Overview

Dataset statistics

Number of variables17
Number of observations43
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.6 KiB
Average record size in memory156.1 B

Variable types

Numeric17

Dataset

Description동부, 서부, 남부, 중부 광산안전사무소 관할 광산(전국)의 광산 재해 연도별, 유형별 재해 현황(낙반붕락, 운반, 화약 등의 재해자 및 사망자)에 대한 정보 제공
URLhttps://www.data.go.kr/data/15054408/fileData.do

Alerts

연도 is highly overall correlated with 낙반붕락_재해자 and 15 other fieldsHigh correlation
낙반붕락_재해자 is highly overall correlated with 연도 and 15 other fieldsHigh correlation
낙반붕락_사망자 is highly overall correlated with 연도 and 15 other fieldsHigh correlation
운반_재해자 is highly overall correlated with 연도 and 15 other fieldsHigh correlation
운반_사망자 is highly overall correlated with 연도 and 15 other fieldsHigh correlation
화약_재해자 is highly overall correlated with 연도 and 15 other fieldsHigh correlation
화약_사망자 is highly overall correlated with 연도 and 15 other fieldsHigh correlation
가스_재해자 is highly overall correlated with 연도 and 15 other fieldsHigh correlation
가스_사망자 is highly overall correlated with 연도 and 15 other fieldsHigh correlation
출수_재해자 is highly overall correlated with 연도 and 15 other fieldsHigh correlation
출수_사망자 is highly overall correlated with 연도 and 15 other fieldsHigh correlation
추락-전석_재해자 is highly overall correlated with 연도 and 15 other fieldsHigh correlation
추락-전석_사망자 is highly overall correlated with 연도 and 15 other fieldsHigh correlation
기계-전기_재해자 is highly overall correlated with 연도 and 15 other fieldsHigh correlation
기계-전기_사망자 is highly overall correlated with 연도 and 15 other fieldsHigh correlation
기타_재해자 is highly overall correlated with 연도 and 15 other fieldsHigh correlation
기타_사망자 is highly overall correlated with 연도 and 15 other fieldsHigh correlation
연도 has unique valuesUnique
낙반붕락_사망자 has 3 (7.0%) zerosZeros
운반_사망자 has 6 (14.0%) zerosZeros
화약_재해자 has 6 (14.0%) zerosZeros
화약_사망자 has 19 (44.2%) zerosZeros
가스_재해자 has 14 (32.6%) zerosZeros
가스_사망자 has 17 (39.5%) zerosZeros
출수_재해자 has 20 (46.5%) zerosZeros
출수_사망자 has 23 (53.5%) zerosZeros
추락-전석_사망자 has 12 (27.9%) zerosZeros
기계-전기_재해자 has 1 (2.3%) zerosZeros
기계-전기_사망자 has 13 (30.2%) zerosZeros
기타_사망자 has 19 (44.2%) zerosZeros

Reproduction

Analysis started2023-12-12 07:04:11.212191
Analysis finished2023-12-12 07:04:44.595436
Duration33.38 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct43
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2001
Minimum1980
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-12T16:04:44.670669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1980
5-th percentile1982.1
Q11990.5
median2001
Q32011.5
95-th percentile2019.9
Maximum2022
Range42
Interquartile range (IQR)21

Descriptive statistics

Standard deviation12.556539
Coefficient of variation (CV)0.0062751318
Kurtosis-1.2
Mean2001
Median Absolute Deviation (MAD)11
Skewness0
Sum86043
Variance157.66667
MonotonicityStrictly increasing
2023-12-12T16:04:44.818716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
1980 1
 
2.3%
1981 1
 
2.3%
2004 1
 
2.3%
2005 1
 
2.3%
2006 1
 
2.3%
2007 1
 
2.3%
2008 1
 
2.3%
2009 1
 
2.3%
2010 1
 
2.3%
2011 1
 
2.3%
Other values (33) 33
76.7%
ValueCountFrequency (%)
1980 1
2.3%
1981 1
2.3%
1982 1
2.3%
1983 1
2.3%
1984 1
2.3%
1985 1
2.3%
1986 1
2.3%
1987 1
2.3%
1988 1
2.3%
1989 1
2.3%
ValueCountFrequency (%)
2022 1
2.3%
2021 1
2.3%
2020 1
2.3%
2019 1
2.3%
2018 1
2.3%
2017 1
2.3%
2016 1
2.3%
2015 1
2.3%
2014 1
2.3%
2013 1
2.3%

낙반붕락_재해자
Real number (ℝ)

