Overview

Dataset statistics

Number of variables13
Number of observations10000
Missing cells14878
Missing cells (%)11.4%
Duplicate rows515
Duplicate rows (%)5.1%
Total size in memory1.1 MiB
Average record size in memory117.0 B

Variable types

Text5
Categorical1
Numeric5
DateTime2

Alerts

Dataset has 515 (5.1%) duplicate rowsDuplicates
설치목적구분 is highly imbalanced (53.9%)Imbalance
소재지도로명주소 has 5024 (50.2%) missing valuesMissing
카메라화소수 has 1043 (10.4%) missing valuesMissing
촬영방면정보 has 4612 (46.1%) missing valuesMissing
보관일수 has 734 (7.3%) missing valuesMissing
설치연월 has 2691 (26.9%) missing valuesMissing
위도 has 384 (3.8%) missing valuesMissing
경도 has 384 (3.8%) missing valuesMissing

Reproduction

Analysis started2024-03-16 04:13:52.383640
Analysis finished2024-03-16 04:14:08.778540
Duration16.39 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리기관명
Text

Distinct58
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-16T04:14:09.001474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length8
Mean length7.7879
Min length3

Characters and Unicode

Total characters77879
Distinct characters91
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

Unique6 ?
Unique (%)0.1%

Sample

1st row연천군 안전총괄과
2nd row경기도 시흥시청
3rd row경기도 구리시청
4th row경기도 수원시
5th row경기도 의정부시
ValueCountFrequency (%)
경기도 7706
41.3%
화성시청 2213
 
11.9%
수원시 843
 
4.5%
용인시 682
 
3.7%
이천시청 494
 
2.6%
평택시청 458
 
2.5%
양평군청 435
 
2.3%
안산시 373
 
2.0%
부천시청 341
 
1.8%
도시정보센터 310
 
1.7%
Other values (52) 4802
25.7%
2024-03-16T04:14:09.906795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 10065
12.9%
8657
11.1%
도 8456
10.9%
경 7723
 
9.9%
기 7718
 
9.9%
청 7017
 
9.0%
성 2781
 
3.6%
화 2215
 
2.8%
양 1360
 
1.7%
천 1311
 
1.7%
Other values (81) 20576
26.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 68603
88.1%
Space Separator 8657
 
11.1%
Open Punctuation 309
 
0.4%
Close Punctuation 309
 
0.4%
Decimal Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 10065
14.7%
도 8456
12.3%
경 7723
11.3%
기 7718
11.3%
청 7017
 
10.2%
성 2781
 
4.1%
화 2215
 
3.2%
양 1360
 
2.0%
천 1311
 
1.9%
정 1267
 
1.8%
Other values (77) 18690
27.2%
Space Separator
ValueCountFrequency (%)
8657
100.0%
Open Punctuation
ValueCountFrequency (%)
( 309
100.0%
Close Punctuation
ValueCountFrequency (%)
) 309
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 68603
88.1%
Common 9276
 
11.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 10065
14.7%
도 8456
12.3%
경 7723
11.3%
기 7718
11.3%
청 7017
 
10.2%
성 2781
 
4.1%
화 2215
 
3.2%
양 1360
 
2.0%
천 1311
 
1.9%
정 1267
 
1.8%
Other values (77) 18690
27.2%
Common
ValueCountFrequency (%)
8657
93.3%
( 309
 
3.3%
) 309
 
3.3%
1 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 68603
88.1%
ASCII 9276
 
11.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 10065
14.7%
도 8456
12.3%
경 7723
11.3%
기 7718
11.3%
청 7017
 
10.2%
성 2781
 
4.1%
화 2215
 
3.2%
양 1360
 
2.0%
천 1311
 
1.9%
정 1267
 
1.8%
Other values (77) 18690
27.2%
ASCII
ValueCountFrequency (%)
8657
93.3%
( 309
 
3.3%
) 309
 
3.3%
1 1
 
< 0.1%

소재지도로명주소
Text

MISSING 

Distinct4648
Distinct (%)93.4%
Missing5024
Missing (%)50.2%
Memory size156.2 KiB
2024-03-16T04:14:10.580243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length59
Mean length21.469051
Min length11

Characters and Unicode

Total characters106830
Distinct characters528
Distinct categories13 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4405 ?
Unique (%)88.5%

Sample

1st row경기도 시흥시 수인로3402번길 24-1
2nd row경기도 구리시 안골로20번길 62
3rd row경기도 수원시 팔달구 고등동 54-11
4th row경기도 의정부시 평화로484번길 7 (의정부동)
5th row경기도 남양주시 와부읍 수레로 108
ValueCountFrequency (%)
경기도 4978
 
20.7%
수원시 843
 
3.5%
화성시 533
 
2.2%
안산시 377
 
1.6%
부천시 341
 
1.4%
안양시 301
 
1.2%
권선구 253
 
1.0%
영통구 229
 
1.0%
평택시 227
 
0.9%
이천시 227
 
0.9%
Other values (6024) 15792
65.5%
2024-03-16T04:14:11.796599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19277
 
