Overview

Dataset statistics

Number of variables11
Number of observations31
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.1 KiB
Average record size in memory102.3 B

Variable types

Text1
Numeric10

Dataset

Description퇴직연금, 유족연금, 장해연금 등 공무원연금공단에서 관리하는 연금의 수급 기간별 평균 연금 수급기간에 대한 현황 데이터입니다.
URLhttps://www.data.go.kr/data/15054093/fileData.do

Alerts

인원(계) is highly overall correlated with 평균수급기간 and 8 other fieldsHigh correlation
평균수급기간 is highly overall correlated with 인원(계) and 8 other fieldsHigh correlation
퇴직연금(인원) is highly overall correlated with 인원(계) and 8 other fieldsHigh correlation
퇴직연금(수급기간) is highly overall correlated with 인원(계) and 8 other fieldsHigh correlation
유족연금인원(퇴직연금수급기간포함) is highly overall correlated with 인원(계) and 8 other fieldsHigh correlation
유족연금수급기간(퇴직연금수급기간포함) is highly overall correlated with 인원(계) and 8 other fieldsHigh correlation
유족연금수급기간(인원) is highly overall correlated with 인원(계) and 8 other fieldsHigh correlation
유족연금수급기간 is highly overall correlated with 인원(계) and 8 other fieldsHigh correlation
장해연금(인원) is highly overall correlated with 인원(계) and 8 other fieldsHigh correlation
장해연금수급기간 is highly overall correlated with 인원(계) and 8 other fieldsHigh correlation
구분 has unique valuesUnique
인원(계) has unique valuesUnique
평균수급기간 has unique valuesUnique
퇴직연금(인원) has unique valuesUnique
퇴직연금(수급기간) has unique valuesUnique
유족연금인원(퇴직연금수급기간포함) has unique valuesUnique
유족연금수급기간(인원) has unique valuesUnique
유족연금수급기간 has unique valuesUnique
장해연금수급기간 has unique valuesUnique

Reproduction

Analysis started2023-12-12 14:03:01.885610
Analysis finished2023-12-12 14:03:12.659451
Duration10.77 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-12T23:03:12.796682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.8387097
Min length2

Characters and Unicode

Total characters88
Distinct characters15
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)100.0%

Sample

1st row1년미만
2nd row2년
3rd row3년
4th row4년
5th row5년
ValueCountFrequency (%)
1년미만 1
 
3.2%
17년 1
 
3.2%
30년 1
 
3.2%
29년 1
 
3.2%
28년 1
 
3.2%
27년 1
 
3.2%
26년 1
 
3.2%
25년 1
 
3.2%
24년 1
 
3.2%
23년 1
 
3.2%
Other values (21) 21
67.7%
2023-12-12T23:03:13.130259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
31
35.2%
1 13
14.8%
2 13
14.8%
3 5
 
5.7%
0 4
 
4.5%
4 3
 
3.4%
5 3
 
3.4%
6 3
 
3.4%
7 3
 
3.4%
8 3
 
3.4%
Other values (5) 7
 
8.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 53
60.2%
Other Letter 35
39.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13
24.5%
2 13
24.5%
3 5
 
9.4%
0 4
 
7.5%
4 3
 
5.7%
5 3
 
5.7%
6 3
 
5.7%
7 3
 
5.7%
8 3
 
5.7%
9 3
 
5.7%
Other Letter
ValueCountFrequency (%)
31
88.6%
1
 
2.9%
1
 
2.9%
1
 
2.9%
1
 
2.9%

Most occurring scripts

ValueCountFrequency (%)
Common 53
60.2%
Hangul 35
39.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 13
24.5%
2 13
24.5%
3 5
 
9.4%
0 4
 
7.5%
4 3
 
5.7%
5 3
 
5.7%
6 3
 
5.7%
7 3
 
5.7%
8 3
 
5.7%
9 3
 
5.7%
Hangul
ValueCountFrequency (%)
31
88.6%
1
 
2.9%
1
 
2.9%
1
 
2.9%
1
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 53
60.2%
Hangul 35
39.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
31
88.6%
1
 
2.9%
1
 
2.9%
1
 
2.9%
1
 
2.9%
ASCII
ValueCountFrequency (%)
1 13
24.5%
2 13
24.5%
3 5
 
9.4%
0 4
 
7.5%
4 3
 
5.7%
5 3
 
5.7%
6 3
 
5.7%
7 3
 
5.7%
8 3
 
5.7%
9 3
 
5.7%

인원(계)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20266.129
Minimum2998
Maximum55156
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-12T23:03:13.263761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2998
5-th percentile4309
Q111500
median18820
Q329587
95-th percentile37997
Maximum55156
Range52158
Interquartile range (IQR)18087

Descriptive statistics

Standard deviation12482.848
Coefficient of variation (CV)0.61594635
Kurtosis0.39745103
Mean20266.129
Median Absolute Deviation (MAD)9737
Skewness0.73329884
Sum628250
Variance1.558215 × 108
MonotonicityNot monotonic
2023-12-12T23:03:13.404494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
55156 1
 