HIGH CORRELATION 

Distinct39
Distinct (%)90.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean484.23256
Minimum3
Maximum1694
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-12T16:04:44.946246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile6.1
Q114.5
median49
Q31296
95-th percentile1599.4
Maximum1694
Range1691
Interquartile range (IQR)1281.5

Descriptive statistics

Standard deviation672.68456
Coefficient of variation (CV)1.3891766
Kurtosis-1.0164559
Mean484.23256
Median Absolute Deviation (MAD)42
Skewness0.94689824
Sum20822
Variance452504.52
MonotonicityNot monotonic
2023-12-12T16:04:45.146437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
12 2
 
4.7%
30 2
 
4.7%
8 2
 
4.7%
18 2
 
4.7%
1648 1
 
2.3%
35 1
 
2.3%
11 1
 
2.3%
16 1
 
2.3%
28 1
 
2.3%
25 1
 
2.3%
Other values (29) 29
67.4%
ValueCountFrequency (%)
3 1
2.3%
5 1
2.3%
6 1
2.3%
7 1
2.3%
8 2
4.7%
10 1
2.3%
11 1
2.3%
12 2
4.7%
13 1
2.3%
16 1
2.3%
ValueCountFrequency (%)
1694 1
2.3%
1648 1
2.3%
1600 1
2.3%
1594 1
2.3%
1581 1
2.3%
1547 1
2.3%
1525 1
2.3%
1511 1
2.3%
1499 1
2.3%
1496 1
2.3%

낙반붕락_사망자
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct24
Distinct (%)55.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.604651
Minimum0
Maximum130
Zeros3
Zeros (%)7.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-12T16:04:45.302270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.1
Q12
median5
Q362.5
95-th percentile120
Maximum130
Range130
Interquartile range (IQR)60.5

Descriptive statistics

Standard deviation47.767861
Coefficient of variation (CV)1.3803885
Kurtosis-0.54425344
Mean34.604651
Median Absolute Deviation (MAD)4
Skewness1.1146712
Sum1488
Variance2281.7685
MonotonicityNot monotonic
2023-12-12T16:04:45.469360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
2 5
 
11.6%
1 5
 
11.6%
4 4
 
9.3%
3 3
 
7.0%
0 3
 
7.0%
5 3
 
7.0%
120 3
 
7.0%
115 1
 
2.3%
16 1
 
2.3%
8 1
 
2.3%
Other values (14) 14
32.6%
ValueCountFrequency (%)
0 3
7.0%
1 5
11.6%
2 5
11.6%
3 3
7.0%
4 4
9.3%
5 3
7.0%
7 1
 
2.3%
8 1
 
2.3%
11 1
 
2.3%
13 1
 
2.3%
ValueCountFrequency (%)
130 1
 
2.3%
123 1
 
2.3%
120 3
7.0%
118 1
 
2.3%
117 1
 
2.3%
115 1
 
2.3%
111 1
 
2.3%
81 1
 
2.3%
77 1
 
2.3%
48 1
 
2.3%

운반_재해자
Real number (ℝ)

HIGH CORRELATION 

Distinct36
Distinct (%)83.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean481.60465
Minimum1
Maximum1983
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-12T16:04:45.597435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q111
median38
Q3926.5
95-th percentile1819.9
Maximum1983
Range1982
Interquartile range (IQR)915.5

Descriptive statistics

Standard deviation714.33579
Coefficient of variation (CV)1.4832411
Kurtosis-0.46955077
Mean481.60465
Median Absolute Deviation (MAD)34
Skewness1.1420389
Sum20709
Variance510275.63
MonotonicityNot monotonic
2023-12-12T16:04:45.727892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
7 3
 
7.0%
11 2
 
4.7%
1 2
 
4.7%
3 2
 
4.7%
17 2
 
4.7%
14 2
 
4.7%
1983 1
 
2.3%
38 1
 
2.3%
21 1
 
2.3%
23 1
 
2.3%
Other values (26) 26
60.5%
ValueCountFrequency (%)
1 2
4.7%
3 2
4.7%
4 1
 
2.3%
5 1
 
2.3%
6 1
 
2.3%
7 3
7.0%
11 2
4.7%
13 1
 
2.3%
14 2
4.7%
16 1
 
2.3%
ValueCountFrequency (%)
1983 1
2.3%
1926 1
2.3%
1822 1
2.3%
1801 1
2.3%
1708 1
2.3%
1703 1
2.3%
1631 1
2.3%
1557 1
2.3%
1443 1
2.3%
1381 1
2.3%

