Overview

Dataset statistics

Number of variables51
Number of observations806
Missing cells6889
Missing cells (%)16.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory344.9 KiB
Average record size in memory438.2 B

Variable types

Categorical20
Numeric23
Text5
Boolean2
DateTime1

Dataset

Description2019년 기준부터 2021년까지 울산광역시 대형화재의 재난 일시, 재난 장소, 재난대상물, 화재원인 정보 데이터
Author울산광역시
URLhttps://www.data.go.kr/data/15109124/fileData.do

Alerts

재난시명 has constant value ""Constant
지하 여부 has constant value ""Constant
화학사고여부 has constant value ""Constant
주용도명 is highly imbalanced (75.5%)Imbalance
다중이용업여부 is highly imbalanced (98.6%)Imbalance
건물구조식 is highly imbalanced (65.5%)Imbalance
건물구조즙 is highly imbalanced (74.9%)Imbalance
지하층수 is highly imbalanced (82.5%)Imbalance
발화열원 분류명 is highly imbalanced (61.0%)Imbalance
발화사유 대분류명 is highly imbalanced (62.2%)Imbalance
화재발생요일 is highly imbalanced (52.8%)Imbalance
인명피해합계수 is highly imbalanced (94.1%)Imbalance
풍향 is highly imbalanced (55.5%)Imbalance
재난리명 has 439 (54.5%) missing valuesMissing
도로명 has 95 (11.8%) missing valuesMissing
읍면동순번 has 90 (11.2%) missing valuesMissing
대상물명 has 676 (83.9%) missing valuesMissing
화재발생일자 has 621 (77.0%) missing valuesMissing
초진월 has 621 (77.0%) missing valuesMissing
초진일 has 621 (77.0%) missing valuesMissing
초진시 has 621 (77.0%) missing valuesMissing
초진분 has 621 (77.0%) missing valuesMissing
완진월 has 621 (77.0%) missing valuesMissing
완진일 has 621 (77.0%) missing valuesMissing
완진시 has 621 (77.0%) missing valuesMissing
완진분 has 621 (77.0%) missing valuesMissing
신고시 has 25 (3.1%) zerosZeros
신고분 has 20 (2.5%) zerosZeros
상황종료시 has 31 (3.8%) zerosZeros
상황종료분 has 25 (3.1%) zerosZeros
건물구조동수 has 712 (88.3%) zerosZeros
지상층수 has 620 (76.9%) zerosZeros
그을음면적 has 761 (94.4%) zerosZeros
초진시 has 9 (1.1%) zerosZeros
완진시 has 9 (1.1%) zerosZeros
소실면적 has 766 (95.0%) zerosZeros
온도 has 632 (78.4%) zerosZeros
습도 has 632 (78.4%) zerosZeros

Reproduction

Analysis started2024-03-14 13:44:55.281221
Analysis finished2024-03-14 13:44:56.630325
Duration1.35 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

접수경로명
Categorical

Distinct6
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
일반전화
460 
이동전화
198 
IP전화
88 
사후각지
 
29
기타
 
16

Length

Max length6
Median length4
Mean length3.9975186
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row이동전화
2nd row이동전화
3rd row이동전화
4th row이동전화
5th row기타

Common Values

ValueCountFrequency (%)
일반전화 460
57.1%
이동전화 198
24.6%
IP전화 88
 
10.9%
사후각지 29
 
3.6%
기타 16
 
2.0%
모바일앱신고 15
 
1.9%

Length

2024-03-14T22:44:56.857414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T22:44:57.222757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반전화 460
57.1%
이동전화 198
24.6%
ip전화 88
 
10.9%
사후각지 29
 
3.6%
기타 16
 
2.0%
모바일앱신고 15
 
1.9%

신고연도
Categorical

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
2021
662 
2020
78 
2019
 
66

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019
2nd row2019
3rd row2019
4th row2019
5th row2019

Common Values

ValueCountFrequency (%)
2021 662
82.1%
2020 78
 
9.7%
2019 66
 
8.2%

Length

2024-03-14T22:44:57.591000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T22:44:57.843810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 662
82.1%
2020 78
 
9.7%
2019 66
 
8.2%

신고월
Real number (ℝ)

Distinct12
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.0471464
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2024-03-14T22:44:58.178920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q16
median7
Q38
95-th percentile11
Maximum12
Range11
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.4454822
Coefficient of variation (CV)0.34701737
Kurtosis0.083933359
Mean7.0471464
Median Absolute Deviation (MAD)1
Skewness-0.11299553
Sum5680
Variance5.9803832
MonotonicityNot monotonic
2024-03-14T22:44:58.557829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
7 152
18.9%
8 132
16.4%
6 131
16.3%
5 109
13.5%
9 60
 
7.4%
10 55
 
6.8%
11 43
 
5.3%
12 36
 
4.5%
4 35
 
4.3%
1 23
 
2.9%
Other values (2) 30
 
3.7%
ValueCountFrequency (%)
1 23
 
2.9%
2 19
 
2.4%
3 11
 
1.4%
4 35
 
4.3%
5 109
13.5%
6 131
16.3%
7 152
18.9%
8 132
16.4%
9 60
 
7.4%
10 55
 
6.8%
ValueCountFrequency (%)
12 36
 
4.5%
11 43
 
5.3%
10 55
 
6.8%
9 60
 
7.4%
8 132
16.4%
7 152
18.9%
6 131
16.3%
5 109
13.5%
4 35
 
4.3%
3 11
 
1.4%

신고일
Real number (ℝ)

Distinct31
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.219603
Minimum1
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2024-03-14T22:44:59.161254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q18
median15
Q323
95-th percentile29
Maximum31
Range30
Interquartile range (IQR)15

Descriptive statistics

Standard deviation8.732045
Coefficient of variation (CV)0.57373671
Kurtosis-1.1846987
Mean15.219603
Median Absolute Deviation (MAD)8
Skewness0.10181481
Sum12267
Variance76.248609
MonotonicityNot monotonic
2024-03-14T22:44:59.709406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
16 38
 
4.7%
4 37
 
4.6%
10 34
 
4.2%
7 32
 
4.0%
12 31
 
3.8%
24 31
 
3.8%
22 31
 
3.8%
5 30
 
3.7%
8 30
 
3.7%
15 30
 
3.7%
Other values (21) 482
59.8%
ValueCountFrequency (%)
1 25
3.1%
2 26
3.2%
3 23
2.9%
4 37
4.6%
5 30
3.7%
6 26
3.2%
7 32
4.0%
8 30
3.7%
9 26
3.2%
10 34
4.2%
ValueCountFrequency (%)
31 11
 
1.4%
30 27
3.3%
29 21
2.6%
28 28
3.5%
27 24
3.0%
26 15
1.9%
25 25
3.1%
24 31
3.8%
23 25
3.1%
22 31
3.8%

신고시
Real number (ℝ)

ZEROS 

Distinct24
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.847395
Minimum0
Maximum23
Zeros25
Zeros (%)3.1%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2024-03-14T22:45:00.296836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q17
median12
Q317
95-th percentile22
Maximum23
Range23
Interquartile range (IQR)10

Descriptive statistics

Standard deviation6.3173064
Coefficient of variation (CV)0.53322326
Kurtosis-0.89189526
Mean11.847395
Median Absolute Deviation (MAD)5
Skewness-0.049692957
Sum9549
Variance39.90836
MonotonicityNot monotonic
2024-03-14T22:45:00.709809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
11 53
 
6.6%
14 52
 
6.5%
9 45
 
5.6%
10 44
 
5.5%
12 42
 
5.2%
15 40
 
5.0%
13 37
 
4.6%
8 37
 
4.6%
7 37
 
4.6%
16 35
 
4.3%
Other values (14) 384
47.6%
ValueCountFrequency (%)
0 25
3.1%
1 28
3.5%
2 24
3.0%
3 17
 
2.1%
4 25
3.1%
5 28
3.5%
6 29
3.6%
7 37
4.6%
8 37
4.6%
9 45
5.6%
ValueCountFrequency (%)
23 31
3.8%
22 27
3.3%
21 30
3.7%
20 31
3.8%
19 28
3.5%
18 26
3.2%
17 35
4.3%
16 35
4.3%
15 40
5.0%
14 52
6.5%

신고분
Real number (ℝ)

ZEROS 

Distinct60
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.179901
Minimum0
Maximum59
Zeros20
Zeros (%)2.5%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2024-03-14T22:45:01.294847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q113
median30
Q344
95-th percentile56
Maximum59
Range59
Interquartile range (IQR)31

Descriptive statistics

Standard deviation17.612069
Coefficient of variation (CV)0.60356851
Kurtosis-1.2409298
Mean29.179901
Median Absolute Deviation (MAD)15
Skewness-0.052091876
Sum23519
Variance310.18499
MonotonicityNot monotonic
2024-03-14T22:45:01.938959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
44 22
 
2.7%
12 21
 
2.6%
1 20
 
2.5%
0 20
 
2.5%
57 19
 
2.4%
41 18
 
2.2%
50 18
 
2.2%
4 18
 
2.2%
36 17
 
2.1%
31 17
 
2.1%
Other values (50) 616
76.4%
ValueCountFrequency (%)
0 20
2.5%
1 20
2.5%
2 10
1.2%
3 16
2.0%
4 18
2.2%
5 14
1.7%
6 17
2.1%
7 12
1.5%
8 7
 
0.9%
9 14
1.7%
ValueCountFrequency (%)
59 12
1.5%
58 7
 
0.9%
57 19
2.4%
56 7
 
0.9%
55 15
1.9%
54 12
1.5%
53 11
1.4%
52 14
1.7%
51 16
2.0%
50 18
2.2%

재난시명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
울산광역시
806 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
울산광역시 806
100.0%

