Overview

Dataset statistics

Number of variables8
Number of observations49
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.5 KiB
Average record size in memory73.7 B

Variable types

Text1
Numeric7

Dataset

Description공무원 연령별, 퇴직사유별(의원면직,명예퇴직,정년퇴직,일반퇴직, 직권면직 등) 퇴직연금수급자 현황 데이터입니다. 38세 미만부터 시작되며 연령별로 구분됩니다.
URLhttps://www.data.go.kr/data/15052977/fileData.do

Alerts

계 is highly overall correlated with 명예퇴직 and 5 other fieldsHigh correlation
명예퇴직 is highly overall correlated with 계 and 5 other fieldsHigh correlation
정년퇴직 is highly overall correlated with 계 and 4 other fieldsHigh correlation
일반퇴직 is highly overall correlated with 계 and 5 other fieldsHigh correlation
당연퇴직 is highly overall correlated with 계 and 5 other fieldsHigh correlation
직권면직 is highly overall correlated with 계 and 4 other fieldsHigh correlation
기타 is highly overall correlated with 계 and 3 other fieldsHigh correlation
구분 has unique valuesUnique
계 has unique valuesUnique
일반퇴직 has unique valuesUnique
기타 has unique valuesUnique
명예퇴직 has 4 (8.2%) zerosZeros
정년퇴직 has 12 (24.5%) zerosZeros
당연퇴직 has 1 (2.0%) zerosZeros
직권면직 has 15 (30.6%) zerosZeros

Reproduction

Analysis started2023-12-12 12:23:48.073100
Analysis finished2023-12-12 12:23:54.004886
Duration5.93 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Text

UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size524.0 B
2023-12-12T21:23:54.187565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.1836735
Min length3

Characters and Unicode

Total characters156
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)100.0%

Sample

1st row38세 미만
2nd row38세 이상
3rd row39세
4th row40세
5th row41세
ValueCountFrequency (%)
38세 2
 
3.8%
이상 2
 
3.8%
74세 1
 
1.9%
64세 1
 
1.9%
65세 1
 
1.9%
66세 1
 
1.9%
67세 1
 
1.9%
68세 1
 
1.9%
69세 1
 
1.9%
70세 1
 
1.9%
Other values (40) 40
76.9%
2023-12-12T21:23:54.597739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
세 49
31.4%
4 15
 
9.6%
5 15
 
9.6%
6 14
 
9.0%
7 14
 
9.0%
8 12
 
7.7%
3 8
 
5.1%
9 5
 
3.2%
0 5
 
3.2%
1 5
 
3.2%
Other values (6) 14
 
9.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 98
62.8%
Other Letter 55
35.3%
Space Separator 3
 
1.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 15
15.3%
5 15
15.3%
6 14
14.3%
7 14
14.3%
8 12
12.2%
3 8
8.2%
9 5
 
5.1%
0 5
 
5.1%
1 5
 
5.1%
2 5
 
5.1%
Other Letter
ValueCountFrequency (%)
세 49
89.1%
이 2
 
3.6%
상 2
 
3.6%
미 1
 
1.8%
만 1
 
1.8%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 101
64.7%
Hangul 55
35.3%

Most frequent character per script

Common
ValueCountFrequency (%)
4 15
14.9%
5 15
14.9%
6 14
13.9%
7 14
13.9%
8 12
11.9%
3 8
7.9%
9 5
 
5.0%
0 5
 
5.0%
1 5
 
5.0%
2 5
 
5.0%
Hangul
ValueCountFrequency (%)
세 49
89.1%
이 2
 
3.6%
상 2
 
3.6%
미 1
 
1.8%
만 1
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 101
64.7%
Hangul 55
35.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
세 49
89.1%
이 2
 
3.6%
상 2
 
3.6%
미 1
 
1.8%
만 1
 
1.8%
ASCII
ValueCountFrequency (%)
4 15
14.9%
5 15
14.9%
6 14
13.9%
7 14
13.9%
8 12
11.9%
3 8
7.9%
9 5
 
5.0%
0 5
 
5.0%
1 5
 
5.0%
2 5
 
5.0%

계
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11143.061
Minimum104
Maximum32004
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-12T21:23:54.767503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum104
5-th percentile216.8
Q11522
median8525
Q316919
95-th percentile30099.2
Maximum32004
Range31900
Interquartile range (IQR)15397

