Overview

Dataset statistics

Number of variables9
Number of observations48
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.9 KiB
Average record size in memory82.8 B

Variable types

Text1
Numeric7
Categorical1

Dataset

Description공무원이 퇴직시 퇴직을 하는 사유(명예퇴직, 정년퇴직, 일반퇴직, 당연퇴직, 사망 등)별, 연령별 퇴직자 수 데이터입니다.
URLhttps://www.data.go.kr/data/15053010/fileData.do

Alerts

계 is highly overall correlated with 명예퇴직 and 2 other fieldsHigh correlation
명예퇴직 is highly overall correlated with 계 and 3 other fieldsHigh correlation
정년퇴직 is highly overall correlated with 계 and 2 other fieldsHigh correlation
당연퇴직 is highly overall correlated with 사망 and 2 other fieldsHigh correlation
사망 is highly overall correlated with 계 and 4 other fieldsHigh correlation
기타 is highly overall correlated with 명예퇴직 and 2 other fieldsHigh correlation
직권면직 is highly overall correlated with 당연퇴직High correlation
직권면직 is highly imbalanced (69.6%)Imbalance
구 분 has unique valuesUnique
명예퇴직 has 22 (45.8%) zerosZeros
정년퇴직 has 31 (64.6%) zerosZeros
당연퇴직 has 6 (12.5%) zerosZeros
사망 has 4 (8.3%) zerosZeros
기타 has 7 (14.6%) zerosZeros

Reproduction

Analysis started2023-12-12 16:52:37.464558
Analysis finished2023-12-12 16:52:43.430613
Duration5.97 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구 분
Text

UNIQUE 

Distinct48
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size516.0 B
2023-12-13T01:52:43.612344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.1041667
Min length3

Characters and Unicode

Total characters149
Distinct characters14
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

Unique48 ?
Unique (%)100.0%

Sample

1st row18세이상
2nd row19세
3rd row20세
4th row21세
5th row22세
ValueCountFrequency (%)
18세이상 1
 
2.0%
43세 1
 
2.0%
44세 1
 
2.0%
45세 1
 
2.0%
46세 1
 
2.0%
47세 1
 
2.0%
48세 1
 
2.0%
49세 1
 
2.0%
50세 1
 
2.0%
51세 1
 
2.0%
Other values (39) 39
79.6%
2023-12-13T01:52:44.034126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
세 48
32.2%
2 15
 
10.1%
3 15
 
10.1%
4 15
 
10.1%
5 15
 
10.1%
6 10
 
6.7%
1 7
 
4.7%
8 5
 
3.4%
9 5
 
3.4%
0 5
 
3.4%
Other values (4) 9
 
6.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 96
64.4%
Other Letter 52
34.9%
Space Separator 1
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 15
15.6%
3 15
15.6%
4 15
15.6%
5 15
15.6%
6 10
10.4%
1 7
7.3%
8 5
 
5.2%
9 5
 
5.2%
0 5
 
5.2%
7 4
 
4.2%
Other Letter
ValueCountFrequency (%)
세 48
92.3%
이 2
 
3.8%
상 2
 
3.8%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 97
65.1%
Hangul 52
34.9%

Most frequent character per script

Common
ValueCountFrequency (%)
2 15
15.5%
3 15
15.5%
4 15
15.5%
5 15
15.5%
6 10
10.3%
1 7
7.2%
8 5
 
5.2%
9 5
 
5.2%
0 5
 
5.2%
7 4
 
4.1%
Hangul
ValueCountFrequency (%)
세 48
92.3%
이 2
 
3.8%
상 2
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 97
65.1%
Hangul 52
34.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
세 48
92.3%
이 2
 
3.8%
상 2
 
3.8%
ASCII
ValueCountFrequency (%)
2 15
15.5%
3 15
15.5%
4 15
15.5%
5 15
15.5%
6 10
10.3%
1 7
7.2%
8 5
 
5.2%
9 5
 
5.2%
0 5
 
5.2%
7 4
 
4.1%

계
Real number (ℝ)

HIGH CORRELATION 

Distinct45
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1145.6875
Minimum1
Maximum16567
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-13T01:52:44.211464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile11.15
Q1532.75
median645.5
Q3979.25
95-th percentile2814.55
Maximum16567
Range16566
Interquartile range (IQR)446.5

