Overview

Dataset statistics

Number of variables10
Number of observations439
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory36.1 KiB
Average record size in memory84.3 B

Variable types

Categorical5
Text3
Numeric2

Dataset

Description2017~2021년 연간 사망만인율이 규모별 같은 업종 평균 사망만인율 이상인 사업장을 공표. 산업안전보건법 위반죄가 확정된 사업장을 공표. 원도급업체와 동일한 장소에서 작업을 하는 하도급업체의 근로자가 사망한 경우 산업안전보건법 위반으로 처벌받은 원도급업체와 하도급업체의 사업장명을 함께 공표
URLhttps://www.data.go.kr/data/15090126/fileData.do

Alerts

규모별 동종업종 평균 사망만인율(퍼밀리아드) is highly overall correlated with 업종명(중분류)High correlation
연도 is highly overall correlated with 지역High correlation
지역 is highly overall correlated with 연도 High correlation
업종명(중분류) is highly overall correlated with 규모별 동종업종 평균 사망만인율(퍼밀리아드)High correlation
규모 is highly imbalanced (67.6%)Imbalance
사망자수(명) is highly imbalanced (86.6%)Imbalance
사업장명(현장) has unique valuesUnique
사업장 소재지 has unique valuesUnique

Reproduction

Analysis started2023-12-12 23:09:48.440314
Analysis finished2023-12-12 23:09:50.348700
Duration1.91 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
2021
257 
2020
131 
2019
42 
2018
 
6
2017
 
3

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2017
2nd row2017
3rd row2017
4th row2018
5th row2018

Common Values

ValueCountFrequency (%)
2021 257
58.5%
2020 131
29.8%
2019 42
 
9.6%
2018 6
 
1.4%
2017 3
 
0.7%

Length

2023-12-13T08:09:50.430727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:09:50.562597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 257
58.5%
2020 131
29.8%
2019 42
 
9.6%
2018 6
 
1.4%
2017 3
 
0.7%

지역
Categorical

HIGH CORRELATION 

Distinct25
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
경기
104 
경북
40 
경남
39 
서울
36 
인천
29 
Other values (20)
191 

Length

Max length4
Median length2
Mean length2.0364465
Min length2

Unique

Unique6 ?
Unique (%)1.4%

Sample

1st row대구
2nd row충북
3rd row충북
4th row인천
5th row인천

Common Values

ValueCountFrequency (%)
경기 104
23.7%
경북 40
 
9.1%
경남 39
 
8.9%
서울 36
 
8.2%
인천 29
 
6.6%
충남 27
 
6.2%
전남 26
 
5.9%
강원 25
 
5.7%
부산 23
 
5.2%
전북 20
 
4.6%
Other values (15) 70
15.9%

Length

2023-12-13T08:09:50.728192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기 108
24.6%
경북 40
 
9.1%
경남 39
 
8.9%
서울 36
 
8.2%
인천 29
 
6.6%
충남 27
 
6.2%
전남 27
 
6.2%
부산 25
 
5.7%
강원 25
 
5.7%
충북 21
 
4.8%
Other values (7) 62
14.1%

업종명(중분류)
Categorical

HIGH CORRELATION 

Distinct29
Distinct (%)6.6%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
건설업
268 
기계기구·금속·비금속광물제품제조업
53 
시설관리및사업지원서비스업
 
15
화학및고무제품제조업
 
13
수제품및기타제품제조업
 
10
Other values (24)
80 

Length

Max length19
Median length3
Mean length6.9612756
Min length2

Unique

Unique5 ?
Unique (%)1.1%

Sample

1st row섬유또는섬유제품제조업(을)
2nd row건설업
3rd row건설업
4th row건설업
5th row건설업

Common Values

ValueCountFrequency (%)
건설업 268
61.0%
기계기구·금속·비금속광물제품제조업 53
 
12.1%
시설관리및사업지원서비스업 15
 
3.4%
화학및고무제품제조업 13
 
3.0%
수제품및기타제품제조업 10
 
2.3%
도소매·음식·숙박업 9
 
2.1%
기타의각종사업 7
 
1.6%
석회석·금속·비금속광업및기타광업 6
 
1.4%
전문·보건·교육·여가관련서비스업 5
 
1.1%
철도·항공·창고·운수관련서비스업 5
 
1.1%
Other values (19) 48
 
10.9%

Length

2023-12-13T08:09:50.898596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
건설업 272
62.0%
기계기구·금속·비금속광물제품제조업 53
 
