Overview

Dataset statistics

Number of variables24
Number of observations3446
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory693.4 KiB
Average record size in memory206.0 B

Variable types

DateTime1
Categorical11
Numeric12

Dataset

Description해상조난사고 상세데이터 통계현황에 관한 데이터로 발생일시,관할서,발생해역,위도(도),위도(분),위도(초),경도(도),경도(분),경도(초),기상상태,발생원인,발생유형,사고선박수,발생인원,구조,부상,사망,실종,선종,톤수 등의 항목을 제공합니다.
Author해양경찰청
URLhttps://www.data.go.kr/data/15098854/fileData.do

Alerts

기상상태 is highly imbalanced (82.2%)Imbalance
사망 is highly imbalanced (95.3%)Imbalance
실종 is highly imbalanced (98.0%)Imbalance
선질 is highly imbalanced (50.5%)Imbalance
선령 is highly skewed (γ1 = 37.35689647)Skewed
위도_분 has 51 (1.5%) zerosZeros
위도_초 has 243 (7.1%) zerosZeros
경도_분 has 47 (1.4%) zerosZeros
경도_초 has 228 (6.6%) zerosZeros
발생인원 has 516 (15.0%) zerosZeros
구조 has 545 (15.8%) zerosZeros
부상 has 3358 (97.4%) zerosZeros
톤수 has 55 (1.6%) zerosZeros
선령 has 486 (14.1%) zerosZeros

Reproduction

Analysis started2023-12-12 12:19:05.725012
Analysis finished2023-12-12 12:19:06.180898
Duration0.46 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

발생일시
Date

Distinct3427
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size27.1 KiB
Minimum2022-01-01 11:08:00
Maximum2022-12-31 18:17:00
2023-12-12T21:19:06.258885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:19:06.424322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

관할해경서
Categorical

Distinct20
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size27.1 KiB
목포
505 
여수
287 
제주
214 
인천
211 
보령
211 
Other values (15)
2018 

Length

Max length3
Median length2
Mean length2.053105
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row제주
2nd row서귀포
3rd row여수
4th row통영
5th row통영

Common Values

ValueCountFrequency (%)
목포 505
14.7%
여수 287
 
8.3%
제주 214
 
6.2%
인천 211
 
6.1%
보령 211
 
6.1%
창원 203
 
5.9%
서귀포 183
 
5.3%
포항 177
 
5.1%
통영 173
 
5.0%
완도 169
 
4.9%
Other values (10) 1113
32.3%

Length

2023-12-12T21:19:06.594677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
목포 505
14.7%
여수 287
 
8.3%
제주 214
 
6.2%
인천 211
 
6.1%
보령 211
 
6.1%
창원 203
 
5.9%
서귀포 183
 
5.3%
포항 177
 
5.1%
통영 173
 
5.0%
완도 169
 
4.9%
Other values (10) 1113
32.3%

발생해역
Categorical

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size27.1 KiB
영해
1879 
항계 내
1255 
영해-EEZ
205 
협수로
 
92
공해
 
14

Length

Max length6
Median length2
Mean length2.9936158
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row항계 내
2nd row영해
3rd row영해
4th row항계 내
5th row항계 내

Common Values

ValueCountFrequency (%)
영해 1879
54.5%
항계 내 1255
36.4%
영해-EEZ 205
 
5.9%
협수로 92
 
2.7%
공해 14
 
0.4%
북한해역 1
 
< 0.1%

Length

2023-12-12T21:19:06.778633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:19:06.938199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영해 1879
40.0%
항계 1255
26.7%
내 1255
26.7%
영해-eez 205
 
4.4%
협수로 92
 
2.0%
공해 14
 
0.3%
북한해역 1
 
< 0.1%

정박(계류)여부
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.1 KiB
정박안함
2936 
정박
510 

Length

Max length4
Median length4
Mean length3.7040046
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row정박
2nd row정박안함
3rd row정박안함
4th row정박안함
5th row정박

