Overview

Dataset statistics

Number of variables11
Number of observations5937
Missing cells1316
Missing cells (%)2.0%
Duplicate rows163
Duplicate rows (%)2.7%
Total size in memory533.5 KiB
Average record size in memory92.0 B

Variable types

Categorical4
Text2
Numeric4
DateTime1

Dataset

Description광주광역시 CCTV통합관제센터에서 관제 및 운영중인 CCTV 현황에 대한 정보로 관리기관명, 소재지 지번/도로명주소, 카메라대수, 카메라화소, 촬영방면정보 등을 제공하는 데이터입니다.
Author광주광역시
URLhttps://www.data.go.kr/data/15084631/fileData.do

Alerts

관리기관명 has constant value ""Constant
카메라화소 has constant value ""Constant
촬영방면 has constant value ""Constant
보관일수 has constant value ""Constant
데이터기준일자 has constant value ""Constant
Dataset has 163 (2.7%) duplicate rowsDuplicates
소재지도로명주소 has 1278 (21.5%) missing valuesMissing

Reproduction

Analysis started2024-03-14 10:23:31.125339
Analysis finished2024-03-14 10:23:36.674021
Duration5.55 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size46.5 KiB
광주광역시 사회재난과
5937 

Length

Max length11
Median length11
Mean length11
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row광주광역시 사회재난과
2nd row광주광역시 사회재난과
3rd row광주광역시 사회재난과
4th row광주광역시 사회재난과
5th row광주광역시 사회재난과

Common Values

ValueCountFrequency (%)
광주광역시 사회재난과 5937
100.0%

Length

2024-03-14T19:23:36.785001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T19:23:37.038069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
광주광역시 5937
50.0%
사회재난과 5937
50.0%

소재지지번주소
Text

Distinct3393
Distinct (%)57.2%
Missing0
Missing (%)0.0%
Memory size46.5 KiB
2024-03-14T19:23:38.377054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length20
Mean length12.122452
Min length7

Characters and Unicode

Total characters71971
Distinct characters148
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1554 ?
Unique (%)26.2%

Sample

1st row광산구 광산동 666-7
2nd row광산구 도덕동 320-15
3rd row광산구 도덕동 320-15
4th row광산구 도산동 1128-4
5th row광산구 도산동 1282-1
ValueCountFrequency (%)
북구 1591
 
8.9%
광산구 1535
 
8.6%
서구 1189
 
6.7%
남구 919
 
5.1%
동구 703
 
3.9%
쌍촌동 229
 
1.3%
화정동 205
 
1.1%
두암동 188
 
1.1%
우산동 154
 
0.9%
봉선동 151
 
0.8%
Other values (3238) 10986
61.5%
2024-03-14T19:23:40.247921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12015
16.7%
동 6739
 
9.4%
구 5949
 
8.3%
1 4868
 
6.8%
- 4425
 
6.1%
2 2849
 
4.0%
산 2437
 
3.4%
5 2329
 
3.2%
3 2318
 
3.2%
4 2135
 
3.0%
Other values (138) 25907
36.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 31144
43.3%
Decimal Number 24354
33.8%
Space Separator 12015
 
16.7%
Dash Punctuation 4425
 
6.1%
Close Punctuation 14
 
< 0.1%
Open Punctuation 14
 
< 0.1%
Other Punctuation 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 6739
21.6%
구 5949
19.1%
산 2437
 
7.8%
북 1608
 
5.2%
광 1594
 
5.1%
서 1238
 
4.0%
남 1123
 
3.6%
월 695
 
2.2%
암 570
 
1.8%
촌 407
 
1.3%
Other values (122) 8784
28.2%
Decimal Number
ValueCountFrequency (%)
1 4868
20.0%
2 2849
11.7%
5 2329
9.6%
3 2318
9.5%
4 2135
8.8%
6 2091
8.6%
8 2064
8.5%
9 1954
8.0%
7 1922
 
7.9%
0 1824
 
7.5%
Other Punctuation
ValueCountFrequency (%)
# 3
60.0%
, 2
40.0%
Space Separator
ValueCountFrequency (%)
12015
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4425
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 40827
56.7%
Hangul 31144
43.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 6739
21.6%
구 5949
19.1%
산 2437
 
7.8%
북 1608
 
5.2%
광 1594
 
5.1%
서 1238
 
4.0%
남 1123
 
3.6%
월 695
 
2.2%
암 570
 
1.8%
촌 407
 
1.3%
Other values (122) 8784
28.2%
Common
ValueCountFrequency (%)
12015
29.4%
1 4868
11.9%
- 4425
 
