Overview

Dataset statistics

Number of variables9
Number of observations49
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.0 KiB
Average record size in memory83.7 B

Variable types

Numeric9

Dataset

Description퇴직사유(의원면직, 명예퇴직, 정년퇴직, 일반퇴직, 직권면직, 사망 등)별 퇴직자 수에 대한 데이터입니다. 1974년부터 2022년까지 연 단위로 구분됩니다.
URLhttps://www.data.go.kr/data/15053003/fileData.do

Alerts

연도 is highly overall correlated with 의원면직 and 4 other fieldsHigh correlation
의원면직 is highly overall correlated with 연도 and 5 other fieldsHigh correlation
명예퇴직 is highly overall correlated with 연도 and 4 other fieldsHigh correlation
정년퇴직 is highly overall correlated with 연도 and 4 other fieldsHigh correlation
일반퇴직 is highly overall correlated with 연도 and 5 other fieldsHigh correlation
직권면직 is highly overall correlated with 의원면직 and 2 other fieldsHigh correlation
사망 is highly overall correlated with 연도 and 5 other fieldsHigh correlation
연도 has unique valuesUnique
정년퇴직 has unique valuesUnique
당연퇴직 has unique valuesUnique
사망 has unique valuesUnique
기타 has unique valuesUnique
의원면직 has 9 (18.4%) zerosZeros
명예퇴직 has 22 (44.9%) zerosZeros
일반퇴직 has 40 (81.6%) zerosZeros
직권면직 has 1 (2.0%) zerosZeros

Reproduction

Analysis started2023-12-12 17:25:44.565626
Analysis finished2023-12-12 17:25:55.173829
Duration10.61 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1998
Minimum1974
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-13T02:25:55.290687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1974
5-th percentile1976.4
Q11986
median1998
Q32010
95-th percentile2019.6
Maximum2022
Range48
Interquartile range (IQR)24

Descriptive statistics

Standard deviation14.28869
Coefficient of variation (CV)0.0071514966
Kurtosis-1.2
Mean1998
Median Absolute Deviation (MAD)12
Skewness0
Sum97902
Variance204.16667
MonotonicityStrictly increasing
2023-12-13T02:25:55.654227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
1974 1
 
2.0%
2011 1
 
2.0%
2001 1
 
2.0%
2002 1
 
2.0%
2003 1
 
2.0%
2004 1
 
2.0%
2005 1
 
2.0%
2006 1
 
2.0%
2007 1
 
2.0%
2008 1
 
2.0%
Other values (39) 39
79.6%
ValueCountFrequency (%)
1974 1
2.0%
1975 1
2.0%
1976 1
2.0%
1977 1
2.0%
1978 1
2.0%
1979 1
2.0%
1980 1
2.0%
1981 1
2.0%
1982 1
2.0%
1983 1
2.0%
ValueCountFrequency (%)
2022 1
2.0%
2021 1
2.0%
2020 1
2.0%
2019 1
2.0%
2018 1
2.0%
2017 1
2.0%
2016 1
2.0%
2015 1
2.0%
2014 1
2.0%
2013 1
2.0%

의원면직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct41
Distinct (%)83.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13459.531
Minimum0
Maximum35398
Zeros9
Zeros (%)18.4%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-13T02:25:56.118127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15330
median15183
Q320704
95-th percentile30612
Maximum35398
Range35398
Interquartile range (IQR)15374

Descriptive statistics

Standard deviation10226.928
Coefficient of variation (CV)0.75982795
Kurtosis-0.8793018
Mean13459.531
Median Absolute Deviation (MAD)9359
Skewness0.29692611
Sum659517
Variance1.0459005 × 108
MonotonicityNot monotonic
2023-12-13T02:25:56.407360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
0 9
 
18.4%
21975 1
 
2.0%
5717 1
 
2.0%
13120 1
 
2.0%
13895 1
 
2.0%
17016 1
 
2.0%
15996 1
 
2.0%
11685 1
 
2.0%
9006 1
 
2.0%
7261 1
 
2.0%
Other values (31) 31
63.3%
ValueCountFrequency (%)
0 9
18.4%
4677 1
 
2.0%
4986 1
 
2.0%
5026 1
 
2.0%
5330 1
 
2.0%
5482 1
 
2.0%
5601 1
 
2.0%
5717 1
 
2.0%
5741 1
 
2.0%
5824 1
 
2.0%
ValueCountFrequency (%)
35398 1
2.0%
33498 1
2.0%
30862 1
2.0%
30237 1
2.0%
30161 1
2.0%
27985 1
2.0%
25086 1
2.0%
21975 1
2.0%
21902 1
2.0%
21481 1
2.0%