Common Values

ValueCountFrequency (%)
정박안함 2936
85.2%
정박 510
 
14.8%

Length

2023-12-12T21:19:07.077193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:19:07.194939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정박안함 2936
85.2%
정박 510
 
14.8%

위도_도
Real number (ℝ)

Distinct10
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.908299
Minimum30
Maximum39
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size30.4 KiB
2023-12-12T21:19:07.298282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum30
5-th percentile33
Q134
median35
Q336
95-th percentile37
Maximum39
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.3519886
Coefficient of variation (CV)0.038729717
Kurtosis-0.61792352
Mean34.908299
Median Absolute Deviation (MAD)1
Skewness0.22953093
Sum120294
Variance1.827873
MonotonicityNot monotonic
2023-12-12T21:19:07.418064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
34 1188
34.5%
35 691
20.1%
36 580
16.8%
37 514
14.9%
33 369
 
10.7%
38 53
 
1.5%
32 42
 
1.2%
31 5
 
0.1%
30 3
 
0.1%
39 1
 
< 0.1%
ValueCountFrequency (%)
30 3
 
0.1%
31 5
 
0.1%
32 42
 
1.2%
33 369
 
10.7%
34 1188
34.5%
35 691
20.1%
36 580
16.8%
37 514
14.9%
38 53
 
1.5%
39 1
 
< 0.1%
ValueCountFrequency (%)
39 1
 
< 0.1%
38 53
 
1.5%
37 514
14.9%
36 580
16.8%
35 691
20.1%
34 1188
34.5%
33 369
 
10.7%
32 42
 
1.2%
31 5
 
0.1%
30 3
 
0.1%

위도_분
Real number (ℝ)

ZEROS 

Distinct60
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27.66686
Minimum0
Maximum59
Zeros51
Zeros (%)1.5%
Negative0
Negative (%)0.0%
Memory size30.4 KiB
2023-12-12T21:19:07.571001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q112
median27
Q343
95-th percentile56
Maximum59
Range59
Interquartile range (IQR)31

Descriptive statistics

Standard deviation17.513201
Coefficient of variation (CV)0.63300284
Kurtosis-1.2021355
Mean27.66686
Median Absolute Deviation (MAD)15
Skewness0.11120743
Sum95340
Variance306.71221
MonotonicityNot monotonic
2023-12-12T21:19:07.721890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 102
 
3.0%
4 93
 
2.7%
13 85
 
2.5%
19 81
 
2.4%
28 80
 
2.3%
1 79
 
2.3%
5 77
 
2.2%
2 74
 
2.1%
31 73
 
2.1%
48 72
 
2.1%
Other values (50) 2630
76.3%
ValueCountFrequency (%)
0 51
1.5%
1 79
2.3%
2 74
2.1%
3 102
3.0%
4 93
2.7%
5 77
2.2%
6 66
1.9%
7 63
1.8%
8 49
1.4%
9 56
1.6%
ValueCountFrequency (%)
59 57
1.7%
58 52
1.5%
57 35
1.0%
56 44
1.3%
55 68
2.0%
54 41
1.2%
53 42
1.2%
52 47
1.4%
51 55
1.6%
50 52
1.5%

위도_초
Real number (ℝ)

ZEROS 

Distinct61
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.69646
Minimum0
Maximum60
Zeros243
Zeros (%)7.1%
Negative0
Negative (%)0.0%
Memory size30.4 KiB
2023-12-12T21:19:07.901112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q112
median28
Q345
95-th percentile58
Maximum60
Range60
Interquartile range (IQR)33

Descriptive statistics

Standard deviation18.646435
Coefficient of variation (CV)0.64978173
Kurtosis-1.2422915
Mean28.69646
Median Absolute Deviation (MAD)16
Skewness0.049778131
Sum98888
Variance347.68955
MonotonicityNot monotonic
2023-12-12T21:19:08.056394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 243
 
