Overview

Dataset statistics

Number of variables12
Number of observations38
Missing cells46
Missing cells (%)10.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.8 KiB
Average record size in memory101.5 B

Variable types

Numeric2
Categorical5
DateTime1
Text4

Dataset

Description지리산, 설악산국립공원에서 2019년에 발생한 안전사고에 대해 날짜, 요일, 관할 사무소, 사고 유형 등의 데이터를 포함하고 있습니다.
Author국립공원공단
URLhttps://www.data.go.kr/data/15090303/fileData.do

Alerts

유형 is highly overall correlated with 구분High correlation
구분 is highly overall correlated with 유형High correlation
좌표(위도) has 23 (60.5%) missing valuesMissing
좌표(경도) has 23 (60.5%) missing valuesMissing

Reproduction

Analysis started2023-12-12 07:17:45.404668
Analysis finished2023-12-12 07:17:46.774593
Duration1.37 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

월
Real number (ℝ)

Distinct10
Distinct (%)26.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7
Minimum1
Maximum11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size474.0 B
2023-12-12T16:17:46.834182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q15.25
median8
Q310
95-th percentile10.15
Maximum11
Range10
Interquartile range (IQR)4.75

Descriptive statistics

Standard deviation2.9591818
Coefficient of variation (CV)0.42274025
Kurtosis-0.80697574
Mean7
Median Absolute Deviation (MAD)2
Skewness-0.56808608
Sum266
Variance8.7567568
MonotonicityIncreasing
2023-12-12T16:17:46.956702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
10 9
23.7%
6 6
15.8%
8 6
15.8%
2 5
13.2%
9 3
 
7.9%
4 2
 
5.3%
5 2
 
5.3%
7 2
 
5.3%
11 2
 
5.3%
1 1
 
2.6%
ValueCountFrequency (%)
1 1
 
2.6%
2 5
13.2%
4 2
 
5.3%
5 2
 
5.3%
6 6
15.8%
7 2
 
5.3%
8 6
15.8%
9 3
 
7.9%
10 9
23.7%
11 2
 
5.3%
ValueCountFrequency (%)
11 2
 
5.3%
10 9
23.7%
9 3
 
7.9%
8 6
15.8%
7 2
 
5.3%
6 6
15.8%
5 2
 
5.3%
4 2
 
5.3%
2 5
13.2%
1 1
 
2.6%

일
Real number (ℝ)

Distinct24
Distinct (%)63.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.026316
Minimum1
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size474.0 B
2023-12-12T16:17:47.088382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.85
Q18.25
median15.5
Q325
95-th percentile30
Maximum31
Range30
Interquartile range (IQR)16.75

Descriptive statistics

Standard deviation9.9552698
Coefficient of variation (CV)0.62118268
Kurtosis-1.3665334
Mean16.026316
Median Absolute Deviation (MAD)9.5
Skewness0.0076190912
Sum609
Variance99.107397
MonotonicityNot monotonic
2023-12-12T16:17:47.243894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
19 3
 
7.9%
2 3
 
7.9%
30 3
 
7.9%
10 2
 
5.3%
27 2
 
5.3%
25 2
 
5.3%
1 2
 
5.3%
9 2
 
5.3%
6 2
 
5.3%
12 2
 
5.3%
Other values (14) 15
39.5%
ValueCountFrequency (%)
1 2
5.3%
2 3
7.9%
3 1
 
2.6%
5 1
 
2.6%
6 2
5.3%
8 1
 
2.6%
9 2
5.3%
10 2
5.3%
12 2
5.3%
13 1
 
2.6%
ValueCountFrequency (%)
31 1
 
2.6%
30 3
7.9%
29 2
5.3%
28 1
 
2.6%
27 2
5.3%
25 2
5.3%
24 1
 
2.6%
23 1
 
2.6%
20 1
 
2.6%
19 3
7.9%

요일
Categorical

Distinct6
Distinct (%)15.8%
Missing0
Missing (%)0.0%
Memory size436.0 B
토
18 
일
8 
화
5 
수
4 
월
2 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)2.6%