Length

2024-03-14T22:45:02.207153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T22:45:02.521047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
울산광역시 806
100.0%

재난구명
Categorical

Distinct5
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
울주군
367 
북구
223 
남구
144 
중구
59 
동구
 
13

Length

Max length3
Median length2
Mean length2.455335
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row북구
2nd row울주군
3rd row울주군
4th row울주군
5th row남구

Common Values

ValueCountFrequency (%)
울주군 367
45.5%
북구 223
27.7%
남구 144
 
17.9%
중구 59
 
7.3%
동구 13
 
1.6%

Length

2024-03-14T22:45:02.782473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T22:45:02.979761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
울주군 367
45.5%
북구 223
27.7%
남구 144
 
17.9%
중구 59
 
7.3%
동구 13
 
1.6%

재난동명
Text

Distinct57
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
2024-03-14T22:45:03.609704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.9975186
Min length2

Characters and Unicode

Total characters2416
Distinct characters66
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)1.2%

Sample

1st row시례동
2nd row온산읍
3rd row언양읍
4th row온양읍
5th row성암동
ValueCountFrequency (%)
온산읍 120
 
14.9%
중산동 60
 
7.4%
매곡동 55
 
6.8%
웅촌면 48
 
6.0%
언양읍 38
 
4.7%
상북면 38
 
4.7%
효문동 38
 
4.7%
연암동 34
 
4.2%
옥교동 33
 
4.1%
청량읍 28
 
3.5%
Other values (47) 314
39.0%
2024-03-14T22:45:04.488498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 463
19.2%
읍 218
 
9.0%
산 190
 
7.9%
면 149
 
6.2%
온 140
 
5.8%
매 75
 
3.1%
암 68
 
2.8%
곡 63
 
2.6%
중 60
 
2.5%
양 59
 
2.4%
Other values (56) 931
38.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2416
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 463
19.2%
읍 218
 
9.0%
산 190
 
7.9%
면 149
 
6.2%
온 140
 
5.8%
매 75
 
3.1%
암 68
 
2.8%
곡 63
 
2.6%
중 60
 
2.5%
양 59
 
2.4%
Other values (56) 931
38.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2416
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 463
19.2%
읍 218
 
9.0%
산 190
 
7.9%
면 149
 
6.2%
온 140
 
5.8%
매 75
 
3.1%
암 68
 
2.8%
곡 63
 
2.6%
중 60
 
2.5%
양 59
 
2.4%
Other values (56) 931
38.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2416
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 463
19.2%
읍 218
 
9.0%
산 190
 
7.9%
면 149
 
6.2%
온 140
 
5.8%
매 75
 
3.1%
암 68
 
2.8%
곡 63
 
2.6%
중 60
 
2.5%
양 59
 
2.4%
Other values (56) 931
38.5%

재난리명
Text

MISSING 

Distinct55
Distinct (%)15.0%
Missing439
Missing (%)54.5%
Memory size6.4 KiB
2024-03-14T22:45:05.254420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9373297
Min length2

Characters and Unicode

Total characters1078
Distinct characters65
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)3.8%

Sample

1st row원산리
2nd row반송리
3rd row동상리
4th row원산리
5th row교동리
ValueCountFrequency (%)
처용리 32
 
8.7%
고연리 32
 
8.7%
원산리 24
 
6.5%
용암리 23
 
6.3%
거리 22
 
6.0%
반천리 21
 
5.7%
화산리 19
 
5.2%
남부리 14
 
3.8%
학남리 13
 
3.5%
덕신리 13
 
3.5%
Other values (45) 154
42.0%
2024-03-14T22:45:06.277662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 367
34.0%
용 55
 
5.1%
천 51
 
4.7%
산 46
 
4.3%
고 33
 
3.1%
대 32
 
3.0%
처 32
 
3.0%
연 32
 
3.0%
남 31
 
2.9%
암 24
 
2.2%
Other values (55) 375
34.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1078
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 367
34.0%
용 55
 
5.1%
천 51
 
4.7%
산 46
 
4.3%
고 33
 
3.1%
대 32
 
3.0%
처 32
 
3.0%
연 32
 
3.0%
남 31
 
2.9%
암 24
 
2.2%
Other values (55) 375
34.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1078
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 367
34.0%
용 55
 
5.1%
천 51
 
4.7%
산 46
 
4.3%
고 33
 
3.1%
대 32
 
3.0%
처 32
 
3.0%
연 32
 
3.0%
남 31
 
2.9%
암 24
 
2.2%
Other values (55) 375
34.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1078
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 367
34.0%
용 55
 
5.1%
천 51
 
4.7%
산 46
 
4.3%
고 33
 
3.1%
대 32
 
3.0%
처 32
 
3.0%
연 32
 
3.0%
남 31
 
2.9%
암 24
 
2.2%
Other values (55) 375
34.8%

상황종료연도
Categorical

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
2021
662 
2020
78 
2019
 
66

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019
2nd row2019
3rd row2019
4th row2019
5th row2019

Common Values

ValueCountFrequency (%)
2021 662
82.1%
2020 78
 
9.7%
2019 66
 
8.2%

Length

2024-03-14T22:45:06.512589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T22:45:06.834358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 662
82.1%
2020 78
 
9.7%
2019 66
 
8.2%

상황종료월
Real number (ℝ)

Distinct12
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.0483871
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2024-03-14T22:45:07.161101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q16
median7
Q38
95-th percentile11
Maximum12
Range11
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.4441877
Coefficient of variation (CV)0.34677262
Kurtosis0.088317492
Mean7.0483871
Median Absolute Deviation (MAD)1
Skewness-0.11302046
Sum5681
Variance5.9740533
MonotonicityNot monotonic
2024-03-14T22:45:07.528239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
7 152
18.9%
8 132
16.4%
6 131
16.3%
5 110
13.6%
9 60
 
7.4%
10 55
 
6.8%
11 43
 
5.3%
12 36
 
4.5%
4 34
 
4.2%
1 23
 
2.9%
Other values (2) 30
 
3.7%
ValueCountFrequency (%)
1 23
 
2.9%
2 19
 
2.4%
3 11
 
1.4%
4 34
 
4.2%
5 110
13.6%
6 131
16.3%
7 152
18.9%
8 132
16.4%
9 60
 
7.4%
10 55
 
6.8%
ValueCountFrequency (%)
12 36
 
4.5%
11 43
 
5.3%
10 55
 
6.8%
9 60
 
7.4%
8 132
16.4%
7 152
18.9%
6 131
16.3%
5 110
13.6%
4 34
 
4.2%
3 11
 
1.4%

상황종료일
Real number (ℝ)

Distinct31
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.236973
Minimum1
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2024-03-14T22:45:08.100373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q18
median15
Q323
95-th percentile29
Maximum31
Range30
Interquartile range (IQR)15

Descriptive statistics

Standard deviation8.7209136
Coefficient of variation (CV)0.57235211
Kurtosis-1.1867243
Mean15.236973
Median Absolute Deviation (MAD)7.5
Skewness0.099494942
Sum12281
Variance76.054333
MonotonicityNot monotonic
2024-03-14T22:45:08.514593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
16 38
 
4.7%
4 37
 
4.6%
10 34
 
4.2%
8 33
 
4.1%
24 32
 
4.0%
12 32
 
4.0%
5 32
 
4.0%
22 31
 
3.8%
28 30
 
3.7%
7 29
 
3.6%
Other values (21) 478
59.3%
ValueCountFrequency (%)
1 24
3.0%
2 26
3.2%
3 23
2.9%
4 37
4.6%
5 32
4.0%
6 25
3.1%
7 29
3.6%
8 33
4.1%
9 25
3.1%
10 34
4.2%
ValueCountFrequency (%)
31 11
 
1.4%
30 26
3.2%
29 21
2.6%
28 30
3.7%
27 22
2.7%
26 15
1.9%
25 27
3.3%
24 32
4.0%
23 23
2.9%
22 31
3.8%

상황종료시
Real number (ℝ)

ZEROS 

Distinct24
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.94665
Minimum0
Maximum23
Zeros31
Zeros (%)3.8%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2024-03-14T22:45:08.892653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q18
median12
Q317
95-th percentile22
Maximum23
Range23
Interquartile range (IQR)9

Descriptive statistics

Standard deviation6.3179431
Coefficient of variation (CV)0.52884642
Kurtosis-0.87553576
Mean11.94665
Median Absolute Deviation (MAD)5
Skewness-0.14052744
Sum9629
Variance39.916405
MonotonicityNot monotonic
2024-03-14T22:45:09.269297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
15 54
 
6.7%
12 46
 
5.7%
11 46
 
5.7%
10 45
 
5.6%
16 45
 
5.6%
8 43
 
5.3%
13 40
 
5.0%
14 40
 
5.0%
17 39
 
4.8%
9 38
 
4.7%
Other values (14) 370
45.9%
ValueCountFrequency (%)
0 31
3.8%
1 26
3.2%
2 21
2.6%
3 22
2.7%
4 23
2.9%
5 29
3.6%
6 18
2.2%
7 31
3.8%
8 43
5.3%
9 38
4.7%
ValueCountFrequency (%)
23 24
3.0%
22 32
4.0%
21 29
3.6%
20 28
3.5%
19 33
4.1%
18 23
2.9%
17 39
4.8%
16 45
5.6%
15 54
6.7%
14 40
5.0%

상황종료분
Real number (ℝ)

ZEROS 

Distinct60
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.008685
Minimum0
Maximum59
Zeros25
Zeros (%)3.1%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2024-03-14T22:45:09.648678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q114
median29
Q344
95-th percentile57
Maximum59
Range59
Interquartile range (IQR)30