명예퇴직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct28
Distinct (%)57.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5495.8571
Minimum0
Maximum35409
Zeros22
Zeros (%)44.9%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-13T02:25:57.155327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3122
Q39863
95-th percentile16540.6
Maximum35409
Range35409
Interquartile range (IQR)9863

Descriptive statistics

Standard deviation7194.8705
Coefficient of variation (CV)1.3091444
Kurtosis4.9207254
Mean5495.8571
Median Absolute Deviation (MAD)3122
Skewness1.8633823
Sum269297
Variance51766161
MonotonicityNot monotonic
2023-12-13T02:25:57.360092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0 22
44.9%
6226 1
 
2.0%
13887 1
 
2.0%
12780 1
 
2.0%
12721 1
 
2.0%
10693 1
 
2.0%
10497 1
 
2.0%
9261 1
 
2.0%
10297 1
 
2.0%
15298 1
 
2.0%
Other values (18) 18
36.7%
ValueCountFrequency (%)
0 22
44.9%
2738 1
 
2.0%
2875 1
 
2.0%
3122 1
 
2.0%
3231 1
 
2.0%
3482 1
 
2.0%
3621 1
 
2.0%
3944 1
 
2.0%
5387 1
 
2.0%
6226 1
 
2.0%
ValueCountFrequency (%)
35409 1
2.0%
20342 1
2.0%
17369 1
2.0%
15298 1
2.0%
14816 1
2.0%
13887 1
2.0%
12780 1
2.0%
12721 1
2.0%
12381 1
2.0%
10693 1
2.0%

정년퇴직
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8407.8367
Minimum655
Maximum23870
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-13T02:25:57.656530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum655
5-th percentile1124.6
Q13440
median6537
Q312020
95-th percentile18553.6
Maximum23870
Range23215
Interquartile range (IQR)8580

Descriptive statistics

Standard deviation5928.3906
Coefficient of variation (CV)0.70510297
Kurtosis-0.44396726
Mean8407.8367
Median Absolute Deviation (MAD)4407
Skewness0.67107364
Sum411984
Variance35145816
MonotonicityNot monotonic
2023-12-13T02:25:57.964813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
1424 1
 
2.0%
6426 1
 
2.0%
7681 1
 
2.0%
6419 1
 
2.0%
9271 1
 
2.0%
11132 1
 
2.0%
9612 1
 
2.0%
13660 1
 
2.0%
11544 1
 
2.0%
11270 1
 
2.0%
Other values (39) 39
79.6%
ValueCountFrequency (%)
655 1
2.0%
822 1
2.0%
925 1
2.0%
1424 1
2.0%
1708 1
2.0%
2028 1
2.0%
2130 1
2.0%
2386 1
2.0%
2482 1
2.0%
3120 1
2.0%
ValueCountFrequency (%)
23870 1
2.0%
20180 1
2.0%
19338 1
2.0%
17377 1
2.0%
17261 1
2.0%
16362 1
2.0%
15871 1
2.0%
15823 1
2.0%
14839 1
2.0%
14452 1
2.0%

일반퇴직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct10
Distinct (%)20.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2199.0408
Minimum0
Maximum19595
Zeros40
Zeros (%)81.6%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-13T02:25:58.277546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile12540.2
Maximum19595
Range19595
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4918.7956
Coefficient of variation (CV)2.2367914
Kurtosis3.4684809
Mean2199.0408
Median Absolute Deviation (MAD)0
Skewness2.1113531
Sum107753
Variance24194550
MonotonicityNot monotonic
2023-12-13T02:25:58.536299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 40
81.6%
9892 1
 
2.0%
8609 1
 
2.0%
10448 1
 
2.0%
9167 1
 
2.0%
10037 1
 
2.0%
10350 1
 
2.0%
13935 1
 
2.0%
15720 1
 
2.0%
19595 1
 
2.0%
ValueCountFrequency (%)
0 40
81.6%
8609 1
 
2.0%
9167 1
 
2.0%
9892 1
 
2.0%
10037 1
 
2.0%
10350 1
 
2.0%
10448 1
 
2.0%
13935 1
 
2.0%
15720 1
 
2.0%
19595 1
 
2.0%
ValueCountFrequency (%)
19595 1
 
2.0%
15720 1
 
2.0%
13935 1
 
2.0%
10448 1
 
2.0%
10350 1
 
2.0%
10037 1
 
2.0%
9892 1
 
2.0%
9167 1
 
2.0%
8609 1
 
2.0%
0 40
81.6%

당연퇴직
Real number (ℝ)

UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1546.6939
Minimum84
Maximum5425
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-13T02:25:58.817143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum84
5-th percentile140.4
Q1216
median645
Q32942
95-th percentile4287.8
Maximum5425
Range5341
Interquartile range (IQR)2726

