Overview

Dataset statistics

Number of variables27
Number of observations79
Missing cells2
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory17.5 KiB
Average record size in memory226.7 B

Variable types

DateTime1
Categorical18
Text4
Numeric4

Dataset

Description철도안전법 및 하위법령에 의거하여 철도운영자와 시설관리자가 철도안전정보종합관리시스템으로 보고한 철도사고 목록정보 입니다.철도사고 발생일시, 원인, 노선, 사상자 현황이 포함되어 있습니다.
Author국토교통부
URLhttps://www.data.go.kr/data/15123062/fileData.do

Alerts

사고 종류 has constant value ""Constant
경상 has constant value ""Constant
사상자보상액 has constant value ""Constant
부상(중상) is highly imbalanced (50.7%)Imbalance
행정구역 has 2 (2.5%) missing valuesMissing
총 피해액(백만원) has 48 (60.8%) zerosZeros
재산피해액 has 68 (86.1%) zerosZeros
기타피해액 has 54 (68.4%) zerosZeros
합계최대지연시간(분) has 42 (53.2%) zerosZeros

Reproduction

Analysis started2023-12-12 07:11:06.050612
Analysis finished2023-12-12 07:11:06.477817
Duration0.43 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일시
Date

Distinct72
Distinct (%)91.1%
Missing0
Missing (%)0.0%
Memory size764.0 B
Minimum2022-01-04 00:00:00
Maximum2022-12-20 00:00:00
2023-12-12T16:11:06.539069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:11:06.681582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

요일
Categorical

Distinct7
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Memory size764.0 B
목
14 
토
13 
일
11 
수
11 
화
10 
Other values (2)
20 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row화
2nd row일
3rd row수
4th row금
5th row화

Common Values

ValueCountFrequency (%)
목 14
17.7%
토 13
16.5%
일 11
13.9%
수 11
13.9%
화 10
12.7%
금 10
12.7%
월 10
12.7%

Length

2023-12-12T16:11:06.785507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:11:06.882916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
목 14
17.7%
토 13
16.5%
일 11
13.9%
수 11
13.9%
화 10
12.7%
금 10
12.7%
월 10
12.7%

철도구분
Categorical

Distinct3
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size764.0 B
일반철도
45 
도시철도
26 
고속철도
8 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row일반철도
2nd row도시철도
3rd row일반철도
4th row일반철도
5th row도시철도

Common Values

ValueCountFrequency (%)
일반철도 45
57.0%
도시철도 26
32.9%
고속철도 8
 
10.1%

Length

2023-12-12T16:11:06.988979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:11:07.066757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반철도 45
57.0%
도시철도 26
32.9%
고속철도 8
 
10.1%

사고 종류
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size764.0 B
사고
79 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사고 79
100.0%

Length

2023-12-12T16:11:07.148917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:11:07.221103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사고 79
100.0%

철도사고 종류
Categorical

Distinct10
Distinct (%)12.7%
Missing0
Missing (%)0.0%
Memory size764.0 B
교통사상사고-공중
24 
충돌ㆍ탈선ㆍ화재-탈선
18 
철도교통사고-건널목사고
13 
교통사상사고-직원
8 
안전사상사고-직원
4 
Other values (5)
12 

Length

Max length13
Median length9
Mean length10.151899
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row충돌ㆍ탈선ㆍ화재-탈선
2nd row교통사상사고-공중
3rd row충돌ㆍ탈선ㆍ화재-탈선
4th row교통사상사고-공중
5th row교통사상사고-공중

Common Values

ValueCountFrequency (%)
교통사상사고-공중 24
30.4%
충돌ㆍ탈선ㆍ화재-탈선 18
22.8%
철도교통사고-건널목사고 13
16.5%
교통사상사고-직원 8
 
10.1%
안전사상사고-직원 4
 
5.1%
철도안전사고-철도화재사고 3
 
3.8%
안전사상사고-공중 3
 
3.8%
충돌ㆍ탈선ㆍ화재-충돌 2
 
2.5%
교통사상사고-여객 2
 
2.5%
안전사상사고-여객 2
 
2.5%

Length

2023-12-12T16:11:07.309891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:11:07.413219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
교통사상사고-공중 24
30.4%
충돌ㆍ탈선ㆍ화재-탈선 18
22.8%
철도교통사고-건널목사고 13
16.5%
교통사상사고-직원 8
 
10.1%
안전사상사고-직원 4
 
5.1%
철도안전사고-철도화재사고 3
 
3.8%
안전사상사고-공중 3
 
3.8%
충돌ㆍ탈선ㆍ화재-충돌 2
 
2.5%
교통사상사고-여객 2
 
2.5%
안전사상사고-여객 2
 
2.5%

주원인
Categorical

Distinct37
Distinct (%)46.8%
Missing0
Missing (%)0.0%
Memory size764.0 B
통행자(자동차)-일단정지 무시횡단
13 
공중(교통)-열차에 뛰어듦(자살)
10 
공중(교통)-선로무단통행(자살)
8 
공중(교통)-선로무단통행
5 
직원(교통)-기타
 