10.8%
2 2849
 
7.0%
5 2329
 
5.7%
3 2318
 
5.7%
4 2135
 
5.2%
6 2091
 
5.1%
8 2064
 
5.1%
9 1954
 
4.8%
Other values (6) 3779
 
9.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 40827
56.7%
Hangul 31144
43.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12015
29.4%
1 4868
11.9%
- 4425
 
10.8%
2 2849
 
7.0%
5 2329
 
5.7%
3 2318
 
5.7%
4 2135
 
5.2%
6 2091
 
5.1%
8 2064
 
5.1%
9 1954
 
4.8%
Other values (6) 3779
 
9.3%
Hangul
ValueCountFrequency (%)
동 6739
21.6%
구 5949
19.1%
산 2437
 
7.8%
북 1608
 
5.2%
광 1594
 
5.1%
서 1238
 
4.0%
남 1123
 
3.6%
월 695
 
2.2%
암 570
 
1.8%
촌 407
 
1.3%
Other values (122) 8784
28.2%

소재지도로명주소
Text

MISSING 

Distinct2571
Distinct (%)55.2%
Missing1278
Missing (%)21.5%
Memory size46.5 KiB
2024-03-14T19:23:41.635841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length17
Mean length12.739
Min length8

Characters and Unicode

Total characters59351
Distinct characters227
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

Unique1131 ?
Unique (%)24.3%

Sample

1st row광산구 고봉로 905
2nd row광산구 삼도로 342
3rd row광산구 삼도로 342
4th row광산구 도산로9번길 58
5th row광산구 남동길48번길 25
ValueCountFrequency (%)
북구 1361
 
9.7%
광산구 1087
 
7.8%
서구 938
 
6.7%
남구 721
 
5.2%
동구 552
 
3.9%
10 113
 
0.8%
16 101
 
0.7%
7 98
 
0.7%
11 83
 
0.6%
9 79
 
0.6%
Other values (2191) 8857
63.3%
2024-03-14T19:23:43.473420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9353
 
15.8%
구 4704
 
7.9%
로 4241
 
7.1%
1 3756
 
6.3%
길 2895
 
4.9%
2 2506
 
4.2%
번 2494
 
4.2%
3 1860
 
3.1%
4 1526
 
2.6%
5 1512
 
2.5%
Other values (217) 24504
41.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 31917
53.8%
Decimal Number 17088
28.8%
Space Separator 9353
 
15.8%
Dash Punctuation 979
 
1.6%
Close Punctuation 7
 
< 0.1%
Open Punctuation 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 4704
14.7%
로 4241
13.3%
길 2895
 
9.1%
번 2494
 
7.8%
산 1473
 
4.6%
북 1426
 
4.5%
서 1298
 
4.1%
광 1149
 
3.6%
남 943
 
3.0%
동 791
 
2.5%
Other values (203) 10503
32.9%
Decimal Number
ValueCountFrequency (%)
1 3756
22.0%
2 2506
14.7%
3 1860
10.9%
4 1526
8.9%
5 1512
8.8%
6 1377
 
8.1%
7 1259
 
7.4%
0 1116
 
6.5%
8 1106
 
6.5%
9 1070
 
6.3%
Space Separator
ValueCountFrequency (%)
9353
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 979
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 31917
53.8%
Common 27434
46.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 4704
14.7%
로 4241
13.3%
길 2895
 
9.1%
번 2494
 
7.8%
산 1473
 
4.6%
북 1426
 
4.5%
서 1298
 
4.1%
광 1149
 
3.6%
남 943
 
3.0%
동 791
 
2.5%
Other values (203) 10503
32.9%
Common
ValueCountFrequency (%)
9353
34.1%
1 3756
13.7%
2 2506
 
9.1%
3 1860
 
6.8%
4 1526
 
5.6%
5 1512
 
5.5%
6 1377
 
5.0%
7 1259
 
4.6%
0 1116
 
4.1%
8 1106
 
4.0%
Other values (4) 2063
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 31917
53.8%
ASCII 27434
46.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9353
34.1%
1 3756
13.7%
2 2506
 
9.1%
3 1860
 
6.8%
4 1526
 
5.6%
5 1512
 
5.5%
6 1377
 
5.0%
7 1259
 
4.6%
0 1116
 
4.1%
8 1106
 
4.0%
Other values (4) 2063
 
7.5%
Hangul
ValueCountFrequency (%)
구 4704
14.7%
로 4241
13.3%
길 2895
 
9.1%
번 2494
 
7.8%
산 1473
 
4.6%
북 1426
 
4.5%
서 1298
 
4.1%
광 1149
 
3.6%
남 943
 
3.0%
동 791
 
2.5%
Other values (203) 10503
32.9%

카메라대수
Real number (ℝ)

