Overview

Dataset statistics

Number of variables13
Number of observations489
Missing cells4
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory51.2 KiB
Average record size in memory107.3 B

Variable types

Text3
Categorical4
Boolean4
Numeric1
DateTime1

Dataset

Description충청남도 안전베싱벨위치 정보로 안전비상벨관리번호, 설치목적, 설치장소유형, 설치위치, 소재지지번주소, 경찰연계 유뮤 등의 현황을 제공합니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=30&beforeMenuCd=DOM_000000201001001000&publicdatapk=15118736

Alerts

경비업체연계유무 has constant value ""Constant
최종점검결과구분 has constant value ""Constant
관리사무소연계유무 is highly overall correlated with 설치장소유형 and 3 other fieldsHigh correlation
관리기관전화번호 is highly overall correlated with 설치목적 and 4 other fieldsHigh correlation
경찰연계유무 is highly overall correlated with 설치장소유형 and 3 other fieldsHigh correlation
관리기관명 is highly overall correlated with 설치목적 and 4 other fieldsHigh correlation
안전비상벨설치년도 is highly overall correlated with 설치목적High correlation
설치목적 is highly overall correlated with 안전비상벨설치년도 and 2 other fieldsHigh correlation
설치장소유형 is highly overall correlated with 경찰연계유무 and 3 other fieldsHigh correlation

Reproduction

Analysis started2024-01-09 22:44:37.070006
Analysis finished2024-01-09 22:44:37.938927
Duration0.87 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

안전비상벨관리번호
Text

Distinct433
Distinct (%)88.5%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2024-01-10T07:44:38.107269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length7.6400818
Min length1

Characters and Unicode

Total characters3736
Distinct characters182
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique396 ?
Unique (%)81.0%

Sample

1st rowE04S001-09
2nd rowE04S002-09
3rd rowE04C005-16
4th rowE04C090-16
5th rowW30C084-16
ValueCountFrequency (%)
c-01 6
 
1.2%
b-02 4
 
0.8%
10 3
 
0.6%
c-02 3
 
0.6%
2 3
 
0.6%
8 3
 
0.6%
5 3
 
0.6%
6 3
 
0.6%
7 3
 
0.6%
9 3
 
0.6%
Other values (421) 455
93.0%
2024-01-10T07:44:38.465181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 670
17.9%
1 486
13.0%
2 385
10.3%
- 273
 
7.3%
7 220
 
5.9%
3 191
 
5.1%
6 184
 
4.9%
9 158
 
4.2%
8 146
 
3.9%
4 138
 
3.7%
Other values (172) 885
23.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2673
71.5%
Other Letter 550
 
14.7%
Dash Punctuation 273
 
7.3%
Uppercase Letter 228
 
6.1%
Lowercase Letter 12
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
방 95
 
17.3%
마 16
 
2.9%
을 16
 
2.9%
리 16
 
2.9%
거 12
 
2.2%
입 11
 
2.0%
진 10
 
1.8%
삼 9
 
1.6%
장 9
 
1.6%
부 8
 
1.5%
Other values (152) 348
63.3%
Decimal Number
ValueCountFrequency (%)
0 670
25.1%
1 486
18.2%
2 385
14.4%
7 220
 
8.2%
3 191
 
7.1%
6 184
 
6.9%
9 158
 
5.9%
8 146
 
5.5%
4 138
 
5.2%
5 95
 
3.6%
Uppercase Letter
ValueCountFrequency (%)
W 92
40.4%
C 58
25.4%
S 26
 
11.4%
A 24
 
10.5%
P 19
 
8.3%
E 8
 
3.5%
B 1
 
0.4%
Lowercase Letter
ValueCountFrequency (%)
c 7
58.3%
b 5
41.7%
Dash Punctuation
ValueCountFrequency (%)
- 273
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2946
78.9%
Hangul 550
 
14.7%
Latin 240
 
6.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
방 95
 
17.3%
마 16
 
2.9%
을 16
 
2.9%
리 16
 
2.9%
거 12
 
2.2%
입 11
 
2.0%
진 10
 
1.8%
삼 9
 
1.6%
장 9
 
1.6%
부 8
 
1.5%
Other values (152) 348
63.3%
Common
ValueCountFrequency (%)
0 670
22.7%
1 486
16.5%
2 385
13.1%
- 273
9.3%
7 220
 