12.1%
시설관리및사업지원서비스업 15
 
3.4%
화학및고무제품제조업 13
 
3.0%
수제품및기타제품제조업 10
 
2.3%
도소매·음식·숙박업 9
 
2.1%
기타의각종사업 7
 
1.6%
석회석·금속·비금속광업및기타광업 6
 
1.4%
전문·보건·교육·여가관련서비스업 5
 
1.1%
철도·항공·창고·운수관련서비스업 5
 
1.1%
Other values (16) 44
 
10.0%

규모
Categorical

IMBALANCE 

Distinct7
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
50인미만
372 
50인~99인
 
27
100~299인
 
25
300~499인
 
6
500~999인
 
6
Other values (2)
 
3

Length

Max length9
Median length5
Mean length5.3986333
Min length5

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row50인~99인
2nd row100~299인
3rd row50인미만
4th row50인~99인
5th row50인미만

Common Values

ValueCountFrequency (%)
50인미만 372
84.7%
50인~99인 27
 
6.2%
100~299인 25
 
5.7%
300~499인 6
 
1.4%
500~999인 6
 
1.4%
1,000인이상 2
 
0.5%
100인~299인 1
 
0.2%

Length

2023-12-13T08:09:51.085483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:09:51.260393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
50인미만 372
84.7%
50인~99인 27
 
6.2%
100~299인 25
 
5.7%
300~499인 6
 
1.4%
500~999인 6
 
1.4%
1,000인이상 2
 
0.5%
100인~299인 1
 
0.2%

사업장명(현장)
Text

UNIQUE 

Distinct439
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
2023-12-13T08:09:51.473785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length108
Median length50
Mean length26.492027
Min length3

Characters and Unicode

Total characters11630
Distinct characters526
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique439 ?
Unique (%)100.0%

Sample

1st row원진염직
2nd row일진건설㈜, 삼영글로벌㈜(구), (주)한성에스엘씨(하청)(청풍호 그린 케이블카 조성공사)
3rd row한국전력공사(원청), 삼우전력합자회사(하청)(154kv국사-봉명T/L지장철탑이설공사)
4th row(주)신일(원청), ㈜세정철강(하청)(원창동 물류창고 신축공사)
5th row관악개발㈜(영흥화력제 2부두 하자보수공사)
ValueCountFrequency (%)
개인사업자 36
 
3.6%
신축공사 27
 
2.7%
및 15
 
1.5%
공사 9
 
0.9%
설치공사 5
 
0.5%
공장 4
 
0.4%
주식회사 4
 
0.4%
균열보수 4
 
0.4%
주상복합 4
 
0.4%
근린생활시설 4
 
0.4%
Other values (853) 878
88.7%
2023-12-13T08:09:51.850712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 940
 
8.1%
) 938
 
8.1%
554
 
4.8%
사 374
 
3.2%
주 365
 
3.1%
공 320
 
2.8%
청 312
 
2.7%
설 242
 
2.1%
건 220
 
1.9%
원 193
 
1.7%
Other values (516) 7172
61.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8216
70.6%
Open Punctuation 944
 