3
Other values (32)
40 

Length

Max length20
Median length17
Mean length13.632911
Min length5

Unique

Unique24 ?
Unique (%)30.4%

Sample

1st row운전취급자-기타
2nd row공중(교통)-선로무단통행(자살)
3rd row운전취급자-선로전환잘못
4th row공중(교통)-선로무단통행
5th row공중(교통)-선로무단통행

Common Values

ValueCountFrequency (%)
통행자(자동차)-일단정지 무시횡단 13
16.5%
공중(교통)-열차에 뛰어듦(자살) 10
 
12.7%
공중(교통)-선로무단통행(자살) 8
 
10.1%
공중(교통)-선로무단통행 5
 
6.3%
직원(교통)-기타 3
 
3.8%
여객(안전)-에스컬레이터 추락/넘어짐 2
 
2.5%
직원(교통)-열차방호소홀 2
 
2.5%
차량-주행장치고장 2
 
2.5%
직원(교통)-부주의한 행동 2
 
2.5%
운전취급자-운전취급잘못 2
 
2.5%
Other values (27) 30
38.0%

Length

2023-12-12T16:11:07.540413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
통행자(자동차)-일단정지 13
 
12.0%
무시횡단 13
 
12.0%
공중(교통)-열차에 10
 
9.3%
뛰어듦(자살 10
 
9.3%
공중(교통)-선로무단통행(자살 8
 
7.4%
공중(교통)-선로무단통행 5
 
4.6%
직원(교통)-기타 3
 
2.8%
추락/넘어짐 3
 
2.8%
행동 2
 
1.9%
공중(안전)-전기감전 2
 
1.9%
Other values (32) 39
36.1%

근본원인별 그룹
Categorical

Distinct2
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size764.0 B
인적요인
68 
기술적요인
11 

Length

Max length5
Median length4
Mean length4.1392405
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
인적요인 68
86.1%
기술적요인 11
 
13.9%

Length

2023-12-12T16:11:07.636898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:11:07.721804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인적요인 68
86.1%
기술적요인 11
 
13.9%

근본원인별 원인
Categorical

Distinct12
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Memory size764.0 B
공중
40 
작업자
9 
역무원
5 
기타설비
 
4
기관사(운전자)
 
4
Other values (7)
17 

Length

Max length24
Median length2
Mean length3.9746835
Min length2

Unique

Unique1 ?
Unique (%)1.3%

Sample

1st row운전취급자(신호기/선로전환기/조작판 취급자)
2nd row공중
3rd row운전취급자(신호기/선로전환기/조작판 취급자)
4th row공중
5th row공중

Common Values

ValueCountFrequency (%)
공중 40
50.6%
작업자 9
 
11.4%
역무원 5
 
6.3%
기타설비 4
 
5.1%
기관사(운전자) 4
 
5.1%
운전취급자(신호기/선로전환기/조작판 취급자) 3
 
3.8%
선로및구조물 3
 
3.8%
열차차량설비 3
 
3.8%
여객 3
 
3.8%
승무원(기관사외) 2
 
2.5%
Other values (2) 3
 
3.8%

Length

2023-12-12T16:11:07.817948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
공중 40
48.8%
작업자 9
 
11.0%
역무원 5
 
6.1%
기타설비 4
 
4.9%
기관사(운전자 4
 
4.9%
운전취급자(신호기/선로전환기/조작판 3
 
3.7%
취급자 3
 
3.7%
선로및구조물 3
 
3.7%
열차차량설비 3
 
3.7%
여객 3
 
3.7%
Other values (3) 5
 
6.1%

근본원인별 상세
Categorical

Distinct9
Distinct (%)11.4%
Missing0
Missing (%)0.0%
Memory size764.0 B
부주의/오류
24 
자살
18 
불법행위
17 
기타
9 
단품불량/부품노후
4 
Other values (4)
7 

Length

Max length9
Median length6
Mean length4.2151899
Min length2

Unique

Unique2 ?
Unique (%)2.5%

Sample

1st row부주의/오류
2nd row자살
3rd row부주의/오류
4th row불법행위
5th row불법행위

Common Values

ValueCountFrequency (%)
부주의/오류 24
30.4%
자살 18
22.8%
불법행위 17
21.5%
기타 9
 
11.4%
단품불량/부품노후 4
 
5.1%
규정위반 3
 
3.8%
도입/설치 2
 
2.5%
유지관리 1
 
1.3%
설계/제작 1
 
1.3%

Length

2023-12-12T16:11:07.927383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:11:08.041451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부주의/오류 24
30.4%
자살 18
22.8%
불법행위 17
21.5%
기타 9
 
11.4%
단품불량/부품노후 4
 
5.1%
규정위반 3
 
3.8%
도입/설치 2
 
2.5%
유지관리 1
 
1.3%
설계/제작 1
 
1.3%

행정구역
Text

MISSING 

Distinct66
Distinct (%)85.7%
Missing2
Missing (%)2.5%
Memory size764.0 B
2023-12-12T16:11:08.410386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length36
Mean length20.077922
Min length3

Characters and Unicode

Total characters1546
Distinct characters150
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

Unique57 ?
Unique (%)74.0%

Sample

1st row강원도 동해시 동해역길 69
2nd row경기도 수원시 덕영대로 924
3rd row전라북도 익산시 익산대로 153
4th row강원도 삼척시 신기면 신기역길 89
5th row경기도 의왕시 철도박물관로 66
ValueCountFrequency (%)
경기도 14
 