Sample

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

Common Values

ValueCountFrequency (%)
토 18
47.4%
일 8
21.1%
화 5
 
13.2%
수 4
 
10.5%
월 2
 
5.3%
목 1
 
2.6%

Length

2023-12-12T16:17:47.363707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:17:47.518410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
토 18
47.4%
일 8
21.1%
화 5
 
13.2%
수 4
 
10.5%
월 2
 
5.3%
목 1
 
2.6%

사무소
Categorical

Distinct4
Distinct (%)10.5%
Missing0
Missing (%)0.0%
Memory size436.0 B
설악
27 
경남
7 
전남
3 
전북
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)2.6%

Sample

1st row전남
2nd row전남
3rd row경남
4th row전남
5th row설악

Common Values

ValueCountFrequency (%)
설악 27
71.1%
경남 7
 
18.4%
전남 3
 
7.9%
전북 1
 
2.6%

Length

2023-12-12T16:17:47.727045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:17:47.895583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
설악 27
71.1%
경남 7
 
18.4%
전남 3
 
7.9%
전북 1
 
2.6%

시 간
Date

Distinct33
Distinct (%)86.8%
Missing0
Missing (%)0.0%
Memory size436.0 B
Minimum2023-12-12 03:28:00
Maximum2023-12-12 17:47:00
2023-12-12T16:17:48.048684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:17:48.190586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)

위 치
Text

Distinct37
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Memory size436.0 B
2023-12-12T16:17:48.468617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length18.5
Mean length12.815789
Min length3

Characters and Unicode

Total characters487
Distinct characters130
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)94.7%

Sample

1st row성삼재~노고단 방향 1km
2nd row직전마을 거점 초소 인근
3rd row상불재 부근
4th row도계삼거리→성삼재주차장 방향 1km지점
5th row설악 10-02지점
ValueCountFrequency (%)
일원 13
 
12.5%
노적봉 3
 
2.9%
암벽 3
 
2.9%
정상 3
 
2.9%
방향 2
 
1.9%
백담지구 2
 
1.9%
일원(소토왕골 2
 
1.9%
주전골 2
 
1.9%
상단 2
 
1.9%
다목적위치 1
 
1.0%
Other values (71) 71
68.3%
2023-12-12T16:17:48.931149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
67
 
13.8%
원 21
 
4.3%
0 19
 
3.9%
일 18
 
3.7%
지 13
 
2.7%
1 13
 
2.7%
구 9
 
1.8%
- 9
 
1.8%
봉 9
 
1.8%
( 8
 
1.6%
Other values (120) 301
61.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 335
68.8%
Space Separator 67
 
13.8%
Decimal Number 48
 
9.9%
Dash Punctuation 9
 
1.8%
Open Punctuation 8
 
1.6%
Close Punctuation 8
 
1.6%
Lowercase Letter 7
 
1.4%
Math Symbol 5
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 21
 
6.3%
일 18
 
5.4%
지 13
 
3.9%
구 9
 
2.7%
봉 9
 
2.7%
폭 8
 
2.4%
대 7
 
2.1%
상 7
 
2.1%
포 7
 
2.1%
적 7
 
2.1%
Other values (104) 229
68.4%
Decimal Number
ValueCountFrequency (%)
0 19
39.6%
1 13
27.1%
2 5
 
10.4%
5 3
 
6.2%
7 2
 
4.2%
6 2
 
4.2%
8 2
 
4.2%
4 2
 
4.2%
Lowercase Letter
ValueCountFrequency (%)
m 5
71.4%
k 2
 
28.6%
Math Symbol
ValueCountFrequency (%)
~ 4
80.0%
→ 1
 
20.0%
Space Separator
ValueCountFrequency (%)
67
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 335
68.8%
Common 145
29.8%
Latin 7
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 21
 