Descriptive statistics

Standard deviation1588.3627
Coefficient of variation (CV)1.0269406
Kurtosis-0.48818948
Mean1546.6939
Median Absolute Deviation (MAD)495
Skewness0.91458296
Sum75788
Variance2522896
MonotonicityNot monotonic
2023-12-13T02:25:59.042581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
175 1
 
2.0%
613 1
 
2.0%
2942 1
 
2.0%
2970 1
 
2.0%
3364 1
 
2.0%
5233 1
 
2.0%
3664 1
 
2.0%
5425 1
 
2.0%
4403 1
 
2.0%
1187 1
 
2.0%
Other values (39) 39
79.6%
ValueCountFrequency (%)
84 1
2.0%
130 1
2.0%
134 1
2.0%
150 1
2.0%
172 1
2.0%
175 1
2.0%
176 1
2.0%
186 1
2.0%
191 1
2.0%
192 1
2.0%
ValueCountFrequency (%)
5425 1
2.0%
5233 1
2.0%
4403 1
2.0%
4115 1
2.0%
4049 1
2.0%
3664 1
2.0%
3568 1
2.0%
3539 1
2.0%
3534 1
2.0%
3460 1
2.0%

직권면직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct46
Distinct (%)93.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1576.6939
Minimum0
Maximum16253
Zeros1
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-13T02:25:59.301761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.4
Q165
median276
Q31278
95-th percentile8667.6
Maximum16253
Range16253
Interquartile range (IQR)1213

Descriptive statistics

Standard deviation3366.8815
Coefficient of variation (CV)2.1354059
Kurtosis10.604717
Mean1576.6939
Median Absolute Deviation (MAD)271
Skewness3.253027
Sum77258
Variance11335891
MonotonicityNot monotonic
2023-12-13T02:25:59.517530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
61 2
 
4.1%
112 2
 
4.1%
5 2
 
4.1%
65 1
 
2.0%
121 1
 
2.0%
16253 1
 
2.0%
492 1
 
2.0%
111 1
 
2.0%
276 1
 
2.0%
11642 1
 
2.0%
Other values (36) 36
73.5%
ValueCountFrequency (%)
0 1
2.0%
1 1
2.0%
3 1
2.0%
4 1
2.0%
5 2
4.1%
6 1
2.0%
9 1
2.0%
28 1
2.0%
41 1
2.0%
61 2
4.1%
ValueCountFrequency (%)
16253 1
2.0%
13187 1
2.0%
11642 1
2.0%
4206 1
2.0%
4145 1
2.0%
3947 1
2.0%
3883 1
2.0%
3123 1
2.0%
1836 1
2.0%
1445 1
2.0%

사망
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1175.0612
Minimum653
Maximum2145
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-13T02:25:59.689440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum653
5-th percentile692.4
Q1837
median1142
Q31463
95-th percentile1772.2
Maximum2145
Range1492
Interquartile range (IQR)626

Descriptive statistics

Standard deviation389.15712
Coefficient of variation (CV)0.3311803
Kurtosis-0.85873103
Mean1175.0612
Median Absolute Deviation (MAD)312
Skewness0.48433291
Sum57578
Variance151443.27
MonotonicityNot monotonic
2023-12-13T02:25:59.908588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
1142 1
 
2.0%
875 1
 
2.0%
926 1
 
2.0%
966 1
 
2.0%
945 1
 
2.0%
916 1
 
2.0%
901 1
 
2.0%
844 1
 
2.0%
826 1
 
2.0%
858 1
 
2.0%
Other values (39) 39
79.6%
ValueCountFrequency (%)
653 1
2.0%
672 1
2.0%
680 1
2.0%
711 1
2.0%
729 1
2.0%
735 1
2.0%
748 1
2.0%
763 1
2.0%
826 1
2.0%
830 1
2.0%
ValueCountFrequency (%)
2145 1
2.0%
1813 1
2.0%
1783 1
2.0%
1756 1
2.0%
1745 1
2.0%
1725 1
2.0%
1708 1
2.0%
1704 1
2.0%
1565 1
2.0%
1558 1
2.0%

기타
Real number (ℝ)

UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1458.7959
Minimum191
Maximum6511
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-13T02:26:00.178000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum191
5-th percentile304
Q1409
median551
Q31627
95-th percentile5559.2
Maximum6511
Range6320
Interquartile range (IQR)1218

Descriptive statistics

Standard deviation1743.8232
Coefficient of variation (CV)1.1953853
Kurtosis1.6615937
Mean1458.7959
Median Absolute Deviation (MAD)218
Skewness1.7179149
Sum71481
Variance3040919.5
MonotonicityNot monotonic
2023-12-13T02:26:00.354173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
471 1
 
