Overview

Dataset statistics

Number of variables19
Number of observations10000
Missing cells3381
Missing cells (%)1.8%
Duplicate rows675
Duplicate rows (%)6.8%
Total size in memory1.6 MiB
Average record size in memory166.0 B

Variable types

Text6
Categorical4
Numeric4
Boolean4
DateTime1

Dataset

Description안전비상벨 위치 현황(제공표준)
Author경기도
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=64I5OUQUMRCWUEZI5WAQ27006963&infSeq=1

Alerts

Dataset has 675 (6.8%) duplicate rowsDuplicates
관리사무소연계유무 is highly overall correlated with 경도 and 2 other fieldsHigh correlation
데이터기준일자 is highly overall correlated with 설치장소유형 and 7 other fieldsHigh correlation
설치장소유형 is highly overall correlated with 부가기능 and 1 other fieldsHigh correlation
위도 is highly overall correlated with 데이터기준일자High correlation
경도 is highly overall correlated with 관리사무소연계유무 and 1 other fieldsHigh correlation
설치목적 is highly overall correlated with 데이터기준일자High correlation
연계방식 is highly overall correlated with 경비업체연계유무 and 2 other fieldsHigh correlation
경찰연계유무 is highly overall correlated with 부가기능 and 1 other fieldsHigh correlation
경비업체연계유무 is highly overall correlated with 연계방식High correlation
부가기능 is highly overall correlated with 설치장소유형 and 4 other fieldsHigh correlation
설치목적 is highly imbalanced (88.6%)Imbalance
연계방식 is highly imbalanced (87.0%)Imbalance
경비업체연계유무 is highly imbalanced (98.3%)Imbalance
최종점검결과구분 is highly imbalanced (98.9%)Imbalance
소재지도로명주소 has 3381 (33.8%) missing valuesMissing

Reproduction

Analysis started2024-03-12 23:56:33.709330
Analysis finished2024-03-12 23:56:37.886345
Duration4.18 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

안전비상벨관리번호
Text

Distinct8905
Distinct (%)89.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-13T08:56:38.139920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length6.8735
Min length1

Characters and Unicode

Total characters68735
Distinct characters203
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7982 ?
Unique (%)79.8%

Sample

1st row수정양지-A-6
2nd rowPV-0061
3rd row15364
4th row대야동 002
5th row김포-A-448
ValueCountFrequency (%)
cctv관제센터 196
 
1.8%
비상벨 158
 
1.5%
군포1동 77
 
0.7%
금정동 47
 
0.4%
군포2동 41
 
0.4%
산본1동 38
 
0.4%
송부동 33
 
0.3%
대야동 31
 
0.3%
광정동 22
 
0.2%
산본2동 21
 
0.2%
Other values (8370) 10077
93.8%
2024-03-13T08:56:38.550925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 8835
 
12.9%
0 8107
 
11.8%
1 7347
 
10.7%
2 4886
 
7.1%
3 3916
 
5.7%
4 2857
 
4.2%
5 2543
 
3.7%
6 2505
 
3.6%
7 2169
 
3.2%
9 2074
 
3.0%
Other values (193) 23496
34.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 38427
55.9%
Other Letter 13107
 
19.1%
Dash Punctuation 8835
 
12.9%
Uppercase Letter 7547
 
11.0%
Space Separator 741
 
1.1%
Close Punctuation 70
 
0.1%
Lowercase Letter 6
 
< 0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 1104
 
8.4%
벨 1061
 
8.1%
비 1061
 
8.1%
호 843
 
6.4%
포 619
 
4.7%
당 391
 
3.0%
분 387
 
3.0%
동 375
 
2.9%
정 364
 
2.8%
김 348
 
2.7%
Other values (152) 6554
50.0%
Uppercase Letter
ValueCountFrequency (%)
A 1876
24.9%
P 1709
22.6%
V 1655
21.9%
C 669
 
8.9%
B 585
 
7.8%
T 235
 
3.1%
Z 201
 
2.7%
S 162
 
2.1%
G 95
 
1.3%
D 81
 
1.1%
Other values (12) 279
 
3.7%
Decimal Number
ValueCountFrequency (%)
0 8107
21.1%
1 7347
19.1%
2 4886
12.7%
3 3916
10.2%
4 2857
 
7.4%
5 2543
 
6.6%
6 2505
 
6.5%
7 2169
 
5.6%
9 2074
 
5.4%
8 2023
 
5.3%
Lowercase Letter
ValueCountFrequency (%)
a 2
33.3%
c 1
16.7%
y 1
16.7%
n 1
16.7%
e 1
16.7%
Dash Punctuation
ValueCountFrequency (%)
- 8835
100.0%
Space Separator
ValueCountFrequency (%)
741
100.0%
Close Punctuation
ValueCountFrequency (%)
) 70
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 48075
69.9%
Hangul 13107
 
19.1%
Latin 7553
 
11.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 1104
 
8.4%
벨 1061
 
8.1%
비 1061
 
8.1%
호 843
 
6.4%
포 619
 
4.7%
당 391
 
3.0%
분 387
 
3.0%
동 375
 
2.9%
정 364
 
2.8%
김 348
 
2.7%
Other values (152) 6554
50.0%
Latin
ValueCountFrequency (%)
A 1876
24.8%
P 1709
22.6%
V 1655
21.9%
C 669
 
8.9%
B 585
 
7.7%
T 235
 
3.1%
Z 201
 
2.7%
S 162
 
2.1%
G 95
 
1.3%
D 81
 
1.1%
Other values (17) 285
 
3.8%
Common
ValueCountFrequency (%)
- 8835
18.4%
0 8107
16.9%
1 7347
15.3%
2 4886
10.2%
3 3916
8.1%
4 2857
 
5.9%
5 2543
 
5.3%
6 2505
 
5.2%
7 2169
 
4.5%
9 2074
 
4.3%
Other values (4) 2836
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 55628
80.9%
Hangul 13107
 
19.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 8835
15.9%
0 8107
14.6%
1 7347
13.2%
2 4886
8.8%
3 3916
 
7.0%
4 2857
 
5.1%
5 2543
 
4.6%
6 2505
 
4.5%
7 2169
 
3.9%
9 2074
 
3.7%
Other values (31) 10389
18.7%
Hangul
ValueCountFrequency (%)
상 1104
 
8.4%
벨 1061
 
8.1%
비 1061
 
8.1%
호 843
 
6.4%
포 619
 
4.7%
당 391
 
3.0%
분 387
 
3.0%
동 375
 
2.9%
정 364
 
2.8%
김 348
 
2.7%
Other values (152) 6554
50.0%

설치목적
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
9738 
2
 
254
99
 
8

Length

Max length2
Median length1
Mean length1.0008
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 9738
97.4%
2 254
 
