Overview

Dataset statistics

Number of variables13
Number of observations118
Missing cells79
Missing cells (%)5.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.7 KiB
Average record size in memory110.1 B

Variable types

Categorical5
Text2
Numeric4
DateTime2

Dataset

Description공공데이터 제공 표준데이터 속성정보(허용값, 표현형식/단위 등)는 [공공데이터 제공 표준] 전문을 참고하시기 바랍니다.(공공데이터포털>정보공유>자료실)
URLhttps://www.data.go.kr/data/15013094/fileData.do

Alerts

촬영방면정보 is highly overall correlated with 카메라대수 and 5 other fieldsHigh correlation
보관일수 is highly overall correlated with 관리기관명 and 3 other fieldsHigh correlation
설치목적구분 is highly overall correlated with 관리기관명 and 3 other fieldsHigh correlation
관리기관명 is highly overall correlated with 카메라화소수 and 4 other fieldsHigh correlation
관리기관전화번호 is highly overall correlated with 카메라대수 and 5 other fieldsHigh correlation
카메라대수 is highly overall correlated with 촬영방면정보 and 1 other fieldsHigh correlation
카메라화소수 is highly overall correlated with 관리기관명 and 2 other fieldsHigh correlation
소재지도로명주소 has 47 (39.8%) missing valuesMissing
소재지지번주소 has 7 (5.9%) missing valuesMissing
카메라화소수 has 7 (5.9%) missing valuesMissing
설치연월 has 9 (7.6%) missing valuesMissing
위도 has 5 (4.2%) missing valuesMissing
경도 has 4 (3.4%) missing valuesMissing

Reproduction

Analysis started2023-12-12 07:36:15.427147
Analysis finished2023-12-12 07:36:18.423610
Duration3 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리기관명
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
수원도시공사 견인거주자팀
56 
수원도시공사
55 
수원도시공사 환승센터
 
4
광교웰빙국민체육센터
 
1
서수원칠보체육관(수원도시공사)
 
1

Length

Max length16
Median length13
Mean length9.6101695
Min length6

Unique

Unique3 ?
Unique (%)2.5%

Sample

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

Common Values

ValueCountFrequency (%)
수원도시공사 견인거주자팀 56
47.5%
수원도시공사 55
46.6%
수원도시공사 환승센터 4
 
3.4%
광교웰빙국민체육센터 1
 
0.8%
서수원칠보체육관(수원도시공사) 1
 
0.8%
장안구민회관 1
 
0.8%

Length

2023-12-12T16:36:18.498398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:36:18.646222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수원도시공사 115
64.6%
견인거주자팀 56
31.5%
환승센터 4
 
2.2%
광교웰빙국민체육센터 1
 
0.6%
서수원칠보체육관(수원도시공사 1
 
0.6%
장안구민회관 1
 
0.6%

소재지도로명주소
Text

MISSING 

Distinct63
Distinct (%)88.7%
Missing47
Missing (%)39.8%
Memory size1.1 KiB
2023-12-12T16:36:18.976385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length30
Mean length26.014085
Min length15

Characters and Unicode

Total characters1847
Distinct characters109
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

Unique58 ?
Unique (%)81.7%

Sample

1st row경기도 수원시 장안구 광교산로 160 (하광교동)
2nd row경기도 수원시 영통구 봉영로 1598 (영통동)
3rd row경기도 수원시 권선구 정조로 291 (대황교동)
4th row경기도 수원시 권선구 정조로 379 (세류동)
5th row경기도 수원시 권선구 경수대로 270 (권선동)
ValueCountFrequency (%)
수원시 70
17.4%
경기도 67
 
16.7%
영통구 27
 
6.7%
권선구 19
 
4.7%
장안구 16
 
4.0%
팔달구 12
 
3.0%
광교호수로 10
 
2.5%
278-1(하동 4
 
1.0%
수원시자원순환센터 4
 
1.0%
정조로 4
 
1.0%
Other values (130) 169
42.0%
2023-12-12T16:36:19.524282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
331
 
