Overview

Dataset statistics

Number of variables10
Number of observations25
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.2 KiB
Average record size in memory88.3 B

Variable types

Numeric3
Categorical4
Text3

Dataset

Description부산광역시서구_재난예경보시스템현황_20230907
Author부산광역시 서구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15089611

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
연번 is highly overall correlated with 시스템유형High correlation
시스템유형 is highly overall correlated with 연번High correlation
설치장소 has unique valuesUnique

Reproduction

Analysis started2023-12-10 16:47:26.668786
Analysis finished2023-12-10 16:47:28.459445
Duration1.79 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION 

Distinct24
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.28
Minimum1
Maximum24
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-11T01:47:28.528847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.2
Q17
median12
Q318
95-th percentile22.8
Maximum24
Range23
Interquartile range (IQR)11

Descriptive statistics

Standard deviation7.0090418
Coefficient of variation (CV)0.57076887
Kurtosis-1.1957231
Mean12.28
Median Absolute Deviation (MAD)6
Skewness0.080503967
Sum307
Variance49.126667
MonotonicityIncreasing
2023-12-11T01:47:28.735790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
7 2
 
8.0%
1 1
 
4.0%
14 1
 
4.0%
24 1
 
4.0%
23 1
 
4.0%
22 1
 
4.0%
21 1
 
4.0%
20 1
 
4.0%
19 1
 
4.0%
18 1
 
4.0%
Other values (14) 14
56.0%
ValueCountFrequency (%)
1 1
4.0%
2 1
4.0%
3 1
4.0%
4 1
4.0%
5 1
4.0%
6 1
4.0%
7 2
8.0%
8 1
4.0%
9 1
4.0%
10 1
4.0%
ValueCountFrequency (%)
24 1
4.0%
23 1
4.0%
22 1
4.0%
21 1
4.0%
20 1
4.0%
19 1
4.0%
18 1
4.0%
17 1
4.0%
16 1
4.0%
15 1
4.0%

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
부산광역시
25 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부산광역시 25
100.0%

Length

2023-12-11T01:47:28.882298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:47:29.021394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 25
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
서구
25 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서구 25
100.0%

Length

2023-12-11T01:47:29.153613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:47:29.269599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서구 25
100.0%

행정동명
Text

Distinct14
Distinct (%)56.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-11T01:47:29.413592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.92
Min length3

Characters and Unicode

Total characters98
Distinct characters18
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)32.0%

Sample

1st row암남동
2nd row암남동
3rd row암남동
4th row서대신3동
5th row아미동
ValueCountFrequency (%)
암남동 7
28.0%
서대신3동 2
 
8.0%
아미동 2
 
8.0%
동대신1동 2
 
8.0%
서대신1동 2
 
8.0%
충무동 2
 
8.0%
남부민동 1
 
4.0%
동대신2동 1
 
4.0%
동대신3동 1
 
4.0%
서대신4동 1
 
4.0%
Other values (4) 4
16.0%
2023-12-11T01:47:29.731052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 29
29.6%
남 10
 
10.2%
신 9
 
9.2%
대 9
 
9.2%
암 7
 
7.1%
1 5
 
5.1%
서 5
 
5.1%
부 4
 
4.1%
민 4
 
4.1%
3 3
 
3.1%
Other values (8) 13
13.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 87
88.8%
Decimal Number 11
 