3.9%
서울 12
 
3.3%
경상북도 9
 
2.5%
동구 6
 
1.7%
강원도 6
 
1.7%
전라남도 5
 
1.4%
의왕시 4
 
1.1%
부산광역시 4
 
1.1%
215 4
 
1.1%
대전광역시 4
 
1.1%
Other values (229) 294
81.2%
2023-12-12T16:11:09.027246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
301
 
19.5%
1 68
 
4.4%
로 58
 
3.8%
시 52
 
3.4%
도 47
 
3.0%
2 44
 
2.8%
구 38
 
2.5%
동 36
 
2.3%
대 34
 
2.2%
역 31
 
2.0%
Other values (140) 837
54.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 916
59.2%
Space Separator 301
 
19.5%
Decimal Number 276
 
17.9%
Dash Punctuation 29
 
1.9%
Close Punctuation 12
 
0.8%
Open Punctuation 12
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 58
 
6.3%
시 52
 
5.7%
도 47
 
5.1%
구 38
 
4.1%
동 36
 
3.9%
대 34
 
3.7%
역 31
 
3.4%
경 28
 
3.1%
남 18
 
2.0%
원 17
 
1.9%
Other values (126) 557
60.8%
Decimal Number
ValueCountFrequency (%)
1 68
24.6%
2 44
15.9%
5 28
10.1%
3 28
10.1%
6 23
 
8.3%
9 23
 
8.3%
7 19
 
6.9%
0 18
 
6.5%
4 16
 
5.8%
8 9
 
3.3%
Space Separator
ValueCountFrequency (%)
301
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 916
59.2%
Common 630
40.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 58
 
6.3%
시 52
 
5.7%
도 47
 
5.1%
구 38
 
4.1%
동 36
 
3.9%
대 34
 
3.7%
역 31
 
3.4%
경 28
 
3.1%
남 18
 
2.0%
원 17
 
1.9%
Other values (126) 557
60.8%
Common
ValueCountFrequency (%)
301
47.8%
1 68
 
10.8%
2 44
 
7.0%
- 29
 
4.6%
5 28
 
4.4%
3 28
 
4.4%
6 23
 
3.7%
9 23
 
3.7%
7 19
 
3.0%
0 18
 
2.9%
Other values (4) 49
 
7.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 916
59.2%
ASCII 630
40.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
301
47.8%
1 68
 
10.8%
2 44
 
7.0%
- 29
 
4.6%
5 28
 
4.4%
3 28
 
4.4%
6 23
 
3.7%
9 23
 
3.7%
7 19
 
3.0%
0 18
 
2.9%
Other values (4) 49
 
7.8%
Hangul
ValueCountFrequency (%)
로 58
 
6.3%
시 52
 
5.7%
도 47
 
5.1%
구 38
 
4.1%
동 36
 
3.9%
대 34
 
3.7%
역 31
 
3.4%
경 28
 
3.1%
남 18
 
2.0%
원 17
 
1.9%
Other values (126) 557
60.8%

총피해명
Categorical

Distinct5
Distinct (%)6.3%
Missing0
Missing (%)0.0%
Memory size764.0 B
1
47 
0
27 
2
 
3
12
 
1
3
 
1

Length

Max length2
Median length1
Mean length1.0126582
Min length1

Unique

Unique2 ?
Unique (%)2.5%

Sample

1st row0
2nd row1
3rd row0
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 47
59.5%
0 27
34.2%
2 3
 
3.8%
12 1
 
1.3%
3 1
 
1.3%

Length

2023-12-12T16:11:09.237612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:11:09.375977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 47
59.5%
0 27
34.2%
2 3
 
3.8%
12 1
 
1.3%
3 1
 
1.3%

사망
Categorical

Distinct3
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size764.0 B
0
52 
1
26 
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.3%

Sample

1st row0
2nd row1
3rd row0
4th row1
5th row1

Common Values

ValueCountFrequency (%)
0 52
65.8%
1 26
32.9%
2 1
 
1.3%

Length

2023-12-12T16:11:09.901563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:11:10.060862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 52
65.8%
1 26
32.9%
2 1
 
1.3%

부상(중상)
Categorical

IMBALANCE 

Distinct5
Distinct (%)6.3%
Missing0
Missing (%)0.0%
Memory size764.0 B
0
53 
1
23 
12
 
1
2
 
1
3
 
1

Length

Max length2
Median length1
Mean length1.0126582
Min length1

Unique

Unique3 ?
Unique (%)3.8%

Sample

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

Common Values

ValueCountFrequency (%)
0 53
67.1%
1 23
29.1%
12 1
 
1.3%
2 1
 
1.3%
3 1
 
1.3%

Length

2023-12-12T16:11:10.198540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:11:10.384936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 53
67.1%
1 23
29.1%
12 1
 
1.3%
2 1
 
1.3%
3 1
 
1.3%

경상
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size764.0 B
0
79 

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 79
100.0%

Length

2023-12-12T16:11:10.541610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:11:10.672040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 79
100.0%

총 피해액(백만원)
Real number (ℝ)

