Overview

Dataset statistics

Number of variables16
Number of observations82
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.6 KiB
Average record size in memory144.6 B

Variable types

Numeric15
Categorical1

Dataset

Description연금급여 종류별(퇴직연금, 퇴직연금일시금, 유족연금 유족연금일시금 등) 급여지급액(정부부담급여) 추이에 대한 데이터입니다.
URLhttps://www.data.go.kr/data/15054027/fileData.do

Alerts

연도 is highly overall correlated with 재해보상급여(계) and 7 other fieldsHigh correlation
재해보상급여(계) is highly overall correlated with 연도 and 7 other fieldsHigh correlation
공무상요양비 is highly overall correlated with 연도 and 7 other fieldsHigh correlation
유족보상금 is highly overall correlated with 장해보상금 and 5 other fieldsHigh correlation
유족연금 is highly overall correlated with 연도 and 6 other fieldsHigh correlation
장해연금 is highly overall correlated with 연도 and 7 other fieldsHigh correlation
장해유족연금 is highly overall correlated with 연도 and 7 other fieldsHigh correlation
장해보상금 is highly overall correlated with 유족보상금 and 3 other fieldsHigh correlation
순직유족연금 is highly overall correlated with 연도 and 7 other fieldsHigh correlation
순직유족보상금 is highly overall correlated with 연도 and 7 other fieldsHigh correlation
부조급여(계) is highly overall correlated with 유족보상금 and 3 other fieldsHigh correlation
재해부조금 is highly overall correlated with 공무상요양비 and 3 other fieldsHigh correlation
사망조위금 is highly overall correlated with 유족보상금 and 3 other fieldsHigh correlation
퇴직수당 is highly overall correlated with 연도 and 10 other fieldsHigh correlation
구분 is highly overall correlated with 유족보상금 and 5 other fieldsHigh correlation
재해보상급여(계) has unique valuesUnique
공무상요양비 has unique valuesUnique
장해연금 has unique valuesUnique
부조급여(계) has unique valuesUnique
공무상요양일시금 has 29 (35.4%) zerosZeros
유족연금 has 60 (73.2%) zerosZeros
장해유족연금 has 16 (19.5%) zerosZeros
순직유족연금 has 48 (58.5%) zerosZeros
순직유족보상금 has 48 (58.5%) zerosZeros
사망조위금 has 6 (7.3%) zerosZeros
퇴직수당 has 18 (22.0%) zerosZeros

Reproduction

Analysis started2023-12-12 13:58:06.160796
Analysis finished2023-12-12 13:58:28.312857
Duration22.15 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Real number (ℝ)

HIGH CORRELATION 

Distinct41
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2002
Minimum1982
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2023-12-12T22:58:28.470066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1982
5-th percentile1984
Q11992
median2002
Q32012
95-th percentile2020
Maximum2022
Range40
Interquartile range (IQR)20

Descriptive statistics

Standard deviation11.904974
Coefficient of variation (CV)0.0059465402
Kurtosis-1.2011399
Mean2002
Median Absolute Deviation (MAD)10
Skewness0
Sum164164
Variance141.7284
MonotonicityIncreasing
2023-12-12T22:58:28.666641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
1982 2
 
2.4%
2013 2
 
2.4%
2005 2
 
2.4%
2006 2
 
2.4%
2007 2
 
2.4%
2008 2
 
2.4%
2009 2
 
2.4%
2010 2
 
2.4%
2011 2
 
2.4%
2012 2
 
2.4%
Other values (31) 62
75.6%
ValueCountFrequency (%)
1982 2
2.4%
1983 2
2.4%
1984 2
2.4%
1985 2
2.4%
1986 2
2.4%
1987 2
2.4%
1988 2
2.4%
1989 2
2.4%
1990 2
2.4%
1991 2
2.4%
ValueCountFrequency (%)
2022 2
2.4%
2021 2
2.4%
2020 2
2.4%
2019 2
2.4%
2018 2
2.4%
2017 2
2.4%
2016 2
2.4%
2015 2
2.4%
2014 2
2.4%
2013 2
2.4%

구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size788.0 B
건수
41 
금액
41 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row건수
2nd row금액
3rd row건수
4th row금액
5th row건수

Common Values

ValueCountFrequency (%)
건수 41
50.0%
금액 41
50.0%

Length

2023-12-12T22:58:29.206242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:58:29.342382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건수 41
50.0%
금액 41
50.0%

