Overview

Dataset statistics

Number of variables11
Number of observations26
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.6 KiB
Average record size in memory104.1 B

Variable types

Numeric11

Dataset

Description사립학교교직원연금공단 사학연금수급자 현황과 관련된 데이터로 연도별, 연금종류별(퇴직연금, 유족연금, 장해연금, 연계퇴직연금) 인원, 평균 연금액 등의 항목을 제공합니다. (단위 : 명, 천원)
URLhttps://www.data.go.kr/data/15045820/fileData.do

Alerts

연도 is highly overall correlated with 퇴직연금 인원(명) and 8 other fieldsHigh correlation
퇴직연금 인원(명) is highly overall correlated with 연도 and 8 other fieldsHigh correlation
퇴직연금 평균 연금액 is highly overall correlated with 연도 and 8 other fieldsHigh correlation
유족연금 인원(명) is highly overall correlated with 연도 and 8 other fieldsHigh correlation
유족연금 평균 연금액 is highly overall correlated with 연도 and 9 other fieldsHigh correlation
장해연금 인원(명) is highly overall correlated with 연도 and 8 other fieldsHigh correlation
장해연금 평균 연금액 is highly overall correlated with 연도 and 9 other fieldsHigh correlation
장해유족연금 인원(명) is highly overall correlated with 연도 and 8 other fieldsHigh correlation
장해유족연금 평균 연금액 is highly overall correlated with 유족연금 평균 연금액 and 2 other fieldsHigh correlation
연계퇴직연금 인원(명) is highly overall correlated with 연도 and 8 other fieldsHigh correlation
연계퇴직연금 평균연금액 is highly overall correlated with 연도 and 9 other fieldsHigh correlation
연도 has unique valuesUnique
퇴직연금 인원(명) has unique valuesUnique
퇴직연금 평균 연금액 has unique valuesUnique
유족연금 인원(명) has unique valuesUnique
유족연금 평균 연금액 has unique valuesUnique
장해연금 평균 연금액 has unique valuesUnique
장해유족연금 인원(명) has 6 (23.1%) zerosZeros
장해유족연금 평균 연금액 has 6 (23.1%) zerosZeros
연계퇴직연금 인원(명) has 12 (46.2%) zerosZeros
연계퇴직연금 평균연금액 has 12 (46.2%) zerosZeros

Reproduction

Analysis started2023-12-12 18:35:32.121358
Analysis finished2023-12-12 18:35:49.086403
Duration16.97 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2009.5
Minimum1997
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-13T03:35:49.185992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1997
5-th percentile1998.25
Q12003.25
median2009.5
Q32015.75
95-th percentile2020.75
Maximum2022
Range25
Interquartile range (IQR)12.5

Descriptive statistics

Standard deviation7.6485293
Coefficient of variation (CV)0.0038061853
Kurtosis-1.2
Mean2009.5
Median Absolute Deviation (MAD)6.5
Skewness0
Sum52247
Variance58.5
MonotonicityStrictly increasing
2023-12-13T03:35:49.382556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
1997 1
 
3.8%
2011 1
 
3.8%
2022 1
 
3.8%
2021 1
 
3.8%
2020 1
 
3.8%
2019 1
 
3.8%
2018 1
 
3.8%
2017 1
 
3.8%
2016 1
 
3.8%
2015 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
1997 1
3.8%
1998 1
3.8%
1999 1
3.8%
2000 1
3.8%
2001 1
3.8%
2002 1
3.8%
2003 1
3.8%
2004 1
3.8%
2005 1
3.8%
2006 1
3.8%
ValueCountFrequency (%)
2022 1
3.8%
2021 1
3.8%
2020 1
3.8%
2019 1
3.8%
2018 1
3.8%
2017 1
3.8%
2016 1
3.8%
2015 1
3.8%
2014 1
3.8%
2013 1
3.8%

퇴직연금 인원(명)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38584.538
Minimum4997
Maximum94086
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-13T03:35:49.561132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4997
5-th percentile6874.25
Q117017.5
median32611.5
Q356105.5
95-th percentile85603.25
Maximum94086
Range89089
Interquartile range (IQR)39088

