Overview

Dataset statistics

Number of variables10
Number of observations41
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.7 KiB
Average record size in memory93.2 B

Variable types

Numeric10

Dataset

Description퇴직사유(정년퇴직, 당연퇴직, 일반퇴직, 사망 등)별 퇴직자 추이에 대한 데이터입니다. 1982년부터 시작되며 연 단위로 구분됩니다.
URLhttps://www.data.go.kr/data/15054059/fileData.do

Alerts

구분 is highly overall correlated with 의원면직 and 5 other fieldsHigh correlation
is highly overall correlated with 명예퇴직 and 2 other fieldsHigh correlation
의원면직 is highly overall correlated with 구분 and 5 other fieldsHigh correlation
명예퇴직 is highly overall correlated with 구분 and 5 other fieldsHigh correlation
정년퇴직 is highly overall correlated with 구분 and 6 other fieldsHigh correlation
일반퇴직 is highly overall correlated with 구분 and 7 other fieldsHigh correlation
당연퇴직 is highly overall correlated with 일반퇴직High correlation
직권면직 is highly overall correlated with 구분 and 4 other fieldsHigh correlation
사망 is highly overall correlated with 구분 and 5 other fieldsHigh correlation
구분 has unique valuesUnique
has unique valuesUnique
정년퇴직 has unique valuesUnique
당연퇴직 has unique valuesUnique
사망 has unique valuesUnique
기타 has unique valuesUnique
의원면직 has 9 (22.0%) zerosZeros
명예퇴직 has 14 (34.1%) zerosZeros
일반퇴직 has 32 (78.0%) zerosZeros
직권면직 has 1 (2.4%) zerosZeros

Reproduction

Analysis started2023-12-12 14:40:39.596478
Analysis finished2023-12-12 14:40:50.288763
Duration10.69 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2002
Minimum1982
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T23:40:50.350586image/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 deviation11.979149
Coefficient of variation (CV)0.0059835907
Kurtosis-1.2
Mean2002
Median Absolute Deviation (MAD)10
Skewness0
Sum82082
Variance143.5
MonotonicityStrictly increasing
2023-12-12T23:40:50.485802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
1982 1
 
2.4%
2013 1
 
2.4%
2005 1
 
2.4%
2006 1
 
2.4%
2007 1
 
2.4%
2008 1
 
2.4%
2009 1
 
2.4%
2010 1
 
2.4%
2011 1
 
2.4%
2012 1
 
2.4%
Other values (31) 31
75.6%
ValueCountFrequency (%)
1982 1
2.4%
1983 1
2.4%
1984 1
2.4%
1985 1
2.4%
1986 1
2.4%
1987 1
2.4%
1988 1
2.4%
1989 1
2.4%
1990 1
2.4%
1991 1
2.4%
ValueCountFrequency (%)
2022 1
2.4%
2021 1
2.4%
2020 1
2.4%
2019 1
2.4%
2018 1
2.4%
2017 1
2.4%
2016 1
2.4%
2015 1
2.4%
2014 1
2.4%
2013 1
2.4%


Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36509.317
Minimum23095
Maximum94797
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T23:40:50.640494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum23095
5-th percentile24496
Q128820
median34757
Q338844
95-th percentile54993
Maximum94797
Range71702
Interquartile range (IQR)10024

Descriptive statistics

Standard deviation12973.485
Coefficient of variation (CV)0.35534725
Kurtosis9.6518802
Mean36509.317
Median Absolute Deviation (MAD)5393
Skewness2.6326078
Sum1496882
Variance1.6831132 × 108
MonotonicityNot monotonic
2023-12-12T23:40:51.037616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
38844 1
 
2.4%
29364 1
 
2.4%
34757 1
 
2.4%
30021 1
 
2.4%
30909 1
 
2.4%
36934 1
 
2.4%
24280 1
 
2.4%
30035 1
 
2.4%
26163 1
 
2.4%
35408 1
 
2.4%
Other values (31) 31
75.6%
ValueCountFrequency (%)
23095 1
2.4%
24280 1
2.4%
24496 1
2.4%
24651 1
2.4%
24899 1
2.4%
25589 1
2.4%
26163 1
2.4%
27129 1
2.4%
27384 1
2.4%
27866 1
2.4%
ValueCountFrequency (%)
94797 1
2.4%
64345 1
2.4%
54993 1
2.4%
54900 1
2.4%
47319 1
2.4%
44676 1
2.4%
44010 1
2.4%
42907 1
2.4%
40340 1
2.4%
39781 1
2.4%

