Overview

Dataset statistics

Number of variables12
Number of observations21
Missing cells16
Missing cells (%)6.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.3 KiB
Average record size in memory114.3 B

Variable types

Numeric6
Categorical6

Dataset

Description항공사고 발생현황 통계를 연도별, 발생건수별, 인명피해 명수, 사고원인, 사고기종, 비행단계별로 항공통계 정보를 제공합니다
URLhttps://www.data.go.kr/data/15052305/fileData.do

Alerts

사고원인4(조사중) is highly overall correlated with 발생건수 and 6 other fieldsHigh correlation
비행단계2(이착륙) is highly overall correlated with 사고원인4(조사중) and 1 other fieldsHigh correlation
사고기종1(운송용정기항공) is highly overall correlated with 사고원인4(조사중) and 2 other fieldsHigh correlation
비행단계3(기타) is highly overall correlated with 발생건수 and 7 other fieldsHigh correlation
사고원인3(기타) is highly overall correlated with 년도 and 3 other fieldsHigh correlation
년도 is highly overall correlated with 사고원인2(정비불량) and 1 other fieldsHigh correlation
발생건수 is highly overall correlated with 인명피해(명) and 4 other fieldsHigh correlation
인명피해(명) is highly overall correlated with 발생건수 and 4 other fieldsHigh correlation
사고원인1(조종과실) is highly overall correlated with 발생건수 and 2 other fieldsHigh correlation
사고기종2(기타) is highly overall correlated with 발생건수 and 3 other fieldsHigh correlation
비행단계1(순항) is highly overall correlated with 사고기종2(기타) and 3 other fieldsHigh correlation
사고원인2(정비불량) is highly overall correlated with 년도High correlation
인명피해(명) has 4 (19.0%) missing valuesMissing
사고원인1(조종과실) has 5 (23.8%) missing valuesMissing
사고기종2(기타) has 2 (9.5%) missing valuesMissing
비행단계1(순항) has 5 (23.8%) missing valuesMissing
년도 has unique valuesUnique

Reproduction

Analysis started2023-12-12 10:32:17.375788
Analysis finished2023-12-12 10:32:23.091266
Duration5.72 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2012
Minimum2002
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-12T19:32:23.157518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2002
5-th percentile2003
Q12007
median2012
Q32017
95-th percentile2021
Maximum2022
Range20
Interquartile range (IQR)10

Descriptive statistics

Standard deviation6.2048368
Coefficient of variation (CV)0.0030839149
Kurtosis-1.2
Mean2012
Median Absolute Deviation (MAD)5
Skewness0
Sum42252
Variance38.5
MonotonicityStrictly increasing
2023-12-12T19:32:23.295770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
2002 1
 
4.8%
2003 1
 
4.8%
2022 1
 
4.8%
2021 1
 
4.8%
2020 1
 
4.8%
2019 1
 
4.8%
2018 1
 
4.8%
2017 1
 
4.8%
2016 1
 
4.8%
2015 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
2002 1
4.8%
2003 1
4.8%
2004 1
4.8%
2005 1
4.8%
2006 1
4.8%
2007 1
4.8%
2008 1
4.8%
2009 1
4.8%
2010 1
4.8%
2011 1
4.8%
ValueCountFrequency (%)
2022 1
4.8%
2021 1
4.8%
2020 1
4.8%
2019 1
4.8%
2018 1
4.8%
2017 1
4.8%
2016 1
4.8%
2015 1
4.8%
2014 1
4.8%
2013 1
4.8%

발생건수
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)38.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.1428571
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-12T19:32:23.440911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median4
Q35
95-th percentile7
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.1044171
Coefficient of variation (CV)0.50796275
Kurtosis0.029212991
Mean4.1428571
Median Absolute Deviation (MAD)1
Skewness0.36159693
Sum87
Variance4.4285714
MonotonicityNot monotonic
2023-12-12T19:32:23.585733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
5 6
28.6%
3 5
23.8%
1 3
14.3%
4 2
 
9.5%
7 2
 
9.5%
9 1
 
4.8%
2 1
 
4.8%
6 1
 
4.8%
ValueCountFrequency (%)
1 3
14.3%
2 1
 
4.8%
3 5
23.8%
4 2
 
9.5%
5 6
28.6%
6 1
 
4.8%
7 2
 
9.5%
9 1
 
4.8%
ValueCountFrequency (%)
9 1
 
4.8%
7 2
 
9.5%
6 1
 
4.8%
5 6
28.6%
4 2
 
9.5%
3 5
23.8%
2 1
 
4.8%
1 3
14.3%

인명피해(명)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct8
Distinct (%)47.1%
Missing4
Missing (%)19.0%
Infinite0
Infinite (%)0.0%
Mean4.1176471
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-12T19:32:23.713145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q37
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.4073882
Coefficient of variation (CV)0.82750855
Kurtosis-1.0799543
Mean4.1176471
Median Absolute Deviation (MAD)1
Skewness0.74557653
Sum70
Variance11.610294
MonotonicityNot monotonic
2023-12-12T19:32:23.841122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 5
23.8%
2 4
19.0%
5 2
 