재해보상급여(계)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct82
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59628.671
Minimum1464
Maximum228030
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2023-12-12T22:58:29.507419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1464
5-th percentile3966.35
Q16505.75
median33694.5
Q3100675
95-th percentile183638.1
Maximum228030
Range226566
Interquartile range (IQR)94169.25

Descriptive statistics

Standard deviation62239.79
Coefficient of variation (CV)1.0437897
Kurtosis0.099861071
Mean59628.671
Median Absolute Deviation (MAD)28798.5
Skewness1.0420458
Sum4889551
Variance3.8737914 × 109
MonotonicityNot monotonic
2023-12-12T22:58:29.696594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1464 1
 
1.2%
155317 1
 
1.2%
122749 1
 
1.2%
68062 1
 
1.2%
120685 1
 
1.2%
61538 1
 
1.2%
116602 1
 
1.2%
61162 1
 
1.2%
111310 1
 
1.2%
60758 1
 
1.2%
Other values (72) 72
87.8%
ValueCountFrequency (%)
1464 1
1.2%
2078 1
1.2%
3753 1
1.2%
3777 1
1.2%
3932 1
1.2%
4619 1
1.2%
4646 1
1.2%
4760 1
1.2%
4786 1
1.2%
4823 1
1.2%
ValueCountFrequency (%)
228030 1
1.2%
222232 1
1.2%
200270 1
1.2%
198333 1
1.2%
184053 1
1.2%
175755 1
1.2%
175159 1
1.2%
171462 1
1.2%
157538 1
1.2%
155317 1
1.2%

공무상요양비
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct82
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30906.695
Minimum712
Maximum176647
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2023-12-12T22:58:29.854264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum712
5-th percentile1486
Q13757
median10565
Q333519.25
95-th percentile135226.2
Maximum176647
Range175935
Interquartile range (IQR)29762.25

Descriptive statistics

Standard deviation44230.464
Coefficient of variation (CV)1.4310965
Kurtosis2.2079105
Mean30906.695
Median Absolute Deviation (MAD)8443
Skewness1.7906389
Sum2534349
Variance1.956334 × 109
MonotonicityNot monotonic
2023-12-12T22:58:30.060757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1151 1
 
1.2%
113387 1
 
1.2%
82664 1
 
1.2%
14288 1
 
1.2%
82004 1
 
1.2%
14032 1
 
1.2%
79186 1
 
1.2%
15529 1
 
1.2%
75292 1
 
1.2%
13688 1
 
1.2%
Other values (72) 72
87.8%
ValueCountFrequency (%)
712 1
1.2%
746 1
1.2%
1083 1
1.2%
1151 1
1.2%
1474 1
1.2%
1714 1
1.2%
1719 1
1.2%
1740 1
1.2%
1839 1
1.2%
1841 1
1.2%
ValueCountFrequency (%)
176647 1
1.2%
166094 1
1.2%
144313 1
1.2%
141756 1
1.2%
135736 1
1.2%
125540 1
1.2%
113988 1
1.2%
113428 1
1.2%
113387 1
1.2%
109597 1
1.2%

공무상요양일시금
Real number (ℝ)

ZEROS 

Distinct44
Distinct (%)53.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean72.97561
Minimum0
Maximum1151
Zeros29
Zeros (%)35.4%
Negative0
Negative (%)0.0%
Memory size870.0 B
2023-12-12T22:58:30.271750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median16
Q363.5
95-th percentile280.35
Maximum1151
Range1151
Interquartile range (IQR)63.5

Descriptive statistics

Standard deviation172.71106
Coefficient of variation (CV)2.3666957
Kurtosis23.005634
Mean72.97561
Median Absolute Deviation (MAD)16
Skewness4.4850596
Sum5984
Variance29829.111
MonotonicityNot monotonic
2023-12-12T22:58:30.464305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
0 29
35.4%
16 4
 
4.9%
12 3
 
3.7%
17 2
 
2.4%
51 2
 
2.4%
13 2
 
2.4%
49 2
 
2.4%
117 2
 
2.4%
440 1
 
1.2%
230 1
 
1.2%
Other values (34) 34
41.5%
ValueCountFrequency (%)
0 29
35.4%
1 1
 
1.2%
2 1
 
1.2%
9 1
 
1.2%
11 1
 
1.2%
12 3
 
3.7%
13 2
 
2.4%
14 1
 
1.2%
15 1
 
1.2%
16 4
 
4.9%
ValueCountFrequency (%)
1151 1
1.2%
841 1
1.2%
478 1
1.2%
440 1
1.2%
283 1
1.2%
230 1
1.2%
218 1
1.2%
211 1
1.2%
160 1
1.2%
127 1
1.2%

