Overview

Dataset statistics

Number of variables13
Number of observations840
Missing cells39
Missing cells (%)0.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory89.5 KiB
Average record size in memory109.2 B

Variable types

Categorical7
Text2
Numeric3
DateTime1

Dataset

Description경상남도 남해군 CCTV 별 설치목적구분, 카메라대수, 카메라화소수, 촬영방면정보, 보관일수, 설치연월, 관리기관전화번호, 위도, 경도, 데이터기준일자 등에 대한 자료
Author경상남도 남해군
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15111802

Alerts

관리기관명 has constant value ""Constant
카메라대수 has constant value ""Constant
보관일수 has constant value ""Constant
관리기관전화번호 has constant value ""Constant
데이터기준일자 has constant value ""Constant
소재지도로명주소 is highly overall correlated with 카메라화소수 and 3 other fieldsHigh correlation
설치목적구분 is highly overall correlated with 소재지도로명주소High correlation
카메라화소수 is highly overall correlated with 소재지도로명주소High correlation
위도 is highly overall correlated with 소재지도로명주소High correlation
경도 is highly overall correlated with 소재지도로명주소High correlation
소재지도로명주소 is highly imbalanced (90.7%)Imbalance
소재지지번주소 has 28 (3.3%) missing valuesMissing
촬영방면정보 has unique valuesUnique

Reproduction

Analysis started2023-12-10 23:17:36.998159
Analysis finished2023-12-10 23:17:38.653568
Duration1.66 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.7 KiB
경상남도 남해군
840 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경상남도 남해군
2nd row경상남도 남해군
3rd row경상남도 남해군
4th row경상남도 남해군
5th row경상남도 남해군

Common Values

ValueCountFrequency (%)
경상남도 남해군 840
100.0%

Length

2023-12-11T08:17:38.701288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:17:38.777171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상남도 840
50.0%
남해군 840
50.0%

소재지도로명주소
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct10
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size6.7 KiB
<NA>
812 
경남 남해군 남해읍 화전로 43번길 16
 
6
경남 남해군 남면 남서대로748번길 7
 
5
경남 남해군 남해읍 화전로95번길 31-26
 
5
경남 남해군 설천면 설천로696번길 11
 
3
Other values (5)
 
9

Length

Max length27
Median length4
Mean length4.6095238
Min length4

Unique

Unique2 ?
Unique (%)0.2%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 812
96.7%
경남 남해군 남해읍 화전로 43번길 16 6
 
0.7%
경남 남해군 남면 남서대로748번길 7 5
 
0.6%
경남 남해군 남해읍 화전로95번길 31-26 5
 
0.6%
경남 남해군 설천면 설천로696번길 11 3
 
0.4%
경남 남해군 남해읍 화전로78번길 26 3
 
0.4%
경남 남해군 남해읍 망운로9번길 12 2
 
0.2%
경남 남해군 삼동면 동부대로1030번길 42-26 2
 
0.2%
경남 남해군 남해읍 화전로 78번길 30 1
 
0.1%
경남 남해군 미조면 미조로236번길 21 1
 
0.1%

Length

2023-12-11T08:17:38.868941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:17:38.982687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 812
84.7%
남해군 28
 
2.9%
경남 28
 
2.9%
남해읍 17
 
1.8%
화전로 7
 
0.7%
43번길 6
 
0.6%
16 6
 
0.6%
남면 5
 
0.5%
남서대로748번길 5
 
0.5%
7 5
 
0.5%
Other values (17) 40
 
4.2%

소재지지번주소
Text

MISSING 

Distinct387
Distinct (%)47.7%
Missing28
Missing (%)3.3%
Memory size6.7 KiB
2023-12-11T08:17:39.298810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length26
Mean length19.839901
Min length16

Characters and Unicode

Total characters16110
Distinct characters123
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

Unique124 ?
Unique (%)15.3%

Sample

1st row경남 남해군 고현면 대사리 689-3
2nd row경남 남해군 고현면 대사리 689-3
3rd row경남 남해군 고현면 대사리 689-3
4th row경남 남해군 고현면 대사리 1398-11
5th row경남 남해군 고현면 대사리 1398-11
ValueCountFrequency (%)
남해군 813
19.9%
경남 812
19.9%
남해읍 263
 