2.5%
99 8
 
0.1%

Length

2024-03-13T08:56:38.658614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T08:56:38.758813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 9738
97.4%
2 254
 
2.5%
99 8
 
0.1%

설치장소유형
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean45.877
Minimum1
Maximum99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T08:56:38.838013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q15
median5
Q399
95-th percentile99
Maximum99
Range98
Interquartile range (IQR)94

Descriptive statistics

Standard deviation47.395047
Coefficient of variation (CV)1.0330895
Kurtosis-1.945764
Mean45.877
Median Absolute Deviation (MAD)4
Skewness0.227372
Sum458770
Variance2246.2905
MonotonicityNot monotonic
2024-03-13T08:56:38.925228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
99 4430
44.3%
5 3285
32.9%
2 1312
 
13.1%
1 911
 
9.1%
4 54
 
0.5%
3 8
 
0.1%
ValueCountFrequency (%)
1 911
 
9.1%
2 1312
 
13.1%
3 8
 
0.1%
4 54
 
0.5%
5 3285
32.9%
99 4430
44.3%
ValueCountFrequency (%)
99 4430
44.3%
5 3285
32.9%
4 54
 
0.5%
3 8
 
0.1%
2 1312
 
13.1%
1 911
 
9.1%

설치위치
Text

Distinct7768
Distinct (%)77.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-13T08:56:39.132978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length44
Mean length10.4647
Min length1

Characters and Unicode

Total characters104647
Distinct characters797
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6958 ?
Unique (%)69.6%

Sample

1st row.
2nd row신길동 1368-50
3rd row청와삼대 맞은편
4th row시티그린빌
5th row경기도 김포시 구래동 638-2 (솔터마을 자연앤힐스테이트아파트 503동 육교위)
ValueCountFrequency (%)
경기도 1797
 
7.6%
앞 993
 
4.2%
파주시 831
 
3.5%
안산시 437
 
1.8%
삼거리 369
 
1.6%
김포시 348
 
1.5%
342
 
1.4%
본오동 309
 
1.3%
상록구 296
 
1.2%
주변 287
 
1.2%
Other values (8757) 17763
74.7%
2024-03-13T08:56:39.478929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13785
 
13.2%
동 3479
 
3.3%
1 3087
 
2.9%
- 2283
 
2.2%
원 2195
 
2.1%
도 2178
 
2.1%
시 2024
 
1.9%
기 1958
 
1.9%
경 1940
 
1.9%
2 1781
 
1.7%
Other values (787) 69937
66.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 70651
67.5%
Decimal Number 14720
 
14.1%
Space Separator 13785
 
13.2%
Dash Punctuation 2283
 
2.2%
Close Punctuation 1019
 
1.0%
Open Punctuation 1017
 
1.0%
Uppercase Letter 562
 
0.5%
Other Punctuation 455
 
0.4%
Lowercase Letter 65
 
0.1%
Connector Punctuation 63
 
0.1%
Other values (2) 27
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 3479
 
4.9%
원 2195
 
3.1%
도 2178
 
3.1%
시 2024
 
2.9%
기 1958
 
2.8%
경 1940
 
2.7%
주 1726
 
2.4%
리 1657
 
2.3%
공 1600
 
2.3%
이 1342
 
1.9%
Other values (719) 50552
71.6%
Uppercase Letter
ValueCountFrequency (%)
E 67
11.9%
C 62
11.0%
A 56
10.0%
S 50
 
8.9%
R 44
 
7.8%
G 42
 
7.5%
T 32
 
5.7%
I 30
 
5.3%
P 26
 
4.6%
K 25
 
4.4%
Other values (14) 128
22.8%
Lowercase Letter
ValueCountFrequency (%)
e 14
21.5%
s 7
10.8%
c 6
9.2%
g 6
9.2%
o 5
 
7.7%
k 4
 
6.2%
t 4
 
6.2%
r 3
 
4.6%
a 3
 
4.6%
i 3
 
4.6%
Other values (6) 10
15.4%
Decimal Number
ValueCountFrequency (%)
1 3087
21.0%
2 1781
12.1%
6 1405
9.5%
7 1375
9.3%
5 1367
9.3%
3 1301
8.8%
4 1295
8.8%
8 1120
 
7.6%
0 1036
 
7.0%
9 953
 
6.5%
Other Punctuation
ValueCountFrequency (%)
. 242
53.2%
, 82
 
18.0%
/ 51
 
11.2%
# 33
 
7.3%
@ 32
 
7.0%
: 13
 
2.9%
& 1
 
0.2%
? 1
 
0.2%
Close Punctuation
ValueCountFrequency (%)
) 1011
99.2%
] 8
 
0.8%
Open Punctuation
ValueCountFrequency (%)
( 1009
99.2%
[ 8
 
0.8%
Math Symbol
ValueCountFrequency (%)
~ 13
92.9%
→ 1
 
7.1%
Space Separator
ValueCountFrequency (%)
13785
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2283
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 63
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 70664
67.5%
Common 33356
31.9%
Latin 627
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 3479
 
4.9%
원 2195
 
3.1%
도 2178
 
3.1%
시 2024
 
2.9%
기 1958
 
2.8%
경 1940
 
2.7%
주 1726
 
2.4%
리 1657
 
2.3%
공 1600
 
2.3%
이 1342
 
1.9%
Other values (720) 50565
71.6%
Latin
ValueCountFrequency (%)
E 67
 
10.7%
C 62
 
9.9%
A 56
 
8.9%
S 50
 
8.0%
R 44
 
7.0%
G 42
 
6.7%
T 32
 
5.1%
I 30
 
4.8%
P 26
 
4.1%
K 25
 
4.0%
Other values (30) 193
30.8%
Common
ValueCountFrequency (%)
13785
41.3%
1 3087
 
9.3%
- 2283
 
6.8%
2 1781
 
5.3%
6 1405
 
4.2%
7 1375
 
4.1%
5 1367
 
4.1%
3 1301
 
3.9%
4 1295
 
3.9%
8 1120
 
3.4%
Other values (17) 4557
 
13.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 70651
67.5%
ASCII 33982
32.5%
None 13
 