유족보상금
Real number (ℝ)

HIGH CORRELATION 

Distinct80
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3778.3293
Minimum68
Maximum17138
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2023-12-12T22:58:30.670581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum68
5-th percentile78.15
Q1147.25
median1404
Q37126
95-th percentile11338.15
Maximum17138
Range17070
Interquartile range (IQR)6978.75

Descriptive statistics

Standard deviation4277.639
Coefficient of variation (CV)1.1321509
Kurtosis-0.027293886
Mean3778.3293
Median Absolute Deviation (MAD)1335.5
Skewness0.89156957
Sum309823
Variance18298195
MonotonicityNot monotonic
2023-12-12T22:58:30.880571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
220 2
 
2.4%
99 2
 
2.4%
14019 1
 
1.2%
75 1
 
1.2%
7266 1
 
1.2%
5178 1
 
1.2%
72 1
 
1.2%
5802 1
 
1.2%
83 1
 
1.2%
8111 1
 
1.2%
Other values (70) 70
85.4%
ValueCountFrequency (%)
68 1
1.2%
69 1
1.2%
72 1
1.2%
75 1
1.2%
78 1
1.2%
81 1
1.2%
82 1
1.2%
83 1
1.2%
84 1
1.2%
86 1
1.2%
ValueCountFrequency (%)
17138 1
1.2%
14019 1
1.2%
13739 1
1.2%
11485 1
1.2%
11371 1
1.2%
10714 1
1.2%
10703 1
1.2%
9293 1
1.2%
9053 1
1.2%
8920 1
1.2%

유족연금
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct23
Distinct (%)28.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1689.8902
Minimum0
Maximum21945
Zeros60
Zeros (%)73.2%
Negative0
Negative (%)0.0%
Memory size870.0 B
2023-12-12T22:58:31.067885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3278.75
95-th percentile10701.3
Maximum21945
Range21945
Interquartile range (IQR)278.75

Descriptive statistics

Standard deviation4218.4617
Coefficient of variation (CV)2.4962933
Kurtosis10.397203
Mean1689.8902
Median Absolute Deviation (MAD)0
Skewness3.180494
Sum138571
Variance17795419
MonotonicityNot monotonic
2023-12-12T22:58:31.208421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 60
73.2%
194 1
 
1.2%
21945 1
 
1.2%
7762 1
 
1.2%
18398 1
 
1.2%
6799 1
 
1.2%
16002 1
 
1.2%
5972 1
 
1.2%
14006 1
 
1.2%
5189 1
 
1.2%
Other values (13) 13
 
15.9%
ValueCountFrequency (%)
0 60
73.2%
194 1
 
1.2%
307 1
 
1.2%
783 1
 
1.2%
1255 1
 
1.2%
1267 1
 
1.2%
1830 1
 
1.2%
1897 1
 
1.2%
2605 1
 
1.2%
2858 1
 
1.2%
ValueCountFrequency (%)
21945 1
1.2%
18398 1
1.2%
16002 1
1.2%
14006 1
1.2%
10856 1
1.2%
7762 1
1.2%
6799 1
1.2%
6136 1
1.2%
5972 1
1.2%
5189 1
1.2%

장해연금
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct82
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17933.61
Minimum46
Maximum54450
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2023-12-12T22:58:31.374777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46
5-th percentile97.9
Q1440.25
median12674.5
Q334283.75
95-th percentile45535.15
Maximum54450
Range54404
Interquartile range (IQR)33843.5

Descriptive statistics

Standard deviation17922.185
Coefficient of variation (CV)0.99936292
Kurtosis-1.454377
Mean17933.61
Median Absolute Deviation (MAD)12531.5
Skewness0.38712586
Sum1470556
Variance3.212047 × 108
MonotonicityNot monotonic
2023-12-12T22:58:31.527074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
46 1
 
1.2%
33914 1
 
1.2%
33295 1
 
1.2%
35266 1
 
1.2%
32723 1
 
1.2%
33678 1
 
1.2%
32157 1
 
1.2%
32795 1
 
1.2%
31211 1
 
1.2%
30523 1
 
1.2%
Other values (72) 72
87.8%
ValueCountFrequency (%)
46 1
1.2%
59 1
1.2%
70 1
1.2%
93 1
1.2%
97 1
1.2%
115 1
1.2%
120 1
1.2%
142 1
1.2%
144 1
1.2%
161 1
1.2%
ValueCountFrequency (%)
54450 1
1.2%
51758 1
1.2%
49520 1
1.2%
46960 1
1.2%
45587 1
1.2%
44550 1
1.2%
44388 1
1.2%
43209 1
1.2%
43014 1
1.2%
41593 1
1.2%