6.5%
창선면 92
 
2.3%
삼동면 75
 
1.8%
북변리 73
 
1.8%
미조면 66
 
1.6%
남면 63
 
1.5%
서면 62
 
1.5%
이동면 59
 
1.4%
Other values (469) 1698
41.7%
2023-12-11T08:17:39.729542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3314
20.6%
남 2005
12.4%
해 1079
 
6.7%
군 813
 
5.0%
경 812
 
5.0%
리 780
 
4.8%
1 732
 
4.5%
- 627
 
3.9%
면 551
 
3.4%
2 444
 
2.8%
Other values (113) 4953
30.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8864
55.0%
Space Separator 3314
 
20.6%
Decimal Number 3283
 
20.4%
Dash Punctuation 627
 
3.9%
Close Punctuation 11
 
0.1%
Open Punctuation 11
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 2005
22.6%
해 1079
12.2%
군 813
 
9.2%
경 812
 
9.2%
리 780
 
8.8%
면 551
 
6.2%
읍 263
 
3.0%
변 167
 
1.9%
동 159
 
1.8%
서 156
 
1.8%
Other values (99) 2079
23.5%
Decimal Number
ValueCountFrequency (%)
1 732
22.3%
2 444
13.5%
4 369
11.2%
3 342
10.4%
5 285
 
8.7%
6 243
 
7.4%
7 236
 
7.2%
0 219
 
6.7%
9 219
 
6.7%
8 194
 
5.9%
Space Separator
ValueCountFrequency (%)
3314
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 627
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8864
55.0%
Common 7246
45.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 2005
22.6%
해 1079
12.2%
군 813
 
9.2%
경 812
 
9.2%
리 780
 
8.8%
면 551
 
6.2%
읍 263
 
3.0%
변 167
 
1.9%
동 159
 
1.8%
서 156
 
1.8%
Other values (99) 2079
23.5%
Common
ValueCountFrequency (%)
3314
45.7%
1 732
 
10.1%
- 627
 
8.7%
2 444
 
6.1%
4 369
 
5.1%
3 342
 
4.7%
5 285
 
3.9%
6 243
 
3.4%
7 236
 
3.3%
0 219
 
3.0%
Other values (4) 435
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8864
55.0%
ASCII 7246
45.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3314
45.7%
1 732
 
10.1%
- 627
 
8.7%
2 444
 
6.1%
4 369
 
5.1%
3 342
 
4.7%
5 285
 
3.9%
6 243
 
3.4%
7 236
 
3.3%
0 219
 
3.0%
Other values (4) 435
 
6.0%
Hangul
ValueCountFrequency (%)
남 2005
22.6%
해 1079
12.2%
군 813
 
9.2%
경 812
 
9.2%
리 780
 
8.8%
면 551
 
6.2%
읍 263
 
3.0%
변 167
 
1.9%
동 159
 
1.8%
서 156
 
1.8%
Other values (99) 2079
23.5%

설치목적구분
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size6.7 KiB
생활방범
403 
어린이보호
165 
재난재해
88 
시설물관리
69 
기타
 
36
Other values (3)
79 

Length

Max length5
Median length4
Mean length4.227381
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
생활방범 403
48.0%
어린이보호 165
19.6%
재난재해 88
 
10.5%
시설물관리 69
 
8.2%
기타 36
 
4.3%
공원방범 35
 
4.2%
쓰레기단속 29
 
3.5%
교통단속 15
 
1.8%

Length

2023-12-11T08:17:39.845431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:17:39.963129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
생활방범 403
48.0%
어린이보호 165
19.6%
재난재해 88
 
10.5%
시설물관리 69
 
8.2%
기타 36
 
4.3%
공원방범 35
 
4.2%
쓰레기단속 29
 
3.5%
교통단속 15
 
1.8%

카메라대수
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.7 KiB
1
840 

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 (%)
1 840
100.0%

Length

2023-12-11T08:17:40.074202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:17:40.154940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 840
100.0%

카메라화소수
Real number (ℝ)