7.5%
3 191
 
6.5%
6 184
 
6.2%
9 158
 
5.4%
8 146
 
5.0%
4 138
 
4.7%
Latin
ValueCountFrequency (%)
W 92
38.3%
C 58
24.2%
S 26
 
10.8%
A 24
 
10.0%
P 19
 
7.9%
E 8
 
3.3%
c 7
 
2.9%
b 5
 
2.1%
B 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3186
85.3%
Hangul 550
 
14.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 670
21.0%
1 486
15.3%
2 385
12.1%
- 273
8.6%
7 220
 
6.9%
3 191
 
6.0%
6 184
 
5.8%
9 158
 
5.0%
8 146
 
4.6%
4 138
 
4.3%
Other values (10) 335
10.5%
Hangul
ValueCountFrequency (%)
방 95
 
17.3%
마 16
 
2.9%
을 16
 
2.9%
리 16
 
2.9%
거 12
 
2.2%
입 11
 
2.0%
진 10
 
1.8%
삼 9
 
1.6%
장 9
 
1.6%
부 8
 
1.5%
Other values (152) 348
63.3%

설치목적
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
1
393 
2
96 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 393
80.4%
2 96
 
19.6%

Length

2024-01-10T07:44:38.572310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:44:38.646024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 393
80.4%
2 96
 
19.6%

설치장소유형
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2
193 
5
182 
99
58 
1
56 

Length

Max length2
Median length1
Mean length1.1186094
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5
2nd row5
3rd row5
4th row5
5th row5

Common Values

ValueCountFrequency (%)
2 193
39.5%
5 182
37.2%
99 58
 
11.9%
1 56
 
11.5%

Length

2024-01-10T07:44:38.727589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:44:38.827110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 193
39.5%
5 182
37.2%
99 58
 
11.9%
1 56
 
11.5%

설치위치
Text

Distinct256
Distinct (%)52.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2024-01-10T07:44:39.083551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length7.3701431
Min length2

Characters and Unicode

Total characters3604
Distinct characters290
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique251 ?
Unique (%)51.3%

Sample

1st row북면
2nd row북면
3rd row북면
4th row북면
5th row부성2동
ValueCountFrequency (%)
방범 100
 
13.4%
cctv 100
 
13.4%
부성2동 60
 
8.1%
공중화장실 45
 
6.0%
부성1동 32
 
4.3%
화장실 27
 
3.6%
대천해수욕장 19
 
2.6%
무창포해수욕장 11
 
1.5%
11
 
1.5%
북면 8
 
1.1%
Other values (284) 331
44.5%
2024-01-10T07:44:39.456832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
255
 
7.1%
C 200
 
5.5%
장 175
 
4.9%
공 135
 
3.7%
동 107
 
3.0%
성 103
 
2.9%
방 101
 
2.8%
범 101
 
2.8%
T 100
 
2.8%
V 100
 
2.8%
Other values (280) 2227
61.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2618
72.6%
Uppercase Letter 403
 
11.2%
Space Separator 255
 
7.1%
Decimal Number 166
 
4.6%
Close Punctuation 75
 
2.1%
Open Punctuation 75
 
2.1%
Dash Punctuation 11
 
0.3%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 175
 
6.7%
공 135
 
5.2%
동 107
 
4.1%
성 103
 
3.9%
방 101
 
3.9%
범 101
 
3.9%
화 99
 
3.8%
부 98
 
3.7%
실 90
 
3.4%
원 88
 
3.4%
Other values (259) 1521
58.1%
Decimal Number
ValueCountFrequency (%)
2 80
48.2%
1 58
34.9%
3 6
 
3.6%
4 5
 
3.0%
5 4
 
2.4%
8 3
 
1.8%
0 3
 
1.8%
7 3
 
1.8%
9 2
 
1.2%
6 2
 
1.2%
Uppercase Letter
ValueCountFrequency (%)
C 200
49.6%
T 100
24.8%
V 100
24.8%
S 1
 