운반_사망자
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct18
Distinct (%)41.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.1162791
Minimum0
Maximum45
Zeros6
Zeros (%)14.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-12T16:04:45.851819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q315.5
95-th percentile24
Maximum45
Range45
Interquartile range (IQR)14.5

Descriptive statistics

Standard deviation10.238139
Coefficient of variation (CV)1.2614326
Kurtosis2.6184378
Mean8.1162791
Median Absolute Deviation (MAD)2
Skewness1.5852785
Sum349
Variance104.81949
MonotonicityNot monotonic
2023-12-12T16:04:45.979099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
1 10
23.3%
0 6
14.0%
2 6
14.0%
24 2
 
4.7%
20 2
 
4.7%
3 2
 
4.7%
12 2
 
4.7%
4 2
 
4.7%
16 2
 
4.7%
5 1
 
2.3%
Other values (8) 8
18.6%
ValueCountFrequency (%)
0 6
14.0%
1 10
23.3%
2 6
14.0%
3 2
 
4.7%
4 2
 
4.7%
5 1
 
2.3%
7 1
 
2.3%
10 1
 
2.3%
12 2
 
4.7%
15 1
 
2.3%
ValueCountFrequency (%)
45 1
2.3%
29 1
2.3%
24 2
4.7%
22 1
2.3%
20 2
4.7%
19 1
2.3%
17 1
2.3%
16 2
4.7%
15 1
2.3%
12 2
4.7%

화약_재해자
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct23
Distinct (%)53.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.697674
Minimum0
Maximum102
Zeros6
Zeros (%)14.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-12T16:04:46.077730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.5
median6
Q367.5
95-th percentile100.8
Maximum102
Range102
Interquartile range (IQR)66

Descriptive statistics

Standard deviation38.70987
Coefficient of variation (CV)1.3488853
Kurtosis-0.83099981
Mean28.697674
Median Absolute Deviation (MAD)5
Skewness0.99565563
Sum1234
Variance1498.454
MonotonicityNot monotonic
2023-12-12T16:04:46.187021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 6
14.0%
1 5
 
11.6%
4 4
 
9.3%
2 3
 
7.0%
3 3
 
7.0%
6 3
 
7.0%
8 2
 
4.7%
102 2
 
4.7%
99 1
 
2.3%
18 1
 
2.3%
Other values (13) 13
30.2%
ValueCountFrequency (%)
0 6
14.0%
1 5
11.6%
2 3
7.0%
3 3
7.0%
4 4
9.3%
6 3
7.0%
7 1
 
2.3%
8 2
 
4.7%
9 1
 
2.3%
18 1
 
2.3%
ValueCountFrequency (%)
102 2
4.7%
101 1
2.3%
99 1
2.3%
96 1
2.3%
89 1
2.3%
86 1
2.3%
85 1
2.3%
84 1
2.3%
74 1
2.3%
73 1
2.3%

화약_사망자
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct13
Distinct (%)30.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.3488372
Minimum0
Maximum16
Zeros19
Zeros (%)44.2%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-12T16:04:46.308955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q36
95-th percentile12
Maximum16
Range16
Interquartile range (IQR)6

Descriptive statistics

Standard deviation4.6490333
Coefficient of variation (CV)1.388253
Kurtosis0.26289477
Mean3.3488372
Median Absolute Deviation (MAD)1
Skewness1.2567712
Sum144
Variance21.613511
MonotonicityNot monotonic
2023-12-12T16:04:46.417168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 19
44.2%
1 6
 
14.0%
9 3
 
7.0%
12 3
 
7.0%
2 3
 
7.0%
3 2
 
4.7%
16 1
 
2.3%
13 1
 
2.3%
8 1
 
2.3%
5 1
 
2.3%
Other values (3) 3
 
7.0%
ValueCountFrequency (%)
0 19
44.2%
1 6
 
14.0%
2 3
 
7.0%
3 2
 
4.7%
4 1
 
2.3%
5 1
 
2.3%
7 1
 
2.3%
8 1
 
2.3%
9 3
 
7.0%
10 1
 
2.3%
ValueCountFrequency (%)
16 1
 
2.3%
13 1
 
2.3%
12 3
7.0%
10 1
 
2.3%
9 3
7.0%
8 1
 
2.3%
7 1
 
2.3%
5 1
 
2.3%
4 1
 
2.3%
3 2
4.7%

가스_재해자
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct17
Distinct (%)39.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.465116
Minimum0
Maximum71
Zeros14
Zeros (%)32.6%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-12T16:04:46.536628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q319
95-th percentile36.9
Maximum71
Range71
Interquartile range (IQR)19