17.9%
수 99
 
5.4%
원 93
 
5.0%
시 78
 
4.2%
구 75
 
4.1%
경 71
 
3.8%
도 68
 
3.7%
기 68
 
3.7%
로 62
 
3.4%
1 54
 
2.9%
Other values (99) 848
45.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1157
62.6%
Space Separator 331
 
17.9%
Decimal Number 259
 
14.0%
Close Punctuation 42
 
2.3%
Open Punctuation 42
 
2.3%
Dash Punctuation 16
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 99
 
8.6%
원 93
 
8.0%
시 78
 
6.7%
구 75
 
6.5%
경 71
 
6.1%
도 68
 
5.9%
기 68
 
5.9%
로 62
 
5.4%
동 53
 
4.6%
영 38
 
3.3%
Other values (85) 452
39.1%
Decimal Number
ValueCountFrequency (%)
1 54
20.8%
2 37
14.3%
3 25
9.7%
7 25
9.7%
0 24
9.3%
8 22
8.5%
4 21
 
8.1%
6 19
 
7.3%
5 17
 
6.6%
9 15
 
5.8%
Space Separator
ValueCountFrequency (%)
331
100.0%
Close Punctuation
ValueCountFrequency (%)
) 42
100.0%
Open Punctuation
ValueCountFrequency (%)
( 42
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1157
62.6%
Common 690
37.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 99
 
8.6%
원 93
 
8.0%
시 78
 
6.7%
구 75
 
6.5%
경 71
 
6.1%
도 68
 
5.9%
기 68
 
5.9%
로 62
 
5.4%
동 53
 
4.6%
영 38
 
3.3%
Other values (85) 452
39.1%
Common
ValueCountFrequency (%)
331
48.0%
1 54
 
7.8%
) 42
 
6.1%
( 42
 
6.1%
2 37
 
5.4%
3 25
 
3.6%
7 25
 
3.6%
0 24
 
3.5%
8 22
 
3.2%
4 21
 
3.0%
Other values (4) 67
 
9.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1157
62.6%
ASCII 690
37.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
331
48.0%
1 54
 
7.8%
) 42
 
6.1%
( 42
 
6.1%
2 37
 
5.4%
3 25
 
3.6%
7 25
 
3.6%
0 24
 
3.5%
8 22
 
3.2%
4 21
 
3.0%
Other values (4) 67
 
9.7%
Hangul
ValueCountFrequency (%)
수 99
 
8.6%
원 93
 
8.0%
시 78
 
6.7%
구 75
 
6.5%
경 71
 
6.1%
도 68
 
5.9%
기 68
 
5.9%
로 62
 
5.4%
동 53
 
4.6%
영 38
 
3.3%
Other values (85) 452
39.1%

소재지지번주소
Text

MISSING 

Distinct106
Distinct (%)95.5%
Missing7
Missing (%)5.9%
Memory size1.1 KiB
2023-12-12T16:36:19.906346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length32
Mean length18.747748
Min length6

Characters and Unicode

Total characters2081
Distinct characters116
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique102 ?
Unique (%)91.9%

Sample

1st row경기도 수원시 장안구 하광교동 403-1
2nd row경기도 수원시 영통구 영통동 995-3
3rd row경기도 수원시 권선구 대황교동 259-5
4th row경기도 수원시 권선구 장지동 44-10
5th row경기도 수원시 권선구 권선동 1189
ValueCountFrequency (%)
수원시 79
 
16.4%
경기도 75
 
15.6%
영통구 25
 
5.2%
권선구 24
 
5.0%
팔달구 17
 
3.5%
장안구 17
 
3.5%
곡반정동 9
 
1.9%
하동 7
 
1.5%
이의동 6
 
1.2%
조원1동 6
 
1.2%
Other values (139) 216
44.9%
2023-12-12T16:36:20.332445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
370
17.8%
동 110
 
5.3%
1 102
 
4.9%
원 99
 
4.8%
수 91
 
4.4%
시 88
 
4.2%
구 86
 
4.1%
경 76
 
3.7%
기 76
 
3.7%
도 76
 
3.7%
Other values (106) 907
43.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1189
57.1%
Decimal Number 445
 