Descriptive statistics

Standard deviation10453.176
Coefficient of variation (CV)0.93808839
Kurtosis-0.88973665
Mean11143.061
Median Absolute Deviation (MAD)7656
Skewness0.67710385
Sum546010
Variance1.092689 × 108
MonotonicityNot monotonic
2023-12-12T21:23:54.921959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
139 1
 
2.0%
15925 1
 
2.0%
28669 1
 
2.0%
30056 1
 
2.0%
28256 1
 
2.0%
28376 1
 
2.0%
23383 1
 
2.0%
20472 1
 
2.0%
22338 1
 
2.0%
16156 1
 
2.0%
Other values (39) 39
79.6%
ValueCountFrequency (%)
104 1
2.0%
139 1
2.0%
180 1
2.0%
272 1
2.0%
359 1
2.0%
436 1
2.0%
482 1
2.0%
509 1
2.0%
589 1
2.0%
710 1
2.0%
ValueCountFrequency (%)
32004 1
2.0%
30632 1
2.0%
30128 1
2.0%
30056 1
2.0%
28669 1
2.0%
28376 1
2.0%
28256 1
2.0%
25621 1
2.0%
23383 1
2.0%
22858 1
2.0%

명예퇴직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct45
Distinct (%)91.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4325.8571
Minimum0
Maximum12287
Zeros4
Zeros (%)8.2%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-12T21:23:55.084389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1420
median3314
Q37316
95-th percentile11576.2
Maximum12287
Range12287
Interquartile range (IQR)6896

Descriptive statistics

Standard deviation4076.8343
Coefficient of variation (CV)0.94243387
Kurtosis-0.81116436
Mean4325.8571
Median Absolute Deviation (MAD)3012
Skewness0.69534083
Sum211967
Variance16620578
MonotonicityNot monotonic
2023-12-12T21:23:55.282486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
0 4
 
8.2%
6 2
 
4.1%
4378 1
 
2.0%
11432 1
 
2.0%
11807 1
 
2.0%
8557 1
 
2.0%
7316 1
 
2.0%
7605 1
 
2.0%
4834 1
 
2.0%
5223 1
 
2.0%
Other values (35) 35
71.4%
ValueCountFrequency (%)
0 4
8.2%
6 2
4.1%
38 1
 
2.0%
62 1
 
2.0%
92 1
 
2.0%
153 1
 
2.0%
198 1
 
2.0%
302 1
 
2.0%
420 1
 
2.0%
629 1
 
2.0%
ValueCountFrequency (%)
12287 1
2.0%
11807 1
2.0%
11589 1
2.0%
11557 1
2.0%
11532 1
2.0%
11432 1
2.0%
10926 1
2.0%
10797 1
2.0%
9720 1
2.0%
8557 1
2.0%

정년퇴직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct38
Distinct (%)77.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5515.1429
Minimum0
Maximum17908
Zeros12
Zeros (%)24.5%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-12T21:23:55.452219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3401
Q310119
95-th percentile16146.2
Maximum17908
Range17908
Interquartile range (IQR)10118

Descriptive statistics

Standard deviation6214.2913
Coefficient of variation (CV)1.1267689
Kurtosis-1.1436013
Mean5515.1429
Median Absolute Deviation (MAD)3401
Skewness0.62921318
Sum270242
Variance38617417
MonotonicityNot monotonic
2023-12-12T21:23:55.633318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
0 12
24.5%
6489 1
 
2.0%
12839 1
 
2.0%
9905 1
 
2.0%
10119 1
 
2.0%
9959 1
 
2.0%
9712 1
 
2.0%
9686 1
 
2.0%
8068 1
 
2.0%
6166 1
 
2.0%
Other values (28) 28
57.1%
ValueCountFrequency (%)
0 12
24.5%
1 1
 
2.0%
2 1
 
2.0%
5 1
 
2.0%
10 1
 
2.0%
11 1
 
2.0%
25 1
 
2.0%
42 1
 
2.0%
56 1
 
2.0%
120 1
 
2.0%
ValueCountFrequency (%)
17908 1
2.0%
17531 1
2.0%
16377 1
2.0%
15800 1
2.0%
15477 1
2.0%
14632 1
2.0%
14604 1
2.0%
13964 1
2.0%
12839 1
2.0%
12838 1
2.0%