Descriptive statistics

Standard deviation26230.673
Coefficient of variation (CV)0.67982343
Kurtosis-0.62506287
Mean38584.538
Median Absolute Deviation (MAD)18295.5
Skewness0.66299543
Sum1003198
Variance6.8804821 × 108
MonotonicityStrictly increasing
2023-12-13T03:35:49.736956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
4997 1
 
3.8%
36849 1
 
3.8%
94086 1
 
3.8%
87273 1
 
3.8%
80594 1
 
3.8%
73832 1
 
3.8%
67607 1
 
3.8%
61692 1
 
3.8%
57084 1
 
3.8%
53170 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
4997 1
3.8%
5863 1
3.8%
9908 1
3.8%
12626 1
3.8%
13708 1
3.8%
14924 1
3.8%
16542 1
3.8%
18444 1
3.8%
20412 1
3.8%
22638 1
3.8%
ValueCountFrequency (%)
94086 1
3.8%
87273 1
3.8%
80594 1
3.8%
73832 1
3.8%
67607 1
3.8%
61692 1
3.8%
57084 1
3.8%
53170 1
3.8%
47782 1
3.8%
43697 1
3.8%

퇴직연금 평균 연금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2270435.8
Minimum1346800
Maximum2994830
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-13T03:35:49.909880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1346800
5-th percentile1354542.5
Q11829212.5
median2371635
Q32824342.5
95-th percentile2924717.8
Maximum2994830
Range1648030
Interquartile range (IQR)995130

Descriptive statistics

Standard deviation585464.99
Coefficient of variation (CV)0.25786458
Kurtosis-1.3254333
Mean2270435.8
Median Absolute Deviation (MAD)470300
Skewness-0.43054767
Sum59031331
Variance3.4276925 × 1011
MonotonicityNot monotonic
2023-12-13T03:35:50.077154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
1365170 1
 
3.8%
2500430 1
 
3.8%
2994830 1
 
3.8%
2935580 1
 
3.8%
2892131 1
 
3.8%
2873790 1
 
3.8%
2859260 1
 
3.8%
2845480 1
 
3.8%
2826720 1
 
3.8%
2817210 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
1346800 1
3.8%
1351000 1
3.8%
1365170 1
3.8%
1398720 1
3.8%
1444350 1
3.8%
1539660 1
3.8%
1803990 1
3.8%
1904880 1
3.8%
1999670 1
3.8%
2089270 1
3.8%
ValueCountFrequency (%)
2994830 1
3.8%
2935580 1
3.8%
2892131 1
3.8%
2873790 1
3.8%
2859260 1
3.8%
2845480 1
3.8%
2826720 1
3.8%
2817210 1
3.8%
2749300 1
3.8%
2692910 1
3.8%

유족연금 인원(명)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3894.1538
Minimum447
Maximum10431
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-13T03:35:50.222093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum447
5-th percentile551.75
Q11371.25
median3051.5
Q35872.75
95-th percentile9396.5
Maximum10431
Range9984
Interquartile range (IQR)4501.5

Descriptive statistics

Standard deviation3048.3371
Coefficient of variation (CV)0.78279833
Kurtosis-0.58356686
Mean3894.1538
Median Absolute Deviation (MAD)2047.5
Skewness0.74930838
Sum101248
Variance9292359.3
MonotonicityStrictly increasing
2023-12-13T03:35:50.395360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
447 1
 
3.8%
3585 1
 
3.8%
10431 1
 
3.8%
9571 1
 
3.8%
8873 1
 
3.8%
8139 1
 
3.8%
7337 1
 
3.8%
6672 1
 
3.8%
6039 1
 
3.8%
5374 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
447 1
3.8%
528 1
3.8%
623 1
3.8%
734 1
3.8%
904 1
3.8%
1104 1
3.8%
1319 1
3.8%
1528 1
3.8%
1743 1
3.8%
2011 1
3.8%
ValueCountFrequency (%)
10431 1
3.8%
9571 1
3.8%
8873 1
3.8%
8139 1
3.8%
7337 1
3.8%
6672 1
3.8%
6039 1
3.8%
5374 1
3.8%
4884 1
3.8%
4435 1
3.8%

유족연금 평균 연금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1435270.8
Minimum982080
Maximum1757760
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-13T03:35:50.553513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum982080
5-th percentile988407.5
Q11275865
median1531740
Q31629302.5
95-th percentile1727412.5
Maximum1757760
Range775680
Interquartile range (IQR)353437.5