7.1%
59 86
 
2.5%
11 83
 
2.4%
39 74
 
2.1%
27 74
 
2.1%
60 73
 
2.1%
54 73
 
2.1%
42 71
 
2.1%
17 71
 
2.1%
51 71
 
2.1%
Other values (51) 2527
73.3%
ValueCountFrequency (%)
0 243
7.1%
1 34
 
1.0%
2 62
 
1.8%
3 51
 
1.5%
4 34
 
1.0%
5 59
 
1.7%
6 65
 
1.9%
7 40
 
1.2%
8 67
 
1.9%
9 47
 
1.4%
ValueCountFrequency (%)
60 73
2.1%
59 86
2.5%
58 46
1.3%
57 55
1.6%
56 52
1.5%
55 36
1.0%
54 73
2.1%
53 61
1.8%
52 43
1.2%
51 71
2.1%

경도_도
Real number (ℝ)

Distinct11
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.91265
Minimum124
Maximum134
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size30.4 KiB
2023-12-12T21:19:08.192703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum124
5-th percentile125
Q1126
median126
Q3128
95-th percentile129
Maximum134
Range10
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.3913175
Coefficient of variation (CV)0.010962796
Kurtosis0.47180919
Mean126.91265
Median Absolute Deviation (MAD)1
Skewness0.83951943
Sum437341
Variance1.9357644
MonotonicityNot monotonic
2023-12-12T21:19:08.325383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
126 1703
49.4%
128 563
 
16.3%
129 536
 
15.6%
127 328
 
9.5%
125 218
 
6.3%
130 35
 
1.0%
124 26
 
0.8%
131 17
 
0.5%
132 14
 
0.4%
133 4
 
0.1%
ValueCountFrequency (%)
124 26
 
0.8%
125 218
 
6.3%
126 1703
49.4%
127 328
 
9.5%
128 563
 
16.3%
129 536
 
15.6%
130 35
 
1.0%
131 17
 
0.5%
132 14
 
0.4%
133 4
 
0.1%
ValueCountFrequency (%)
134 2
 
0.1%
133 4
 
0.1%
132 14
 
0.4%
131 17
 
0.5%
130 35
 
1.0%
129 536
 
15.6%
128 563
 
16.3%
127 328
 
9.5%
126 1703
49.4%
125 218
 
6.3%

경도_분
Real number (ℝ)

ZEROS 

Distinct60
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27.785548
Minimum0
Maximum59
Zeros47
Zeros (%)1.4%
Negative0
Negative (%)0.0%
Memory size30.4 KiB
2023-12-12T21:19:08.464015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q117
median27
Q339
95-th percentile55
Maximum59
Range59
Interquartile range (IQR)22

Descriptive statistics

Standard deviation15.315838
Coefficient of variation (CV)0.55121597
Kurtosis-0.76401094
Mean27.785548
Median Absolute Deviation (MAD)11
Skewness0.12173099
Sum95749
Variance234.5749
MonotonicityNot monotonic
2023-12-12T21:19:08.615925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
27 124
 
3.6%
28 117
 
3.4%
25 104
 
3.0%
24 98
 
2.8%
21 96
 
2.8%
26 95
 
2.8%
23 89
 
2.6%
22 88
 
2.6%
31 87
 
2.5%
35 82
 
2.4%
Other values (50) 2466
71.6%
ValueCountFrequency (%)
0 47
1.4%
1 49
1.4%
2 53
1.5%
3 46
1.3%
4 55
1.6%
5 46
1.3%
6 49
1.4%
7 77
2.2%
8 67
1.9%
9 50
1.5%
ValueCountFrequency (%)
59 31
0.9%
58 54
1.6%
57 38
1.1%
56 33
1.0%
55 48
1.4%
54 21
 
0.6%
53 22
0.6%
52 39
1.1%
51 32
0.9%
50 24
0.7%

경도_초
Real number (ℝ)

ZEROS 

Distinct61
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.446605
Minimum0
Maximum60
Zeros228
Zeros (%)6.6%
Negative0
Negative (%)0.0%
Memory size30.4 KiB
2023-12-12T21:19:08.777239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q113
median30
Q346
95-th percentile58
Maximum60
Range60
Interquartile range (IQR)33