18.0%
도 5170
 
4.8%
경 5115
 
4.8%
기 5099
 
4.8%
시 4977
 
4.7%
1 3989
 
3.7%
로 2817
 
2.6%
2 2669
 
2.5%
동 2581
 
2.4%
구 2223
 
2.1%
Other values (518) 52913
49.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 64626
60.5%
Space Separator 19277
 
18.0%
Decimal Number 19135
 
17.9%
Dash Punctuation 1885
 
1.8%
Close Punctuation 741
 
0.7%
Open Punctuation 740
 
0.7%
Other Punctuation 372
 
0.3%
Uppercase Letter 39
 
< 0.1%
Lowercase Letter 9
 
< 0.1%
Final Punctuation 2
 
< 0.1%
Other values (3) 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 5170
 
8.0%
경 5115
 
7.9%
기 5099
 
7.9%
시 4977
 
7.7%
로 2817
 
4.4%
동 2581
 
4.0%
구 2223
 
3.4%
길 2112
 
3.3%
원 1521
 
2.4%
안 1501
 
2.3%
Other values (469) 31510
48.8%
Uppercase Letter
ValueCountFrequency (%)
G 6
15.4%
S 6
15.4%
A 4
10.3%
C 3
7.7%
I 3
7.7%
L 2
 
5.1%
U 2
 
5.1%
E 2
 
5.1%
B 2
 
5.1%
O 2
 
5.1%
Other values (6) 7
17.9%
Decimal Number
ValueCountFrequency (%)
1 3989
20.8%
2 2669
13.9%
3 2110
11.0%
4 1741
9.1%
5 1695
8.9%
7 1486
 
7.8%
6 1473
 
7.7%
0 1386
 
7.2%
8 1327
 
6.9%
9 1259
 
6.6%
Lowercase Letter
ValueCountFrequency (%)
e 2
22.2%
n 1
11.1%
a 1
11.1%
y 1
11.1%
s 1
11.1%
h 1
11.1%
u 1
11.1%
o 1
11.1%
Other Punctuation
ValueCountFrequency (%)
, 357
96.0%
. 7
 
1.9%
: 3
 
0.8%
? 2
 
0.5%
/ 1
 
0.3%
* 1
 
0.3%
# 1
 
0.3%
Space Separator
ValueCountFrequency (%)
19277
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1885
100.0%
Close Punctuation
ValueCountFrequency (%)
) 741
100.0%
Open Punctuation
ValueCountFrequency (%)
( 740
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 2
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 2
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%
Math Symbol
ValueCountFrequency (%)
↔ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 64627
60.5%
Common 42155
39.5%
Latin 48
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 5170
 
8.0%
경 5115
 
7.9%
기 5099
 
7.9%
시 4977
 
7.7%
로 2817
 
4.4%
동 2581
 
4.0%
구 2223
 
3.4%
길 2112
 
3.3%
원 1521
 
2.4%
안 1501
 
2.3%
Other values (470) 31511
48.8%
Common
ValueCountFrequency (%)
19277
45.7%
1 3989
 
9.5%
2 2669
 
6.3%
3 2110
 
5.0%
- 1885
 
4.5%
4 1741
 
4.1%
5 1695
 
4.0%
7 1486
 
3.5%
6 1473
 
3.5%
0 1386
 
3.3%
Other values (14) 4444
 
10.5%
Latin
ValueCountFrequency (%)
G 6
 
12.5%
S 6
 
12.5%
A 4
 
8.3%
C 3
 
6.2%
I 3
 
6.2%
e 2
 
4.2%
L 2
 
4.2%
U 2
 
4.2%
E 2
 
4.2%
B 2
 
4.2%
Other values (14) 16
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 64626
60.5%
ASCII 42198
39.5%
Punctuation 4
 
< 0.1%
None 1
 
< 0.1%
Arrows 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19277
45.7%
1 3989
 
9.5%
2 2669
 
6.3%
3 2110
 
5.0%
- 1885
 
4.5%
4 1741
 
4.1%
5 1695
 
4.0%
7 1486
 
3.5%
6 1473
 
3.5%
0 1386
 
3.3%
Other values (35) 4487
 
10.6%
Hangul
ValueCountFrequency (%)
도 5170
 
8.0%
경 5115
 
7.9%
기 5099
 
7.9%
시 4977
 
7.7%
로 2817
 
4.4%
동 2581
 
4.0%
구 2223
 
3.4%
길 2112
 
3.3%
원 1521
 
2.4%
안 1501
 
2.3%
Other values (469) 31510
48.8%
Punctuation
ValueCountFrequency (%)
’ 2
50.0%
‘ 2
50.0%
None
ValueCountFrequency (%)
㈜ 1
100.0%
Arrows
ValueCountFrequency (%)
↔ 1
100.0%

소재지지번주소
Text

Distinct9112
Distinct (%)91.2%
Missing6
Missing (%)0.1%
Memory size156.2 KiB
2024-03-16T04:14:12.516945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length70
Median length61
Mean length20.767961
Min length13

Characters and Unicode

Total characters207555
Distinct characters599
Distinct categories14 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8389 ?
Unique (%)83.9%

Sample

1st row경기도 연천군 전곡읍 전곡리 263-10
2nd row경기도 시흥시 신천동 314-23
3rd row경기도 구리시 교문동 757-6
4th row경기도 수원시 팔달구 고등로71번길 19-23
5th row경기도 의정부시 의정부동 138-29
ValueCountFrequency (%)
경기도 9994
 
