Overview

Dataset statistics

Number of variables13
Number of observations82
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.4 KiB
Average record size in memory117.6 B

Variable types

Numeric12
Categorical1

Dataset

Description연금급여 종류별(퇴직연금, 퇴직연금일시금, 유족연금 유족연금일시금 등) 급여지급액(연금급여) 추이에 대한 데이터입니다.
URLhttps://www.data.go.kr/data/15054026/fileData.do

Alerts

연도 is highly overall correlated with 퇴직급여(계) and 5 other fieldsHigh correlation
퇴직급여(계) is highly overall correlated with 연도 and 5 other fieldsHigh correlation
퇴직(연금)일시금 is highly overall correlated with 퇴직연금공제일시금 and 5 other fieldsHigh correlation
퇴직연금공제일시금 is highly overall correlated with 퇴직(연금)일시금 and 3 other fieldsHigh correlation
퇴직연금 is highly overall correlated with 연도 and 5 other fieldsHigh correlation
기타급여 is highly overall correlated with 퇴직(연금)일시금 and 2 other fieldsHigh correlation
유족급여(계) is highly overall correlated with 연도 and 5 other fieldsHigh correlation
유족(연금)일시금 is highly overall correlated with 퇴직(연금)일시금 and 4 other fieldsHigh correlation
유족연금 is highly overall correlated with 연도 and 5 other fieldsHigh correlation
유족연금부가금 is highly overall correlated with 연도 and 9 other fieldsHigh correlation
유족연금특별부가금 is highly overall correlated with 연도 and 8 other fieldsHigh correlation
유족급여가산금 is highly overall correlated with 기타급여 High correlation
구분 is highly overall correlated with 퇴직(연금)일시금 and 3 other fieldsHigh correlation
퇴직급여(계) has unique valuesUnique
퇴직(연금)일시금 has unique valuesUnique
퇴직연금공제일시금 has unique valuesUnique
퇴직연금 has unique valuesUnique
유족급여(계) has unique valuesUnique
유족연금 has unique valuesUnique
기타급여 has 64 (78.0%) zerosZeros
유족연금특별부가금 has 6 (7.3%) zerosZeros
유족급여가산금 has 71 (86.6%) zerosZeros

Reproduction

Analysis started2023-12-12 16:08:15.450303
Analysis finished2023-12-12 16:08:29.491304
Duration14.04 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
2023-12-13T01:08:29.565776image/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
2023-12-13T01:08:29.703790image/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

2023-12-13T01:08:29.854107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:08:29.944418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건수 41
50.0%
금액 41
50.0%

퇴직급여(계)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct82
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3540721.8
Minimum37152
Maximum16725152
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2023-12-13T01:08:30.056147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37152
5-th percentile40109.55
Q1193637.75
median2548938
Q34981731
95-th percentile12519728
Maximum16725152
Range16688000
Interquartile range (IQR)4788093.2

Descriptive statistics

Standard deviation4019540.3
Coefficient of variation (CV)1.1352319
Kurtosis1.8042512
Mean3540721.8
Median Absolute Deviation (MAD)2369852
Skewness1.4892295
Sum2.9033919 × 108
Variance1.6156704 × 1013
MonotonicityNot monotonic
2023-12-13T01:08:30.182637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
42058 1
 
1.2%
3662123 1
 
1.2%
3471050 1
 
1.2%
7298872 1
 
1.2%
3322632 1
 
1.2%
6720728 1
 
1.2%
3158627 1
 
1.2%
6234759 1
 
1.2%
3028012 1
 
1.2%
5819764 1
 
1.2%
Other values (72) 72
87.8%
ValueCountFrequency (%)
37152 1
1.2%
37514 1
1.2%
38799 1
1.2%
39510 1
1.2%
40007 1
1.2%
42058 1
1.2%
42888 1
1.2%
43594 1
1.2%
50213 1
1.2%
56700 1
1.2%
ValueCountFrequency (%)
16725152 1
1.2%
15363319 1
1.2%
14350692 1
1.2%
13398458 1
1.2%
12558078 1
1.2%
11791082 1
1.2%
11105905 1
1.2%
10489001 1
1.2%
9416504 1
1.2%
8691962 1
1.2%

