Overview

Dataset statistics

Number of variables12
Number of observations46
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.0 KiB
Average record size in memory110.9 B

Variable types

Numeric10
Categorical2

Dataset

Description사립학교교직원연금공단 교직원 사망 현황(학교급별·직종별)과 관련된 데이터로 연도, 학교급(유치원, 초등학교, 중학교, 고등학교, 전문대학교, 대학교, 특수학교), 직종(일반직, 기술직, 기능직, 고용직, 경노무) 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15045806/fileData.do

Alerts

연도 is highly overall correlated with 유치원교원 and 5 other fieldsHigh correlation
유치원교원 is highly overall correlated with 연도 and 4 other fieldsHigh correlation
초등학교교원 is highly overall correlated with 유치원교원 and 2 other fieldsHigh correlation
중학교교원 is highly overall correlated with 연도 and 4 other fieldsHigh correlation
고등학교교원 is highly overall correlated with 유치원교원 and 3 other fieldsHigh correlation
전문대학교원 is highly overall correlated with 연도 and 3 other fieldsHigh correlation
대학(교)교원 is highly overall correlated with 연도 and 4 other fieldsHigh correlation
일반기술직 is highly overall correlated with 연도 and 1 other fieldsHigh correlation
기능직 is highly overall correlated with 초등학교교원 and 2 other fieldsHigh correlation
고용직 is highly overall correlated with 연도 and 3 other fieldsHigh correlation
특수학교교원 is highly overall correlated with 유치원교원High correlation
연도 has unique valuesUnique
유치원교원 has 32 (69.6%) zerosZeros
초등학교교원 has 6 (13.0%) zerosZeros
전문대학교원 has 1 (2.2%) zerosZeros
일반기술직 has 1 (2.2%) zerosZeros
기능직 has 18 (39.1%) zerosZeros
고용직 has 29 (63.0%) zerosZeros

Reproduction

Analysis started2023-12-12 09:55:40.555998
Analysis finished2023-12-12 09:55:53.856759
Duration13.3 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1999.5
Minimum1977
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-12T18:55:53.977734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1977
5-th percentile1979.25
Q11988.25
median1999.5
Q32010.75
95-th percentile2019.75
Maximum2022
Range45
Interquartile range (IQR)22.5

Descriptive statistics

Standard deviation13.422618
Coefficient of variation (CV)0.0067129871
Kurtosis-1.2
Mean1999.5
Median Absolute Deviation (MAD)11.5
Skewness0
Sum91977
Variance180.16667
MonotonicityStrictly increasing
2023-12-12T18:55:54.196195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
1977 1
 
2.2%
2012 1
 
2.2%
2003 1
 
2.2%
2004 1
 
2.2%
2005 1
 
2.2%
2006 1
 
2.2%
2007 1
 
2.2%
2008 1
 
2.2%
2009 1
 
2.2%
2010 1
 
2.2%
Other values (36) 36
78.3%
ValueCountFrequency (%)
1977 1
2.2%
1978 1
2.2%
1979 1
2.2%
1980 1
2.2%
1981 1
2.2%
1982 1
2.2%
1983 1
2.2%
1984 1
2.2%
1985 1
2.2%
1986 1
2.2%
ValueCountFrequency (%)
2022 1
2.2%
2021 1
2.2%
2020 1
2.2%
2019 1
2.2%
2018 1
2.2%
2017 1
2.2%
2016 1
2.2%
2015 1
2.2%
2014 1
2.2%
2013 1
2.2%

유치원교원
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct9
Distinct (%)19.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2608696
Minimum0
Maximum9
Zeros32
Zeros (%)69.6%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-12T18:55:54.387655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31.75
95-th percentile5.75
Maximum9
Range9
Interquartile range (IQR)1.75

Descriptive statistics

Standard deviation2.3039559
Coefficient of variation (CV)1.8272753
Kurtosis2.9378638
Mean1.2608696
Median Absolute Deviation (MAD)0
Skewness1.8886969
Sum58
Variance5.3082126
MonotonicityNot monotonic
2023-12-12T18:55:54.559873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 32
69.6%
4 3
 