HIGH CORRELATION 

Distinct11
Distinct (%)1.3%
Missing4
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean209.79665
Minimum130
Maximum500
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2023-12-11T08:17:40.222178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum130
5-th percentile200
Q1200
median200
Q3200
95-th percentile300
Maximum500
Range370
Interquartile range (IQR)0

Descriptive statistics

Standard deviation50.063019
Coefficient of variation (CV)0.2386264
Kurtosis17.55399
Mean209.79665
Median Absolute Deviation (MAD)0
Skewness3.6978052
Sum175390
Variance2506.3059
MonotonicityNot monotonic
2023-12-11T08:17:40.310964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
200 715
85.1%
130 36
 
4.3%
300 35
 
4.2%
280 23
 
2.7%
500 13
 
1.5%
400 8
 
1.0%
201 2
 
0.2%
202 1
 
0.1%
203 1
 
0.1%
131 1
 
0.1%
(Missing) 4
 
0.5%
ValueCountFrequency (%)
130 36
 
4.3%
131 1
 
0.1%
132 1
 
0.1%
200 715
85.1%
201 2
 
0.2%
202 1
 
0.1%
203 1
 
0.1%
280 23
 
2.7%
300 35
 
4.2%
400 8
 
1.0%
ValueCountFrequency (%)
500 13
 
1.5%
400 8
 
1.0%
300 35
 
4.2%
280 23
 
2.7%
203 1
 
0.1%
202 1
 
0.1%
201 2
 
0.2%
200 715
85.1%
132 1
 
0.1%
131 1
 
0.1%

촬영방면정보
Text

UNIQUE 

Distinct840
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size6.7 KiB
2023-12-11T08:17:40.496585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length32
Mean length23.763095
Min length9

Characters and Unicode

Total characters19961
Distinct characters345
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique840 ?
Unique (%)100.0%

Sample

1st row고현_생활방범_고현면사무소_정보고정문_설천방향_(번호인식)
2nd row고현_생활방범_고현면사무소_정보고정문_설천방향_(회전)
3rd row고현_생활방범_고현면사무소_정보고정문_읍방향_(번호인식)
4th row고현_생활방범_대사마을입구삼거리_대사마을방향
5th row고현_생활방범_대사마을입구삼거리_설천방향_(회전)
ValueCountFrequency (%)
앞 19
 
1.8%
삼동_재난감시_화천 6
 
0.6%
서면_공원방범_스포츠파크 4
 
0.4%
서면_번호인식_연죽삼거리 4
 
0.4%
남해읍_생활방범_노인복지회관앞 4
 
0.4%
남해읍_생활방범_신기마을 4
 
0.4%
회관 4
 
0.4%
이동_생활방범_장평소류지 4
 
0.4%
남해읍_생활방범_카페아호이 4
 
0.4%
고현_생활방범_농공단지 4
 
0.4%
Other values (916) 977
94.5%
2023-12-11T08:17:40.824266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
_ 2888
 
14.5%
방 1061
 
5.3%
향 609
 
3.1%
회 544
 
2.7%
남 497
 
2.5%
) 496
 
2.5%
( 494
 
2.5%
전 481
 
2.4%
범 438
 
2.2%
해 429
 
2.1%
Other values (335) 12024
60.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15748
78.9%
Connector Punctuation 2888
 
14.5%
Close Punctuation 496
 
2.5%
Open Punctuation 494
 
2.5%
Space Separator 194
 
1.0%
Decimal Number 46
 
0.2%
Dash Punctuation 39
 
0.2%
Math Symbol 28
 
0.1%
Other Punctuation 20
 
0.1%
Uppercase Letter 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
방 1061
 
6.7%
향 609
 
3.9%
회 544
 
3.5%
남 497
 
3.2%
전 481
 
3.1%
범 438
 
2.8%
해 429
 
2.7%
생 405
 
2.6%
활 404
 
2.6%
이 341
 
2.2%
Other values (312) 10539
66.9%
Decimal Number
ValueCountFrequency (%)
2 17
37.0%
1 13
28.3%
3 4
 
8.7%
4 3
 
6.5%
6 3
 
6.5%
5 3
 
6.5%
7 1
 
2.2%
8 1
 
2.2%
9 1
 
2.2%
Uppercase Letter
ValueCountFrequency (%)
T 2
25.0%
K 2
25.0%
C 1
12.5%
U 1
12.5%
G 1
12.5%
S 1
12.5%
Other Punctuation
ValueCountFrequency (%)
. 18
90.0%
, 2
 