ZEROS 

Distinct32
Distinct (%)40.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39.060363
Minimum0
Maximum1665.4
Zeros48
Zeros (%)60.8%
Negative0
Negative (%)0.0%
Memory size843.0 B
2023-12-12T16:11:10.821472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.64585
95-th percentile38.473331
Maximum1665.4
Range1665.4
Interquartile range (IQR)0.64585

Descriptive statistics

Standard deviation210.36013
Coefficient of variation (CV)5.3855139
Kurtosis49.139247
Mean39.060363
Median Absolute Deviation (MAD)0
Skewness6.8001069
Sum3085.7687
Variance44251.384
MonotonicityNot monotonic
2023-12-12T16:11:10.985865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
0.0 48
60.8%
16.4056 1
 
1.3%
0.008 1
 
1.3%
1665.4 1
 
1.3%
59.628115 1
 
1.3%
19.8 1
 
1.3%
0.69 1
 
1.3%
2.3 1
 
1.3%
4.2 1
 
1.3%
0.01 1
 
1.3%
Other values (22) 22
27.8%
ValueCountFrequency (%)
0.0 48
60.8%
0.008 1
 
1.3%
0.01 1
 
1.3%
0.0128 1
 
1.3%
0.0495 1
 
1.3%
0.1415 1
 
1.3%
0.2191 1
 
1.3%
0.2631 1
 
1.3%
0.39 1
 
1.3%
0.418 1
 
1.3%
ValueCountFrequency (%)
1665.4 1
1.3%
828.4 1
1.3%
323.0 1
1.3%
59.628115 1
1.3%
36.1228 1
1.3%
34.557 1
1.3%
19.8 1
1.3%
19.79 1
1.3%
17.733 1
1.3%
16.4056 1
1.3%

사상자보상액
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size764.0 B
0
79 

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 79
100.0%

Length

2023-12-12T16:11:11.146459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:11:11.249975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 79
100.0%

재산피해액
Real number (ℝ)

ZEROS 

Distinct12
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.386615
Minimum0
Maximum1448.7
Zeros68
Zeros (%)86.1%
Negative0
Negative (%)0.0%
Memory size843.0 B
2023-12-12T16:11:11.380114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile21.2757
Maximum1448.7
Range1448.7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation166.40957
Coefficient of variation (CV)6.8238079
Kurtosis71.331631
Mean24.386615
Median Absolute Deviation (MAD)0
Skewness8.3206516
Sum1926.5426
Variance27692.146
MonotonicityNot monotonic
2023-12-12T16:11:11.524863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0.0 68
86.1%
14.0 1
 
1.3%
6.218 1
 
1.3%
4.562 1
 
1.3%
13.202 1
 
1.3%
323.0 1
 
1.3%
19.79 1
 
1.3%
34.557 1
 
1.3%
4.2 1
 
1.3%
19.8 1
 
1.3%
Other values (2) 2
 
2.5%
ValueCountFrequency (%)
0.0 68
86.1%
4.2 1
 
1.3%
4.562 1
 
1.3%
6.218 1
 
1.3%
13.202 1
 
1.3%
14.0 1
 
1.3%
19.79 1
 
1.3%
19.8 1
 
1.3%
34.557 1
 
1.3%
38.513565 1
 
1.3%
ValueCountFrequency (%)
1448.7 1
1.3%
323.0 1
1.3%
38.513565 1
1.3%
34.557 1
1.3%
19.8 1
1.3%
19.79 1
1.3%
14.0 1
1.3%
13.202 1
1.3%
6.218 1
1.3%
4.562 1
1.3%

기타피해액
Real number (ℝ)

ZEROS 

Distinct26
Distinct (%)32.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.673749
Minimum0
Maximum828.4
Zeros54
Zeros (%)68.4%
Negative0
Negative (%)0.0%
Memory size843.0 B
2023-12-12T16:11:11.676117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.08075
95-th percentile18.071155
Maximum828.4
Range828.4
Interquartile range (IQR)0.08075

Descriptive statistics

Standard deviation95.985456
Coefficient of variation (CV)6.5413043
Kurtosis68.67042
Mean14.673749
Median Absolute Deviation (MAD)0
Skewness8.1337326
Sum1159.2261
Variance9213.2077
MonotonicityNot monotonic
2023-12-12T16:11:11.827200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0.0 54
68.4%
0.39 1
 
1.3%
0.008 1
 
1.3%
216.7 1
 
1.3%
21.11455 1
 
1.3%
0.69 1
 
1.3%
2.3 1
 
1.3%
0.01 1
 
1.3%
36.1228 1
 
1.3%
0.2191 1
 
1.3%
Other values (16) 16
 
20.3%
ValueCountFrequency (%)
0.0 54
68.4%
0.0077 1
 
1.3%
0.008 1
 
1.3%
0.01 1
 
1.3%
0.0128 1
 
1.3%
0.0495 1
 
1.3%
0.112 1
 
1.3%
0.1415 1
 
1.3%
0.2191 1
 
1.3%
0.2631 1
 
1.3%
ValueCountFrequency (%)
828.4 1
1.3%
216.7 1
1.3%
36.1228 1
1.3%
21.11455 1
1.3%
17.733 1
1.3%
16.4056 1
1.3%
8.1174 1
1.3%
3.677 1
1.3%
3.3052 1
1.3%
2.3 1
1.3%

