Overview

Dataset statistics

Number of variables15
Number of observations21
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.9 KiB
Average record size in memory139.3 B

Variable types

Categorical14
Text1

Dataset

Description대구교통공사 철도사고 및 운행장애 통계 데이터로 열차사고, 철도교통 사상사고 등 연간, 월별 사고 건수 및 피해발생 금액 등의 정보를 제공합니다.
URLhttps://www.data.go.kr/data/15002093/fileData.do

Alerts

연도 has constant value ""Constant
4월 has constant value ""Constant
5월 has constant value ""Constant
6월 has constant value ""Constant
7월 has constant value ""Constant
8월 has constant value ""Constant
9월 has constant value ""Constant
10월 has constant value ""Constant
11월 has constant value ""Constant
12월 has constant value ""Constant
1월 is highly imbalanced (72.4%)Imbalance
2월 is highly imbalanced (65.4%)Imbalance
3월 is highly imbalanced (72.4%)Imbalance
세분류 has unique valuesUnique

Reproduction

Analysis started2023-12-12 01:12:43.442331
Analysis finished2023-12-12 01:12:44.072935
Duration0.63 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
2022
21 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2022
3rd row2022
4th row2022
5th row2022

Common Values

ValueCountFrequency (%)
2022 21
100.0%

Length

2023-12-12T10:12:44.135341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:12:44.230402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 21
100.0%

구분
Categorical

Distinct4
Distinct (%)19.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
철도교통사고
8 
철도안전사고
6 
운행장애피해현황
6 
철도준사고
1 

Length

Max length8
Median length6
Mean length6.5238095
Min length5

Unique

Unique1 ?
Unique (%)4.8%

Sample

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

Common Values

ValueCountFrequency (%)
철도교통사고 8
38.1%
철도안전사고 6
28.6%
운행장애피해현황 6
28.6%
철도준사고 1
 
4.8%

Length

2023-12-12T10:12:44.343266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:12:44.487506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
철도교통사고 8
38.1%
철도안전사고 6
28.6%
운행장애피해현황 6
28.6%
철도준사고 1
 
4.8%

세분류
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-12T10:12:44.700411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length8
Mean length7.7619048
Min length4

Characters and Unicode

Total characters163
Distinct characters54
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)100.0%

Sample

1st row충돌사고
2nd row탈선사고
3rd row열차화재사고
4th row위험물사고
5th row건널목사고
ValueCountFrequency (%)
충돌사고 1
 
4.8%
철도안전사상사고(공중 1
 
4.8%
인명피해(경상 1
 
4.8%
인명피해(중상 1
 
4.8%
인명피해(사망 1
 
4.8%
운행지연 1
 
4.8%
무정차통과 1
 
4.8%
철도준사고 1
 
4.8%
기타안전사고 1
 
4.8%
철도안전사상사고(직원 1
 
4.8%
Other values (11) 11
52.4%
2023-12-12T10:12:45.155707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 22
 
13.5%
고 15
 
9.2%
) 10
 
6.1%
( 10
 
6.1%
도 9
 
5.5%
철 9
 
5.5%
상 8
 
4.9%
해 4
 
2.5%
피 4
 
2.5%
안 4
 
2.5%
Other values (44) 68
41.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 143
87.7%
Close Punctuation 10
 
6.1%
Open Punctuation 10
 
6.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 22
 
15.4%
고 15
 
10.5%
도 9
 
6.3%
철 9
 
6.3%
상 8
 
5.6%
해 4
 
2.8%
피 4
 
2.8%
안 4
 
2.8%
전 4
 
2.8%
통 4
 
2.8%
Other values (42) 60
42.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 143
87.7%
Common 20
 
12.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 22
 
15.4%
고 15
 
10.5%
도 9
 
6.3%
철 9
 
6.3%
상 8
 
5.6%
해 4
 
2.8%
피 4
 
2.8%
안 4
 
2.8%
전 4
 
2.8%
통 4
 
2.8%
Other values (42) 60
42.0%
Common
ValueCountFrequency (%)
) 10
50.0%
( 10
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 143
87.7%
ASCII 20
 
12.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 22
 
15.4%
고 15
 
10.5%
도 9
 
6.3%
철 9
 
6.3%
상 8
 
5.6%
해 4
 
2.8%
피 4
 
2.8%
안 4
 
2.8%
전 4
 
2.8%
통 4
 
2.8%
Other values (42) 60
42.0%
ASCII
ValueCountFrequency (%)
) 10
50.0%
( 10
50.0%

