Overview

Dataset statistics

Number of variables11
Number of observations1519
Missing cells0
Missing cells (%)0.0%
Duplicate rows4
Duplicate rows (%)0.3%
Total size in memory138.1 KiB
Average record size in memory93.1 B

Variable types

Categorical5
Text2
Numeric3
DateTime1

Dataset

Description세종시 설치된 cctv현황 및 위치 정보입니다- (제공정보) 관리기관명, 소재지지번주소, 설치목적구분, 카메라대수, 카메라화소수, 촬영방면정보, 보관일수,관리기관전화번호, 위도, 경도
Author세종특별자치시
URLhttps://www.data.go.kr/data/3037683/fileData.do

Alerts

관리기관명 has constant value ""Constant
보관일수 has constant value ""Constant
관리기관전화번호 has constant value ""Constant
데이터기준일자 has constant value ""Constant
Dataset has 4 (0.3%) duplicate rowsDuplicates
설치목적구분 is highly imbalanced (75.7%)Imbalance
카메라화소수 is highly imbalanced (83.1%)Imbalance

Reproduction

Analysis started2024-03-23 06:40:10.341437
Analysis finished2024-03-23 06:40:16.550621
Duration6.21 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size12.0 KiB
세종특별자치시청
1519 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
세종특별자치시청 1519
100.0%

Length

2024-03-23T06:40:16.862611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T06:40:17.520974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
세종특별자치시청 1519
100.0%

소재지지번주소
Text

Distinct1375
Distinct (%)90.5%
Missing0
Missing (%)0.0%
Memory size12.0 KiB
2024-03-23T06:40:18.379034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length24
Mean length18.451613
Min length13

Characters and Unicode

Total characters28028
Distinct characters153
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

Unique1291 ?
Unique (%)85.0%

Sample

1st row세종특별자치시 세종동 747-432
2nd row세종특별자치시 대평동 77-61
3rd row세종특별자치시 연기면 세종동 747-89
4th row세종특별자치시 세종동 747-373
5th row세종특별자치시 연기면 세종동 747-272
ValueCountFrequency (%)
세종특별자치시 1509
28.3%
조치원읍 205
 
3.9%
금남면 125
 
2.3%
연기면 106
 
2.0%
고운동 94
 
1.8%
어진동 81
 
1.5%
세종동 65
 
1.2%
부강면 62
 
1.2%
집현동 56
 
1.1%
장군면 53
 
1.0%
Other values (1414) 2967
55.7%
2024-03-23T06:40:19.997865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3846
 
13.7%
치 1718
 
6.1%
종 1644
 
5.9%
세 1625
 
5.8%
시 1519
 
5.4%
별 1512
 
5.4%
특 1511
 
5.4%
자 1511
 
5.4%
1 1101
 
3.9%
- 837
 
3.0%
Other values (143) 11204
40.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 17666
63.0%
Decimal Number 5669
 
20.2%
Space Separator 3846
 
13.7%
Dash Punctuation 837
 
3.0%
Open Punctuation 5
 
< 0.1%
Close Punctuation 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
치 1718
 
9.7%
종 1644
 
9.3%
세 1625
 
9.2%
시 1519
 
8.6%
별 1512
 
8.6%
특 1511
 
8.6%
자 1511
 
8.6%
동 829
 
4.7%
리 768
 
4.3%
면 543
 
3.1%
Other values (129) 4486
25.4%
Decimal Number
ValueCountFrequency (%)
1 1101
19.4%
2 667
11.8%
3 610
10.8%
6 529
9.3%
5 526
9.3%
4 493
8.7%
7 475
8.4%
8 454
8.0%
0 414
 
7.3%
9 400
 
7.1%
Space Separator
ValueCountFrequency (%)
3846
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 837
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 17666
63.0%
Common 10362
37.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
치 1718
 
9.7%
종 1644
 
9.3%
세 1625
 
9.2%
시 1519
 
8.6%
별 1512
 
8.6%
특 1511
 
8.6%
자 1511
 
8.6%
동 829
 
4.7%
리 768
 
4.3%
면 543
 
3.1%
Other values (129) 4486
25.4%
Common
ValueCountFrequency (%)
3846
37.1%
1 1101
 