노선
Categorical

Distinct30
Distinct (%)38.0%
Missing0
Missing (%)0.0%
Memory size764.0 B
경부선
18 
기타선
6 
경전선
6 
영동선
5 
충북선
 
4
Other values (25)
40 

Length

Max length12
Median length3
Mean length4.1518987
Min length3

Unique

Unique16 ?
Unique (%)20.3%

Sample

1st row영동선
2nd row경부선
3rd row호남선
4th row영동선
5th row경부선

Common Values

ValueCountFrequency (%)
경부선 18
22.8%
기타선 6
 
7.6%
경전선 6
 
7.6%
영동선 5
 
6.3%
충북선 4
 
5.1%
경의선 4
 
5.1%
중앙선 4
 
5.1%
경춘선 3
 
3.8%
경북선 3
 
3.8%
호남선 2
 
2.5%
Other values (20) 24
30.4%

Length

2023-12-12T16:11:11.980898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경부선 18
20.2%
수도권도시철도 6
 
6.7%
경전선 6
 
6.7%
기타선 6
 
6.7%
영동선 5
 
5.6%
충북선 4
 
4.5%
경의선 4
 
4.5%
중앙선 4
 
4.5%
경춘선 3
 
3.4%
경북선 3
 
3.4%
Other values (20) 30
33.7%

발생장소역A
Text

Distinct60
Distinct (%)75.9%
Missing0
Missing (%)0.0%
Memory size764.0 B
2023-12-12T16:11:12.240789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.4303797
Min length2

Characters and Unicode

Total characters192
Distinct characters85
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

Unique47 ?
Unique (%)59.5%

Sample

1st row동해
2nd row수원
3rd row익산
4th row상정
5th row의왕
ValueCountFrequency (%)
대전조차장 3
 
3.8%
수색 3
 
3.8%
의왕 3
 
3.8%
보성 3
 
3.8%
용산 3
 
3.8%
부산진 3
 
3.8%
천안 2
 
2.5%
개포 2
 
2.5%
동해 2
 
2.5%
옥계 2
 
2.5%
Other values (50) 53
67.1%
2023-12-12T16:11:12.678789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
산 10
 
5.2%
대 8
 
4.2%
천 6
 
3.1%
양 5
 
2.6%
수 5
 
2.6%
원 5
 
2.6%
전 5
 
2.6%
보 4
 
2.1%
포 4
 
2.1%
오 4
 
2.1%
Other values (75) 136
70.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 192
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 10
 
5.2%
대 8
 
4.2%
천 6
 
3.1%
양 5
 
2.6%
수 5
 
2.6%
원 5
 
2.6%
전 5
 
2.6%
보 4
 
2.1%
포 4
 
2.1%
오 4
 
2.1%
Other values (75) 136
70.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 192
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 10
 
5.2%
대 8
 
4.2%
천 6
 
3.1%
양 5
 
2.6%
수 5
 
2.6%
원 5
 
2.6%
전 5
 
2.6%
보 4
 
2.1%
포 4
 
2.1%
오 4
 
2.1%
Other values (75) 136
70.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 192
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
산 10
 
5.2%
대 8
 
4.2%
천 6
 
3.1%
양 5
 
2.6%
수 5
 
2.6%
원 5
 
2.6%
전 5
 
2.6%
보 4
 
2.1%
포 4
 
2.1%
오 4
 
2.1%
Other values (75) 136
70.8%

발생장소역B
Text

Distinct63
Distinct (%)79.7%
Missing0
Missing (%)0.0%
Memory size764.0 B
2023-12-12T16:11:12.953578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length2
Mean length2.5822785
Min length2

Characters and Unicode

Total characters204
Distinct characters98
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

Unique52 ?
Unique (%)65.8%

Sample

1st row동해
2nd row수원
3rd row익산
4th row신기
5th row의왕
ValueCountFrequency (%)
대전조차장 4
 
5.1%
수색 3
 
3.8%
부산진 3
 
3.8%
의왕 3
 
3.8%
점촌 2
 
2.5%
묵호 2
 
2.5%
득량 2
 
2.5%
천안 2
 
2.5%
이촌 2
 
2.5%
익산 2
 
2.5%
Other values (53) 54
68.4%
2023-12-12T16:11:13.299192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
대 10
 
4.9%
천 9
 
4.4%
산 6
 
2.9%
장 5
 
2.5%
전 5
 
2.5%
수 5
 
2.5%
양 5
 
2.5%
동 5
 
2.5%
조 4
 
2.0%
부 4
 
2.0%
Other values (88) 146
71.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 201
98.5%
Uppercase Letter 3
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 10
 
5.0%
천 9
 
4.5%
산 6
 
3.0%
장 5
 
2.5%
전 5
 
2.5%
수 5
 
2.5%
양 5
 
2.5%
동 5
 
2.5%
조 4
 
2.0%
부 4
 
2.0%
Other values (85) 143
71.1%
Uppercase Letter
ValueCountFrequency (%)
C 1
33.3%
E 1
33.3%
I 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 201
98.5%
Latin 3
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 10
 