장해유족연금
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct67
Distinct (%)81.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3330.2561
Minimum0
Maximum11580
Zeros16
Zeros (%)19.5%
Negative0
Negative (%)0.0%
Memory size870.0 B
2023-12-12T22:58:31.671540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q190.5
median2030
Q36064
95-th percentile10299.95
Maximum11580
Range11580
Interquartile range (IQR)5973.5

Descriptive statistics

Standard deviation3658.4154
Coefficient of variation (CV)1.0985388
Kurtosis-0.72136238
Mean3330.2561
Median Absolute Deviation (MAD)2030
Skewness0.80684261
Sum273081
Variance13384004
MonotonicityNot monotonic
2023-12-12T22:58:31.843999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 16
 
19.5%
5220 1
 
1.2%
6863 1
 
1.2%
6765 1
 
1.2%
6344 1
 
1.2%
6148 1
 
1.2%
5812 1
 
1.2%
5469 1
 
1.2%
4842 1
 
1.2%
78 1
 
1.2%
Other values (57) 57
69.5%
ValueCountFrequency (%)
0 16
19.5%
78 1
 
1.2%
80 1
 
1.2%
82 1
 
1.2%
83 1
 
1.2%
89 1
 
1.2%
95 1
 
1.2%
96 1
 
1.2%
109 1
 
1.2%
113 1
 
1.2%
ValueCountFrequency (%)
11580 1
1.2%
11130 1
1.2%
10830 1
1.2%
10524 1
1.2%
10304 1
1.2%
10223 1
1.2%
9891 1
1.2%
9461 1
1.2%
9337 1
1.2%
8871 1
1.2%

장해보상금
Real number (ℝ)

HIGH CORRELATION 

Distinct72
Distinct (%)87.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean960.95122
Minimum7
Maximum5793
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2023-12-12T22:58:32.059957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile17.05
Q147.25
median272.5
Q31401
95-th percentile3782.9
Maximum5793
Range5786
Interquartile range (IQR)1353.75

Descriptive statistics

Standard deviation1318.1347
Coefficient of variation (CV)1.3716979
Kurtosis3.4491473
Mean960.95122
Median Absolute Deviation (MAD)257
Skewness1.8507507
Sum78798
Variance1737479.2
MonotonicityNot monotonic
2023-12-12T22:58:32.234321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
47 2
 
2.4%
54 2
 
2.4%
22 2
 
2.4%
18 2
 
2.4%
13 2
 
2.4%
20 2
 
2.4%
2424 2
 
2.4%
48 2
 
2.4%
60 2
 
2.4%
34 2
 
2.4%
Other values (62) 62
75.6%
ValueCountFrequency (%)
7 1
1.2%
13 2
2.4%
14 1
1.2%
17 1
1.2%
18 2
2.4%
19 1
1.2%
20 2
2.4%
22 2
2.4%
26 1
1.2%
30 1
1.2%
ValueCountFrequency (%)
5793 1
1.2%
5528 1
1.2%
4966 1
1.2%
3924 1
1.2%
3802 1
1.2%
3420 1
1.2%
2863 1
1.2%
2625 1
1.2%
2451 1
1.2%
2424 2
2.4%

순직유족연금
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct35
Distinct (%)42.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean588.68293
Minimum0
Maximum4655
Zeros48
Zeros (%)58.5%
Negative0
Negative (%)0.0%
Memory size870.0 B
2023-12-12T22:58:32.385800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3757
95-th percentile3336.9
Maximum4655
Range4655
Interquartile range (IQR)757

Descriptive statistics

Standard deviation1091.4321
Coefficient of variation (CV)1.8540237
Kurtosis4.8250037
Mean588.68293
Median Absolute Deviation (MAD)0
Skewness2.2653467
Sum48272
Variance1191224
MonotonicityNot monotonic
2023-12-12T22:58:32.500667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
0 48
58.5%
8 1
 
1.2%
1825 1
 
1.2%
1167 1
 
1.2%
1979 1
 
1.2%
1308 1
 
1.2%
2328 1
 
1.2%
1491 1
 
1.2%
3390 1
 
1.2%
1633 1
 
1.2%
Other values (25) 25
30.5%
ValueCountFrequency (%)
0 48
58.5%
8 1
 
1.2%
11 1
 
1.2%
67 1
 
1.2%
88 1
 
1.2%
159 1
 
1.2%
274 1
 
1.2%
275 1
 
1.2%
342 1
 
1.2%
357 1
 
1.2%
ValueCountFrequency (%)
4655 1
1.2%
4397 1
1.2%
4186 1
1.2%
3754 1
1.2%
3390 1
1.2%
2328 1
1.2%
2000 1
1.2%
1979 1
1.2%
1908 1
1.2%
1873 1
1.2%