Descriptive statistics

Standard deviation17.342618
Coefficient of variation (CV)0.59784225
Kurtosis-1.1672488
Mean29.008685
Median Absolute Deviation (MAD)15
Skewness0.038116723
Sum23381
Variance300.76638
MonotonicityNot monotonic
2024-03-14T22:45:10.093074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 25
 
3.1%
11 22
 
2.7%
34 21
 
2.6%
32 19
 
2.4%
29 18
 
2.2%
21 17
 
2.1%
10 17
 
2.1%
16 17
 
2.1%
17 17
 
2.1%
2 17
 
2.1%
Other values (50) 616
76.4%
ValueCountFrequency (%)
0 25
3.1%
1 9
 
1.1%
2 17
2.1%
3 10
 
1.2%
4 13
1.6%
5 10
 
1.2%
6 11
1.4%
7 7
 
0.9%
8 14
1.7%
9 17
2.1%
ValueCountFrequency (%)
59 17
2.1%
58 14
1.7%
57 11
1.4%
56 7
0.9%
55 15
1.9%
54 15
1.9%
53 13
1.6%
52 14
1.7%
51 16
2.0%
50 7
0.9%

관할서명
Categorical

Distinct6
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
온산소방서
232 
북부소방서
222 
남부소방서
143 
중부소방서
119 
울주소방서
76 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row북부소방서
2nd row온산소방서
3rd row중부소방서
4th row온산소방서
5th row남부소방서

Common Values

ValueCountFrequency (%)
온산소방서 232
28.8%
북부소방서 222
27.5%
남부소방서 143
17.7%
중부소방서 119
14.8%
울주소방서 76
 
9.4%
동부소방서 14
 
1.7%

Length

2024-03-14T22:45:10.508915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T22:45:10.840125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
온산소방서 232
28.8%
북부소방서 222
27.5%
남부소방서 143
17.7%
중부소방서 119
14.8%
울주소방서 76
 
9.4%
동부소방서 14
 
1.7%

관할센터명
Categorical

Distinct24
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
매곡119안전센터
123 
언양119안전센터
101 
화산119안전센터
92 
웅촌119안전센터
59 
온산119안전센터
57 
Other values (19)
374 

Length

Max length10
Median length9
Mean length9.0471464
Min length9

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row농소119안전센터
2nd row화산119안전센터
3rd row범서119안전센터
4th row온양119안전센터
5th row공단119안전센터

Common Values

ValueCountFrequency (%)
매곡119안전센터 123
15.3%
언양119안전센터 101
12.5%
화산119안전센터 92
11.4%
웅촌119안전센터 59
 
7.3%
온산119안전센터 57
 
7.1%
공단119안전센터 54
 
6.7%
송정119안전센터 44
 
5.5%
염포119안전센터 44
 
5.5%
성남119안전센터 42
 
5.2%
장생포119안전센터 38
 
4.7%
Other values (14) 152
18.9%

Length

2024-03-14T22:45:11.249510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
매곡119안전센터 123
15.3%
언양119안전센터 101
12.5%
화산119안전센터 92
11.4%
웅촌119안전센터 59
 
7.3%
온산119안전센터 57
 
7.1%
공단119안전센터 54
 
6.7%
송정119안전센터 44
 
5.5%
염포119안전센터 44
 
5.5%
성남119안전센터 42
 
5.2%
장생포119안전센터 38
 
4.7%
Other values (14) 152
18.9%

도로명
Text

MISSING 

Distinct209
Distinct (%)29.4%
Missing95
Missing (%)11.8%
Memory size6.4 KiB
2024-03-14T22:45:12.270958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length4.9353024
Min length3

Characters and Unicode

Total characters3509
Distinct characters166
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

Unique96 ?
Unique (%)13.5%

Sample

1st row화산로
2nd row상서길
3rd row처용로487번길
4th row삼산로
5th row여천로
ValueCountFrequency (%)
모듈화산업로 33
 
4.6%
중앙시장길 28
 
3.9%
처용산업3길 25
 
3.5%
중산산업2길 23
 
3.2%
길천산업로 21
 
3.0%
반천산업로 18
 
2.5%
매곡산업1길 17
 
2.4%
장터1길 14
 
2.0%
중산산업3길 12
 
1.7%
매곡산업6길 10
 
1.4%
Other values (199) 510
71.7%
2024-03-14T22:45:13.753439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
길 422
 
12.0%
로 383
 
10.9%
산 358
 
10.2%
업 268
 
7.6%
1 123
 
3.5%
중 88
 
2.5%
용 86
 
2.5%
3 81
 
2.3%
2 71
 
2.0%
장 70
 
2.0%
Other values (156) 1559
44.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3065
87.3%
Decimal Number 444
 
12.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
길 422
 
13.8%
로 383
 
12.5%
산 358
 
11.7%
업 268
 
8.7%
중 88
 
2.9%
용 86
 
2.8%
장 70
 
2.3%
번 70
 
2.3%
처 69
 
2.3%
천 62
 
2.0%
Other values (146) 1189
38.8%
Decimal Number
ValueCountFrequency (%)
1 123
27.7%
3 81
18.2%
2 71
16.0%
4 52
11.7%
7 28
 
6.3%
5 27
 
6.1%
6 23
 
5.2%
8 18
 
4.1%
0 13
 
2.9%
9 8
 
1.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3065
87.3%
Common 444
 
12.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
길 422
 
13.8%
로 383
 
12.5%
산 358
 
11.7%
업 268
 
8.7%
중 88
 
2.9%
용 86
 
2.8%
장 70
 
2.3%
번 70
 
2.3%
처 69
 
2.3%
천 62
 
2.0%
Other values (146) 1189
38.8%
Common
ValueCountFrequency (%)
1 123
27.7%
3 81
18.2%
2 71
16.0%
4 52
11.7%
7 28
 
6.3%
5 27
 
6.1%
6 23
 
5.2%
8 18
 
4.1%
0 13
 
2.9%
9 8
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3065
87.3%
ASCII 444
 
12.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
길 422
 
13.8%
로 383
 
12.5%
산 358
 
11.7%
업 268
 
8.7%
중 88
 
2.9%
용 86
 
2.8%
장 70
 
2.3%
번 70
 
2.3%
처 69
 
2.3%
천 62
 
2.0%
Other values (146) 1189
38.8%
ASCII
ValueCountFrequency (%)
1 123
27.7%
3 81
18.2%
2 71
16.0%
4 52
11.7%
7 28
 
6.3%
5 27
 
6.1%
6 23
 
5.2%
8 18
 
4.1%
0 13
 
2.9%
9 8
 
1.8%

읍면동순번
Real number (ℝ)

MISSING 

Distinct8
Distinct (%)1.1%
Missing90
Missing (%)11.2%
Infinite0
Infinite (%)0.0%
Mean1.3351955
Minimum0
Maximum7
Zeros2
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2024-03-14T22:45:14.104905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q31
95-th percentile3
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.84749988
Coefficient of variation (CV)0.6347384
Kurtosis13.588825
Mean1.3351955
Median Absolute Deviation (MAD)0
Skewness3.3376597
Sum956
Variance0.71825605
MonotonicityNot monotonic
2024-03-14T22:45:14.461076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 574
71.2%
2 81
 
10.0%
3 35
 
4.3%
4 13
 
1.6%
5 6
 
0.7%
7 3
 
0.4%
0 2
 
0.2%
6 2
 
0.2%
(Missing) 90
 
11.2%
ValueCountFrequency (%)
0 2
 
0.2%
1 574
71.2%
2 81
 
10.0%
3 35
 
4.3%
4 13
 
1.6%
5 6
 
0.7%
6 2
 
0.2%
7 3
 
0.4%
ValueCountFrequency (%)
7 3
 
0.4%
6 2
 
0.2%
5 6
 
0.7%
4 13
 
1.6%
3 35
 
4.3%
2 81
 
10.0%
1 574
71.2%
0 2
 
0.2%

지하 여부
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
0
806 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 806
100.0%

Length

2024-03-14T22:45:14.847731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T22:45:15.157081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 806
100.0%

화학사고여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size934.0 B
False
806 
ValueCountFrequency (%)
False 806
100.0%
2024-03-14T22:45:15.425683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

출동대센터정보
Text

Distinct438
Distinct (%)54.3%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
2024-03-14T22:45:16.176271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length214
Median length156
Mean length88.054591
Min length7

Characters and Unicode

Total characters70972
Distinct characters78
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

Unique333 ?
Unique (%)41.3%

Sample

1st row(구)항공구조구급대, 농소119안전센터, 매곡119안전센터, 병영119안전센터, 북부구조대, 북부예방안전과, 삼산119안전센터, 송정119안전센터, 신정119안전센터, 유곡119안전센터, 태화119안전센터
2nd row공단119안전센터, 남부구조대, 삼산119안전센터, 서생119지역대, 신정119안전센터, 여천119안전센터, 옥동119안전센터, 온산119안전센터, 온산예방안전과, 웅촌119안전센터, 유곡119안전센터, 장생포119안전센터, 화산119안전센터
3rd row무거119안전센터, 범서119안전센터, 삼동119지역대, 삼산119안전센터, 언양119안전센터, 웅촌119안전센터, 유곡119안전센터, 중부구조대, 중부방호구조과, 태화119안전센터
4th row공단119안전센터, 온산119안전센터, 온산구조대, 온산예방안전과, 온양119안전센터, 웅촌119안전센터, 화산119안전센터
5th row(구)특수화학구조대, 공단119안전센터, 남부구조대, 남부방호구조과, 병영119안전센터, 삼산119안전센터, 송정119안전센터, 신정119안전센터, 여천119안전센터, 염포119안전센터, 온산119안전센터, 유곡119안전센터, 장생포119안전센터, 화산119안전센터, 화암119안전센터
ValueCountFrequency (%)
119재난대응과 732
 
