Overview

Dataset statistics

Number of variables17
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 MiB
Average record size in memory148.0 B

Variable types

DateTime1
Categorical10
Text3
Numeric3

Dataset

Description전국 화재통계로 시도, 시군구, 읍면동, 화재유형, 발화열원, 발화요인, 최초착화물, 인명피해 현황, 재산피해 현황 , 장소에 대한 데이터를 포함하고 있음
Author소방청
URLhttps://www.data.go.kr/data/15060386/fileData.do

Alerts

화재유형 is highly overall correlated with 장소대분류 and 1 other fieldsHigh correlation
발화열원대분류 is highly overall correlated with 발화열원소분류 and 2 other fieldsHigh correlation
장소대분류 is highly overall correlated with 화재유형 and 1 other fieldsHigh correlation
발화요인소분류 is highly overall correlated with 발화열원대분류 and 2 other fieldsHigh correlation
장소중분류 is highly overall correlated with 화재유형 and 1 other fieldsHigh correlation
발화열원소분류 is highly overall correlated with 발화열원대분류 and 2 other fieldsHigh correlation
발화요인대분류 is highly overall correlated with 발화열원대분류 and 2 other fieldsHigh correlation
인명피해(명)소계 is highly overall correlated with 부상High correlation
부상 is highly overall correlated with 인명피해(명)소계High correlation
사망 is highly imbalanced (95.9%)Imbalance
재산피해소계 is highly skewed (γ1 = 43.53431027)Skewed
인명피해(명)소계 has 9523 (95.2%) zerosZeros
부상 has 9584 (95.8%) zerosZeros
재산피해소계 has 764 (7.6%) zerosZeros

Reproduction

Analysis started2024-03-16 04:15:52.979966
Analysis finished2024-03-16 04:15:59.876002
Duration6.9 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일시
Date

Distinct9889
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2023-01-01 00:29:00
Maximum2023-12-31 23:50:00
2024-03-16T13:15:59.955279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:00.175801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

시도
Categorical

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
경기도
2055 
서울특별시
1433 
경상남도
888 
경상북도
766 
전라남도
681 
Other values (12)
4177 

Length

Max length7
Median length5
Mean length4.5159
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울특별시
2nd row경상남도
3rd row강원특별자치도
4th row경상남도
5th row경기도

Common Values

ValueCountFrequency (%)
경기도 2055
20.5%
서울특별시 1433
14.3%
경상남도 888
8.9%
경상북도 766
 
7.7%
전라남도 681
 
6.8%
부산광역시 636
 
6.4%
전북특별자치도 540
 
5.4%
강원특별자치도 518
 
5.2%
충청남도 498
 
5.0%
충청북도 406
 
4.1%
Other values (7) 1579
15.8%

Length

2024-03-16T13:16:00.385159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 2055
20.5%
서울특별시 1433
14.3%
경상남도 888
8.9%
경상북도 766
 
7.7%
전라남도 681
 
6.8%
부산광역시 636
 
6.4%
전북특별자치도 540
 
5.4%
강원특별자치도 518
 
5.2%
충청남도 498
 
5.0%
충청북도 406
 
4.1%
Other values (7) 1579
15.8%

시_군_구
Text

Distinct228
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-16T13:16:00.918439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length3
Mean length3.3478
Min length2

Characters and Unicode

Total characters33478
Distinct characters143
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

Unique1 ?
Unique (%)< 0.1%

Sample

1st row송파구
2nd row진주시
3rd row평창군
4th row사천시
5th row김포시
ValueCountFrequency (%)
서구 243
 
2.4%
중구 189
 
1.8%
강서구 165
 
1.6%
창원시 156
 
1.5%
청주시 151
 
1.5%
동구 150
 
1.5%
북구 147
 
1.4%
남구 141
 
1.4%
화성시 137
 
1.3%
강남구 116
 
1.1%
Other values (220) 8712
84.5%
2024-03-16T13:16:01.824366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 4788
 
14.3%
구 4528
 
13.5%
군 2137
 
6.4%
주 1326
 
4.0%
산 999
 
3.0%
천 964
 
2.9%
성 877
 
2.6%
서 817
 
2.4%
양 771
 
2.3%
남 752
 
2.2%
Other values (133) 15519
46.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 33171
99.1%
Space Separator 307
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 4788
 
14.4%
구 4528
 
13.7%
군 2137
 
6.4%
주 1326
 
4.0%
산 999
 
3.0%
천 964
 
2.9%
성 877
 
2.6%
서 817
 
2.5%
양 771
 
2.3%
남 752
 
2.3%
Other values (132) 15212
45.9%
Space Separator
ValueCountFrequency (%)
307
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 33171
99.1%
Common 307
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 4788
 