일반퇴직
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean714.44898
Minimum101
Maximum2642
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-12T21:23:55.832284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile212.8
Q1502
median625
Q3928
95-th percentile1106.8
Maximum2642
Range2541
Interquartile range (IQR)426

Descriptive statistics

Standard deviation385.44904
Coefficient of variation (CV)0.53950534
Kurtosis12.216301
Mean714.44898
Median Absolute Deviation (MAD)169
Skewness2.5383538
Sum35008
Variance148570.96
MonotonicityNot monotonic
2023-12-12T21:23:56.015189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
134 1
 
2.0%
769 1
 
2.0%
980 1
 
2.0%
1066 1
 
2.0%
1134 1
 
2.0%
1224 1
 
2.0%
1033 1
 
2.0%
960 1
 
2.0%
1058 1
 
2.0%
728 1
 
2.0%
Other values (39) 39
79.6%
ValueCountFrequency (%)
101 1
2.0%
134 1
2.0%
178 1
2.0%
265 1
2.0%
345 1
2.0%
411 1
2.0%
416 1
2.0%
457 1
2.0%
459 1
2.0%
470 1
2.0%
ValueCountFrequency (%)
2642 1
2.0%
1224 1
2.0%
1134 1
2.0%
1066 1
2.0%
1058 1
2.0%
1033 1
2.0%
993 1
2.0%
980 1
2.0%
960 1
2.0%
956 1
2.0%

당연퇴직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct44
Distinct (%)89.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean122.53061
Minimum0
Maximum526
Zeros1
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-12T21:23:56.211794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.4
Q114
median120
Q3193
95-th percentile245.6
Maximum526
Range526
Interquartile range (IQR)179

Descriptive statistics

Standard deviation104.86521
Coefficient of variation (CV)0.85582867
Kurtosis2.840661
Mean122.53061
Median Absolute Deviation (MAD)86
Skewness1.0613138
Sum6004
Variance10996.713
MonotonicityNot monotonic
2023-12-12T21:23:56.423677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
3 3
 
6.1%
2 2
 
4.1%
1 2
 
4.1%
120 2
 
4.1%
0 1
 
2.0%
155 1
 
2.0%
242 1
 
2.0%
186 1
 
2.0%
116 1
 
2.0%
93 1
 
2.0%
Other values (34) 34
69.4%
ValueCountFrequency (%)
0 1
 
2.0%
1 2
4.1%
2 2
4.1%
3 3
6.1%
4 1
 
2.0%
5 1
 
2.0%
6 1
 
2.0%
10 1
 
2.0%
14 1
 
2.0%
21 1
 
2.0%
ValueCountFrequency (%)
526 1
2.0%
262 1
2.0%
248 1
2.0%
242 1
2.0%
233 1
2.0%
232 1
2.0%
228 1
2.0%
223 1
2.0%
208 1
2.0%
207 1
2.0%

직권면직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct33
Distinct (%)67.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean246
Minimum0
Maximum901
Zeros15
Zeros (%)30.6%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-12T21:23:56.589328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median145
Q3539
95-th percentile651.6
Maximum901
Range901
Interquartile range (IQR)539

Descriptive statistics

Standard deviation269.70447
Coefficient of variation (CV)1.0963596
Kurtosis-1.0398983
Mean246
Median Absolute Deviation (MAD)145
Skewness0.67291704
Sum12054
Variance72740.5
MonotonicityNot monotonic
2023-12-12T21:23:56.749351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
0 15
30.6%
1 2
 
4.1%
89 2
 
4.1%
201 1
 
2.0%
199 1
 
2.0%
145 1
 
2.0%
156 1
 
2.0%
165 1
 
2.0%
590 1
 
2.0%
62 1
 
2.0%
Other values (23) 23
46.9%
ValueCountFrequency (%)
0 15
30.6%
1 2
 
4.1%
6 1
 
2.0%
33 1
 
2.0%
62 1
 
2.0%
79 1
 
2.0%
89 2
 
4.1%
116 1
 
2.0%
145 1
 
2.0%
156 1
 
2.0%
ValueCountFrequency (%)
901 1
2.0%
671 1
2.0%
654 1
2.0%
648 1
2.0%
642 1
2.0%
619 1
2.0%
607 1
2.0%
603 1
2.0%
590 1
2.0%
580 1
2.0%