10.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2888
100.0%
Close Punctuation
ValueCountFrequency (%)
) 496
100.0%
Open Punctuation
ValueCountFrequency (%)
( 494
100.0%
Space Separator
ValueCountFrequency (%)
194
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 39
100.0%
Math Symbol
ValueCountFrequency (%)
> 28
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15748
78.9%
Common 4205
 
21.1%
Latin 8
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
방 1061
 
6.7%
향 609
 
3.9%
회 544
 
3.5%
남 497
 
3.2%
전 481
 
3.1%
범 438
 
2.8%
해 429
 
2.7%
생 405
 
2.6%
활 404
 
2.6%
이 341
 
2.2%
Other values (312) 10539
66.9%
Common
ValueCountFrequency (%)
_ 2888
68.7%
) 496
 
11.8%
( 494
 
11.7%
194
 
4.6%
- 39
 
0.9%
> 28
 
0.7%
. 18
 
0.4%
2 17
 
0.4%
1 13
 
0.3%
3 4
 
0.1%
Other values (7) 14
 
0.3%
Latin
ValueCountFrequency (%)
T 2
25.0%
K 2
25.0%
C 1
12.5%
U 1
12.5%
G 1
12.5%
S 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15748
78.9%
ASCII 4213
 
21.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
_ 2888
68.5%
) 496
 
11.8%
( 494
 
11.7%
194
 
4.6%
- 39
 
0.9%
> 28
 
0.7%
. 18
 
0.4%
2 17
 
0.4%
1 13
 
0.3%
3 4
 
0.1%
Other values (13) 22
 
0.5%
Hangul
ValueCountFrequency (%)
방 1061
 
6.7%
향 609
 
3.9%
회 544
 
3.5%
남 497
 
3.2%
전 481
 
3.1%
범 438
 
2.8%
해 429
 
2.7%
생 405
 
2.6%
활 404
 
2.6%
이 341
 
2.2%
Other values (312) 10539
66.9%

보관일수
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.7 KiB
30
840 

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 (%)
30 840
100.0%

Length

2023-12-11T08:17:40.929629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:17:41.006918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
30 840
100.0%

설치연월
Date

Distinct72
Distinct (%)8.6%
Missing7
Missing (%)0.8%
Memory size6.7 KiB
Minimum2007-01-01 00:00:00
Maximum2022-05-01 00:00:00
2023-12-11T08:17:41.092598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:17:41.476171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

관리기관전화번호
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.7 KiB
055-860-8811
840 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row055-860-8811
2nd row055-860-8811
3rd row055-860-8811
4th row055-860-8811
5th row055-860-8811

Common Values

ValueCountFrequency (%)
055-860-8811 840
100.0%

Length

2023-12-11T08:17:41.592637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:17:41.674602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
055-860-8811 840
100.0%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct394
Distinct (%)46.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.824352
Minimum34.697416
Maximum34.942243
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2023-12-11T08:17:41.789916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34.697416
5-th percentile34.719484
Q134.799953
median34.835156
Q334.846913
95-th percentile34.917383
Maximum34.942243
Range0.244827
Interquartile range (IQR)0.0469595

Descriptive statistics

Standard deviation0.054615455
Coefficient of variation (CV)0.0015683122
Kurtosis-0.10861892
Mean34.824352
Median Absolute Deviation (MAD)0.026396
Skewness-0.28905116
Sum29252.456
Variance0.002982848
MonotonicityNot monotonic
2023-12-11T08:17:41.967266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34.83768 11
 