20.8%
화성시 2213
 
4.6%
수원시 844
 
1.8%
용인시 682
 
1.4%
이천시 494
 
1.0%
평택시 458
 
1.0%
양평군 435
 
0.9%
안산시 424
 
0.9%
부천시 341
 
0.7%
안양시 308
 
0.6%
Other values (10783) 31753
66.2%
2024-03-16T04:14:13.985996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
38011
 
18.3%
도 10518
 
5.1%
기 10446
 
5.0%
경 10068
 
4.9%
시 9399
 
4.5%
1 7920
 
3.8%
- 6889
 
3.3%
동 6371
 
3.1%
2 5323
 
2.6%
3 4372
 
2.1%
Other values (589) 98238
47.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 120030
57.8%
Decimal Number 40984
 
19.7%
Space Separator 38011
 
18.3%
Dash Punctuation 6889
 
3.3%
Open Punctuation 616
 
0.3%
Close Punctuation 615
 
0.3%
Other Punctuation 218
 
0.1%
Uppercase Letter 151
 
0.1%
Math Symbol 23
 
< 0.1%
Lowercase Letter 11
 
< 0.1%
Other values (4) 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 10518
 
8.8%
기 10446
 
8.7%
경 10068
 
8.4%
시 9399
 
7.8%
동 6371
 
5.3%
리 4169
 
3.5%
구 3110
 
2.6%
성 3072
 
2.6%
화 2495
 
2.1%
양 2256
 
1.9%
Other values (528) 58126
48.4%
Uppercase Letter
ValueCountFrequency (%)
G 24
15.9%
S 22
14.6%
E 17
11.3%
C 14
9.3%
P 12
7.9%
A 11
7.3%
F 10
6.6%
I 9
 
6.0%
L 6
 
4.0%
T 6
 
4.0%
Other values (12) 20
13.2%
Decimal Number
ValueCountFrequency (%)
1 7920
19.3%
2 5323
13.0%
3 4372
10.7%
4 3956
9.7%
5 3817
9.3%
6 3572
8.7%
7 3295
8.0%
8 3060
 
7.5%
9 2873
 
7.0%
0 2796
 
6.8%
Lowercase Letter
ValueCountFrequency (%)
m 2
18.2%
y 2
18.2%
e 1
9.1%
s 1
9.1%
u 1
9.1%
o 1
9.1%
h 1
9.1%
n 1
9.1%
a 1
9.1%
Other Punctuation
ValueCountFrequency (%)
, 192
88.1%
# 7
 
3.2%
? 5
 
2.3%
: 5
 
2.3%
/ 3
 
1.4%
@ 3
 
1.4%
& 3
 
1.4%
Math Symbol
ValueCountFrequency (%)
> 6
26.1%
~ 6
26.1%
→ 6
26.1%
↔ 4
17.4%
< 1
 
4.3%
Space Separator
ValueCountFrequency (%)
38011
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6889
100.0%
Open Punctuation
ValueCountFrequency (%)
( 616
100.0%
Close Punctuation
ValueCountFrequency (%)
) 615
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 2
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 2
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 120032
57.8%
Common 87361
42.1%
Latin 162
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 10518
 
8.8%
기 10446
 
8.7%
경 10068
 
8.4%
시 9399
 
7.8%
동 6371
 
5.3%
리 4169
 
3.5%
구 3110
 
2.6%
성 3072
 
2.6%
화 2495
 
2.1%
양 2256
 
1.9%
Other values (529) 58128
48.4%
Latin
ValueCountFrequency (%)
G 24
14.8%
S 22
13.6%
E 17
10.5%
C 14
8.6%
P 12
 
7.4%
A 11
 
6.8%
F 10
 
6.2%
I 9
 
5.6%
L 6
 
3.7%
T 6
 
3.7%
Other values (21) 31
19.1%
Common
ValueCountFrequency (%)
38011
43.5%
1 7920
 
9.1%
- 6889
 
7.9%
2 5323
 
6.1%
3 4372
 
5.0%
4 3956
 
4.5%
5 3817
 
4.4%
6 3572
 
4.1%
7 3295
 
3.8%
8 3060
 
3.5%
Other values (19) 7146
 
8.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 120030
57.8%
ASCII 87509
42.2%
Arrows 10
 
< 0.1%
Punctuation 4
 
< 0.1%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
38011
43.4%
1 7920
 
9.1%
- 6889
 
7.9%
2 5323
 
6.1%
3 4372
 
5.0%
4 3956
 
4.5%
5 3817
 
4.4%
6 3572
 
4.1%
7 3295
 
3.8%
8 3060
 
3.5%
Other values (46) 7294
 
8.3%
Hangul
ValueCountFrequency (%)
도 10518
 
8.8%
기 10446
 
8.7%
경 10068
 
8.4%
시 9399
 
7.8%
동 6371
 
5.3%
리 4169
 
3.5%
구 3110
 
2.6%
성 3072
 
2.6%
화 2495
 
2.1%
양 2256
 
1.9%
Other values (528) 58126
48.4%
Arrows
ValueCountFrequency (%)
→ 6
60.0%
↔ 4
40.0%
None
ValueCountFrequency (%)
㈜ 2
100.0%
Punctuation
ValueCountFrequency (%)
’ 2
50.0%
‘ 2
50.0%