6.3%
일 18
 
5.4%
지 13
 
3.9%
구 9
 
2.7%
봉 9
 
2.7%
폭 8
 
2.4%
대 7
 
2.1%
상 7
 
2.1%
포 7
 
2.1%
적 7
 
2.1%
Other values (104) 229
68.4%
Common
ValueCountFrequency (%)
67
46.2%
0 19
 
13.1%
1 13
 
9.0%
- 9
 
6.2%
( 8
 
5.5%
) 8
 
5.5%
2 5
 
3.4%
~ 4
 
2.8%
5 3
 
2.1%
7 2
 
1.4%
Other values (4) 7
 
4.8%
Latin
ValueCountFrequency (%)
m 5
71.4%
k 2
 
28.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 335
68.8%
ASCII 151
31.0%
Arrows 1
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
67
44.4%
0 19
 
12.6%
1 13
 
8.6%
- 9
 
6.0%
( 8
 
5.3%
) 8
 
5.3%
2 5
 
3.3%
m 5
 
3.3%
~ 4
 
2.6%
5 3
 
2.0%
Other values (5) 10
 
6.6%
Hangul
ValueCountFrequency (%)
원 21
 
6.3%
일 18
 
5.4%
지 13
 
3.9%
구 9
 
2.7%
봉 9
 
2.7%
폭 8
 
2.4%
대 7
 
2.1%
상 7
 
2.1%
포 7
 
2.1%
적 7
 
2.1%
Other values (104) 229
68.4%
Arrows
ValueCountFrequency (%)
→ 1
100.0%

좌표(위도)
Text

MISSING 

Distinct14
Distinct (%)93.3%
Missing23
Missing (%)60.5%
Memory size436.0 B
2023-12-12T16:17:49.128698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length9
Min length7

Characters and Unicode

Total characters135
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)86.7%

Sample

1st row35.2665
2nd row35.1427
3rd row38.95919
4th row38.9.51.5493
5th row38.78.8137
ValueCountFrequency (%)
38.07.52 2
 
11.1%
38 2
 
11.1%
35.2665 1
 
5.6%
35.1427 1
 
5.6%
38.95919 1
 
5.6%
38.9.51.5493 1
 
5.6%
38.78.8137 1
 
5.6%
35.20.12.1 1
 
5.6%
8 1
 
5.6%
3.7564 1
 
5.6%
Other values (6) 6
33.3%
2023-12-12T16:17:49.487624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 27
20.0%
3 23
17.0%
5 16
11.9%
8 13
9.6%
7 10
 
7.4%
1 10
 
7.4%
6 8
 
5.9%
0 7
 
5.2%
2 6
 
4.4%
4 6
 
4.4%
Other values (2) 9
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 105
77.8%
Other Punctuation 27
 
20.0%
Space Separator 3
 
2.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 23
21.9%
5 16
15.2%
8 13
12.4%
7 10
9.5%
1 10
9.5%
6 8
 
7.6%
0 7
 
6.7%
2 6
 
5.7%
4 6
 
5.7%
9 6
 
5.7%
Other Punctuation
ValueCountFrequency (%)
. 27
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 135
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 27
20.0%
3 23
17.0%
5 16
11.9%
8 13
9.6%
7 10
 
7.4%
1 10
 
7.4%
6 8
 
5.9%
0 7
 
5.2%
2 6
 
4.4%
4 6
 
4.4%
Other values (2) 9
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 135
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 27
20.0%
3 23
17.0%
5 16
11.9%
8 13
9.6%
7 10
 
7.4%
1 10
 
7.4%
6 8
 
5.9%
0 7
 
5.2%
2 6
 
4.4%
4 6
 
4.4%
Other values (2) 9
 
6.7%

좌표(경도)
Text

MISSING 

Distinct14
Distinct (%)93.3%
Missing23
Missing (%)60.5%
Memory size436.0 B
2023-12-12T16:17:49.727003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length10.4
Min length6

Characters and Unicode

Total characters156
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)86.7%

Sample

1st row127.5793
2nd row127.41
3rd row128.223767
4th row128.29.33.7402
5th row128.27.55.3836
ValueCountFrequency (%)
128.26.01 2
 