6.5%
3 3
 
6.5%
1 2
 
4.3%
5 2
 
4.3%
2 1
 
2.2%
8 1
 
2.2%
9 1
 
2.2%
6 1
 
2.2%
ValueCountFrequency (%)
0 32
69.6%
1 2
 
4.3%
2 1
 
2.2%
3 3
 
6.5%
4 3
 
6.5%
5 2
 
4.3%
6 1
 
2.2%
8 1
 
2.2%
9 1
 
2.2%
ValueCountFrequency (%)
9 1
 
2.2%
8 1
 
2.2%
6 1
 
2.2%
5 2
 
4.3%
4 3
 
6.5%
3 3
 
6.5%
2 1
 
2.2%
1 2
 
4.3%
0 32
69.6%

초등학교교원
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct8
Distinct (%)17.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.4782609
Minimum0
Maximum9
Zeros6
Zeros (%)13.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-12T18:55:54.729718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33.75
95-th percentile5.75
Maximum9
Range9
Interquartile range (IQR)2.75

Descriptive statistics

Standard deviation1.9970993
Coefficient of variation (CV)0.8058471
Kurtosis1.035449
Mean2.4782609
Median Absolute Deviation (MAD)1
Skewness0.99592777
Sum114
Variance3.9884058
MonotonicityNot monotonic
2023-12-12T18:55:54.911352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 12
26.1%
2 9
19.6%
3 7
15.2%
5 6
13.0%
0 6
13.0%
4 3
 
6.5%
6 2
 
4.3%
9 1
 
2.2%
ValueCountFrequency (%)
0 6
13.0%
1 12
26.1%
2 9
19.6%
3 7
15.2%
4 3
 
6.5%
5 6
13.0%
6 2
 
4.3%
9 1
 
2.2%
ValueCountFrequency (%)
9 1
 
2.2%
6 2
 
4.3%
5 6
13.0%
4 3
 
6.5%
3 7
15.2%
2 9
19.6%
1 12
26.1%
0 6
13.0%

중학교교원
Real number (ℝ)

HIGH CORRELATION 

Distinct31
Distinct (%)67.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.282609
Minimum3
Maximum54
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-12T18:55:55.077902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile7.25
Q111.5
median23
Q335.75
95-th percentile45.75
Maximum54
Range51
Interquartile range (IQR)24.25

Descriptive statistics

Standard deviation13.627852
Coefficient of variation (CV)0.56121863
Kurtosis-1.0938112
Mean24.282609
Median Absolute Deviation (MAD)12.5
Skewness0.28540703
Sum1117
Variance185.71836
MonotonicityNot monotonic
2023-12-12T18:55:55.281002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
9 4
 
8.7%
14 3
 
6.5%
32 2
 
4.3%
40 2
 
4.3%
8 2
 
4.3%
20 2
 
4.3%
19 2
 
4.3%
10 2
 
4.3%
30 2
 
4.3%
25 2
 
4.3%
Other values (21) 23
50.0%
ValueCountFrequency (%)
3 1
 
2.2%
6 1
 
2.2%
7 1
 
2.2%
8 2
4.3%
9 4
8.7%
10 2
4.3%
11 1
 
2.2%
13 1
 
2.2%
14 3
6.5%
16 1
 
2.2%
ValueCountFrequency (%)
54 1
2.2%
47 1
2.2%
46 1
2.2%
45 1
2.2%
42 1
2.2%
41 2
4.3%
40 2
4.3%
38 1
2.2%
37 1
2.2%
36 1
2.2%

고등학교교원
Real number (ℝ)

HIGH CORRELATION 

Distinct32
Distinct (%)69.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44.891304
Minimum14
Maximum85
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-12T18:55:55.465011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum14
5-th percentile19
Q134.25
median44.5
Q355.75
95-th percentile69.25
Maximum85
Range71
Interquartile range (IQR)21.5

Descriptive statistics

Standard deviation16.010036
Coefficient of variation (CV)0.35664003
Kurtosis-0.0996883
Mean44.891304
Median Absolute Deviation (MAD)11
Skewness0.22517398
Sum2065
Variance256.32126
MonotonicityNot monotonic
2023-12-12T18:55:55.662198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
45 3
 
6.5%
46 3
 
6.5%
44 3
 
6.5%
67 2
 
4.3%
65 2
 
4.3%
19 2
 
4.3%
39 2
 
4.3%
48 2
 
4.3%
57 2
 
4.3%
33 2
 
4.3%
Other values (22) 23
50.0%
ValueCountFrequency (%)
14 1
2.2%
15 1
2.2%
19 2
4.3%
24 1
2.2%
26 1
2.2%
29 1
2.2%
30 1
2.2%
31 1
2.2%
33 2
4.3%
34 1
2.2%
ValueCountFrequency (%)
85 1
2.2%
75 1
2.2%
70 1
2.2%
67 2
4.3%
65 2
4.3%
64 1
2.2%
61 1
2.2%
59 1
2.2%
57 2
4.3%
52 1
2.2%