설치목적구분
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
생활방범
7528 
어린이보호
 
659
교통단속
 
411
다목적
 
377
재난재해
 
212
Other values (5)
813 

Length

Max length6
Median length4
Mean length4.0694
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
생활방범 7528
75.3%
어린이보호 659
 
6.6%
교통단속 411
 
4.1%
다목적 377
 
3.8%
재난재해 212
 
2.1%
시설물관리 212
 
2.1%
차량방범 192
 
1.9%
쓰레기단속 154
 
1.5%
교통정보수집 139
 
1.4%
기타 116
 
1.2%

Length

2024-03-16T04:14:14.520014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T04:14:14.860370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
생활방범 7528
75.3%
어린이보호 659
 
6.6%
교통단속 411
 
4.1%
다목적 377
 
3.8%
재난재해 212
 
2.1%
시설물관리 212
 
2.1%
차량방범 192
 
1.9%
쓰레기단속 154
 
1.5%
교통정보수집 139
 
1.4%
기타 116
 
1.2%

카메라대수
Real number (ℝ)

Distinct24
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.5346
Minimum1
Maximum61
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-16T04:14:15.276350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q34
95-th percentile5
Maximum61
Range60
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.039073
Coefficient of variation (CV)0.80449498
Kurtosis155.12418
Mean2.5346
Median Absolute Deviation (MAD)1
Skewness7.5893544
Sum25346
Variance4.1578186
MonotonicityNot monotonic
2024-03-16T04:14:15.720487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1 4695
46.9%
4 2036
20.4%
3 1346
 
13.5%
5 1160
 
11.6%
2 609
 
6.1%
6 80
 
0.8%
7 28
 
0.3%
8 15
 
0.1%
9 5
 
0.1%
10 4
 
< 0.1%
Other values (14) 22
 
0.2%
ValueCountFrequency (%)
1 4695
46.9%
2 609
 
6.1%
3 1346
 
13.5%
4 2036
20.4%
5 1160
 
11.6%
6 80
 
0.8%
7 28
 
0.3%
8 15
 
0.1%
9 5
 
0.1%
10 4
 
< 0.1%
ValueCountFrequency (%)
61 1
< 0.1%
48 1
< 0.1%
44 1
< 0.1%
42 1
< 0.1%
41 1
< 0.1%
33 1
< 0.1%
32 2
< 0.1%
28 2
< 0.1%
21 2
< 0.1%
18 1
< 0.1%

카메라화소수
Real number (ℝ)

MISSING 

Distinct23
Distinct (%)0.3%
Missing1043
Missing (%)10.4%
Infinite0
Infinite (%)0.0%
Mean97320.763
Minimum40
Maximum2000000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-16T04:14:16.133443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum40
5-th percentile200
Q1200
median200
Q3200
95-th percentile740
Maximum2000000
Range1999960
Interquartile range (IQR)0

Descriptive statistics

Standard deviation429896.28
Coefficient of variation (CV)4.4173131
Kurtosis15.651254
Mean97320.763
Median Absolute Deviation (MAD)0
Skewness4.2009235
Sum8.7170208 × 108
Variance1.8481081 × 1011
MonotonicityNot monotonic
2024-03-16T04:14:16.573027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
200 8086
80.9%
2000000 435
 
4.3%
41 163
 
1.6%
130 111
 
1.1%
700 31
 
0.3%
280 23
 
0.2%
500 17
 
0.2%
300 16
 
0.2%
140 12
 
0.1%
40 12
 
0.1%
Other values (13) 51
 
0.5%
(Missing) 1043
 
10.4%
ValueCountFrequency (%)
40 12
 
0.1%
41 163
 
1.6%
42 9
 
0.1%
52 12
 
0.1%
130 111
 
1.1%
140 12
 
0.1%
145 1
 
< 0.1%
192 1
 
< 0.1%
200 8086
80.9%
204 1
 
< 0.1%
ValueCountFrequency (%)
2000000 435
4.3%
1200 7
 
0.1%
900 6
 
0.1%
700 31
 
0.3%
500 17
 
0.2%
400 9
 
0.1%
330 1
 
< 0.1%
300 16
 
0.2%
280 23
 
0.2%
229 1
 
< 0.1%

촬영방면정보
Text

MISSING 

Distinct566
Distinct (%)10.5%
Missing4612
Missing (%)46.1%
Memory size156.2 KiB
2024-03-16T04:14:17.158217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length30
Mean length6.887899
Min length2

Characters and Unicode

Total characters37112
Distinct characters426
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

Unique536 ?
Unique (%)9.9%

Sample

1st row360도 전방면
2nd row360도 전방면
3rd row360도 전방면
4th row예봉초교(정문)
5th row공원방범[96] 360도 전방면
ValueCountFrequency (%)
360도 2534
30.2%
전방면 1845
22.0%
360도전방면 733
 