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.7739599
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size52.3 KiB
2024-03-14T19:23:43.839353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

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

Descriptive statistics

Standard deviation0.9668228
Coefficient of variation (CV)0.54500826
Kurtosis0.065692343
Mean1.7739599
Median Absolute Deviation (MAD)0
Skewness1.043721
Sum10532
Variance0.93474633
MonotonicityNot monotonic
2024-03-14T19:23:44.199102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 3097
52.2%
2 1569
26.4%
3 801
 
13.5%
4 458
 
7.7%
5 10
 
0.2%
6 2
 
< 0.1%
ValueCountFrequency (%)
1 3097
52.2%
2 1569
26.4%
3 801
 
13.5%
4 458
 
7.7%
5 10
 
0.2%
6 2
 
< 0.1%
ValueCountFrequency (%)
6 2
 
< 0.1%
5 10
 
0.2%
4 458
 
7.7%
3 801
 
13.5%
2 1569
26.4%
1 3097
52.2%

카메라화소
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size46.5 KiB
200만
5937 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row200만
2nd row200만
3rd row200만
4th row200만
5th row200만

Common Values

ValueCountFrequency (%)
200만 5937
100.0%

Length

2024-03-14T19:23:44.580664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T19:23:44.878628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
200만 5937
100.0%

촬영방면
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size46.5 KiB
360도
5937 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row360도
2nd row360도
3rd row360도
4th row360도
5th row360도

Common Values

ValueCountFrequency (%)
360도 5937
100.0%

Length

2024-03-14T19:23:45.195106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T19:23:45.490312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
360도 5937
100.0%

보관일수
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size46.5 KiB
30일
5937 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row30일
2nd row30일
3rd row30일
4th row30일
5th row30일

Common Values

ValueCountFrequency (%)
30일 5937
100.0%

Length

2024-03-14T19:23:45.806484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T19:23:46.104713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
30일 5937
100.0%

설치연도
Real number (ℝ)

Distinct15
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2018.938
Minimum2008
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size52.3 KiB
2024-03-14T19:23:46.374698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2008
5-th percentile2013
Q12017
median2020
Q32022
95-th percentile2023
Maximum2023
Range15
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.4560971
Coefficient of variation (CV)0.0017118392
Kurtosis-0.05374396
Mean2018.938
Median Absolute Deviation (MAD)2
Skewness-0.90998823
Sum11986435
Variance11.944607
MonotonicityNot monotonic
2024-03-14T19:23:46.750922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
2022 1141
19.2%
2021 945
15.9%
2019 659
11.1%
2013 621
10.5%
2023 570
9.6%
2020 534
9.0%
2018 444
 
7.5%
2016 443
 
7.5%
2017 170
 
2.9%
2015 131
 
2.2%
Other values (5) 279
 
4.7%
ValueCountFrequency (%)
2008 17
 
0.3%
2009 35
 
0.6%
2010 112
 
1.9%
2011 4
 
0.1%
2013 621
10.5%
2014 111
 
1.9%
2015 131
 
2.2%
2016 443
7.5%
2017 170
 
2.9%
2018 444
7.5%
ValueCountFrequency (%)
2023 570
9.6%
2022 1141
19.2%
2021 945
15.9%
2020 534
9.0%
2019 659
11.1%
2018 444
 
7.5%
2017 170
 
2.9%
2016 443
 
7.5%
2015 131
 
2.2%
2014 111
 
1.9%

위도
Real number (ℝ)

Distinct3778
Distinct (%)63.8%
Missing19
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean35.160571
Minimum35.05282
Maximum35.252811
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size52.3 KiB
2024-03-14T19:23:47.176461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.05282
5-th percentile35.114391
Q135.140119
median35.158592
Q335.180245
95-th percentile35.212719
Maximum35.252811
Range0.1999915
Interquartile range (IQR)0.040125477

Descriptive statistics

Standard deviation0.030318777
Coefficient of variation (CV)0.0008622948
Kurtosis0.070910935
Mean35.160571
Median Absolute Deviation (MAD)0.020039
Skewness0.011615511
Sum208080.26
Variance0.00091922827
MonotonicityNot monotonic
2024-03-14T19:23:47.645117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.17231937 4
 