Descriptive statistics

Standard deviation263857.21
Coefficient of variation (CV)0.18383793
Kurtosis-0.96231131
Mean1435270.8
Median Absolute Deviation (MAD)147330
Skewness-0.7012884
Sum37317040
Variance6.9620627 × 1010
MonotonicityNot monotonic
2023-12-13T03:35:51.208715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
982080 1
 
3.8%
1598960 1
 
3.8%
1609570 1
 
3.8%
1582130 1
 
3.8%
1584560 1
 
3.8%
1602110 1
 
3.8%
1635880 1
 
3.8%
1672220 1
 
3.8%
1712750 1
 
3.8%
1757760 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
982080 1
3.8%
987410 1
3.8%
991400 1
3.8%
1022850 1
3.8%
1037040 1
3.8%
1085710 1
3.8%
1262400 1
3.8%
1316260 1
3.8%
1377560 1
3.8%
1414450 1
3.8%
ValueCountFrequency (%)
1757760 1
3.8%
1732300 1
3.8%
1712750 1
3.8%
1700770 1
3.8%
1672220 1
3.8%
1663980 1
3.8%
1635880 1
3.8%
1609570 1
3.8%
1602110 1
3.8%
1598960 1
3.8%

장해연금 인원(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct24
Distinct (%)92.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean68.230769
Minimum10
Maximum110
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-13T03:35:51.395275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile14
Q137.5
median73
Q3102.75
95-th percentile107
Maximum110
Range100
Interquartile range (IQR)65.25

Descriptive statistics

Standard deviation35.279805
Coefficient of variation (CV)0.51706591
Kurtosis-1.4953751
Mean68.230769
Median Absolute Deviation (MAD)31.5
Skewness-0.30966477
Sum1774
Variance1244.6646
MonotonicityNot monotonic
2023-12-13T03:35:51.562456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
107 3
 
11.5%
10 1
 
3.8%
78 1
 
3.8%
110 1
 
3.8%
105 1
 
3.8%
106 1
 
3.8%
103 1
 
3.8%
102 1
 
3.8%
97 1
 
3.8%
93 1
 
3.8%
Other values (14) 14
53.8%
ValueCountFrequency (%)
10 1
3.8%
13 1
3.8%
17 1
3.8%
20 1
3.8%
27 1
3.8%
31 1
3.8%
36 1
3.8%
42 1
3.8%
44 1
3.8%
51 1
3.8%
ValueCountFrequency (%)
110 1
 
3.8%
107 3
11.5%
106 1
 
3.8%
105 1
 
3.8%
103 1
 
3.8%
102 1
 
3.8%
97 1
 
3.8%
93 1
 
3.8%
92 1
 
3.8%
88 1
 
3.8%

장해연금 평균 연금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1330816.5
Minimum934810
Maximum1470090
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-13T03:35:51.740732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum934810
5-th percentile1035615
Q11248465
median1407140
Q31431935
95-th percentile1468952.5
Maximum1470090
Range535280
Interquartile range (IQR)183470

Descriptive statistics

Standard deviation157707.56
Coefficient of variation (CV)0.11850436
Kurtosis0.37200549
Mean1330816.5
Median Absolute Deviation (MAD)43840
Skewness-1.2650817
Sum34601230
Variance2.4871673 × 1010
MonotonicityNot monotonic
2023-12-13T03:35:51.915124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
934810 1
 
3.8%
1420430 1
 
3.8%
1450390 1
 
3.8%
1427660 1
 
3.8%
1451570 1
 
3.8%
1418240 1
 
3.8%
1415050 1
 
3.8%
1423580 1
 
3.8%
1470090 1
 
3.8%
1469430 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
934810 1
3.8%
1029520 1
3.8%
1053900 1
3.8%
1095960 1
3.8%
1137630 1
3.8%
1199110 1
3.8%
1243480 1
3.8%
1263420 1
3.8%
1372080 1
3.8%
1376380 1
3.8%
ValueCountFrequency (%)
1470090 1
3.8%
1469430 1
3.8%
1467520 1
3.8%
1453730 1
3.8%
1451570 1
3.8%
1450390 1
3.8%
1433360 1
3.8%
1427660 1
3.8%
1423580 1
3.8%
1420430 1
3.8%

