Overview

Dataset statistics

Number of variables13
Number of observations635
Missing cells56
Missing cells (%)0.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory67.7 KiB
Average record size in memory109.2 B

Variable types

Categorical7
Text2
DateTime2
Numeric2

Dataset

Description파일 다운로드
Author종로구
URLhttps://data.seoul.go.kr/dataList/OA-11568/F/1/datasetView.do

Alerts

관리기관명 has constant value ""Constant
보관일수 has constant value ""Constant
관리기관전화번호 has constant value ""Constant
데이터기준일자 has constant value ""Constant
설치목적구분 is highly imbalanced (54.4%)Imbalance
카메라화소수 is highly imbalanced (59.3%)Imbalance
촬영방면정보 is highly imbalanced (57.5%)Imbalance
소재지지번주소 has 56 (8.8%) missing valuesMissing

Reproduction

Analysis started2023-12-11 04:54:56.460282
Analysis finished2023-12-11 04:54:59.118712
Duration2.66 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
서울특별시 종로구청
635 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울특별시 종로구청
2nd row서울특별시 종로구청
3rd row서울특별시 종로구청
4th row서울특별시 종로구청
5th row서울특별시 종로구청

Common Values

ValueCountFrequency (%)
서울특별시 종로구청 635
100.0%

Length

2023-12-11T13:54:59.242665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T13:54:59.435093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 635
50.0%
종로구청 635
50.0%

소재지도로명주소
Text

Distinct563
Distinct (%)88.7%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
2023-12-11T13:55:00.018492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length34
Mean length18.795276
Min length13

Characters and Unicode

Total characters11935
Distinct characters157
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

Unique507 ?
Unique (%)79.8%

Sample

1st row서울특별시 종로구 경교장길 5
2nd row서울특별시 종로구 경교장길 5
3rd row서울특별시 종로구 경희궁1길 1
4th row서울특별시 종로구 경희궁3나길 2
5th row서울특별시 종로구 경희궁길 10-2
ValueCountFrequency (%)
서울특별시 635
24.6%
종로구 635
24.6%
종로 32
 
1.2%
1 15
 
0.6%
9 14
 
0.5%
26 13
 
0.5%
5 12
 
0.5%
29 12
 
0.5%
3 12
 
0.5%
자하문로 11
 
0.4%
Other values (574) 1187
46.0%
2023-12-11T13:55:01.096723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1943
16.3%
로 1070
 
9.0%
종 728
 
6.1%
서 640
 
5.4%
구 637
 
5.3%
시 637
 
5.3%
울 636
 
5.3%
별 635
 
5.3%
특 635
 
5.3%
길 485
 
4.1%
Other values (147) 3889
32.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7836
65.7%
Decimal Number 1960
 
16.4%
Space Separator 1943
 
16.3%
Dash Punctuation 118
 
1.0%
Open Punctuation 39
 
0.3%
Close Punctuation 39
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 1070
13.7%
종 728
9.3%
서 640
 
8.2%
구 637
 
8.1%
시 637
 
8.1%
울 636
 
8.1%
별 635
 
8.1%
특 635
 
8.1%
길 485
 
6.2%
문 104
 
1.3%
Other values (133) 1629
20.8%
Decimal Number
ValueCountFrequency (%)
1 453
23.1%
2 288
14.7%
3 247
12.6%
5 187
9.5%
4 180
 
9.2%
6 153
 
7.8%
9 126
 
6.4%
7 125
 
6.4%
0 108
 
5.5%
8 93
 
4.7%
Space Separator
ValueCountFrequency (%)
1943
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 118
100.0%
Open Punctuation
ValueCountFrequency (%)
( 39
100.0%
Close Punctuation
ValueCountFrequency (%)
) 39
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7836
65.7%
Common 4099
34.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 1070
13.7%
종 728
9.3%
서 640
 
8.2%
구 637
 
8.1%
시 637
 
8.1%
울 636
 
8.1%
별 635
 
8.1%
특 635
 
8.1%
길 485
 
6.2%
문 104
 
1.3%
Other values (133) 1629
20.8%
Common
ValueCountFrequency (%)
1943
47.4%
1 453
 
