
5.9%
Space Separator
ValueCountFrequency (%)
2953
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 872
100.0%
Other Punctuation
ValueCountFrequency (%)
? 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11761
59.1%
Common 8133
40.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 2103
17.9%
산 1997
17.0%
광 978
8.3%
역 975
8.3%
시 975
8.3%
진 975
8.3%
구 975
8.3%
동 969
8.2%
전 229
 
1.9%
범 140
 
1.2%
Other values (27) 1445
12.3%
Common
ValueCountFrequency (%)
2953
36.3%
- 872
 
10.7%
1 744
 
9.1%
3 564
 
6.9%
2 550
 
6.8%
4 446
 
5.5%
6 415
 
5.1%
5 386
 
4.7%
7 348
 
4.3%
8 333
 
4.1%
Other values (3) 522
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11761
59.1%
ASCII 8133
40.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2953
36.3%
- 872
 
10.7%
1 744
 
9.1%
3 564
 
6.9%
2 550
 
6.8%
4 446
 
5.5%
6 415
 
5.1%
5 386
 
4.7%
7 348
 
4.3%
8 333
 
4.1%
Other values (3) 522
 
6.4%
Hangul
ValueCountFrequency (%)
부 2103
17.9%
산 1997
17.0%
광 978
8.3%
역 975
8.3%
시 975
8.3%
진 975
8.3%
구 975
8.3%
동 969
8.2%
전 229
 
1.9%
범 140
 
1.2%
Other values (27) 1445
12.3%

설치목적구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.8 KiB
생활방범
980 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
생활방범 980
100.0%

Length

2023-12-12T13:38:49.533412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:38:49.647127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
생활방범 980
100.0%

카메라대수
Real number (ℝ)

Distinct6
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.6357143
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.7 KiB
2023-12-12T13:38:49.784953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile4
Maximum6
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.0468836
Coefficient of variation (CV)0.64001617
Kurtosis1.0066402
Mean1.6357143
Median Absolute Deviation (MAD)0
Skewness1.4656673
Sum1603
Variance1.0959653
MonotonicityNot monotonic
2023-12-12T13:38:49.957935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 666
68.0%
3 125
 
12.8%
2 104
 
10.6%
4 72
 
7.3%
5 12
 
1.2%
6 1
 
0.1%
ValueCountFrequency (%)
1 666
68.0%
2 104
 
10.6%
3 125
 
12.8%
4 72
 
7.3%
5 12
 
1.2%
6 1
 
0.1%
ValueCountFrequency (%)
6 1
 
0.1%
5 12
 
1.2%
4 72
 
7.3%
3 125
 
12.8%
2 104
 
10.6%
1 666
68.0%

카메라화소수
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.8 KiB
200
980 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row200
2nd row200
3rd row200
4th row200
5th row200

Common Values

ValueCountFrequency (%)
200 980
100.0%

Length

2023-12-12T13:38:50.129047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:38:50.234724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
200 980
100.0%

촬영방면정보
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.8 KiB
360도전방면
980 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row360도전방면
2nd row360도전방면
3rd row360도전방면
4th row360도전방면
5th row360도전방면

Common Values

ValueCountFrequency (%)
360도전방면 980
100.0%

Length

2023-12-12T13:38:50.344079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:38:50.460559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
360도전방면 980
100.0%

보관일수
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.8 KiB
30
980 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row30
2nd row30
3rd row30
4th row30
5th row30

Common Values

ValueCountFrequency (%)
30 980
100.0%

Length

2023-12-12T13:38:50.563262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:38:50.656562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
30 980
100.0%

관리기관전화번호
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.8 KiB
051-605-4646
980 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row051-605-4646
2nd row051-605-4646
3rd row051-605-4646
4th row051-605-4646
5th row051-605-4646

Common Values

ValueCountFrequency (%)
051-605-4646 980
100.0%

Length

2023-12-12T13:38:50.776542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:38:50.890135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
051-605-4646 980
100.0%

위도
Real number (ℝ)

SKEWED 

Distinct939
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.162203
Minimum35.141397
Maximum37.010097
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.7 KiB
2023-12-12T13:38:51.053187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.141397
5-th percentile35.144766
Q135.15173
median35.158976
Q335.168475
95-th percentile35.178601
Maximum37.010097
Range1.8687001
Interquartile range (IQR)0.016745

Descriptive statistics

Standard deviation0.060016122
Coefficient of variation (CV)0.0017068362
Kurtosis920.6595
Mean35.162203
Median Absolute Deviation (MAD)0.0084465
Skewness29.875183
Sum34458.959
Variance0.0036019349
MonotonicityNot monotonic
2023-12-12T13:38:51.269124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.163772 15
 