Descriptive statistics

Standard deviation15.727363
Coefficient of variation (CV)1.3717578
Kurtosis4.219209
Mean11.465116
Median Absolute Deviation (MAD)5
Skewness1.8894067
Sum493
Variance247.34994
MonotonicityNot monotonic
2023-12-12T16:04:46.671277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 14
32.6%
1 5
 
11.6%
16 3
 
7.0%
5 3
 
7.0%
2 2
 
4.7%
23 2
 
4.7%
21 2
 
4.7%
17 2
 
4.7%
6 2
 
4.7%
37 1
 
2.3%
Other values (7) 7
16.3%
ValueCountFrequency (%)
0 14
32.6%
1 5
 
11.6%
2 2
 
4.7%
5 3
 
7.0%
6 2
 
4.7%
15 1
 
2.3%
16 3
 
7.0%
17 2
 
4.7%
21 2
 
4.7%
22 1
 
2.3%
ValueCountFrequency (%)
71 1
2.3%
52 1
2.3%
37 1
2.3%
36 1
2.3%
30 1
2.3%
24 1
2.3%
23 2
4.7%
22 1
2.3%
21 2
4.7%
17 2
4.7%

가스_사망자
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct16
Distinct (%)37.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.0697674
Minimum0
Maximum20
Zeros17
Zeros (%)39.5%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-12T16:04:46.793317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q37
95-th percentile13.9
Maximum20
Range20
Interquartile range (IQR)7

Descriptive statistics

Standard deviation5.2707429
Coefficient of variation (CV)1.2950968
Kurtosis0.87108184
Mean4.0697674
Median Absolute Deviation (MAD)1
Skewness1.2870076
Sum175
Variance27.780731
MonotonicityNot monotonic
2023-12-12T16:04:46.903969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0 17
39.5%
1 6
 
14.0%
11 3
 
7.0%
4 2
 
4.7%
7 2
 
4.7%
2 2
 
4.7%
6 2
 
4.7%
9 1
 
2.3%
13 1
 
2.3%
5 1
 
2.3%
Other values (6) 6
 
14.0%
ValueCountFrequency (%)
0 17
39.5%
1 6
 
14.0%
2 2
 
4.7%
3 1
 
2.3%
4 2
 
4.7%
5 1
 
2.3%
6 2
 
4.7%
7 2
 
4.7%
8 1
 
2.3%
9 1
 
2.3%
ValueCountFrequency (%)
20 1
 
2.3%
16 1
 
2.3%
14 1
 
2.3%
13 1
 
2.3%
11 3
7.0%
10 1
 
2.3%
9 1
 
2.3%
8 1
 
2.3%
7 2
4.7%
6 2
4.7%

출수_재해자
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct19
Distinct (%)44.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.3488372
Minimum0
Maximum37
Zeros20
Zeros (%)46.5%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-12T16:04:47.022772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q314.5
95-th percentile32.8
Maximum37
Range37
Interquartile range (IQR)14.5

Descriptive statistics

Standard deviation11.698359
Coefficient of variation (CV)1.4011962
Kurtosis0.38836544
Mean8.3488372
Median Absolute Deviation (MAD)1
Skewness1.285376
Sum359
Variance136.85161
MonotonicityNot monotonic
2023-12-12T16:04:47.161804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 20
46.5%
31 2
 
4.7%
9 2
 
4.7%
2 2
 
4.7%
1 2
 
4.7%
16 2
 
4.7%
37 1
 
2.3%
28 1
 
2.3%
21 1
 
2.3%
13 1
 
2.3%
Other values (9) 9
20.9%
ValueCountFrequency (%)
0 20
46.5%
1 2
 
4.7%
2 2
 
4.7%
3 1
 
2.3%
5 1
 
2.3%
6 1
 
2.3%
9 2
 
4.7%
10 1
 
2.3%
13 1
 
2.3%
14 1
 
2.3%
ValueCountFrequency (%)
37 1
2.3%
36 1
2.3%
33 1
2.3%
31 2
4.7%
28 1
2.3%
21 1
2.3%
20 1
2.3%
16 2
4.7%
15 1
2.3%
14 1
2.3%

출수_사망자
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct13
Distinct (%)30.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.3488372
Minimum0
Maximum20
Zeros23
Zeros (%)53.5%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-12T16:04:47.273094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q35
95-th percentile14.7
Maximum20
Range20
Interquartile range (IQR)5