전문대학교원
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct18
Distinct (%)39.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.217391
Minimum0
Maximum20
Zeros1
Zeros (%)2.2%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-12T18:55:55.846047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q17
median11
Q313
95-th percentile18
Maximum20
Range20
Interquartile range (IQR)6

Descriptive statistics

Standard deviation4.6567182
Coefficient of variation (CV)0.45576391
Kurtosis-0.5874859
Mean10.217391
Median Absolute Deviation (MAD)3
Skewness0.057313877
Sum470
Variance21.685024
MonotonicityNot monotonic
2023-12-12T18:55:56.069153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
12 8
17.4%
8 4
 
8.7%
4 4
 
8.7%
13 3
 
6.5%
5 3
 
6.5%
7 3
 
6.5%
11 3
 
6.5%
18 3
 
6.5%
9 3
 
6.5%
6 2
 
4.3%
Other values (8) 10
21.7%
ValueCountFrequency (%)
0 1
 
2.2%
3 1
 
2.2%
4 4
8.7%
5 3
6.5%
6 2
4.3%
7 3
6.5%
8 4
8.7%
9 3
6.5%
10 1
 
2.2%
11 3
6.5%
ValueCountFrequency (%)
20 1
 
2.2%
18 3
 
6.5%
17 1
 
2.2%
16 2
 
4.3%
15 1
 
2.2%
14 2
 
4.3%
13 3
 
6.5%
12 8
17.4%
11 3
 
6.5%
10 1
 
2.2%

대학(교)교원
Real number (ℝ)

HIGH CORRELATION 

Distinct31
Distinct (%)67.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.913043
Minimum11
Maximum60
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-12T18:55:56.284170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile14.75
Q126.25
median39
Q346.5
95-th percentile57
Maximum60
Range49
Interquartile range (IQR)20.25

Descriptive statistics

Standard deviation13.523356
Coefficient of variation (CV)0.36635711
Kurtosis-0.94196134
Mean36.913043
Median Absolute Deviation (MAD)10
Skewness-0.2977548
Sum1698
Variance182.88116
MonotonicityNot monotonic
2023-12-12T18:55:56.489357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
45 4
 
8.7%
38 3
 
6.5%
19 2
 
4.3%
33 2
 
4.3%
43 2
 
4.3%
58 2
 
4.3%
51 2
 
4.3%
49 2
 
4.3%
36 2
 
4.3%
42 2
 
4.3%
Other values (21) 23
50.0%
ValueCountFrequency (%)
11 1
2.2%
12 1
2.2%
14 1
2.2%
17 2
4.3%
18 1
2.2%
19 2
4.3%
21 1
2.2%
22 1
2.2%
26 2
4.3%
27 1
2.2%
ValueCountFrequency (%)
60 1
 
2.2%
58 2
4.3%
54 1
 
2.2%
53 1
 
2.2%
52 1
 
2.2%
51 2
4.3%
50 1
 
2.2%
49 2
4.3%
47 1
 
2.2%
45 4
8.7%

특수학교교원
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size500.0 B
0
34 
1
6 
3
 
3
2
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 34
73.9%
1 6
 
13.0%
3 3
 
6.5%
2 3
 
6.5%

Length

2023-12-12T18:55:56.682703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:55:56.819146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 34
73.9%
1 6
 
13.0%
3 3
 
6.5%
2 3
 
6.5%

일반기술직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct30
Distinct (%)65.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.043478
Minimum0
Maximum60
Zeros1
Zeros (%)2.2%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-12T18:55:56.971106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10.75
Q125.25
median34
Q339.75
95-th percentile48.75
Maximum60
Range60
Interquartile range (IQR)14.5

Descriptive statistics

Standard deviation11.938652
Coefficient of variation (CV)0.37257664
Kurtosis0.75020009
Mean32.043478
Median Absolute Deviation (MAD)7
Skewness-0.49233394
Sum1474
Variance142.5314
MonotonicityNot monotonic
2023-12-12T18:55:57.136010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
36 4
 
8.7%
34 3
 
6.5%
30 3
 
6.5%
37 3
 
6.5%
40 2
 
4.3%
18 2
 
4.3%
26 2
 
4.3%
41 2
 
4.3%
39 2
 
4.3%
29 2
 
4.3%
Other values (20) 21
45.7%
ValueCountFrequency (%)
0 1
2.2%
4 1
2.2%
9 1
2.2%
16 1
2.2%
18 2
4.3%
19 1
2.2%
21 1
2.2%
22 1
2.2%
23 1
2.2%
24 1
2.2%
ValueCountFrequency (%)
60 1
2.2%
52 1
2.2%
49 1
2.2%
48 1
2.2%
44 1
2.2%
43 1
2.2%
42 2
4.3%
41 2
4.3%
40 2
4.3%
39 2
4.3%