8.7%
180도 439
 
5.2%
이상 435
 
5.2%
120 321
 
3.8%
전방향(360도 235
 
2.8%
360 150
 
1.8%
회전 137
 
1.6%
주변100m이내 114
 
1.4%
Other values (749) 1458
17.4%
2024-03-16T04:14:18.134663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4829
13.0%
도 4172
11.2%
3 3806
10.3%
6 3788
10.2%
방 3172
8.5%
전 3078
8.3%
3014
8.1%
면 2687
 
7.2%
1 1020
 
2.7%
이 606
 
1.6%
Other values (416) 6940
18.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 18743
50.5%
Decimal Number 14490
39.0%
Space Separator 3014
 
8.1%
Open Punctuation 341
 
0.9%
Close Punctuation 341
 
0.9%
Lowercase Letter 114
 
0.3%
Other Punctuation 28
 
0.1%
Uppercase Letter 28
 
0.1%
Dash Punctuation 9
 
< 0.1%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 4172
22.3%
방 3172
16.9%
전 3078
16.4%
면 2687
14.3%
이 606
 
3.2%
상 453
 
2.4%
향 313
 
1.7%
주 176
 
0.9%
회 167
 
0.9%
내 141
 
0.8%
Other values (379) 3778
20.2%
Uppercase Letter
ValueCountFrequency (%)
T 5
17.9%
A 5
17.9%
C 3
10.7%
P 2
 
7.1%
S 2
 
7.1%
X 2
 
7.1%
K 2
 
7.1%
D 1
 
3.6%
U 1
 
3.6%
E 1
 
3.6%
Other values (4) 4
14.3%
Decimal Number
ValueCountFrequency (%)
0 4829
33.3%
3 3806
26.3%
6 3788
26.1%
1 1020
 
7.0%
8 471
 
3.3%
2 405
 
2.8%
4 63
 
0.4%
9 48
 
0.3%
5 34
 
0.2%
7 26
 
0.2%
Other Punctuation
ValueCountFrequency (%)
, 14
50.0%
. 12
42.9%
@ 2
 
7.1%
Open Punctuation
ValueCountFrequency (%)
( 297
87.1%
[ 44
 
12.9%
Close Punctuation
ValueCountFrequency (%)
) 297
87.1%
] 44
 
12.9%
Math Symbol
ValueCountFrequency (%)
→ 2
66.7%
~ 1
33.3%
Space Separator
ValueCountFrequency (%)
3014
100.0%
Lowercase Letter
ValueCountFrequency (%)
m 114
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 18744
50.5%
Common 18226
49.1%
Latin 142
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 4172
22.3%
방 3172
16.9%
전 3078
16.4%
면 2687
14.3%
이 606
 
3.2%
상 453
 
2.4%
향 313
 
1.7%
주 176
 
0.9%
회 167
 
0.9%
내 141
 
0.8%
Other values (380) 3779
20.2%
Common
ValueCountFrequency (%)
0 4829
26.5%
3 3806
20.9%
6 3788
20.8%
3014
16.5%
1 1020
 
5.6%
8 471
 
2.6%
2 405
 
2.2%
( 297
 
1.6%
) 297
 
1.6%
4 63
 
0.3%
Other values (11) 236
 
1.3%
Latin
ValueCountFrequency (%)
m 114
80.3%
T 5
 
3.5%
A 5
 
3.5%
C 3
 
2.1%
P 2
 
1.4%
S 2
 
1.4%
X 2
 
1.4%
K 2
 
1.4%
D 1
 
0.7%
U 1
 
0.7%
Other values (5) 5
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 18743
50.5%
ASCII 18366
49.5%
Arrows 2
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4829
26.3%
3 3806
20.7%
6 3788
20.6%
3014
16.4%
1 1020
 
5.6%
8 471
 
2.6%
2 405
 
2.2%
( 297
 
1.6%
) 297
 
1.6%
m 114
 
0.6%
Other values (25) 325
 
1.8%
Hangul
ValueCountFrequency (%)
도 4172
22.3%
방 3172
16.9%
전 3078
16.4%
면 2687
14.3%
이 606
 
3.2%
상 453
 
2.4%
향 313
 
1.7%
주 176
 
0.9%
회 167
 
0.9%
내 141
 
0.8%
Other values (379) 3778
20.2%
Arrows
ValueCountFrequency (%)
→ 2
100.0%
None
ValueCountFrequency (%)
㈜ 1
100.0%

보관일수
Real number (ℝ)

MISSING 

Distinct20
Distinct (%)0.2%
Missing734
Missing (%)7.3%
Infinite0
Infinite (%)0.0%
Mean29.755666
Minimum0
Maximum90
Zeros8
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-16T04:14:18.556423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile30
Q130
median30
Q330
95-th percentile30
Maximum90
Range90
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.9134452
Coefficient of variation (CV)0.097912282
Kurtosis168.80686
Mean29.755666
Median Absolute Deviation (MAD)0
Skewness2.5954733
Sum275716
Variance8.4881627
MonotonicityNot monotonic
2024-03-16T04:14:18.964586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
30 9094
90.9%
15 49
 