8.1%
Close Punctuation 942
 
8.1%
Space Separator 554
 
4.8%
Decimal Number 394
 
3.4%
Other Punctuation 208
 
1.8%
Other Symbol 165
 
1.4%
Uppercase Letter 126
 
1.1%
Dash Punctuation 55
 
0.5%
Lowercase Letter 20
 
0.2%
Other values (2) 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 374
 
4.6%
주 365
 
4.4%
공 320
 
3.9%
청 312
 
3.8%
설 242
 
2.9%
건 220
 
2.7%
원 193
 
2.3%
하 176
 
2.1%
업 154
 
1.9%
이 145
 
1.8%
Other values (458) 5715
69.6%
Uppercase Letter
ValueCountFrequency (%)
B 11
 
8.7%
L 11
 
8.7%
E 10
 
7.9%
G 10
 
7.9%
C 10
 
7.9%
A 9
 
7.1%
T 8
 
6.3%
P 8
 
6.3%
N 8
 
6.3%
M 6
 
4.8%
Other values (12) 35
27.8%
Lowercase Letter
ValueCountFrequency (%)
n 3
15.0%
t 3
15.0%
o 2
10.0%
r 2
10.0%
w 2
10.0%
k 2
10.0%
v 1
 
5.0%
x 1
 
5.0%
l 1
 
5.0%
a 1
 
5.0%
Other values (2) 2
10.0%
Decimal Number
ValueCountFrequency (%)
1 96
24.4%
2 80
20.3%
0 40
10.2%
4 39
9.9%
3 38
 
9.6%
9 23
 
5.8%
6 22
 
5.6%
8 20
 
5.1%
5 18
 
4.6%
7 18
 
4.6%
Other Punctuation
ValueCountFrequency (%)
, 189
90.9%
/ 11
 
5.3%
. 6
 
2.9%
@ 1
 
0.5%
· 1
 
0.5%
Open Punctuation
ValueCountFrequency (%)
( 940
99.6%
[ 4
 
0.4%
Close Punctuation
ValueCountFrequency (%)
) 938
99.6%
] 4
 
0.4%
Space Separator
ValueCountFrequency (%)
554
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 165
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 55
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8381
72.1%
Common 3103
 
26.7%
Latin 146
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 374
 
4.5%
주 365
 
4.4%
공 320
 
3.8%
청 312
 
3.7%
설 242
 
2.9%
건 220
 
2.6%
원 193
 
2.3%
하 176
 
2.1%
㈜ 165
 
2.0%
업 154
 
1.8%
Other values (459) 5860
69.9%
Latin
ValueCountFrequency (%)
B 11
 
7.5%
L 11
 
7.5%
E 10
 
6.8%
G 10
 
6.8%
C 10
 
6.8%
A 9
 
6.2%
T 8
 
5.5%
P 8
 
5.5%
N 8
 
5.5%
M 6
 
4.1%
Other values (24) 55
37.7%
Common
ValueCountFrequency (%)
( 940
30.3%
) 938
30.2%
554
17.9%
, 189
 
6.1%
1 96
 
3.1%
2 80
 
2.6%
- 55
 
1.8%
0 40
 
1.3%
4 39
 
1.3%
3 38
 
1.2%
Other values (13) 134
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8162
70.2%
ASCII 3248
 
27.9%
None 166
 
1.4%
Compat Jamo 54
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 940
28.9%
) 938
28.9%
554
17.1%
, 189
 
5.8%
1 96
 
3.0%
2 80
 
2.5%
- 55
 
1.7%
0 40
 
1.2%
4 39
 
1.2%
3 38
 
1.2%
Other values (46) 279
 
8.6%
Hangul
ValueCountFrequency (%)
사 374
 
4.6%
주 365
 
4.5%
공 320
 
3.9%
청 312
 
3.8%
설 242
 
3.0%
건 220
 
2.7%
원 193
 
2.4%
하 176
 
2.2%
업 154
 
1.9%
이 145
 
1.8%
Other values (457) 5661
69.4%
None
ValueCountFrequency (%)
㈜ 165
99.4%
· 1
 
0.6%
Compat Jamo
ValueCountFrequency (%)
ㅇ 54
100.0%

사업장 소재지
Text

UNIQUE 

Distinct439
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
2023-12-13T08:09:52.156520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length45
Mean length21.897494
Min length12

Characters and Unicode

Total characters9613
Distinct characters369
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique439 ?
Unique (%)100.0%

Sample

1st row대구 서구 달서천로 146 (평리동)
2nd row충북 제천시 청풍면 물태리 산6-29(임) 외 15필지
3rd row충북 청주시 흥덕구 외북로 65 (외북동)
4th row인천 서구 북항로120번길 95 (원창동)
5th row인천 옹진군 영흥면 영흥남로293번길 75 영흥화력발전본부 전면해상
ValueCountFrequency (%)
경기 109
 