0.2%
L 1
 
0.2%
G 1
 
0.2%
Space Separator
ValueCountFrequency (%)
255
100.0%
Close Punctuation
ValueCountFrequency (%)
) 75
100.0%
Open Punctuation
ValueCountFrequency (%)
( 75
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2618
72.6%
Common 583
 
16.2%
Latin 403
 
11.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 175
 
6.7%
공 135
 
5.2%
동 107
 
4.1%
성 103
 
3.9%
방 101
 
3.9%
범 101
 
3.9%
화 99
 
3.8%
부 98
 
3.7%
실 90
 
3.4%
원 88
 
3.4%
Other values (259) 1521
58.1%
Common
ValueCountFrequency (%)
255
43.7%
2 80
 
13.7%
) 75
 
12.9%
( 75
 
12.9%
1 58
 
9.9%
- 11
 
1.9%
3 6
 
1.0%
4 5
 
0.9%
5 4
 
0.7%
8 3
 
0.5%
Other values (5) 11
 
1.9%
Latin
ValueCountFrequency (%)
C 200
49.6%
T 100
24.8%
V 100
24.8%
S 1
 
0.2%
L 1
 
0.2%
G 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2617
72.6%
ASCII 986
 
27.4%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
255
25.9%
C 200
20.3%
T 100
 
10.1%
V 100
 
10.1%
2 80
 
8.1%
) 75
 
7.6%
( 75
 
7.6%
1 58
 
5.9%
- 11
 
1.1%
3 6
 
0.6%
Other values (11) 26
 
2.6%
Hangul
ValueCountFrequency (%)
장 175
 
6.7%
공 135
 
5.2%
동 107
 
4.1%
성 103
 
3.9%
방 101
 
3.9%
범 101
 
3.9%
화 99
 
3.8%
부 98
 
3.7%
실 90
 
3.4%
원 88
 
3.4%
Other values (258) 1520
58.1%
Compat Jamo
ValueCountFrequency (%)
ㄱ 1
100.0%

소재지지번주소
Text

Distinct452
Distinct (%)93.2%
Missing4
Missing (%)0.8%
Memory size3.9 KiB
2024-01-10T07:44:39.674742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length24
Mean length20.321649
Min length14

Characters and Unicode

Total characters9856
Distinct characters169
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

Unique431 ?
Unique (%)88.9%

Sample

1st row충청남도 천안시 동남구 북면 오곡리 360
2nd row충청남도 천안시 동남구 북면 용암리 36-1
3rd row충청남도 천안시 동남구 북면 은지리 181
4th row충청남도 천안시 동남구 북면 대평리 497-5
5th row충청남도 천안시 서북구 차암동 523
ValueCountFrequency (%)
충청남도 485
21.2%
서산시 100
 
4.4%
천안시 100
 
4.4%
논산시 96
 
4.2%
서북구 92
 
4.0%
두정동 60
 
2.6%
당진시 45
 
2.0%
태안군 38
 
1.7%
보령시 37
 
1.6%
아산시 30
 
1.3%
Other values (676) 1206
52.7%
2024-01-10T07:44:40.001570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1804
18.3%
남 508
 
5.2%
도 500
 
5.1%
청 490
 
5.0%
충 485
 
4.9%
시 439
 
4.5%
1 387
 
3.9%
산 325
 
3.3%
- 298
 
3.0%
동 279
 
2.8%
Other values (159) 4341
44.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5867
59.5%
Decimal Number 1885
 
19.1%
Space Separator 1804
 
18.3%
Dash Punctuation 298
 
3.0%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 508
 
8.7%
도 500
 
8.5%
청 490
 
8.4%
충 485
 
8.3%
시 439
 
7.5%
산 325
 
5.5%
동 279
 
4.8%
리 238
 
4.1%
서 194
 
3.3%
면 171
 
2.9%
Other values (145) 2238
38.1%
Decimal Number
ValueCountFrequency (%)
1 387
20.5%
2 260
13.8%
3 204
10.8%
4 173
9.2%
6 164
8.7%
5 156
8.3%
7 143
 