0.1%
35.15099158 4
 
0.1%
35.20793656 4
 
0.1%
35.1564766 4
 
0.1%
35.1707812 4
 
0.1%
35.14568375 4
 
0.1%
35.13563423 4
 
0.1%
35.14759252 4
 
0.1%
35.147321 4
 
0.1%
35.170827 4
 
0.1%
Other values (3768) 5878
99.0%
(Missing) 19
 
0.3%
ValueCountFrequency (%)
35.05282 1
< 0.1%
35.053175 1
< 0.1%
35.054221 1
< 0.1%
35.054344 1
< 0.1%
35.054725 1
< 0.1%
35.055218 1
< 0.1%
35.056163 1
< 0.1%
35.056422 2
< 0.1%
35.057588 1
< 0.1%
35.061569 1
< 0.1%
ValueCountFrequency (%)
35.2528115 1
< 0.1%
35.251293 1
< 0.1%
35.25074332 2
< 0.1%
35.2464067 1
< 0.1%
35.24593972 2
< 0.1%
35.24487899 1
< 0.1%
35.24486505 2
< 0.1%
35.2443586 2
< 0.1%
35.24430096 2
< 0.1%
35.243 1
< 0.1%

경도
Real number (ℝ)

Distinct3770
Distinct (%)63.7%
Missing19
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean126.87348
Minimum126.65932
Maximum127.00941
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size52.3 KiB
2024-03-14T19:23:48.075423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.65932
5-th percentile126.79262
Q1126.84018
median126.88387
Q3126.91181
95-th percentile126.93506
Maximum127.00941
Range0.3500852
Interquartile range (IQR)0.071637575

Descriptive statistics

Standard deviation0.048812327
Coefficient of variation (CV)0.00038473229
Kurtosis0.55387433
Mean126.87348
Median Absolute Deviation (MAD)0.03176765
Skewness-0.78431746
Sum750837.28
Variance0.0023826432
MonotonicityNot monotonic
2024-03-14T19:23:48.529084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.899636 5
 
0.1%
126.904333 4
 
0.1%
126.8949179 4
 
0.1%
126.8908015 4
 
0.1%
126.9171812 4
 
0.1%
126.91485 4
 
0.1%
126.8719215 4
 
0.1%
126.901557 4
 
0.1%
126.8777549 4
 
0.1%
126.8881502 4
 
0.1%
Other values (3760) 5877
99.0%
(Missing) 19
 
0.3%
ValueCountFrequency (%)
126.6593226 1
< 0.1%
126.663872 1
< 0.1%
126.6667742 2
< 0.1%
126.66801 1
< 0.1%
126.672621 1
< 0.1%
126.6730681 1
< 0.1%
126.674396 2
< 0.1%
126.6747901 1
< 0.1%
126.6750844 1
< 0.1%
126.6754334 1
< 0.1%
ValueCountFrequency (%)
127.0094078 2
< 0.1%
127.0028075 1
 
< 0.1%
127.0026844 1
 
< 0.1%
127.002538 1
 
< 0.1%
127.0016209 2
< 0.1%
127.001046 2
< 0.1%
126.999021 3
0.1%
126.9873862 2
< 0.1%
126.9863875 1
 
< 0.1%
126.9815374 1
 
< 0.1%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size46.5 KiB
Minimum2023-12-31 00:00:00
Maximum2023-12-31 00:00:00
2024-03-14T19:23:48.886488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:23:49.188436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-03-14T19:23:34.996654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:23:31.897880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:23:32.955795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:23:33.848239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:23:35.267800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:23:32.153024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:23:33.124303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:23:34.121338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:23:35.554671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:23:32.583072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:23:33.303826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:23:34.408933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:23:35.847949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:23:32.781897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:23:33.565342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:23:34.704101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T19:23:49.397270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
카메라대수설치연도위도경도
카메라대수1.0000.3410.0410.045
설치연도0.3411.0000.0890.105
위도0.0410.0891.0000.460
경도0.0450.1050.4601.000
2024-03-14T19:23:49.838409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
카메라대수설치연도위도경도
카메라대수1.0000.0780.023-0.036
설치연도0.0781.0000.0070.028
위도0.0230.0071.000-0.143
경도-0.0360.028-0.1431.000

Missing values

2024-03-14T19:23:36.091163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T19:23:36.370943image/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.
2024-03-14T19:23:36.572435image/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