2.0%
5720 1
 
2.0%
396 1
 
2.0%
392 1
 
2.0%
325 1
 
2.0%
409 1
 
2.0%
488 1
 
2.0%
333 1
 
2.0%
1221 1
 
2.0%
5318 1
 
2.0%
Other values (39) 39
79.6%
ValueCountFrequency (%)
191 1
2.0%
278 1
2.0%
290 1
2.0%
325 1
2.0%
333 1
2.0%
382 1
2.0%
386 1
2.0%
389 1
2.0%
392 1
2.0%
396 1
2.0%
ValueCountFrequency (%)
6511 1
2.0%
5760 1
2.0%
5720 1
2.0%
5318 1
2.0%
4948 1
2.0%
4611 1
2.0%
4116 1
2.0%
3639 1
2.0%
2872 1
2.0%
2642 1
2.0%

Interactions

2023-12-13T02:25:53.565317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:44.819022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:45.829059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:47.138137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:48.229335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:49.249529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:50.656200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:51.605199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:52.568125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:53.666419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:44.910619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:45.952317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:47.253630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:48.345883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:49.359354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:50.778306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:51.703125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:52.656206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:53.772317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:45.027779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:46.098310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:47.378642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:48.441338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:49.501207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:50.893311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:51.808909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:52.775203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:53.881251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:45.141273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:46.241477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:47.501199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:48.548152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:49.949563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:51.011393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:51.934741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:52.880690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:53.987625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:45.248815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:46.428732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:47.599936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:48.654350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:50.048444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:51.112552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:52.046576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:52.989980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:54.104686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:45.374523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:46.589933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:47.717014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:48.773541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:50.169849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:51.212842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:52.163723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:53.101354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:54.213534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:45.464853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:46.736127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:47.829293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:48.879586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:50.270014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:51.294600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:52.254359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:53.215546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:54.363936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:45.600518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:46.895592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:47.973400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:49.004497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:50.406006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:51.405379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:52.361662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:53.326673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:54.512146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:45.718882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:47.033834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:48.103061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:49.151180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:50.533882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:51.517958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:52.468182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:25:53.465743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T02:26:00.505383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도의원면직명예퇴직정년퇴직일반퇴직당연퇴직직권면직사망기타
연도1.0000.9090.7180.8870.5520.7910.4410.8810.807
의원면직0.9091.0000.4970.6240.2630.5670.0000.7610.000
명예퇴직0.7180.4971.0000.8050.4790.3340.7670.6250.000
정년퇴직0.8870.6240.8051.0000.7590.6770.6180.7390.000
일반퇴직0.5520.2630.4790.7591.0000.0000.0000.3160.000
당연퇴직0.7910.5670.3340.6770.0001.0000.5380.4330.915
직권면직0.4410.0000.7670.6180.0000.5381.0000.6780.565
사망0.8810.7610.6250.7390.3160.4330.6781.0000.000
기타0.8070.0000.0000.0000.0000.9150.5650.0001.000
2023-12-13T02:26:00.685395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도의원면직명예퇴직정년퇴직일반퇴직당연퇴직직권면직사망기타
연도1.000-0.9290.8490.8970.6740.238-0.480-0.7470.050
의원면직-0.9291.000-0.814-0.836-0.668-0.1360.5750.783-0.038
명예퇴직0.849-0.8141.0000.8520.5820.200-0.407-0.7510.022
정년퇴직0.897-0.8360.8521.0000.6200.319-0.337-0.6180.027
일반퇴직0.674-0.6680.5820.6201.000-0.423-0.667-0.654-0.243
당연퇴직0.238-0.1360.2000.319-0.4231.0000.4980.1680.200
직권면직-0.4800.575-0.407-0.337-0.6670.4981.0000.7690.119
사망-0.7470.783-0.751-0.618-0.6540.1680.7691.0000.098
기타0.050-0.0380.0220.027-0.2430.2000.1190.0981.000

Missing values

2023-12-13T02:25:54.785074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:25:55.073074image/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

연도의원면직명예퇴직정년퇴직일반퇴직당연퇴직직권면직사망기타
0197421975014240175651142471
119751704501708084411198708
219761962202028013412311831201
3197720739024820150611228851
41978279850213001302481225543
5197930161082201762171309467
6198030862065501923411224551
7198135398092502233421399406
81982334980238605645001384512
919833023703159026410101458476
연도의원면직명예퇴직정년퇴직일반퇴직당연퇴직직권면직사망기타
3920135330986375270799618364948
402014017369144529892408287631098
4120150152981434986094809838757
42201601029715823104485365680609
432017092611726191671950729446
44201801049715871100371861711407
45201901069317377103501725653531
46202001272119338139352083672442
47202101278014839157202164735382
48202201388720180195951916748386