의원면직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct33
Distinct (%)80.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11115.317
Minimum0
Maximum33498
Zeros9
Zeros (%)22.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T23:40:51.162766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14986
median9006
Q317889
95-th percentile25086
Maximum33498
Range33498
Interquartile range (IQR)12903

Descriptive statistics

Standard deviation9144.176
Coefficient of variation (CV)0.82266443
Kurtosis-0.59312399
Mean11115.317
Median Absolute Deviation (MAD)8010
Skewness0.47560045
Sum455728
Variance83615954
MonotonicityNot monotonic
2023-12-12T23:40:51.294380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
0 9
 
22.0%
33498 1
 
2.4%
5482 1
 
2.4%
11685 1
 
2.4%
9006 1
 
2.4%
7261 1
 
2.4%
6296 1
 
2.4%
5715 1
 
2.4%
5741 1
 
2.4%
5824 1
 
2.4%
Other values (23) 23
56.1%
ValueCountFrequency (%)
0 9
22.0%
4677 1
 
2.4%
4986 1
 
2.4%
5026 1
 
2.4%
5330 1
 
2.4%
5482 1
 
2.4%
5601 1
 
2.4%
5715 1
 
2.4%
5741 1
 
2.4%
5824 1
 
2.4%
ValueCountFrequency (%)
33498 1
2.4%
30237 1
2.4%
25086 1
2.4%
21902 1
2.4%
21481 1
2.4%
21372 1
2.4%
20704 1
2.4%
20681 1
2.4%
19342 1
2.4%
18168 1
2.4%

명예퇴직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct28
Distinct (%)68.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6568.2195
Minimum0
Maximum35409
Zeros14
Zeros (%)34.1%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T23:40:51.407473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3944
Q310497
95-th percentile17369
Maximum35409
Range35409
Interquartile range (IQR)10497

Descriptive statistics

Standard deviation7409.4395
Coefficient of variation (CV)1.1280743
Kurtosis4.3431112
Mean6568.2195
Median Absolute Deviation (MAD)3944
Skewness1.6905925
Sum269297
Variance54899794
MonotonicityNot monotonic
2023-12-12T23:40:51.543491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0 14
34.1%
6226 1
 
2.4%
13887 1
 
2.4%
12780 1
 
2.4%
12721 1
 
2.4%
10693 1
 
2.4%
10497 1
 
2.4%
9261 1
 
2.4%
10297 1
 
2.4%
15298 1
 
2.4%
Other values (18) 18
43.9%
ValueCountFrequency (%)
0 14
34.1%
2738 1
 
2.4%
2875 1
 
2.4%
3122 1
 
2.4%
3231 1
 
2.4%
3482 1
 
2.4%
3621 1
 
2.4%
3944 1
 
2.4%
5387 1
 
2.4%
6226 1
 
2.4%
ValueCountFrequency (%)
35409 1
2.4%
20342 1
2.4%
17369 1
2.4%
15298 1
2.4%
14816 1
2.4%
13887 1
2.4%
12780 1
2.4%
12721 1
2.4%
12381 1
2.4%
10693 1
2.4%

정년퇴직
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9751.4634
Minimum2386
Maximum23870
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T23:40:51.663666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2386
5-th percentile3159
Q15040
median8050
Q314349
95-th percentile19338
Maximum23870
Range21484
Interquartile range (IQR)9309

Descriptive statistics

Standard deviation5546.2721
Coefficient of variation (CV)0.56876306
Kurtosis-0.47951608
Mean9751.4634
Median Absolute Deviation (MAD)3714
Skewness0.6248832
Sum399810
Variance30761135
MonotonicityNot monotonic
2023-12-12T23:40:51.769750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
2386 1
 