10.4%
삼산119안전센터 483
 
6.9%
여천119안전센터 444
 
6.3%
유곡119안전센터 409
 
5.8%
공단119안전센터 363
 
5.2%
온산119안전센터 340
 
4.8%
병영119안전센터 249
 
3.5%
송정119안전센터 243
 
3.5%
온산구조대 223
 
3.2%
화산119안전센터 219
 
3.1%
Other values (38) 3331
47.3%
2024-03-14T22:45:17.149654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 11958
16.8%
, 6230
 
8.8%
6230
 
8.8%
9 5979
 
8.4%
전 4822
 
6.8%
안 4798
 
6.8%
터 4780
 
6.7%
센 4780
 
6.7%
대 2218
 
3.1%
산 1278
 
1.8%
Other values (68) 17899
25.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 40565
57.2%
Decimal Number 17937
25.3%
Other Punctuation 6230
 
8.8%
Space Separator 6230
 
8.8%
Open Punctuation 5
 
< 0.1%
Close Punctuation 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 4822
 
11.9%
안 4798
 
11.8%
터 4780
 
11.8%
센 4780
 
11.8%
대 2218
 
5.5%
산 1278
 
3.2%
구 1043
 
2.6%
조 1038
 
2.6%
과 768
 
1.9%
재 734
 
1.8%
Other values (62) 14306
35.3%
Decimal Number
ValueCountFrequency (%)
1 11958
66.7%
9 5979
33.3%
Other Punctuation
ValueCountFrequency (%)
, 6230
100.0%
Space Separator
ValueCountFrequency (%)
6230
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 40565
57.2%
Common 30407
42.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 4822
 
11.9%
안 4798
 
11.8%
터 4780
 
11.8%
센 4780
 
11.8%
대 2218
 
5.5%
산 1278
 
3.2%
구 1043
 
2.6%
조 1038
 
2.6%
과 768
 
1.9%
재 734
 
1.8%
Other values (62) 14306
35.3%
Common
ValueCountFrequency (%)
1 11958
39.3%
, 6230
20.5%
6230
20.5%
9 5979
19.7%
( 5
 
< 0.1%
) 5
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 40565
57.2%
ASCII 30407
42.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 11958
39.3%
, 6230
20.5%
6230
20.5%
9 5979
19.7%
( 5
 
< 0.1%
) 5
 
< 0.1%
Hangul
ValueCountFrequency (%)
전 4822
 
11.9%
안 4798
 
11.8%
터 4780
 
11.8%
센 4780
 
11.8%
대 2218
 
5.5%
산 1278
 
3.2%
구 1043
 
2.6%
조 1038
 
2.6%
과 768
 
1.9%
재 734
 
1.8%
Other values (62) 14306
35.3%

대상물명
Text

MISSING 

Distinct126
Distinct (%)96.9%
Missing676
Missing (%)83.9%
Memory size6.4 KiB
2024-03-14T22:45:17.811170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length24
Mean length10.646154
Min length2

Characters and Unicode

Total characters1384
Distinct characters254
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

Unique123 ?
Unique (%)94.6%

Sample

1st row(주)TEPC
2nd row㈜효성언양공장(폐업) .
3rd row유림 ENG
4th row대상산업가스(주)
5th row수산물종합동(소매시장)
ValueCountFrequency (%)
공장 9
 
3.9%
동 4
 
1.7%
4
 
1.7%
내 4
 
1.7%
명칭 3
 
1.3%
a동 3
 
1.3%
보관소 2
 
0.9%
a동(공장동 2
 
0.9%
주)큐로 2
 
0.9%
동명칭 2
 
0.9%
Other values (189) 195
84.8%
2024-03-14T22:45:18.774745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
101
 
7.3%
( 81
 
5.9%
) 81
 
5.9%
주 53
 
3.8%
* 49
 
3.5%
장 42
 
3.0%
공 42
 
3.0%
동 39
 
2.8%
산 27
 
2.0%
이 25
 
1.8%
Other values (244) 844
61.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 989
71.5%
Space Separator 101
 
7.3%
Open Punctuation 81
 
5.9%
Close Punctuation 81
 
5.9%
Other Punctuation 62
 
4.5%
Uppercase Letter 56
 
4.0%
Dash Punctuation 6
 
0.4%
Lowercase Letter 6
 
0.4%
Math Symbol 1
 
0.1%
Other Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 53
 
5.4%
장 42
 
4.2%
공 42
 
4.2%
동 39
 
3.9%
산 27
 
2.7%
이 25
 
2.5%
업 22
 
2.2%
기 21
 
2.1%
대 20
 
2.0%
화 17
 
1.7%
Other values (214) 681
68.9%
Uppercase Letter
ValueCountFrequency (%)
C 9
16.1%
A 7
12.5%
T 6
10.7%
K 5
8.9%
H 4
7.1%
M 4
7.1%
P 4
7.1%
S 3
 
5.4%
V 3
 
5.4%
R 2
 
3.6%
Other values (6) 9
16.1%
Lowercase Letter
ValueCountFrequency (%)
s 2
33.3%
o 1
16.7%
i 1
16.7%
l 1
16.7%
g 1
16.7%
Other Punctuation
ValueCountFrequency (%)
* 49
79.0%
. 9
 
14.5%
, 4
 
6.5%
Space Separator
ValueCountFrequency (%)
101
100.0%
Open Punctuation
ValueCountFrequency (%)
( 81
100.0%
Close Punctuation
ValueCountFrequency (%)
) 81
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 990
71.5%
Common 332
 
24.0%
Latin 62
 
4.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 53
 
5.4%
장 42
 
4.2%
공 42
 
4.2%
동 39
 
3.9%
산 27
 
2.7%
이 25
 
2.5%
업 22
 
2.2%
기 21
 
2.1%
대 20
 
2.0%
화 17
 
1.7%
Other values (215) 682
68.9%
Latin
ValueCountFrequency (%)
C 9
14.5%
A 7
11.3%
T 6
 
9.7%
K 5
 
8.1%
H 4
 
6.5%
M 4
 
6.5%
P 4
 
6.5%
S 3
 
4.8%
V 3
 
4.8%
R 2
 
3.2%
Other values (11) 15
24.2%
Common
ValueCountFrequency (%)
101
30.4%
( 81
24.4%
) 81
24.4%
* 49
14.8%
. 9
 
2.7%
- 6
 
1.8%
, 4
 
1.2%
~ 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 989
71.5%
ASCII 394
 
28.5%
None 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
101
25.6%
( 81
20.6%
) 81
20.6%
* 49
12.4%
C 9
 
2.3%
. 9
 
2.3%
A 7
 
1.8%
- 6
 
1.5%
T 6
 
1.5%
K 5
 
1.3%
Other values (19) 40
 
10.2%
Hangul
ValueCountFrequency (%)
주 53
 
5.4%
장 42
 
4.2%
공 42
 
4.2%
동 39
 
3.9%
산 27
 
2.7%
이 25
 
2.5%
업 22
 
2.2%
기 21
 
2.1%
대 20
 
2.0%
화 17
 
1.7%
Other values (214) 681
68.9%
None
ValueCountFrequency (%)
㈜ 1
100.0%

주용도명
Categorical

IMBALANCE 

Distinct11
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
<NA>
705 
공장
 
42
근린생활
 
23
판매시설및 영업시설
 
16
위생등관련시설
 
6
Other values (6)
 
14

Length

Max length11
Median length4
Mean length4.0533499
Min length2

Unique

Unique2 ?
Unique (%)0.2%

Sample

1st row<NA>
2nd row<NA>
3rd row공장
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 705
87.5%
공장 42
 
5.2%
근린생활 23
 
2.9%
판매시설및 영업시설 16
 
2.0%
위생등관련시설 6
 
0.7%
창고시설 4
 
0.5%
복합건축물 3
 
0.4%
노유자시설 3
 
0.4%
의료시설 2
 
0.2%
위험물저장및 처리시설 1
 
0.1%

Length

2024-03-14T22:45:19.194438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 705
85.7%
공장 42
 
5.1%
근린생활 23
 
2.8%
판매시설및 16
 
1.9%
영업시설 16
 
1.9%
위생등관련시설 6
 
0.7%
창고시설 4
 
0.5%
복합건축물 3
 
0.4%
노유자시설 3
 
0.4%
의료시설 2
 
0.2%
Other values (3) 3
 
0.4%

다중이용업여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size934.0 B
False
805 
True
 
1
ValueCountFrequency (%)
False 805
99.9%
True 1
 
0.1%
2024-03-14T22:45:19.523236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

건물구조식
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
<NA>
703 
양식(옥)
73 
조립식
 
24
기타 식
 
6

Length

Max length5
Median length4
Mean length4.060794
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 703
87.2%
양식(옥) 73
 
9.1%
조립식 24
 
3.0%
기타 식 6
 
0.7%

Length

2024-03-14T22:45:19.906603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T22:45:20.268875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 703
86.6%
양식(옥 73
 
9.0%
조립식 24
 
3.0%
기타 6
 
0.7%
식 6
 
0.7%

건물구조즙
Categorical

IMBALANCE 

Distinct11
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
<NA>
703 
슬라브가
 
39
칼라피복철판
 
19
샌드위치패널
 
19
기타 즙
 
13
Other values (6)
 
13

Length

Max length11
Median length4
Mean length4.1389578
Min length2

Unique

Unique3 ?
Unique (%)0.4%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 703
87.2%
슬라브가 39
 