11.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 29
33.3%
남 10
 
11.5%
신 9
 
10.3%
대 9
 
10.3%
암 7
 
8.0%
서 5
 
5.7%
부 4
 
4.6%
민 4
 
4.6%
아 2
 
2.3%
미 2
 
2.3%
Other values (4) 6
 
6.9%
Decimal Number
ValueCountFrequency (%)
1 5
45.5%
3 3
27.3%
2 2
 
18.2%
4 1
 
9.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 87
88.8%
Common 11
 
11.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 29
33.3%
남 10
 
11.5%
신 9
 
10.3%
대 9
 
10.3%
암 7
 
8.0%
서 5
 
5.7%
부 4
 
4.6%
민 4
 
4.6%
아 2
 
2.3%
미 2
 
2.3%
Other values (4) 6
 
6.9%
Common
ValueCountFrequency (%)
1 5
45.5%
3 3
27.3%
2 2
 
18.2%
4 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 87
88.8%
ASCII 11
 
11.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 29
33.3%
남 10
 
11.5%
신 9
 
10.3%
대 9
 
10.3%
암 7
 
8.0%
서 5
 
5.7%
부 4
 
4.6%
민 4
 
4.6%
아 2
 
2.3%
미 2
 
2.3%
Other values (4) 6
 
6.9%
ASCII
ValueCountFrequency (%)
1 5
45.5%
3 3
27.3%
2 2
 
18.2%
4 1
 
9.1%

설치장소
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-11T01:47:30.009853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length22
Mean length18.28
Min length5

Characters and Unicode

Total characters457
Distinct characters86
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)100.0%

Sample

1st row송도해수욕장 송림공원 입구
2nd row송도해수욕장 임해행정봉사실 옥상
3rd row송도해수욕장 송도공영주차장 옥상
4th row꽃마을 마을버스 주차장 인근
5th row아미동 행복센터 진입로 입구
ValueCountFrequency (%)
옥상 15
 
14.0%
주민센터 13
 
12.1%
부산광역시 13
 
12.1%
서구 13
 
12.1%
송도해수욕장 4
 
3.7%
옆 3
 
2.8%
입구 2
 
1.9%
임해행정봉사실 2
 
1.9%
아미동 2
 
1.9%
출구 2
 
1.9%
Other values (38) 38
35.5%
2023-12-11T01:47:30.493201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
82
 
17.9%
서 19
 
4.2%
동 18
 
3.9%
구 18
 
3.9%
부 16
 
3.5%
민 16
 
3.5%
상 15
 
3.3%
주 15
 
3.3%
옥 15
 
3.3%
센 14
 
3.1%
Other values (76) 229
50.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 365
79.9%
Space Separator 82
 
17.9%
Decimal Number 10
 
2.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 19
 
5.2%
동 18
 
4.9%
구 18
 
4.9%
부 16
 
4.4%
민 16
 
4.4%
상 15
 
4.1%
주 15
 
4.1%
옥 15
 
4.1%
센 14
 
3.8%
역 14
 
3.8%
Other values (70) 205
56.2%
Decimal Number
ValueCountFrequency (%)
1 3
30.0%
2 3
30.0%
3 2
20.0%
4 1
 
10.0%
7 1
 
10.0%
Space Separator
ValueCountFrequency (%)
82
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 365
79.9%
Common 92
 
20.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 19
 
5.2%
동 18
 
4.9%
구 18
 
4.9%
부 16
 
4.4%
민 16
 
4.4%
상 15
 
4.1%
주 15
 
4.1%
옥 15
 
4.1%
센 14
 
3.8%
역 14
 
3.8%
Other values (70) 205
56.2%
Common
ValueCountFrequency (%)
82
89.1%
1 3
 
3.3%
2 3
 
3.3%
3 2
 
2.2%
4 1
 
1.1%
7 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 365
79.9%
ASCII 92
 
20.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
82
89.1%
1 3
 
3.3%
2 3
 
3.3%
3 2
 
2.2%
4 1
 
1.1%
7 1
 
1.1%
Hangul
ValueCountFrequency (%)
서 19
 
5.2%
동 18
 
4.9%
구 18
 
4.9%
부 16
 
4.4%
민 16
 
4.4%
상 15
 
4.1%
주 15
 
4.1%
옥 15
 
4.1%
센 14
 
3.8%
역 14
 
3.8%
Other values (70) 205
56.2%

주소
Text

Distinct23
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-11T01:47:30.766436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length21
Mean length18.44
Min length15

Characters and Unicode

Total characters461
Distinct characters54
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)84.0%

Sample

1st row부산광역시 서구 암남동 124-51
2nd row부산광역시 서구 송도해변로 100
3rd row부산광역시 서구 암남공원로 25
4th row부산광역시 서구 꽃마을로163번길 4
5th row부산광역시 서구 까치고개로 130
ValueCountFrequency (%)
부산광역시 25
23.4%
서구 25
23.4%
충무대로 4
 