14.4%
구 4528
 
13.7%
군 2137
 
6.4%
주 1326
 
4.0%
산 999
 
3.0%
천 964
 
2.9%
성 877
 
2.6%
서 817
 
2.5%
양 771
 
2.3%
남 752
 
2.3%
Other values (132) 15212
45.9%
Common
ValueCountFrequency (%)
307
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 33171
99.1%
ASCII 307
 
0.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 4788
 
14.4%
구 4528
 
13.7%
군 2137
 
6.4%
주 1326
 
4.0%
산 999
 
3.0%
천 964
 
2.9%
성 877
 
2.6%
서 817
 
2.5%
양 771
 
2.3%
남 752
 
2.3%
Other values (132) 15212
45.9%
ASCII
ValueCountFrequency (%)
307
100.0%

화재유형
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
건축,구조물
6356 
기타(쓰레기 화재등)
2009 
자동차,철도차량
1227 
임야
 
382
선박,항공기
 
18

Length

Max length11
Median length6
Mean length7.1003
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row기타(쓰레기 화재등)
2nd row건축,구조물
3rd row자동차,철도차량
4th row임야
5th row건축,구조물

Common Values

ValueCountFrequency (%)
건축,구조물 6356
63.6%
기타(쓰레기 화재등) 2009
 
20.1%
자동차,철도차량 1227
 
12.3%
임야 382
 
3.8%
선박,항공기 18
 
0.2%
위험물,가스제조소등 8
 
0.1%

Length

2024-03-16T13:16:02.124932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T13:16:02.303564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건축,구조물 6356
52.9%
기타(쓰레기 2009
 
16.7%
화재등 2009
 
16.7%
자동차,철도차량 1227
 
10.2%
임야 382
 
3.2%
선박,항공기 18
 
0.1%
위험물,가스제조소등 8
 
0.1%

발화열원대분류
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
작동기기
4582 
담뱃불, 라이터불
1895 
불꽃, 불티
1574 
미상
979 
마찰, 전도, 복사
629 
Other values (4)
 
341

Length

Max length10
Median length9
Mean length5.4742
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row담뱃불, 라이터불
2nd row불꽃, 불티
3rd row담뱃불, 라이터불
4th row담뱃불, 라이터불
5th row불꽃, 불티

Common Values

ValueCountFrequency (%)
작동기기 4582
45.8%
담뱃불, 라이터불 1895
18.9%
불꽃, 불티 1574
 
15.7%
미상 979
 
9.8%
마찰, 전도, 복사 629
 
6.3%
화학적 발화열 148
 
1.5%
기타 144
 
1.4%
자연적 발화열 37
 
0.4%
폭발물, 폭죽 12
 
0.1%

Length

2024-03-16T13:16:02.501863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T13:16:02.670285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
작동기기 4582
30.7%
담뱃불 1895
12.7%
라이터불 1895
12.7%
불꽃 1574
 
10.5%
불티 1574
 
10.5%
미상 979
 
6.6%
마찰 629
 
4.2%
전도 629
 
4.2%
복사 629
 
4.2%
발화열 185
 
1.2%
Other values (5) 353
 
2.4%

발화열원소분류
Categorical

HIGH CORRELATION 

Distinct28
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
전기적 아크(단락)
2428 
담뱃불
1427 
기기 전도,복사열,기기발열
1407 
미상
979 
쓰레기, 논밭두렁
542 
Other values (23)
3217 

Length

Max length14
Median length10
Mean length8.3399
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row담뱃불
2nd row비화
3rd row담뱃불
4th row라이터불, 성냥불
5th row용접, 절단, 연마

Common Values

ValueCountFrequency (%)
전기적 아크(단락) 2428
24.3%
담뱃불 1427
14.3%
기기 전도,복사열,기기발열 1407
14.1%
미상 979
9.8%
쓰레기, 논밭두렁 542
 
5.4%
불꽃, 스파크, 정전기 497
 
5.0%
화염 전도,복사열 362
 
3.6%
라이터불, 성냥불 317
 
3.2%
기타(불꽃,불티) 285
 
2.9%
용접, 절단, 연마 247
 
2.5%
Other values (18) 1509
15.1%

Length

2024-03-16T13:16:02.910004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전기적 2428
14.0%
아크(단락 2428
14.0%
담뱃불 1427
 