1.5%
35.148951 12
 
1.2%
35.16140073 4
 
0.4%
35.16667 2
 
0.2%
35.15757111 2
 
0.2%
35.158244 2
 
0.2%
35.157201 2
 
0.2%
35.161679 2
 
0.2%
35.17136 2
 
0.2%
35.153765 2
 
0.2%
Other values (929) 935
95.4%
ValueCountFrequency (%)
35.141397 1
0.1%
35.141659 1
0.1%
35.141676 1
0.1%
35.141733 1
0.1%
35.142041 1
0.1%
35.142055 1
0.1%
35.1422 1
0.1%
35.142313 1
0.1%
35.142429 1
0.1%
35.142659 1
0.1%
ValueCountFrequency (%)
37.01009709 1
0.1%
35.188454 1
0.1%
35.18839986 1
0.1%
35.187734 1
0.1%
35.187373 1
0.1%
35.1847 1
0.1%
35.184116 1
0.1%
35.183856 1
0.1%
35.183528 1
0.1%
35.183006 1
0.1%

경도
Real number (ℝ)

SKEWED 

Distinct942
Distinct (%)96.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.04635
Minimum127.27162
Maximum129.08072
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.7 KiB
2023-12-12T13:38:51.456140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.27162
5-th percentile129.02016
Q1129.0348
median129.04944
Q3129.06187
95-th percentile129.07179
Maximum129.08072
Range1.809099
Interquartile range (IQR)0.027064

Descriptive statistics

Standard deviation0.059037671
Coefficient of variation (CV)0.00045749197
Kurtosis836.26338
Mean129.04635
Median Absolute Deviation (MAD)0.0135955
Skewness-27.801413
Sum126465.43
Variance0.0034854466
MonotonicityNot monotonic
2023-12-12T13:38:51.640348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
129.070706 15
 
1.5%
129.033382 12
 
1.2%
129.027183 4
 
0.4%
129.034922 2
 
0.2%
129.0407911 2
 
0.2%
129.064778 2
 
0.2%
129.0554775 2
 
0.2%
129.072771 2
 
0.2%
129.067321 2
 
0.2%
129.0236947 2
 
0.2%
Other values (932) 935
95.4%
ValueCountFrequency (%)
127.271618 1
0.1%
129.015425 1
0.1%
129.015462 1
0.1%
129.01589 1
0.1%
129.015902 1
0.1%
129.016285 1
0.1%
129.016308 2
0.2%
129.016357 1
0.1%
129.016452 1
0.1%
129.016526 1
0.1%
ValueCountFrequency (%)
129.080717 1
0.1%
129.079438 1
0.1%
129.078767 1
0.1%
129.078463 1
0.1%
129.077798 1
0.1%
129.077472 1
0.1%
129.07698 1
0.1%
129.07677 1
0.1%
129.076559 1
0.1%
129.076532 1
0.1%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.8 KiB
2023-10-18
980 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-10-18
2nd row2023-10-18
3rd row2023-10-18
4th row2023-10-18
5th row2023-10-18

Common Values

ValueCountFrequency (%)
2023-10-18 980
100.0%

Length

2023-12-12T13:38:51.786849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:38:51.911371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-10-18 980
100.0%

Interactions

2023-12-12T13:38:46.724957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:45.848075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:46.263038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:46.874328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:45.969556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:46.394541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:47.000600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:46.114446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:46.569211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:38:51.975848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
카메라대수위도경도
카메라대수1.0000.0000.000
위도0.0001.0000.706
경도0.0000.7061.000
2023-12-12T13:38:52.080787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
카메라대수위도경도
카메라대수1.000-0.024-0.031
위도-0.0241.0000.256
경도-0.0310.2561.000

Missing values

2023-12-12T13:38:47.190465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:38:47.427644image/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.
2023-12-12T13:38:47.556937image/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