7.6%
8 136
 
7.2%
9 132
 
7.0%
0 130
 
6.9%
Space Separator
ValueCountFrequency (%)
1804
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 298
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5867
59.5%
Common 3989
40.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 508
 
8.7%
도 500
 
8.5%
청 490
 
8.4%
충 485
 
8.3%
시 439
 
7.5%
산 325
 
5.5%
동 279
 
4.8%
리 238
 
4.1%
서 194
 
3.3%
면 171
 
2.9%
Other values (145) 2238
38.1%
Common
ValueCountFrequency (%)
1804
45.2%
1 387
 
9.7%
- 298
 
7.5%
2 260
 
6.5%
3 204
 
5.1%
4 173
 
4.3%
6 164
 
4.1%
5 156
 
3.9%
7 143
 
3.6%
8 136
 
3.4%
Other values (4) 264
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5867
59.5%
ASCII 3989
40.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1804
45.2%
1 387
 
9.7%
- 298
 
7.5%
2 260
 
6.5%
3 204
 
5.1%
4 173
 
4.3%
6 164
 
4.1%
5 156
 
3.9%
7 143
 
3.6%
8 136
 
3.4%
Other values (4) 264
 
6.6%
Hangul
ValueCountFrequency (%)
남 508
 
8.7%
도 500
 
8.5%
청 490
 
8.4%
충 485
 
8.3%
시 439
 
7.5%
산 325
 
5.5%
동 279
 
4.8%
리 238
 
4.1%
서 194
 
3.3%
면 171
 
2.9%
Other values (145) 2238
38.1%

경찰연계유무
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size621.0 B
True
267 
False
222 
ValueCountFrequency (%)
True 267
54.6%
False 222
45.4%
2024-01-10T07:44:40.095932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

경비업체연계유무
Boolean

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size621.0 B
False
489 
ValueCountFrequency (%)
False 489
100.0%
2024-01-10T07:44:40.157314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

관리사무소연계유무
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size621.0 B
False
389 
True
100 
ValueCountFrequency (%)
False 389
79.6%
True 100
 
20.4%
2024-01-10T07:44:40.226277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

안전비상벨설치년도
Real number (ℝ)

HIGH CORRELATION 

Distinct11
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2016.7362
Minimum2010
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2024-01-10T07:44:40.326753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2010
5-th percentile2014
Q12016
median2017
Q32018
95-th percentile2018
Maximum2020
Range10
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.4869441
Coefficient of variation (CV)0.00073730223
Kurtosis4.8577081
Mean2016.7362
Median Absolute Deviation (MAD)1
Skewness-1.6323106
Sum986184
Variance2.2110027
MonotonicityNot monotonic
2024-01-10T07:44:40.437532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
2017 189
38.7%
2018 113
23.1%
2016 110
22.5%
2014 23
 
4.7%
2019 19
 
3.9%
2015 14
 
2.9%
2010 5
 
1.0%
2012 5
 
1.0%
2020 5
 
1.0%
2013 4
 
0.8%
ValueCountFrequency (%)
2010 5
 
1.0%
2011 2
 
0.4%
2012 5
 
1.0%
2013 4
 
0.8%
2014 23
 
4.7%
2015 14
 
2.9%
2016 110
22.5%
2017 189
38.7%
2018 113
23.1%
2019 19
 
3.9%
ValueCountFrequency (%)
2020 5
 
1.0%
2019 19
 
3.9%
2018 113
23.1%
2017 189
38.7%
2016 110
22.5%
2015 14
 
2.9%
2014 23
 
4.7%
2013 4
 
0.8%
2012 5
 
1.0%
2011 2
 
0.4%

최종점검일자
Date

Distinct10
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
Minimum2017-04-27 00:00:00
Maximum2020-10-20 00:00:00
2024-01-10T07:44:40.541741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:44:40.633982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)

최종점검결과구분
Boolean

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size621.0 B
True
489 
ValueCountFrequency (%)
True 489
100.0%
2024-01-10T07:44:40.714991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

관리기관명
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
천안시 안전총괄과
100 
충청남도 서산시청
100 
충청남도 논산시청
96 
당진시청
45 
충청남도 태안군청
38 
Other values (12)
110 