순직유족보상금
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct27
Distinct (%)32.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean366.42683
Minimum0
Maximum3108
Zeros48
Zeros (%)58.5%
Negative0
Negative (%)0.0%
Memory size870.0 B
2023-12-12T22:58:32.624738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q314
95-th percentile2741.55
Maximum3108
Range3108
Interquartile range (IQR)14

Descriptive statistics

Standard deviation837.73181
Coefficient of variation (CV)2.2862186
Kurtosis3.7296253
Mean366.42683
Median Absolute Deviation (MAD)0
Skewness2.2510883
Sum30047
Variance701794.59
MonotonicityNot monotonic
2023-12-12T22:58:32.770357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 48
58.5%
14 5
 
6.1%
4 3
 
3.7%
9 2
 
2.4%
3 2
 
2.4%
10 1
 
1.2%
1926 1
 
1.2%
1964 1
 
1.2%
2809 1
 
1.2%
1654 1
 
1.2%
Other values (17) 17
 
20.7%
ValueCountFrequency (%)
0 48
58.5%
3 2
 
2.4%
4 3
 
3.7%
8 1
 
1.2%
9 2
 
2.4%
10 1
 
1.2%
14 5
 
6.1%
16 1
 
1.2%
17 1
 
1.2%
18 1
 
1.2%
ValueCountFrequency (%)
3108 1
1.2%
2986 1
1.2%
2831 1
1.2%
2809 1
1.2%
2759 1
1.2%
2410 1
1.2%
1964 1
1.2%
1962 1
1.2%
1926 1
1.2%
1807 1
1.2%

부조급여(계)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct82
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19781.866
Minimum17
Maximum51095
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2023-12-12T22:58:32.913832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum17
5-th percentile123.25
Q111467
median15889
Q326818.75
95-th percentile46376.4
Maximum51095
Range51078
Interquartile range (IQR)15351.75

Descriptive statistics

Standard deviation12396.118
Coefficient of variation (CV)0.62664049
Kurtosis-0.056204256
Mean19781.866
Median Absolute Deviation (MAD)6262
Skewness0.70396698
Sum1622113
Variance1.5366374 × 108
MonotonicityNot monotonic
2023-12-12T22:58:33.069078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
28 1
 
1.2%
12318 1
 
1.2%
12034 1
 
1.2%
32104 1
 
1.2%
11879 1
 
1.2%
32891 1
 
1.2%
13695 1
 
1.2%
27213 1
 
1.2%
11331 1
 
1.2%
27226 1
 
1.2%
Other values (72) 72
87.8%
ValueCountFrequency (%)
17 1
1.2%
28 1
1.2%
85 1
1.2%
111 1
1.2%
123 1
1.2%
128 1
1.2%
4995 1
1.2%
7488 1
1.2%
9594 1
1.2%
9660 1
1.2%
ValueCountFrequency (%)
51095 1
1.2%
47807 1
1.2%
47639 1
1.2%
47014 1
1.2%
46569 1
1.2%
42717 1
1.2%
39393 1
1.2%
39309 1
1.2%
38727 1
1.2%
37011 1
1.2%

재해부조금
Real number (ℝ)

HIGH CORRELATION 

Distinct67
Distinct (%)81.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean117.76829
Minimum3
Maximum629
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2023-12-12T22:58:33.226137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile8.05
Q119.5
median80
Q3149.5
95-th percentile407
Maximum629
Range626
Interquartile range (IQR)130

Descriptive statistics

Standard deviation126.03638
Coefficient of variation (CV)1.0702064
Kurtosis3.6156223
Mean117.76829
Median Absolute Deviation (MAD)63
Skewness1.8432901
Sum9657
Variance15885.168
MonotonicityNot monotonic
2023-12-12T22:58:33.381516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13 5
 
6.1%
14 2
 
2.4%
78 2
 
2.4%
17 2
 
2.4%
126 2
 
2.4%
26 2
 
2.4%
90 2
 
2.4%
18 2
 
2.4%
6 2
 
2.4%
150 2
 
2.4%
Other values (57) 59
72.0%
ValueCountFrequency (%)
3 1
 
1.2%
6 2
 
2.4%
7 1
 
1.2%
8 1
 
1.2%
9 1
 
1.2%
10 1
 
1.2%
11 1
 
1.2%
12 1
 
1.2%
13 5
6.1%
14 2
 
2.4%
ValueCountFrequency (%)
629 1
1.2%
463 1
1.2%
449 1
1.2%
438 1
1.2%
408 1
1.2%
388 1
1.2%
365 1
1.2%
331 1
1.2%
266 1
1.2%
244 1
1.2%