10.6%
- 837
 
8.1%
2 667
 
6.4%
3 610
 
5.9%
6 529
 
5.1%
5 526
 
5.1%
4 493
 
4.8%
7 475
 
4.6%
8 454
 
4.4%
Other values (4) 824
 
8.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 17666
63.0%
ASCII 10362
37.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3846
37.1%
1 1101
 
10.6%
- 837
 
8.1%
2 667
 
6.4%
3 610
 
5.9%
6 529
 
5.1%
5 526
 
5.1%
4 493
 
4.8%
7 475
 
4.6%
8 454
 
4.4%
Other values (4) 824
 
8.0%
Hangul
ValueCountFrequency (%)
치 1718
 
9.7%
종 1644
 
9.3%
세 1625
 
9.2%
시 1519
 
8.6%
별 1512
 
8.6%
특 1511
 
8.6%
자 1511
 
8.6%
동 829
 
4.7%
리 768
 
4.3%
면 543
 
3.1%
Other values (129) 4486
25.4%

설치목적구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size12.0 KiB
생활방범
1458 
차량방범
 
61

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
생활방범 1458
96.0%
차량방범 61
 
4.0%

Length

2024-03-23T06:40:20.540483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T06:40:20.926724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
생활방범 1458
96.0%
차량방범 61
 
4.0%

카메라대수
Real number (ℝ)

Distinct6
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.3396972
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.5 KiB
2024-03-23T06:40:21.210042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q33
95-th percentile4
Maximum6
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.0726926
Coefficient of variation (CV)0.45847499
Kurtosis-0.65623516
Mean2.3396972
Median Absolute Deviation (MAD)1
Skewness0.27703432
Sum3554
Variance1.1506695
MonotonicityNot monotonic
2024-03-23T06:40:21.727531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
3 546
35.9%
1 438
28.8%
2 351
23.1%
4 145
 
9.5%
5 38
 
2.5%
6 1
 
0.1%
ValueCountFrequency (%)
1 438
28.8%
2 351
23.1%
3 546
35.9%
4 145
 
9.5%
5 38
 
2.5%
6 1
 
0.1%
ValueCountFrequency (%)
6 1
 
0.1%
5 38
 
2.5%
4 145
 
9.5%
3 546
35.9%
2 351
23.1%
1 438
28.8%

카메라화소수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size12.0 KiB
200
1481 
130
 
38

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
200 1481
97.5%
130 38
 
2.5%

Length

2024-03-23T06:40:22.299719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T06:40:22.736672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
200 1481
97.5%
130 38
 
2.5%

촬영방면정보
Text

Distinct1299
Distinct (%)85.5%
Missing0
Missing (%)0.0%
Memory size12.0 KiB
2024-03-23T06:40:23.737118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length27
Mean length10.658986
Min length3

Characters and Unicode

Total characters16191
Distinct characters535
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1213 ?
Unique (%)79.9%

Sample

1st row공원 산책로 일대
2nd row공원 산책로 일대
3rd row공원 산책로 일대
4th row공원 산책로 일대
5th row공원 산책로 일대
ValueCountFrequency (%)
양방향 329
 
9.1%
앞 124
 
3.4%
주변 89
 
2.5%
고운동 88
 
2.4%
삼거리 67
 
1.9%
방향 54
 
1.5%
회전교차로 46
 
1.3%
입구 46
 
1.3%
교차로 44
 
1.2%
옆 40
 
1.1%
Other values (1598) 2685
74.3%
2024-03-23T06:40:25.639942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2099
 
13.0%
방 452
 
2.8%
향 421
 
2.6%
로 421
 
2.6%
동 420
 
2.6%
리 386
 
2.4%
양 355
 
2.2%
원 330
 
2.0%
길 290
 
1.8%
교 282
 
1.7%
Other values (525) 10735
66.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12953
80.0%
Space Separator 2099
 
13.0%
Decimal Number 812
 
5.0%
Uppercase Letter 108
 
0.7%
Other Punctuation 97
 
0.6%
Open Punctuation 53
 
0.3%
Close Punctuation 51
 
0.3%
Modifier Symbol 10
 
0.1%
Dash Punctuation 6
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
방 452
 