3.7%
구덕로 3
 
2.8%
32 3
 
2.8%
100 2
 
1.9%
대영로 2
 
1.9%
송도해변로 2
 
1.9%
56 2
 
1.9%
해돋이로 2
 
1.9%
Other values (37) 37
34.6%
2023-12-11T01:47:31.174596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
82
17.8%
구 29
 
6.3%
시 26
 
5.6%
서 26
 
5.6%
부 25
 
5.4%
산 25
 
5.4%
광 25
 
5.4%
역 25
 
5.4%
로 22
 
4.8%
2 18
 
3.9%
Other values (44) 158
34.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 289
62.7%
Decimal Number 86
 
18.7%
Space Separator 82
 
17.8%
Dash Punctuation 4
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 29
10.0%
시 26
 
9.0%
서 26
 
9.0%
부 25
 
8.7%
산 25
 
8.7%
광 25
 
8.7%
역 25
 
8.7%
로 22
 
7.6%
길 10
 
3.5%
번 9
 
3.1%
Other values (32) 67
23.2%
Decimal Number
ValueCountFrequency (%)
2 18
20.9%
1 14
16.3%
5 11
12.8%
3 8
9.3%
6 7
 
8.1%
0 7
 
8.1%
7 7
 
8.1%
8 5
 
5.8%
9 5
 
5.8%
4 4
 
4.7%
Space Separator
ValueCountFrequency (%)
82
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 289
62.7%
Common 172
37.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 29
10.0%
시 26
 
9.0%
서 26
 
9.0%
부 25
 
8.7%
산 25
 
8.7%
광 25
 
8.7%
역 25
 
8.7%
로 22
 
7.6%
길 10
 
3.5%
번 9
 
3.1%
Other values (32) 67
23.2%
Common
ValueCountFrequency (%)
82
47.7%
2 18
 
10.5%
1 14
 
8.1%
5 11
 
6.4%
3 8
 
4.7%
6 7
 
4.1%
0 7
 
4.1%
7 7
 
4.1%
8 5
 
2.9%
9 5
 
2.9%
Other values (2) 8
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 289
62.7%
ASCII 172
37.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
82
47.7%
2 18
 
10.5%
1 14
 
8.1%
5 11
 
6.4%
3 8
 
4.7%
6 7
 
4.1%
0 7
 
4.1%
7 7
 
4.1%
8 5
 
2.9%
9 5
 
2.9%
Other values (2) 8
 
4.7%
Hangul
ValueCountFrequency (%)
구 29
10.0%
시 26
 
9.0%
서 26
 
9.0%
부 25
 
8.7%
산 25
 
8.7%
광 25
 
8.7%
역 25
 
8.7%
로 22
 
7.6%
길 10
 
3.5%
번 9
 
3.1%
Other values (32) 67
23.2%

시스템유형
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
자동음성통보시스템
15 
자동음성통보시스템 및 CCTV
5 
재난문자 전광판
4 
CCTV
 
1

Length

Max length16
Median length9
Mean length10.04
Min length4

Unique

Unique1 ?
Unique (%)4.0%

Sample

1st row자동음성통보시스템 및 CCTV
2nd row자동음성통보시스템
3rd row자동음성통보시스템
4th row자동음성통보시스템 및 CCTV
5th row자동음성통보시스템 및 CCTV

Common Values

ValueCountFrequency (%)
자동음성통보시스템 15
60.0%
자동음성통보시스템 및 CCTV 5
 
20.0%
재난문자 전광판 4
 
16.0%
CCTV 1
 
4.0%

Length

2023-12-11T01:47:31.346377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:47:31.497101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자동음성통보시스템 20
51.3%
cctv 6
 
15.4%
및 5
 
12.8%
재난문자 4
 
10.3%
전광판 4
 
10.3%

위도
Real number (ℝ)

Distinct23
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.097481
Minimum35.073143
Maximum35.127621
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-11T01:47:31.620172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.073143
5-th percentile35.074292
Q135.079907
median35.100171
Q335.110832
95-th percentile35.114228
Maximum35.127621
Range0.054478
Interquartile range (IQR)0.030925