장해유족연금 인원(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct18
Distinct (%)69.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.423077
Minimum0
Maximum41
Zeros6
Zeros (%)23.1%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-13T03:35:52.101286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median10
Q319.75
95-th percentile39.75
Maximum41
Range41
Interquartile range (IQR)16.75

Descriptive statistics

Standard deviation12.946577
Coefficient of variation (CV)0.96450141
Kurtosis-0.11831614
Mean13.423077
Median Absolute Deviation (MAD)9.5
Skewness0.89981537
Sum349
Variance167.61385
MonotonicityIncreasing
2023-12-13T03:35:52.275206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 6
23.1%
41 2
 
7.7%
10 2
 
7.7%
3 2
 
7.7%
19 1
 
3.8%
36 1
 
3.8%
33 1
 
3.8%
24 1
 
3.8%
21 1
 
3.8%
20 1
 
3.8%
Other values (8) 8
30.8%
ValueCountFrequency (%)
0 6
23.1%
3 2
 
7.7%
5 1
 
3.8%
6 1
 
3.8%
8 1
 
3.8%
9 1
 
3.8%
10 2
 
7.7%
12 1
 
3.8%
13 1
 
3.8%
17 1
 
3.8%
ValueCountFrequency (%)
41 2
7.7%
36 1
3.8%
33 1
3.8%
24 1
3.8%
21 1
3.8%
20 1
3.8%
19 1
3.8%
18 1
3.8%
17 1
3.8%
13 1
3.8%

장해유족연금 평균 연금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct21
Distinct (%)80.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1117048.8
Minimum0
Maximum1782330
Zeros6
Zeros (%)23.1%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-13T03:35:52.460636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11174525
median1346000
Q31568870
95-th percentile1694362.5
Maximum1782330
Range1782330
Interquartile range (IQR)394345

Descriptive statistics

Standard deviation642810.74
Coefficient of variation (CV)0.57545446
Kurtosis-0.40398492
Mean1117048.8
Median Absolute Deviation (MAD)212110
Skewness-1.1420228
Sum29043270
Variance4.1320565 × 1011
MonotonicityNot monotonic
2023-12-13T03:35:52.649794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 6
23.1%
1720400 1
 
3.8%
1259590 1
 
3.8%
1175320 1
 
3.8%
1174260 1
 
3.8%
1269340 1
 
3.8%
1534800 1
 
3.8%
1607590 1
 
3.8%
1616250 1
 
3.8%
1615840 1
 
3.8%
Other values (11) 11
42.3%
ValueCountFrequency (%)
0 6
23.1%
1174260 1
 
3.8%
1175320 1
 
3.8%
1259590 1
 
3.8%
1269340 1
 
3.8%
1310810 1
 
3.8%
1336220 1
 
3.8%
1341510 1
 
3.8%
1350490 1
 
3.8%
1365180 1
 
3.8%
ValueCountFrequency (%)
1782330 1
3.8%
1720400 1
3.8%
1616250 1
3.8%
1615840 1
3.8%
1607590 1
3.8%
1583070 1
3.8%
1579630 1
3.8%
1536590 1
3.8%
1534800 1
3.8%
1480650 1
3.8%

연계퇴직연금 인원(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct15
Distinct (%)57.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean348.5
Minimum0
Maximum2143
Zeros12
Zeros (%)46.2%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-13T03:35:52.854510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median12.5
Q3476
95-th percentile1572.5
Maximum2143
Range2143
Interquartile range (IQR)476

Descriptive statistics

Standard deviation582.71525
Coefficient of variation (CV)1.6720667
Kurtosis3.0568038
Mean348.5
Median Absolute Deviation (MAD)12.5
Skewness1.9037169
Sum9061
Variance339557.06
MonotonicityIncreasing
2023-12-13T03:35:53.010201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 12
46.2%
7 1
 
3.8%
18 1
 
3.8%
42 1
 
3.8%
137 1
 
3.8%
154 1
 
3.8%
240 1
 
3.8%
371 1
 
3.8%
511 1
 
3.8%
684 1
 
3.8%
Other values (5) 5
19.2%
ValueCountFrequency (%)
0 12
46.2%
7 1
 
3.8%
18 1
 
3.8%
42 1
 
3.8%
137 1
 
3.8%
154 1
 
3.8%
240 1
 
3.8%
371 1
 
3.8%
511 1
 
3.8%
684 1
 
3.8%
ValueCountFrequency (%)
2143 1
3.8%
1661 1
3.8%
1307 1
3.8%
1001 1
3.8%
785 1
3.8%
684 1
3.8%
511 1
3.8%
371 1
3.8%
240 1
3.8%
154 1
3.8%