Descriptive statistics

Standard deviation2376.8061
Coefficient of variation (CV)2.0745675
Kurtosis39.67925
Mean1145.6875
Median Absolute Deviation (MAD)296
Skewness6.0716653
Sum54993
Variance5649207.2
MonotonicityNot monotonic
2023-12-13T01:52:44.402754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
594 2
 
4.2%
532 2
 
4.2%
677 2
 
4.2%
596 1
 
2.1%
538 1
 
2.1%
590 1
 
2.1%
608 1
 
2.1%
710 1
 
2.1%
709 1
 
2.1%
715 1
 
2.1%
Other values (35) 35
72.9%
ValueCountFrequency (%)
1 1
2.1%
7 1
2.1%
8 1
2.1%
17 1
2.1%
39 1
2.1%
70 1
2.1%
84 1
2.1%
180 1
2.1%
344 1
2.1%
510 1
2.1%
ValueCountFrequency (%)
16567 1
2.1%
3266 1
2.1%
2971 1
2.1%
2524 1
2.1%
2104 1
2.1%
1499 1
2.1%
1401 1
2.1%
1349 1
2.1%
1140 1
2.1%
1111 1
2.1%

명예퇴직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct26
Distinct (%)54.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean289.3125
Minimum0
Maximum2673
Zeros22
Zeros (%)45.8%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-13T01:52:44.546717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q3235.25
95-th percentile1600.05
Maximum2673
Range2673
Interquartile range (IQR)235.25

Descriptive statistics

Standard deviation597.25212
Coefficient of variation (CV)2.0643841
Kurtosis6.9855871
Mean289.3125
Median Absolute Deviation (MAD)5
Skewness2.6539613
Sum13887
Variance356710.09
MonotonicityNot monotonic
2023-12-13T01:52:44.692115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 22
45.8%
11 2
 
4.2%
546 1
 
2.1%
3 1
 
2.1%
8 1
 
2.1%
229 1
 
2.1%
925 1
 
2.1%
812 1
 
2.1%
2673 1
 
2.1%
2240 1
 
2.1%
Other values (16) 16
33.3%
ValueCountFrequency (%)
0 22
45.8%
3 1
 
2.1%
4 1
 
2.1%
6 1
 
2.1%
8 1
 
2.1%
11 2
 
4.2%
42 1
 
2.1%
48 1
 
2.1%
74 1
 
2.1%
89 1
 
2.1%
ValueCountFrequency (%)
2673 1
2.1%
2240 1
2.1%
1809 1
2.1%
1212 1
2.1%
1025 1
2.1%
925 1
2.1%
812 1
2.1%
775 1
2.1%
546 1
2.1%
356 1
2.1%

정년퇴직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct15
Distinct (%)31.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean420.41667
Minimum0
Maximum15280
Zeros31
Zeros (%)64.6%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-13T01:52:44.818440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32.25
95-th percentile1077.55
Maximum15280
Range15280
Interquartile range (IQR)2.25

Descriptive statistics

Standard deviation2236.6576
Coefficient of variation (CV)5.3200974
Kurtosis43.930337
Mean420.41667
Median Absolute Deviation (MAD)0
Skewness6.5330329
Sum20180
Variance5002637.4
MonotonicityNot monotonic
2023-12-13T01:52:44.960986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 31
64.6%
1 3
 
6.2%
2 2
 
4.2%
3 1
 
2.1%
4 1
 
2.1%
6 1
 
2.1%
9 1
 
2.1%
15 1
 
2.1%
17 1
 
2.1%
20 1
 
2.1%
Other values (5) 5
 
10.4%
ValueCountFrequency (%)
0 31
64.6%
1 3
 
6.2%
2 2
 
4.2%
3 1
 
2.1%
4 1
 
2.1%
6 1
 
2.1%
9 1
 
2.1%
15 1
 
2.1%
17 1
 
2.1%
18 1
 
2.1%
ValueCountFrequency (%)
15280 1
2.1%
2828 1
2.1%
1290 1
2.1%
683 1
2.1%
20 1
2.1%
18 1
2.1%
17 1
2.1%
15 1
2.1%
9 1
2.1%
6 1
2.1%

일반퇴직
Real number (ℝ)

Distinct47
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean408.22917
Minimum1
Maximum1120
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-13T01:52:45.121102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10.45
Q1214.5
median399.5
Q3555.25
95-th percentile939.75
Maximum1120
Range1119
Interquartile range (IQR)340.75