4.8%
칼라피복철판 19
 
2.4%
샌드위치패널 19
 
2.4%
기타 즙 13
 
1.6%
기타(건물구조즙코드) 4
 
0.5%
스레트가 3
 
0.4%
철근콘크리트조 3
 
0.4%
석조 1
 
0.1%
비닐하우스 1
 
0.1%

Length

2024-03-14T22:45:20.651082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 703
85.8%
슬라브가 39
 
4.8%
칼라피복철판 19
 
2.3%
샌드위치패널 19
 
2.3%
기타 13
 
1.6%
즙 13
 
1.6%
기타(건물구조즙코드 4
 
0.5%
스레트가 3
 
0.4%
철근콘크리트조 3
 
0.4%
석조 1
 
0.1%
Other values (2) 2
 
0.2%

건물구조동수
Real number (ℝ)

ZEROS 

Distinct15
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.56327543
Minimum0
Maximum113
Zeros712
Zeros (%)88.3%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2024-03-14T22:45:20.989134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum113
Range113
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5.3336239
Coefficient of variation (CV)9.4689447
Kurtosis308.35378
Mean0.56327543
Median Absolute Deviation (MAD)0
Skewness16.77477
Sum454
Variance28.447544
MonotonicityNot monotonic
2024-03-14T22:45:21.341146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 712
88.3%
1 66
 
8.2%
2 5
 
0.6%
3 4
 
0.5%
5 3
 
0.4%
4 3
 
0.4%
6 3
 
0.4%
8 2
 
0.2%
9 2
 
0.2%
113 1
 
0.1%
Other values (5) 5
 
0.6%
ValueCountFrequency (%)
0 712
88.3%
1 66
 
8.2%
2 5
 
0.6%
3 4
 
0.5%
4 3
 
0.4%
5 3
 
0.4%
6 3
 
0.4%
8 2
 
0.2%
9 2
 
0.2%
10 1
 
0.1%
ValueCountFrequency (%)
113 1
 
0.1%
69 1
 
0.1%
67 1
 
0.1%
15 1
 
0.1%
13 1
 
0.1%
10 1
 
0.1%
9 2
0.2%
8 2
0.2%
6 3
0.4%
5 3
0.4%

지상층수
Real number (ℝ)

ZEROS 

Distinct10
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.55459057
Minimum0
Maximum15
Zeros620
Zeros (%)76.9%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2024-03-14T22:45:21.664833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3
Maximum15
Range15
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.319278
Coefficient of variation (CV)2.3788324
Kurtosis23.005956
Mean0.55459057
Median Absolute Deviation (MAD)0
Skewness3.7749299
Sum447
Variance1.7404944
MonotonicityNot monotonic
2024-03-14T22:45:22.033397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 620
76.9%
1 70
 
8.7%
2 50
 
6.2%
3 30
 
3.7%
4 15
 
1.9%
5 13
 
1.6%
7 3
 
0.4%
6 3
 
0.4%
15 1
 
0.1%
8 1
 
0.1%
ValueCountFrequency (%)
0 620
76.9%
1 70
 
8.7%
2 50
 
6.2%
3 30
 
3.7%
4 15
 
1.9%
5 13
 
1.6%
6 3
 
0.4%
7 3
 
0.4%
8 1
 
0.1%
15 1
 
0.1%
ValueCountFrequency (%)
15 1
 
0.1%
8 1
 
0.1%
7 3
 
0.4%
6 3
 
0.4%
5 13
 
1.6%
4 15
 
1.9%
3 30
 
3.7%
2 50
 
6.2%
1 70
 
8.7%
0 620
76.9%

지하층수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
0
769 
1
 
36
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 769
95.4%
1 36
 
4.5%
2 1
 
0.1%

Length

2024-03-14T22:45:22.422609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T22:45:22.746314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 769
95.4%
1 36
 
4.5%
2 1
 
0.1%

발화열원 분류명
Categorical

IMBALANCE 

Distinct12
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
<NA>
621 
작동기기
 
61
미상(발화원인)
 
35
불꽃, 불티
 
23
담뱃불, 라이터불
 
23
Other values (7)
 
43

Length

Max length10
Median length4
Mean length4.5942928
Min length4

Unique

Unique3 ?
Unique (%)0.4%

Sample

1st row미상(발화원인)
2nd row<NA>
3rd row마찰, 전도, 복사
4th row불꽃, 불티
5th row작동기기

Common Values

ValueCountFrequency (%)
<NA> 621
77.0%
작동기기 61
 
7.6%
미상(발화원인) 35
 
4.3%
불꽃, 불티 23
 
2.9%
담뱃불, 라이터불 23
 
2.9%
마찰, 전도, 복사 16
 
2.0%
화학적 발화열 15
 
1.9%
기타(발화원인) 6
 
0.7%
P82101 3
 
0.4%
P82103 1
 
0.1%
Other values (2) 2
 
0.2%

Length

2024-03-14T22:45:23.029209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 621
69.0%
작동기기 61
 
6.8%
미상(발화원인 35
 
3.9%
불꽃 23
 
2.6%
불티 23
 
2.6%
담뱃불 23
 
2.6%
라이터불 23
 
2.6%
복사 16
 
1.8%
발화열 16
 
1.8%
전도 16
 
1.8%
Other values (7) 43
 
4.8%

발화사유 대분류명
Categorical

IMBALANCE 

Distinct13
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
<NA>
621 
부주의
 
55
전기적 요인
 
39
미상
 
30
기계적 요인
 
25
Other values (8)
 
36

Length

Max length8
Median length4
Mean length4.0694789
Min length2

Unique

Unique3 ?
Unique (%)0.4%

Sample

1st row미상
2nd row<NA>
3rd row기타
4th row부주의
5th row전기적 요인

Common Values

ValueCountFrequency (%)
<NA> 621
77.0%
부주의 55
 
6.8%
전기적 요인 39
 
4.8%
미상 30
 
3.7%
기계적 요인 25
 
3.1%
화학적 요인 17
 
2.1%
기타 7
 
0.9%
가스누출(폭발) 4
 
0.5%
자연적인 요인 3
 
0.4%
제품결함 2
 
0.2%
Other values (3) 3
 
0.4%

Length

2024-03-14T22:45:23.339806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 621
69.8%
요인 84
 
9.4%
부주의 55
 
6.2%
전기적 39
 
4.4%
미상 30
 
3.4%
기계적 25
 
2.8%
화학적 17
 
1.9%
기타 7
 
0.8%
가스누출(폭발 4
 
0.4%
자연적인 3
 
0.3%
Other values (4) 5
 
0.6%

그을음면적
Real number (ℝ)

ZEROS 

Distinct30
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.7506203
Minimum0
Maximum750
Zeros761
Zeros (%)94.4%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2024-03-14T22:45:23.678869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile4.5
Maximum750
Range750
Interquartile range (IQR)0

Descriptive statistics

Standard deviation44.479137
Coefficient of variation (CV)7.7346676
Kurtosis150.37484
Mean5.7506203
Median Absolute Deviation (MAD)0
Skewness11.386856
Sum4635
Variance1978.3936
MonotonicityNot monotonic
2024-03-14T22:45:23.913416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0 761
94.4%
5 4
 
0.5%
3 4
 
0.5%
10 4
 
0.5%
20 3
 
0.4%
40 2
 
0.2%
66 2
 
0.2%
200 2
 
0.2%
13 2
 
0.2%
30 2
 
0.2%
Other values (20) 20
 
2.5%
ValueCountFrequency (%)
0 761
94.4%
3 4
 
0.5%
5 4
 
0.5%
9 1
 
0.1%
10 4
 
0.5%
13 2
 
0.2%
20 3
 
0.4%
23 1
 
0.1%
25 1
 
0.1%
30 2
 
0.2%
ValueCountFrequency (%)
750 1
0.1%
550 1
0.1%
450 1
0.1%
409 1
0.1%
330 1
0.1%
260 1
0.1%
200 2
0.2%
165 1
0.1%
150 1
0.1%
138 1
0.1%

화재발생일자
Date

MISSING 

Distinct173
Distinct (%)93.5%
Missing621
Missing (%)77.0%
Memory size6.4 KiB
Minimum2019-01-09 00:00:00
Maximum2021-12-20 00:00:00
2024-03-14T22:45:24.282713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:45:24.701421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

화재발생요일
Categorical

IMBALANCE 

Distinct8
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
<NA>
621 
토
 
34
목
 
33
금
 
27
월
 
25
Other values (3)
66 

Length

Max length4
Median length4
Mean length3.3114144
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row수
2nd row<NA>
3rd row수
4th row수
5th row월

Common Values

ValueCountFrequency (%)
<NA> 621
77.0%
토 34
 
4.2%
목 33
 
4.1%
금 27
 
3.3%
월 25
 
3.1%
화 25
 
3.1%
일 23
 
2.9%
수 18
 
2.2%

Length

2024-03-14T22:45:25.124826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T22:45:25.486896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 621
77.0%
토 34
 
4.2%
목 33
 
4.1%
금 27
 
3.3%
월 25
 
3.1%
화 25
 
3.1%
일 23
 
2.9%
수 18
 
2.2%

초진연도
Categorical

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
<NA>
621 
2021
68 
2020
64 
2019
 
53

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019
2nd row<NA>
3rd row2019
4th row2019
5th row2019

Common Values

ValueCountFrequency (%)
<NA> 621
77.0%
2021 68
 
8.4%
2020 64
 
7.9%
2019 53
 
6.6%

Length

2024-03-14T22:45:25.700029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T22:45:25.880057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 621
77.0%
2021 68
 