8.2%
기기 1407
 
8.1%
전도,복사열,기기발열 1407
 
8.1%
미상 979
 
5.6%
스파크 701
 
4.0%
쓰레기 542
 
3.1%
논밭두렁 542
 
3.1%
정전기 497
 
2.9%
Other values (32) 5042
29.0%

발화요인대분류
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
부주의
4659 
전기적 요인
2623 
기계적 요인
1048 
미상
909 
화학적 요인
 
181
Other values (7)
580 

Length

Max length8
Median length7
Mean length4.111
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부주의 4659
46.6%
전기적 요인 2623
26.2%
기계적 요인 1048
 
10.5%
미상 909
 
9.1%
화학적 요인 181
 
1.8%
기타 143
 
1.4%
교통사고 115
 
1.1%
방화 90
 
0.9%
방화의심 81
 
0.8%
자연적인 요인 71
 
0.7%
Other values (2) 80
 
0.8%

Length

2024-03-16T13:16:03.170009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
부주의 4659
33.5%
요인 3923
28.2%
전기적 2623
18.8%
기계적 1048
 
7.5%
미상 909
 
6.5%
화학적 181
 
1.3%
기타 143
 
1.0%
교통사고 115
 
0.8%
방화 90
 
0.6%
방화의심 81
 
0.6%
Other values (3) 151
 
1.1%

발화요인소분류
Categorical

HIGH CORRELATION 

Distinct49
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
담배꽁초
1448 
미상
909 
미확인단락
872 
과열, 과부하
662 
음식물 조리중
641 
Other values (44)
5468 

Length

Max length21
Median length12
Mean length7.0415
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row담배꽁초
2nd row음식물 조리중
3rd row담배꽁초
4th row논,임야태우기
5th row용접, 절단, 연마

Common Values

ValueCountFrequency (%)
담배꽁초 1448
14.5%
미상 909
 
9.1%
미확인단락 872
 
8.7%
과열, 과부하 662
 
6.6%
음식물 조리중 641
 
6.4%
불씨,불꽃,화원방치 613
 
6.1%
쓰레기 소각 530
 
5.3%
절연열화에 의한 단락 486
 
4.9%
기기(전기, 기계 등) 사용.설치부주의 469
 
4.7%
트래킹에 의한 단락 365
 
3.6%
Other values (39) 3005
30.0%

Length

2024-03-16T13:16:03.356353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
담배꽁초 1448
 
8.7%
의한 1221
 
7.4%
단락 1221
 
7.4%
미상 909
 
5.5%
미확인단락 872
 
5.3%
과열 662
 
4.0%
과부하 662
 
4.0%
음식물 641
 
3.9%
조리중 641
 
3.9%
불씨,불꽃,화원방치 613
 
3.7%
Other values (58) 7718
46.5%

최초착화물대분류
Categorical

Distinct13
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
전기,전자
2461 
종이,목재,건초등
1969 
쓰레기류
1162 
합성수지
1070 
기타
748 
Other values (8)
2590 

Length

Max length15
Median length7
Mean length5.5044
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row쓰레기류
2nd row가연성가스
3rd row종이,목재,건초등
4th row종이,목재,건초등
5th row합성수지

Common Values

ValueCountFrequency (%)
전기,전자 2461
24.6%
종이,목재,건초등 1969
19.7%
쓰레기류 1162
11.6%
합성수지 1070
10.7%
기타 748
 
7.5%
미상 739
 
7.4%
식품 604
 
6.0%
자동차,철도차량,선박,항공기 573
 
5.7%
침구,직물류 322
 
3.2%
위험물등 171
 
1.7%
Other values (3) 181
 
1.8%

Length

2024-03-16T13:16:03.635211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전기,전자 2461
24.6%
종이,목재,건초등 1969
19.7%
쓰레기류 1162
11.6%
합성수지 1070
10.7%
기타 748
 
7.5%
미상 739
 
7.4%
식품 604
 
6.0%
자동차,철도차량,선박,항공기 573
 
5.7%
침구,직물류 322
 
3.2%
위험물등 171
 
1.7%
Other values (3) 181
 
1.8%

최초착화물소분류
Text

Distinct86
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-16T13:16:04.061364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length5.8074
Min length2

Characters and Unicode

Total characters58074
Distinct characters166
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)0.1%

Sample

1st row쓰레기
2nd row프로판가스
3rd row종이
4th row기타(종이,목재,건초등)
5th row발포폴리스티렌
ValueCountFrequency (%)
전선피복 1348
 
9.1%
쓰레기 972
 
6.6%
기타 968
 
6.5%
플라스틱 754
 
5.1%
pvc 754
 
5.1%
비닐 754
 
5.1%
장판 754
 
5.1%
미상 739
 
5.0%
전자기기 645
 
4.3%
종이 565
 
3.8%
Other values (93) 6575
44.3%
2024-03-16T13:16:04.724316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 5133
 