Descriptive statistics

Standard deviation5.1171221
Coefficient of variation (CV)1.5280295
Kurtosis2.2131918
Mean3.3488372
Median Absolute Deviation (MAD)0
Skewness1.6765624
Sum144
Variance26.184939
MonotonicityNot monotonic
2023-12-12T16:04:47.381235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 23
53.5%
3 3
 
7.0%
5 3
 
7.0%
2 2
 
4.7%
9 2
 
4.7%
7 2
 
4.7%
1 2
 
4.7%
12 1
 
2.3%
20 1
 
2.3%
16 1
 
2.3%
Other values (3) 3
 
7.0%
ValueCountFrequency (%)
0 23
53.5%
1 2
 
4.7%
2 2
 
4.7%
3 3
 
7.0%
5 3
 
7.0%
7 2
 
4.7%
8 1
 
2.3%
9 2
 
4.7%
11 1
 
2.3%
12 1
 
2.3%
ValueCountFrequency (%)
20 1
 
2.3%
16 1
 
2.3%
15 1
 
2.3%
12 1
 
2.3%
11 1
 
2.3%
9 2
4.7%
8 1
 
2.3%
7 2
4.7%
5 3
7.0%
3 3
7.0%

추락-전석_재해자
Real number (ℝ)

HIGH CORRELATION 

Distinct31
Distinct (%)72.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean260.39535
Minimum2
Maximum1076
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-12T16:04:47.506608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2.1
Q17
median13
Q3409
95-th percentile1005.7
Maximum1076
Range1074
Interquartile range (IQR)402

Descriptive statistics

Standard deviation395.54123
Coefficient of variation (CV)1.5190027
Kurtosis-0.41481854
Mean260.39535
Median Absolute Deviation (MAD)11
Skewness1.1862081
Sum11197
Variance156452.86
MonotonicityNot monotonic
2023-12-12T16:04:47.622418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
8 5
 
11.6%
3 4
 
9.3%
2 3
 
7.0%
9 3
 
7.0%
4 2
 
4.7%
1006 1
 
2.3%
1076 1
 
2.3%
5 1
 
2.3%
10 1
 
2.3%
11 1
 
2.3%
Other values (21) 21
48.8%
ValueCountFrequency (%)
2 3
7.0%
3 4
9.3%
4 2
 
4.7%
5 1
 
2.3%
6 1
 
2.3%
8 5
11.6%
9 3
7.0%
10 1
 
2.3%
11 1
 
2.3%
13 1
 
2.3%
ValueCountFrequency (%)
1076 1
2.3%
1026 1
2.3%
1006 1
2.3%
1003 1
2.3%
955 1
2.3%
941 1
2.3%
920 1
2.3%
898 1
2.3%
823 1
2.3%
815 1
2.3%

추락-전석_사망자
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct12
Distinct (%)27.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.2325581
Minimum0
Maximum15
Zeros12
Zeros (%)27.9%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-12T16:04:47.721190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q34.5
95-th percentile13.9
Maximum15
Range15
Interquartile range (IQR)4.5

Descriptive statistics

Standard deviation4.2974921
Coefficient of variation (CV)1.32944
Kurtosis2.1264961
Mean3.2325581
Median Absolute Deviation (MAD)1
Skewness1.7261116
Sum139
Variance18.468439
MonotonicityNot monotonic
2023-12-12T16:04:47.831028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 12
27.9%
1 11
25.6%
2 4
 
9.3%
5 3
 
7.0%
4 3
 
7.0%
15 2
 
4.7%
6 2
 
4.7%
3 2
 
4.7%
13 1
 
2.3%
11 1
 
2.3%
Other values (2) 2
 
4.7%
ValueCountFrequency (%)
0 12
27.9%
1 11
25.6%
2 4
 
9.3%
3 2
 
4.7%
4 3
 
7.0%
5 3
 
7.0%
6 2
 
4.7%
7 1
 
2.3%
11 1
 
2.3%
13 1
 
2.3%
ValueCountFrequency (%)
15 2
4.7%
14 1
 
2.3%
13 1
 
2.3%
11 1
 
2.3%
7 1
 
2.3%
6 2
4.7%
5 3
7.0%
4 3
7.0%
3 2
4.7%
2 4
9.3%

기계-전기_재해자
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct29
Distinct (%)67.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean65
Minimum0
Maximum229
Zeros1
Zeros (%)2.3%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-12T16:04:48.007390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q16
median16
Q3136.5
95-th percentile225.8
Maximum229
Range229
Interquartile range (IQR)130.5