관리기관명소재지도로명주소소재지지번주소설치목적구분카메라대수카메라화소수촬영방면정보보관일수관리기관전화번호위도경도데이터기준일자
0부산광역시 부산진구청부산광역시 부산진구 신암로83번길 13부산광역시 부산진구 범천동 1252-70생활방범1200360도전방면30051-605-464635.148287129.0530762023-10-18
1부산광역시 부산진구청부산광역시 부산진구 동평로127번길 52부산광역시 부산진구 부암동 365-1생활방범1200360도전방면30051-605-464635.168618129.0428192023-10-18
2부산광역시 부산진구청부산광역시 부산진구 동평로131번길 48부산광역시 부산진구 부암동 320-143생활방범1200360도전방면30051-605-464635.167787129.0452432023-10-18
3부산광역시 부산진구청부산광역시 부산진구 개금본동로66번길 11부산광역시 부산진구 개금동 412-13생활방범4200360도전방면30051-605-464635.157692129.0202222023-10-18
4부산광역시 부산진구청부산광역시 부산진구 가야대로703번길 16부산광역시 부산진구 당감동 71-8생활방범1200360도전방면30051-605-464635.158192129.0475622023-10-18
5부산광역시 부산진구청부산광역시 부산진구 엄광로305번길 3부산광역시 부산진구 가야동 16-141생활방범1200360도전방면30051-605-464635.155195129.042972023-10-18
6부산광역시 부산진구청부산광역시 부산진구 가야대로668번길 18부산광역시 부산진구 가야동 5-16생활방범4200360도전방면30051-605-464635.155371129.04432023-10-18
7부산광역시 부산진구청부산광역시 부산진구 서전로67번길 39부산광역시 부산진구 전포동 192-3생활방범1200360도전방면30051-605-464635.159512129.0670742023-10-18
8부산광역시 부산진구청부산광역시 부산진구 새싹로266번길 18부산광역시 부산진구 초읍동 276-2생활방범1200360도전방면30051-605-464635.179772129.0484632023-10-18
9부산광역시 부산진구청부산광역시 부산진구 성지로46번길22부산광역시 부산진구 연지동 290-2생활방범1200360도전방면30051-605-464635.174635129.0555472023-10-18
관리기관명소재지도로명주소소재지지번주소설치목적구분카메라대수카메라화소수촬영방면정보보관일수관리기관전화번호위도경도데이터기준일자
970부산광역시 부산진구청부산광역시 부산진구 범양로117번길 9부산광역시 부산진구 양정동 447-6생활방범2200360도전방면30051-605-464635.173565129.0652612023-10-18
971부산광역시 부산진구청부산광역시 부산진구 진남로395번길 5부산광역시 부산진구 전포동 191-942생활방범2200360도전방면30051-605-464635.160025129.0704712023-10-18
972부산광역시 부산진구청부산광역시 부산진구 새싹로 10-1부산광역시 부산진구 부전동 261-4생활방범2200360도전방면30051-605-464635.158934129.0583332023-10-18
973부산광역시 부산진구청부산광역시 부산진구 새싹로 37부산광역시 부산진구 부전동 401-9생활방범2200360도전방면30051-605-464635.160948129.056362023-10-18
974부산광역시 부산진구청부산광역시 부산진구 부암동 700-5부산광역시 부산진구 가야대로 지하 719생활방범1200360도전방면30051-605-464635.158036129.050842023-10-18
975부산광역시 부산진구청부산광역시 부산진구 중앙대로 909부산광역시 부산진구 양정동 393-19생활방범1200360도전방면30051-605-464635.17162129.0699382023-10-18
976부산광역시 부산진구청부산광역시 부산진구 중앙대로 639부산광역시 부산진구 범천동 863-1생활방범1200360도전방면30051-605-464635.149467129.0590462023-10-18
977부산광역시 부산진구청부산광역시 부산진구 중앙대로621번길 624부산광역시 부산진구 범천동 857-14생활방범1200360도전방면30051-605-464635.148251129.0594252023-10-18
978부산광역시 부산진구청부산광역시 부산진구 동천로 79부산광역시 부산진구 부전동 168-269생활방범2200360도전방면30051-605-464635.155379129.0621112023-10-18
979부산광역시 부산진구청<NA>부산광역시 부산진구 전포동 362-69생활방범1200360도전방면30051-605-464635.149692129.0656542023-10-18

Duplicate rows

Most frequently occurring

관리기관명소재지도로명주소소재지지번주소설치목적구분카메라대수카메라화소수촬영방면정보보관일수관리기관전화번호위도경도데이터기준일자# duplicates
0부산광역시 부산진구청부산광역시 부산진구 가야대로548번길 109부산광역시 부산진구 가야동 553생활방범1200360도전방면30051-605-464635.148951129.0333822023-10-1812
4부산광역시 부산진구청<NA>부산광역시 부산진구 전포동 산12생활방범1200360도전방면30051-605-464635.163772129.0707062023-10-183
1부산광역시 부산진구청부산광역시 부산진구 개금온정로17번길 77부산광역시 부산진구 개금동 276-12생활방범1200360도전방면30051-605-464635.155962129.0236952023-10-182
2부산광역시 부산진구청부산광역시 부산진구 백양대로208번길 70부산광역시 부산진구 개금동 56생활방범1200360도전방면30051-605-464635.161401129.0271832023-10-182
3부산광역시 부산진구청부산광역시 부산진구 신암로 56부산광역시 부산진구 범천동 1258-41생활방범1200360도전방면30051-605-464635.147111129.0554772023-10-182