Descriptive statistics

Standard deviation0.015802857
Coefficient of variation (CV)0.00045025615
Kurtosis-1.1247528
Mean35.097481
Median Absolute Deviation (MAD)0.012816
Skewness-0.16769808
Sum877.43702
Variance0.00024973028
MonotonicityNot monotonic
2023-12-11T01:47:31.772391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
35.101724 2
 
8.0%
35.113474 2
 
8.0%
35.0765104 1
 
4.0%
35.114417 1
 
4.0%
35.079907 1
 
4.0%
35.084486 1
 
4.0%
35.092702 1
 
4.0%
35.097991 1
 
4.0%
35.09594 1
 
4.0%
35.100171 1
 
4.0%
Other values (13) 13
52.0%
ValueCountFrequency (%)
35.073143 1
4.0%
35.0737377 1
4.0%
35.0765104 1
4.0%
35.076762 1
4.0%
35.0777603 1
4.0%
35.078491 1
4.0%
35.079907 1
4.0%
35.084486 1
4.0%
35.092702 1
4.0%
35.09594 1
4.0%
ValueCountFrequency (%)
35.127621 1
4.0%
35.114417 1
4.0%
35.113474 2
8.0%
35.112987 1
4.0%
35.111103 1
4.0%
35.110832 1
4.0%
35.110624 1
4.0%
35.109658 1
4.0%
35.103817 1
4.0%
35.101724 2
8.0%

경도
Real number (ℝ)

Distinct23
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.01751
Minimum129.0069
Maximum129.02469
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-11T01:47:31.922350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum129.0069
5-th percentile129.0109
Q1129.01437
median129.01837
Q3129.02064
95-th percentile129.02353
Maximum129.02469
Range0.01779
Interquartile range (IQR)0.00627

Descriptive statistics

Standard deviation0.0046766303
Coefficient of variation (CV)3.6248029 × 10-5
Kurtosis-0.48396404
Mean129.01751
Median Absolute Deviation (MAD)0.002949
Skewness-0.49573587
Sum3225.4376
Variance2.1870871 × 10-5
MonotonicityNot monotonic
2023-12-11T01:47:32.057478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
129.010904 2
 
8.0%
129.011928 2
 
8.0%
129.023581 1
 
4.0%
129.017311 1
 
4.0%
129.020983 1
 
4.0%
129.02064 1
 
4.0%
129.023334 1
 
4.0%
129.021654 1
 
4.0%
129.020307 1
 
4.0%
129.015423 1
 
4.0%
Other values (13) 13
52.0%
ValueCountFrequency (%)
129.006897 1
4.0%
129.010904 2
8.0%
129.011928 2
8.0%
129.012295 1
4.0%
129.01437 1
4.0%
129.015423 1
4.0%
129.015829 1
4.0%
129.017311 1
4.0%
129.017883 1
4.0%
129.017887 1
4.0%
ValueCountFrequency (%)
129.024687 1
4.0%
129.023581 1
4.0%
129.023334 1
4.0%
129.02321 1
4.0%
129.021654 1
4.0%
129.020983 1
4.0%
129.02064 1
4.0%
129.020307 1
4.0%
129.020262 1
4.0%
129.019962 1
4.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-09-07
25 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-09-07
2nd row2023-09-07
3rd row2023-09-07
4th row2023-09-07
5th row2023-09-07

Common Values

ValueCountFrequency (%)
2023-09-07 25
100.0%

Length

2023-12-11T01:47:32.218031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:47:32.311709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-09-07 25
100.0%

Interactions

2023-12-11T01:47:27.926153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:47:27.029488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:47:27.320118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:47:28.013522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:47:27.123188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:47:27.432329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:47:28.101518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:47:27.219032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:47:27.542087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:47:32.388047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번행정동명설치장소주소시스템유형위도경도
연번1.0000.6761.0000.9680.8110.7220.488
행정동명0.6761.0001.0001.0000.0000.9130.000
설치장소1.0001.0001.0001.0001.0001.0001.000
주소0.9681.0001.0001.0000.0001.0000.975
시스템유형0.8110.0001.0000.0001.0000.0000.175
위도0.7220.9131.0001.0000.0001.0000.000
경도0.4880.0001.0000.9750.1750.0001.000
2023-12-11T01:47:32.505878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도시스템유형
연번1.0000.1970.2970.531
위도0.1971.000-0.4530.000
경도0.297-0.4531.0000.078
시스템유형0.5310.0000.0781.000