< 0.1%
Arrows 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
13785
40.6%
1 3087
 
9.1%
- 2283
 
6.7%
2 1781
 
5.2%
6 1405
 
4.1%
7 1375
 
4.0%
5 1367
 
4.0%
3 1301
 
3.8%
4 1295
 
3.8%
8 1120
 
3.3%
Other values (56) 5183
 
15.3%
Hangul
ValueCountFrequency (%)
동 3479
 
4.9%
원 2195
 
3.1%
도 2178
 
3.1%
시 2024
 
2.9%
기 1958
 
2.8%
경 1940
 
2.7%
주 1726
 
2.4%
리 1657
 
2.3%
공 1600
 
2.3%
이 1342
 
1.9%
Other values (719) 50552
71.6%
None
ValueCountFrequency (%)
㈜ 13
100.0%
Arrows
ValueCountFrequency (%)
→ 1
100.0%

소재지도로명주소
Text

MISSING 

Distinct5381
Distinct (%)81.3%
Missing3381
Missing (%)33.8%
Memory size156.2 KiB
2024-03-13T08:56:39.741881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length38
Mean length20.061187
Min length12

Characters and Unicode

Total characters132785
Distinct characters402
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4512 ?
Unique (%)68.2%

Sample

1st row경기도 성남시 수정구 산성대로527번길 8 (양지동)
2nd row경기도 안산시 단원구 신길동 1368-50
3rd row경기도 군포시 대야2로 93
4th row경기도 안산시 상록구 각골로2안길 18
5th row경기도 양주시 옥정로 214
ValueCountFrequency (%)
경기도 6619
 
21.0%
안산시 2450
 
7.8%
상록구 1373
 
4.4%
단원구 1077
 
3.4%
안양시 691
 
2.2%
평택시 538
 
1.7%
성남시 407
 
1.3%
파주시 399
 
1.3%
하남시 352
 
1.1%
동안구 348
 
1.1%
Other values (5200) 17282
54.8%
2024-03-13T08:56:40.106281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
24920
18.8%
경 6721
 
5.1%
도 6705
 
5.0%
기 6650
 
5.0%
시 6593
 
5.0%
1 4793
 
3.6%
안 4446
 
3.3%
로 4186
 
3.2%
구 3761
 
2.8%
2 3230
 
2.4%
Other values (392) 60780
45.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 82122
61.8%
Space Separator 24920
 
18.8%
Decimal Number 23084
 
17.4%
Dash Punctuation 1770
 
1.3%
Close Punctuation 419
 
0.3%
Open Punctuation 418
 
0.3%
Other Punctuation 50
 
< 0.1%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 6721
 
8.2%
도 6705
 
8.2%
기 6650
 
8.1%
시 6593
 
8.0%
안 4446
 
5.4%
로 4186
 
5.1%
구 3761
 
4.6%
길 3093
 
3.8%
산 3083
 
3.8%
동 2643
 
3.2%
Other values (375) 34241
41.7%
Decimal Number
ValueCountFrequency (%)
1 4793
20.8%
2 3230
14.0%
3 2751
11.9%
5 2156
9.3%
4 2114
9.2%
6 1843
 
8.0%
7 1818
 
7.9%
0 1502
 
6.5%
8 1502
 
6.5%
9 1375
 
6.0%
Uppercase Letter
ValueCountFrequency (%)
K 1
50.0%
S 1
50.0%
Space Separator
ValueCountFrequency (%)
24920
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1770
100.0%
Close Punctuation
ValueCountFrequency (%)
) 419
100.0%
Open Punctuation
ValueCountFrequency (%)
( 418
100.0%
Other Punctuation
ValueCountFrequency (%)
, 50
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 82122
61.8%
Common 50661
38.2%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 6721
 
8.2%
도 6705
 
8.2%
기 6650
 
8.1%
시 6593
 
8.0%
안 4446
 
5.4%
로 4186
 
5.1%
구 3761
 
4.6%
길 3093
 
3.8%
산 3083
 
3.8%
동 2643
 
3.2%
Other values (375) 34241
41.7%
Common
ValueCountFrequency (%)
24920
49.2%
1 4793
 
9.5%
2 3230
 
6.4%
3 2751
 
5.4%
5 2156
 
4.3%
4 2114
 
4.2%
6 1843
 
3.6%
7 1818
 
3.6%
- 1770
 
3.5%
0 1502
 
3.0%
Other values (5) 3764
 
7.4%
Latin
ValueCountFrequency (%)
K 1
50.0%
S 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 82122
61.8%
ASCII 50663
38.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
24920
49.2%
1 4793
 
9.5%
2 3230
 
6.4%
3 2751
 
5.4%
5 2156
 
4.3%
4 2114
 
4.2%
6 1843
 
3.6%
7 1818
 
3.6%
- 1770
 
3.5%
0 1502
 
3.0%
Other values (7) 3766
 
7.4%
Hangul
ValueCountFrequency (%)
경 6721
 
8.2%
도 6705
 
8.2%
기 6650
 
8.1%
시 6593
 
8.0%
안 4446
 
5.4%
로 4186
 
5.1%
구 3761
 
4.6%
길 3093
 
3.8%
산 3083
 
3.8%
동 2643
 
3.2%
Other values (375) 34241
41.7%

소재지지번주소
Text

Distinct8592
Distinct (%)85.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-13T08:56:40.373379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length45
Mean length20.5982
Min length13

Characters and Unicode

Total characters205982
Distinct characters498
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7597 ?
Unique (%)76.0%

Sample

1st row경기도 성남시 수정구 양지동 270
2nd row경기도 안산시 단원구 신길동 1368-50
3rd row경기도 평택시 죽백동 131-2
4th row경기도 군포시 대야미동 634-1번지 씨티빌
5th row경기도 김포시 구래동 638-2 (솔터마을 자연앤힐스테이트아파트 503동 육교위)
ValueCountFrequency (%)
경기도 10000
 
21.0%
안산시 2517
 
5.3%
상록구 1413
 
3.0%
단원구 1104
 
2.3%
평택시 882
 
1.9%
파주시 831
 
1.7%
안양시 743
 
1.6%
성남시 709
 
1.5%
광주시 694
 
1.5%
양주시 475
 
1.0%
Other values (9088) 28250
59.3%
2024-03-13T08:56:40.751528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
37618
 