0.5%
10 43
 
0.4%
14 37
 
0.4%
0 8
 
0.1%
7 8
 
0.1%
90 7
 
0.1%
21 6
 
0.1%
5 3
 
< 0.1%
26 1
 
< 0.1%
Other values (10) 10
 
0.1%
(Missing) 734
 
7.3%
ValueCountFrequency (%)
0 8
 
0.1%
5 3
 
< 0.1%
7 8
 
0.1%
10 43
0.4%
12 1
 
< 0.1%
14 37
0.4%
15 49
0.5%
21 6
 
0.1%
25 1
 
< 0.1%
26 1
 
< 0.1%
ValueCountFrequency (%)
90 7
 
0.1%
59 1
 
< 0.1%
57 1
 
< 0.1%
53 1
 
< 0.1%
34 1
 
< 0.1%
33 1
 
< 0.1%
32 1
 
< 0.1%
30 9094
90.9%
28 1
 
< 0.1%
27 1
 
< 0.1%

설치연월
Date

MISSING 

Distinct180
Distinct (%)2.5%
Missing2691
Missing (%)26.9%
Memory size156.2 KiB
Minimum1998-06-01 00:00:00
Maximum2024-06-01 00:00:00
2024-03-16T04:14:19.322556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:14:19.814816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

관리기관전화번호
Text

Distinct146
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-16T04:14:20.415216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.3407
Min length12

Characters and Unicode

Total characters123407
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique58 ?
Unique (%)0.6%

Sample

1st row031-839-2330
2nd row031-310-3702
3rd row031-550-2551
4th row031-228-2591
5th row031-828-2633
ValueCountFrequency (%)
031-5189-3528 2213
22.1%
031-228-2591 843
 
8.4%
031-324-2304 682
 
6.8%
031-644-2942 494
 
4.9%
031-8024-5295 458
 
4.6%
031-770-2302 435
 
4.3%
032-625-4036 341
 
3.4%
031-481-3896 310
 
3.1%
031-940-8794 296
 
3.0%
031-729-2482 290
 
2.9%
Other values (136) 3638
36.4%
2024-03-16T04:14:21.776841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 20000
16.2%
3 18031
14.6%
0 17500
14.2%
2 13762
11.2%
1 13560
11.0%
8 11242
9.1%
5 9252
7.5%
9 6698
 
5.4%
4 6218
 
5.0%
7 3661
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 103407
83.8%
Dash Punctuation 20000
 
16.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 18031
17.4%
0 17500
16.9%
2 13762
13.3%
1 13560
13.1%
8 11242
10.9%
5 9252
8.9%
9 6698
 
6.5%
4 6218
 
6.0%
7 3661
 
3.5%
6 3483
 
3.4%
Dash Punctuation
ValueCountFrequency (%)
- 20000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 123407
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 20000
16.2%
3 18031
14.6%
0 17500
14.2%
2 13762
11.2%
1 13560
11.0%
8 11242
9.1%
5 9252
7.5%
9 6698
 
5.4%
4 6218
 
5.0%
7 3661
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 123407
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 20000
16.2%
3 18031
14.6%
0 17500
14.2%
2 13762
11.2%
1 13560
11.0%
8 11242
9.1%
5 9252
7.5%
9 6698
 
5.4%
4 6218
 
5.0%
7 3661
 
3.0%

위도
Real number (ℝ)

MISSING 

Distinct8749
Distinct (%)91.0%
Missing384
Missing (%)3.8%
Infinite0
Infinite (%)0.0%
Mean37.377027
Minimum36.915001
Maximum38.236346
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-16T04:14:22.326942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.915001
5-th percentile37.042134
Q137.208816
median37.306847
Q337.507243
95-th percentile37.844022
Maximum38.236346
Range1.3213456
Interquartile range (IQR)0.29842651

Descriptive statistics

Standard deviation0.24644831
Coefficient of variation (CV)0.0065935771
Kurtosis0.37194893
Mean37.377027
Median Absolute Deviation (MAD)0.1347133
Skewness0.85867974
Sum359417.49
Variance0.060736768
MonotonicityNot monotonic
2024-03-16T04:14:22.879668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.8969545 8
 
0.1%
37.4799450904 6
 
0.1%
37.2037541849 6
 
0.1%
37.4740971502 6
 
0.1%
37.53040803 6
 
0.1%
37.1291737733 5
 
0.1%
37.2083873538 5
 
0.1%
37.2142473381 4
 
< 0.1%
37.2934055085 4
 
< 0.1%
37.654779 4
 
< 0.1%
Other values (8739) 9562
95.6%
(Missing) 384
 
3.8%
ValueCountFrequency (%)
36.9150005182 1
< 0.1%
36.9157514905 1
< 0.1%
36.9161223194 1
< 0.1%
36.9168392141 1
< 0.1%
36.9199770195 1
< 0.1%
36.9203043244 1
< 0.1%
36.924897978 1
< 0.1%
36.9277525067 1
< 0.1%
36.9278099196 1
< 0.1%
36.935362243 1
< 0.1%
ValueCountFrequency (%)
38.2363461258 2
< 0.1%
38.2129545632 2
< 0.1%
38.2128758367 1
< 0.1%
38.1928771938 1
< 0.1%
38.1861562537 1
< 0.1%
38.1834907621 2
< 0.1%
38.182950099 1
< 0.1%
38.1809350861 1
< 0.1%
38.1806810207 1
< 0.1%
38.1798207386 2
< 0.1%