3.5%
향 421
 
3.3%
로 421
 
3.3%
동 420
 
3.2%
리 386
 
3.0%
양 355
 
2.7%
원 330
 
2.5%
길 290
 
2.2%
교 282
 
2.2%
앞 280
 
2.2%
Other values (484) 9316
71.9%
Uppercase Letter
ValueCountFrequency (%)
S 12
11.1%
B 11
10.2%
A 10
9.3%
T 9
 
8.3%
L 8
 
7.4%
I 8
 
7.4%
R 7
 
6.5%
C 7
 
6.5%
K 6
 
5.6%
H 6
 
5.6%
Other values (11) 24
22.2%
Decimal Number
ValueCountFrequency (%)
1 246
30.3%
2 142
17.5%
0 104
12.8%
3 97
 
11.9%
4 58
 
7.1%
5 46
 
5.7%
6 36
 
4.4%
9 35
 
4.3%
8 30
 
3.7%
7 18
 
2.2%
Other Punctuation
ValueCountFrequency (%)
, 95
97.9%
? 1
 
1.0%
/ 1
 
1.0%
Space Separator
ValueCountFrequency (%)
2099
100.0%
Open Punctuation
ValueCountFrequency (%)
( 53
100.0%
Close Punctuation
ValueCountFrequency (%)
) 51
100.0%
Modifier Symbol
ValueCountFrequency (%)
˚ 10
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12953
80.0%
Common 3129
 
19.3%
Latin 109
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
방 452
 
3.5%
향 421
 
3.3%
로 421
 
3.3%
동 420
 
3.2%
리 386
 
3.0%
양 355
 
2.7%
원 330
 
2.5%
길 290
 
2.2%
교 282
 
2.2%
앞 280
 
2.2%
Other values (484) 9316
71.9%
Latin
ValueCountFrequency (%)
S 12
11.0%
B 11
10.1%
A 10
 
9.2%
T 9
 
8.3%
L 8
 
7.3%
I 8
 
7.3%
R 7
 
6.4%
C 7
 
6.4%
K 6
 
5.5%
H 6
 
5.5%
Other values (12) 25
22.9%
Common
ValueCountFrequency (%)
2099
67.1%
1 246
 
7.9%
2 142
 
4.5%
0 104
 
3.3%
3 97
 
3.1%
, 95
 
3.0%
4 58
 
1.9%
( 53
 
1.7%
) 51
 
1.6%
5 46
 
1.5%
Other values (9) 138
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12953
80.0%
ASCII 3228
 
19.9%
Modifier Letters 10
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2099
65.0%
1 246
 
7.6%
2 142
 
4.4%
0 104
 
3.2%
3 97
 
3.0%
, 95
 
2.9%
4 58
 
1.8%
( 53
 
1.6%
) 51
 
1.6%
5 46
 
1.4%
Other values (30) 237
 
7.3%
Hangul
ValueCountFrequency (%)
방 452
 
3.5%
향 421
 
3.3%
로 421
 
3.3%
동 420
 
3.2%
리 386
 
3.0%
양 355
 
2.7%
원 330
 
2.5%
길 290
 
2.2%
교 282
 
2.2%
앞 280
 
2.2%
Other values (484) 9316
71.9%
Modifier Letters
ValueCountFrequency (%)
˚ 10
100.0%

보관일수
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size12.0 KiB
30
1519 

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 1519
100.0%

Length

2024-03-23T06:40:26.086006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T06:40:26.378846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
30 1519
100.0%

관리기관전화번호
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size12.0 KiB
044-300-2454
1519 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row044-300-2454
2nd row044-300-2454
3rd row044-300-2454
4th row044-300-2454
5th row044-300-2454

Common Values

ValueCountFrequency (%)
044-300-2454 1519
100.0%

Length

2024-03-23T06:40:26.719785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T06:40:27.071706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
044-300-2454 1519
100.0%

위도
Real number (ℝ)

Distinct1403
Distinct (%)92.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.532687
Minimum36.41192
Maximum36.73294
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.5 KiB
2024-03-23T06:40:27.843770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.41192
5-th percentile36.466479
Q136.488755
median36.5083
Q336.58043
95-th percentile36.678541
Maximum36.73294
Range0.32102
Interquartile range (IQR)0.091675