Descriptive statistics

Standard deviation18.729157
Coefficient of variation (CV)0.63603792
Kurtosis-1.2608694
Mean29.446605
Median Absolute Deviation (MAD)17
Skewness-0.0023033364
Sum101473
Variance350.78133
MonotonicityNot monotonic
2023-12-12T21:19:08.933751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 228
 
6.6%
59 90
 
2.6%
54 85
 
2.5%
60 78
 
2.3%
45 76
 
2.2%
21 75
 
2.2%
48 75
 
2.2%
57 72
 
2.1%
3 71
 
2.1%
30 70
 
2.0%
Other values (51) 2526
73.3%
ValueCountFrequency (%)
0 228
6.6%
1 30
 
0.9%
2 51
 
1.5%
3 71
 
2.1%
4 27
 
0.8%
5 52
 
1.5%
6 62
 
1.8%
7 45
 
1.3%
8 52
 
1.5%
9 60
 
1.7%
ValueCountFrequency (%)
60 78
2.3%
59 90
2.6%
58 47
1.4%
57 72
2.1%
56 51
1.5%
55 40
1.2%
54 85
2.5%
53 51
1.5%
52 45
1.3%
51 55
1.6%

기상상태
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size27.1 KiB
양호
3189 
풍랑주의보
 
103
황천6급
 
43
저시정
 
43
황천5급
 
29
Other values (4)
 
39

Length

Max length5
Median length2
Mean length2.1688915
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
양호 3189
92.5%
풍랑주의보 103
 
3.0%
황천6급 43
 
1.2%
저시정 43
 
1.2%
황천5급 29
 
0.8%
황천4급 17
 
0.5%
태풍주의보 8
 
0.2%
풍랑경보 8
 
0.2%
태풍경보 6
 
0.2%

Length

2023-12-12T21:19:09.082048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:19:09.214610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
양호 3189
92.5%
풍랑주의보 103
 
3.0%
황천6급 43
 
1.2%
저시정 43
 
1.2%
황천5급 29
 
0.8%
황천4급 17
 
0.5%
태풍주의보 8
 
0.2%
풍랑경보 8
 
0.2%
태풍경보 6
 
0.2%

발생원인
Categorical

Distinct12
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size27.1 KiB
정비불량
1453 
운항부주의
957 
관리소홀
377 
안전부주의
166 
원인미상
 
131
Other values (7)
362 

Length

Max length7
Median length4
Mean length4.3990133
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row관리소홀
2nd row배터리 방전
3rd row정비불량
4th row정비불량
5th row관리소홀

Common Values

ValueCountFrequency (%)
정비불량 1453
42.2%
운항부주의 957
27.8%
관리소홀 377
 
10.9%
안전부주의 166
 
4.8%
원인미상 131
 
3.8%
기상악화 127
 
3.7%
연료고갈 94
 
2.7%
배터리 방전 86
 
2.5%
화기취급부주의 31
 
0.9%
기타 13
 
0.4%
Other values (2) 11
 
0.3%

Length

2023-12-12T21:19:09.362599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
정비불량 1453
41.1%
운항부주의 957
27.1%
관리소홀 377
 
10.7%
안전부주의 166
 
4.7%
원인미상 131
 
3.7%
기상악화 127
 
3.6%
연료고갈 94
 
2.7%
배터리 86
 
2.4%
방전 86
 
2.4%
화기취급부주의 31
 
0.9%
Other values (3) 24
 
0.7%

발생유형
Categorical

Distinct21
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size27.1 KiB
기관손상
1083 
부유물감김
506 
운항저해
278 
침수
267 
추진기손상
227 
Other values (16)
1085 

Length

Max length9
Median length6
Mean length3.7887406
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row침수
2nd row운항저해
3rd row키손상
4th row침수
5th row해양오염