2.4%
7527 1
 
2.4%
9612 1
 
2.4%
13660 1
 
2.4%
11544 1
 
2.4%
11270 1
 
2.4%
6246 1
 
2.4%
11055 1
 
2.4%
6426 1
 
2.4%
12020 1
 
2.4%
Other values (31) 31
75.6%
ValueCountFrequency (%)
2386 1
2.4%
3120 1
2.4%
3159 1
2.4%
3310 1
2.4%
3440 1
2.4%
3576 1
2.4%
3625 1
2.4%
4336 1
2.4%
4355 1
2.4%
4771 1
2.4%
ValueCountFrequency (%)
23870 1
2.4%
20180 1
2.4%
19338 1
2.4%
17377 1
2.4%
17261 1
2.4%
16362 1
2.4%
15871 1
2.4%
15823 1
2.4%
14839 1
2.4%
14452 1
2.4%

일반퇴직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct10
Distinct (%)24.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2628.122
Minimum0
Maximum19595
Zeros32
Zeros (%)78.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T23:40:51.869232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile13935
Maximum19595
Range19595
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5279.9234
Coefficient of variation (CV)2.00901
Kurtosis2.2302526
Mean2628.122
Median Absolute Deviation (MAD)0
Skewness1.8239592
Sum107753
Variance27877591
MonotonicityNot monotonic
2023-12-12T23:40:51.969263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 32
78.0%
9892 1
 
2.4%
8609 1
 
2.4%
10448 1
 
2.4%
9167 1
 
2.4%
10037 1
 
2.4%
10350 1
 
2.4%
13935 1
 
2.4%
15720 1
 
2.4%
19595 1
 
2.4%
ValueCountFrequency (%)
0 32
78.0%
8609 1
 
2.4%
9167 1
 
2.4%
9892 1
 
2.4%
10037 1
 
2.4%
10350 1
 
2.4%
10448 1
 
2.4%
13935 1
 
2.4%
15720 1
 
2.4%
19595 1
 
2.4%
ValueCountFrequency (%)
19595 1
 
2.4%
15720 1
 
2.4%
13935 1
 
2.4%
10448 1
 
2.4%
10350 1
 
2.4%
10037 1
 
2.4%
9892 1
 
2.4%
9167 1
 
2.4%
8609 1
 
2.4%
0 32
78.0%

당연퇴직
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1817.4146
Minimum172
Maximum5425
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T23:40:52.097779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum172
5-th percentile191
Q1536
median1187
Q33364
95-th percentile4403
Maximum5425
Range5253
Interquartile range (IQR)2828

Descriptive statistics

Standard deviation1601.6493
Coefficient of variation (CV)0.88127898
Kurtosis-0.85523299
Mean1817.4146
Median Absolute Deviation (MAD)979
Skewness0.67762215
Sum74514
Variance2565280.5
MonotonicityNot monotonic
2023-12-12T23:40:52.235210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
564 1
 
2.4%
799 1
 
2.4%
3654 1
 
2.4%
5425 1
 
2.4%
4403 1
 
2.4%
1187 1
 
2.4%
1836 1
 
2.4%
1591 1
 
2.4%
613 1
 
2.4%
3534 1
 
2.4%
Other values (31) 31
75.6%
ValueCountFrequency (%)
172 1
2.4%
186 1
2.4%
191 1
2.4%
195 1
2.4%
208 1
2.4%
216 1
2.4%
245 1
2.4%
264 1
2.4%
408 1
2.4%
480 1
2.4%
ValueCountFrequency (%)
5425 1
2.4%
5233 1
2.4%
4403 1
2.4%
4115 1
2.4%
4049 1
2.4%
3654 1
2.4%
3568 1
2.4%
3539 1
2.4%
3534 1
2.4%
3460 1
2.4%

직권면직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct39
Distinct (%)95.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1849.4634
Minimum0
Maximum16253
Zeros1
Zeros (%)2.4%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T23:40:52.349024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q174
median492
Q31381
95-th percentile11650
Maximum16253
Range16253
Interquartile range (IQR)1307

Descriptive statistics

Standard deviation3624.6158
Coefficient of variation (CV)1.9598202
Kurtosis8.3897993
Mean1849.4634
Median Absolute Deviation (MAD)487
Skewness2.9307405
Sum75828
Variance13137840
MonotonicityNot monotonic
2023-12-12T23:40:52.479180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
112 2
 