18.3%
도 10237
 
5.0%
기 10073
 
4.9%
경 10052
 
4.9%
시 9753
 
4.7%
동 8818
 
4.3%
1 7999
 
3.9%
- 6894
 
3.3%
2 4702
 
2.3%
안 4510
 
2.2%
Other values (488) 95326
46.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 120447
58.5%
Decimal Number 40352
 
19.6%
Space Separator 37618
 
18.3%
Dash Punctuation 6894
 
3.3%
Close Punctuation 300
 
0.1%
Open Punctuation 299
 
0.1%
Uppercase Letter 51
 
< 0.1%
Lowercase Letter 13
 
< 0.1%
Other Punctuation 7
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 10237
 
8.5%
기 10073
 
8.4%
경 10052
 
8.3%
시 9753
 
8.1%
동 8818
 
7.3%
안 4510
 
3.7%
구 4330
 
3.6%
산 3699
 
3.1%
지 2930
 
2.4%
양 2656
 
2.2%
Other values (444) 53389
44.3%
Uppercase Letter
ValueCountFrequency (%)
C 7
13.7%
G 5
9.8%
S 5
9.8%
I 5
9.8%
L 5
9.8%
K 5
9.8%
A 3
 
5.9%
V 3
 
5.9%
P 2
 
3.9%
H 2
 
3.9%
Other values (8) 9
17.6%
Decimal Number
ValueCountFrequency (%)
1 7999
19.8%
2 4702
11.7%
3 4043
10.0%
5 3818
9.5%
4 3796
9.4%
7 3607
8.9%
6 3603
8.9%
8 3128
 
7.8%
9 2984
 
7.4%
0 2672
 
6.6%
Lowercase Letter
ValueCountFrequency (%)
e 4
30.8%
o 3
23.1%
t 2
15.4%
c 1
 
7.7%
s 1
 
7.7%
r 1
 
7.7%
i 1
 
7.7%
Close Punctuation
ValueCountFrequency (%)
) 296
98.7%
] 4
 
1.3%
Open Punctuation
ValueCountFrequency (%)
( 295
98.7%
[ 4
 
1.3%
Other Punctuation
ValueCountFrequency (%)
, 6
85.7%
. 1
 
14.3%
Space Separator
ValueCountFrequency (%)
37618
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6894
100.0%
Math Symbol
ValueCountFrequency (%)
→ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 120447
58.5%
Common 85471
41.5%
Latin 64
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 10237
 
8.5%
기 10073
 
8.4%
경 10052
 
8.3%
시 9753
 
8.1%
동 8818
 
7.3%
안 4510
 
3.7%
구 4330
 
3.6%
산 3699
 
3.1%
지 2930
 
2.4%
양 2656
 
2.2%
Other values (444) 53389
44.3%
Latin
ValueCountFrequency (%)
C 7
 
10.9%
G 5
 
7.8%
S 5
 
7.8%
I 5
 
7.8%
L 5
 
7.8%
K 5
 
7.8%
e 4
 
6.2%
o 3
 
4.7%
A 3
 
4.7%
V 3
 
4.7%
Other values (15) 19
29.7%
Common
ValueCountFrequency (%)
37618
44.0%
1 7999
 
9.4%
- 6894
 
8.1%
2 4702
 
5.5%
3 4043
 
4.7%
5 3818
 
4.5%
4 3796
 
4.4%
7 3607
 
4.2%
6 3603
 
4.2%
8 3128
 
3.7%
Other values (9) 6263
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 120447
58.5%
ASCII 85534
41.5%
Arrows 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
37618
44.0%
1 7999
 
9.4%
- 6894
 
8.1%
2 4702
 
5.5%
3 4043
 
4.7%
5 3818
 
4.5%
4 3796
 
4.4%
7 3607
 
4.2%
6 3603
 
4.2%
8 3128
 
3.7%
Other values (33) 6326
 
7.4%
Hangul
ValueCountFrequency (%)
도 10237
 
8.5%
기 10073
 
8.4%
경 10052
 
8.3%
시 9753
 
8.1%
동 8818
 
7.3%
안 4510
 
3.7%
구 4330
 
3.6%
산 3699
 
3.1%
지 2930
 
2.4%
양 2656
 
2.2%
Other values (444) 53389
44.3%
Arrows
ValueCountFrequency (%)
→ 1
100.0%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct8529
Distinct (%)85.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.441518
Minimum36.914
Maximum38.194513
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T08:56:40.865223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.914
5-th percentile37.01299
Q137.314032
median37.387497
Q337.621867
95-th percentile37.856249
Maximum38.194513
Range1.2805134
Interquartile range (IQR)0.30783568

Descriptive statistics

Standard deviation0.23256742
Coefficient of variation (CV)0.006211485
Kurtosis-0.17013012
Mean37.441518
Median Absolute Deviation (MAD)0.090989965
Skewness0.31589757
Sum374415.18
Variance0.054087607
MonotonicityNot monotonic
2024-03-13T08:56:41.031005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.544177 28
 
0.3%
37.392293 19
 
0.2%
37.32507331 17
 
0.2%
37.29961696 13
 
0.1%
37.3330736 13
 
0.1%
37.519389 13
 
0.1%
37.3412445 11
 
0.1%
37.390734 9
 
0.1%
37.32049003 9
 
0.1%
37.32627348 8
 
0.1%
Other values (8519) 9860
98.6%
ValueCountFrequency (%)
36.914 1
< 0.1%
36.915 1
< 0.1%
36.9153 1
< 0.1%
36.918 1
< 0.1%
36.9183 1
< 0.1%
36.9203 1
< 0.1%
36.9293 1
< 0.1%
36.934 1
< 0.1%
36.9349 1
< 0.1%
36.9353 1
< 0.1%
ValueCountFrequency (%)
38.19451337 1
< 0.1%
38.18549638 1
< 0.1%
38.18276922 1
< 0.1%
38.17804124 1
< 0.1%
38.1528279074 1
< 0.1%
38.13481183 1
< 0.1%
38.13376713 1
< 0.1%
38.12919448 1
< 0.1%
38.10690341 1
< 0.1%
38.10546202 1
< 0.1%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct8545
Distinct (%)85.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.98909
Minimum126.36632
Maximum127.75286
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T08:56:41.139663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.36632
5-th percentile126.71765
Q1126.84743
median126.95348
Q3127.1152
95-th percentile127.3376
Maximum127.75286
Range1.38655
Interquartile range (IQR)0.2677777