8.4%
2020 64
 
7.9%
2019 53
 
6.6%

초진월
Real number (ℝ)

MISSING 

Distinct12
Distinct (%)6.5%
Missing621
Missing (%)77.0%
Infinite0
Infinite (%)0.0%
Mean6.3567568
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2024-03-14T22:45:26.061163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median6
Q39
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.437686
Coefficient of variation (CV)0.54079244
Kurtosis-1.1347916
Mean6.3567568
Median Absolute Deviation (MAD)3
Skewness-0.011583781
Sum1176
Variance11.817685
MonotonicityNot monotonic
2024-03-14T22:45:26.249037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 20
 
2.5%
7 20
 
2.5%
5 17
 
2.1%
2 16
 
2.0%
6 16
 
2.0%
4 15
 
1.9%
8 15
 
1.9%
9 15
 
1.9%
10 15
 
1.9%
12 14
 
1.7%
Other values (2) 22
 
2.7%
(Missing) 621
77.0%
ValueCountFrequency (%)
1 20
2.5%
2 16
2.0%
3 9
1.1%
4 15
1.9%
5 17
2.1%
6 16
2.0%
7 20
2.5%
8 15
1.9%
9 15
1.9%
10 15
1.9%
ValueCountFrequency (%)
12 14
1.7%
11 13
1.6%
10 15
1.9%
9 15
1.9%
8 15
1.9%
7 20
2.5%
6 16
2.0%
5 17
2.1%
4 15
1.9%
3 9
1.1%

초진일
Real number (ℝ)

MISSING 

Distinct31
Distinct (%)16.8%
Missing621
Missing (%)77.0%
Infinite0
Infinite (%)0.0%
Mean15.686486
Minimum1
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2024-03-14T22:45:26.714292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q18
median16
Q324
95-th percentile29
Maximum31
Range30
Interquartile range (IQR)16

Descriptive statistics

Standard deviation8.7934685
Coefficient of variation (CV)0.56057604
Kurtosis-1.2215884
Mean15.686486
Median Absolute Deviation (MAD)8
Skewness0.039055967
Sum2902
Variance77.325088
MonotonicityNot monotonic
2024-03-14T22:45:27.109248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
5 11
 
1.4%
24 10
 
1.2%
16 10
 
1.2%
7 9
 
1.1%
10 9
 
1.1%
25 8
 
1.0%
11 8
 
1.0%
19 8
 
1.0%
1 7
 
0.9%
20 7
 
0.9%
Other values (21) 98
 
12.2%
(Missing) 621
77.0%
ValueCountFrequency (%)
1 7
0.9%
2 5
0.6%
3 3
 
0.4%
4 4
 
0.5%
5 11
1.4%
6 5
0.6%
7 9
1.1%
8 5
0.6%
9 5
0.6%
10 9
1.1%
ValueCountFrequency (%)
31 4
 
0.5%
30 4
 
0.5%
29 6
0.7%
28 6
0.7%
27 6
0.7%
26 6
0.7%
25 8
1.0%
24 10
1.2%
23 4
 
0.5%
22 4
 
0.5%

초진시
Real number (ℝ)

MISSING  ZEROS 

Distinct24
Distinct (%)13.0%
Missing621
Missing (%)77.0%
Infinite0
Infinite (%)0.0%
Mean11.659459
Minimum0
Maximum23
Zeros9
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2024-03-14T22:45:27.483634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q16
median12
Q317
95-th percentile22
Maximum23
Range23
Interquartile range (IQR)11

Descriptive statistics

Standard deviation6.6877345
Coefficient of variation (CV)0.57358873
Kurtosis-0.99096129
Mean11.659459
Median Absolute Deviation (MAD)5
Skewness-0.061610714
Sum2157
Variance44.725793
MonotonicityNot monotonic
2024-03-14T22:45:27.789640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
11 14
 
1.7%
13 14
 
1.7%
6 12
 
1.5%
15 11
 
1.4%
22 10
 
1.2%
8 9
 
1.1%
0 9
 
1.1%
1 9
 
1.1%
12 9
 
1.1%
17 9
 
1.1%
Other values (14) 79
 
9.8%
(Missing) 621
77.0%
ValueCountFrequency (%)
0 9
1.1%
1 9
1.1%
2 6
0.7%
3 2
 
0.2%
4 5
0.6%
5 6
0.7%
6 12
1.5%
7 6
0.7%
8 9
1.1%
9 5
0.6%
ValueCountFrequency (%)
23 6
0.7%
22 10
1.2%
21 8
1.0%
20 7
0.9%
19 5
0.6%
18 5
0.6%
17 9
1.1%
16 4
 
0.5%
15 11
1.4%
14 8
1.0%

초진분
Real number (ℝ)

MISSING 

Distinct57
Distinct (%)30.8%
Missing621
Missing (%)77.0%
Infinite0
Infinite (%)0.0%
Mean30.972973
Minimum0
Maximum59
Zeros1
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2024-03-14T22:45:28.118400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4.2
Q118
median31
Q344
95-th percentile55.8
Maximum59
Range59
Interquartile range (IQR)26

Descriptive statistics

Standard deviation16.587853
Coefficient of variation (CV)0.53555896
Kurtosis-1.1575341
Mean30.972973
Median Absolute Deviation (MAD)13
Skewness-0.10723622
Sum5730
Variance275.15687
MonotonicityNot monotonic
2024-03-14T22:45:28.559286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
40 7
 
0.9%
30 7
 
0.9%
55 7
 
0.9%
49 6
 
0.7%
14 6
 
0.7%
10 6
 
0.7%
43 6
 
0.7%
36 5
 
0.6%
53 5
 
0.6%
24 5
 
0.6%
Other values (47) 125
 
15.5%
(Missing) 621
77.0%
ValueCountFrequency (%)
0 1
 
0.1%
1 1
 
0.1%
2 3
0.4%
3 2
0.2%
4 3
0.4%
5 3
0.4%
6 1
 
0.1%
7 4
0.5%
8 4
0.5%
9 2
0.2%
ValueCountFrequency (%)
59 1
 
0.1%
58 4
0.5%
56 5
0.6%
55 7
0.9%
53 5
0.6%
52 2
 
0.2%
51 3
0.4%
50 4
0.5%
49 6
0.7%
48 1
 
0.1%

완진연도
Categorical

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
<NA>
621 
2021
68 
2020
64 
2019
 
53

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019
2nd row<NA>
3rd row2019
4th row2019
5th row2019

Common Values

ValueCountFrequency (%)
<NA> 621
77.0%
2021 68
 
8.4%
2020 64
 
7.9%
2019 53
 
6.6%

Length

2024-03-14T22:45:28.959438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T22:45:29.282151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 621
77.0%
2021 68
 
8.4%
2020 64
 
7.9%
2019 53
 
6.6%

완진월
Real number (ℝ)

MISSING 

Distinct12
Distinct (%)6.5%
Missing621
Missing (%)77.0%
Infinite0
Infinite (%)0.0%
Mean6.3567568
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2024-03-14T22:45:29.614332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median6
Q39
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.437686
Coefficient of variation (CV)0.54079244
Kurtosis-1.1347916
Mean6.3567568
Median Absolute Deviation (MAD)3
Skewness-0.011583781
Sum1176
Variance11.817685
MonotonicityNot monotonic
2024-03-14T22:45:29.902660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 20
 
2.5%
7 20
 
2.5%
5 17
 
2.1%
2 16
 
2.0%
6 16
 
2.0%
4 15
 
1.9%
8 15
 
1.9%
9 15
 
1.9%
10 15
 
1.9%
12 14
 
1.7%
Other values (2) 22
 
2.7%
(Missing) 621
77.0%
ValueCountFrequency (%)
1 20
2.5%
2 16
2.0%
3 9
1.1%
4 15
1.9%
5 17
2.1%
6 16
2.0%
7 20
2.5%
8 15
1.9%
9 15
1.9%
10 15
1.9%
ValueCountFrequency (%)
12 14
1.7%
11 13
1.6%
10 15
1.9%
9 15
1.9%
8 15
1.9%
7 20
2.5%
6 16
2.0%
5 17
2.1%
4 15
1.9%
3 9
1.1%

완진일
Real number (ℝ)

MISSING 

Distinct31
Distinct (%)16.8%
Missing621
Missing (%)77.0%
Infinite0
Infinite (%)0.0%
Mean15.691892
Minimum1
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2024-03-14T22:45:30.184493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q18
median16
Q324
95-th percentile29
Maximum31
Range30
Interquartile range (IQR)16

Descriptive statistics

Standard deviation8.7989123
Coefficient of variation (CV)0.56072986
Kurtosis-1.2236347
Mean15.691892
Median Absolute Deviation (MAD)8
Skewness0.039001885
Sum2903
Variance77.420858
MonotonicityNot monotonic
2024-03-14T22:45:30.401780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
5 11
 
1.4%
16 10
 
1.2%
24 9
 
1.1%
25 9
 
1.1%
7 9
 
1.1%
10 9
 
1.1%
11 8
 
1.0%
19 8
 
1.0%
1 7
 
0.9%
20 7
 
0.9%
Other values (21) 98
 
12.2%
(Missing) 621
77.0%
ValueCountFrequency (%)
1 7
0.9%
2 5
0.6%
3 3
 
0.4%
4 4
 
0.5%
5 11
1.4%
6 5
0.6%
7 9
1.1%
8 5
0.6%
9 5
0.6%
10 9
1.1%
ValueCountFrequency (%)
31 4
0.5%
30 4
0.5%
29 6
0.7%
28 6
0.7%
27 6
0.7%
26 6
0.7%
25 9
1.1%
24 9
1.1%
23 4
0.5%
22 4
0.5%