1.3%
34.9173826 9
 
1.1%
34.835469 6
 
0.7%
34.838207 6
 
0.7%
34.789077 6
 
0.7%
34.715965 6
 
0.7%
34.83363 6
 
0.7%
34.715658 5
 
0.6%
34.842226 5
 
0.6%
34.913367 5
 
0.6%
Other values (384) 775
92.3%
ValueCountFrequency (%)
34.697416 2
0.2%
34.705225 1
0.1%
34.705611 1
0.1%
34.707825 1
0.1%
34.708457 2
0.2%
34.709927 2
0.2%
34.71028 2
0.2%
34.710604 1
0.1%
34.711594 1
0.1%
34.711985 1
0.1%
ValueCountFrequency (%)
34.942243 2
0.2%
34.941176 2
0.2%
34.941144 1
0.1%
34.941019 2
0.2%
34.941012 1
0.1%
34.937644 1
0.1%
34.937086 2
0.2%
34.936147 2
0.2%
34.934927 2
0.2%
34.932546 2
0.2%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct397
Distinct (%)47.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.93254
Minimum127.81926
Maximum128.06304
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2023-12-11T08:17:42.094121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.81926
5-th percentile127.83915
Q1127.89023
median127.89776
Q3128.00085
95-th percentile128.04595
Maximum128.06304
Range0.243783
Interquartile range (IQR)0.1106195

Descriptive statistics

Standard deviation0.06559106
Coefficient of variation (CV)0.00051270038
Kurtosis-1.114213
Mean127.93254
Median Absolute Deviation (MAD)0.0266655
Skewness0.52918986
Sum107463.33
Variance0.0043021872
MonotonicityNot monotonic
2023-12-11T08:17:42.221648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.892601 11
 
1.3%
128.0291597 9
 
1.1%
128.02119 6
 
0.7%
127.893206 6
 
0.7%
128.043768 6
 
0.7%
128.04152 5
 
0.6%
127.890017 5
 
0.6%
127.898687 5
 
0.6%
127.894971 5
 
0.6%
128.029757 5
 
0.6%
Other values (387) 777
92.5%
ValueCountFrequency (%)
127.81926 2
0.2%
127.819578 2
0.2%
127.82198 1
 
0.1%
127.828108 2
0.2%
127.829575 3
0.4%
127.831398 2
0.2%
127.83243 2
0.2%
127.833095 2
0.2%
127.833226 1
 
0.1%
127.833523 1
 
0.1%
ValueCountFrequency (%)
128.063043 1
 
0.1%
128.060297 2
0.2%
128.057757 2
0.2%
128.056093 2
0.2%
128.054114 1
 
0.1%
128.053346 3
0.4%
128.052839 2
0.2%
128.052631 2
0.2%
128.050464 2
0.2%
128.050339 2
0.2%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.7 KiB
2023-01-10
840 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-01-10
2nd row2023-01-10
3rd row2023-01-10
4th row2023-01-10
5th row2023-01-10

Common Values

ValueCountFrequency (%)
2023-01-10 840
100.0%

Length

2023-12-11T08:17:42.338570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:17:42.435099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-01-10 840
100.0%

Interactions

2023-12-11T08:17:38.073639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:17:37.536968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:17:37.820597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:17:38.152785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:17:37.637999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:17:37.923267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:17:38.230749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:17:37.735708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:17:37.999865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T08:17:42.491563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지도로명주소설치목적구분카메라화소수설치연월위도경도
소재지도로명주소1.0001.0001.0001.0001.0001.000
설치목적구분1.0001.0000.5340.9490.3360.281
카메라화소수1.0000.5341.0000.9380.3690.288
설치연월1.0000.9490.9381.0000.7770.710
위도1.0000.3360.3690.7771.0000.795
경도1.0000.2810.2880.7100.7951.000
2023-12-11T08:17:42.581167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지도로명주소설치목적구분
소재지도로명주소1.0000.909
설치목적구분0.9091.000
2023-12-11T08:17:42.677109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
카메라화소수위도경도소재지도로명주소설치목적구분
카메라화소수1.000-0.0190.0320.8250.344
위도-0.0191.000-0.2660.9090.167
경도0.032-0.2661.0000.8720.138
소재지도로명주소0.8250.9090.8721.0000.909
설치목적구분0.3440.1670.1380.9091.000

