Overview

Dataset statistics

Number of variables9
Number of observations85
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.7 KiB
Average record size in memory80.6 B

Variable types

DateTime1
Categorical7
Numeric1

Dataset

Description국내 가스종류(LPG, 도시가스)별, 원인(취급부주의, 시설미비, 제품노흐 가스누출, 자연재해, 아차사고 등 12개)별, 월별 가스사고 현황에 대한 데이터로가스사고 통계 자료등으로 활용가능한 데이터입니다.
Author한국가스안전공사
URLhttps://www.data.go.kr/data/15067796/fileData.do

Alerts

교통사고 is highly imbalanced (78.0%)Imbalance
사용자취급부주의 has 43 (50.6%) zerosZeros

Reproduction

Analysis started2023-12-12 17:44:02.830149
Analysis finished2023-12-12 17:44:03.761335
Duration0.93 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct31
Distinct (%)36.5%
Missing0
Missing (%)0.0%
Memory size812.0 B
Minimum2021-01-01 00:00:00
Maximum2023-08-01 00:00:00
2023-12-13T02:44:03.838378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:44:04.003545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)

가스구분
Categorical

Distinct4
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size812.0 B
LPG
28 
이동식부탄연소기(접합용기)
20 
도시가스
19 
고압가스
18 

Length

Max length14
Median length4
Mean length6.0235294
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowLPG
2nd row도시가스
3rd row이동식부탄연소기(접합용기)
4th row고압가스
5th rowLPG

Common Values

ValueCountFrequency (%)
LPG 28
32.9%
이동식부탄연소기(접합용기) 20
23.5%
도시가스 19
22.4%
고압가스 18
21.2%

Length

2023-12-13T02:44:04.173660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:44:04.299401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
lpg 28
32.9%
이동식부탄연소기(접합용기 20
23.5%
도시가스 19
22.4%
고압가스 18
21.2%
Distinct3
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size812.0 B
0
69 
1
14 
2
 
2

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 69
81.2%
1 14
 
16.5%
2 2
 
2.4%

Length

2023-12-13T02:44:04.430406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:44:04.566821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 69
81.2%
1 14
 
16.5%
2 2
 
2.4%

기타(1-3급)
Categorical

Distinct3
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size812.0 B
0
66 
1
18 
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.2%

Sample

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

Common Values

ValueCountFrequency (%)
0 66
77.6%
1 18
 
21.2%
2 1
 
1.2%

Length

2023-12-13T02:44:04.679602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:44:04.793771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 66
77.6%
1 18
 
21.2%
2 1
 
1.2%

사용자취급부주의
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.69411765
Minimum0
Maximum5
Zeros43
Zeros (%)50.6%
Negative0
Negative (%)0.0%
Memory size897.0 B
2023-12-13T02:44:04.905712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.92612261
Coefficient of variation (CV)1.3342444
Kurtosis6.0145013
Mean0.69411765
Median Absolute Deviation (MAD)0
Skewness2.0343428
Sum59
Variance0.85770308
MonotonicityNot monotonic
2023-12-13T02:44:05.014091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 43
50.6%
1 31
36.5%
2 8
 
9.4%
3 1
 
1.2%
5 1
 
1.2%
4 1
 
1.2%
ValueCountFrequency (%)
0 43
50.6%
1 31
36.5%
2 8
 
9.4%
3 1
 
1.2%
4 1
 
1.2%
5 1
 
1.2%
ValueCountFrequency (%)
5 1
 
1.2%
4 1
 
1.2%
3 1
 
1.2%
2 8
 
9.4%
1 31
36.5%
0 43
50.6%

시설미비
Categorical

Distinct4
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size812.0 B
0
61 
1
14 
2
3
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row3

Common Values

ValueCountFrequency (%)
0 61
71.8%
1 14
 
16.5%
2 7
 
8.2%
3 3
 
3.5%

Length

2023-12-13T02:44:05.136075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:44:05.255465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 61
71.8%
1 14
 
16.5%
2 7
 
8.2%
3 3
 
3.5%
Distinct4
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size812.0 B
0
59 
1
20 
2
 