Length

Max length12
Median length9
Mean length8.4826176
Min length3

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row천안시 안전총괄과
2nd row천안시 안전총괄과
3rd row천안시 안전총괄과
4th row천안시 안전총괄과
5th row천안시 안전총괄과

Common Values

ValueCountFrequency (%)
천안시 안전총괄과 100
20.4%
충청남도 서산시청 100
20.4%
충청남도 논산시청 96
19.6%
당진시청 45
9.2%
충청남도 태안군청 38
 
7.8%
보령시청 환경보호과 37
 
7.6%
아산시 환경보전과 30
 
6.1%
금산군 14
 
2.9%
공주시청 문화재과 8
 
1.6%
공주시청 환경자원과 5
 
1.0%
Other values (7) 16
 
3.3%

Length

2024-01-10T07:44:40.790465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
충청남도 234
25.5%
천안시 100
10.9%
서산시청 100
10.9%
안전총괄과 100
10.9%
논산시청 96
10.5%
당진시청 45
 
4.9%
태안군청 38
 
4.1%
보령시청 37
 
4.0%
환경보호과 37
 
4.0%
아산시 30
 
3.3%
Other values (13) 100
10.9%

관리기관전화번호
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
041-521-5587
100 
041-660-3170
100 
041-746-6462
96 
041-350-3303
45 
041-670-2721
38 
Other values (13)
110 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row041-521-5587
2nd row041-521-5587
3rd row041-521-5587
4th row041-521-5587
5th row041-521-5587

Common Values

ValueCountFrequency (%)
041-521-5587 100
20.4%
041-660-3170 100
20.4%
041-746-6462 96
19.6%
041-350-3303 45
9.2%
041-670-2721 38
 
7.8%
041-930-3681 37
 
7.6%
041-540-2348 30
 
6.1%
041-750-2532 14
 
2.9%
041-840-8385 5
 
1.0%
041-840-8530 5
 
1.0%
Other values (8) 19
 
3.9%

Length

2024-01-10T07:44:40.881432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
041-521-5587 100
20.4%
041-660-3170 100
20.4%
041-746-6462 96
19.6%
041-350-3303 45
9.2%
041-670-2721 38
 
7.8%
041-930-3681 37
 
7.6%
041-540-2348 30
 
6.1%
041-750-2532 14
 
2.9%
041-840-8530 5
 
1.0%
041-840-8385 5
 
1.0%
Other values (8) 19
 
3.9%

Interactions

2024-01-10T07:44:37.648107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T07:44:40.950777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치목적설치장소유형경찰연계유무관리사무소연계유무안전비상벨설치년도최종점검일자관리기관명관리기관전화번호
설치목적1.0000.3400.6420.3680.6590.9560.8620.943
설치장소유형0.3401.0000.7900.8560.6700.8990.9130.918
경찰연계유무0.6420.7901.0000.7600.5460.9980.9650.998
관리사무소연계유무0.3680.8560.7601.0000.4861.0001.0001.000
안전비상벨설치년도0.6590.6700.5460.4861.0000.8380.7280.732
최종점검일자0.9560.8990.9981.0000.8381.0000.9870.989
관리기관명0.8620.9130.9651.0000.7280.9871.0001.000
관리기관전화번호0.9430.9180.9981.0000.7320.9891.0001.000
2024-01-10T07:44:41.288437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리사무소연계유무관리기관전화번호설치장소유형경찰연계유무관리기관명설치목적
관리사무소연계유무1.0000.9830.6540.5500.9840.240
관리기관전화번호0.9831.0000.7650.9480.9990.804
설치장소유형0.6540.7651.0000.5800.7660.226
경찰연계유무0.5500.9480.5801.0000.9490.444
관리기관명0.9840.9990.7660.9491.0000.805
설치목적0.2400.8040.2260.4440.8051.000
2024-01-10T07:44:41.375652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
안전비상벨설치년도설치목적설치장소유형경찰연계유무관리사무소연계유무관리기관명관리기관전화번호
안전비상벨설치년도1.0000.5200.4730.4260.3740.3890.387
설치목적0.5201.0000.2260.4440.2400.8050.804
설치장소유형0.4730.2261.0000.5800.6540.7660.765
경찰연계유무0.4260.4440.5801.0000.5500.9490.948
관리사무소연계유무0.3740.2400.6540.5501.0000.9840.983
관리기관명0.3890.8050.7660.9490.9841.0000.999
관리기관전화번호0.3870.8040.7650.9480.9830.9991.000