Descriptive statistics

Standard deviation0.19892823
Coefficient of variation (CV)0.0015664986
Kurtosis0.45561684
Mean126.98909
Median Absolute Deviation (MAD)0.12885895
Skewness0.62440405
Sum1269890.9
Variance0.039572439
MonotonicityNot monotonic
2024-03-13T08:56:41.243842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.584442 28
 
0.3%
126.958038 19
 
0.2%
126.8099722 17
 
0.2%
126.7955405 13
 
0.1%
127.455865 13
 
0.1%
126.862762 13
 
0.1%
126.8209669 11
 
0.1%
126.8572248 9
 
0.1%
126.933815 9
 
0.1%
126.8258812 8
 
0.1%
Other values (8535) 9860
98.6%
ValueCountFrequency (%)
126.366315 1
< 0.1%
126.5015 1
< 0.1%
126.5027 1
< 0.1%
126.5031 1
< 0.1%
126.504 1
< 0.1%
126.5042 1
< 0.1%
126.5260509 1
< 0.1%
126.5288208 1
< 0.1%
126.529751 1
< 0.1%
126.5323576 1
< 0.1%
ValueCountFrequency (%)
127.752865 4
< 0.1%
127.752241 6
0.1%
127.7511801 1
 
< 0.1%
127.749438 1
 
< 0.1%
127.702966 4
< 0.1%
127.6905592 1
 
< 0.1%
127.6778663 1
 
< 0.1%
127.672821 1
 
< 0.1%
127.671635 2
 
< 0.1%
127.6669094 1
 
< 0.1%

연계방식
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3
9711 
1
 
250
2
 
39

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 9711
97.1%
1 250
 
2.5%
2 39
 
0.4%

Length

2024-03-13T08:56:41.341170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T08:56:41.413695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 9711
97.1%
1 250
 
2.5%
2 39
 
0.4%

경찰연계유무
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
False
8735 
True
1265 
ValueCountFrequency (%)
False 8735
87.4%
True 1265
 
12.7%
2024-03-13T08:56:41.476276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

경비업체연계유무
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
False
9984 
True
 
16
ValueCountFrequency (%)
False 9984
99.8%
True 16
 
0.2%
2024-03-13T08:56:41.534434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

관리사무소연계유무
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
False
7913 
True
2087 
ValueCountFrequency (%)
False 7913
79.1%
True 2087
 
20.9%
2024-03-13T08:56:41.592635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

부가기능
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
CCTV
3908 
<NA>
2292 
경보등 + 경보음 + CCTV
1134 
경보등+경보음+CCTV
844 
X
475 
Other values (10)
1347 

Length

Max length16
Median length4
Mean length6.0851
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경보등 + 경보음 + CCTV
2nd rowCCTV
3rd rowCCTV
4th row경보등+경보음+CCTV
5th row경보등+경보음+CCTV

Common Values

ValueCountFrequency (%)
CCTV 3908
39.1%
<NA> 2292
22.9%
경보등 + 경보음 + CCTV 1134
 
11.3%
경보등+경보음+CCTV 844
 
8.4%
X 475
 
4.8%
경보등 472
 
4.7%
경고등+경보음 232
 
2.3%
경보등+경보음 217
 
2.2%
계도방송 171
 
1.7%
경광등+경보음 127
 
1.3%
Other values (5) 128
 
1.3%

Length

2024-03-13T08:56:41.703550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
cctv 5042
34.1%
2383
16.1%
na 2292
15.5%
경보등 1689
 
11.4%
경보음 1221
 
8.3%
경보등+경보음+cctv 844
 
5.7%
x 475
 
3.2%
경고등+경보음 232
 
1.6%
경보등+경보음 217
 
1.5%
계도방송 171
 
1.2%
Other values (5) 200
 
1.4%

안전비상벨설치년도
Real number (ℝ)

Distinct18
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2015.9468
Minimum2005
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T08:56:41.799813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2005
5-th percentile2010
Q12013
median2016
Q32019
95-th percentile2021
Maximum2023
Range18
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.7443253
Coefficient of variation (CV)0.0018573532
Kurtosis-0.86360466
Mean2015.9468
Median Absolute Deviation (MAD)3
Skewness-0.1931777
Sum20159468
Variance14.019972
MonotonicityNot monotonic
2024-03-13T08:56:41.904528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
2013 1203
12.0%
2016 1143
11.4%
2019 1098
11.0%
2017 1056
10.6%
2021 893
8.9%
2018 759
7.6%
2010 753
7.5%
2015 552
 
5.5%
2014 491
 
4.9%
2020 479
 
4.8%
Other values (8) 1573
15.7%
ValueCountFrequency (%)
2005 2
 
< 0.1%
2007 11
 
0.1%
2008 115
 
1.1%
2009 262
 
2.6%
2010 753
7.5%
2011 400
 
4.0%
2012 314
 
3.1%
2013 1203
12.0%
2014 491
4.9%
2015 552
5.5%
ValueCountFrequency (%)
2023 197
 
2.0%
2022 272
 
2.7%
2021 893
8.9%
2020 479
4.8%
2019 1098
11.0%
2018 759
7.6%
2017 1056
10.6%
2016 1143
11.4%
2015 552
5.5%
2014 491
4.9%

최종점검일자
Date

Distinct54
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-01-22 00:00:00
Maximum2024-01-02 00:00:00
2024-03-13T08:56:42.013517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:56:42.155815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

최종점검결과구분
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
True
9990 
False
 
10
ValueCountFrequency (%)
True 9990
99.9%
False 10
 
0.1%
2024-03-13T08:56:42.247455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

관리기관명
Text

Distinct88
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-13T08:56:42.396646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length17
Mean length6.9565
Min length3

Characters and Unicode

Total characters69565
Distinct characters170
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)0.4%

Sample

1st row성남시청
2nd row안산시 도시정보센터
3rd row평택시청
4th row군포시청
5th row김포시
ValueCountFrequency (%)
안산시 2387
15.9%
도시정보센터 2387
15.9%
경기도 1329
 
8.8%
평택시청 882
 
5.9%
파주시청 831
 
5.5%
안양시 743
 
4.9%
스마트도시정보과 743
 
4.9%
광주시청 694
 
4.6%
성남시청 693
 
4.6%
양주시청 471
 
3.1%
Other values (98) 3865
25.7%
2024-03-13T08:56:42.682805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 12893
18.5%
청 5848
 