21.4%
Space Separator 370
 
17.8%
Dash Punctuation 70
 
3.4%
Uppercase Letter 3
 
0.1%
Close Punctuation 2
 
0.1%
Open Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 110
 
9.3%
원 99
 
8.3%
수 91
 
7.7%
시 88
 
7.4%
구 86
 
7.2%
경 76
 
6.4%
기 76
 
6.4%
도 76
 
6.4%
영 32
 
2.7%
통 30
 
2.5%
Other values (90) 425
35.7%
Decimal Number
ValueCountFrequency (%)
1 102
22.9%
2 63
14.2%
4 44
9.9%
5 40
 
9.0%
3 38
 
8.5%
8 35
 
7.9%
9 33
 
7.4%
7 32
 
7.2%
0 31
 
7.0%
6 27
 
6.1%
Uppercase Letter
ValueCountFrequency (%)
S 2
66.7%
B 1
33.3%
Space Separator
ValueCountFrequency (%)
370
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 70
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1189
57.1%
Common 889
42.7%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 110
 
9.3%
원 99
 
8.3%
수 91
 
7.7%
시 88
 
7.4%
구 86
 
7.2%
경 76
 
6.4%
기 76
 
6.4%
도 76
 
6.4%
영 32
 
2.7%
통 30
 
2.5%
Other values (90) 425
35.7%
Common
ValueCountFrequency (%)
370
41.6%
1 102
 
11.5%
- 70
 
7.9%
2 63
 
7.1%
4 44
 
4.9%
5 40
 
4.5%
3 38
 
4.3%
8 35
 
3.9%
9 33
 
3.7%
7 32
 
3.6%
Other values (4) 62
 
7.0%
Latin
ValueCountFrequency (%)
S 2
66.7%
B 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1189
57.1%
ASCII 892
42.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
370
41.5%
1 102
 
11.4%
- 70
 
7.8%
2 63
 
7.1%
4 44
 
4.9%
5 40
 
4.5%
3 38
 
4.3%
8 35
 
3.9%
9 33
 
3.7%
7 32
 
3.6%
Other values (6) 65
 
7.3%
Hangul
ValueCountFrequency (%)
동 110
 
9.3%
원 99
 
8.3%
수 91
 
7.7%
시 88
 
7.4%
구 86
 
7.2%
경 76
 
6.4%
기 76
 
6.4%
도 76
 
6.4%
영 32
 
2.7%
통 30
 
2.5%
Other values (90) 425
35.7%

설치목적구분
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
시설물관리
58 
차량방범
51 
다목적
7 
기타
 
1
생활방범
 
1

Length

Max length5
Median length4
Mean length4.4152542
Min length2

Unique

Unique2 ?
Unique (%)1.7%

Sample

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

Common Values

ValueCountFrequency (%)
시설물관리 58
49.2%
차량방범 51
43.2%
다목적 7
 
5.9%
기타 1
 
0.8%
생활방범 1
 
0.8%

Length

2023-12-12T16:36:20.523889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:36:20.641740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
시설물관리 58
49.2%
차량방범 51
43.2%
다목적 7
 
5.9%
기타 1
 
0.8%
생활방범 1
 
0.8%

카메라대수
Real number (ℝ)

HIGH CORRELATION 

Distinct37
Distinct (%)31.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.915254
Minimum1
Maximum275
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T16:36:20.740311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q14
median8.5
Q315.75
95-th percentile51.75
Maximum275
Range274
Interquartile range (IQR)11.75

Descriptive statistics

Standard deviation28.206072
Coefficient of variation (CV)1.7722665
Kurtosis61.454798
Mean15.915254
Median Absolute Deviation (MAD)4.5
Skewness6.9826842
Sum1878
Variance795.5825
MonotonicityNot monotonic
2023-12-12T16:36:20.861218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
4 16
 