Descriptive statistics

Standard deviation276.06322
Coefficient of variation (CV)0.67624571
Kurtosis-0.0077143596
Mean408.22917
Median Absolute Deviation (MAD)182
Skewness0.59447094
Sum19595
Variance76210.904
MonotonicityNot monotonic
2023-12-13T01:52:45.290241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
174 2
 
4.2%
1 1
 
2.1%
248 1
 
2.1%
453 1
 
2.1%
417 1
 
2.1%
423 1
 
2.1%
403 1
 
2.1%
381 1
 
2.1%
396 1
 
2.1%
356 1
 
2.1%
Other values (37) 37
77.1%
ValueCountFrequency (%)
1 1
2.1%
7 1
2.1%
8 1
2.1%
15 1
2.1%
37 1
2.1%
67 1
2.1%
74 1
2.1%
96 1
2.1%
174 2
4.2%
192 1
2.1%
ValueCountFrequency (%)
1120 1
2.1%
979 1
2.1%
945 1
2.1%
930 1
2.1%
857 1
2.1%
785 1
2.1%
657 1
2.1%
654 1
2.1%
629 1
2.1%
604 1
2.1%

당연퇴직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct13
Distinct (%)27.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.9791667
Minimum0
Maximum16
Zeros6
Zeros (%)12.5%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-13T01:52:45.462843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q36
95-th percentile9.65
Maximum16
Range16
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.4300895
Coefficient of variation (CV)0.86201203
Kurtosis2.4627587
Mean3.9791667
Median Absolute Deviation (MAD)2
Skewness1.3321855
Sum191
Variance11.765514
MonotonicityNot monotonic
2023-12-13T01:52:45.624961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
1 8
16.7%
3 7
14.6%
0 6
12.5%
5 6
12.5%
6 5
10.4%
4 4
8.3%
2 4
8.3%
8 2
 
4.2%
7 2
 
4.2%
9 1
 
2.1%
Other values (3) 3
 
6.2%
ValueCountFrequency (%)
0 6
12.5%
1 8
16.7%
2 4
8.3%
3 7
14.6%
4 4
8.3%
5 6
12.5%
6 5
10.4%
7 2
 
4.2%
8 2
 
4.2%
9 1
 
2.1%
ValueCountFrequency (%)
16 1
 
2.1%
13 1
 
2.1%
10 1
 
2.1%
9 1
 
2.1%
8 2
 
4.2%
7 2
 
4.2%
6 5
10.4%
5 6
12.5%
4 4
8.3%
3 7
14.6%

직권면직
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size516.0 B
0
44 
1
 
3
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)2.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 44
91.7%
1 3
 
6.2%
3 1
 
2.1%

Length

2023-12-13T01:52:45.805534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:52:45.970860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 44
91.7%
1 3
 
6.2%
3 1
 
2.1%

사망
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct26
Distinct (%)54.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.583333
Minimum0
Maximum43
Zeros4
Zeros (%)8.3%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-13T01:52:46.159713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15
median11.5
Q327.25
95-th percentile37
Maximum43
Range43
Interquartile range (IQR)22.25

Descriptive statistics

Standard deviation12.814276
Coefficient of variation (CV)0.82230649
Kurtosis-0.90714917
Mean15.583333
Median Absolute Deviation (MAD)8.5
Skewness0.58920794
Sum748
Variance164.20567
MonotonicityNot monotonic
2023-12-13T01:52:46.327686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 4
 
8.3%
12 3
 
6.2%
32 3
 
6.2%
28 3
 
6.2%
1 3
 
6.2%
11 3
 
6.2%
20 3
 
6.2%
8 3
 
6.2%
9 3
 
6.2%
37 2
 
4.2%
Other values (16) 18
37.5%
ValueCountFrequency (%)
0 4
8.3%
1 3
6.2%
2 1
 
2.1%
3 1
 
2.1%
4 2
4.2%
5 2
4.2%
6 1
 
2.1%
7 1
 
2.1%
8 3
6.2%
9 3
6.2%
ValueCountFrequency (%)
43 1
 
2.1%
41 1
 
2.1%
37 2
4.2%
36 1
 
2.1%
35 1
 
2.1%
32 3
6.2%
28 3
6.2%
27 1
 
2.1%
25 1
 
2.1%
22 1
 
2.1%

기타
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct18
Distinct (%)37.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.0416667
Minimum0
Maximum23
Zeros7
Zeros (%)14.6%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-13T01:52:46.486974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median7.5
Q312
95-th percentile18.6
Maximum23
Range23
Interquartile range (IQR)9