연계퇴직연금 평균연금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct15
Distinct (%)57.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean407550.38
Minimum0
Maximum1168730
Zeros12
Zeros (%)46.2%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-13T03:35:53.185664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median608305
Q3747102.5
95-th percentile807855
Maximum1168730
Range1168730
Interquartile range (IQR)747102.5

Descriptive statistics

Standard deviation397231.36
Coefficient of variation (CV)0.97468036
Kurtosis-1.6944114
Mean407550.38
Median Absolute Deviation (MAD)381480
Skewness0.069564813
Sum10596310
Variance1.5779275 × 1011
MonotonicityNot monotonic
2023-12-13T03:35:53.402493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 12
46.2%
1168730 1
 
3.8%
810840 1
 
3.8%
798900 1
 
3.8%
747190 1
 
3.8%
746840 1
 
3.8%
778320 1
 
3.8%
788340 1
 
3.8%
774020 1
 
3.8%
737940 1
 
3.8%
Other values (5) 5
19.2%
ValueCountFrequency (%)
0 12
46.2%
600450 1
 
3.8%
616160 1
 
3.8%
637420 1
 
3.8%
678720 1
 
3.8%
712440 1
 
3.8%
737940 1
 
3.8%
746840 1
 
3.8%
747190 1
 
3.8%
774020 1
 
3.8%
ValueCountFrequency (%)
1168730 1
3.8%
810840 1
3.8%
798900 1
3.8%
788340 1
3.8%
778320 1
3.8%
774020 1
3.8%
747190 1
3.8%
746840 1
3.8%
737940 1
3.8%
712440 1
3.8%