Common Values

ValueCountFrequency (%)
기관손상 1083
31.4%
부유물감김 506
14.7%
운항저해 278
 
8.1%
침수 267
 
7.7%
추진기손상 227
 
6.6%
좌초/좌주 178
 
5.2%
충돌 153
 
4.4%
화재 144
 
4.2%
표류 119
 
3.5%
키손상 100
 
2.9%
Other values (11) 391
 
11.3%

Length

2023-12-12T21:19:09.499961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
기관손상 1083
30.4%
부유물감김 506
14.2%
운항저해 278
 
7.8%
침수 267
 
7.5%
추진기손상 227
 
6.4%
좌초/좌주 178
 
5.0%
충돌 153
 
4.3%
화재 144
 
4.0%
표류 119
 
3.3%
키손상 100
 
2.8%
Other values (13) 511
14.3%

사고선박수
Real number (ℝ)

Distinct9
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.0966338
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size30.4 KiB
2023-12-12T21:19:09.625473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile2
Maximum9
Range8
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.44324341
Coefficient of variation (CV)0.40418544
Kurtosis111.19592
Mean1.0966338
Median Absolute Deviation (MAD)0
Skewness8.8708512
Sum3779
Variance0.19646472
MonotonicityNot monotonic
2023-12-12T21:19:09.804303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 3188
92.5%
2 231
 
6.7%
3 10
 
0.3%
4 5
 
0.1%
6 3
 
0.1%
5 3
 
0.1%
7 3
 
0.1%
8 2
 
0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
1 3188
92.5%
2 231
 
6.7%
3 10
 
0.3%
4 5
 
0.1%
5 3
 
0.1%
6 3
 
0.1%
7 3
 
0.1%
8 2
 
0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
9 1
 
< 0.1%
8 2
 
0.1%
7 3
 
0.1%
6 3
 
0.1%
5 3
 
0.1%
4 5
 
0.1%
3 10
 
0.3%
2 231
 
6.7%
1 3188
92.5%

발생인원
Real number (ℝ)

ZEROS 

Distinct70
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.1033082
Minimum0
Maximum381
Zeros516
Zeros (%)15.0%
Negative0
Negative (%)0.0%
Memory size30.4 KiB
2023-12-12T21:19:09.947433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q37
95-th percentile21
Maximum381
Range381
Interquartile range (IQR)6

Descriptive statistics

Standard deviation14.612987
Coefficient of variation (CV)2.3942732
Kurtosis216.52087
Mean6.1033082
Median Absolute Deviation (MAD)2
Skewness12.299602
Sum21032
Variance213.5394
MonotonicityNot monotonic
2023-12-12T21:19:10.094669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 600
17.4%
2 574
16.7%
0 516
15.0%
3 356
10.3%
4 243
 
7.1%
5 134
 
3.9%
6 129
 
3.7%
9 89
 
2.6%
8 83
 
2.4%
7 82
 
2.4%
Other values (60) 640
18.6%
ValueCountFrequency (%)
0 516
15.0%
1 600
17.4%
2 574
16.7%
3 356
10.3%
4 243
7.1%
5 134
 
3.9%
6 129
 
3.7%
7 82
 
2.4%
8 83
 
2.4%
9 89
 
2.6%
ValueCountFrequency (%)
381 1
< 0.1%
242 1
< 0.1%
233 1
< 0.1%
208 1
< 0.1%
206 1
< 0.1%
188 1
< 0.1%
181 1
< 0.1%
177 1
< 0.1%
175 1
< 0.1%
161 1
< 0.1%

구조
Real number (ℝ)

ZEROS 

Distinct70
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.0858967
Minimum0
Maximum381
Zeros545
Zeros (%)15.8%
Negative0
Negative (%)0.0%
Memory size30.4 KiB
2023-12-12T21:19:10.261499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q37
95-th percentile21
Maximum381
Range381
Interquartile range (IQR)6