8.8%
, 4962
 
8.5%
4828
 
8.3%
전 2902
 
5.0%
타 1943
 
3.3%
선 1698
 
2.9%
피 1348
 
2.3%
복 1348
 
2.3%
스 1309
 
2.3%
판 1206
 
2.1%
Other values (156) 31397
54.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 43780
75.4%
Other Punctuation 4962
 
8.5%
Space Separator 4828
 
8.3%
Uppercase Letter 2262
 
3.9%
Close Punctuation 1100
 
1.9%
Open Punctuation 1100
 
1.9%
Decimal Number 42
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 5133
 
11.7%
전 2902
 
6.6%
타 1943
 
4.4%
선 1698
 
3.9%
피 1348
 
3.1%
복 1348
 
3.1%
스 1309
 
3.0%
판 1206
 
2.8%
이 1154
 
2.6%
레 1025
 
2.3%
Other values (143) 24714
56.5%
Decimal Number
ValueCountFrequency (%)
4 34
81.0%
1 2
 
4.8%
2 2
 
4.8%
3 2
 
4.8%
6 1
 
2.4%
5 1
 
2.4%
Uppercase Letter
ValueCountFrequency (%)
P 754
33.3%
C 754
33.3%
V 754
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4962
100.0%
Space Separator
ValueCountFrequency (%)
4828
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1100
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1100
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 43780
75.4%
Common 12032
 
20.7%
Latin 2262
 
3.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 5133
 
11.7%
전 2902
 
6.6%
타 1943
 
4.4%
선 1698
 
3.9%
피 1348
 
3.1%
복 1348
 
3.1%
스 1309
 
3.0%
판 1206
 
2.8%
이 1154
 
2.6%
레 1025
 
2.3%
Other values (143) 24714
56.5%
Common
ValueCountFrequency (%)
, 4962
41.2%
4828
40.1%
) 1100
 
9.1%
( 1100
 
9.1%
4 34
 
0.3%
1 2
 
< 0.1%
2 2
 
< 0.1%
3 2
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%
Latin
ValueCountFrequency (%)
P 754
33.3%
C 754
33.3%
V 754
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 43780
75.4%
ASCII 14294
 
24.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 5133
 
11.7%
전 2902
 
6.6%
타 1943
 
4.4%
선 1698
 
3.9%
피 1348
 
3.1%
복 1348
 
3.1%
스 1309
 
3.0%
판 1206
 
2.8%
이 1154
 
2.6%
레 1025
 
2.3%
Other values (143) 24714
56.5%
ASCII
ValueCountFrequency (%)
, 4962
34.7%
4828
33.8%
) 1100
 
7.7%
( 1100
 
7.7%
P 754
 
5.3%
C 754
 
5.3%
V 754
 
5.3%
4 34
 
0.2%
1 2
 
< 0.1%
2 2
 
< 0.1%
Other values (3) 4
 
< 0.1%

인명피해(명)소계
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0642
Minimum0
Maximum8
Zeros9523
Zeros (%)95.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-16T13:16:04.891964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum8
Range8
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.35368188
Coefficient of variation (CV)5.5090635
Kurtosis134.94317
Mean0.0642
Median Absolute Deviation (MAD)0
Skewness9.569385
Sum642
Variance0.12509087
MonotonicityNot monotonic
2024-03-16T13:16:05.026104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 9523
95.2%
1 388
 
3.9%
2 53
 
0.5%
3 21
 
0.2%
6 4
 
< 0.1%
5 4
 
< 0.1%
4 3
 
< 0.1%
7 3
 
< 0.1%
8 1
 
< 0.1%
ValueCountFrequency (%)
0 9523
95.2%
1 388
 
3.9%
2 53
 
0.5%
3 21
 
0.2%
4 3
 
< 0.1%
5 4
 
< 0.1%
6 4
 
< 0.1%
7 3
 
< 0.1%
8 1
 
< 0.1%
ValueCountFrequency (%)
8 1
 
< 0.1%
7 3
 
< 0.1%
6 4
 
< 0.1%
5 4
 
< 0.1%
4 3
 
< 0.1%
3 21
 
0.2%
2 53
 
0.5%
1 388
 
3.9%
0 9523
95.2%

사망
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
9928 
1
 
67
2
 
5

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 9928
99.3%
1 67
 
0.7%
2 5
 
0.1%

Length

2024-03-16T13:16:05.217585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T13:16:05.410017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 9928
99.3%
1 67
 