4.8%
경북 39
 
1.7%
경남 37
 
1.6%
서울 35
 
1.5%
인천 28
 
1.2%
충남 27
 
1.2%
전남 26
 
1.1%
강원 23
 
1.0%
부산 22
 
1.0%
충북 21
 
0.9%
Other values (1338) 1895
83.8%
2023-12-13T08:09:52.616064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1872
 
19.5%
1 333
 
3.5%
로 276
 
2.9%
시 246
 
2.6%
2 244
 
2.5%
경 208
 
2.2%
3 195
 
2.0%
동 194
 
2.0%
구 188
 
2.0%
산 177
 
1.8%
Other values (359) 5680
59.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5565
57.9%
Space Separator 1872
 
19.5%
Decimal Number 1725
 
17.9%
Dash Punctuation 174
 
1.8%
Close Punctuation 104
 
1.1%
Open Punctuation 104
 
1.1%
Other Punctuation 47
 
0.5%
Uppercase Letter 16
 
0.2%
Lowercase Letter 5
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 276
 
5.0%
시 246
 
4.4%
경 208
 
3.7%
동 194
 
3.5%
구 188
 
3.4%
산 177
 
3.2%
남 170
 
3.1%
길 161
 
2.9%
면 139
 
2.5%
기 126
 
2.3%
Other values (329) 3680
66.1%
Decimal Number
ValueCountFrequency (%)
1 333
19.3%
2 244
14.1%
3 195
11.3%
4 177
10.3%
5 165
9.6%
0 133
 
7.7%
6 130
 
7.5%
7 129
 
7.5%
9 112
 
6.5%
8 107
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
T 3
18.8%
L 3
18.8%
B 3
18.8%
P 2
12.5%
K 2
12.5%
E 1
 
6.2%
Y 1
 
6.2%
M 1
 
6.2%
Lowercase Letter
ValueCountFrequency (%)
t 1
20.0%
n 1
20.0%
a 1
20.0%
l 1
20.0%
m 1
20.0%
Other Punctuation
ValueCountFrequency (%)
, 43
91.5%
. 4
 
8.5%
Space Separator
ValueCountFrequency (%)
1872
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 174
100.0%
Close Punctuation
ValueCountFrequency (%)
) 104
100.0%
Open Punctuation
ValueCountFrequency (%)
( 104
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5565
57.9%
Common 4027
41.9%
Latin 21
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 276
 
5.0%
시 246
 
4.4%
경 208
 
3.7%
동 194
 
3.5%
구 188
 
3.4%
산 177
 
3.2%
남 170
 
3.1%
길 161
 
2.9%
면 139
 
2.5%
기 126
 
2.3%
Other values (329) 3680
66.1%
Common
ValueCountFrequency (%)
1872
46.5%
1 333
 
8.3%
2 244
 
6.1%
3 195
 
4.8%
4 177
 
4.4%
- 174
 
4.3%
5 165
 
4.1%
0 133
 
3.3%
6 130
 
3.2%
7 129
 
3.2%
Other values (7) 475
 
11.8%
Latin
ValueCountFrequency (%)
T 3
14.3%
L 3
14.3%
B 3
14.3%
P 2
9.5%
K 2
9.5%
t 1
 
4.8%
n 1
 
4.8%
a 1
 
4.8%
l 1
 
4.8%
E 1
 
4.8%
Other values (3) 3
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5565
57.9%
ASCII 4048
42.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1872
46.2%
1 333
 
8.2%
2 244
 
6.0%
3 195
 
4.8%
4 177
 
4.4%
- 174
 
4.3%
5 165
 
4.1%
0 133
 
3.3%
6 130
 
3.2%
7 129
 
3.2%
Other values (20) 496
 
12.3%
Hangul
ValueCountFrequency (%)
로 276
 
5.0%
시 246
 
4.4%
경 208
 
3.7%
동 194
 
3.5%
구 188
 
3.4%
산 177
 
3.2%
남 170
 
3.1%
길 161
 
2.9%
면 139
 
2.5%
기 126
 
2.3%
Other values (329) 3680
66.1%

근로자수(명)
Text

Distinct131
Distinct (%)29.8%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
2023-12-13T08:09:52.871080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
Mean length2.1116173
Min length1