퇴직(연금)일시금
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct82
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean228760.94
Minimum6493
Maximum2433918
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2023-12-13T01:08:30.336638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6493
5-th percentile8280.1
Q118981.25
median93557.5
Q3282424.25
95-th percentile844500.55
Maximum2433918
Range2427425
Interquartile range (IQR)263443

Descriptive statistics

Standard deviation393095.92
Coefficient of variation (CV)1.7183699
Kurtosis17.438218
Mean228760.94
Median Absolute Deviation (MAD)84308.5
Skewness3.807521
Sum18758397
Variance1.545244 × 1011
MonotonicityNot monotonic
2023-12-13T01:08:30.495112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37795 1
 
1.2%
8930 1
 
1.2%
12002 1
 
1.2%
257035 1
 
1.2%
9676 1
 
1.2%
271700 1
 
1.2%
11852 1
 
1.2%
256862 1
 
1.2%
9507 1
 
1.2%
352399 1
 
1.2%
Other values (72) 72
87.8%
ValueCountFrequency (%)
6493 1
1.2%
6810 1
1.2%
7321 1
1.2%
7395 1
1.2%
8269 1
1.2%
8491 1
1.2%
8930 1
1.2%
9507 1
1.2%
9676 1
1.2%
9798 1
1.2%
ValueCountFrequency (%)
2433918 1
1.2%
2101181 1
1.2%
1033752 1
1.2%
869073 1
1.2%
846907 1
1.2%
798778 1
1.2%
655505 1
1.2%
575439 1
1.2%
464186 1
1.2%
449606 1
1.2%

퇴직연금공제일시금
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct82
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean58319.305
Minimum222
Maximum929227
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2023-12-13T01:08:30.620277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum222
5-th percentile831.55
Q12371
median7704
Q363340
95-th percentile173275.55
Maximum929227
Range929005
Interquartile range (IQR)60969

Descriptive statistics

Standard deviation121599.9
Coefficient of variation (CV)2.0850712
Kurtosis33.188024
Mean58319.305
Median Absolute Deviation (MAD)7114.5
Skewness5.1085068
Sum4782183
Variance1.4786536 × 1010
MonotonicityNot monotonic
2023-12-13T01:08:30.745361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
222 1
 
1.2%
1383 1
 
1.2%
1206 1
 
1.2%
52618 1
 
1.2%
1006 1
 
1.2%
62527 1
 
1.2%
1376 1
 
1.2%
58363 1
 
1.2%
1101 1
 
1.2%
110082 1
 
1.2%
Other values (72) 72
87.8%
ValueCountFrequency (%)
222 1
1.2%
381 1
1.2%
471 1
1.2%
708 1
1.2%
828 1
1.2%
899 1
1.2%
1006 1
1.2%
1073 1
1.2%
1101 1
1.2%
1113 1
1.2%
ValueCountFrequency (%)
929227 1
1.2%
402782 1
1.2%
334575 1
1.2%
227828 1
1.2%
173684 1
1.2%
165515 1
1.2%
148098 1
1.2%
138527 1
1.2%
136233 1
1.2%
135990 1
1.2%

퇴직연금
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct82
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3246685.6
Minimum3556
Maximum16359522
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2023-12-13T01:08:30.878448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3556
5-th percentile9951.45
Q160306.5
median1986767
Q34741470.8
95-th percentile12272940
Maximum16359522
Range16355966
Interquartile range (IQR)4681164.2