기능직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct22
Distinct (%)47.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.913043
Minimum0
Maximum50
Zeros18
Zeros (%)39.1%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-12T18:55:57.317550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median10
Q324.75
95-th percentile42.5
Maximum50
Range50
Interquartile range (IQR)24.75

Descriptive statistics

Standard deviation15.454343
Coefficient of variation (CV)1.1107809
Kurtosis-0.61981959
Mean13.913043
Median Absolute Deviation (MAD)10
Skewness0.77266276
Sum640
Variance238.83671
MonotonicityNot monotonic
2023-12-12T18:55:57.503262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 18
39.1%
27 2
 
4.3%
25 2
 
4.3%
12 2
 
4.3%
35 2
 
4.3%
18 2
 
4.3%
19 2
 
4.3%
37 2
 
4.3%
8 1
 
2.2%
14 1
 
2.2%
Other values (12) 12
26.1%
ValueCountFrequency (%)
0 18
39.1%
1 1
 
2.2%
2 1
 
2.2%
3 1
 
2.2%
6 1
 
2.2%
8 1
 
2.2%
12 2
 
4.3%
14 1
 
2.2%
15 1
 
2.2%
18 2
 
4.3%
ValueCountFrequency (%)
50 1
2.2%
46 1
2.2%
43 1
2.2%
41 1
2.2%
37 2
4.3%
35 2
4.3%
27 2
4.3%
25 2
4.3%
24 1
2.2%
21 1
2.2%

고용직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct16
Distinct (%)34.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.1304348
Minimum0
Maximum43
Zeros29
Zeros (%)63.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-12T18:55:57.707092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q318.5
95-th percentile37.5
Maximum43
Range43
Interquartile range (IQR)18.5

Descriptive statistics

Standard deviation14.339702
Coefficient of variation (CV)1.5705388
Kurtosis-0.12900694
Mean9.1304348
Median Absolute Deviation (MAD)0
Skewness1.2101
Sum420
Variance205.62705
MonotonicityNot monotonic
2023-12-12T18:55:57.853289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0 29
63.0%
1 2
 
4.3%
12 2
 
4.3%
32 1
 
2.2%
21 1
 
2.2%
30 1
 
2.2%
43 1
 
2.2%
38 1
 
2.2%
34 1
 
2.2%
36 1
 
2.2%
Other values (6) 6
 
13.0%
ValueCountFrequency (%)
0 29
63.0%
1 2
 
4.3%
12 2
 
4.3%
17 1
 
2.2%
19 1
 
2.2%
21 1
 
2.2%
22 1
 
2.2%
28 1
 
2.2%
30 1
 
2.2%
32 1
 
2.2%
ValueCountFrequency (%)
43 1
2.2%
41 1
2.2%
38 1
2.2%
36 1
2.2%
34 1
2.2%
33 1
2.2%
32 1
2.2%
30 1
2.2%
28 1
2.2%
22 1
2.2%

경노무
Categorical

Distinct5
Distinct (%)10.9%
Missing0
Missing (%)0.0%
Memory size500.0 B
0
24 
1
15 
2
4 
3
 
2
5
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)2.2%

Sample

1st row0
2nd row0
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
0 24
52.2%
1 15
32.6%
2 4
 
8.7%
3 2
 
4.3%
5 1
 
2.2%

Length

2023-12-12T18:55:57.984462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:55:58.083787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 24
52.2%
1 15
32.6%
2 4
 