Characters and Unicode

Total characters927
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

Unique71 ?
Unique (%)16.2%

Sample

1st row77
2nd row146
3rd row15
4th row79
5th row2
ValueCountFrequency (%)
1 117
26.7%
2 33
 
7.5%
4 23
 
5.2%
3 20
 
4.6%
9 15
 
3.4%
5 14
 
3.2%
6 11
 
2.5%
8 10
 
2.3%
12 9
 
2.1%
13 8
 
1.8%
Other values (92) 179
40.8%
2023-12-13T08:09:53.270473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
256
27.6%
1 218
23.5%
2 95
 
10.2%
3 74
 
8.0%
4 73
 
7.9%
9 42
 
4.5%
6 42
 
4.5%
5 42
 
4.5%
8 34
 
3.7%
7 29
 
3.1%
Other values (2) 22
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 670
72.3%
Space Separator 256
 
27.6%
Other Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 218
32.5%
2 95
14.2%
3 74
 
11.0%
4 73
 
10.9%
9 42
 
6.3%
6 42
 
6.3%
5 42
 
6.3%
8 34
 
5.1%
7 29
 
4.3%
0 21
 
3.1%
Space Separator
ValueCountFrequency (%)
256
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 927
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
256
27.6%
1 218
23.5%
2 95
 
10.2%
3 74
 
8.0%
4 73
 
7.9%
9 42
 
4.5%
6 42
 
4.5%
5 42
 
4.5%
8 34
 
3.7%
7 29
 
3.1%
Other values (2) 22
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 927
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
256
27.6%
1 218
23.5%
2 95
 
10.2%
3 74
 
8.0%
4 73
 
7.9%
9 42
 
4.5%
6 42
 
4.5%
5 42
 
4.5%
8 34
 
3.7%
7 29
 
3.1%
Other values (2) 22
 
2.4%

사망자수(명)
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
1
422 
2
 
14
3
 
2
13
 
1

Length

Max length2
Median length1
Mean length1.0022779
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
1 422
96.1%
2 14
 
3.2%
3 2
 
0.5%
13 1
 
0.2%

Length

2023-12-13T08:09:53.418270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:09:53.526742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 422
96.1%
2 14
 
3.2%
3 2
 
0.5%
13 1
 
0.2%

사망만인율(퍼밀리아드)
Real number (ℝ)

Distinct108
Distinct (%)24.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3796.9621
Minimum2.36
Maximum20000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2023-12-13T08:09:53.664241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.36
5-th percentile54.89
Q1416.67
median1538.46
Q310000
95-th percentile10000
Maximum20000
Range19997.64
Interquartile range (IQR)9583.33

Descriptive statistics

Standard deviation4240.2098
Coefficient of variation (CV)1.1167375
Kurtosis-0.10415437
Mean3796.9621
Median Absolute Deviation (MAD)1411.88
Skewness0.96546032
Sum1666866.4
Variance17979380
MonotonicityNot monotonic
2023-12-13T08:09:53.812456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10000.0 116
26.4%
5000.0 31
 
7.1%
2500.0 23
 
5.2%
3333.33 18
 
4.1%
1111.11 15
 
3.4%
2000.0 13
 
3.0%
1666.67 11
 
2.5%
1250.0 10
 
2.3%
833.33 9
 
2.1%
416.67 8
 
1.8%
Other values (98) 185
42.1%
ValueCountFrequency (%)
2.36 1
0.2%
9.61 1
0.2%
12.64 1
0.2%
13.81 1
0.2%
14.71 1
0.2%
15.27 1
0.2%
17.12 1
0.2%
18.59 1
0.2%
20.08 1
0.2%
25.06 1
0.2%
ValueCountFrequency (%)
20000.0 3
 