11.1%
2 288
 
7.0%
3 247
 
6.0%
5 187
 
4.6%
4 180
 
4.4%
6 153
 
3.7%
9 126
 
3.1%
7 125
 
3.0%
- 118
 
2.9%
Other values (4) 279
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7836
65.7%
ASCII 4099
34.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1943
47.4%
1 453
 
11.1%
2 288
 
7.0%
3 247
 
6.0%
5 187
 
4.6%
4 180
 
4.4%
6 153
 
3.7%
9 126
 
3.1%
7 125
 
3.0%
- 118
 
2.9%
Other values (4) 279
 
6.8%
Hangul
ValueCountFrequency (%)
로 1070
13.7%
종 728
9.3%
서 640
 
8.2%
구 637
 
8.1%
시 637
 
8.1%
울 636
 
8.1%
별 635
 
8.1%
특 635
 
8.1%
길 485
 
6.2%
문 104
 
1.3%
Other values (133) 1629
20.8%

소재지지번주소
Text

MISSING 

Distinct525
Distinct (%)90.7%
Missing56
Missing (%)8.8%
Memory size5.1 KiB
2023-12-11T13:55:01.835172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length38
Mean length19.557858
Min length15

Characters and Unicode

Total characters11324
Distinct characters152
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

Unique476 ?
Unique (%)82.2%

Sample

1st row서울특별시 종로구 교남동 7
2nd row서울특별시 종로구 교남동 7
3rd row서울특별시 종로구 신문로2가 1-153
4th row서울특별시 종로구 사직동 311-6
5th row서울특별시 종로구 신문로2가 1-241
ValueCountFrequency (%)
서울특별시 579
24.2%
종로구 579
24.2%
숭인동 64
 
2.7%
창신동 55
 
2.3%
평창동 30
 
1.3%
부암동 29
 
1.2%
명륜3가 24
 
1.0%
명륜1가 19
 
0.8%
동숭동 18
 
0.8%
행촌동 17
 
0.7%
Other values (602) 979
40.9%
2023-12-11T13:55:02.739340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1814
16.0%
로 612
 
5.4%
종 606
 
5.4%
구 596
 
5.3%
서 593
 
5.2%
시 585
 
5.2%
울 579
 
5.1%
별 579
 
5.1%
특 579
 
5.1%
1 524
 
4.6%
Other values (142) 4257
37.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6738
59.5%
Decimal Number 2220
 
19.6%
Space Separator 1814
 
16.0%
Dash Punctuation 466
 
4.1%
Open Punctuation 43
 
0.4%
Close Punctuation 43
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 612
9.1%
종 606
9.0%
구 596
8.8%
서 593
8.8%
시 585
8.7%
울 579
8.6%
별 579
8.6%
특 579
8.6%
동 515
 
7.6%
인 108
 
1.6%
Other values (128) 1386
20.6%
Decimal Number
ValueCountFrequency (%)
1 524
23.6%
2 316
14.2%
3 266
12.0%
6 194
 
8.7%
4 189
 
8.5%
5 184
 
8.3%
8 161
 
7.3%
7 148
 
6.7%
9 124
 
5.6%
0 114
 
5.1%
Space Separator
ValueCountFrequency (%)
1814
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 466
100.0%
Open Punctuation
ValueCountFrequency (%)
( 43
100.0%
Close Punctuation
ValueCountFrequency (%)
) 43
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6738
59.5%
Common 4586
40.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 612
9.1%
종 606
9.0%
구 596
8.8%
서 593
8.8%
시 585
8.7%
울 579
8.6%
별 579
8.6%
특 579
8.6%
동 515
 
7.6%
인 108
 
1.6%
Other values (128) 1386
20.6%
Common
ValueCountFrequency (%)
1814
39.6%
1 524
 
11.4%
- 466
 
10.2%
2 316
 
6.9%
3 266
 
5.8%
6 194
 
4.2%
4 189
 
4.1%
5 184
 
4.0%
8 161
 
3.5%
7 148
 
3.2%
Other values (4) 324
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6738
59.5%
ASCII 4586
40.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1814
39.6%
1 524
 
11.4%
- 466
 
10.2%
2 316
 
6.9%
3 266
 
5.8%
6 194
 
4.2%
4 189
 
4.1%
5 184
 
4.0%
8 161
 
3.5%
7 148
 
3.2%
Other values (4) 324
 
7.1%
Hangul
ValueCountFrequency (%)
로 612
9.1%
종 606
9.0%
구 596
8.8%
서 593
8.8%
시 585
8.7%
울 579
8.6%
별 579
8.6%
특 579
8.6%
동 515
 