9.5%
10 2
 
9.5%
9 1
 
4.8%
7 1
 
4.8%
3 1
 
4.8%
8 1
 
4.8%
(Missing) 4
19.0%
ValueCountFrequency (%)
1 5
23.8%
2 4
19.0%
3 1
 
4.8%
5 2
 
9.5%
7 1
 
4.8%
8 1
 
4.8%
9 1
 
4.8%
10 2
 
9.5%
ValueCountFrequency (%)
10 2
 
9.5%
9 1
 
4.8%
8 1
 
4.8%
7 1
 
4.8%
5 2
 
9.5%
3 1
 
4.8%
2 4
19.0%
1 5
23.8%

사고원인1(조종과실)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct6
Distinct (%)37.5%
Missing5
Missing (%)23.8%
Infinite0
Infinite (%)0.0%
Mean2.9375
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-12T19:32:23.946808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2.5
Q34
95-th percentile5.5
Maximum7
Range6
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.8427787
Coefficient of variation (CV)0.62732892
Kurtosis-0.36991172
Mean2.9375
Median Absolute Deviation (MAD)1.5
Skewness0.61552056
Sum47
Variance3.3958333
MonotonicityNot monotonic
2023-12-12T19:32:24.054590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 5
23.8%
4 4
19.0%
2 3
14.3%
5 2
 
9.5%
7 1
 
4.8%
3 1
 
4.8%
(Missing) 5
23.8%
ValueCountFrequency (%)
1 5
23.8%
2 3
14.3%
3 1
 
4.8%
4 4
19.0%
5 2
 
9.5%
7 1
 
4.8%
ValueCountFrequency (%)
7 1
 
4.8%
5 2
 
9.5%
4 4
19.0%
3 1
 
4.8%
2 3
14.3%
1 5
23.8%

사고원인2(정비불량)
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)19.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
<NA>
13 
1
6 
4
 
1
2
 
1

Length

Max length4
Median length4
Mean length2.8571429
Min length1

Unique

Unique2 ?
Unique (%)9.5%

Sample

1st row<NA>
2nd row<NA>
3rd row1
4th row1
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 13
61.9%
1 6
28.6%
4 1
 
4.8%
2 1
 
4.8%

Length

2023-12-12T19:32:24.202312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:32:24.345187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 13
61.9%
1 6
28.6%
4 1
 
4.8%
2 1
 
4.8%

사고원인3(기타)
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)19.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
<NA>
13 
1
4 
2
3 
4
 
1

Length

Max length4
Median length4
Mean length2.8571429
Min length1

Unique

Unique1 ?
Unique (%)4.8%

Sample

1st row<NA>
2nd row4
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 13
61.9%
1 4
 
19.0%
2 3
 
14.3%
4 1
 
4.8%

Length

2023-12-12T19:32:24.504001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:32:24.638340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 13
61.9%
1 4
 
19.0%
2 3
 
14.3%
4 1
 
4.8%

사고원인4(조사중)
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)23.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
<NA>
16 
2
2 
1
 
1
3
 
1
6
 
1

Length

Max length4
Median length4
Mean length3.2857143
Min length1

Unique

Unique3 ?
Unique (%)14.3%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 16
76.2%
2 2
 
9.5%
1 1
 
4.8%
3 1
 
4.8%
6 1
 
4.8%

Length

2023-12-12T19:32:24.755768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:32:24.875371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 16
76.2%
2 2
 
9.5%
1 1
 
4.8%
3 1
 
4.8%
6 1
 
4.8%

사고기종1(운송용정기항공)
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)19.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
<NA>
9 
1
7 
2
3 
3
2 

Length

Max length4
Median length1
Mean length2.2857143
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row3

Common Values

ValueCountFrequency (%)
<NA> 9
42.9%
1 7
33.3%
2 3
 
14.3%
3 2
 
9.5%

Length

2023-12-12T19:32:25.002938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:32:25.148989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9
42.9%
1 7
33.3%
2 3
 
14.3%
3 2
 
9.5%

사고기종2(기타)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct7
Distinct (%)36.8%
Missing2
Missing (%)9.5%
Infinite0
Infinite (%)0.0%
Mean3.5789474
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-12T19:32:25.250787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median3
Q34.5
95-th percentile6.1
Maximum7
Range6
Interquartile range (IQR)1.5

Descriptive statistics

Standard deviation1.6437014
Coefficient of variation (CV)0.45926952
Kurtosis-0.21751138
Mean3.5789474
Median Absolute Deviation (MAD)1
Skewness0.4313059
Sum68
Variance2.7017544
MonotonicityNot monotonic
2023-12-12T19:32:25.369612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
3 7
33.3%
4 3
14.3%
5 2
 