0.7%
10000.0 116
26.4%
6666.67 2
 
0.5%
5000.0 31
 
7.1%
4000.0 1
 
0.2%
3333.33 18
 
4.1%
2857.14 1
 
0.2%
2500.0 23
 
5.2%
2000.0 13
 
3.0%
1666.67 11
 
2.5%

규모별 동종업종 평균 사망만인율(퍼밀리아드)
Real number (ℝ)

HIGH CORRELATION 

Distinct72
Distinct (%)16.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.9246925
Minimum0.12
Maximum21.74
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2023-12-13T08:09:53.965192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.12
5-th percentile0.538
Q11.255
median3.34
Q33.34
95-th percentile4.86
Maximum21.74
Range21.62
Interquartile range (IQR)2.085

Descriptive statistics

Standard deviation2.2733707
Coefficient of variation (CV)0.77730248
Kurtosis28.420793
Mean2.9246925
Median Absolute Deviation (MAD)0.95
Skewness4.1527625
Sum1283.94
Variance5.1682145
MonotonicityNot monotonic
2023-12-13T08:09:54.100558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.34 135
30.8%
4.29 73
16.6%
1.16 30
 
6.8%
4.86 19
 
4.3%
2.23 16
 
3.6%
1.24 8
 
1.8%
1.28 7
 
1.6%
1.37 7
 
1.6%
1.86 6
 
1.4%
1.18 6
 
1.4%
Other values (62) 132
30.1%
ValueCountFrequency (%)
0.12 3
0.7%
0.16 1
 
0.2%
0.18 1
 
0.2%
0.21 1
 
0.2%
0.22 6
1.4%
0.26 1
 
0.2%
0.28 1
 
0.2%
0.34 2
 
0.5%
0.37 1
 
0.2%
0.42 1
 
0.2%
ValueCountFrequency (%)
21.74 2
 
0.5%
15.7 4
 
0.9%
9.76 1
 
0.2%
6.47 1
 
0.2%
6.05 2
 
0.5%
4.96 1
 
0.2%
4.86 19
 
4.3%
4.68 3
 
0.7%
4.29 73
16.6%
4.1 1
 
0.2%

Interactions

2023-12-13T08:09:49.829227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:09:49.596035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:09:49.951883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:09:49.719539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:09:54.186014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도지역업종명(중분류)규모사망자수(명)사망만인율(퍼밀리아드)규모별 동종업종 평균 사망만인율(퍼밀리아드)
연도1.0000.8680.5390.0350.2660.0000.434
지역0.8681.0000.5150.0000.3210.0000.190
업종명(중분류)0.5390.5151.0000.0000.0000.1520.869
규모0.0350.0000.0001.0000.2280.2060.243
사망자수(명)0.2660.3210.0000.2281.0000.4820.000
사망만인율(퍼밀리아드)0.0000.0000.1520.2060.4821.0000.250
규모별 동종업종 평균 사망만인율(퍼밀리아드)0.4340.1900.8690.2430.0000.2501.000
2023-12-13T08:09:54.321725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
규모연도사망자수(명)지역업종명(중분류)
규모1.0000.0220.1580.0000.000
연도0.0221.0000.2190.5630.281
사망자수(명)0.1580.2191.0000.1700.000
지역0.0000.5630.1701.0000.146
업종명(중분류)0.0000.2810.0000.1461.000
2023-12-13T08:09:54.435029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사망만인율(퍼밀리아드)규모별 동종업종 평균 사망만인율(퍼밀리아드)연도지역업종명(중분류)규모사망자수(명)
사망만인율(퍼밀리아드)1.0000.3400.0000.0000.0650.1240.330
규모별 동종업종 평균 사망만인율(퍼밀리아드)0.3401.0000.3110.0830.5970.1470.000
연도0.0000.3111.0000.5630.2810.0220.219
지역0.0000.0830.5631.0000.1460.0000.170
업종명(중분류)0.0650.5970.2810.1461.0000.0000.000
규모0.1240.1470.0220.0000.0001.0000.158
사망자수(명)0.3300.0000.2190.1700.0000.1581.000

Missing values

2023-12-13T08:09:50.095028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:09:50.268567image/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