0.7%
2 5
 
< 0.1%

부상
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0565
Minimum0
Maximum8
Zeros9584
Zeros (%)95.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-16T13:16:05.567888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum8
Range8
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.33692596
Coefficient of variation (CV)5.9632913
Kurtosis158.51786
Mean0.0565
Median Absolute Deviation (MAD)0
Skewness10.432039
Sum565
Variance0.1135191
MonotonicityNot monotonic
2024-03-16T13:16:05.715927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 9584
95.8%
1 338
 
3.4%
2 45
 
0.4%
3 19
 
0.2%
6 4
 
< 0.1%
4 3
 
< 0.1%
5 3
 
< 0.1%
7 3
 
< 0.1%
8 1
 
< 0.1%
ValueCountFrequency (%)
0 9584
95.8%
1 338
 
3.4%
2 45
 
0.4%
3 19
 
0.2%
4 3
 
< 0.1%
5 3
 
< 0.1%
6 4
 
< 0.1%
7 3
 
< 0.1%
8 1
 
< 0.1%
ValueCountFrequency (%)
8 1
 
< 0.1%
7 3
 
< 0.1%
6 4
 
< 0.1%
5 3
 
< 0.1%
4 3
 
< 0.1%
3 19
 
0.2%
2 45
 
0.4%
1 338
 
3.4%
0 9584
95.8%

재산피해소계
Real number (ℝ)

SKEWED  ZEROS 

Distinct4118
Distinct (%)41.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18956.159
Minimum0
Maximum17323532
Zeros764
Zeros (%)7.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-16T13:16:05.929867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q196
median550
Q33602.25
95-th percentile39158.95
Maximum17323532
Range17323532
Interquartile range (IQR)3506.25

Descriptive statistics

Standard deviation248893.05
Coefficient of variation (CV)13.12993
Kurtosis2570.6033
Mean18956.159
Median Absolute Deviation (MAD)547
Skewness43.53431
Sum1.8956159 × 108
Variance6.1947749 × 1010
MonotonicityNot monotonic
2024-03-16T13:16:06.351997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 764
 
7.6%
11 140
 
1.4%
110 97
 
1.0%
55 73
 
0.7%
550 72
 
0.7%
1 67
 
0.7%
220 56
 
0.6%
330 54
 
0.5%
1100 48
 
0.5%
5 44
 
0.4%
Other values (4108) 8585
85.9%
ValueCountFrequency (%)
0 764
7.6%
1 67
 
0.7%
2 33
 
0.3%
3 33
 
0.3%
4 21
 
0.2%
5 44
 
0.4%
6 28
 
0.3%
7 17
 
0.2%
8 24
 
0.2%
9 33
 
0.3%
ValueCountFrequency (%)
17323532 1
< 0.1%
7709344 1
< 0.1%
6789810 1
< 0.1%
6005834 1
< 0.1%
5536104 1
< 0.1%
4119835 1
< 0.1%
4103880 1
< 0.1%
3949060 1
< 0.1%
3109855 1
< 0.1%
2886858 1
< 0.1%

장소대분류
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
주거
2707 
기타
2009 
자동차,철도차량
1227 
산업시설
1205 
생활서비스
974 
Other values (9)
1878 

Length

Max length9
Median length2
Mean length3.8716
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row기타
2nd row주거
3rd row자동차,철도차량
4th row임야
5th row산업시설

Common Values

ValueCountFrequency (%)
주거 2707
27.1%
기타 2009
20.1%
자동차,철도차량 1227
12.3%
산업시설 1205
12.0%
생활서비스 974
 
9.7%
판매,업무시설 656
 
6.6%
기타서비스 485
 
4.9%
임야 382
 
3.8%
의료,복지시설 106
 
1.1%
집합시설 91
 
0.9%
Other values (4) 158
 
1.6%

Length

2024-03-16T13:16:06.624449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
주거 2707
27.1%
기타 2009
20.1%
자동차,철도차량 1227
12.3%
산업시설 1205
12.0%
생활서비스 974
 
9.7%
판매,업무시설 656
 
6.6%
기타서비스 485
 
4.9%
임야 382
 
3.8%
의료,복지시설 106
 
1.1%
집합시설 91
 
0.9%
Other values (4) 158
 
1.6%

장소중분류
Categorical

HIGH CORRELATION 

Distinct45
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
야외
1938 
단독주택
1350 
공동주택
1222 
자동차
1118 
음식점
684 
Other values (40)
3688 

Length

Max length7
Median length6
Mean length3.4335
Min length2

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

1st row야외
2nd row단독주택
3rd row자동차
4th row들불
5th row작업장

Common Values

ValueCountFrequency (%)
야외 1938
19.4%
단독주택 1350
13.5%
공동주택 1222
12.2%
자동차 1118
11.2%
음식점 684
 