Descriptive statistics

Standard deviation85.026326
Coefficient of variation (CV)1.3080973
Kurtosis-0.7017481
Mean65
Median Absolute Deviation (MAD)12
Skewness1.0491591
Sum2795
Variance7229.4762
MonotonicityNot monotonic
2023-12-12T16:04:48.128400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
6 5
 
11.6%
5 4
 
9.3%
3 3
 
7.0%
7 3
 
7.0%
26 2
 
4.7%
10 2
 
4.7%
229 2
 
4.7%
28 1
 
2.3%
0 1
 
2.3%
8 1
 
2.3%
Other values (19) 19
44.2%
ValueCountFrequency (%)
0 1
 
2.3%
2 1
 
2.3%
3 3
7.0%
4 1
 
2.3%
5 4
9.3%
6 5
11.6%
7 3
7.0%
8 1
 
2.3%
10 2
 
4.7%
16 1
 
2.3%
ValueCountFrequency (%)
229 2
4.7%
227 1
2.3%
215 1
2.3%
208 1
2.3%
206 1
2.3%
205 1
2.3%
191 1
2.3%
183 1
2.3%
170 1
2.3%
166 1
2.3%

기계-전기_사망자
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct8
Distinct (%)18.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9302326
Minimum0
Maximum7
Zeros13
Zeros (%)30.2%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-12T16:04:48.249261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile5.9
Maximum7
Range7
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.0632308
Coefficient of variation (CV)1.0689027
Kurtosis0.0050173807
Mean1.9302326
Median Absolute Deviation (MAD)1
Skewness1.0020099
Sum83
Variance4.2569214
MonotonicityNot monotonic
2023-12-12T16:04:48.399618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 13
30.2%
0 13
30.2%
3 5
 
11.6%
4 4
 
9.3%
5 3
 
7.0%
7 2
 
4.7%
2 2
 
4.7%
6 1
 
2.3%
ValueCountFrequency (%)
0 13
30.2%
1 13
30.2%
2 2
 
4.7%
3 5
 
11.6%
4 4
 
9.3%
5 3
 
7.0%
6 1
 
2.3%
7 2
 
4.7%
ValueCountFrequency (%)
7 2
 
4.7%
6 1
 
2.3%
5 3
 
7.0%
4 4
 
9.3%
3 5
 
11.6%
2 2
 
4.7%
1 13
30.2%
0 13
30.2%

기타_재해자
Real number (ℝ)

HIGH CORRELATION 

Distinct31
Distinct (%)72.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean449.2093
Minimum2
Maximum1793
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-12T16:04:48.581440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3
Q15
median23
Q3786
95-th percentile1767.5
Maximum1793
Range1791
Interquartile range (IQR)781

Descriptive statistics

Standard deviation684.53865
Coefficient of variation (CV)1.5238746
Kurtosis-0.47427949
Mean449.2093
Median Absolute Deviation (MAD)20
Skewness1.162569
Sum19316
Variance468593.17
MonotonicityNot monotonic
2023-12-12T16:04:48.741688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
4 5
 
11.6%
3 3
 
7.0%
5 3
 
7.0%
9 3
 
7.0%
6 2
 
4.7%
13 2
 
4.7%
1621 1
 
2.3%
1618 1
 
2.3%
2 1
 
2.3%
7 1
 
2.3%
Other values (21) 21
48.8%
ValueCountFrequency (%)
2 1
 
2.3%
3 3
7.0%
4 5
11.6%
5 3
7.0%
6 2
 
4.7%
7 1
 
2.3%
9 3
7.0%
10 1
 
2.3%
13 2
 
4.7%
23 1
 
2.3%
ValueCountFrequency (%)
1793 1
2.3%
1785 1
2.3%
1769 1
2.3%
1754 1
2.3%
1621 1
2.3%
1618 1
2.3%
1571 1
2.3%
1527 1
2.3%
1508 1
2.3%
1348 1
2.3%

기타_사망자
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct9
Distinct (%)20.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9534884
Minimum0
Maximum17
Zeros19
Zeros (%)44.2%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-12T16:04:48.874307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32.5
95-th percentile6.9
Maximum17
Range17
Interquartile range (IQR)2.5

Descriptive statistics

Standard deviation3.139256
Coefficient of variation (CV)1.6070001
Kurtosis11.908297
Mean1.9534884
Median Absolute Deviation (MAD)1
Skewness2.9894949
Sum84
Variance9.854928
MonotonicityNot monotonic
2023-12-12T16:04:49.007992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 19
44.2%
1 8
18.6%
2 5
 