Descriptive statistics

Standard deviation4003111.1
Coefficient of variation (CV)1.2329839
Kurtosis1.8463158
Mean3246685.6
Median Absolute Deviation (MAD)1949124
Skewness1.5306567
Sum2.6622822 × 108
Variance1.6024898 × 1013
MonotonicityNot monotonic
2023-12-13T01:08:31.032532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3556 1
 
1.2%
3651810 1
 
1.2%
3457842 1
 
1.2%
6989219 1
 
1.2%
3311950 1
 
1.2%
6386501 1
 
1.2%
3145399 1
 
1.2%
5919534 1
 
1.2%
3017404 1
 
1.2%
5357283 1
 
1.2%
Other values (72) 72
87.8%
ValueCountFrequency (%)
3556 1
1.2%
5390 1
1.2%
6940 1
1.2%
8691 1
1.2%
9926 1
1.2%
10435 1
1.2%
14196 1
1.2%
14973 1
1.2%
17186 1
1.2%
19787 1
1.2%
ValueCountFrequency (%)
16359522 1
1.2%
15073971 1
1.2%
14066376 1
1.2%
13156534 1
1.2%
12311363 1
1.2%
11542906 1
1.2%
10853079 1
1.2%
10176825 1
1.2%
9060745 1
1.2%
8378622 1
1.2%

기타급여
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct19
Distinct (%)23.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6955.9268
Minimum0
Maximum162689
Zeros64
Zeros (%)78.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2023-12-13T01:08:31.144354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile37719.95
Maximum162689
Range162689
Interquartile range (IQR)0

Descriptive statistics

Standard deviation26344.484
Coefficient of variation (CV)3.7873434
Kurtosis23.185062
Mean6955.9268
Median Absolute Deviation (MAD)0
Skewness4.7336282
Sum570386
Variance6.9403182 × 108
MonotonicityNot monotonic
2023-12-13T01:08:31.238305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 64
78.0%
485 1
 
1.2%
1465 1
 
1.2%
815 1
 
1.2%
18371 1
 
1.2%
6068 1
 
1.2%
2047 1
 
1.2%
2260 1
 
1.2%
2688 1
 
1.2%
1725 1
 
1.2%
Other values (9) 9
 
11.0%
ValueCountFrequency (%)
0 64
78.0%
42 1
 
1.2%
485 1
 
1.2%
815 1
 
1.2%
1465 1
 
1.2%
1725 1
 
1.2%
1863 1
 
1.2%
2047 1
 
1.2%
2260 1
 
1.2%
2688 1
 
1.2%
ValueCountFrequency (%)
162689 1
1.2%
138024 1
1.2%
97084 1
1.2%
45052 1
1.2%
38160 1
1.2%
29359 1
1.2%
22189 1
1.2%
18371 1
1.2%
6068 1
1.2%
2688 1
1.2%

유족급여(계)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct82
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean324549.15
Minimum1526
Maximum1374966
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2023-12-13T01:08:31.356553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1526
5-th percentile1782.5
Q117435
median158328
Q3531357.75
95-th percentile1057465
Maximum1374966
Range1373440
Interquartile range (IQR)513922.75

Descriptive statistics

Standard deviation362753.65
Coefficient of variation (CV)1.1177156
Kurtosis0.31418368
Mean324549.15
Median Absolute Deviation (MAD)154485.5
Skewness1.1315084
Sum26613030
Variance1.3159021 × 1011
MonotonicityNot monotonic
2023-12-13T01:08:31.472594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1526 1
 
1.2%
484381 1
 
1.2%
444445 1
 
1.2%
602880 1
 
1.2%
405600 1
 
1.2%
533676 1
 
1.2%
368295 1
 
1.2%
477591 1
 
1.2%
334430 1
 
1.2%
429814 1
 
1.2%
Other values (72) 72
87.8%
ValueCountFrequency (%)
1526 1
1.2%
1670 1
1.2%
1726 1
1.2%
1729 1
1.2%
1772 1
1.2%
1982 1
1.2%
2434 1
1.2%
2778 1
1.2%
3070 1
1.2%
3609 1
1.2%
ValueCountFrequency (%)
1374966 1
1.2%
1265914 1
1.2%
1191253 1
1.2%
1126460 1
1.2%
1060487 1
1.2%
1000046 1
1.2%
939881 1
1.2%
911893 1
1.2%
896734 1
1.2%
854054 1
1.2%