8.4%
5025
 
7.2%
도 4606
 
6.6%
안 3490
 
5.0%
보 3334
 
4.8%
정 3272
 
4.7%
산 2731
 
3.9%
센 2539
 
3.6%
터 2537
 
3.6%
Other values (160) 23290
33.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 64505
92.7%
Space Separator 5025
 
7.2%
Uppercase Letter 11
 
< 0.1%
Other Punctuation 10
 
< 0.1%
Decimal Number 6
 
< 0.1%
Open Punctuation 3
 
< 0.1%
Close Punctuation 3
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 12893
20.0%
청 5848
 
9.1%
도 4606
 
7.1%
안 3490
 
5.4%
보 3334
 
5.2%
정 3272
 
5.1%
산 2731
 
4.2%
센 2539
 
3.9%
터 2537
 
3.9%
주 2489
 
3.9%
Other values (140) 20766
32.2%
Uppercase Letter
ValueCountFrequency (%)
N 1
9.1%
G 1
9.1%
P 1
9.1%
L 1
9.1%
K 1
9.1%
A 1
9.1%
T 1
9.1%
O 1
9.1%
W 1
9.1%
E 1
9.1%
Decimal Number
ValueCountFrequency (%)
1 4
66.7%
0 1
 
16.7%
2 1
 
16.7%
Lowercase Letter
ValueCountFrequency (%)
t 1
50.0%
k 1
50.0%
Space Separator
ValueCountFrequency (%)
5025
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 64505
92.7%
Common 5047
 
7.3%
Latin 13
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 12893
20.0%
청 5848
 
9.1%
도 4606
 
7.1%
안 3490
 
5.4%
보 3334
 
5.2%
정 3272
 
5.1%
산 2731
 
4.2%
센 2539
 
3.9%
터 2537
 
3.9%
주 2489
 
3.9%
Other values (140) 20766
32.2%
Latin
ValueCountFrequency (%)
N 1
 
7.7%
t 1
 
7.7%
G 1
 
7.7%
k 1
 
7.7%
P 1
 
7.7%
L 1
 
7.7%
K 1
 
7.7%
A 1
 
7.7%
T 1
 
7.7%
O 1
 
7.7%
Other values (3) 3
23.1%
Common
ValueCountFrequency (%)
5025
99.6%
/ 10
 
0.2%
1 4
 
0.1%
( 3
 
0.1%
) 3
 
0.1%
0 1
 
< 0.1%
2 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 64505
92.7%
ASCII 5060
 
7.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 12893
20.0%
청 5848
 
9.1%
도 4606
 
7.1%
안 3490
 
5.4%
보 3334
 
5.2%
정 3272
 
5.1%
산 2731
 
4.2%
센 2539
 
3.9%
터 2537
 
3.9%
주 2489
 
3.9%
Other values (140) 20766
32.2%
ASCII
ValueCountFrequency (%)
5025
99.3%
/ 10
 
0.2%
1 4
 
0.1%
( 3
 
0.1%
) 3
 
0.1%
N 1
 
< 0.1%
t 1
 
< 0.1%
G 1
 
< 0.1%
k 1
 
< 0.1%
0 1
 
< 0.1%
Other values (10) 10
 
0.2%

관리기관전화번호
Text

Distinct102
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-13T08:56:42.841669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.2245
Min length11

Characters and Unicode

Total characters122245
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)0.5%

Sample

1st row031-729-4562
2nd row031-481-3896
3rd row031-8024-5295
4th row031-390-0820
5th row031-980-5612
ValueCountFrequency (%)
031-481-3896 1915
19.1%
031-8024-5295 882
 
8.8%
031-940-8794 830
 
8.3%
031-760-0081 694
 
6.9%
031-729-4562 693
 
6.9%
031-8045-5007 595
 
5.9%
031-481-2823 472
 
4.7%
031-590-4302 462
 
4.6%
031-8082-4502 386
 
3.9%
031-390-0820 366
 
3.7%
Other values (92) 2705
27.1%
2024-03-13T08:56:43.126719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 21225
17.4%
- 20000
16.4%
3 14426
11.8%
1 14035
11.5%
8 11167
9.1%
2 9414
7.7%
4 9175
7.5%
9 7575
 
6.2%
5 6017
 
4.9%
6 5102
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 102245
83.6%
Dash Punctuation 20000
 
16.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 21225
20.8%
3 14426
14.1%
1 14035
13.7%
8 11167
10.9%
2 9414
9.2%
4 9175
9.0%
9 7575
 
7.4%
5 6017
 
5.9%
6 5102
 
5.0%
7 4109
 
4.0%
Dash Punctuation
ValueCountFrequency (%)
- 20000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 122245
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 21225
17.4%
- 20000
16.4%
3 14426
11.8%
1 14035
11.5%
8 11167
9.1%
2 9414
7.7%
4 9175
7.5%
9 7575
 
6.2%
5 6017
 
4.9%
6 5102
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 122245
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 21225
17.4%
- 20000
16.4%
3 14426
11.8%
1 14035
11.5%
8 11167
9.1%
2 9414
7.7%
4 9175
7.5%
9 7575
 
6.2%
5 6017
 
4.9%
6 5102
 
4.2%

데이터기준일자
Categorical

HIGH CORRELATION 

Distinct28
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2022-12-08
2517 
2022-05-30
882 
2024-03-05
831 
2023-12-29
743 
2018-04-26
709 
Other values (23)
4318 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2018-04-26
2nd row2022-12-08
3rd row2022-05-30
4th row2022-04-18
5th row2019-05-09

Common Values

ValueCountFrequency (%)
2022-12-08 2517
25.2%
2022-05-30 882
 
8.8%
2024-03-05 831
 
8.3%
2023-12-29 743
 
7.4%
2018-04-26 709
 
7.1%
2023-09-30 694
 
6.9%
2020-05-07 475
 
4.8%
2020-01-28 462
 
4.6%
2022-04-18 366
 
3.7%
2023-02-13 352
 
3.5%
Other values (18) 1969
19.7%

Length

2024-03-13T08:56:43.247468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2022-12-08 2517
25.2%
2022-05-30 882
 