Descriptive statistics

Standard deviation0.063704293
Coefficient of variation (CV)0.0017437615
Kurtosis0.62236647
Mean36.532687
Median Absolute Deviation (MAD)0.02611
Skewness1.1269639
Sum55493.152
Variance0.004058237
MonotonicityNot monotonic
2024-03-23T06:40:28.466806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.48479 10
 
0.7%
36.49816 3
 
0.2%
36.60306 3
 
0.2%
36.54288 3
 
0.2%
36.49845 3
 
0.2%
36.49941 3
 
0.2%
36.48011 3
 
0.2%
36.49728 3
 
0.2%
36.49505 2
 
0.1%
36.51603 2
 
0.1%
Other values (1393) 1484
97.7%
ValueCountFrequency (%)
36.41192 1
0.1%
36.41663 1
0.1%
36.41896 1
0.1%
36.41911 1
0.1%
36.4195 1
0.1%
36.42103 1
0.1%
36.42242 1
0.1%
36.42376 1
0.1%
36.42508 1
0.1%
36.42838 1
0.1%
ValueCountFrequency (%)
36.73294 1
0.1%
36.73293 1
0.1%
36.72848 1
0.1%
36.7277 1
0.1%
36.72651 1
0.1%
36.72637 1
0.1%
36.72618 1
0.1%
36.72564 1
0.1%
36.7248 1
0.1%
36.72454 1
0.1%

경도
Real number (ℝ)

Distinct925
Distinct (%)60.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.27216
Minimum127.1399
Maximum127.4056
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.5 KiB
2024-03-23T06:40:29.415719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.1399
5-th percentile127.19716
Q1127.2501
median127.273
Q3127.2955
95-th percentile127.35152
Maximum127.4056
Range0.2657
Interquartile range (IQR)0.0454

Descriptive statistics

Standard deviation0.042676232
Coefficient of variation (CV)0.00033531475
Kurtosis0.94598401
Mean127.27216
Median Absolute Deviation (MAD)0.0227
Skewness-0.052431785
Sum193326.41
Variance0.0018212608
MonotonicityNot monotonic
2024-03-23T06:40:30.154072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.2927 10
 
0.7%
127.2962 7
 
0.5%
127.2878 7
 
0.5%
127.2622 6
 
0.4%
127.2572 6
 
0.4%
127.2582 6
 
0.4%
127.2632 5
 
0.3%
127.2327 5
 
0.3%
127.2981 5
 
0.3%
127.2892 5
 
0.3%
Other values (915) 1457
95.9%
ValueCountFrequency (%)
127.1399 1
0.1%
127.1422 1
0.1%
127.1428 1
0.1%
127.1451 1
0.1%
127.1462 1
0.1%
127.1474 1
0.1%
127.148 1
0.1%
127.1489 1
0.1%
127.1492 1
0.1%
127.1511 1
0.1%
ValueCountFrequency (%)
127.4056 1
0.1%
127.4036 1
0.1%
127.4028 1
0.1%
127.4023 1
0.1%
127.4017 1
0.1%
127.3993 1
0.1%
127.3987 1
0.1%
127.3968 1
0.1%
127.3965 1
0.1%
127.3926 1
0.1%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size12.0 KiB
Minimum2023-12-31 00:00:00
Maximum2023-12-31 00:00:00
2024-03-23T06:40:30.681080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:40:31.273360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-03-23T06:40:14.297719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:40:11.964980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:40:13.097045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:40:14.657446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:40:12.334966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:40:13.449484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:40:15.134424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:40:12.710353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:40:13.850735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T06:40:31.785085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치목적구분카메라대수카메라화소수위도경도
설치목적구분1.0000.2950.0000.2700.340
카메라대수0.2951.0000.1880.3610.372
카메라화소수0.0000.1881.0000.1060.095
위도0.2700.3610.1061.0000.827
경도0.3400.3720.0950.8271.000
2024-03-23T06:40:32.518318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치목적구분카메라화소수
설치목적구분1.0000.000
카메라화소수0.0001.000
2024-03-23T06:40:33.105675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
카메라대수위도경도설치목적구분카메라화소수
카메라대수1.0000.1300.2060.2120.135
위도0.1301.000-0.0600.2060.081
경도0.206-0.0601.0000.2600.073
설치목적구분0.2120.2060.2601.0000.000
카메라화소수0.1350.0810.0730.0001.000