사망조위금
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct77
Distinct (%)93.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19669.28
Minimum0
Maximum51040
Zeros6
Zeros (%)7.3%
Negative0
Negative (%)0.0%
Memory size870.0 B
2023-12-12T22:58:33.530228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q111448
median15623
Q326715.5
95-th percentile46280.7
Maximum51040
Range51040
Interquartile range (IQR)15267.5

Descriptive statistics

Standard deviation12363.307
Coefficient of variation (CV)0.62855921
Kurtosis-0.032181123
Mean19669.28
Median Absolute Deviation (MAD)6234
Skewness0.71089812
Sum1612881
Variance1.5285137 × 108
MonotonicityNot monotonic
2023-12-12T22:58:33.701794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 6
 
7.3%
11321 1
 
1.2%
33416 1
 
1.2%
12016 1
 
1.2%
31959 1
 
1.2%
11866 1
 
1.2%
32741 1
 
1.2%
13676 1
 
1.2%
27108 1
 
1.2%
27136 1
 
1.2%
Other values (67) 67
81.7%
ValueCountFrequency (%)
0 6
7.3%
4916 1
 
1.2%
7368 1
 
1.2%
9131 1
 
1.2%
9647 1
 
1.2%
10110 1
 
1.2%
10180 1
 
1.2%
10384 1
 
1.2%
10520 1
 
1.2%
10577 1
 
1.2%
ValueCountFrequency (%)
51040 1
1.2%
47684 1
1.2%
47491 1
1.2%
46889 1
1.2%
46473 1
1.2%
42627 1
1.2%
39459 1
1.2%
38955 1
1.2%
38658 1
1.2%
36646 1
1.2%

퇴직수당
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct65
Distinct (%)79.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean518902.38
Minimum0
Maximum2712953
Zeros18
Zeros (%)22.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2023-12-12T22:58:34.223100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q122588.75
median36407
Q3874005
95-th percentile2270894.5
Maximum2712953
Range2712953
Interquartile range (IQR)851416.25

Descriptive statistics

Standard deviation781002.49
Coefficient of variation (CV)1.5051049
Kurtosis0.80719679
Mean518902.38
Median Absolute Deviation (MAD)36407
Skewness1.4381096
Sum42549995
Variance6.0996488 × 1011
MonotonicityNot monotonic
2023-12-12T22:58:34.484974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 18
 
22.0%
36684 1
 
1.2%
36130 1
 
1.2%
1539396 1
 
1.2%
23722 1
 
1.2%
884092 1
 
1.2%
29479 1
 
1.2%
1133252 1
 
1.2%
26473 1
 
1.2%
1000072 1
 
1.2%
Other values (55) 55
67.1%
ValueCountFrequency (%)
0 18
22.0%
3077 1
 
1.2%
16148 1
 
1.2%
22211 1
 
1.2%
23722 1
 
1.2%
24112 1
 
1.2%
26458 1
 
1.2%
26473 1
 
1.2%
26940 1
 
1.2%
28639 1
 
1.2%
ValueCountFrequency (%)
2712953 1
1.2%
2566243 1
1.2%
2335012 1
1.2%
2280149 1
1.2%
2272105 1
1.2%
2247894 1
1.2%
2216637 1
1.2%
2071530 1
1.2%
2044082 1
1.2%
1930235 1
1.2%