3.2%
38769 1
 
3.2%
11779 1
 
3.2%
2998 1
 
3.2%
4248 1
 
3.2%
4370 1
 
3.2%
4813 1
 
3.2%
5685 1
 
3.2%
16703 1
 
3.2%
25267 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
2998 1
3.2%
4248 1
3.2%
4370 1
3.2%
4813 1
3.2%
5685 1
3.2%
7875 1
3.2%
9083 1
3.2%
11221 1
3.2%
11779 1
3.2%
13250 1
3.2%
ValueCountFrequency (%)
55156 1
3.2%
38769 1
3.2%
37225 1
3.2%
35732 1
3.2%
34352 1
3.2%
32787 1
3.2%
32392 1
3.2%
30603 1
3.2%
28571 1
3.2%
25267 1
3.2%

평균수급기간
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.519355
Minimum0.3
Maximum34.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-12T23:03:13.549030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.3
5-th percentile1.9
Q17.95
median15.4
Q322.95
95-th percentile28.9
Maximum34.1
Range33.8
Interquartile range (IQR)15

Descriptive statistics

Standard deviation9.3094726
Coefficient of variation (CV)0.59986209
Kurtosis-1.0066248
Mean15.519355
Median Absolute Deviation (MAD)7.9
Skewness0.095525353
Sum481.1
Variance86.66628
MonotonicityStrictly increasing
2023-12-12T23:03:13.691655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0.3 1
 
3.2%
1.4 1
 
3.2%
34.1 1
 
3.2%
29.4 1
 
3.2%
28.4 1
 
3.2%
27.4 1
 
3.2%
26.4 1
 
3.2%
25.4 1
 
3.2%
24.2 1
 
3.2%
23.4 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
0.3 1
3.2%
1.4 1
3.2%
2.4 1
3.2%
3.4 1
3.2%
4.4 1
3.2%
5.4 1
3.2%
6.4 1
3.2%
7.5 1
3.2%
8.4 1
3.2%
9.5 1
3.2%
ValueCountFrequency (%)
34.1 1
3.2%
29.4 1
3.2%
28.4 1
3.2%
27.4 1
3.2%
26.4 1
3.2%
25.4 1
3.2%
24.2 1
3.2%
23.4 1
3.2%
22.5 1
3.2%
21.4 1
3.2%

퇴직연금(인원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17613.226
Minimum2530
Maximum48677
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-12T23:03:13.833444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2530
5-th percentile3829
Q19820.5
median15920
Q325295
95-th percentile32232
Maximum48677
Range46147
Interquartile range (IQR)15474.5

Descriptive statistics

Standard deviation10923.733
Coefficient of variation (CV)0.62020058
Kurtosis0.49429533
Mean17613.226
Median Absolute Deviation (MAD)8378
Skewness0.74104279
Sum546010
Variance1.1932794 × 108
MonotonicityNot monotonic
2023-12-12T23:03:14.001556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
48677 1
 
3.2%
32769 1
 
3.2%
10206 1
 
3.2%
2530 1
 
3.2%
3773 1
 
3.2%
3885 1
 
3.2%
4223 1
 
3.2%
4985 1
 
3.2%
15920 1
 
3.2%
24236 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
2530 1
3.2%
3773 1
3.2%
3885 1
3.2%
4223 1
3.2%
4985 1
3.2%
6528 1
3.2%
7542 1
3.2%
9435 1
3.2%
10206 1
3.2%
10742 1
3.2%
ValueCountFrequency (%)
48677 1
3.2%
32769 1
3.2%
31695 1
3.2%
30758 1
3.2%
30490 1
3.2%
28958 1
3.2%
27505 1
3.2%
26111 1
3.2%
24479 1
3.2%
24236 1
3.2%

퇴직연금(수급기간)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.525806
Minimum0.3
Maximum34.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-12T23:03:14.168865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.3
5-th percentile1.9
Q17.95
median15.4
Q322.95
95-th percentile28.9
Maximum34.3
Range34
Interquartile range (IQR)15

Descriptive statistics

Standard deviation9.3228382
Coefficient of variation (CV)0.60047368
Kurtosis-0.99210449
Mean15.525806
Median Absolute Deviation (MAD)7.9
Skewness0.10210325
Sum481.3
Variance86.915312
MonotonicityStrictly increasing
2023-12-12T23:03:14.292659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0.3 1
 