7.6%
인 108
 
1.6%
Other values (128) 1386
20.6%

설치목적구분
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
생활방범
513 
교통단속
78 
다목적
 
41
재난재해
 
3

Length

Max length4
Median length4
Mean length3.9354331
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
생활방범 513
80.8%
교통단속 78
 
12.3%
다목적 41
 
6.5%
재난재해 3
 
0.5%

Length

2023-12-11T13:55:03.019523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T13:55:03.218015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
생활방범 513
80.8%
교통단속 78
 
12.3%
다목적 41
 
6.5%
재난재해 3
 
0.5%

카메라대수
Categorical

Distinct4
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
1
247 
3
190 
2
171 
4
27 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row1
3rd row1
4th row4
5th row2

Common Values

ValueCountFrequency (%)
1 247
38.9%
3 190
29.9%
2 171
26.9%
4 27
 
4.3%

Length

2023-12-11T13:55:03.424929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T13:55:03.673553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 247
38.9%
3 190
29.9%
2 171
26.9%
4 27
 
4.3%

카메라화소수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
200
559 
41
 
45
130
 
31

Length

Max length3
Median length3
Mean length2.9291339
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row200
2nd row130
3rd row200
4th row200
5th row200

Common Values

ValueCountFrequency (%)
200 559
88.0%
41 45
 
7.1%
130 31
 
4.9%

Length

2023-12-11T13:55:03.939062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T13:55:04.229114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
200 559
88.0%
41 45
 
7.1%
130 31
 
4.9%

촬영방면정보
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
360도전방면
580 
카메라 전면(고정)
 
55

Length

Max length10
Median length7
Mean length7.2598425
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row카메라 전면(고정)
2nd row360도전방면
3rd row카메라 전면(고정)
4th row360도전방면
5th row360도전방면

Common Values

ValueCountFrequency (%)
360도전방면 580
91.3%
카메라 전면(고정) 55
 
8.7%

Length

2023-12-11T13:55:04.573918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T13:55:04.922710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
360도전방면 580
84.1%
카메라 55
 
8.0%
전면(고정 55
 
8.0%

보관일수
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
30
635 

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 (%)
30 635
100.0%

Length

2023-12-11T13:55:05.232816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T13:55:05.439816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
30 635
100.0%

설치년월
Date

Distinct41
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
Minimum2002-11-01 00:00:00
Maximum2017-09-01 00:00:00
2023-12-11T13:55:05.604300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:55:05.853049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)

관리기관전화번호
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
02-2148-4301
635 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row02-2148-4301
2nd row02-2148-4301
3rd row02-2148-4301
4th row02-2148-4301
5th row02-2148-4301

Common Values

ValueCountFrequency (%)
02-2148-4301 635
100.0%

Length

2023-12-11T13:55:06.103046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T13:55:06.305617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
02-2148-4301 635
100.0%

위도
Real number (ℝ)

Distinct591
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.581659
Minimum37.567387
Maximum37.616553
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2023-12-11T13:55:06.514981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.567387
5-th percentile37.57028
Q137.573864
median37.578095
Q337.586806
95-th percentile37.606381
Maximum37.616553
Range0.0491658
Interquartile range (IQR)0.012942

Descriptive statistics

Standard deviation0.010722309
Coefficient of variation (CV)0.00028530697
Kurtosis1.0495484
Mean37.581659
Median Absolute Deviation (MAD)0.0054259
Skewness1.2798328
Sum23864.354
Variance0.00011496792
MonotonicityNot monotonic
2023-12-11T13:55:06.854000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.567387 2
 