11.8%
127.5793 1
 
5.9%
127.41 1
 
5.9%
128.223767 1
 
5.9%
128.29.33.7402 1
 
5.9%
128.27.55.3836 1
 
5.9%
127.43.50.1 1
 
5.9%
128 1
 
5.9%
25 1
 
5.9%
17.6636 1
 
5.9%
Other values (6) 6
35.3%
2023-12-12T16:17:50.104179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 32
20.5%
. 28
17.9%
1 23
14.7%
8 15
9.6%
7 14
9.0%
3 10
 
6.4%
6 8
 
5.1%
4 8
 
5.1%
5 7
 
4.5%
0 5
 
3.2%
Other values (2) 6
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 126
80.8%
Other Punctuation 28
 
17.9%
Space Separator 2
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 32
25.4%
1 23
18.3%
8 15
11.9%
7 14
11.1%
3 10
 
7.9%
6 8
 
6.3%
4 8
 
6.3%
5 7
 
5.6%
0 5
 
4.0%
9 4
 
3.2%
Other Punctuation
ValueCountFrequency (%)
. 28
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 156
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 32
20.5%
. 28
17.9%
1 23
14.7%
8 15
9.6%
7 14
9.0%
3 10
 
6.4%
6 8
 
5.1%
4 8
 
5.1%
5 7
 
4.5%
0 5
 
3.2%
Other values (2) 6
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 156
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 32
20.5%
. 28
17.9%
1 23
14.7%
8 15
9.6%
7 14
9.0%
3 10
 
6.4%
6 8
 
5.1%
4 8
 
5.1%
5 7
 
4.5%
0 5
 
3.2%
Other values (2) 6
 
3.8%

구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size436.0 B
부상
29 
사망
9 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부상 29
76.3%
사망 9
 
23.7%

Length

2023-12-12T16:17:50.247339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:17:50.346617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부상 29
76.3%
사망 9
 
23.7%

유형
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size436.0 B
골절상처
29 
추락사
5 
심정지
4 

Length

Max length4
Median length4
Mean length3.7631579
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
골절상처 29
76.3%
추락사 5
 
13.2%
심정지 4
 
10.5%

Length

2023-12-12T16:17:50.452385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:17:50.564984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
골절상처 29
76.3%
추락사 5
 
13.2%
심정지 4
 
10.5%

구체적 상태
Text

Distinct27
Distinct (%)71.1%
Missing0
Missing (%)0.0%
Memory size436.0 B
2023-12-12T16:17:50.781638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length20
Mean length7.1052632
Min length3

Characters and Unicode

Total characters270
Distinct characters88
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

Unique23 ?
Unique (%)60.5%

Sample

1st row팔.어께골절
2nd row발목골절
3rd row발목골절
4th row발목골절
5th row팔목골절
ValueCountFrequency (%)
발목골절 7
 
9.2%
및 5
 
6.6%
추락사 4
 
5.3%
두부 3
 
3.9%
열상 3
 
3.9%
다리골절 2
 
2.6%
골절 2
 
2.6%
심정지 2
 
2.6%
두부출혈 2
 
2.6%
찰과상 2
 
2.6%
Other values (43) 44
57.9%
2023-12-12T16:17:51.164281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
38
 
14.1%
골 20
 
7.4%
절 18
 
6.7%
상 11
 
4.1%
목 10
 
3.7%
부 10
 
3.7%
발 8
 
3.0%
두 8
 
3.0%
락 6
 
2.2%
열 6
 
2.2%
Other values (78) 135
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 215
79.6%
Space Separator 38
 
14.1%
Other Punctuation 6
 
2.2%
Open Punctuation 3
 
1.1%
Close Punctuation 3
 
1.1%
Decimal Number 3
 
1.1%
Lowercase Letter 2
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
골 20
 
9.3%
절 18
 
8.4%
상 11
 
5.1%
목 10
 
4.7%
부 10
 
4.7%
발 8
 
3.7%
두 8
 
3.7%
락 6
 
2.8%
열 6
 
2.8%
및 5
 
2.3%
Other values (69) 113
52.6%
Other Punctuation
ValueCountFrequency (%)
, 5
83.3%
. 1
 