13.6%
8 11
 
9.3%
5 9
 
7.6%
9 8
 
6.8%
3 7
 
5.9%
2 7
 
5.9%
6 6
 
5.1%
10 5
 
4.2%
14 5
 
4.2%
16 4
 
3.4%
Other values (27) 40
33.9%
ValueCountFrequency (%)
1 2
 
1.7%
2 7
5.9%
3 7
5.9%
4 16
13.6%
5 9
7.6%
6 6
 
5.1%
7 1
 
0.8%
8 11
9.3%
9 8
6.8%
10 5
 
4.2%
ValueCountFrequency (%)
275 1
0.8%
76 1
0.8%
64 1
0.8%
60 1
0.8%
59 1
0.8%
56 1
0.8%
51 1
0.8%
50 1
0.8%
48 1
0.8%
44 1
0.8%

카메라화소수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct7
Distinct (%)6.3%
Missing7
Missing (%)5.9%
Infinite0
Infinite (%)0.0%
Mean100.61261
Minimum40
Maximum500
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T16:36:20.980729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum40
5-th percentile41
Q141
median41
Q3200
95-th percentile200
Maximum500
Range460
Interquartile range (IQR)159

Descriptive statistics

Standard deviation97.415061
Coefficient of variation (CV)0.96821917
Kurtosis4.5878033
Mean100.61261
Median Absolute Deviation (MAD)0
Skewness1.9997154
Sum11168
Variance9489.694
MonotonicityNot monotonic
2023-12-12T16:36:21.088412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
41 68
57.6%
200 26
 
22.0%
100 10
 
8.5%
400 2
 
1.7%
40 2
 
1.7%
500 2
 
1.7%
300 1
 
0.8%
(Missing) 7
 
5.9%
ValueCountFrequency (%)
40 2
 
1.7%
41 68
57.6%
100 10
 
8.5%
200 26
 
22.0%
300 1
 
0.8%
400 2
 
1.7%
500 2
 
1.7%
ValueCountFrequency (%)
500 2
 
1.7%
400 2
 
1.7%
300 1
 
0.8%
200 26
 
22.0%
100 10
 
8.5%
41 68
57.6%
40 2
 
1.7%

촬영방면정보
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)8.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
주차출입
54 
주차장내부
46 
<NA>
10 
견인보관소내
 
2
화장로
 
1
Other values (5)
 
5

Length

Max length25
Median length4
Mean length4.7118644
Min length3

Unique

Unique6 ?
Unique (%)5.1%

Sample

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

Common Values

ValueCountFrequency (%)
주차출입 54
45.8%
주차장내부 46
39.0%
<NA> 10
 
8.5%
견인보관소내 2
 
1.7%
화장로 1
 
0.8%
승화원,추모의집 1
 
0.8%
주차장 1
 
0.8%
체육센터 내외부 1
 
0.8%
서수원칠보제육관내,외 1
 
0.8%
장안구민회관 내 외부주차장 및 전기,기계실 등 1
 
0.8%

Length

2023-12-12T16:36:21.198717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:36:21.304699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주차출입 54
43.5%
주차장내부 46
37.1%
na 10
 
8.1%
견인보관소내 2
 
1.6%
화장로 1
 
0.8%
승화원,추모의집 1
 
0.8%
주차장 1
 
0.8%
체육센터 1
 
0.8%
내외부 1
 
0.8%
서수원칠보제육관내,외 1
 
0.8%
Other values (6) 6
 
4.8%

보관일수
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
30
56 
20
56 
<NA>
6 

Length

Max length4
Median length2
Mean length2.1016949
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
30 56
47.5%
20 56
47.5%
<NA> 6
 
5.1%

Length

2023-12-12T16:36:21.541649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:36:21.738492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
30 56
47.5%
20 56
47.5%
na 6
 
5.1%

설치연월
Date

MISSING 

Distinct44
Distinct (%)40.4%
Missing9
Missing (%)7.6%
Memory size1.1 KiB
Minimum2005-02-01 00:00:00
Maximum2020-12-01 00:00:00
2023-12-12T16:36:22.226544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:22.437257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)

관리기관전화번호
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)9.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
031-238-0560
56 
031-240-2840
46 
031-888-7935
 