11.6%
4 3
 
7.0%
3 2
 
4.7%
7 2
 
4.7%
6 2
 
4.7%
17 1
 
2.3%
5 1
 
2.3%
ValueCountFrequency (%)
0 19
44.2%
1 8
18.6%
2 5
 
11.6%
3 2
 
4.7%
4 3
 
7.0%
5 1
 
2.3%
6 2
 
4.7%
7 2
 
4.7%
17 1
 
2.3%
ValueCountFrequency (%)
17 1
 
2.3%
7 2
 
4.7%
6 2
 
4.7%
5 1
 
2.3%
4 3
 
7.0%
3 2
 
4.7%
2 5
 
11.6%
1 8
18.6%
0 19
44.2%

Interactions

2023-12-12T16:04:41.938158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:11.779008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:13.846035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:15.732196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:17.457380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:19.498616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:21.276913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:23.106762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:25.103206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:27.242946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:29.238699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:31.075318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:32.914785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:34.486593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:36.333776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:38.232645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:40.039322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:42.027154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:11.892040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:13.938638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:15.890969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:17.539798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:19.605426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:21.360671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:23.213103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:25.203167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:27.337364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:29.329539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:31.178905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:32.981839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:34.581542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:36.432920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:38.314485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:40.126208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:42.141376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:11.993402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:14.047711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:16.008528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:17.621912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:19.715613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:21.488890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:23.329664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:25.318353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:27.440786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:29.448229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:31.272135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:33.064477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:34.690468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:36.614672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:38.422839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:40.229970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:42.256946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:12.089520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:14.160283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:16.107988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:17.713267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:19.813557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:21.583352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:23.446209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:25.433717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:27.553759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:29.566133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:31.365176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:33.159818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:34.802359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:36.706981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:38.536639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:40.319475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:42.399157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:12.220644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:14.270088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:16.218071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:17.811897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:19.909592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:21.711477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
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2023-12-12T16:04:15.605078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:17.355933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:19.350031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:21.195733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:22.989171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:24.986264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:27.154529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:29.109825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:30.979490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:32.839002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:34.340608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:36.207419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:38.149098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:39.934305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:41.831078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T16:04:49.121187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도낙반붕락_재해자낙반붕락_사망자운반_재해자운반_사망자화약_재해자화약_사망자가스_재해자가스_사망자출수_재해자출수_사망자추락-전석_재해자추락-전석_사망자기계-전기_재해자기계-전기_사망자기타_재해자기타_사망자
연도1.0000.6120.6930.5730.7740.7570.8570.5540.6130.6490.7010.6700.5930.7460.3120.7880.558
낙반붕락_재해자0.6121.0000.8770.9400.7400.9460.7730.9240.7470.8200.7670.9310.7040.9330.7840.9310.706
낙반붕락_사망자0.6930.8771.0000.9540.8610.9630.8610.7490.6970.7950.8090.9810.9170.9650.8740.9860.777
운반_재해자0.5730.9400.9541.0000.7730.9250.8680.8320.8070.9470.8190.9410.7830.8840.8120.9590.858
운반_사망자0.7740.7400.8610.7731.0000.8950.8510.8230.8270.8150.8720.9370.9470.9220.8710.9300.726
화약_재해자0.7570.9460.9630.9250.8951.0000.8580.7540.7970.8310.7910.9850.8870.9740.8140.9890.722
화약_사망자0.8570.7730.8610.8680.8510.8581.0000.6960.9020.7880.9200.8960.7850.8080.7190.9400.797
가스_재해자0.5540.9240.7490.8320.8230.7540.6961.0000.9130.7880.8590.8130.8190.8080.7990.8190.597
가스_사망자0.6130.7470.6970.8070.8270.7970.9020.9131.0000.7650.9520.7560.8250.8150.7590.7840.731
출수_재해자0.6490.8200.7950.9470.8150.8310.7880.7880.7651.0000.8870.8920.8050.8260.7120.8630.832
출수_사망자0.7010.7670.8090.8190.8720.7910.9200.8590.9520.8871.0000.8230.8820.8110.7450.8250.586
추락-전석_재해자0.6700.9310.9810.9410.9370.9850.8960.8130.7560.8920.8231.0000.8780.9700.9050.9960.761
추락-전석_사망자0.5930.7040.9170.7830.9470.8870.7850.8190.8250.8050.8820.8781.0000.9320.8950.8820.638
기계-전기_재해자0.7460.9330.9650.8840.9220.9740.8080.8080.8150.8260.8110.9700.9321.0000.8940.9730.719
기계-전기_사망자0.3120.7840.8740.8120.8710.8140.7190.7990.7590.7120.7450.9050.8950.8941.0000.8850.575
기타_재해자0.7880.9310.9860.9590.9300.9890.9400.8190.7840.8630.8250.9960.8820.9730.8851.0000.768
기타_사망자0.5580.7060.7770.8580.7260.7220.7970.5970.7310.8320.5860.7610.6380.7190.5750.7681.000
2023-12-12T16:04:49.586974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도낙반붕락_재해자낙반붕락_사망자운반_재해자운반_사망자화약_재해자화약_사망자가스_재해자가스_사망자출수_재해자출수_사망자추락-전석_재해자추락-전석_사망자기계-전기_재해자기계-전기_사망자기타_재해자기타_사망자
연도1.000-0.969-0.910-0.979-0.877-0.859-0.784-0.762-0.775-0.835-0.794-0.904-0.805-0.870-0.653-0.951-0.655
낙반붕락_재해자-0.9691.0000.9380.9730.8860.8520.7660.7640.7780.8470.8050.9160.7970.8770.6500.9240.629
낙반붕락_사망자-0.9100.9381.0000.9090.8320.8270.7600.7760.7830.8430.7880.8850.7680.8430.6400.8580.640
운반_재해자-0.9790.9730.9091.0000.9150.8600.7750.7650.7710.8380.8000.9260.7920.8770.6550.9500.645
운반_사망자-0.8770.8860.8320.9151.0000.8130.7330.7410.7390.7850.7470.8590.7400.8020.6210.8690.606
화약_재해자-0.8590.8520.8270.8600.8131.0000.8490.7100.7350.8140.7820.8170.7400.8230.6910.8670.637
화약_사망자-0.7840.7660.7600.7750.7330.8491.0000.6330.6700.7270.6530.7510.6910.7560.6440.7770.630
가스_재해자-0.7620.7640.7760.7650.7410.7100.6331.0000.9290.7550.6980.7390.7960.7150.6590.7040.537
가스_사망자-0.7750.7780.7830.7710.7390.7350.6700.9291.0000.7440.7010.7710.8190.7390.6560.7380.595
출수_재해자-0.8350.8470.8430.8380.7850.8140.7270.7550.7441.0000.9400.8500.8060.8560.7120.8580.688
출수_사망자-0.7940.8050.7880.8000.7470.7820.6530.6980.7010.9401.0000.8090.7690.7830.6370.8130.593
추락-전석_재해자-0.9040.9160.8850.9260.8590.8170.7510.7390.7710.8500.8091.0000.8270.9440.7210.9120.663
추락-전석_사망자-0.8050.7970.7680.7920.7400.7400.6910.7960.8190.8060.7690.8271.0000.8090.7190.7920.593
기계-전기_재해자-0.8700.8770.8430.8770.8020.8230.7560.7150.7390.8560.7830.9440.8091.0000.7220.9060.733
기계-전기_사망자-0.6530.6500.6400.6550.6210.6910.6440.6590.6560.7120.6370.7210.7190.7221.0000.6760.506
기타_재해자-0.9510.9240.8580.9500.8690.8670.7770.7040.7380.8580.8130.9120.7920.9060.6761.0000.702
기타_사망자-0.6550.6290.6400.6450.6060.6370.6300.5370.5950.6880.5930.6630.5930.7330.5060.7021.000