Descriptive statistics

Standard deviation14.617291
Coefficient of variation (CV)2.4018302
Kurtosis216.32123
Mean6.0858967
Median Absolute Deviation (MAD)2
Skewness12.291954
Sum20972
Variance213.66519
MonotonicityNot monotonic
2023-12-12T21:19:10.448411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 577
16.7%
2 575
16.7%
0 545
15.8%
3 353
10.2%
4 244
 
7.1%
5 134
 
3.9%
6 125
 
3.6%
9 89
 
2.6%
8 83
 
2.4%
7 81
 
2.4%
Other values (60) 640
18.6%
ValueCountFrequency (%)
0 545
15.8%
1 577
16.7%
2 575
16.7%
3 353
10.2%
4 244
7.1%
5 134
 
3.9%
6 125
 
3.6%
7 81
 
2.4%
8 83
 
2.4%
9 89
 
2.6%
ValueCountFrequency (%)
381 1
< 0.1%
242 1
< 0.1%
233 1
< 0.1%
208 1
< 0.1%
206 1
< 0.1%
188 1
< 0.1%
181 1
< 0.1%
177 1
< 0.1%
175 1
< 0.1%
161 1
< 0.1%

부상
Real number (ℝ)

ZEROS 

Distinct10
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.049042368
Minimum0
Maximum12
Zeros3358
Zeros (%)97.4%
Negative0
Negative (%)0.0%
Memory size30.4 KiB
2023-12-12T21:19:10.602539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum12
Range12
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.44189585
Coefficient of variation (CV)9.0104917
Kurtosis352.76506
Mean0.049042368
Median Absolute Deviation (MAD)0
Skewness16.511898
Sum169
Variance0.19527194
MonotonicityNot monotonic
2023-12-12T21:19:10.742404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 3358
97.4%
1 59
 
1.7%
2 12
 
0.3%
3 8
 
0.2%
5 3
 
0.1%
4 2
 
0.1%
12 1
 
< 0.1%
7 1
 
< 0.1%
9 1
 
< 0.1%
11 1
 
< 0.1%
ValueCountFrequency (%)
0 3358
97.4%
1 59
 
1.7%
2 12
 
0.3%
3 8
 
0.2%
4 2
 
0.1%
5 3
 
0.1%
7 1
 
< 0.1%
9 1
 
< 0.1%
11 1
 
< 0.1%
12 1
 
< 0.1%
ValueCountFrequency (%)
12 1
 
< 0.1%
11 1
 
< 0.1%
9 1
 
< 0.1%
7 1
 
< 0.1%
5 3
 
0.1%
4 2
 
0.1%
3 8
 
0.2%
2 12
 
0.3%
1 59
 
1.7%
0 3358
97.4%

사망
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.1 KiB
0
3409 
1
 
31
2
 
3
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 row0

Common Values

ValueCountFrequency (%)
0 3409
98.9%
1 31
 
0.9%
2 3
 
0.1%
3 3
 
0.1%

Length

2023-12-12T21:19:10.991872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:19:11.176052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3409
98.9%
1 31
 
0.9%
2 3
 
0.1%
3 3
 
0.1%

실종
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.1 KiB
0
3435 
1
 
10
4
 
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 3435
99.7%
1 10
 
0.3%
4 1
 
< 0.1%

Length

2023-12-12T21:19:11.302661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:19:11.424447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3435
99.7%
1 10
 
0.3%
4 1
 
< 0.1%

선종
Categorical

Distinct12
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size27.1 KiB
어선
1574 
모터보트
626 
낚시어선
289 
예부선
217 
화물선
188 
Other values (7)
552 

Length

Max length4
Median length2
Mean length2.7980267
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row기타
2nd row낚시어선
3rd row기타
4th row기타
5th row유조선

Common Values

ValueCountFrequency (%)
어선 1574
45.7%
모터보트 626
 
18.2%
낚시어선 289
 
8.4%
예부선 217
 
6.3%
화물선 188
 
5.5%
고무보트 168
 
4.9%
기타 130
 
3.8%
유조선 81
 
2.4%
요트 75
 
2.2%
여객선 52
 
1.5%
Other values (2) 46
 
1.3%

Length

2023-12-12T21:19:11.902472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
어선 1574
45.7%
모터보트 626
 