경도
Real number (ℝ)

MISSING 

Distinct8752
Distinct (%)91.0%
Missing384
Missing (%)3.8%
Infinite0
Infinite (%)0.0%
Mean127.05149
Minimum126.5219
Maximum127.81192
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-16T04:14:23.411728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.5219
5-th percentile126.74328
Q1126.8982
median127.04136
Q3127.14033
95-th percentile127.49684
Maximum127.81192
Range1.2900154
Interquartile range (IQR)0.24212772

Descriptive statistics

Standard deviation0.2249015
Coefficient of variation (CV)0.0017701603
Kurtosis0.29712198
Mean127.05149
Median Absolute Deviation (MAD)0.12562242
Skewness0.6862074
Sum1221727.1
Variance0.050580685
MonotonicityNot monotonic
2024-03-16T04:14:24.057980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.1826752 8
 
0.1%
127.0612380778 6
 
0.1%
126.8561667713 6
 
0.1%
126.849203233 6
 
0.1%
127.3735223 6
 
0.1%
127.1157116595 5
 
0.1%
126.9247725937 5
 
0.1%
126.8220669236 4
 
< 0.1%
126.638739 4
 
< 0.1%
126.9131285101 4
 
< 0.1%
Other values (8742) 9562
95.6%
(Missing) 384
 
3.8%
ValueCountFrequency (%)
126.521902 1
< 0.1%
126.533872 1
< 0.1%
126.537329 1
< 0.1%
126.541048 1
< 0.1%
126.544551 1
< 0.1%
126.547640313 1
< 0.1%
126.547867 1
< 0.1%
126.551171 1
< 0.1%
126.5535095 1
< 0.1%
126.55415 1
< 0.1%
ValueCountFrequency (%)
127.8119174141 1
< 0.1%
127.7725961 1
< 0.1%
127.7710573 1
< 0.1%
127.7649392 1
< 0.1%
127.763781 1
< 0.1%
127.7581963 1
< 0.1%
127.7572437 1
< 0.1%
127.7550419 1
< 0.1%
127.7543991 1
< 0.1%
127.7541669 1
< 0.1%

데이터기준일자
Date

Distinct29
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2017-01-01 00:00:00
Maximum2024-03-10 00:00:00
2024-03-16T04:14:24.509840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:14:24.976842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)

Interactions

2024-03-16T04:14:05.632090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:13:57.477447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:13:59.428116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:14:01.545963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:14:03.775209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:14:05.950655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:13:57.881298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:13:59.884290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:14:02.021932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:14:04.189296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:14:06.268199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:13:58.321478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:14:00.273774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:14:02.401021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:14:04.618591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:14:06.764060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:13:58.738885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:14:00.633342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:14:02.786253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:14:04.932135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:14:07.092961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:13:59.110317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:14:01.025842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:14:03.428886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:14:05.340051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-16T04:14:25.488706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리기관명설치목적구분카메라대수카메라화소수보관일수위도경도데이터기준일자
관리기관명1.0000.8790.5031.0000.7740.9620.9091.000
설치목적구분0.8791.0000.2430.4090.4420.6280.4460.769
카메라대수0.5030.2431.0000.0000.1930.1070.0390.232
카메라화소수1.0000.4090.0001.0000.0000.7950.7391.000
보관일수0.7740.4420.1930.0001.0000.2850.0720.447
위도0.9620.6280.1070.7950.2851.0000.5710.952
경도0.9090.4460.0390.7390.0720.5711.0000.889
데이터기준일자1.0000.7690.2321.0000.4470.9520.8891.000
2024-03-16T04:14:25.791418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
카메라대수카메라화소수보관일수위도경도설치목적구분
카메라대수1.000-0.1450.0720.271-0.0810.123
카메라화소수-0.1451.0000.0300.0390.2610.314
보관일수0.0720.0301.000-0.1390.0150.242
위도0.2710.039-0.1391.000-0.0540.237
경도-0.0810.2610.015-0.0541.0000.151
설치목적구분0.1230.3140.2420.2370.1511.000

Missing values

2024-03-16T04:14:07.493357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-16T04:14:08.065119image/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.
2024-03-16T04:14:08.513431image/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