0.3%
37.5767695 2
 
0.3%
37.5804556 2
 
0.3%
37.5800658 2
 
0.3%
37.5820976 2
 
0.3%
37.570675 2
 
0.3%
37.571682 2
 
0.3%
37.5761316 2
 
0.3%
37.5774038 2
 
0.3%
37.572896 2
 
0.3%
Other values (581) 615
96.9%
ValueCountFrequency (%)
37.567387 2
0.3%
37.5685594 1
0.2%
37.568702 1
0.2%
37.568766 1
0.2%
37.568989 1
0.2%
37.569073 1
0.2%
37.5692068 1
0.2%
37.5692685 1
0.2%
37.569284 1
0.2%
37.569303 1
0.2%
ValueCountFrequency (%)
37.6165528 1
0.2%
37.61485 1
0.2%
37.614766 1
0.2%
37.6147147 1
0.2%
37.614664 1
0.2%
37.6134556 1
0.2%
37.6131269 1
0.2%
37.612638 1
0.2%
37.612555 1
0.2%
37.612514 1
0.2%

경도
Real number (ℝ)

Distinct595
Distinct (%)93.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.98878
Minimum126.95498
Maximum127.02296
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2023-12-11T13:55:07.236711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.95498
5-th percentile126.96084
Q1126.96833
median126.99091
Q3127.0051
95-th percentile127.01856
Maximum127.02296
Range0.0679726
Interquartile range (IQR)0.03677035

Descriptive statistics

Standard deviation0.019852241
Coefficient of variation (CV)0.00015633067
Kurtosis-1.351488
Mean126.98878
Median Absolute Deviation (MAD)0.019344
Skewness-0.026374129
Sum80637.873
Variance0.00039411146
MonotonicityNot monotonic
2023-12-11T13:55:07.616735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.965804 2
 
0.3%
127.0107339 2
 
0.3%
126.9891318 2
 
0.3%
126.9669432 2
 
0.3%
126.9687049 2
 
0.3%
127.0000597 2
 
0.3%
127.0147411 2
 
0.3%
127.00333 2
 
0.3%
126.9633656 2
 
0.3%
126.993857 2
 
0.3%
Other values (585) 615
96.9%
ValueCountFrequency (%)
126.954983 1
0.2%
126.955233 1
0.2%
126.9558748 1
0.2%
126.95616 1
0.2%
126.95634 1
0.2%
126.956509 1
0.2%
126.956637 1
0.2%
126.956638 1
0.2%
126.956799 1
0.2%
126.956861 1
0.2%
ValueCountFrequency (%)
127.0229556 1
0.2%
127.02271 1
0.2%
127.022696 1
0.2%
127.0225795 1
0.2%
127.0220012 1
0.2%
127.021571 1
0.2%
127.021516 1
0.2%
127.0209148 1
0.2%
127.02071 2
0.3%
127.020395 1
0.2%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
Minimum2018-02-09 00:00:00
Maximum2018-02-09 00:00:00
2023-12-11T13:55:07.897363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:55:08.117918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-11T13:54:57.728711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:54:57.377262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:54:57.899351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:54:57.543279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T13:55:08.294170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치목적구분카메라대수카메라화소수촬영방면정보설치년월위도경도
설치목적구분1.0000.6750.0900.1790.9900.3060.178
카메라대수0.6751.0000.2880.1860.7710.0760.173
카메라화소수0.0900.2881.0000.2070.8500.1860.153
촬영방면정보0.1790.1860.2071.0000.6080.0000.000
설치년월0.9900.7710.8500.6081.0000.5770.503
위도0.3060.0760.1860.0000.5771.0000.731
경도0.1780.1730.1530.0000.5030.7311.000
2023-12-11T13:55:08.556466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
촬영방면정보카메라대수설치목적구분카메라화소수
촬영방면정보1.0000.1230.1190.340
카메라대수0.1231.0000.3230.276
설치목적구분0.1190.3231.0000.084
카메라화소수0.3400.2760.0841.000
2023-12-11T13:55:08.786482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도설치목적구분카메라대수카메라화소수촬영방면정보
위도1.000-0.3460.1870.0450.1120.000
경도-0.3461.0000.1070.1030.0910.000
설치목적구분0.1870.1071.0000.3230.0840.119
카메라대수0.0450.1030.3231.0000.2760.123
카메라화소수0.1120.0910.0840.2761.0000.340
촬영방면정보0.0000.0000.1190.1230.3401.000

Missing values

2023-12-11T13:54:58.653272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T13:54:58.978480image/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