18.2%
낚시어선 289
 
8.4%
예부선 217
 
6.3%
화물선 188
 
5.5%
고무보트 168
 
4.9%
기타 130
 
3.8%
유조선 81
 
2.4%
요트 75
 
2.2%
여객선 52
 
1.5%
Other values (2) 46
 
1.3%

톤수
Real number (ℝ)

ZEROS 

Distinct932
Distinct (%)27.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean791.47147
Minimum0
Maximum166381
Zeros55
Zeros (%)1.6%
Negative0
Negative (%)0.0%
Memory size30.4 KiB
2023-12-12T21:19:12.050964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.3
Q11.97
median6.4
Q329
95-th percentile2114
Maximum166381
Range166381
Interquartile range (IQR)27.03

Descriptive statistics

Standard deviation6350.3101
Coefficient of variation (CV)8.0234225
Kurtosis330.09307
Mean791.47147
Median Absolute Deviation (MAD)5.13
Skewness16.209409
Sum2727410.7
Variance40326438
MonotonicityNot monotonic
2023-12-12T21:19:12.223388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9.77 347
 
10.1%
7.93 108
 
3.1%
29.0 102
 
3.0%
0.1 73
 
2.1%
3.0 68
 
2.0%
4.99 62
 
1.8%
2.99 57
 
1.7%
0.0 55
 
1.6%
24.0 46
 
1.3%
1.0 46
 
1.3%
Other values (922) 2482
72.0%
ValueCountFrequency (%)
0.0 55
1.6%
0.01 9
 
0.3%
0.05 1
 
< 0.1%
0.1 73
2.1%
0.16 1
 
< 0.1%
0.2 23
 
0.7%
0.23 1
 
< 0.1%
0.26 1
 
< 0.1%
0.28 1
 
< 0.1%
0.3 18
 
0.5%
ValueCountFrequency (%)
166381.0 1
< 0.1%
160000.0 1
< 0.1%
109534.0 1
< 0.1%
107737.0 1
< 0.1%
89492.0 1
< 0.1%
68871.0 1
< 0.1%
66278.0 1
< 0.1%
64575.0 1
< 0.1%
63915.0 1
< 0.1%
59580.0 1
< 0.1%

선적지
Categorical

Distinct22
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size27.1 KiB
기타
1037 
부산
235 
인천
229 
제주
204 
여수
198 
Other values (17)
1543 

Length

Max length3
Median length2
Mean length2.0751596
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row제주
2nd row제주
3rd row여수
4th row사천
5th row부산

Common Values

ValueCountFrequency (%)
기타 1037
30.1%
부산 235
 
6.8%
인천 229
 
6.6%
제주 204
 
5.9%
여수 198
 
5.7%
보령 151
 
4.4%
서귀포 151
 
4.4%
통영 149
 
4.3%
창원 131
 
3.8%
목포 124
 
3.6%
Other values (12) 837
24.3%

Length

2023-12-12T21:19:12.374100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
기타 1037
30.1%
부산 235
 
6.8%
인천 229
 
6.6%
제주 204
 
5.9%
여수 198
 
5.7%
보령 151
 
4.4%
서귀포 151
 
4.4%
통영 149
 
4.3%
창원 131
 
3.8%
목포 124
 
3.6%
Other values (12) 837
24.3%

선질
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size27.1 KiB
FRP
2415 
강
701 
고무
 
163
기타
 
144
알루미늄
 
16

Length

Max length4
Median length3
Mean length2.5066744
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row강
2nd rowFRP
3rd row강
4th rowFRP
5th row강

Common Values

ValueCountFrequency (%)
FRP 2415
70.1%
강 701
 
20.3%
고무 163
 
4.7%
기타 144
 
4.2%
알루미늄 16
 
0.5%
목재 7
 
0.2%

Length

2023-12-12T21:19:12.506461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:19:12.648608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
frp 2415
70.1%
강 701
 