5.0%
천 9
 
4.5%
산 6
 
3.0%
장 5
 
2.5%
전 5
 
2.5%
수 5
 
2.5%
양 5
 
2.5%
동 5
 
2.5%
조 4
 
2.0%
부 4
 
2.0%
Other values (85) 143
71.1%
Latin
ValueCountFrequency (%)
C 1
33.3%
E 1
33.3%
I 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 201
98.5%
ASCII 3
 
1.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
대 10
 
5.0%
천 9
 
4.5%
산 6
 
3.0%
장 5
 
2.5%
전 5
 
2.5%
수 5
 
2.5%
양 5
 
2.5%
동 5
 
2.5%
조 4
 
2.0%
부 4
 
2.0%
Other values (85) 143
71.1%
ASCII
ValueCountFrequency (%)
C 1
33.3%
E 1
33.3%
I 1
33.3%

발생장소
Text

Distinct67
Distinct (%)84.8%
Missing0
Missing (%)0.0%
Memory size764.0 B
2023-12-12T16:11:13.603897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length9
Mean length3.7848101
Min length2

Characters and Unicode

Total characters299
Distinct characters112
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique59 ?
Unique (%)74.7%

Sample

1st row동해
2nd row수원
3rd row익산
4th row상정-신기
5th row의왕
ValueCountFrequency (%)
의왕 3
 
3.8%
대전조차장 3
 
3.8%
수색 3
 
3.8%
부산진 3
 
3.8%
익산 2
 
2.5%
천안 2
 
2.5%
용산-이촌 2
 
2.5%
보성-득량 2
 
2.5%
석포 1
 
1.3%
정선-선평 1
 
1.3%
Other values (57) 57
72.2%
2023-12-12T16:11:14.052368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 30
 
10.0%
천 11
 
3.7%
대 11
 
3.7%
산 10
 
3.3%
동 6
 
2.0%
전 6
 
2.0%
장 5
 
1.7%
원 5
 
1.7%
평 5
 
1.7%
성 5
 
1.7%
Other values (102) 205
68.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 266
89.0%
Dash Punctuation 30
 
10.0%
Uppercase Letter 3
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 11
 
4.1%
대 11
 
4.1%
산 10
 
3.8%
동 6
 
2.3%
전 6
 
2.3%
장 5
 
1.9%
원 5
 
1.9%
평 5
 
1.9%
성 5
 
1.9%
보 5
 
1.9%
Other values (98) 197
74.1%
Uppercase Letter
ValueCountFrequency (%)
I 1
33.3%
E 1
33.3%
C 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 266
89.0%
Common 30
 
10.0%
Latin 3
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 11
 
4.1%
대 11
 
4.1%
산 10
 
3.8%
동 6
 
2.3%
전 6
 
2.3%
장 5
 
1.9%
원 5
 
1.9%
평 5
 
1.9%
성 5
 
1.9%
보 5
 
1.9%
Other values (98) 197
74.1%
Latin
ValueCountFrequency (%)
I 1
33.3%
E 1
33.3%
C 1
33.3%
Common
ValueCountFrequency (%)
- 30
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 266
89.0%
ASCII 33
 
11.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 30
90.9%
I 1
 
3.0%
E 1
 
3.0%
C 1
 
3.0%
Hangul
ValueCountFrequency (%)
천 11
 
4.1%
대 11
 
4.1%
산 10
 
3.8%
동 6
 
2.3%
전 6
 
2.3%
장 5
 
1.9%
원 5
 
1.9%
평 5
 
1.9%
성 5
 
1.9%
보 5
 
1.9%
Other values (98) 197
74.1%

열차종류
Categorical

Distinct9
Distinct (%)11.4%
Missing0
Missing (%)0.0%
Memory size764.0 B
여객열차
26 
도시전동차
17 
관계없음
12 
입환차량
9 
작업차량
4 
Other values (4)
11 

Length

Max length5
Median length4
Mean length4.2658228
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row입환차량
2nd row도시전동차
3rd row입환차량
4th row여객열차
5th row도시전동차

Common Values

ValueCountFrequency (%)
여객열차 26
32.9%
도시전동차 17
21.5%
관계없음 12
15.2%
입환차량 9
 
11.4%
작업차량 4
 
5.1%
화물열차 4
 
5.1%
회송열차 3
 
3.8%
단행기관차 2
 
2.5%
시운전열차 2
 
2.5%

Length

2023-12-12T16:11:14.205214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:11:14.338302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여객열차 26
32.9%
도시전동차 17
21.5%
관계없음 12
15.2%
입환차량 9
 
11.4%
작업차량 4
 
5.1%
화물열차 4
 
5.1%
회송열차 3
 
3.8%
단행기관차 2
 
2.5%
시운전열차 2
 
2.5%

합계최대지연시간(분)
Real number (ℝ)

ZEROS 

Distinct30
Distinct (%)38.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.78481
Minimum0
Maximum390
Zeros42
Zeros (%)53.2%
Negative0
Negative (%)0.0%
Memory size843.0 B
2023-12-12T16:11:14.493057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q335.5
95-th percentile103.9
Maximum390
Range390
Interquartile range (IQR)35.5