Missing values

2023-12-11T01:47:28.227724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:47:28.385184image/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

연번시도명시군구명행정동명설치장소주소시스템유형위도경도데이터기준일자
01부산광역시서구암남동송도해수욕장 송림공원 입구부산광역시 서구 암남동 124-51자동음성통보시스템 및 CCTV35.07651129.0235812023-09-07
12부산광역시서구암남동송도해수욕장 임해행정봉사실 옥상부산광역시 서구 송도해변로 100자동음성통보시스템35.07776129.0199622023-09-07
23부산광역시서구암남동송도해수욕장 송도공영주차장 옥상부산광역시 서구 암남공원로 25자동음성통보시스템35.073738129.0158292023-09-07
34부산광역시서구서대신3동꽃마을 마을버스 주차장 인근부산광역시 서구 꽃마을로163번길 4자동음성통보시스템 및 CCTV35.127621129.0068972023-09-07
45부산광역시서구아미동아미동 행복센터 진입로 입구부산광역시 서구 까치고개로 130자동음성통보시스템 및 CCTV35.101724129.0109042023-09-07
56부산광역시서구남부민동풀리페 아파트 도로변부산광역시 서구 해돋이로 32자동음성통보시스템 및 CCTV35.101724129.0109042023-09-07
67부산광역시서구암남동송도 탑스빌 맞은편 교통섬부산광역시 서구 충무대로 56자동음성통보시스템 및 CCTV35.078491129.0185522023-09-07
77부산광역시서구암남동송도오션파크 테트라포트 옆부산광역시 서구 충무대로 56CCTV35.073143129.0178872023-09-07
88부산광역시서구암남동송도해수욕장 임해행정봉사실 옆부산광역시 서구 송도해변로 100재난문자 전광판35.076762129.0178832023-09-07
99부산광역시서구동대신1동동대신교차로 신한은행 옆 지하철 7번 출구부산광역시 서구 대영로 62-3재난문자 전광판35.110832129.0183722023-09-07
연번시도명시군구명행정동명설치장소주소시스템유형위도경도데이터기준일자
1515부산광역시서구서대신1동부산광역시 서구 서대신1동 주민센터 옥상부산광역시 서구 구덕로315번길 49자동음성통보시스템35.111103129.014372023-09-07
1616부산광역시서구서대신3동부산광역시 서구 서대신3동 주민센터 옥상부산광역시 서구 대신로 27자동음성통보시스템35.113474129.0119282023-09-07
1717부산광역시서구서대신4동부산광역시 서구 서대신4동 주민센터 옥상부산광역시 서구 꽃마을로 58자동음성통보시스템35.113474129.0119282023-09-07
1818부산광역시서구부민동부산광역시 서구 부민동 주민센터 옥상부산광역시 서구 임시수도기념로 22-11자동음성통보시스템35.103817129.0185432023-09-07
1919부산광역시서구아미동부산광역시 서구 아미동 주민센터 옥상부산광역시 서구 해돋이로 269번길 17자동음성통보시스템35.100171129.0154232023-09-07
2020부산광역시서구초장동부산광역시 서구 초장동 주민센터 옥상부산광역시 서구 초장로 27번길 32자동음성통보시스템35.09594129.0203072023-09-07
2121부산광역시서구충무동부산광역시 서구 충무동 주민센터 옥상부산광역시 서구 구덕로 148번길 16자동음성통보시스템35.097991129.0216542023-09-07
2222부산광역시서구남부민1동부산광역시 서구 남부민1동 주민센터 옥상부산광역시 서구 충무대로 255번길 5-26자동음성통보시스템35.092702129.0233342023-09-07
2323부산광역시서구남부민2동부산광역시 서구 남부민2동 주민센터 옥상부산광역시 서구 천마로 87자동음성통보시스템35.084486129.020642023-09-07
2424부산광역시서구암남동부산광역시 서구 암남동 주민센터 옥상부산광역시 서구 충무대로 85자동음성통보시스템35.079907129.0209832023-09-07