기타
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean219.08163
Minimum1
Maximum755
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-12T21:23:56.945117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.4
Q121
median111
Q3457
95-th percentile688
Maximum755
Range754
Interquartile range (IQR)436

Descriptive statistics

Standard deviation246.32438
Coefficient of variation (CV)1.1243498
Kurtosis-0.69724483
Mean219.08163
Median Absolute Deviation (MAD)103
Skewness0.91397038
Sum10735
Variance60675.702
MonotonicityNot monotonic
2023-12-12T21:23:57.114754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
5 1
 
2.0%
68 1
 
2.0%
350 1
 
2.0%
300 1
 
2.0%
262 1
 
2.0%
238 1
 
2.0%
166 1
 
2.0%
136 1
 
2.0%
144 1
 
2.0%
118 1
 
2.0%
Other values (39) 39
79.6%
ValueCountFrequency (%)
1 1
2.0%
2 1
2.0%
4 1
2.0%
5 1
2.0%
6 1
2.0%
7 1
2.0%
8 1
2.0%
9 1
2.0%
11 1
2.0%
14 1
2.0%
ValueCountFrequency (%)
755 1
2.0%
716 1
2.0%
702 1
2.0%
667 1
2.0%
649 1
2.0%
595 1
2.0%
568 1
2.0%
566 1
2.0%
531 1
2.0%
505 1
2.0%

Interactions

2023-12-12T21:23:53.105255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:48.355943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:49.195953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:49.960885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:50.792914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:51.537961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:52.456300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:53.196675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:48.464059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:49.306993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:50.069504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:50.894906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:51.961612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:52.538012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:53.302302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:48.596527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:49.412353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:50.189911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:50.998434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:52.040174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:52.618749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:53.407797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:48.734042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:49.511595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:50.324405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:51.096194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:52.131463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:52.706476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:53.502635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:48.856715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:49.625471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:50.436483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:51.192197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:52.215578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:52.786606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:53.598804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:48.962283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:49.736409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:50.543582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:51.310821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:52.293507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:52.871741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:53.681848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:49.071621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:49.849291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:50.660205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:51.417773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:52.376005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:23:52.956022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:23:57.228018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분계명예퇴직정년퇴직일반퇴직당연퇴직직권면직기타
구분1.0001.0001.0001.0001.0001.0001.0001.000
계1.0001.0000.9190.9360.7890.7600.7640.696
명예퇴직1.0000.9191.0000.8560.5800.7970.7350.697
정년퇴직1.0000.9360.8561.0000.6190.6150.8440.194
일반퇴직1.0000.7890.5800.6191.0000.8360.6640.612
당연퇴직1.0000.7600.7970.6150.8361.0000.5460.434
직권면직1.0000.7640.7350.8440.6640.5461.0000.461
기타1.0000.6960.6970.1940.6120.4340.4611.000
2023-12-12T21:23:57.380563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
계명예퇴직정년퇴직일반퇴직당연퇴직직권면직기타
계1.0000.9570.9820.8020.8000.9220.527
명예퇴직0.9571.0000.9090.7180.8290.9150.639
정년퇴직0.9820.9091.0000.7780.7660.9150.442
일반퇴직0.8020.7180.7781.0000.5100.6510.508
당연퇴직0.8000.8290.7660.5101.0000.7620.579
직권면직0.9220.9150.9150.6510.7621.0000.428
기타0.5270.6390.4420.5080.5790.4281.000

Missing values

2023-12-12T21:23:53.803281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:23:53.947725image/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

구분계명예퇴직정년퇴직일반퇴직당연퇴직직권면직기타
038세 미만13900134005
138세 이상10400101102
239세18000178101
340세27200265304
441세35960345206
542세43660416419
643세5093804573011
744세482620411207
845세5899204756016
946세71015305313023
구분계명예퇴직정년퇴직일반퇴직당연퇴직직권면직기타
3976세127943685806871615511654
4077세10253284464896251886245
4178세10162308861666081778934
4279세9439365849595731348926
4380세109625121479774510416530
4481세8525331443595809615620
4582세6976253336565191151458
4683세71422841340153714319921
4784세60612044313550116620114
4885세 이상22858442014632264252659048