관리기관명소재지지번주소소재지도로명주소카메라대수카메라화소촬영방면보관일수설치연도위도경도데이터기준일자
0광주광역시 사회재난과광산구 광산동 666-7광산구 고봉로 9052200만360도30일201835.225272126.7358542023-12-31
1광주광역시 사회재난과광산구 도덕동 320-15광산구 삼도로 3421200만360도30일201335.162851126.6999112023-12-31
2광주광역시 사회재난과광산구 도덕동 320-15광산구 삼도로 3421200만360도30일202235.162851126.6999112023-12-31
3광주광역시 사회재난과광산구 도산동 1128-4광산구 도산로9번길 584200만360도30일202035.127057126.7893532023-12-31
4광주광역시 사회재난과광산구 도산동 1282-1광산구 남동길48번길 251200만360도30일201335.130739126.7898652023-12-31
5광주광역시 사회재난과광산구 도산동 1282-1광산구 남동길48번길 252200만360도30일201935.130739126.7898652023-12-31
6광주광역시 사회재난과광산구 도산동 1282-1광산구 남동길48번길 251200만360도30일202235.130739126.7898652023-12-31
7광주광역시 사회재난과광산구 도산동 1283-6광산구 남동길 42-133200만360도30일202135.130713126.7892382023-12-31
8광주광역시 사회재난과광산구 도산동 1294-6광산구 도산로 91200만360도30일200935.129063126.791522023-12-31
9광주광역시 사회재난과광산구 도산동 1294-6광산구 도산로 91200만360도30일201835.129063126.791522023-12-31
관리기관명소재지지번주소소재지도로명주소카메라대수카메라화소촬영방면보관일수설치연도위도경도데이터기준일자
5927광주광역시 사회재난과광산구 우산동 1609-7광산구 무진대로212번길 163200만360도30일202335.16104126.8035682023-12-31
5928광주광역시 사회재난과광산구 수완동 926광산구 왕버들로132번길 352200만360도30일202335.20017126.8243112023-12-31
5929광주광역시 사회재난과광산구 신촌동 703-2<NA>2200만360도30일202335.142395126.8035752023-12-31
5930광주광역시 사회재난과광산구 월곡동 564-2광산구 월곡반월로76번길 5-123200만360도30일202335.171237126.8136482023-12-31
5931광주광역시 사회재난과광산구 도산동 925-11광산구 송도로 2153200만360도30일202335.133263126.7959942023-12-31
5932광주광역시 사회재난과광산구 송정동 466-9<NA>4200만360도30일202335.138717126.8023242023-12-31
5933광주광역시 사회재난과광산구 도산동 979-4<NA>3200만360도30일202335.132666126.7843272023-12-31
5934광주광역시 사회재난과광산구 수완동 267-21<NA>2200만360도30일202335.208397126.8304962023-12-31
5935광주광역시 사회재난과광산구 우산동 846광산구 우산로125번길 263200만360도30일202335.156813126.8150622023-12-31
5936광주광역시 사회재난과광산구 흑석동 691<NA>3200만360도30일202335.185516126.8044192023-12-31

Duplicate rows

Most frequently occurring

관리기관명소재지지번주소소재지도로명주소카메라대수카메라화소촬영방면보관일수설치연도위도경도데이터기준일자# duplicates
124광주광역시 사회재난과북구 중흥동 526-2<NA>2200만360도30일2022<NA><NA>2023-12-314
114광주광역시 사회재난과북구 우산동 264-28<NA>2200만360도30일2022<NA><NA>2023-12-313
115광주광역시 사회재난과북구 운암동 424-1북구 금호로 6-11200만360도30일202235.169953126.8901912023-12-313
0광주광역시 사회재난과광산구 도산동 1287-5광산구 남동길 401200만360도30일201535.130477126.7885522023-12-312
1광주광역시 사회재난과광산구 비아동 86-1광산구 비아중앙로 361200만360도30일202135.220299126.8252023-12-312
2광주광역시 사회재난과광산구 산월동 884-1광산구 첨단중앙로68번길 1001200만360도30일202135.211347126.8473672023-12-312
3광주광역시 사회재난과광산구 산정동 949-6광산구 산정로54번길 231200만360도30일202035.17129126.8057672023-12-312
4광주광역시 사회재난과광산구 선암동 694광산구 선운로2번길 352200만360도30일202235.146369126.7731582023-12-312
5광주광역시 사회재난과광산구 소촌동 358-1광산구 소촌로46번길 151200만360도30일201935.149268126.7949962023-12-312
6광주광역시 사회재난과광산구 소촌동 7-1광산구 사암로95번길 131200만360도30일201835.152865126.8064572023-12-312