4
031-218-6518
 
3
031-8053-8517
 
2
Other values (6)
7 

Length

Max length13
Median length12
Mean length12.016949
Min length12

Unique

Unique5 ?
Unique (%)4.2%

Sample

1st row031-240-2840
2nd row031-240-2840
3rd row031-240-2840
4th row031-240-2840
5th row031-240-2840

Common Values

ValueCountFrequency (%)
031-238-0560 56
47.5%
031-240-2840 46
39.0%
031-888-7935 4
 
3.4%
031-218-6518 3
 
2.5%
031-8053-8517 2
 
1.7%
031-240-2734 2
 
1.7%
031-207-7697 1
 
0.8%
031-211-6490 1
 
0.8%
031-259-4612 1
 
0.8%
031-259-5413 1
 
0.8%

Length

2023-12-12T16:36:22.611407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
031-238-0560 56
47.5%
031-240-2840 46
39.0%
031-888-7935 4
 
3.4%
031-218-6518 3
 
2.5%
031-8053-8517 2
 
1.7%
031-240-2734 2
 
1.7%
031-207-7697 1
 
0.8%
031-211-6490 1
 
0.8%
031-259-4612 1
 
0.8%
031-259-5413 1
 
0.8%

위도
Real number (ℝ)

MISSING 

Distinct73
Distinct (%)64.6%
Missing5
Missing (%)4.2%
Infinite0
Infinite (%)0.0%
Mean37.241604
Minimum35.798787
Maximum37.305004
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T16:36:22.765429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.798787
5-th percentile37.233744
Q137.253314
median37.274386
Q337.289886
95-th percentile37.302416
Maximum37.305004
Range1.5062166
Interquartile range (IQR)0.036572

Descriptive statistics

Standard deviation0.20206513
Coefficient of variation (CV)0.0054257903
Kurtosis46.05768
Mean37.241604
Median Absolute Deviation (MAD)0.018439
Skewness-6.7008177
Sum4208.3013
Variance0.040830318
MonotonicityNot monotonic
2023-12-12T16:36:22.951205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.289239 4
 
3.4%
37.289297 3
 
2.5%
37.237136 3
 
2.5%
37.3035517 2
 
1.7%
37.3011121 2
 
1.7%
37.2740021 2
 
1.7%
37.2873695 2
 
1.7%
37.2849518 2
 
1.7%
37.3008682 2
 
1.7%
37.2848993 2
 
1.7%
Other values (63) 89
75.4%
(Missing) 5
 
4.2%
ValueCountFrequency (%)
35.7987874 2
1.7%
36.8945269 2
1.7%
37.2336302 2
1.7%
37.2338191 2
1.7%
37.236039 1
 
0.8%
37.237136 3
2.5%
37.2395445 1
 
0.8%
37.2399814 2
1.7%
37.2407831 2
1.7%
37.242429 1
 
0.8%
ValueCountFrequency (%)
37.305004 1
0.8%
37.3046152 2
1.7%
37.304028 1
0.8%
37.3035517 2
1.7%
37.301659 1
0.8%
37.3015785 2
1.7%
37.301448 2
1.7%
37.3011121 2
1.7%
37.3008682 2
1.7%
37.298551 2
1.7%

경도
Real number (ℝ)

MISSING 

Distinct74
Distinct (%)64.9%
Missing4
Missing (%)3.4%
Infinite0
Infinite (%)0.0%
Mean127.01379
Minimum126.63779
Maximum127.08628
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T16:36:23.114861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.63779
5-th percentile126.96203
Q1127.00634
median127.01914
Q3127.03267
95-th percentile127.08452
Maximum127.08628
Range0.448492
Interquartile range (IQR)0.026331275

Descriptive statistics

Standard deviation0.060413956
Coefficient of variation (CV)0.00047564877
Kurtosis25.378362
Mean127.01379
Median Absolute Deviation (MAD)0.013531
Skewness-4.3386648
Sum14479.573
Variance0.003649846
MonotonicityNot monotonic
2023-12-12T16:36:23.309215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.086281 4
 