Missing values

2023-12-12T16:04:44.217074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:04:44.493309image/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

연도낙반붕락_재해자낙반붕락_사망자운반_재해자운반_사망자화약_재해자화약_사망자가스_재해자가스_사망자출수_재해자출수_사망자추락-전석_재해자추락-전석_사망자기계-전기_재해자기계-전기_사망자기타_재해자기타_사망자
0198016481151983249993743112100613227716213
11981169412019264584971133120107611206716181
2198215811231631197312161610394115205415277
31983147411114432089122311202823142153150817
419841499120170822861252201439206170515715
519851547118180120101163614331689815191417542
61986160011718222910213231136910265229517934
71987152513017032496921737810034208217857
8198815111201557121028161128119554229317694
919891594811381158552192158156183513486
연도낙반붕락_재해자낙반붕락_사망자운반_재해자운반_사망자화약_재해자화약_사망자가스_재해자가스_사망자출수_재해자출수_사망자추락-전석_재해자추락-전석_사망자기계-전기_재해자기계-전기_사망자기타_재해자기타_사망자
332013202174000000906050
34201412073000000316060
35201510271000000803041
36201613371810000305140
3720177162306100202050
3820188131840000806140
39201960501051009210120
4020208310101010216131
4120215130000000408042
4220223110001121310430