Interactions

2023-12-12T22:58:26.699678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:06.695213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:08.289240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:09.774498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:11.180692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:12.757924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:14.267325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:15.507531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:16.799414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:18.786167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:20.386863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:21.700604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:22.880459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:24.317083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:25.577422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:26.785479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:06.800498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:08.403487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:09.888602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:11.279395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:12.871918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:14.358520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:15.612589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:16.949441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:18.903972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:20.494292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:21.791503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:22.959897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:24.412461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:25.661153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:26.857756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:06.909929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:08.484609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:09.981432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:11.635235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:12.968978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:14.430895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:15.681676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:17.079338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:19.008437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:20.590004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:21.860351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:23.026272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:24.490430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:25.729009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:26.937330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:07.062382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:08.584053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:10.104813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:11.719760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:13.066691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:14.518951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:15.766775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:17.226953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:19.112865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:20.678718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:21.938102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:23.113562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:24.569675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:25.818918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:27.037067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:07.172441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:08.685531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:10.228222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:11.817481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:13.169734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:14.601632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:15.846525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:17.686121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:19.219105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:20.767800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:22.024292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:23.197521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:24.655053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:25.895460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:27.123590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:07.269295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:08.775200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:10.314821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:11.902173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:13.280539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:14.702891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:15.944364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:17.777503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:19.332584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:20.865869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:22.104298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:23.266180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:24.743140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:25.969873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:27.193555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:07.363537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:08.859324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:10.402224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:11.988209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:13.372769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:14.810366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:16.021569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:17.885187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:19.451293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:20.960649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:22.187360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:23.330039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:24.826969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:26.040983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:27.264961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:07.466233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:08.948503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:10.480841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:12.091341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:13.461531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:14.904529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:16.087670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:17.991369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:19.548209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:21.046133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:22.263507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:23.647961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:24.903820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:26.116374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:27.341713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:07.575979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:09.051004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:10.568738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:12.174562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:13.552951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:14.988390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:16.170335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:18.101989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:19.665195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:21.130640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:22.344816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:23.714895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:24.977618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:26.204508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:27.435095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:07.678911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:09.167503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:10.654064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:12.256746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:13.654522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:15.064921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:16.244167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:18.197371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:19.772510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:21.216242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:22.424154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:23.807121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:25.066590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:26.274262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:27.506397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:07.775995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:09.285760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:10.749795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:12.350462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:13.766806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:15.127374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:16.315027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:18.292866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:19.857849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:21.283121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:22.495013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:23.890438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:25.141441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:26.338802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:27.585744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:07.879890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:09.396438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:10.839072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:12.441825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:13.869809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:15.198766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:16.409291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:18.394930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:19.951165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:21.361355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:22.566247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:23.984757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:25.225821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:26.408135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:27.671899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:07.989341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:09.498544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:10.931851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:12.520149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:13.982446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:15.270591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:16.497548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:18.492778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:20.054421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:21.456968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:22.650439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:24.066981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:25.297943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:26.483805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:27.755421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:08.085873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:09.584563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:11.015395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:12.598545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:14.072872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:15.348787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:16.591150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:18.593132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:20.162708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:21.533296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:22.729886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:24.157134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:25.380117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:26.561152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:27.848702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:08.185970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:09.678393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:11.096331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:12.676655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:14.177242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:15.415129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:16.696579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:18.673287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:20.280159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:21.611551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:22.804989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:24.242029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:25.496220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:26.629048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:58:34.684970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도구분재해보상급여(계)공무상요양비공무상요양일시금유족보상금유족연금장해연금장해유족연금장해보상금순직유족연금순직유족보상금부조급여(계)재해부조금사망조위금퇴직수당
연도1.0000.0000.8410.6640.3640.2790.5740.9340.9660.4060.7170.3830.8310.5170.8310.516
구분0.0001.0000.4560.5050.3531.0000.0000.0000.0000.8630.0470.5490.7970.6830.7970.737
재해보상급여(계)0.8410.4561.0000.8900.1680.0000.7130.8960.9150.0720.7650.4470.7590.0000.7590.577
공무상요양비0.6640.5050.8901.0000.0000.0000.8290.7530.7960.0000.8510.0000.4900.0000.4900.346
공무상요양일시금0.3640.3530.1680.0001.0000.4780.0000.3150.5540.5240.0000.8270.5690.0000.5690.744
유족보상금0.2791.0000.0000.0000.4781.0000.4380.4730.1820.9120.3860.3230.6700.8030.6700.841
유족연금0.5740.0000.7130.8290.0000.4381.0000.7230.7580.0000.9710.6910.5180.0000.5180.841
장해연금0.9340.0000.8960.7530.3150.4730.7231.0000.9460.4770.8220.5930.8250.0000.8250.671
장해유족연금0.9660.0000.9150.7960.5540.1820.7580.9461.0000.0000.8280.6770.7690.0000.7690.410
장해보상금0.4060.8630.0720.0000.5240.9120.0000.4770.0001.0000.0000.2850.5290.7220.5290.886
순직유족연금0.7170.0470.7650.8510.0000.3860.9710.8220.8280.0001.0000.7590.7830.0000.7830.793
순직유족보상금0.3830.5490.4470.0000.8270.3230.6910.5930.6770.2850.7591.0000.7170.2700.7170.747
부조급여(계)0.8310.7970.7590.4900.5690.6700.5180.8250.7690.5290.7830.7171.0000.6011.0000.653
재해부조금0.5170.6830.0000.0000.0000.8030.0000.0000.0000.7220.0000.2700.6011.0000.6010.679
사망조위금0.8310.7970.7590.4900.5690.6700.5180.8250.7690.5290.7830.7171.0000.6011.0000.653
퇴직수당0.5160.7370.5770.3460.7440.8410.8410.6710.4100.8860.7930.7470.6530.6790.6531.000
2023-12-12T22:58:34.982038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도재해보상급여(계)공무상요양비공무상요양일시금유족보상금유족연금장해연금장해유족연금장해보상금순직유족연금순직유족보상금부조급여(계)재해부조금사망조위금퇴직수당구분
연도1.0000.9320.8830.042-0.0750.7780.9750.986-0.1430.8900.8330.379-0.3830.3790.6790.000
재해보상급여(계)0.9321.0000.8970.039-0.1220.7230.9440.944-0.1780.8440.7660.256-0.3550.2560.5220.329
공무상요양비0.8830.8971.000-0.001-0.3540.6340.8150.855-0.4290.7670.6890.143-0.5550.1450.3640.485
공무상요양일시금0.0420.039-0.0011.0000.342-0.4520.0700.0580.461-0.221-0.0690.2380.3000.2350.3340.365
유족보상금-0.075-0.122-0.3540.3421.000-0.0700.056-0.0200.901-0.0970.0290.5660.7480.5650.5270.955
유족연금0.7780.7230.634-0.452-0.0701.0000.7750.782-0.2420.8700.7340.343-0.2810.3440.4660.000
장해연금0.9750.9440.8150.0700.0560.7751.0000.984-0.0170.8940.8540.432-0.2450.4320.7040.000
장해유족연금0.9860.9440.8550.058-0.0200.7820.9841.000-0.1020.8950.8400.404-0.3330.4040.6890.000
장해보상금-0.143-0.178-0.4290.4610.901-0.242-0.017-0.1021.000-0.242-0.1060.4850.7140.4830.5180.856
순직유족연금0.8900.8440.767-0.221-0.0970.8700.8940.895-0.2421.0000.9520.377-0.3030.3780.5320.028
순직유족보상금0.8330.7660.689-0.0690.0290.7340.8540.840-0.1060.9521.0000.451-0.1790.4510.5900.397
부조급여(계)0.3790.2560.1430.2380.5660.3430.4320.4040.4850.3770.4511.0000.4831.0000.6750.598
재해부조금-0.383-0.355-0.5550.3000.748-0.281-0.245-0.3330.714-0.303-0.1790.4831.0000.4780.1100.661
사망조위금0.3790.2560.1450.2350.5650.3440.4320.4040.4830.3780.4511.0000.4781.0000.6760.598
퇴직수당0.6790.5220.3640.3340.5270.4660.7040.6890.5180.5320.5900.6750.1100.6761.0000.718
구분0.0000.3290.4850.3650.9550.0000.0000.0000.8560.0280.3970.5980.6610.5980.7181.000