연도지역업종명(중분류)규모사업장명(현장)사업장 소재지근로자수(명)사망자수(명)사망만인율(퍼밀리아드)규모별 동종업종 평균 사망만인율(퍼밀리아드)
02017대구섬유또는섬유제품제조업(을)50인~99인원진염직대구 서구 달서천로 146 (평리동)771129.872.83
12017충북건설업100~299인일진건설㈜, 삼영글로벌㈜(구), (주)한성에스엘씨(하청)(청풍호 그린 케이블카 조성공사)충북 제천시 청풍면 물태리 산6-29(임) 외 15필지1462136.991.62
22017충북건설업50인미만한국전력공사(원청), 삼우전력합자회사(하청)(154kv국사-봉명T/L지장철탑이설공사)충북 청주시 흥덕구 외북로 65 (외북동)151666.674.1
32018인천건설업50인~99인(주)신일(원청), ㈜세정철강(하청)(원창동 물류창고 신축공사)인천 서구 북항로120번길 95 (원창동)791126.582.56
42018인천건설업50인미만관악개발㈜(영흥화력제 2부두 하자보수공사)인천 옹진군 영흥면 영흥남로293번길 75 영흥화력발전본부 전면해상2210000.04.68
52018세종건설업100~299인(주)부원건설(원청), 유아건설(하청)(세종 TREESHADE 주상복합아파트 신축공사)세종 새롬동 2203-11943154.642.25
62018경기건설업50인미만욕실나라(성남보미리즌빌상가 철거공사)경기 성남시 수정구 위례광장로 97 (창곡동, 위례 자연앤 센트럴자이 보미리즌빌상가101)1110000.04.68
72018경기건설업50인미만흥안이앤씨㈜(원청), (주)유스틸(하청)((주)가연 본사사옥 신축공사)경기 안산시 단원구 산단로 295 (원시동)331303.034.68
82018경북섬유또는섬유제품제조업(을)50인미만(주)한영(원청), 세인ENG(하청)경북 고령군 대가야읍 장기공단1길 38-11332606.063.34
92019서울건설업300~499인현대건설(주)(원청), 한민국제화학(주)(하청)(신길9구역 주택재개발 정비사업)서울 영등포구 가마산로80길 35 (신길동) 240-16번지 일대498120.081.39
연도지역업종명(중분류)규모사업장명(현장)사업장 소재지근로자수(명)사망자수(명)사망만인율(퍼밀리아드)규모별 동종업종 평균 사망만인율(퍼밀리아드)
4292021경남임업50인미만남해군산림조합(남해800회선증설선토공사)경남 남해군 남해읍 화전로 46131769.231.98
4302021경남어업50인미만대양호경상남도 거제시 광리길 31 (사등면 덕호리)313333.336.05
4312021경남시설관리및사업지원서비스업100~299인무림페이퍼㈜(원청), (주)맨파워코리아(하청)(무림페이퍼㈜)경남 진주시 남강로 1003106194.340.16
4322021경남시설관리및사업지원서비스업50인~99인(주)한진양산지점(원청), 에스씨케이㈜(하청)경남 양산시 물금읍 제방로 225511196.080.87
4332021경남도소매·음식·숙박업50인미만미농영농조합법인경남 합천군 청덕면 가현길 100-11313333.330.22
4342021경남도소매·음식·숙박업50인미만㈜창신, (주)우철(구)경남 김해시 진례면 고모로 93-30412500.00.22
4352021제주건설업50인미만개인사업자 김동현(금능리근린생활시설및단독주택신축공사)제주 제주시 한림읍 한림로 2141110000.03.34
4362021제주건설업50인미만정우토건㈜(서귀포시대정읍안성리139번지빗물이용시설설치공사)제주 서귀포시 대정읍 안성리 1391110000.03.34
4372021제주건설업50인미만휴아림(휴아림타운하우스신축공사(대정읍안성리1104-2가/신축195))제주 서귀포시 대정읍 안성리 안성리 1104-2번지1110000.03.34
4382021제주육상및수상운수업50인미만형제레카제주 제주시 오남로 7-1215000.03.15