Missing values

2024-01-10T07:44:37.745020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T07:44:37.882267image/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

안전비상벨관리번호설치목적설치장소유형설치위치소재지지번주소경찰연계유무경비업체연계유무관리사무소연계유무안전비상벨설치년도최종점검일자최종점검결과구분관리기관명관리기관전화번호
0E04S001-0925북면충청남도 천안시 동남구 북면 오곡리 360YNN20142020-10-20Y천안시 안전총괄과041-521-5587
1E04S002-0925북면충청남도 천안시 동남구 북면 용암리 36-1YNN20142020-10-20Y천안시 안전총괄과041-521-5587
2E04C005-1615북면충청남도 천안시 동남구 북면 은지리 181YNN20162020-10-20Y천안시 안전총괄과041-521-5587
3E04C090-1615북면충청남도 천안시 동남구 북면 대평리 497-5YNN20162020-10-20Y천안시 안전총괄과041-521-5587
4W30C084-1615부성2동충청남도 천안시 서북구 차암동 523YNN20162020-10-20Y천안시 안전총괄과041-521-5587
5W30P021-1621부성2동충청남도 천안시 서북구 차암동 495YNN20162020-10-20Y천안시 안전총괄과041-521-5587
6W30S006-1625부성2동충청남도 천안시 서북구 두정동 526-1YNN20162020-10-20Y천안시 안전총괄과041-521-5587
7W30S009-1625부성2동충청남도 천안시 서북구 차암동 254YNN20162020-10-20Y천안시 안전총괄과041-521-5587
8W30P032-1621부성2동충청남도 천안시 서북구 차암동 547YNN20142020-10-20Y천안시 안전총괄과041-521-5587
9W30P033-1621부성2동충청남도 천안시 서북구 차암동 547YNN20142020-10-20Y천안시 안전총괄과041-521-5587
안전비상벨관리번호설치목적설치장소유형설치위치소재지지번주소경찰연계유무경비업체연계유무관리사무소연계유무안전비상벨설치년도최종점검일자최종점검결과구분관리기관명관리기관전화번호
479070-8064-965112외암리민속마을 반석교 화장실충청남도 아산시 송악면 외암리 595-106YNN20182018-06-22Y아산시 환경보전과041-540-2348
480070-8064-965212외암리민속마을 주차장충청남도 아산시 송악면 역촌리 66YNN20182018-06-22Y아산시 환경보전과041-540-2348
481070-8064-965312외암리민속마을 저잣거리 입구충청남도 아산시 송악면 역촌리 77YNN20182018-06-22Y아산시 환경보전과041-540-2348
482070-8064-965412외암리민속마을 저잣거리 내부충청남도 아산시 송악면 역촌리 77YNN20182018-06-22Y아산시 환경보전과041-540-2348
483070-8064-965512남산 보광사 입구충청남도 아산시 방축동 118-2YNN20182018-06-22Y아산시 환경보전과041-540-2348
484070-8064-965612솔바람 화장실충청남도 아산시 송악면 강당리 297-1YNN20182018-06-22Y아산시 환경보전과041-540-2348
485070-8064-965712여울목(강당골주차장)충청남도 아산시 송악면 강당리 300YNN20182018-06-22Y아산시 환경보전과041-540-2348
486070-8064-965812용곡공원충청남도 아산시 배방읍 장재리 1201YNN20182018-06-22Y아산시 환경보전과041-540-2348
487070-8064-965912지산공원1충청남도 아산시 배방읍 장재리 1197YNN20182018-06-22Y아산시 환경보전과041-540-2348
488070-8064-966012지산공원2충청남도 아산시 배방읍 장재리 1343YNN20182018-06-22Y아산시 환경보전과041-540-2348