Missing values

2023-12-12T22:58:27.985857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:58:28.186059image/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

연도구분재해보상급여(계)공무상요양비공무상요양일시금유족보상금유족연금장해연금장해유족연금장해보상금순직유족연금순직유족보상금부조급여(계)재해부조금사망조위금퇴직수당
01982건수14641151022004604700282800
11982금액377771202525093044700171700
21983건수2078171902560590440011111100
31983금액476074603415012004790012312300
41984건수37533415023407003400858500
51984금액4786108303099014404600012812800
61985건수496945680252097052001357657135190
71985금액5546147403215022306340049957949160
81986건수5414499702510115051001738065173150
91986금액63981714036890308068700748812073680
연도구분재해보상급여(계)공무상요양비공무상요양일시금유족보상금유족연금장해연금장해유족연금장해보상금순직유족연금순직유족보상금부조급여(계)재해부조금사망조위금퇴직수당
722018건수1983331443130864446391708806714911413407131339435287
732018금액1061552551308237108564558793374043390283147014126468892071530
742019건수222232166094084518939742946120163391299781311238786
752019금액1207363395408920140064696098911597375416544656998464732335012
762020건수20027014175606859724022610304221908141312591311644488
772020금액126104342170741816002495201022317294186280947807123476842566243
782021건수175755113428081679943014105242218731413054131304140378
792021금액127498306890819218398517581083012704397196447639148474912216637
802022건수1751591095970927762445501113019200091401431401150191
812022금액135899292110107142194554450115801418465519265109555510402712953