Missing values

2023-12-11T08:17:38.341255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:17:38.488593image/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.
2023-12-11T08:17:38.602478image/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
0경상남도 남해군<NA>경남 남해군 고현면 대사리 689-3생활방범1200고현_생활방범_고현면사무소_정보고정문_설천방향_(번호인식)302021-04055-860-881134.895666127.8734672023-01-10
1경상남도 남해군<NA>경남 남해군 고현면 대사리 689-3생활방범1200고현_생활방범_고현면사무소_정보고정문_설천방향_(회전)302017-07055-860-881134.895666127.8734662023-01-10
2경상남도 남해군<NA>경남 남해군 고현면 대사리 689-3생활방범1200고현_생활방범_고현면사무소_정보고정문_읍방향_(번호인식)302021-04055-860-881134.895666127.8734672023-01-10
3경상남도 남해군<NA>경남 남해군 고현면 대사리 1398-11생활방범1200고현_생활방범_대사마을입구삼거리_대사마을방향302018-06055-860-881134.896496127.8793922023-01-10
4경상남도 남해군<NA>경남 남해군 고현면 대사리 1398-11생활방범1200고현_생활방범_대사마을입구삼거리_설천방향_(회전)302018-06055-860-881134.896496127.8793922023-01-10
5경상남도 남해군<NA>경남 남해군 고현면 포상리 979-2생활방범1200고현_생활방범_천동마을삼거리_갈화방향)302016-06055-860-881134.896795127.8699742023-01-10
6경상남도 남해군<NA>경남 남해군 고현면 포상리 979-2생활방범1200고현_생활방범_천동마을삼거리_정보고방향_(회전)302016-06055-860-881134.896795127.8699742023-01-10
7경상남도 남해군<NA>경남 남해군 고현면 오곡리 389-3생활방범1200고현_생활방범_관당마을앞_마을방향_(회전)302019-03055-860-881134.894405127.8819172023-01-10
8경상남도 남해군<NA>경남 남해군 고현면 오곡리 389-3생활방범1200고현_생활방범_관당마을앞_설천방향302019-03055-860-881134.894405127.8819172023-01-10
9경상남도 남해군<NA>경남 남해군 고현면 대곡리 568-6생활방범1200고현_생활방범_대곡저수지밑_대곡방향302019-03055-860-881134.868224127.8822872023-01-10
관리기관명소재지도로명주소소재지지번주소설치목적구분카메라대수카메라화소수촬영방면정보보관일수설치연월관리기관전화번호위도경도데이터기준일자
830경상남도 남해군<NA>경남 남해군 서면 중현리 1461-1기타1132서면_번호인식_중현삼거리_스포츠파크->고현302012-01055-860-881134.872681127.8281082023-01-10
831경상남도 남해군<NA>경남 남해군 서면 대정리 551-1기타1280서면_번호인식_연죽삼거리 서면방향_남해읍->서면302010-01055-860-881134.815877127.8699952023-01-10
832경상남도 남해군<NA>경남 남해군 서면 대정리 551-1기타1280서면_번호인식_연죽삼거리 서면방향_서면->남해읍302010-01055-860-881134.815877127.8699952023-01-10
833경상남도 남해군<NA>경남 남해군 이동면 용소리 1492-3기타1280이동_번호인식_이동 남면 경계_이동면->남면302010-01055-860-881134.773132127.9167482023-01-10
834경상남도 남해군<NA>경남 남해군 이동면 용소리 1492-3기타1280이동_번호인식_이동 남면 경계_남면->이동면302010-01055-860-881134.773132127.9167482023-01-10
835경상남도 남해군<NA>경남 남해군 설천면 덕신리 1351-11기타1280설천_번호인식_노량대교_하동방면1302018-09055-860-881134.931382127.8670272023-01-10
836경상남도 남해군<NA>경남 남해군 설천면 덕신리 1351-11기타1280설천_번호인식_노량대교_하동방면2302018-09055-860-881134.931382127.8670272023-01-10
837경상남도 남해군<NA>경남 남해군 설천면 덕신리 1345-4기타1280설천_번호인식_노량대교_남해방면1302018-09055-860-881134.932546127.8679892023-01-10
838경상남도 남해군<NA>경남 남해군 설천면 덕신리 1345-4기타1280설천_번호인식_노량대교_남해방면2302018-09055-860-881134.932546127.8679892023-01-10
839경상남도 남해군<NA>경남 남해군 설천면 노량리 511-1기타1280설천_번호인식_노량대교_감암마을방향302018-09055-860-881134.937644127.8680952023-01-10