20.3%
고무 163
 
4.7%
기타 144
 
4.2%
알루미늄 16
 
0.5%
목재 7
 
0.2%

선령
Real number (ℝ)

SKEWED  ZEROS 

Distinct59
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.43906
Minimum0
Maximum1032
Zeros486
Zeros (%)14.1%
Negative0
Negative (%)0.0%
Memory size30.4 KiB
2023-12-12T21:19:12.828882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14
median10
Q319
95-th percentile30
Maximum1032
Range1032
Interquartile range (IQR)15

Descriptive statistics

Standard deviation20.224148
Coefficient of variation (CV)1.6258583
Kurtosis1875.5459
Mean12.43906
Median Absolute Deviation (MAD)7
Skewness37.356896
Sum42865
Variance409.01617
MonotonicityNot monotonic
2023-12-12T21:19:13.050876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 486
 
14.1%
10 358
 
10.4%
5 242
 
7.0%
7 132
 
3.8%
1 130
 
3.8%
20 119
 
3.5%
15 111
 
3.2%
8 111
 
3.2%
4 108
 
3.1%
6 98
 
2.8%
Other values (49) 1551
45.0%
ValueCountFrequency (%)
0 486
14.1%
1 130
 
3.8%
2 60
 
1.7%
3 88
 
2.6%
4 108
 
3.1%
5 242
7.0%
6 98
 
2.8%
7 132
 
3.8%
8 111
 
3.2%
9 80
 
2.3%
ValueCountFrequency (%)
1032 1
 
< 0.1%
80 1
 
< 0.1%
77 2
 
0.1%
72 1
 
< 0.1%
60 1
 
< 0.1%
55 2
 
0.1%
54 5
0.1%
51 4
0.1%
50 1
 
< 0.1%
49 4
0.1%

Sample

발생일시관할해경서발생해역정박(계류)여부위도_도위도_분위도_초경도_도경도_분경도_초기상상태발생원인발생유형사고선박수발생인원구조부상사망실종선종톤수선적지선질선령
02022-01-01 11:08제주항계 내정박331834126955양호관리소홀침수100000기타17.0제주강30
12022-01-01 18:30서귀포영해정박안함3360126160양호배터리 방전운항저해188000낚시어선3.0제주FRP3
22022-01-01 18:46여수영해정박안함34375127570양호정비불량키손상188000기타10.0여수강10
32022-01-02 09:44통영항계 내정박안함34593512801양호정비불량침수100000기타0.5사천FRP0
42022-01-02 10:51통영항계 내정박3449391282357양호관리소홀해양오염100000유조선126.0부산강14
52022-01-02 11:17창원영해정박안함351131284815양호운항부주의충돌266000낚시어선4.97부산FRP14
62022-01-02 11:30목포영해-EEZ정박33310124160양호운항부주의접촉22121000어선85.0부산강32
72022-01-02 13:35군산영해-EEZ정박안함35336125101양호화기취급부주의화재155000어선29.0목포FRP31
82022-01-02 17:00제주영해정박안함3335261262236양호원인미상침수199000어선29.0서귀포FRP20
92022-01-02 18:02포항영해정박안함3542141293745황천5급정비불량기관손상155000어선9.77기타FRP6
발생일시관할해경서발생해역정박(계류)여부위도_도위도_분위도_초경도_도경도_분경도_초기상상태발생원인발생유형사고선박수발생인원구조부상사망실종선종톤수선적지선질선령
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34392022-12-31 08:47울진영해정박안함363601293760양호기상악화침수122000어선9.77기타FRP1
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34422022-12-31 12:27완도항계 내정박안함34160126550양호운항부주의기관손상111000어선2.65완도FRP5
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34442022-12-31 16:52속초영해정박안함381501283611양호운항부주의부유물감김111000어선24.0속초FRP5
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