Descriptive statistics

Standard deviation73.196201
Coefficient of variation (CV)2.2326254
Kurtosis14.696389
Mean32.78481
Median Absolute Deviation (MAD)0
Skewness3.7367443
Sum2590
Variance5357.6839
MonotonicityNot monotonic
2023-12-12T16:11:14.647502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0 42
53.2%
95 3
 
3.8%
63 2
 
2.5%
22 2
 
2.5%
41 2
 
2.5%
12 2
 
2.5%
34 2
 
2.5%
13 2
 
2.5%
30 1
 
1.3%
10 1
 
1.3%
Other values (20) 20
25.3%
ValueCountFrequency (%)
0 42
53.2%
10 1
 
1.3%
11 1
 
1.3%
12 2
 
2.5%
13 2
 
2.5%
14 1
 
1.3%
15 1
 
1.3%
17 1
 
1.3%
20 1
 
1.3%
22 2
 
2.5%
ValueCountFrequency (%)
390 1
 
1.3%
368 1
 
1.3%
326 1
 
1.3%
184 1
 
1.3%
95 3
3.8%
92 1
 
1.3%
63 2
2.5%
61 1
 
1.3%
56 1
 
1.3%
54 1
 
1.3%

장소유형A
Categorical

Distinct12
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Memory size764.0 B
역(역 구내 선로)
20 
건널목
14 
역간
12 
역(승강장)
9 
차량기지
8 
Other values (7)
16 

Length

Max length10
Median length5
Mean length5.3544304
Min length2

Unique

Unique4 ?
Unique (%)5.1%

Sample

1st row차량기지
2nd row역(승강장)
3rd row역(역 구내 선로)
4th row역간
5th row역(역 구내 선로)

Common Values

ValueCountFrequency (%)
역(역 구내 선로) 20
25.3%
건널목 14
17.7%
역간 12
15.2%
역(승강장) 9
11.4%
차량기지 8
 
10.1%
역(기타) 7
 
8.9%
역(대합실) 3
 
3.8%
측선 2
 
2.5%
열차 내 1
 
1.3%
본선 1
 
1.3%
Other values (2) 2
 
2.5%

Length

2023-12-12T16:11:14.837889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
역(역 20
16.7%
구내 20
16.7%
선로 20
16.7%
건널목 14
11.7%
역간 12
10.0%
역(승강장 9
7.5%
차량기지 8
 
6.7%
역(기타 7
 
5.8%
역(대합실 3
 
2.5%
측선 2
 
1.7%
Other values (5) 5
 
4.2%

장소유형B
Categorical

Distinct9
Distinct (%)11.4%
Missing0
Missing (%)0.0%
Memory size764.0 B
구내 선로
35 
기타
17 
건널목 내
13 
유치선
4 
분기부
 
3
Other values (4)
7 

Length

Max length5
Median length5
Mean length4.0253165
Min length2

Unique

Unique2 ?
Unique (%)2.5%

Sample

1st row구내 선로
2nd row구내 선로
3rd row유치선
4th row구내 선로
5th row구내 선로

Common Values

ValueCountFrequency (%)
구내 선로 35
44.3%
기타 17
21.5%
건널목 내 13
 
16.5%
유치선 4
 
5.1%
분기부 3
 
3.8%
검수고 3
 
3.8%
전기실 2
 
2.5%
터널/지하 1
 
1.3%
운전실 1
 
1.3%

Length

2023-12-12T16:11:15.019560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:11:15.165564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
구내 35
27.6%
선로 35
27.6%
기타 17
13.4%
건널목 13
 
10.2%
내 13
 
10.2%
유치선 4
 
3.1%
분기부 3
 
2.4%
검수고 3
 
2.4%
전기실 2
 
1.6%
터널/지하 1
 
0.8%

운행선 구분
Categorical

Distinct2
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size764.0 B
운행선
50 
운행선 외
29 

Length

Max length5
Median length3
Mean length3.7341772
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row운행선 외
2nd row운행선
3rd row운행선 외
4th row운행선
5th row운행선

Common Values

ValueCountFrequency (%)
운행선 50
63.3%
운행선 외 29
36.7%

Length

2023-12-12T16:11:15.319727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:11:15.462815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
운행선 79
73.1%
외 29
 