Descriptive statistics

Standard deviation6.2055512
Coefficient of variation (CV)0.77167476
Kurtosis-0.25412358
Mean8.0416667
Median Absolute Deviation (MAD)4.5
Skewness0.55667107
Sum386
Variance38.508865
MonotonicityNot monotonic
2023-12-13T01:52:46.627228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 7
14.6%
10 5
10.4%
4 4
 
8.3%
12 4
 
8.3%
7 4
 
8.3%
8 3
 
6.2%
16 3
 
6.2%
15 3
 
6.2%
2 2
 
4.2%
5 2
 
4.2%
Other values (8) 11
22.9%
ValueCountFrequency (%)
0 7
14.6%
1 2
 
4.2%
2 2
 
4.2%
3 2
 
4.2%
4 4
8.3%
5 2
 
4.2%
6 1
 
2.1%
7 4
8.3%
8 3
6.2%
9 1
 
2.1%
ValueCountFrequency (%)
23 2
 
4.2%
20 1
 
2.1%
16 3
6.2%
15 3
6.2%
13 1
 
2.1%
12 4
8.3%
11 1
 
2.1%
10 5
10.4%
9 1
 
2.1%
8 3
6.2%

Interactions

2023-12-13T01:52:42.517269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:37.779505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:38.533438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:39.298203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:40.147501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:40.866542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:41.608292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:42.597577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:37.878985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:38.645069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:39.418366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:40.240922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:40.982337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:41.693458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:42.672731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:37.985795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:38.748747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:39.530386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:40.325732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:41.102691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:41.800216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:42.768052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:38.098704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:38.879193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:39.679621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:40.451652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:41.233357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:41.893427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:42.848060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:38.210802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:38.988870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:39.794072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:40.575417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:41.333119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:41.967841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:42.934551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:38.333532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:39.124065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:39.914432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:40.682490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:41.430646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:42.058130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:43.039582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:38.427431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:39.216525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:40.028024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:40.771622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:41.515955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:52:42.443415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:52:46.709030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구 분계명예퇴직정년퇴직일반퇴직당연퇴직직권면직사망기타
구 분1.0001.0001.0001.0001.0001.0001.0001.0001.000
계1.0001.0000.7600.9660.5320.3280.0000.2370.000
명예퇴직1.0000.7601.0000.2150.0000.6880.1320.6280.319
정년퇴직1.0000.9660.2151.0000.0000.0000.0000.0000.000
일반퇴직1.0000.5320.0000.0001.0000.3530.0000.6610.726
당연퇴직1.0000.3280.6880.0000.3531.0000.9660.6450.579
직권면직1.0000.0000.1320.0000.0000.9661.0000.4790.591
사망1.0000.2370.6280.0000.6610.6450.4791.0000.625
기타1.0000.0000.3190.0000.7260.5790.5910.6251.000
2023-12-13T01:52:46.840377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
계명예퇴직정년퇴직일반퇴직당연퇴직사망기타직권면직
계1.0000.5890.7260.2110.3940.5340.4160.000
명예퇴직0.5891.0000.795-0.3090.4100.7700.6120.055
정년퇴직0.7260.7951.000-0.3900.1840.5150.3120.000
일반퇴직0.211-0.309-0.3901.0000.4090.1860.2930.000
당연퇴직0.3940.4100.1840.4091.0000.6810.5560.725
사망0.5340.7700.5150.1860.6811.0000.8490.296
기타0.4160.6120.3120.2930.5560.8491.0000.291
직권면직0.0000.0550.0000.0000.7250.2960.2911.000

Missing values

2023-12-13T01:52:43.218176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:52:43.359176image/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

구 분계명예퇴직정년퇴직일반퇴직당연퇴직직권면직사망기타
018세이상10010000
119세70070000
220세80080000
321세1700151001
422세3900371010
523세7000671011
624세180001740042
725세344003350054
826세510005014050
927세665006543044
구 분계명예퇴직정년퇴직일반퇴직당연퇴직직권면직사망기타
3856세1499121215219603215
3957세2104180917216403523
4058세25242240202101003212
4159세297126731823760289
4260세1656781215280435202810
4361세111192511740074
4462세3266229282819230113
4563세1401111290961030
4664세8480741010
4765세 이상97236832801023