완진시
Real number (ℝ)

MISSING  ZEROS 

Distinct24
Distinct (%)13.0%
Missing621
Missing (%)77.0%
Infinite0
Infinite (%)0.0%
Mean11.762162
Minimum0
Maximum23
Zeros9
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2024-03-14T22:45:30.616695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q17
median12
Q317
95-th percentile22
Maximum23
Range23
Interquartile range (IQR)10

Descriptive statistics

Standard deviation6.6592267
Coefficient of variation (CV)0.56615668
Kurtosis-0.96491837
Mean11.762162
Median Absolute Deviation (MAD)5
Skewness-0.088924304
Sum2176
Variance44.3453
MonotonicityNot monotonic
2024-03-14T22:45:30.823709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
15 13
 
1.6%
11 13
 
1.6%
14 11
 
1.4%
17 11
 
1.4%
6 11
 
1.4%
13 10
 
1.2%
1 10
 
1.2%
22 10
 
1.2%
21 10
 
1.2%
12 9
 
1.1%
Other values (14) 77
 
9.6%
(Missing) 621
77.0%
ValueCountFrequency (%)
0 9
1.1%
1 10
1.2%
2 3
 
0.4%
3 3
 
0.4%
4 7
0.9%
5 3
 
0.4%
6 11
1.4%
7 7
0.9%
8 9
1.1%
9 7
0.9%
ValueCountFrequency (%)
23 6
0.7%
22 10
1.2%
21 10
1.2%
20 4
 
0.5%
19 5
 
0.6%
18 5
 
0.6%
17 11
1.4%
16 3
 
0.4%
15 13
1.6%
14 11
1.4%

완진분
Real number (ℝ)

MISSING 

Distinct59
Distinct (%)31.9%
Missing621
Missing (%)77.0%
Infinite0
Infinite (%)0.0%
Mean32.383784
Minimum0
Maximum59
Zeros2
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2024-03-14T22:45:31.048967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5
Q116
median35
Q348
95-th percentile57.8
Maximum59
Range59
Interquartile range (IQR)32

Descriptive statistics

Standard deviation17.595972
Coefficient of variation (CV)0.54335749
Kurtosis-1.2596519
Mean32.383784
Median Absolute Deviation (MAD)16
Skewness-0.18745409
Sum5991
Variance309.61821
MonotonicityNot monotonic
2024-03-14T22:45:31.390678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
53 9
 
1.1%
55 7
 
0.9%
35 7
 
0.9%
40 6
 
0.7%
43 6
 
0.7%
59 6
 
0.7%
8 6
 
0.7%
10 6
 
0.7%
27 5
 
0.6%
39 5
 
0.6%
Other values (49) 122
 
15.1%
(Missing) 621
77.0%
ValueCountFrequency (%)
0 2
 
0.2%
1 1
 
0.1%
2 1
 
0.1%
3 1
 
0.1%
4 2
 
0.2%
5 5
0.6%
6 3
0.4%
7 4
0.5%
8 6
0.7%
9 1
 
0.1%
ValueCountFrequency (%)
59 6
0.7%
58 4
0.5%
57 1
 
0.1%
56 4
0.5%
55 7
0.9%
54 1
 
0.1%
53 9
1.1%
52 3
 
0.4%
51 5
0.6%
50 1
 
0.1%

인명피해합계수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
0
797 
1
 
8
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 797
98.9%
1 8
 
1.0%
3 1
 
0.1%

Length

2024-03-14T22:45:31.623546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T22:45:31.797843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 797
98.9%
1 8
 
1.0%
3 1
 
0.1%

소실면적
Real number (ℝ)

ZEROS 

Distinct25
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.4255583
Minimum0
Maximum1800
Zeros766
Zeros (%)95.0%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2024-03-14T22:45:31.975349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1800
Range1800
Interquartile range (IQR)0

Descriptive statistics

Standard deviation85.372527
Coefficient of variation (CV)11.497119
Kurtosis321.82333
Mean7.4255583
Median Absolute Deviation (MAD)0
Skewness17.160571
Sum5985
Variance7288.4684
MonotonicityNot monotonic
2024-03-14T22:45:32.184862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0 766
95.0%
50 6
 
0.7%
10 4
 
0.5%
20 4
 
0.5%
30 4
 
0.5%
12 2
 
0.2%
100 2
 
0.2%
110 1
 
0.1%
1800 1
 
0.1%
585 1
 
0.1%
Other values (15) 15
 
1.9%
ValueCountFrequency (%)
0 766
95.0%
3 1
 
0.1%
4 1
 
0.1%
6 1
 
0.1%
9 1
 
0.1%
10 4
 
0.5%
12 2
 
0.2%
13 1
 
0.1%
18 1
 
0.1%
20 4
 
0.5%
ValueCountFrequency (%)
1800 1
0.1%
1350 1
0.1%
585 1
0.1%
563 1
0.1%
277 1
0.1%
165 1
0.1%
160 1
0.1%
110 1
0.1%
100 2
0.2%
52 1
0.1%

온도
Real number (ℝ)

ZEROS 

Distinct128
Distinct (%)15.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.1502481
Minimum-10.3
Maximum32.6
Zeros632
Zeros (%)78.4%
Negative12
Negative (%)1.5%
Memory size7.2 KiB
2024-03-14T22:45:32.520737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-10.3
5-th percentile0
Q10
median0
Q30
95-th percentile21.8
Maximum32.6
Range42.9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation7.3587582
Coefficient of variation (CV)2.3359297
Kurtosis3.2988859
Mean3.1502481
Median Absolute Deviation (MAD)0
Skewness2.1142657
Sum2539.1
Variance54.151323
MonotonicityNot monotonic
2024-03-14T22:45:32.784177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 632
78.4%
22.0 4
 
0.5%
17.2 3
 
0.4%
12.9 3
 
0.4%
8.7 3
 
0.4%
15.6 3
 
0.4%
18.7 3
 
0.4%
19.0 3
 
0.4%
19.6 3
 
0.4%
17.8 2
 
0.2%
Other values (118) 147
 
18.2%
ValueCountFrequency (%)
-10.3 1
0.1%
-9.1 1
0.1%
-8.7 1
0.1%
-8.6 1
0.1%
-6.1 1
0.1%
-4.0 1
0.1%
-1.8 1
0.1%
-1.2 1
0.1%
-1.0 1
0.1%
-0.9 1
0.1%
ValueCountFrequency (%)
32.6 1
0.1%
30.6 1
0.1%
30.5 2
0.2%
30.0 1
0.1%
29.5 1
0.1%
29.3 1
0.1%
29.1 1
0.1%
27.9 1
0.1%
27.5 1
0.1%
27.2 1
0.1%

습도
Real number (ℝ)

ZEROS 

Distinct76
Distinct (%)9.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.086849
Minimum0
Maximum100
Zeros632
Zeros (%)78.4%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2024-03-14T22:45:33.038202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile85
Maximum100
Range100
Interquartile range (IQR)0

Descriptive statistics

Standard deviation27.553492
Coefficient of variation (CV)2.1054337
Kurtosis2.3218313
Mean13.086849
Median Absolute Deviation (MAD)0
Skewness1.9401899
Sum10548
Variance759.19493
MonotonicityNot monotonic
2024-03-14T22:45:33.464034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 632
78.4%
93 7
 
0.9%
38 7
 
0.9%
97 6
 
0.7%
27 5
 
0.6%
86 5
 
0.6%
85 5
 
0.6%
59 4
 
0.5%
55 4
 
0.5%
57 4
 
0.5%
Other values (66) 127
 
15.8%
ValueCountFrequency (%)
0 632
78.4%
11 1
 
0.1%
12 1
 
0.1%
13 1
 
0.1%
14 3
 
0.4%
17 1
 
0.1%
19 2
 
0.2%
21 1
 
0.1%
22 2
 
0.2%
24 1
 
0.1%
ValueCountFrequency (%)
100 1
 
0.1%
99 3
0.4%
98 1
 
0.1%
97 6
0.7%
96 1
 
0.1%
95 3
0.4%
94 1
 
0.1%
93 7
0.9%
92 1
 
0.1%
91 3
0.4%

풍속
Categorical

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
<NA>
621 
0~4 m/s
136 
5~8 m/s
 
29
NONE
 
20

Length

Max length7
Median length4
Mean length4.6141439
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5~8 m/s
2nd row<NA>
3rd row0~4 m/s
4th row0~4 m/s
5th rowNONE

Common Values

ValueCountFrequency (%)
<NA> 621
77.0%
0~4 m/s 136
 
16.9%
5~8 m/s 29
 
3.6%
NONE 20
 
2.5%

Length

2024-03-14T22:45:33.903734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T22:45:34.247461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 621
64.0%
m/s 165
 
17.0%
0~4 136
 
14.0%
5~8 29
 
3.0%
none 20
 
2.1%

풍향
Categorical

IMBALANCE 

Distinct10
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
<NA>
621 
북
 
35
북동
 
29
남서
 
29
북서
 
22
Other values (5)
70 

Length

Max length4
Median length4
Mean length3.4689826
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row북
2nd row<NA>
3rd row북서
4th row서
5th row서

Common Values

ValueCountFrequency (%)
<NA> 621
77.0%
북 35
 
4.3%
북동 29
 
3.6%
남서 29
 
3.6%
북서 22
 
2.7%
남 18
 
2.2%
서 17
 
2.1%
NONE 12
 
1.5%
동 12
 
1.5%
남동 11
 
1.4%

Length

2024-03-14T22:45:34.635275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T22:45:35.011175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 621
77.0%
북 35
 