8.7%
3 2
 
4.3%
5 1
 
2.2%

Interactions

2023-12-12T18:55:52.187363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:40.969312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:41.861246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:42.829609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:44.214189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:45.427814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:46.719399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:48.053556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:49.387955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:50.602746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:52.305372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:41.059658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:41.961787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:42.936041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:44.309145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:45.537696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:46.851619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:48.166883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:49.485523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:50.704090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:52.418684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:41.151227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:42.079980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:43.014629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:44.435127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:45.635207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:46.975602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:48.292554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:49.637144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:50.816639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:52.532299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:41.229718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:42.151105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:43.453974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:44.609964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:45.754421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:47.101375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:48.409684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:49.796803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:50.924001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:52.649503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:41.311078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:42.220002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:43.550723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:44.711388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:45.881105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:47.231966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:48.529049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:49.900185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:51.032412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:52.776397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:41.402138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:42.320873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:43.654876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:44.841395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:46.020210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:47.383989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:48.665885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:50.006938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:51.189550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:52.931312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:41.494579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:42.440666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:43.776752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:44.973176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:46.174134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:47.535033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:48.813352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:50.128137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:51.342100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:53.052420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:41.578558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:42.555453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:43.886973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:45.082731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:46.310045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:47.669058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:48.950295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:50.245417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:51.464598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:53.185551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:41.666809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:42.660378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:43.993561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:45.194677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:46.465997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:47.809529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:49.119015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:50.354682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:51.585265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:53.312340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:41.762466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:42.743958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:44.105855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:45.316531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:46.595344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:47.931748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:49.271089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:50.475973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:55:52.080427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:55:58.170259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도유치원교원초등학교교원중학교교원고등학교교원전문대학교원대학(교)교원특수학교교원일반기술직기능직고용직경노무
연도1.0000.4390.5290.8790.8590.6800.8310.5910.5630.7790.4590.812
유치원교원0.4391.0000.0000.2740.3870.3570.0000.8950.1020.0000.0000.000
초등학교교원0.5290.0001.0000.2610.5020.0000.4240.0000.0000.3930.0000.407
중학교교원0.8790.2740.2611.0000.6840.2950.6840.3800.0000.6860.5910.772
고등학교교원0.8590.3870.5020.6841.0000.0000.7410.6470.4800.3930.2740.370
전문대학교원0.6800.3570.0000.2950.0001.0000.5850.5870.8330.4390.3280.000
대학(교)교원0.8310.0000.4240.6840.7410.5851.0000.3860.7120.0000.7100.591
특수학교교원0.5910.8950.0000.3800.6470.5870.3861.0000.0000.0000.0000.000
일반기술직0.5630.1020.0000.0000.4800.8330.7120.0001.0000.0000.5870.529
기능직0.7790.0000.3930.6860.3930.4390.0000.0000.0001.0000.0000.000
고용직0.4590.0000.0000.5910.2740.3280.7100.0000.5870.0001.0000.720
경노무0.8120.0000.4070.7720.3700.0000.5910.0000.5290.0000.7201.000
2023-12-12T18:55:58.320774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
특수학교교원경노무
특수학교교원1.0000.000
경노무0.0001.000
2023-12-12T18:55:58.454959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도유치원교원초등학교교원중학교교원고등학교교원전문대학교원대학(교)교원일반기술직기능직고용직특수학교교원경노무
연도1.0000.784-0.300-0.838-0.4320.6080.7460.6400.052-0.7410.3680.427
유치원교원0.7841.000-0.623-0.731-0.6230.2660.3840.404-0.361-0.4790.7630.000
초등학교교원-0.300-0.6231.0000.3620.5850.0830.0020.0860.5030.1770.0000.247
중학교교원-0.838-0.7310.3621.0000.610-0.481-0.616-0.3240.1130.6600.2080.396
고등학교교원-0.432-0.6230.5850.6101.0000.056-0.1960.0270.6120.3230.4100.136
전문대학교원0.6080.2660.083-0.4810.0561.0000.7430.4410.526-0.6950.0000.000
대학(교)교원0.7460.3840.002-0.616-0.1960.7431.0000.5310.367-0.6790.2120.259
일반기술직0.6400.4040.086-0.3240.0270.4410.5311.0000.256-0.4880.0000.000
기능직0.052-0.3610.5030.1130.6120.5260.3670.2561.000-0.3530.0000.000
고용직-0.741-0.4790.1770.6600.323-0.695-0.679-0.488-0.3531.0000.0000.494
특수학교교원0.3680.7630.0000.2080.4100.0000.2120.0000.0000.0001.0000.000
경노무0.4270.0000.2470.3960.1360.0000.2590.0000.0000.4940.0001.000

Missing values

2023-12-12T18:55:53.490920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:55:53.741901image/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

연도유치원교원초등학교교원중학교교원고등학교교원전문대학교원대학(교)교원특수학교교원일반기술직기능직고용직경노무
0197701323001900000
11978013038411040120
21979033229314090191
319800141334120180171
419810238366180190221
519820231465170160283
619830241527210220411
719840136447190180332
819850230456170210361
919860446488260290323
연도유치원교원초등학교교원중학교교원고등학교교원전문대학교원대학(교)교원특수학교교원일반기술직기능직고용직경노무
3620133317419301391200
372014309451544130800
3820154110391743341000
392016809331453139000
40201790819943048000
41201810826940242000
422019616191858149000
43202050715738036000
44202151324838241000
4520223111141060060000