6.8%
공장시설 562
 
5.6%
기타건축물 485
 
4.9%
일반업무 296
 
3.0%
창고시설 290
 
2.9%
들불 243
 
2.4%
Other values (35) 1812
18.1%

Length

2024-03-16T13:16:06.788283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
야외 1938
19.4%
단독주택 1350
13.5%
공동주택 1222
12.2%
자동차 1118
11.2%
음식점 684
 
6.8%
공장시설 562
 
5.6%
기타건축물 485
 
4.9%
일반업무 296
 
3.0%
창고시설 290
 
2.9%
들불 243
 
2.4%
Other values (35) 1812
18.1%

장소소분류
Text

Distinct256
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-16T13:16:07.162065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length15
Mean length4.7939
Min length1

Characters and Unicode

Total characters47939
Distinct characters287
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)0.5%

Sample

1st row쓰레기
2nd row다가구주택
3rd row승용자동차
4th row논밭두렁
5th row공업사
ValueCountFrequency (%)
기타 1256
 
9.8%
기타야외 889
 
6.9%
단독주택 889
 
6.9%
쓰레기 791
 
6.2%
아파트 760
 
5.9%
승용자동차 540
 
4.2%
건축물 467
 
3.6%
화물자동차 397
 
3.1%
다가구주택 352
 
2.7%
다세대주택 287
 
2.2%
Other values (278) 6197
48.3%
2024-03-16T13:16:07.834828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 3465
 
7.2%
2825
 
5.9%
타 2183
 
4.6%
주 2050
 
4.3%
택 1902
 
4.0%
물 1167
 
2.4%
동 1165
 
2.4%
차 1073
 
2.2%
자 1064
 
2.2%
야 975
 
2.0%
Other values (277) 30070
62.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 44002
91.8%
Space Separator 2825
 
5.9%
Other Punctuation 548
 
1.1%
Close Punctuation 271
 
0.6%
Open Punctuation 271
 
0.6%
Uppercase Letter 22
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 3465
 
7.9%
타 2183
 
5.0%
주 2050
 
4.7%
택 1902
 
4.3%
물 1167
 
2.7%
동 1165
 
2.6%
차 1073
 
2.4%
자 1064
 
2.4%
야 975
 
2.2%
트 918
 
2.1%
Other values (267) 28040
63.7%
Uppercase Letter
ValueCountFrequency (%)
C 6
27.3%
P 6
27.3%
S 5
22.7%
A 5
22.7%
Other Punctuation
ValueCountFrequency (%)
, 539
98.4%
/ 5
 
0.9%
. 4
 
0.7%
Space Separator
ValueCountFrequency (%)
2825
100.0%
Close Punctuation
ValueCountFrequency (%)
) 271
100.0%
Open Punctuation
ValueCountFrequency (%)
( 271
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 44002
91.8%
Common 3915
 
8.2%
Latin 22
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 3465
 
7.9%
타 2183
 
5.0%
주 2050
 
4.7%
택 1902
 
4.3%
물 1167
 
2.7%
동 1165
 
2.6%
차 1073
 
2.4%
자 1064
 
2.4%
야 975
 
2.2%
트 918
 
2.1%
Other values (267) 28040
63.7%
Common
ValueCountFrequency (%)
2825
72.2%
, 539
 
13.8%
) 271
 
6.9%
( 271
 
6.9%
/ 5
 
0.1%
. 4
 
0.1%
Latin
ValueCountFrequency (%)
C 6
27.3%
P 6
27.3%
S 5
22.7%
A 5
22.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 44002
91.8%
ASCII 3937
 
8.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 3465
 
7.9%
타 2183
 
5.0%
주 2050
 
4.7%
택 1902
 
4.3%
물 1167
 
2.7%
동 1165
 
2.6%
차 1073
 
2.4%
자 1064
 
2.4%
야 975
 
2.2%
트 918
 
2.1%
Other values (267) 28040
63.7%
ASCII
ValueCountFrequency (%)
2825
71.8%
, 539
 