유족(연금)일시금
Real number (ℝ)

HIGH CORRELATION 

Distinct80
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19560.976
Minimum278
Maximum86303
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2023-12-13T01:08:31.591352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum278
5-th percentile328.45
Q1682.5
median7275.5
Q332126.5
95-th percentile76309.65
Maximum86303
Range86025
Interquartile range (IQR)31444

Descriptive statistics

Standard deviation23324.017
Coefficient of variation (CV)1.1923749
Kurtosis1.0600844
Mean19560.976
Median Absolute Deviation (MAD)6988.5
Skewness1.2597935
Sum1604000
Variance5.4400976 × 108
MonotonicityNot monotonic
2023-12-13T01:08:31.701185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1557 2
 
2.4%
413 2
 
2.4%
1384 1
 
1.2%
33268 1
 
1.2%
429 1
 
1.2%
32349 1
 
1.2%
476 1
 
1.2%
29923 1
 
1.2%
471 1
 
1.2%
31108 1
 
1.2%
Other values (70) 70
85.4%
ValueCountFrequency (%)
278 1
1.2%
296 1
1.2%
311 1
1.2%
321 1
1.2%
327 1
1.2%
356 1
1.2%
361 1
1.2%
364 1
1.2%
413 2
2.4%
429 1
1.2%
ValueCountFrequency (%)
86303 1
1.2%
83895 1
1.2%
81457 1
1.2%
80506 1
1.2%
76708 1
1.2%
68741 1
1.2%
61880 1
1.2%
51641 1
1.2%
46011 1
1.2%
43750 1
1.2%

유족연금
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct82
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean297811.67
Minimum140
Maximum1324424
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2023-12-13T01:08:31.837055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum140
5-th percentile290.8
Q13823.75
median135346.5
Q3513345.25
95-th percentile1010237.6
Maximum1324424
Range1324284
Interquartile range (IQR)509521.5

Descriptive statistics

Standard deviation358731.68
Coefficient of variation (CV)1.2045588
Kurtosis0.19234093
Mean297811.67
Median Absolute Deviation (MAD)134873.5
Skewness1.114672
Sum24420557
Variance1.2868842 × 1011
MonotonicityNot monotonic
2023-12-13T01:08:31.969516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
140 1
 
1.2%
483224 1
 
1.2%
443324 1
 
1.2%
547210 1
 
1.2%
404362 1
 
1.2%
483331 1
 
1.2%
367138 1
 
1.2%
426306 1
 
1.2%
333231 1
 
1.2%
377277 1
 
1.2%
Other values (72) 72
87.8%
ValueCountFrequency (%)
140 1
1.2%
169 1
1.2%
225 1
1.2%
261 1
1.2%
290 1
1.2%
306 1
1.2%
351 1
1.2%
376 1
1.2%
452 1
1.2%
494 1
1.2%
ValueCountFrequency (%)
1324424 1
1.2%
1216201 1
1.2%
1143454 1
1.2%
1077323 1
1.2%
1013288 1
1.2%
952279 1
1.2%
910854 1
1.2%
897469 1
1.2%
853011 1
1.2%
838953 1
1.2%

유족연금부가금
Real number (ℝ)

HIGH CORRELATION 

Distinct79
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4233.0854
Minimum2
Maximum17192
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2023-12-13T01:08:32.094695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile15.05
Q1190
median404
Q38078
95-th percentile16223.25
Maximum17192
Range17190
Interquartile range (IQR)7888