관리기관명소재지도로명주소소재지지번주소설치목적구분카메라대수카메라화소수촬영방면정보보관일수설치연월관리기관전화번호위도경도데이터기준일자
28426연천군 안전총괄과<NA>경기도 연천군 전곡읍 전곡리 263-10생활방범2<NA><NA>302024-06031-839-233038.018229127.070232024-02-22
16978경기도 시흥시청경기도 시흥시 수인로3402번길 24-1경기도 시흥시 신천동 314-23생활방범1200360도 전방면302017-06031-310-370237.443877126.7807962017-01-01
4585경기도 구리시청경기도 구리시 안골로20번길 62경기도 구리시 교문동 757-6생활방범4200360도 전방면302017-07031-550-255137.594613127.1339432023-12-14
12217경기도 수원시경기도 수원시 팔달구 고등동 54-11경기도 수원시 팔달구 고등로71번길 19-23생활방범2200<NA>302022-08031-228-259137.274207127.0039922023-12-15
33620경기도 의정부시경기도 의정부시 평화로484번길 7 (의정부동)경기도 의정부시 의정부동 138-29생활방범5200360도 전방면302015-12031-828-263337.735358127.048452023-05-09
7733경기도 남양주시청경기도 남양주시 와부읍 수레로 108경기도 남양주시 와부읍 덕소리 252번지어린이보호4200예봉초교(정문)30<NA>031-590-430237.592088127.2211952020-01-28
2370경기도 광명시청 공원관리과<NA>경기도 광명시 일직동 293(새빛공원 4)다목적1200공원방범[96] 360도 전방면302018-1102-2680-793337.415721126.8883512022-12-13
33503경기도 의정부시경기도 의정부시 오목로122번길 20 (민락동)경기도 의정부시 민락동 579어린이보호4200360도 전방면302018-12031-828-263337.738022127.0945362023-05-09
11953경기도 수원시경기도 수원시 팔달구 화서동 407경기도 수원시 팔달구 화서동 407재난재해1130<NA>302015-06031-228-259137.283127126.9855052023-12-15
25206경기도 양평군청<NA>경기도 양평군 용문면 신점리 산86임시설물관리12000000180도 이상30<NA>031-770-230237.545287127.5830912020-06-12
관리기관명소재지도로명주소소재지지번주소설치목적구분카메라대수카메라화소수촬영방면정보보관일수설치연월관리기관전화번호위도경도데이터기준일자
39261평택시청<NA>경기도 평택시 죽백동 580-25생활방범4200360도 전방면302016-12031-8024-529537.003688127.1142532022-05-24
2710경기도 광명시청 정보통신과경기도 광명시 광명로848번길 14경기도 광명시 광명동 296-11번지생활방범5200생활방범 39 360도 전방면302017-0602-2680-650037.474267126.8529242022-12-13
54403경기도 화성시청<NA>경기도 화성시 병점동 203-15생활방범1200<NA>302019-01031-5189-352837.213054127.0517532024-01-15
38145경기도 파주시청<NA>경기도 파주시 상지석동 691-4생활방범3200360도전방면302013-06031-940-879437.733567126.7753742023-12-01
8078경기도 남양주시청<NA>경기도 남양주시 진건읍 진관리 산 59-4차량방범1200경춘북로(남양주 → 서울 방향)30<NA>031-590-430237.64739127.1650642020-01-28
52669경기도 화성시청<NA>경기도 화성시 장지동 982-5생활방범1200<NA>302018-12031-5189-352837.158337127.1139962024-01-15
53188경기도 화성시청<NA>경기도 화성시 목동 340생활방범1200<NA>302018-12031-5189-352837.181087127.1245242024-01-15
14538경기도 수원시경기도 수원시 장안구 율전동 273경기도 수원시 장안구 화산로187번길 34생활방범1200<NA>302019-12031-228-259137.297956126.9750582023-12-15
6243김포시 정보통신과<NA>경기도 김포시 감정동 660 (삼환어린이공원)생활방범4200360도전방면30<NA>031-980-561337.628419126.7009612020-02-27
8538경기도 부천시청경기도 부천시 중동로425번길 45경기도 부천시 삼정동 282다목적4<NA><NA>30<NA>032-625-403637.51783126.7666832022-05-25

Duplicate rows

Most frequently occurring

관리기관명소재지도로명주소소재지지번주소설치목적구분카메라대수카메라화소수촬영방면정보보관일수설치연월관리기관전화번호위도경도데이터기준일자# duplicates
17경기도 양평군청<NA>경기도 양평군 양서면 신원리 231-2답시설물관리12000000180도 이상30<NA>031-770-230237.530408127.3735222020-06-126
166경기도 화성시청<NA>경기도 화성시 남양리 2236생활방범1200<NA>302020-04031-5189-3528<NA><NA>2024-01-156
82경기도 화성시청경기도 화성시 동탄순환대로26길 55경기도 화성시 영천동 716생활방범1200<NA>302015-03031-5189-352837.208387127.1157122024-01-155
326경기도 화성시청<NA>경기도 화성시 영천동 897생활방범1200<NA>302023-09031-5189-3528<NA><NA>2024-01-155
121경기도 화성시청경기도 화성시 장안면 장안공단2길 26-17경기도 화성시 수촌리 1470-1생활방범1200<NA><NA>2023-10031-5189-352837.104731126.8488222024-01-154
196경기도 화성시청<NA>경기도 화성시 반송동 132-7생활방범1200<NA>302019-10031-5189-352837.197248127.0737742024-01-154
352경기도 화성시청<NA>경기도 화성시 장지동 974생활방범1200<NA>302018-12031-5189-352837.159701127.11082024-01-154
373경기도 화성시청<NA>경기도 화성시 진안동 930생활방범1200<NA>302006-01031-5189-352837.214247127.0415812024-01-154
403경기도 화성시청<NA>경기도 화성시 행정리 527-2(도)생활방범1200<NA>302014-01031-5189-352837.12617126.9131292024-01-154
405경기도 화성시청<NA>경기도 화성시 행정리 552생활방범1200<NA>302010-01031-5189-352837.126029126.9175962024-01-154