5
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.2%

Sample

1st row2
2nd row1
3rd row0
4th row1
5th row2

Common Values

ValueCountFrequency (%)
0 59
69.4%
1 20
 
23.5%
2 5
 
5.9%
3 1
 
1.2%

Length

2023-12-13T02:44:05.395297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:44:05.519635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 59
69.4%
1 20
 
23.5%
2 5
 
5.9%
3 1
 
1.2%

타공사
Categorical

Distinct3
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size812.0 B
0
69 
1
13 
2
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 69
81.2%
1 13
 
15.3%
2 3
 
3.5%

Length

2023-12-13T02:44:05.661937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:44:05.771744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 69
81.2%
1 13
 
15.3%
2 3
 
3.5%

교통사고
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size812.0 B
0
82 
1
 
3

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 82
96.5%
1 3
 
3.5%

Length

2023-12-13T02:44:05.911353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:44:06.357343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 82
96.5%
1 3
 
3.5%

Interactions

2023-12-13T02:44:03.347577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T02:44:06.429426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사고연월가스구분공급자취급부주의기타(1-3급)사용자취급부주의시설미비제품노후(고장)타공사교통사고
사고연월1.0000.0000.3380.0000.5160.0000.0000.0000.521
가스구분0.0001.0000.2120.0000.4570.5330.4180.3960.201
공급자취급부주의0.3380.2121.0000.0000.0000.0000.0000.2890.000
기타(1-3급)0.0000.0000.0001.0000.0000.0000.0000.0000.000
사용자취급부주의0.5160.4570.0000.0001.0000.0000.3310.0000.000
시설미비0.0000.5330.0000.0000.0001.0000.4810.0000.000
제품노후(고장)0.0000.4180.0000.0000.3310.4811.0000.1010.000
타공사0.0000.3960.2890.0000.0000.0000.1011.0000.000
교통사고0.5210.2010.0000.0000.0000.0000.0000.0001.000
2023-12-13T02:44:06.568171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공급자취급부주의시설미비가스구분제품노후(고장)교통사고타공사기타(1-3급)
공급자취급부주의1.0000.0000.1990.0000.0000.0950.000
시설미비0.0001.0000.2300.2030.0000.0000.000
가스구분0.1990.2301.0000.1720.1300.3840.000
제품노후(고장)0.0000.2030.1721.0000.0000.0920.000
교통사고0.0000.0000.1300.0001.0000.0000.000
타공사0.0950.0000.3840.0920.0001.0000.000
기타(1-3급)0.0000.0000.0000.0000.0000.0001.000
2023-12-13T02:44:06.697283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사용자취급부주의가스구분공급자취급부주의기타(1-3급)시설미비제품노후(고장)타공사교통사고
사용자취급부주의1.0000.3060.0000.0000.0000.2140.0000.000
가스구분0.3061.0000.1990.0000.2300.1720.3840.130
공급자취급부주의0.0000.1991.0000.0000.0000.0000.0950.000
기타(1-3급)0.0000.0000.0001.0000.0000.0000.0000.000
시설미비0.0000.2300.0000.0001.0000.2030.0000.000
제품노후(고장)0.2140.1720.0000.0000.2031.0000.0920.000
타공사0.0000.3840.0950.0000.0000.0921.0000.000
교통사고0.0000.1300.0000.0000.0000.0000.0001.000

Missing values

2023-12-13T02:44:03.489395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:44:03.690257image/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

사고연월가스구분공급자취급부주의기타(1-3급)사용자취급부주의시설미비제품노후(고장)타공사교통사고
02021-01LPG0130200
12021-01도시가스0100110
22021-01이동식부탄연소기(접합용기)0050000
32021-01고압가스0000100
42021-02LPG0003200
52021-02도시가스0000020
62021-02이동식부탄연소기(접합용기)0010000
72021-03LPG0000110
82021-03도시가스0002000
92021-03이동식부탄연소기(접합용기)0010000
사고연월가스구분공급자취급부주의기타(1-3급)사용자취급부주의시설미비제품노후(고장)타공사교통사고
752023-05LPG1000000
762023-05도시가스0110000
772023-05고압가스0010000
782023-06고압가스0011000
792023-07LPG0001000
802023-07도시가스0002000
812023-07고압가스0101000
822023-07이동식부탄연소기(접합용기)0010000
832023-08LPG1010000
842023-08고압가스0012000