Descriptive statistics

Standard deviation5923.3173
Coefficient of variation (CV)1.3992908
Kurtosis-0.45585304
Mean4233.0854
Median Absolute Deviation (MAD)371.5
Skewness1.1212412
Sum347113
Variance35085687
MonotonicityNot monotonic
2023-12-13T01:08:32.307230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
336 2
 
2.4%
15 2
 
2.4%
381 2
 
2.4%
12318 1
 
1.2%
443 1
 
1.2%
16233 1
 
1.2%
449 1
 
1.2%
13831 1
 
1.2%
391 1
 
1.2%
13129 1
 
1.2%
Other values (69) 69
84.1%
ValueCountFrequency (%)
2 1
1.2%
6 1
1.2%
11 1
1.2%
15 2
2.4%
16 1
1.2%
17 1
1.2%
48 1
1.2%
51 1
1.2%
68 1
1.2%
106 1
1.2%
ValueCountFrequency (%)
17192 1
1.2%
16495 1
1.2%
16469 1
1.2%
16394 1
1.2%
16233 1
1.2%
16038 1
1.2%
15140 1
1.2%
14777 1
1.2%
14502 1
1.2%
14271 1
1.2%

유족연금특별부가금
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct75
Distinct (%)91.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2160.9756
Minimum0
Maximum9130
Zeros6
Zeros (%)7.3%
Negative0
Negative (%)0.0%
Memory size870.0 B
2023-12-13T01:08:32.470790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1155.25
median319.5
Q34261.75
95-th percentile8052.1
Maximum9130
Range9130
Interquartile range (IQR)4106.5

Descriptive statistics

Standard deviation2979.2845
Coefficient of variation (CV)1.3786757
Kurtosis-0.41320569
Mean2160.9756
Median Absolute Deviation (MAD)279.5
Skewness1.1276898
Sum177200
Variance8876136.3
MonotonicityNot monotonic
2023-12-13T01:08:32.890737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 6
 
7.3%
336 2
 
2.4%
91 2
 
2.4%
7048 1
 
1.2%
6106 1
 
1.2%
249 1
 
1.2%
7088 1
 
1.2%
313 1
 
1.2%
6591 1
 
1.2%
295 1
 
1.2%
Other values (65) 65
79.3%
ValueCountFrequency (%)
0 6
7.3%
17 1
 
1.2%
19 1
 
1.2%
30 1
 
1.2%
32 1
 
1.2%
34 1
 
1.2%
46 1
 
1.2%
64 1
 
1.2%
72 1
 
1.2%
91 2
 
2.4%
ValueCountFrequency (%)
9130 1
1.2%
8531 1
1.2%
8523 1
1.2%
8466 1
1.2%
8075 1
1.2%
7617 1
1.2%
7364 1
1.2%
7318 1
1.2%
7203 1
1.2%
7088 1
1.2%

유족급여가산금
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct12
Distinct (%)14.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean782.43902
Minimum0
Maximum17081
Zeros71
Zeros (%)86.6%
Negative0
Negative (%)0.0%
Memory size870.0 B
2023-12-13T01:08:32.984715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile5860
Maximum17081
Range17081
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2961.9713
Coefficient of variation (CV)3.7855618
Kurtosis19.347205
Mean782.43902
Median Absolute Deviation (MAD)0
Skewness4.3376382
Sum64160
Variance8773273.8
MonotonicityNot monotonic
2023-12-13T01:08:33.088192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 71
86.6%
3174 1
 
1.2%
4948 1
 
1.2%
5908 1
 
1.2%
6570 1
 
1.2%
10697 1
 
1.2%
15556 1
 
1.2%
17081 1
 
1.2%
184 1
 
1.2%
16 1
 
1.2%
Other values (2) 2
 
2.4%
ValueCountFrequency (%)
0 71
86.6%
4 1
 
1.2%
16 1
 
1.2%
22 1
 
1.2%
184 1
 
1.2%
3174 1
 
1.2%
4948 1
 
1.2%
5908 1
 
1.2%
6570 1
 
1.2%
10697 1
 
1.2%
ValueCountFrequency (%)
17081 1
1.2%
15556 1
1.2%
10697 1
1.2%
6570 1
1.2%
5908 1
1.2%
4948 1
1.2%
3174 1
1.2%
184 1
1.2%
22 1
1.2%
16 1
1.2%