3.4%
127.084524 3
 
2.5%
127.018602 3
 
2.5%
127.016632 2
 
1.7%
126.637789 2
 
1.7%
127.047315 2
 
1.7%
127.037891 2
 
1.7%
127.0562904 2
 
1.7%
127.0306794 2
 
1.7%
126.989091 2
 
1.7%
Other values (64) 90
76.3%
(Missing) 4
 
3.4%
ValueCountFrequency (%)
126.637789 2
1.7%
126.900468 2
1.7%
126.954043 2
1.7%
126.966327 2
1.7%
126.971055 2
1.7%
126.9716322 2
1.7%
126.974008 2
1.7%
126.987154 1
0.8%
126.989091 2
1.7%
126.990344 1
0.8%
ValueCountFrequency (%)
127.086281 4
3.4%
127.084524 3
2.5%
127.077129 1
 
0.8%
127.073947 1
 
0.8%
127.069142 1
 
0.8%
127.066272 1
 
0.8%
127.0583634 1
 
0.8%
127.0571367 1
 
0.8%
127.0562904 2
1.7%
127.055058 1
 
0.8%

데이터기준일자
Date

Distinct3
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2020-12-01 00:00:00
Maximum2020-12-11 00:00:00
2023-12-12T16:36:23.442397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:23.569857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=3)

Interactions

2023-12-12T16:36:17.466850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:16.192406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:16.624846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:17.028240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:17.570959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:16.281471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:16.720176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:17.126510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:17.658486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:16.387995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:16.811413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:17.238679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:17.772271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:16.515494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:16.929197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:17.366124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T16:36:23.669247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리기관명소재지도로명주소설치목적구분카메라대수카메라화소수촬영방면정보보관일수설치연월관리기관전화번호위도경도데이터기준일자
관리기관명1.0001.0000.7190.5960.7531.0001.0000.9441.0000.0000.0000.171
소재지도로명주소1.0001.0000.0000.9140.0000.0001.0000.8991.000NaN1.0000.000
설치목적구분0.7190.0001.0000.4060.6151.0001.0000.9610.8890.0000.3080.423
카메라대수0.5960.9140.4061.0000.7790.7850.4590.9890.7630.0000.0000.134
카메라화소수0.7530.0000.6150.7791.0000.8610.5040.9850.8190.0000.1340.727
촬영방면정보1.0000.0001.0000.7850.8611.0001.0000.9011.0000.0000.0001.000
보관일수1.0001.0001.0000.4590.5041.0001.0000.9991.0000.0940.2470.135
설치연월0.9440.8990.9610.9890.9850.9010.9991.0000.9650.0000.0001.000
관리기관전화번호1.0001.0000.8890.7630.8191.0001.0000.9651.0000.0000.1920.839
위도0.000NaN0.0000.0000.0000.0000.0940.0000.0001.0001.0000.000
경도0.0001.0000.3080.0000.1340.0000.2470.0000.1921.0001.0000.264
데이터기준일자0.1710.0000.4230.1340.7271.0000.1351.0000.8390.0000.2641.000
2023-12-12T16:36:23.828744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
촬영방면정보보관일수설치목적구분관리기관명관리기관전화번호
촬영방면정보1.0000.9660.9800.9800.985
보관일수0.9661.0000.9860.9860.977
설치목적구분0.9800.9861.0000.5830.728
관리기관명0.9800.9860.5831.0000.977
관리기관전화번호0.9850.9770.7280.9771.000
2023-12-12T16:36:23.944228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
카메라대수카메라화소수위도경도관리기관명설치목적구분촬영방면정보보관일수관리기관전화번호
카메라대수1.0000.3880.1090.2450.4240.3400.6240.3060.564
카메라화소수0.3881.0000.0650.0400.6250.4720.7070.3570.659
위도0.1090.0651.0000.0120.0000.0000.0000.1550.000
경도0.2450.0400.0121.0000.0000.1180.0000.2970.099
관리기관명0.4240.6250.0000.0001.0000.5830.9800.9860.977
설치목적구분0.3400.4720.0000.1180.5831.0000.9800.9860.728
촬영방면정보0.6240.7070.0000.0000.9800.9801.0000.9660.985
보관일수0.3060.3570.1550.2970.9860.9860.9661.0000.977
관리기관전화번호0.5640.6590.0000.0990.9770.7280.9850.9771.000