8.8%
2024-03-05 831
 
8.3%
2023-12-29 743
 
7.4%
2018-04-26 709
 
7.1%
2023-09-30 694
 
6.9%
2020-05-07 475
 
4.8%
2020-01-28 462
 
4.6%
2022-04-18 366
 
3.7%
2023-02-13 352
 
3.5%
Other values (18) 1969
19.7%

Interactions

2024-03-13T08:56:37.023300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:56:36.039613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:56:36.353587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:56:36.700476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:56:37.097481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:56:36.113566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:56:36.423836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:56:36.776474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:56:37.175296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:56:36.186279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:56:36.509465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:56:36.860711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:56:37.256577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:56:36.270966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:56:36.613783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:56:36.938925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T08:56:43.316139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치목적설치장소유형위도경도연계방식경찰연계유무경비업체연계유무관리사무소연계유무부가기능안전비상벨설치년도최종점검일자최종점검결과구분관리기관명데이터기준일자
설치목적1.0000.0820.2560.2500.7020.0290.1500.0050.6800.2440.9750.0000.8400.776
설치장소유형0.0821.0000.5080.6940.0870.0090.0410.1490.7770.2610.9900.0360.9520.944
위도0.2560.5081.0000.6850.3550.4360.1430.6340.7340.3660.9400.1160.9470.934
경도0.2500.6940.6851.0000.2480.4400.0910.7250.7470.3390.9170.0730.9270.912
연계방식0.7020.0870.3550.2481.0000.0520.4070.0500.8230.2890.9600.0000.9550.818
경찰연계유무0.0290.0090.4360.4400.0521.0000.0090.1380.9460.2470.9980.0001.0000.982
경비업체연계유무0.1500.0410.1430.0910.4070.0091.0000.0230.3390.0791.0000.0001.0000.436
관리사무소연계유무0.0050.1490.6340.7250.0500.1380.0231.0000.7600.2371.0000.0891.0001.000
부가기능0.6800.7770.7340.7470.8230.9460.3390.7601.0000.6420.9920.0980.9840.949
안전비상벨설치년도0.2440.2610.3660.3390.2890.2470.0790.2370.6421.0000.7800.0680.7350.697
최종점검일자0.9750.9900.9400.9170.9600.9981.0001.0000.9920.7801.0000.1140.9960.999
최종점검결과구분0.0000.0360.1160.0730.0000.0000.0000.0890.0980.0680.1141.0000.0870.129
관리기관명0.8400.9520.9470.9270.9551.0001.0001.0000.9840.7350.9960.0871.0001.000
데이터기준일자0.7760.9440.9340.9120.8180.9820.4361.0000.9490.6970.9990.1291.0001.000
2024-03-13T08:56:43.642854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리사무소연계유무부가기능최종점검결과구분경찰연계유무연계방식경비업체연계유무설치목적데이터기준일자
관리사무소연계유무1.0000.6110.0570.0880.0840.0140.0080.996
부가기능0.6111.0000.0760.8120.6810.2650.4970.719
최종점검결과구분0.0570.0761.0000.0000.0000.0000.0000.102
경찰연계유무0.0880.8120.0001.0000.0870.0060.0490.898
연계방식0.0840.6810.0000.0871.0000.6400.3580.621
경비업체연계유무0.0140.2650.0000.0060.6401.0000.2480.346
설치목적0.0080.4970.0000.0490.3580.2481.0000.566
데이터기준일자0.9960.7190.1020.8980.6210.3460.5661.000
2024-03-13T08:56:43.746029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치장소유형위도경도안전비상벨설치년도설치목적연계방식경찰연계유무경비업체연계유무관리사무소연계유무부가기능최종점검결과구분데이터기준일자
설치장소유형1.000-0.020-0.396-0.0610.1370.1440.0060.0260.0950.6260.0230.828
위도-0.0201.0000.0960.0630.1580.2280.3350.1090.4920.4060.0890.693
경도-0.3960.0961.0000.0160.1540.1520.3380.0690.5670.4200.0560.635
안전비상벨설치년도-0.0610.0630.0161.0000.1100.1320.2490.0780.2360.3170.0670.325
설치목적0.1370.1580.1540.1101.0000.3580.0490.2480.0080.4970.0000.566
연계방식0.1440.2280.1520.1320.3581.0000.0870.6400.0840.6810.0000.621
경찰연계유무0.0060.3350.3380.2490.0490.0871.0000.0060.0880.8120.0000.898
경비업체연계유무0.0260.1090.0690.0780.2480.6400.0061.0000.0140.2650.0000.346
관리사무소연계유무0.0950.4920.5670.2360.0080.0840.0880.0141.0000.6110.0570.996
부가기능0.6260.4060.4200.3170.4970.6810.8120.2650.6111.0000.0760.719
최종점검결과구분0.0230.0890.0560.0670.0000.0000.0000.0000.0570.0761.0000.102
데이터기준일자0.8280.6930.6350.3250.5660.6210.8980.3460.9960.7190.1021.000

Missing values

2024-03-13T08:56:37.393316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T08:56:37.786513image/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