26.9%

Sample

일시요일철도구분사고 종류철도사고 종류주원인근본원인별 그룹근본원인별 원인근본원인별 상세행정구역총피해명사망부상(중상)경상총 피해액(백만원)사상자보상액재산피해액기타피해액노선발생장소역A발생장소역B발생장소열차종류합계최대지연시간(분)장소유형A장소유형B운행선 구분
02022-12-20화일반철도사고충돌ㆍ탈선ㆍ화재-탈선운전취급자-기타인적요인운전취급자(신호기/선로전환기/조작판 취급자)부주의/오류강원도 동해시 동해역길 6900000.000.00.0영동선동해동해동해입환차량0차량기지구내 선로운행선 외
12022-12-18일도시철도사고교통사상사고-공중공중(교통)-선로무단통행(자살)인적요인공중자살경기도 수원시 덕영대로 92411000.000.00.0경부선수원수원수원도시전동차36역(승강장)구내 선로운행선
22022-12-14수일반철도사고충돌ㆍ탈선ㆍ화재-탈선운전취급자-선로전환잘못인적요인운전취급자(신호기/선로전환기/조작판 취급자)부주의/오류전라북도 익산시 익산대로 15300000.000.00.0호남선익산익산익산입환차량0역(역 구내 선로)유치선운행선 외
32022-12-02금일반철도사고교통사상사고-공중공중(교통)-선로무단통행인적요인공중불법행위강원도 삼척시 신기면 신기역길 8911000.592700.00.5927영동선상정신기상정-신기여객열차63역간구내 선로운행선
42022-11-29화도시철도사고교통사상사고-공중공중(교통)-선로무단통행인적요인공중불법행위경기도 의왕시 철도박물관로 6611000.000.00.0경부선의왕의왕의왕도시전동차0역(역 구내 선로)구내 선로운행선
52022-11-23수도시철도사고교통사상사고-공중공중(교통)-선로무단통행(자살)인적요인공중자살경기도 의왕시 철도박물관로 6611000.000.00.0경부선의왕의왕의왕도시전동차35역(역 구내 선로)구내 선로운행선
62022-11-11금고속철도사고교통사상사고-공중공중(교통)-선로무단통행인적요인공중불법행위대전 동구 중앙로 215101017.73300.017.733경부선대전대전대전여객열차22역(역 구내 선로)구내 선로운행선
72022-11-10목도시철도사고충돌ㆍ탈선ㆍ화재-충돌운전취급자-운전취급잘못인적요인운전취급자(신호기/선로전환기/조작판 취급자)부주의/오류인천광역시 서구 검암동00000.000.00.0공항철도선검암청라국제도시검암-청라국제도시작업차량0역간기타운행선
82022-11-06일일반철도사고충돌ㆍ탈선ㆍ화재-탈선선로/구조물-레일파손기술적요인선로및구조물기타서울 동작구 노량진로 151120120828.400.0828.4경부선영등포영등포영등포여객열차368역(역 구내 선로)구내 선로운행선
92022-11-05토일반철도사고교통사상사고-직원직원(교통)-기타인적요인작업자기타경기도 의왕시 오봉로 16811000.000.00.0기타선오봉오봉오봉입환차량0역(역 구내 선로)구내 선로운행선 외
일시요일철도구분사고 종류철도사고 종류주원인근본원인별 그룹근본원인별 원인근본원인별 상세행정구역총피해명사망부상(중상)경상총 피해액(백만원)사상자보상액재산피해액기타피해액노선발생장소역A발생장소역B발생장소열차종류합계최대지연시간(분)장소유형A장소유형B운행선 구분
692022-02-10목일반철도사고안전사상사고-공중공중(안전)-전기감전인적요인공중불법행위충청북도 증평군 역전로 92 (증평읍 630) 증평역10104.204.20.0충북선증평증평증평관계없음0역(역 구내 선로)구내 선로운행선
702022-02-03목일반철도사고철도교통사고-건널목사고통행자(자동차)-일단정지 무시횡단인적요인공중규정위반경상북도 영천시 장수로 917-10 (화산면 522-12) 화산역22002.300.02.3중앙선화산북영천화산-북영천여객열차184건널목건널목 내운행선
712022-01-30일도시철도사고교통사상사고-공중공중(교통)-열차에 뛰어듦(자살)인적요인공중자살부산광역시 연제구 중앙대로 1196 (거제동 42-3) 교대역11000.6900.00.69동해선교대교대교대회송열차92역(승강장)구내 선로운행선
722022-01-29토도시철도사고안전사상사고-공중공중(안전)-기타인적요인공중기타대구광역시 북구 팔달로 163-1 (노원동3가 784-1) 팔달시장역303019.8019.80.0대구도시철도 3호선팔달시장팔달시장팔달시장도시전동차0역(대합실)전기실운행선 외
732022-01-26수도시철도사고충돌ㆍ탈선ㆍ화재-탈선신호통신-열차제어장치고장기술적요인신호제어설비도입/설치<NA>000059.628115038.51356521.11455부산도시철도 2호선구남구명구남-구명시운전열차0역(역 구내 선로)분기부운행선
742022-01-18화도시철도사고교통사상사고-직원직원(교통)-기타인적요인기관사(운전자)부주의/오류서울 강서구 금낭화로26가길 152-3910100.000.00.0수도권도시철도 5호선방화기지방화기지방화기지입환차량0차량기지검수고운행선 외
752022-01-17월도시철도사고교통사상사고-공중공중(교통)-열차에 뛰어듦(자살)인적요인공중자살충청남도 천안시 동남구 대흥로 239 (대흥동 57-1) 천안역10100.000.00.0경부선천안천안천안도시전동차0역(승강장)구내 선로운행선
762022-01-16일일반철도사고안전사상사고-직원직원(안전)-전기감전인적요인작업자부주의/오류서울특별시 마포구 성암로 202 (상암동 1232)10100.000.00.0경의선수색수색수색관계없음0역(작업장)기타운행선 외
772022-01-05수고속철도사고충돌ㆍ탈선ㆍ화재-탈선차량-주행장치고장기술적요인열차차량설비설계/제작대전광역시 동구 중앙로 215 (정동 1-1) 대전역00001665.401448.7216.7경부고속선대전남연결김천구미IEC대전남연결-김천구미IEC여객열차390역간기타운행선
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