9.5%
2 2
 
9.5%
6 2
 
9.5%
1 2
 
9.5%
7 1
 
4.8%
(Missing) 2
 
9.5%
ValueCountFrequency (%)
1 2
 
9.5%
2 2
 
9.5%
3 7
33.3%
4 3
14.3%
5 2
 
9.5%
6 2
 
9.5%
7 1
 
4.8%
ValueCountFrequency (%)
7 1
 
4.8%
6 2
 
9.5%
5 2
 
9.5%
4 3
14.3%
3 7
33.3%
2 2
 
9.5%
1 2
 
9.5%

비행단계1(순항)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct6
Distinct (%)37.5%
Missing5
Missing (%)23.8%
Infinite0
Infinite (%)0.0%
Mean2.75
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-12T19:32:25.476966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q34.25
95-th percentile5.5
Maximum7
Range6
Interquartile range (IQR)3.25

Descriptive statistics

Standard deviation1.9148542
Coefficient of variation (CV)0.69631062
Kurtosis-0.27899373
Mean2.75
Median Absolute Deviation (MAD)1
Skewness0.86270173
Sum44
Variance3.6666667
MonotonicityNot monotonic
2023-12-12T19:32:25.597049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 6
28.6%
2 3
14.3%
5 3
14.3%
3 2
 
9.5%
7 1
 
4.8%
4 1
 
4.8%
(Missing) 5
23.8%
ValueCountFrequency (%)
1 6
28.6%
2 3
14.3%
3 2
 
9.5%
4 1
 
4.8%
5 3
14.3%
7 1
 
4.8%
ValueCountFrequency (%)
7 1
 
4.8%
5 3
14.3%
4 1
 
4.8%
3 2
 
9.5%
2 3
14.3%
1 6
28.6%

비행단계2(이착륙)
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)23.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
<NA>
9 
1
5 
4
4 
2
2 
3
1 

Length

Max length4
Median length1
Mean length2.2857143
Min length1

Unique

Unique1 ?
Unique (%)4.8%

Sample

1st row2
2nd row<NA>
3rd row1
4th row<NA>
5th row4

Common Values

ValueCountFrequency (%)
<NA> 9
42.9%
1 5
23.8%
4 4
19.0%
2 2
 
9.5%
3 1
 
4.8%

Length

2023-12-12T19:32:25.762150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:32:25.892439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9
42.9%
1 5
23.8%
4 4
19.0%
2 2
 
9.5%
3 1
 
4.8%

비행단계3(기타)
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)23.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
<NA>
15 
4
2 
1
2 
3
 
1
2
 
1

Length

Max length4
Median length4
Mean length3.1428571
Min length1

Unique

Unique2 ?
Unique (%)9.5%

Sample

1st row<NA>
2nd row4
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 15
71.4%
4 2
 
9.5%
1 2
 
9.5%
3 1
 
4.8%
2 1
 
4.8%

Length

2023-12-12T19:32:26.041928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:32:26.188942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 15
71.4%
4 2
 