Missing values

2023-12-12T16:36:17.899102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:36:18.150972image/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.
2023-12-12T16:36:18.316336image/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
0수원도시공사경기도 수원시 장안구 광교산로 160 (하광교동)경기도 수원시 장안구 하광교동 403-1차량방범1641주차장내부302007-07031-240-284037.301659127.0307982020-12-11
1수원도시공사경기도 수원시 영통구 봉영로 1598 (영통동)경기도 수원시 영통구 영통동 995-3차량방범3141주차장내부302006-01031-240-284037.253314127.0739472020-12-11
2수원도시공사경기도 수원시 권선구 정조로 291 (대황교동)경기도 수원시 권선구 대황교동 259-5차량방범841주차장내부302006-01031-240-284037.236039127.0183442020-12-11
3수원도시공사경기도 수원시 권선구 정조로 379 (세류동)경기도 수원시 권선구 장지동 44-10차량방범341주차장내부302006-01031-240-284037.242429127.0148242020-12-11
4수원도시공사경기도 수원시 권선구 경수대로 270 (권선동)경기도 수원시 권선구 권선동 1189차량방범441주차장내부302007-01031-240-284037.249203127.0214382020-12-11
5수원도시공사경기도 수원시 팔달구 장다리로306번길 24 (인계동)경기도 수원시 팔달구 인계동 944-1차량방범841주차장내부302006-01031-240-284037.274386127.0305862020-12-11
6수원도시공사경기도 수원시 팔달구 세지로 233 (인계동)경기도 수원시 팔달구 인계동 821-4차량방범541주차장내부302007-09031-240-284037.271786127.0238422020-12-11
7수원도시공사경기도 수원시 팔달구 향교로 140 (교동)경기도 수원시 팔달구 교동 98차량방범2441주차장내부302006-01031-240-284037.273211127.0153512020-12-11
8수원도시공사경기도 수원시 장안구 서부로 2106번길 27(율전동)경기도 수원시 장안구 율전동 433-2차량방범641주차장내부302005-04031-240-284037.297909126.9710552020-12-11
9수원도시공사경기도 수원시 장안구 서부로 2106번길 27(율전동)경기도 수원시 장안구 율전동 433-2차량방범941주차장내부302018-05031-240-284037.297909126.9710552020-12-11
관리기관명소재지도로명주소소재지지번주소설치목적구분카메라대수카메라화소수촬영방면정보보관일수설치연월관리기관전화번호위도경도데이터기준일자
108수원도시공사경기도 수원시 영통구 광교호수로 278 수원시연화장수원시 영통구 하동 25번지차량방범14200주차장30<NA>031-218-651837.289297127.0845242020-12-10
109광교웰빙국민체육센터수원시 영통구 광교웰빙타운로 71수원시 영통구 이의동 1183다목적44200체육센터 내외부302020-01031-259-461237.305004127.0432212020-12-11
110서수원칠보체육관(수원도시공사)경기도 수원시 권선구 서수원로 577번길 171(금곡동)경기도 수원시 권선구 금곡동 1071(서수원칠보체육관)다목적59300서수원칠보제육관내,외302019-07031-259-541337.280358127.0306752020-12-11
111수원도시공사경기도 수원시 장안구 경수대로 893 종합운동장내 수원체육관조원동 775차량방범56<NA><NA><NA><NA>031-240-273437.298551127.0090152020-12-10
112수원도시공사경기도 수원시 장안구 경수대로 893 종합운동장내 수원체육관조원동 775시설물관리76<NA><NA><NA><NA>031-240-273437.298551127.0090152020-12-10
113장안구민회관수원시 장안구 송원로 101수원시 장안구 조원동888다목적50400장안구민회관 내 외부주차장 및 전기,기계실 등302016-01031-240-305037.304028127.0103112020-12-11
114수원도시공사경기도 수원시 영통구 광교호수로 278-1(하동) 수원시자원순환센터<NA>차량방범140<NA>302009-01031-888-793537.289239127.0862812020-12-01
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