Interactions

2023-12-13T03:35:47.346353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:32.424725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:33.852511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:34.947695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:36.733540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:38.607534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:40.243779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:42.114990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:44.352284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:45.202080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:46.190286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:47.517265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:32.521056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:33.943023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:35.082603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:36.895198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:38.788315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:40.371135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:42.271652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:44.422237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:45.280748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:46.268490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:47.616381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:32.595740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:34.027738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:35.212391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:37.065847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:38.954682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:40.485164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:42.496355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:44.491176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:45.375265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:46.339324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:47.755935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:32.680756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:34.141935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:35.342783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:37.224142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:39.118653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:40.614019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:42.805012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:44.575496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:45.466022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:46.448749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:47.884814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:32.802333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:34.225768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:35.497340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:37.340058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:39.250658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:40.811866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:43.002252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:44.646126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:45.552770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:46.621649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:47.994275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:33.304104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:34.321183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:35.715413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:37.539429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:39.439561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:41.049326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:43.202473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:44.732182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:45.641279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:46.731571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:48.093243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:33.392857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:34.417087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:35.888037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:37.716967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:39.569278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:41.249691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:43.357959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:44.817376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:45.727823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:46.841736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:48.203987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:33.468940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:34.503824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:36.001488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:37.870583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:39.693564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:41.411705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:44.027169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:44.901289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:45.821612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:46.932198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:48.323757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:33.548653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:34.595873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:36.144574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:38.007411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:39.827167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:41.579252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:44.117862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:44.978501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:45.913071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:47.033324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:48.480256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:33.647817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:34.712759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:36.329673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:38.275041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:39.968470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:41.798304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:44.204971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:45.054484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:46.022017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:47.158137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:48.613632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:33.739568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:34.806221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:36.549847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:38.440653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:40.104002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:41.955486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:44.273746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:45.120278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:46.107338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:35:47.247119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T03:35:53.586443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도퇴직연금 인원(명)퇴직연금 평균 연금액유족연금 인원(명)유족연금 평균 연금액장해연금 인원(명)장해연금 평균 연금액장해유족연금 인원(명)장해유족연금 평균 연금액연계퇴직연금 인원(명)연계퇴직연금 평균연금액
연도1.0000.9770.9080.9140.8720.9560.6340.8700.9860.3240.904
퇴직연금 인원(명)0.9771.0000.9190.9610.7320.8360.0000.8880.9580.8430.868
퇴직연금 평균 연금액0.9080.9191.0000.7970.9250.9740.8340.7810.8880.0000.789
유족연금 인원(명)0.9140.9610.7971.0000.7210.7670.0000.9450.9540.9620.890
유족연금 평균 연금액0.8720.7320.9250.7211.0000.8530.8760.8420.7780.0000.772
장해연금 인원(명)0.9560.8360.9740.7670.8531.0000.7500.7110.8730.0000.780
장해연금 평균 연금액0.6340.0000.8340.0000.8760.7501.0000.0000.5970.0000.000
장해유족연금 인원(명)0.8700.8880.7810.9450.8420.7110.0001.0000.7240.9320.968
장해유족연금 평균 연금액0.9860.9580.8880.9540.7780.8730.5970.7241.0000.6080.629
연계퇴직연금 인원(명)0.3240.8430.0000.9620.0000.0000.0000.9320.6081.0000.854
연계퇴직연금 평균연금액0.9040.8680.7890.8900.7720.7800.0000.9680.6290.8541.000
2023-12-13T03:35:53.783334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도퇴직연금 인원(명)퇴직연금 평균 연금액유족연금 인원(명)유족연금 평균 연금액장해연금 인원(명)장해연금 평균 연금액장해유족연금 인원(명)장해유족연금 평균 연금액연계퇴직연금 인원(명)연계퇴직연금 평균연금액
연도1.0001.0000.9971.0000.8560.9950.8580.9930.3780.9500.634
퇴직연금 인원(명)1.0001.0000.9971.0000.8560.9950.8580.9930.3780.9500.634
퇴직연금 평균 연금액0.9970.9971.0000.9970.8530.9920.8540.9930.3780.9500.634
유족연금 인원(명)1.0001.0000.9971.0000.8560.9950.8580.9930.3780.9500.634
유족연금 평균 연금액0.8560.8560.8530.8561.0000.8670.9410.8470.6450.7980.788
장해연금 인원(명)0.9950.9950.9920.9950.8671.0000.8620.9880.4040.9450.640
장해연금 평균 연금액0.8580.8580.8540.8580.9410.8621.0000.8520.5460.7950.718
장해유족연금 인원(명)0.9930.9930.9930.9930.8470.9880.8521.0000.3790.9550.639
장해유족연금 평균 연금액0.3780.3780.3780.3780.6450.4040.5460.3791.0000.2580.510
연계퇴직연금 인원(명)0.9500.9500.9500.9500.7980.9450.7950.9550.2581.0000.667
연계퇴직연금 평균연금액0.6340.6340.6340.6340.7880.6400.7180.6390.5100.6671.000

Missing values

2023-12-13T03:35:48.780998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:35:48.992633image/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

연도퇴직연금 인원(명)퇴직연금 평균 연금액유족연금 인원(명)유족연금 평균 연금액장해연금 인원(명)장해연금 평균 연금액장해유족연금 인원(명)장해유족연금 평균 연금액연계퇴직연금 인원(명)연계퇴직연금 평균연금액
0199749971365170447982080109348100000
11998586313510005289874101310295200000
21999990813468006239914001710959600000
3200012626139872073410228502010539000000
4200113708144435090410370402711376300000
52002149241539660110410857103111991100000
62003165421803990131912624003612434803172040000
72004184441904880152813162604212634203178233000
82005204121999670174313775604413763805133622000
92006226382089270201114144505114190206131081000
연도퇴직연금 인원(명)퇴직연금 평균 연금액유족연금 인원(명)유족연금 평균 연금액장해연금 인원(명)장해연금 평균 연금액장해유족연금 인원(명)장해유족연금 평균 연금액연계퇴직연금 인원(명)연계퇴직연금 평균연금액
16201343697269291044351700770931453730171536590154746840
17201447782274930048841732300971467520181583070240778320
182015531702817210537417577601021469430191615840371788340
192016570842826720603917127501031470090201616250511774020
202017616922845480667216722201071423580211607590684737940
212018676072859260733716358801061415050241534800785712440
2220197383228737908139160211010514182403312693401001678720
2320208059428921318873158456010714515703611742601307637420
2420218727329355809571158213010714276604111753201661616160
25202294086299483010431160957011014503904112595902143600450