안전비상벨관리번호설치목적설치장소유형설치위치소재지도로명주소소재지지번주소위도경도연계방식경찰연계유무경비업체연계유무관리사무소연계유무부가기능안전비상벨설치년도최종점검일자최종점검결과구분관리기관명관리기관전화번호데이터기준일자
5186수정양지-A-615.경기도 성남시 수정구 산성대로527번길 8 (양지동)경기도 성남시 수정구 양지동 27037.458438127.1634233NNY경보등 + 경보음 + CCTV20132018-05-10Y성남시청031-729-45622018-04-26
9375PV-0061199신길동 1368-50경기도 안산시 단원구 신길동 1368-50경기도 안산시 단원구 신길동 1368-5037.336144126.7717483NNNCCTV20102020-12-31Y안산시 도시정보센터031-481-38962022-12-08
175261536415청와삼대 맞은편<NA>경기도 평택시 죽백동 131-237.0116127.13523NNNCCTV20192022-05-30Y평택시청031-8024-52952022-05-30
2431대야동 002199시티그린빌경기도 군포시 대야2로 93경기도 군포시 대야미동 634-1번지 씨티빌37.333851126.9148683YNN경보등+경보음+CCTV20122022-04-15Y군포시청031-390-08202022-04-18
3325김포-A-448199경기도 김포시 구래동 638-2 (솔터마을 자연앤힐스테이트아파트 503동 육교위)<NA>경기도 김포시 구래동 638-2 (솔터마을 자연앤힐스테이트아파트 503동 육교위)37.638499126.63173YNY경보등+경보음+CCTV20152019-05-09Y김포시031-980-56122019-05-09
788경안-A-051199이슬람성원앞<NA>경기도 광주시 역동 49-1037.405802127.2574563NNNCCTV20162023-09-30Y광주시청031-760-00812023-09-30
6456CP-0050199본오동 764경기도 안산시 상록구 각골로2안길 18경기도 안산시 상록구 본오동 76437.295877126.8747423NNNCCTV20102020-12-31Y안산시 도시정보센터031-481-38962022-12-08
16663비상벨-1374호199경기도 파주시<NA>경기도 파주시 금촌동 120-537.754636126.7755263NNY<NA>20192024-01-02Y경기도 파주시청031-940-87942024-03-05
16357비상벨-0512호199경기도 파주시<NA>경기도 파주시 문산읍 문산리 148-3037.856448126.7794383NNY<NA>20212024-01-02Y경기도 파주시청031-940-87942024-03-05
12786198199옥정중심상업지구-2경기도 양주시 옥정로 214경기도 양주시 옥정동 963-737.820691127.092123NNNX20192020-05-01Y양주시청031-8082-66172020-05-07
안전비상벨관리번호설치목적설치장소유형설치위치소재지도로명주소소재지지번주소위도경도연계방식경찰연계유무경비업체연계유무관리사무소연계유무부가기능안전비상벨설치년도최종점검일자최종점검결과구분관리기관명관리기관전화번호데이터기준일자
14163미산-0215동이리평화<NA>경기도 연천군 미산면 동이리 23-138.021186127.0161553NNN<NA>20172022-04-04Y연천군 안전총괄과031-839-23302024-02-26
9404PV-19311199본오동 879-4경기도 안산시 상록구 샘골서길 64경기도 안산시 상록구 본오동 879-437.299617126.8627623NNNCCTV20192020-12-31Y안산시 도시정보센터031-481-38962022-12-08
10951ACT-003199성곡동 829경기도 안산시 단원구 성곡동 829경기도 안산시 단원구 성곡동 82937.308648126.726783NNNCCTV20152020-12-31Y안산시 도시정보센터031-481-38962022-12-08
26비상벨-089199북한강강변길<NA>경기도 가평군 청평면 청평리 82637.727104127.409233NNN<NA>20222023-03-31Y경기도 가평군청031-580-25712024-01-16
194055585711장안면 수촌리 1470-1경기도 화성시 장안면 장안공단2길 26-17경기도 화성시 장안면 수촌리 1470-1번지37.105478126.8484661YNN<NA>20172020-04-13Y화성시 공원관리과031-5189-66262020-04-13
4029스쿨존-2011-0315주곡초교<NA>경기도 남양주시 진접읍 금곡리 1127-4237.724187127.2066663NNN<NA>20112019-12-01Y남양주시청031-590-43022020-01-28
18828방43415미사 R6 미사강변한강로 412 주변 사거리경기도 하남시 덕풍동 911경기도 하남시 덕풍동 91137.555912127.2058513NNN경보등 + 경보음 + CCTV20182023-02-13Y하남시청031-790-64002023-02-13
112892140412공인중개사 앞경기도 안양시 동안구 엘에스로 47경기도 안양시 동안구 호계동 706-1번지37.368071126.9544953NNN<NA>20102022-11-30Y안양시 스마트도시정보과031-8045-50072023-12-29
3709스쿨존-2010-1415송촌초교<NA>경기도 남양주시 조안면 송촌리 69237.567062127.318123NNN<NA>20112019-12-01Y남양주시청031-590-43022020-01-28
4758CCTV관제센터 1962137호 어린이공원경기도 동두천시 강변로850번길 84경기도 동두천시 동두천동 555-537.938426127.0526843NNYCCTV20142021-02-01Y동두천시청 공보전산과031-860-28312021-02-24

Duplicate rows

Most frequently occurring

안전비상벨관리번호설치목적설치장소유형설치위치소재지도로명주소소재지지번주소위도경도연계방식경찰연계유무경비업체연계유무관리사무소연계유무부가기능안전비상벨설치년도최종점검일자최종점검결과구분관리기관명관리기관전화번호데이터기준일자# duplicates
0112광덕공원경기도 안산시 단원구 예술대학로 176경기도 안산시 단원구 고잔동 64137.332141126.8401263YNN경광등+경보음20162020-12-04Y안산시청031-481-22442022-12-082
1122여자화장실 내부경기도 의정부시 호국로1346번길 41경기도 의정부시 의정부동 28-2번지37.742804127.053723YNN경광등 + 이상음원감지20172018-07-31Y의정부시031-828-29832020-04-062
210312상록수 스포츠존<NA>경기도 안산시 상록구 본오3동 876-6(상록수역 4번 출구 광장)37.303124126.8655233YNN경광등+경보음20202020-12-04Y안산시청031-481-22442022-12-082
310812나무자연학습장 관리사경기도 안산시 상록구 성호로 285경기도 안산시 상록구 부곡동 709번지 (나무)자연학습장관리사37.328646126.8586683YNN경광등+경보음20202020-12-04Y안산시청031-481-22442022-12-082
411012농수산물도매시장 관리동 1층경기도 안산시 상록구 충장로 312경기도 안산시 상록구 이동 528번지 안산시농수산물도매시장37.308316126.8561553YNN경광등+경보음20212021-10-14Y안산시청031-481-22442022-12-082
511812대부도 산림욕장<NA>경기도 안산시 단원구 대부북동 산 191-137.253311126.5814633YNN경광등+경보음20212021-10-14Y안산시청031-481-22442022-12-082
611912한대앞역 광장 공중화장실(헌혈의 집 앞)<NA>경기도 안산시 상록구 이동 622-1037.309145126.85283YNN경광등+경보음20212021-12-23Y안산시청031-481-22442022-12-082
712312청소년수련관 야외화장실(노적봉화장실)경기도 안산시 상록구 삼일로 696경기도 안산시 상록구 성포동 59537.326273126.8532933YNN이상음원감지기+경광등20222022-05-10Y안산시청031-481-22442022-12-082
81712용하공원경기도 안산시 상록구 용하공원로 44경기도 안산시 상록구 사동 1535-137.305499126.8554453YNN경광등+경보음20172020-12-04Y안산시청031-481-22442022-12-082
91822여자화장실 내부경기도 의정부시 평화로 104-24경기도 의정부시 호원동 144-5번지37.70015127.0479743YNN경광등 + 이상음원감지20172018-07-31Y의정부시031-828-29832020-04-062