13.7%
) 271
 
6.9%
( 271
 
6.9%
C 6
 
0.2%
P 6
 
0.2%
S 5
 
0.1%
/ 5
 
0.1%
A 5
 
0.1%
. 4
 
0.1%

Interactions

2024-03-16T13:15:58.651190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:15:57.247666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:15:58.116712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:15:58.815626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:15:57.452271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:15:58.268291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:15:58.987170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:15:57.624556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:15:58.469910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-16T13:16:07.992460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시도화재유형발화열원대분류발화열원소분류발화요인대분류발화요인소분류최초착화물대분류최초착화물소분류인명피해(명)소계사망부상재산피해소계장소대분류장소중분류
시도1.0000.2430.2740.3410.2270.4050.2720.3960.0160.0320.0000.0350.2920.411
화재유형0.2431.0000.4000.5370.5350.6360.6270.7540.0760.0580.0720.0001.0001.000
발화열원대분류0.2740.4001.0001.0000.8300.9410.6830.7890.1180.1850.0910.0310.3910.505
발화열원소분류0.3410.5371.0001.0000.8810.9530.7700.8310.0990.1620.0650.0000.5710.541
발화요인대분류0.2270.5350.8300.8811.0001.0000.7140.8280.2390.2590.2260.0550.4170.512
발화요인소분류0.4050.6360.9410.9531.0001.0000.8560.8940.3120.2170.3030.1520.6230.598
최초착화물대분류0.2720.6270.6830.7700.7140.8561.0001.0000.2060.2010.1870.0500.5820.667
최초착화물소분류0.3960.7540.7890.8310.8280.8941.0001.0000.2790.3020.2570.0000.7230.712
인명피해(명)소계0.0160.0760.1180.0990.2390.3120.2060.2791.0000.6340.9990.0000.0880.030
사망0.0320.0580.1850.1620.2590.2170.2010.3020.6341.0000.1770.0000.0930.084
부상0.0000.0720.0910.0650.2260.3030.1870.2570.9990.1771.0000.0000.0700.000
재산피해소계0.0350.0000.0310.0000.0550.1520.0500.0000.0000.0000.0001.0000.0720.169
장소대분류0.2921.0000.3910.5710.4170.6230.5820.7230.0880.0930.0700.0721.0001.000
장소중분류0.4111.0000.5050.5410.5120.5980.6670.7120.0300.0840.0000.1691.0001.000
2024-03-16T13:16:08.299347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
화재유형최초착화물대분류발화열원대분류시도장소대분류발화요인소분류장소중분류발화열원소분류사망발화요인대분류
화재유형1.0000.3720.2110.1171.0000.3300.9980.2730.0240.238
최초착화물대분류0.3721.0000.3770.0980.2530.4560.2660.3670.1150.367
발화열원대분류0.2110.3771.0000.1130.1760.7050.1930.9990.0820.545
시도0.1170.0980.1131.0000.1040.1180.1210.1030.0170.084
장소대분류1.0000.2530.1760.1041.0000.2240.9980.1850.0510.170
발화요인소분류0.3300.4560.7050.1180.2241.0000.1360.5340.1080.998
장소중분류0.9980.2660.1930.1210.9980.1361.0000.1400.0380.185
발화열원소분류0.2730.3670.9990.1030.1850.5340.1401.0000.0820.529
사망0.0240.1150.0820.0170.0510.1080.0380.0821.0000.120
발화요인대분류0.2380.3670.5450.0840.1700.9980.1850.5290.1201.000
2024-03-16T13:16:08.948992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인명피해(명)소계부상재산피해소계시도화재유형발화열원대분류발화열원소분류발화요인대분류발화요인소분류최초착화물대분류사망장소대분류장소중분류
인명피해(명)소계1.0000.9320.1390.0060.0380.0380.0370.1030.1170.0890.3520.0370.010
부상0.9321.0000.1200.0000.0360.0290.0240.0970.1130.0810.0780.0290.000
재산피해소계0.1390.1201.0000.0160.0000.0150.0000.0220.0650.0250.0000.0350.072
시도0.0060.0000.0161.0000.1170.1130.1030.0840.1180.0980.0170.1040.121
화재유형0.0380.0360.0000.1171.0000.2110.2730.2380.3300.3720.0241.0000.998
발화열원대분류0.0380.0290.0150.1130.2111.0000.9990.5450.7050.3770.0820.1760.193
발화열원소분류0.0370.0240.0000.1030.2730.9991.0000.5290.5340.3670.0820.1850.140
발화요인대분류0.1030.0970.0220.0840.2380.5450.5291.0000.9980.3670.1200.1700.185
발화요인소분류0.1170.1130.0650.1180.3300.7050.5340.9981.0000.4560.1080.2240.136
최초착화물대분류0.0890.0810.0250.0980.3720.3770.3670.3670.4561.0000.1150.2530.266
사망0.3520.0780.0000.0170.0240.0820.0820.1200.1080.1151.0000.0510.038
장소대분류0.0370.0290.0350.1041.0000.1760.1850.1700.2240.2530.0511.0000.998
장소중분류0.0100.0000.0720.1210.9980.1930.1400.1850.1360.2660.0380.9981.000