4.9%
5 2
 
4.9%
146 1
 
2.4%
276 1
 
2.4%
11650 1
 
2.4%
74 1
 
2.4%
96 1
 
2.4%
164 1
 
2.4%
121 1
 
2.4%
298 1
 
2.4%
Other values (29) 29
70.7%
ValueCountFrequency (%)
0 1
2.4%
1 1
2.4%
3 1
2.4%
4 1
2.4%
5 2
4.9%
6 1
2.4%
9 1
2.4%
28 1
2.4%
61 1
2.4%
74 1
2.4%
ValueCountFrequency (%)
16253 1
2.4%
13187 1
2.4%
11650 1
2.4%
4206 1
2.4%
4145 1
2.4%
3947 1
2.4%
3883 1
2.4%
3123 1
2.4%
1836 1
2.4%
1445 1
2.4%

사망
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1162.6829
Minimum653
Maximum2145
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T23:40:52.592351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum653
5-th percentile680
Q1835
median945
Q31520
95-th percentile1783
Maximum2145
Range1492
Interquartile range (IQR)685

Descriptive statistics

Standard deviation423.83761
Coefficient of variation (CV)0.36453413
Kurtosis-1.132698
Mean1162.6829
Median Absolute Deviation (MAD)234
Skewness0.54095517
Sum47670
Variance179638.32
MonotonicityNot monotonic
2023-12-12T23:40:52.711973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
1384 1
 
2.4%
836 1
 
2.4%
901 1
 
2.4%
844 1
 
2.4%
826 1
 
2.4%
858 1
 
2.4%
835 1
 
2.4%
830 1
 
2.4%
875 1
 
2.4%
837 1
 
2.4%
Other values (31) 31
75.6%
ValueCountFrequency (%)
653 1
2.4%
672 1
2.4%
680 1
2.4%
711 1
2.4%
729 1
2.4%
735 1
2.4%
748 1
2.4%
763 1
2.4%
826 1
2.4%
830 1
2.4%
ValueCountFrequency (%)
2145 1
2.4%
1813 1
2.4%
1783 1
2.4%
1756 1
2.4%
1745 1
2.4%
1725 1
2.4%
1708 1
2.4%
1704 1
2.4%
1565 1
2.4%
1558 1
2.4%

기타
Real number (ℝ)

UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1616.6341
Minimum191
Maximum6511
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T23:40:52.839980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum191
5-th percentile290
Q1407
median609
Q31893
95-th percentile5720
Maximum6511
Range6320
Interquartile range (IQR)1486

Descriptive statistics

Standard deviation1865.5731
Coefficient of variation (CV)1.153986
Kurtosis0.72006738
Mean1616.6341
Median Absolute Deviation (MAD)256
Skewness1.4516576
Sum66282
Variance3480363.1
MonotonicityNot monotonic
2023-12-12T23:40:52.977443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
512 1
 
2.4%
4948 1
 
2.4%
487 1
 
2.4%
333 1
 
2.4%
1221 1
 
2.4%
5318 1
 
2.4%
4116 1
 
2.4%
4611 1
 
2.4%
5720 1
 
2.4%
5760 1
 
2.4%
Other values (31) 31
75.6%
ValueCountFrequency (%)
191 1
2.4%
278 1
2.4%
290 1
2.4%
325 1
2.4%
333 1
2.4%
382 1
2.4%
386 1
2.4%
389 1
2.4%
392 1
2.4%
396 1
2.4%
ValueCountFrequency (%)
6511 1
2.4%
5760 1
2.4%
5720 1
2.4%
5318 1
2.4%
4948 1
2.4%
4611 1
2.4%
4116 1
2.4%
3639 1
2.4%
2872 1
2.4%
2642 1
2.4%