4.3%
북동 29
 
3.6%
남서 29
 
3.6%
북서 22
 
2.7%
남 18
 
2.2%
서 17
 
2.1%
none 12
 
1.5%
동 12
 
1.5%
남동 11
 
1.4%

Sample

접수경로명신고연도신고월신고일신고시신고분재난시명재난구명재난동명재난리명상황종료연도상황종료월상황종료일상황종료시상황종료분관할서명관할센터명도로명읍면동순번지하 여부화학사고여부출동대센터정보대상물명주용도명다중이용업여부건물구조식건물구조즙건물구조동수지상층수지하층수발화열원 분류명발화사유 대분류명그을음면적화재발생일자화재발생요일초진연도초진월초진일초진시초진분완진연도완진월완진일완진시완진분인명피해합계수소실면적온도습도풍속풍향
0이동전화2019191254울산광역시북구시례동<NA>2019191726북부소방서농소119안전센터<NA><NA>0N(구)항공구조구급대, 농소119안전센터, 매곡119안전센터, 병영119안전센터, 북부구조대, 북부예방안전과, 삼산119안전센터, 송정119안전센터, 신정119안전센터, 유곡119안전센터, 태화119안전센터(주)TEPC<NA>N<NA><NA>000미상(발화원인)미상02019-01-09수20191913282019191356004.3375~8 m/s북
1이동전화20191151757울산광역시울주군온산읍원산리2019115181온산소방서화산119안전센터화산로10N공단119안전센터, 남부구조대, 삼산119안전센터, 서생119지역대, 신정119안전센터, 여천119안전센터, 옥동119안전센터, 온산119안전센터, 온산예방안전과, 웅촌119안전센터, 유곡119안전센터, 장생포119안전센터, 화산119안전센터<NA><NA>N<NA><NA>000<NA><NA>0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>000.00<NA><NA>
2이동전화2019116151울산광역시울주군언양읍반송리20191161655중부소방서범서119안전센터<NA><NA>0N무거119안전센터, 범서119안전센터, 삼동119지역대, 삼산119안전센터, 언양119안전센터, 웅촌119안전센터, 유곡119안전센터, 중부구조대, 중부방호구조과, 태화119안전센터㈜효성언양공장(폐업) .공장N<NA><NA>020마찰, 전도, 복사기타02019-01-16수2019116151420191161520004.0140~4 m/s북서
3이동전화20191161653울산광역시울주군온양읍동상리20191161749온산소방서온양119안전센터상서길10N공단119안전센터, 온산119안전센터, 온산구조대, 온산예방안전과, 온양119안전센터, 웅촌119안전센터, 화산119안전센터유림 ENG<NA>N<NA><NA>000불꽃, 불티부주의02019-01-16수20191161722019116172004.9110~4 m/s서
4기타2019121926울산광역시남구성암동<NA>2019122830남부소방서공단119안전센터처용로487번길10N(구)특수화학구조대, 공단119안전센터, 남부구조대, 남부방호구조과, 병영119안전센터, 삼산119안전센터, 송정119안전센터, 신정119안전센터, 여천119안전센터, 염포119안전센터, 온산119안전센터, 유곡119안전센터, 장생포119안전센터, 화산119안전센터, 화암119안전센터대상산업가스(주)<NA>N<NA><NA>000작동기기전기적 요인02019-01-21월201912112302019121172100-4.038NONE서
5일반전화201912421울산광역시남구삼산동<NA>20191241311남부소방서삼산119안전센터삼산로30N공단119안전센터, 남부구조대, 남부방호구조과, 동부구조대, 무거119안전센터, 범서119안전센터, 병영119안전센터, 삼산119안전센터, 성남119안전센터, 송정119안전센터, 신정119안전센터, 여천119안전센터, 염포119안전센터, 옥동119안전센터, 온산구조대, 유곡119안전센터, 장생포119안전센터, 중부구조대, 태화119안전센터, 화정119안전센터수산물종합동(소매시장)<NA>N<NA><NA>000작동기기전기적 요인02019-01-24목2019124250201912444000-0.8410~4 m/s북
6IP전화2019125543울산광역시남구여천동<NA>2019125752남부소방서장생포119안전센터여천로10N공단119안전센터, 남부구조대, 남부방호구조과, 삼산119안전센터, 신정119안전센터, 여천119안전센터, 장생포119안전센터용진유화<NA>N<NA><NA>000화학적 발화열화학적 요인02019-01-25금201912555520191256000-1.0270~4 m/s북서
7이동전화20191251752울산광역시남구여천동<NA>20191252222남부소방서장생포119안전센터<NA><NA>0N공단119안전센터, 광역화재조사단, 남부구조대, 남부방호구조과, 삼산119안전센터, 신정119안전센터, 여천119안전센터, 장생포119안전센터드림바이오(주)공장N<NA><NA>050마찰, 전도, 복사부주의02019-01-25금2019125181420191251816100.1380~4 m/s북동
8이동전화20191271522울산광역시중구우정동<NA>20191271637중부소방서유곡119안전센터유곡로10N공단119안전센터, 남부구조대, 범서119안전센터, 병영119안전센터, 삼산119안전센터, 성남119안전센터, 신정119안전센터, 유곡119안전센터, 중부방호구조과SK공인중개사<NA>N<NA><NA>000미상(발화원인)미상02019-01-27일20191271528201912715300010.4190~4 m/s남동
9이동전화2019128634울산광역시울주군온산읍원산리2019128856온산소방서화산119안전센터<NA>10N공단119안전센터, 서생119지역대, 여천119안전센터, 온산119안전센터, 온산구조대, 온산예방안전과, 온양119안전센터, 화산119안전센터<NA><NA>N<NA><NA>000미상(발화원인)미상02019-01-28월20191286502019128651000.00NONENONE
접수경로명신고연도신고월신고일신고시신고분재난시명재난구명재난동명재난리명상황종료연도상황종료월상황종료일상황종료시상황종료분관할서명관할센터명도로명읍면동순번지하 여부화학사고여부출동대센터정보대상물명주용도명다중이용업여부건물구조식건물구조즙건물구조동수지상층수지하층수발화열원 분류명발화사유 대분류명그을음면적화재발생일자화재발생요일초진연도초진월초진일초진시초진분완진연도완진월완진일완진시완진분인명피해합계수소실면적온도습도풍속풍향
796이동전화20211220525울산광역시중구성남동<NA>20211220629중부소방서유곡119안전센터학성로40N119재난대응과, 공단119안전센터, 남부구조대, 병영119안전센터, 삼산119안전센터, 성남119안전센터, 여천119안전센터, 유곡119안전센터, 중부구조대, 태화119안전센터, 특수화학구조대샛별모텔숙박시설N양식(옥)슬라브가071작동기기전기적 요인32021-12-20월2021122053320211220537002.7520~4 m/s남서
797기타2021122094울산광역시울주군웅촌면대대리20211220948온산소방서웅촌119안전센터이예로10N온산119안전센터, 특수화학구조대<NA><NA>N<NA><NA>000<NA><NA>0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>000.00<NA><NA>
798일반전화202112201118울산광역시중구옥교동<NA>202112201134중부소방서성남119안전센터문화의거리10N병영119안전센터, 성남119안전센터<NA><NA>N<NA><NA>000<NA><NA>0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>000.00<NA><NA>
799일반전화20211221941울산광역시울주군서생면대송리202112211011온산소방서온양119안전센터해맞이로20N서생119지역대, 온양119안전센터, 화산119안전센터<NA><NA>N<NA><NA>000<NA><NA>0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>000.00<NA><NA>
800일반전화20211224029울산광역시북구매곡동<NA>20211224048북부소방서매곡119안전센터매곡산업5길10N농소119안전센터, 매곡119안전센터<NA><NA>N<NA><NA>000<NA><NA>0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>000.00<NA><NA>
801일반전화20211225106울산광역시울주군온양읍동상리202112251054온산소방서온양119안전센터덕남로20N119재난대응과, 공단119안전센터, 온산119안전센터, 온산구조대, 온양119안전센터, 웅촌119안전센터, 청량119지역대, 특수화학구조대, 화산119안전센터<NA><NA>N<NA><NA>000<NA><NA>0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>000.00<NA><NA>
802일반전화20211226739울산광역시북구연암동<NA>20211226816북부소방서송정119안전센터산업로50N119재난대응과, 농소119안전센터, 병영119안전센터, 북부구조대, 삼산119안전센터, 성남119안전센터, 송정119안전센터, 여천119안전센터, 유곡119안전센터, 특수화학구조대<NA><NA>N<NA><NA>000<NA><NA>0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>000.00<NA><NA>
803모바일앱신고20211228930울산광역시남구신정동<NA>20211228934남부소방서옥동119안전센터봉월로67번길10N119재난대응과, 공단119안전센터, 남부구조대, 무거119안전센터, 삼산119안전센터, 성남119안전센터, 여천119안전센터, 옥동119안전센터, 유곡119안전센터, 태화119안전센터, 특수화학구조대<NA><NA>N<NA><NA>000<NA><NA>0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>000.00<NA><NA>
804일반전화202112302142울산광역시북구매곡동<NA>20211230222북부소방서매곡119안전센터괴정1길10N119재난대응과, 농소119안전센터, 매곡119안전센터, 북부구조대, 삼산119안전센터, 성남119안전센터, 송정119안전센터, 여천119안전센터, 유곡119안전센터, 특수화학구조대<NA><NA>N<NA><NA>000<NA><NA>0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>000.00<NA><NA>
805일반전화202112311540울산광역시남구신정동<NA>202112311625남부소방서신정119안전센터중앙로241번길10N삼산119안전센터, 신정119안전센터<NA><NA>N<NA><NA>000<NA><NA>0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>000.00<NA><NA>