16.7%
Decimal Number
ValueCountFrequency (%)
1 2
66.7%
6 1
33.3%
Lowercase Letter
ValueCountFrequency (%)
c 1
50.0%
m 1
50.0%
Space Separator
ValueCountFrequency (%)
38
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 215
79.6%
Common 53
 
19.6%
Latin 2
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
골 20
 
9.3%
절 18
 
8.4%
상 11
 
5.1%
목 10
 
4.7%
부 10
 
4.7%
발 8
 
3.7%
두 8
 
3.7%
락 6
 
2.8%
열 6
 
2.8%
및 5
 
2.3%
Other values (69) 113
52.6%
Common
ValueCountFrequency (%)
38
71.7%
, 5
 
9.4%
( 3
 
5.7%
) 3
 
5.7%
1 2
 
3.8%
6 1
 
1.9%
. 1
 
1.9%
Latin
ValueCountFrequency (%)
c 1
50.0%
m 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 215
79.6%
ASCII 55
 
20.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
38
69.1%
, 5
 
9.1%
( 3
 
5.5%
) 3
 
5.5%
1 2
 
3.6%
6 1
 
1.8%
c 1
 
1.8%
. 1
 
1.8%
m 1
 
1.8%
Hangul
ValueCountFrequency (%)
골 20
 
9.3%
절 18
 
8.4%
상 11
 
5.1%
목 10
 
4.7%
부 10
 
4.7%
발 8
 
3.7%
두 8
 
3.7%
락 6
 
2.8%
열 6
 
2.8%
및 5
 
2.3%
Other values (69) 113
52.6%

사고원인
Categorical

Distinct17
Distinct (%)44.7%
Missing0
Missing (%)0.0%
Memory size436.0 B
부주의
12 
추락
5 
낙상
4 
심정지
2 
무리한산행
2 
Other values (12)
13 

Length

Max length9
Median length7
Mean length3.7105263
Min length2

Unique

Unique11 ?
Unique (%)28.9%

Sample

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

Common Values

ValueCountFrequency (%)
부주의 12
31.6%
추락 5
13.2%
낙상 4
 
10.5%
심정지 2
 
5.3%
무리한산행 2
 
5.3%
부주의로 추락 2
 
5.3%
실족, 추락 1
 
2.6%
낙빙 1
 
2.6%
부주의 낙상 1
 
2.6%
실족 1
 
2.6%
Other values (7) 7
18.4%

Length

2023-12-12T16:17:51.324188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
부주의 13
28.3%
추락 8
17.4%
낙상 6
13.0%
부주의로 5
 