9.5%
1 2
 
9.5%
3 1
 
4.8%
2 1
 
4.8%

Interactions

2023-12-12T19:32:21.851490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:18.011922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:18.752983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:19.543414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:20.582300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:21.208387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:21.974790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:18.133347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:18.881751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:19.677867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:20.682108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:21.320394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:22.072415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:18.270272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:19.001897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:19.808406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:20.792289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:21.445981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:22.175229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:18.381850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:19.114587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:19.908478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:20.929258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:21.557576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:22.285485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:18.494264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:19.238544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:20.361951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:21.027071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:21.655753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:22.398627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:18.634139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:19.401463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:20.474643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:21.115142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:21.741718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T19:32:26.309099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도발생건수인명피해(명)사고원인1(조종과실)사고원인2(정비불량)사고원인3(기타)사고원인4(조사중)사고기종1(운송용정기항공)사고기종2(기타)비행단계1(순항)비행단계2(이착륙)비행단계3(기타)
년도1.0000.1380.6050.0001.0001.0000.5980.5120.2960.4880.0000.000
발생건수0.1381.0000.6810.8950.0000.0001.0000.2260.6700.3840.3011.000
인명피해(명)0.6050.6811.0000.5720.0000.0001.0000.0000.8510.2610.0001.000
사고원인1(조종과실)0.0000.8950.5721.0000.3640.000NaN0.3960.0000.0000.642NaN
사고원인2(정비불량)1.0000.0000.0000.3641.0000.000NaN0.8270.4650.5980.000NaN
사고원인3(기타)1.0000.0000.0000.0000.0001.000NaN0.1650.0001.0000.0001.000
사고원인4(조사중)0.5981.0001.000NaNNaNNaN1.0001.0000.7711.0000.0001.000
사고기종1(운송용정기항공)0.5120.2260.0000.3960.8270.1651.0001.0000.0000.0000.4331.000
사고기종2(기타)0.2960.6700.8510.0000.4650.0000.7710.0001.0000.0000.0001.000
비행단계1(순항)0.4880.3840.2610.0000.5981.0001.0000.0000.0001.0000.0001.000
비행단계2(이착륙)0.0000.3010.0000.6420.0000.0000.0000.4330.0000.0001.000NaN
비행단계3(기타)0.0001.0001.000NaNNaN1.0001.0001.0001.0001.000NaN1.000
2023-12-12T19:32:26.482187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사고원인2(정비불량)사고원인4(조사중)비행단계2(이착륙)사고기종1(운송용정기항공)비행단계3(기타)사고원인3(기타)
사고원인2(정비불량)1.000NaN0.0000.000NaN0.000
사고원인4(조사중)NaN1.0001.0000.5771.0001.000
비행단계2(이착륙)0.0001.0001.0000.577NaN0.000
사고기종1(운송용정기항공)0.0000.5770.5771.0001.0000.000
비행단계3(기타)NaN1.000NaN1.0001.0001.000
사고원인3(기타)0.0001.0000.0000.0001.0001.000
2023-12-12T19:32:26.916995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도발생건수인명피해(명)사고원인1(조종과실)사고기종2(기타)비행단계1(순항)사고원인2(정비불량)사고원인3(기타)사고원인4(조사중)사고기종1(운송용정기항공)비행단계2(이착륙)비행단계3(기타)
년도1.000-0.0070.176-0.017-0.1730.0140.5770.6320.0000.0890.0000.000
발생건수-0.0071.0000.6200.5940.8030.4240.0000.0001.0000.0000.0001.000
인명피해(명)0.1760.6201.0000.8450.5440.0660.0000.0001.0000.0000.0000.866
사고원인1(조종과실)-0.0170.5940.8451.0000.3760.1610.0000.000NaN0.1440.2891.000
사고기종2(기타)-0.1730.8030.5440.3761.0000.5690.2740.0000.0000.0000.0000.866
비행단계1(순항)0.0140.4240.0660.1610.5691.0000.3820.6321.0000.0000.0000.707
사고원인2(정비불량)0.5770.0000.0000.0000.2740.3821.0000.0000.0000.0000.0000.000
사고원인3(기타)0.6320.0000.0000.0000.0000.6320.0001.0001.0000.0000.0001.000
사고원인4(조사중)0.0001.0001.000NaN0.0001.0000.0001.0001.0000.5771.0001.000
사고기종1(운송용정기항공)0.0890.0000.0000.1440.0000.0000.0000.0000.5771.0000.5771.000
비행단계2(이착륙)0.0000.0000.0000.2890.0000.0000.0000.0001.0000.5771.000NaN
비행단계3(기타)0.0001.0000.8661.0000.8660.7070.0001.0001.0001.000NaN1.000

Missing values

2023-12-12T19:32:22.544540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:32:22.735799image/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.
2023-12-12T19:32:22.950312image/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

년도발생건수인명피해(명)사고원인1(조종과실)사고원인2(정비불량)사고원인3(기타)사고원인4(조사중)사고기종1(운송용정기항공)사고기종2(기타)비행단계1(순항)비행단계2(이착륙)비행단계3(기타)
02002424<NA><NA><NA><NA>422<NA>
12003521<NA>4<NA><NA>51<NA>4
220043221<NA><NA><NA>321<NA>
320053121<NA><NA><NA>33<NA><NA>
420065<NA>5<NA><NA><NA>3214<NA>
520071<NA><NA>1<NA><NA>1<NA><NA>1<NA>
620083<NA>21<NA><NA><NA>3<NA>3<NA>
72009554<NA><NA>12314<NA>
820105114<NA><NA>145<NA><NA>
920117105<NA>2<NA>167<NA><NA>
년도발생건수인명피해(명)사고원인1(조종과실)사고원인2(정비불량)사고원인3(기타)사고원인4(조사중)사고기종1(운송용정기항공)사고기종2(기타)비행단계1(순항)비행단계2(이착륙)비행단계3(기타)
112013910711<NA>3654<NA>
122014353<NA><NA><NA><NA>312<NA>
1320151<NA>1<NA><NA><NA>1<NA><NA>1<NA>
14201679412<NA><NA>734<NA>
152017524<NA>1<NA><NA>55<NA><NA>
162018111<NA><NA><NA><NA>1<NA><NA>1
17201937<NA><NA>1212<NA><NA>3
18202043<NA><NA>13132<NA>2
19202121<NA><NA><NA>2111<NA>1
20202268<NA><NA><NA>624114