Interactions

2023-12-13T01:08:27.657277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:15.873080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:17.109126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:18.493837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:19.391067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:20.225327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:21.174707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:22.236825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:23.615434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:24.568728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:25.538160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:26.518077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:27.770509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:15.974520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:17.204684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:18.591139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:19.461903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:20.303299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:21.256330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:22.330725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:23.713009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:24.646442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:25.621053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:26.601953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:27.881114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:16.085888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:17.322121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:18.675781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:19.534396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:20.400478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:21.340571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:22.422480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:23.804355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:24.724920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:25.701396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:26.699416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:27.983245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:16.189309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:17.423956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:18.744025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:19.601033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:20.471414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:21.422268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:22.504160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:23.883938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:24.797403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:25.785919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:26.812444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:28.067525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:16.273736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:17.511739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:18.817090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:19.663570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:20.540764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:21.531227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:22.581613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:23.967086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:24.866422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:25.849923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:26.896079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:28.176818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:16.394993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:17.611103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:18.894683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:19.741362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:20.618167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:21.641744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:22.682402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:24.057341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:24.959694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:25.929290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:26.994782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:28.286305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:16.539551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:17.699036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:18.976032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:19.815260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:20.703963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:21.736327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:22.774539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:24.129760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:25.054577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:26.022308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:27.085352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:28.692697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:16.648929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:17.787584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:19.050671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:19.897042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:20.794121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:21.822480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:23.143403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:24.204294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:25.128241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:26.124138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:27.173297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:28.778315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:16.732135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:17.860557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:19.113952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:19.959329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:20.869903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:21.901413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:23.222618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:24.270747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:25.209377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:26.200020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:27.263085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:28.877392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:16.837643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:17.945038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:19.180296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:20.027093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:20.949992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:21.981941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:23.320018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:24.348907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:25.292643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:26.277131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:27.359924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:28.997618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:16.929312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:18.330626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:19.249537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:20.093674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:21.030470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:22.063803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:23.418873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:24.427190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:25.375902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:26.350364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:27.454884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:29.117146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:17.023711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:18.406137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:19.316021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:20.154514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:21.095809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:22.149461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:23.520311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:24.494230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:25.453505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:26.425254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:27.563438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:08:33.178742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도구분퇴직급여(계)퇴직(연금)일시금퇴직연금공제일시금퇴직연금기타급여유족급여(계)유족(연금)일시금유족연금유족연금부가금유족연금특별부가금유족급여가산금
연도1.0000.0000.8750.4180.2760.8880.3810.8790.4880.9240.5730.5510.312
구분0.0001.0000.3910.5810.6290.4030.3110.0001.0000.0000.7580.7160.258
퇴직급여(계)0.8750.3911.0000.0000.0000.9970.0000.9780.3760.9740.6500.6390.000
퇴직(연금)일시금0.4180.5810.0001.0000.8870.0000.2070.0000.8430.0000.7500.8470.000
퇴직연금공제일시금0.2760.6290.0000.8871.0000.0000.2430.0000.8430.0000.7040.8910.000
퇴직연금0.8880.4030.9970.0000.0001.0000.0000.9840.3480.9820.6730.6620.000
기타급여0.3810.3110.0000.2070.2430.0001.0000.0000.6670.0000.0000.0000.990
유족급여(계)0.8790.0000.9780.0000.0000.9840.0001.0000.0000.9960.5650.5420.000
유족(연금)일시금0.4881.0000.3760.8430.8430.3480.6670.0001.0000.0000.8610.9350.656
유족연금0.9240.0000.9740.0000.0000.9820.0000.9960.0001.0000.5300.4660.000
유족연금부가금0.5730.7580.6500.7500.7040.6730.0000.5650.8610.5301.0000.9430.000
유족연금특별부가금0.5510.7160.6390.8470.8910.6620.0000.5420.9350.4660.9431.0000.000
유족급여가산금0.3120.2580.0000.0000.0000.0000.9900.0000.6560.0000.0000.0001.000
2023-12-13T01:08:33.314456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도퇴직급여(계)퇴직(연금)일시금퇴직연금공제일시금퇴직연금기타급여유족급여(계)유족(연금)일시금유족연금유족연금부가금유족연금특별부가금유족급여가산금구분
연도1.0000.901-0.2000.0280.952-0.4760.940-0.2610.9840.6500.662-0.4020.000
퇴직급여(계)0.9011.0000.1520.3130.978-0.2240.9740.0890.9500.8420.838-0.2250.288
퇴직(연금)일시금-0.2000.1521.0000.8790.0520.501-0.0140.964-0.0780.5360.5150.3290.608
퇴직연금공제일시금0.0280.3130.8791.0000.2520.3410.1620.8740.1340.6710.6690.2160.450
퇴직연금0.9520.9780.0520.2521.000-0.3400.978-0.0020.9850.8230.824-0.2680.290
기타급여-0.476-0.2240.5010.341-0.3401.000-0.2810.543-0.3770.009-0.0280.7910.217
유족급여(계)0.9400.974-0.0140.1620.978-0.2811.000-0.0620.9770.7660.758-0.2250.000
유족(연금)일시금-0.2610.0890.9640.874-0.0020.543-0.0621.000-0.1300.5220.4920.4070.955
유족연금0.9840.950-0.0780.1340.985-0.3770.977-0.1301.0000.7470.753-0.3050.000
유족연금부가금0.6500.8420.5360.6710.8230.0090.7660.5220.7471.0000.9560.0030.740
유족연금특별부가금0.6620.8380.5150.6690.824-0.0280.7580.4920.7530.9561.000-0.0540.696
유족급여가산금-0.402-0.2250.3290.216-0.2680.791-0.2250.407-0.3050.003-0.0541.0000.179
구분0.0000.2880.6080.4500.2900.2170.0000.9550.0000.7400.6960.1791.000