Missing values

2024-03-16T13:15:59.226955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-16T13:15:59.685114image/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

일시시도시_군_구화재유형발화열원대분류발화열원소분류발화요인대분류발화요인소분류최초착화물대분류최초착화물소분류인명피해(명)소계사망부상재산피해소계장소대분류장소중분류장소소분류
250722023-08-08 23:44서울특별시송파구기타(쓰레기 화재등)담뱃불, 라이터불담뱃불부주의담배꽁초쓰레기류쓰레기000165기타야외쓰레기
236192023-07-27 11:27경상남도진주시건축,구조물불꽃, 불티비화부주의음식물 조리중가연성가스프로판가스101476주거단독주택다가구주택
162602023-05-10 12:29강원특별자치도평창군자동차,철도차량담뱃불, 라이터불담뱃불부주의담배꽁초종이,목재,건초등종이000330자동차,철도차량자동차승용자동차
325872023-11-03 10:38경상남도사천시임야담뱃불, 라이터불라이터불, 성냥불부주의논,임야태우기종이,목재,건초등기타(종이,목재,건초등)000100임야들불논밭두렁
58312023-02-18 13:45경기도김포시건축,구조물불꽃, 불티용접, 절단, 연마부주의용접, 절단, 연마합성수지발포폴리스티렌0003159산업시설작업장공업사
40842023-02-03 17:06경기도성남시분당구건축,구조물작동기기기기 전도,복사열,기기발열기계적 요인자동제어 실패식품음식물000274주거공동주택아파트
4122023-01-04 07:50대구광역시서구기타(쓰레기 화재등)불꽃, 불티모닥불, 연탄, 숯부주의가연물 근접방치쓰레기류쓰레기0000기타야외쓰레기
121612023-04-01 22:57경기도과천시건축,구조물작동기기기타(작동기기)부주의음식물 조리중식품튀김유000544주거단독주택다가구주택
162172023-05-10 00:32대구광역시서구자동차,철도차량미상미상미상미상미상미상0008088자동차,철도차량자동차화물자동차
34122023-01-29 19:10전북특별자치도고창군건축,구조물마찰, 전도, 복사화염 전도,복사열부주의기기(전기, 기계 등) 사용.설치부주의합성수지발포폴리스티렌10127440주거단독주택단독주택
일시시도시_군_구화재유형발화열원대분류발화열원소분류발화요인대분류발화요인소분류최초착화물대분류최초착화물소분류인명피해(명)소계사망부상재산피해소계장소대분류장소중분류장소소분류
237962023-07-29 01:43울산광역시남구기타(쓰레기 화재등)작동기기불꽃, 스파크, 정전기전기적 요인기타(전기적요인)기타기타000660기타야외기타야외
113932023-03-28 05:16경기도안성시건축,구조물담뱃불, 라이터불담뱃불부주의담배꽁초종이,목재,건초등톱밥0002333산업시설동식물시설기타 동식물시설
50152023-02-10 02:40경기도광주시건축,구조물미상미상미상미상미상미상220738593산업시설공장시설그 밖의 공업
267452023-08-27 13:23전라남도곡성군건축,구조물불꽃, 불티용접, 절단, 연마부주의용접, 절단, 연마쓰레기류분진00088356산업시설동식물시설기타 동식물시설
318212023-10-26 07:59충청북도제천시건축,구조물작동기기기기 전도,복사열,기기발열기계적 요인과열, 과부하합성수지기타(합성수지)0005005산업시설공장시설금속기계 및 기구공업
30302023-01-26 21:56경기도파주시건축,구조물담뱃불, 라이터불담뱃불부주의담배꽁초합성수지플라스틱, PVC, 비닐, 장판0001361판매,업무시설일반업무일반빌딩
49562023-02-09 17:22전북특별자치도군산시기타(쓰레기 화재등)불꽃, 불티모닥불, 연탄, 숯부주의불씨,불꽃,화원방치종이,목재,건초등건초000594기타야외쓰레기
359712023-12-04 16:38경기도안산시상록구건축,구조물작동기기기기 전도,복사열,기기발열기계적 요인과열, 과부하합성수지플라스틱, PVC, 비닐, 장판000178집합시설운동시설체육도장(태권도, 검도 등)
318662023-10-26 17:54경상남도밀양시기타(쓰레기 화재등)불꽃, 불티쓰레기, 논밭두렁부주의쓰레기 소각쓰레기류기타 쓰레기0000기타야외쓰레기
47762023-02-08 14:51경기도안성시건축,구조물담뱃불, 라이터불담뱃불부주의기타(부주의)미상미상80816111주거공동주택아파트