1월
Categorical

IMBALANCE 

Distinct2
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size300.0 B
0
20 
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)4.8%

Sample

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

Common Values

ValueCountFrequency (%)
0 20
95.2%
1 1
 
4.8%

Length

2023-12-12T10:12:45.308888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:12:45.451141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 20
95.2%
1 1
 
4.8%

2월
Categorical

IMBALANCE 

Distinct3
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size300.0 B
0.0
19 
1.0
 
1
60.056
 
1

Length

Max length6
Median length3
Mean length3.1428571
Min length3

Unique

Unique2 ?
Unique (%)9.5%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 19
90.5%
1.0 1
 
4.8%
60.056 1
 
4.8%

Length

2023-12-12T10:12:45.593887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:12:45.717411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 19
90.5%
1.0 1
 
4.8%
60.056 1
 
4.8%

3월
Categorical

IMBALANCE 

Distinct2
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size300.0 B
0
20 
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)4.8%

Sample

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

Common Values

ValueCountFrequency (%)
0 20
95.2%
1 1
 
4.8%

Length

2023-12-12T10:12:45.854757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:12:45.964385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 20
95.2%
1 1
 
4.8%

4월
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
0
21 

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 21
100.0%

Length

2023-12-12T10:12:46.070131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:12:46.166594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 21
100.0%

5월
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
0
21 

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 21
100.0%

Length

2023-12-12T10:12:46.286997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:12:46.423919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 21
100.0%

6월
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
0
21 

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 21
100.0%

Length

2023-12-12T10:12:46.593487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:12:46.707766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 21
100.0%

7월
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
0
21 

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 21
100.0%

Length

2023-12-12T10:12:46.835942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:12:46.948608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 21
100.0%

8월
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
0
21 

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 21
100.0%

Length

2023-12-12T10:12:47.396981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:12:47.524622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 21
100.0%

9월
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
0
21 

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 21
100.0%

Length

2023-12-12T10:12:47.644714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:12:47.780493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 21
100.0%

10월
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
0
21 

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 21
100.0%

Length

2023-12-12T10:12:47.906948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:12:48.044028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 21
100.0%

11월
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
0
21 

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 21
100.0%

Length

2023-12-12T10:12:48.196407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:12:48.326403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 21
100.0%

12월
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
0
21 

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 21
100.0%

Length

2023-12-12T10:12:48.451246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:12:48.582967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 21
100.0%

Correlations

2023-12-12T10:12:48.669527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분세분류1월2월3월
구분1.0001.0000.0000.0000.000
세분류1.0001.0001.0001.0001.000
1월0.0001.0001.0000.0000.000
2월0.0001.0000.0001.0000.000
3월0.0001.0000.0000.0001.000
2023-12-12T10:12:48.796657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
1월구분2월3월
1월1.0000.0000.0000.000
구분0.0001.0000.0000.000
2월0.0000.0001.0000.000
3월0.0000.0000.0001.000
2023-12-12T10:12:48.899928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분1월2월3월
구분1.0000.0000.0000.000
1월0.0001.0000.0000.000
2월0.0000.0001.0000.000
3월0.0000.0000.0001.000

Missing values

2023-12-12T10:12:43.783954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T10:12:43.999407image/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

연도구분세분류1월2월3월4월5월6월7월8월9월10월11월12월
02022철도교통사고충돌사고00.00000000000
12022철도교통사고탈선사고00.01000000000
22022철도교통사고열차화재사고00.00000000000
32022철도교통사고위험물사고00.00000000000
42022철도교통사고건널목사고00.00000000000
52022철도교통사고철도교통사상사고(여객)00.00000000000
62022철도교통사고철도교통사상사고(공중)00.00000000000
72022철도교통사고철도교통사상사고(직원)00.00000000000
82022철도안전사고철도화재사고00.00000000000
92022철도안전사고철도시설파손사고00.00000000000
연도구분세분류1월2월3월4월5월6월7월8월9월10월11월12월
112022철도안전사고철도안전사상사고(공중)10.00000000000
122022철도안전사고철도안전사상사고(직원)00.00000000000
132022철도안전사고기타안전사고00.00000000000
142022철도준사고철도준사고00.00000000000
152022운행장애피해현황무정차통과00.00000000000
162022운행장애피해현황운행지연01.00000000000
172022운행장애피해현황인명피해(사망)00.00000000000
182022운행장애피해현황인명피해(중상)00.00000000000
192022운행장애피해현황인명피해(경상)00.00000000000
202022운행장애피해현황재산피해(백만원)060.0560000000000