Missing values

2023-12-13T01:08:29.264864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:08:29.419352image/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

연도구분퇴직급여(계)퇴직(연금)일시금퇴직연금공제일시금퇴직연금기타급여유족급여(계)유족(연금)일시금유족연금유족연금부가금유족연금특별부가금유족급여가산금
01982건수4205837795222355648515261384140200
11982금액143994132668135899264213196129242611100
21983건수40007342363815390016701495169600
31983금액166244148505276614973017078167243064800
41984건수395103209947169400172614862251500
51984금액158640135250360319787018506180873516800
61985건수38799285991509869101772144829015190
71985금액198767141267992725384221892173917934452133463174
81986건수375142523818411043501982155737617320
91986금액2429911600961592337613293592982423918704163914948
연도구분퇴직급여(계)퇴직(연금)일시금퇴직연금공제일시금퇴직연금기타급여유족급여(계)유족(연금)일시금유족연금유족연금부가금유족연금특별부가금유족급여가산금
722018건수502468368101113501676007043823117033483873360
732018금액125580781858886082712311363010604872417410132881450285230
742019건수53127068269899530353807521513217511293973040
752019금액133984581911375078713156534011264602628510773231477780750
762020건수562826297981073561739108013213278003533243170
772020금액143506922218226249414066376011912532658311434541275084660
782021건수595333311227828594127808540543568530113683190
792021금액153633192386405070815073971012659142691112162011427185310
802022건수627564514408708626052909118933649108543812940
812022금액167251523197934583716359522013749662808413244241514073180