10.9%
실족 3
 
6.5%
심정지 2
 
4.3%
무리한산행 2
 
4.3%
낙빙 1
 
2.2%
불법산행 1
 
2.2%
미끄러짐 1
 
2.2%
Other values (4) 4
 
8.7%

Interactions

2023-12-12T16:17:46.180958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:17:46.032750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:17:46.272391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:17:46.101033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T16:17:51.421232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
월일요일사무소시 간위 치좌표(위도)좌표(경도)구분유형구체적 상태사고원인
월1.0000.5050.6340.4230.9541.0001.0001.0000.1790.0000.8630.000
일0.5051.0000.4770.5830.8521.0001.0001.0000.1430.4560.6360.485
요일0.6340.4771.0000.3600.8851.0001.0001.0000.0000.0000.0000.000
사무소0.4230.5830.3601.0000.5241.0001.0001.0000.3180.2150.0000.209
시 간0.9540.8520.8850.5241.0001.0000.9690.9690.0000.0000.9240.925
위 치1.0001.0001.0001.0001.0001.0001.0001.0000.0000.0000.9820.972
좌표(위도)1.0001.0001.0001.0000.9691.0001.0001.0001.0001.0000.9460.949
좌표(경도)1.0001.0001.0001.0000.9691.0001.0001.0001.0001.0000.9460.949
구분0.1790.1430.0000.3180.0000.0001.0001.0001.0001.0001.0000.784
유형0.0000.4560.0000.2150.0000.0001.0001.0001.0001.0001.0000.719
구체적 상태0.8630.6360.0000.0000.9240.9820.9460.9461.0001.0001.0000.950
사고원인0.0000.4850.0000.2090.9250.9720.9490.9490.7840.7190.9501.000
2023-12-12T16:17:51.578609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사무소유형사고원인요일구분
사무소1.0000.1960.0000.2240.201
유형0.1961.0000.4070.0000.986
사고원인0.0000.4071.0000.0000.486
요일0.2240.0000.0001.0000.000
구분0.2010.9860.4860.0001.000
2023-12-12T16:17:51.739633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
월일요일사무소구분유형사고원인
월1.000-0.0920.0000.1740.1550.1050.000
일-0.0921.0000.2030.0840.0000.0000.257
요일0.0000.2031.0000.2240.0000.0000.000
사무소0.1740.0840.2241.0000.2010.1960.000
구분0.1550.0000.0000.2011.0000.9860.486
유형0.1050.0000.0000.1960.9861.0000.407
사고원인0.0000.2570.0000.0000.4860.4071.000

Missing values

2023-12-12T16:17:46.406147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:17:46.587837image/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.
2023-12-12T16:17:46.706663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

월일요일사무소시 간위 치좌표(위도)좌표(경도)구분유형구체적 상태사고원인
0110목전남15:30성삼재~노고단 방향 1km<NA><NA>부상골절상처팔.어께골절낙상
126수전남13:30직전마을 거점 초소 인근35.2665127.5793부상골절상처발목골절부주의
2210일경남14:30상불재 부근35.1427127.41부상골절상처발목골절낙상
3216토전남14:35도계삼거리→성삼재주차장 방향 1km지점<NA><NA>부상골절상처발목골절부주의
4219화설악11:33설악 10-02지점38.95919128.223767부상골절상처팔목골절부주의
5223토설악11:10실폭포<NA><NA>부상골절상처안면부 출혈낙빙
6427토설악13:11노적봉 일원(소토왕골 암벽)<NA><NA>사망추락사추락사심정지
7427토설악13:11노적봉 일원(소토왕골 암벽)<NA><NA>부상골절상처두부 열상추락
8525토설악14:10다목적표지 11-18 구간(남교리)<NA><NA>부상골절상처두부 열상, 팔 다리 타박상부주의 낙상
9525토설악15:17노적봉 정상 일원38.9.51.5493128.29.33.7402부상골절상처손가락 골절 및 온몸 찰과상추락
월일요일사무소시 간위 치좌표(위도)좌표(경도)구분유형구체적 상태사고원인
28106일설악13:10설악동 권금성 일대 망군대(비법정)<NA><NA>사망추락사의식불명추락
29109수설악13:10잦은바위골 100m폭포 하향<NA><NA>부상골절상처다리골절부주의
301012토설악12:20오색~대청구간 제2쉼터 상향 150m<NA><NA>부상골절상처팔골절부주의로 미끄러짐
311014월설악11:53주전골 일원<NA><NA>부상골절상처발목골절부주의
321015화설악09:40대청봉~설악폭포 구간<NA><NA>사망심정지심정지원인미상
331019토경남08:00소막골 야영자 여자화장실35.35.08127.81.58부상골절상처손가락 열상출입문 끼임
341019토설악12:05다목적위치 표지판 07-04 일원<NA><NA>부상골절상처후두부 및 왼쪽머리 열상(6cm)낙상
351030수설악13:12백담지구 10-20<NA><NA>부상골절상처치아파절부주의
36112토설악09:23백담지구 10-21<NA><NA>부상골절상처두부열상부주의
37119토설악08:00남설악탐방지원센터~대청봉 구간(06-06 설악폭포 일원)<NA><NA>사망심정지심정지(중국인)심정지