Missing values

2024-03-23T06:40:15.626574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T06:40:16.335779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

관리기관명소재지지번주소설치목적구분카메라대수카메라화소수촬영방면정보보관일수관리기관전화번호위도경도데이터기준일자
0세종특별자치시청세종특별자치시 세종동 747-432생활방범2200공원 산책로 일대30044-300-245436.47627127.27692023-12-31
1세종특별자치시청세종특별자치시 대평동 77-61생활방범1200공원 산책로 일대30044-300-245436.46951127.28012023-12-31
2세종특별자치시청세종특별자치시 연기면 세종동 747-89생활방범3200공원 산책로 일대30044-300-245436.47619127.27512023-12-31
3세종특별자치시청세종특별자치시 세종동 747-373생활방범3200공원 산책로 일대30044-300-245436.46831127.26392023-12-31
4세종특별자치시청세종특별자치시 연기면 세종동 747-272생활방범2200공원 산책로 일대30044-300-245436.4717127.26632023-12-31
5세종특별자치시청세종특별자치시 대평동 580-18생활방범2200배트민턴장 주변30044-300-245436.46684127.26442023-12-31
6세종특별자치시청세종특별자치시 대평동137-12생활방범2200배수펌프장 주변30044-300-245436.46544127.26932023-12-31
7세종특별자치시청세종특별자치시 대평동 643생활방범2200교차로 주변30044-300-245436.46727127.27522023-12-31
8세종특별자치시청세종특별자치시 보람동 664-27생활방범3200교차로 주변30044-300-245436.47674127.28382023-12-31
9세종특별자치시청세종특별자치시 보람동 664-105생활방범3200교차로 주변30044-300-245436.47643127.28392023-12-31
관리기관명소재지지번주소설치목적구분카메라대수카메라화소수촬영방면정보보관일수관리기관전화번호위도경도데이터기준일자
1509세종특별자치시청세종특별자치시 고운동 1008생활방범1200고운동 홍익돈까스옆30044-300-245436.51827127.2322023-12-31
1510세종특별자치시청세종특별자치시 고운동 1370생활방범2200고운동 고운프라자사거리30044-300-245436.5193127.23422023-12-31
1511세종특별자치시청세종특별자치시 고운동 1373생활방범2200고운동 에듀프라자앞30044-300-245436.51982127.23572023-12-31
1512세종특별자치시청세종특별자치시 아름동 1338생활방범2200고운동 대법원 등기정보센터앞30044-300-245436.50985127.24172023-12-31
1513세종특별자치시청세종특별자치시 고운동 산170-2생활방범2200고운동 자전거보관센터30044-300-245436.50908127.24112023-12-31
1514세종특별자치시청세종특별자치시 고운동 1255생활방범1200고운동 시골길 낚지볶음 건너편30044-300-245436.51701127.23112023-12-31
1515세종특별자치시청세종특별자치시 고운동 1356생활방범1200고운동 SK주유소옆30044-300-245436.51455127.23332023-12-31
1516세종특별자치시청세종특별자치시 고운동 2212생활방범2200고운동 자연드림 건너편30044-300-245436.516127.23442023-12-31
1517세종특별자치시청세종특별자치시 고운동 1215생활방범1200고운동 1501동옆30044-300-245436.51683127.2362023-12-31
1518세종특별자치시청세종특별자치시 고운동 904생활방범1200고운동 가락마을 1919동 사거리30044-300-245436.5214127.23282023-12-31

Duplicate rows

Most frequently occurring

관리기관명소재지지번주소설치목적구분카메라대수카메라화소수촬영방면정보보관일수관리기관전화번호위도경도데이터기준일자# duplicates
1세종특별자치시청세종특별자치시 세종동 29-11생활방범1200이응다리 공원내30044-300-245436.48479127.29272023-12-317
0세종특별자치시청세종특별자치시 부강면 부강리 412-9번지생활방범2200새말어린이공원내30044-300-245436.53048127.36392023-12-312
2세종특별자치시청세종특별자치시 장군면 금암리 407차량방범3200금송로30044-300-245436.43867127.20922023-12-312
3세종특별자치시청충청남도 공주시 동현동 19-48차량방범4200장기로30044-300-245436.48918127.19282023-12-312