Interactions

2023-12-12T23:40:49.253740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:39.883417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:41.204709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:42.033930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:43.145154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:44.306760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:45.336733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:46.706589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:47.608409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:48.418256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:49.337365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:40.349071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:41.295843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:42.131394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:43.272009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:44.418029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:45.456944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:46.803484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:47.708262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:48.502000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:49.423003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:40.451186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:41.377652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:42.273854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:43.394364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:44.530041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:45.565640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:46.883762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:47.790818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:48.575710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:49.502687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:40.541623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:41.449916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:42.375298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:43.503931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:44.628191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:45.689193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:46.976436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:47.868684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:48.656852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:49.579749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:40.641521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:41.527125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:42.491841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:43.622339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:44.724570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:45.800335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:47.060422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:47.946841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:48.729945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:49.649372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:40.726189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:41.598093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:42.579165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:43.724712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:44.810749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:45.907950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:47.140745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:48.012405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:48.794464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:49.739976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:40.844044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:41.683176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:42.700499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:43.850007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:44.918201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:46.021906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:47.244294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:48.097514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:48.882113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:49.820849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:40.931555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:41.767565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:42.802035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:43.952393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:45.020538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:46.424746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:47.336138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:48.174740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:48.980303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:49.921804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:41.035573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:41.846584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:42.932621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:44.077702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:45.128263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:46.519137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:47.425315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:48.258320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:49.076300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:50.006309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:41.124881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:41.949027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:43.057460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:44.215906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:45.245881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:46.626131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:47.521937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:48.345150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:40:49.170796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:40:53.072156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분의원면직명예퇴직정년퇴직일반퇴직당연퇴직직권면직사망기타
구분1.0000.6680.7900.7560.8470.5770.7870.2680.8230.784
0.6681.0000.3540.9470.7890.7430.0000.7570.6660.000
의원면직0.7900.3541.0000.4570.4730.1560.5250.2720.7600.000
명예퇴직0.7560.9470.4571.0000.7320.4090.2800.7650.5930.000
정년퇴직0.8470.7890.4730.7321.0000.8610.0000.6570.5320.000
일반퇴직0.5770.7430.1560.4090.8611.0000.0000.0000.2200.000
당연퇴직0.7870.0000.5250.2800.0000.0001.0000.3060.0000.879
직권면직0.2680.7570.2720.7650.6570.0000.3061.0000.6100.531
사망0.8230.6660.7600.5930.5320.2200.0000.6101.0000.000
기타0.7840.0000.0000.0000.0000.0000.8790.5310.0001.000
2023-12-12T23:40:53.184885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분의원면직명예퇴직정년퇴직일반퇴직당연퇴직직권면직사망기타
구분1.0000.361-0.9530.8060.8360.722-0.223-0.775-0.8760.055
0.3611.000-0.2110.5790.5720.555-0.225-0.101-0.3030.047
의원면직-0.953-0.2111.000-0.751-0.773-0.7140.2640.7820.8770.012
명예퇴직0.8060.579-0.7511.0000.8160.574-0.106-0.496-0.7430.018
정년퇴직0.8360.572-0.7730.8161.0000.650-0.064-0.550-0.708-0.008
일반퇴직0.7220.555-0.7140.5740.6501.000-0.685-0.711-0.694-0.262
당연퇴직-0.223-0.2250.264-0.106-0.064-0.6851.0000.4830.3550.233
직권면직-0.775-0.1010.782-0.496-0.550-0.7110.4831.0000.8070.122
사망-0.876-0.3030.877-0.743-0.708-0.6940.3550.8071.0000.102
기타0.0550.0470.0120.018-0.008-0.2620.2330.1220.1021.000

Missing values

2023-12-12T23:40:50.121988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:40:50.239949image/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

구분의원면직명예퇴직정년퇴직일반퇴직당연퇴직직권면직사망기타
0198238844334980238605645001384512
11983366043023703159026410101458476
21984347682508603440024541451463389
31985288202148103625058114451398290
4198624651181680331005877501558278
51987255891636903120064131232145191
619882712915839035760140138831565865
71989244961532004355064598615201670
81990278661788905040065487515151893
919913081120704047710686129817251627
구분의원면직명예퇴직정년퇴직일반퇴직당연퇴직직권면직사망기타
312013293645330986375270799618364948
32201444010017369144529892408287631098
332015403400152981434986094809838757
3420163839801029715823104485365680609
35201737059092611726191671950729446
3620183771001049715871100371861711407
3720193978101069317377103501725653531
3820204731901272119338139352083672442
3920214467601278014839157202164735382
4020225499301388720180195951916748386