관리기관명소재지도로명주소소재지지번주소설치목적구분카메라대수카메라화소수촬영방면정보보관일수설치년월관리기관전화번호위도경도데이터기준일자
0서울특별시 종로구청서울특별시 종로구 경교장길 5서울특별시 종로구 교남동 7생활방범3200카메라 전면(고정)302011-1202-2148-430137.567387126.9658042018-02-09
1서울특별시 종로구청서울특별시 종로구 경교장길 5서울특별시 종로구 교남동 7생활방범1130360도전방면302011-1202-2148-430137.567387126.9658042018-02-09
2서울특별시 종로구청서울특별시 종로구 경희궁1길 1서울특별시 종로구 신문로2가 1-153생활방범1200카메라 전면(고정)302015-1202-2148-430137.570626126.9719322018-02-09
3서울특별시 종로구청서울특별시 종로구 경희궁3나길 2서울특별시 종로구 사직동 311-6생활방범4200360도전방면302015-1202-2148-430137.573822126.9672132018-02-09
4서울특별시 종로구청서울특별시 종로구 경희궁길 10-2서울특별시 종로구 신문로2가 1-241생활방범2200360도전방면302015-1202-2148-430137.571228126.9719642018-02-09
5서울특별시 종로구청서울특별시 종로구 계동4길 19서울특별시 종로구 계동 34-1생활방범1200카메라 전면(고정)302015-1202-2148-430137.582416126.9879612018-02-09
6서울특별시 종로구청서울특별시 종로구 계동4길 9서울특별시 종로구 계동 29생활방범2200360도전방면302013-1202-2148-430137.582238126.9873872018-02-09
7서울특별시 종로구청서울특별시 종로구 계동길 69서울특별시 종로구 계동 79-7생활방범2200360도전방면302013-1202-2148-430137.580421126.9867472018-02-09
8서울특별시 종로구청서울특별시 종로구 김상옥로 42-1서울특별시 종로구 효제동 295생활방범2200360도전방면302013-1202-2148-430137.573255127.0022182018-02-09
9서울특별시 종로구청서울특별시 종로구 김상옥로 51서울특별시 종로구 효제동 115-1생활방범2200360도전방면302011-0402-2148-430137.573347127.0034812018-02-09
관리기관명소재지도로명주소소재지지번주소설치목적구분카메라대수카메라화소수촬영방면정보보관일수설치년월관리기관전화번호위도경도데이터기준일자
625서울특별시 종로구청서울특별시 종로구 혜화로9길 28서울특별시 종로구 명륜1가 23생활방범141360도전방면302005-1202-2148-430137.587558126.9982552018-02-09
626서울특별시 종로구청서울특별시 종로구 혜화로9길 40서울특별시 종로구 명륜1가 60-1생활방범2200360도전방면302013-1202-2148-430137.587154126.9980082018-02-09
627서울특별시 종로구청서울특별시 종로구 혜화로9길 48서울특별시 종로구 명륜1가 65-1생활방범141360도전방면302005-1202-2148-430137.586768126.997772018-02-09
628서울특별시 종로구청서울특별시 종로구 혜화로9길 6서울특별시 종로구 명륜1가 33-6생활방범141360도전방면302005-1202-2148-430137.58784126.9993162018-02-09
629서울특별시 종로구청서울특별시 종로구 홍지문2가길 16서울특별시 종로구 홍지동 34-15생활방범3200360도전방면302016-1202-2148-430137.600108126.9549832018-02-09
630서울특별시 종로구청서울특별시 종로구 홍지문2길 1<NA>다목적1200360도전방면302014-1002-2148-430137.600788126.9568612018-02-09
631서울특별시 종로구청서울특별시 종로구 홍지문길 28서울특별시 종로구 홍지동 69-3생활방범4200360도전방면302015-1202-2148-430137.60191126.9570492018-02-09
632서울특별시 종로구청서울특별시 종로구 홍지문길 88서울특별시 종로구 구기동 55-17생활방범1200360도전방면302013-0202-2148-430137.606011126.9576512018-02-09
633서울특별시 종로구청서울특별시 종로구 홍지문길 88서울특별시 종로구 구기동 55-17생활방범2130카메라 전면(고정)302013-0202-2148-430137.606011126.9576512018-02-09
634서울특별시 종로구청서울특별시 종로구 효자로7길 20서울특별시 종로구 통의동 28-2생활방범2200360도전방면302013-1202-2148-430137.578604126.9731142018-02-09