3.2%
1.4 1
 
3.2%
34.3 1
 
3.2%
29.4 1
 
3.2%
28.4 1
 
3.2%
27.4 1
 
3.2%
26.4 1
 
3.2%
25.4 1
 
3.2%
24.2 1
 
3.2%
23.4 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
0.3 1
3.2%
1.4 1
3.2%
2.4 1
3.2%
3.4 1
3.2%
4.4 1
3.2%
5.4 1
3.2%
6.4 1
3.2%
7.5 1
3.2%
8.4 1
3.2%
9.5 1
3.2%
ValueCountFrequency (%)
34.3 1
3.2%
29.4 1
3.2%
28.4 1
3.2%
27.4 1
3.2%
26.4 1
3.2%
25.4 1
3.2%
24.2 1
3.2%
23.4 1
3.2%
22.5 1
3.2%
21.4 1
3.2%

유족연금인원(퇴직연금수급기간포함)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2532.1935
Minimum444
Maximum6374
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-12T23:03:14.434830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum444
5-th percentile447.5
Q11169
median2178
Q33565.5
95-th percentile5585.5
Maximum6374
Range5930
Interquartile range (IQR)2396.5

Descriptive statistics

Standard deviation1721.8655
Coefficient of variation (CV)0.67998969
Kurtosis-0.55419172
Mean2532.1935
Median Absolute Deviation (MAD)1270
Skewness0.64652043
Sum78498
Variance2964820.8
MonotonicityNot monotonic
2023-12-12T23:03:14.577662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
6374 1
 
3.2%
5837 1
 
3.2%
1460 1
 
3.2%
449 1
 
3.2%
446 1
 
3.2%
444 1
 
3.2%
557 1
 
3.2%
664 1
 
3.2%
661 1
 
3.2%
896 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
444 1
3.2%
446 1
3.2%
449 1
3.2%
557 1
3.2%
661 1
3.2%
664 1
3.2%
896 1
3.2%
1069 1
3.2%
1269 1
3.2%
1444 1
3.2%
ValueCountFrequency (%)
6374 1
3.2%
5837 1
3.2%
5334 1
3.2%
5068 1
3.2%
4752 1
3.2%
4377 1
3.2%
3963 1
3.2%
3683 1
3.2%
3448 1
3.2%
3344 1
3.2%
Distinct27
Distinct (%)87.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.790323
Minimum19.3
Maximum34.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-12T23:03:14.714718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19.3
5-th percentile19.6
Q121.3
median23.9
Q327.7
95-th percentile31.8
Maximum34.9
Range15.6
Interquartile range (IQR)6.4

Descriptive statistics

Standard deviation4.3194409
Coefficient of variation (CV)0.174239
Kurtosis-0.58633282
Mean24.790323
Median Absolute Deviation (MAD)3
Skewness0.66512236
Sum768.5
Variance18.65757
MonotonicityNot monotonic
2023-12-12T23:03:14.871869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
20.5 2
 
6.5%
21.5 2
 
6.5%
23.9 2
 
6.5%
25.3 2
 
6.5%
19.4 1
 
3.2%
26.2 1
 
3.2%
34.9 1
 
3.2%
32.0 1
 
3.2%
31.6 1
 
3.2%
31.0 1
 
3.2%
Other values (17) 17
54.8%
ValueCountFrequency (%)
19.3 1
3.2%
19.4 1
3.2%
19.8 1
3.2%
20.2 1
3.2%
20.5 2
6.5%
20.9 1
3.2%
21.1 1
3.2%
21.5 2
6.5%
22.2 1
3.2%
22.4 1
3.2%
ValueCountFrequency (%)
34.9 1
3.2%
32.0 1
3.2%
31.6 1
3.2%
31.0 1
3.2%
30.5 1
3.2%
29.8 1
3.2%
29.5 1
3.2%
28.1 1
3.2%
27.3 1
3.2%
26.6 1
3.2%

유족연금수급기간(인원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2532.1935
Minimum444
Maximum6374
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-12T23:03:15.003095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum444
5-th percentile447.5
Q11169
median2178
Q33565.5
95-th percentile5585.5
Maximum6374
Range5930
Interquartile range (IQR)2396.5

Descriptive statistics

Standard deviation1721.8655
Coefficient of variation (CV)0.67998969
Kurtosis-0.55419172
Mean2532.1935
Median Absolute Deviation (MAD)1270
Skewness0.64652043
Sum78498
Variance2964820.8
MonotonicityNot monotonic
2023-12-12T23:03:15.123852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
6374 1
 
3.2%
5837 1
 
3.2%
1460 1
 
3.2%
449 1
 
3.2%
446 1
 
3.2%
444 1
 
3.2%
557 1
 
3.2%
664 1
 
3.2%
661 1
 
3.2%
896 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
444 1
3.2%
446 1
3.2%
449 1
3.2%
557 1
3.2%
661 1
3.2%
664 1
3.2%
896 1
3.2%
1069 1
3.2%
1269 1
3.2%
1444 1
3.2%
ValueCountFrequency (%)
6374 1
3.2%
5837 1
3.2%
5334 1
3.2%
5068 1
3.2%
4752 1
3.2%
4377 1
3.2%
3963 1
3.2%
3683 1
3.2%
3448 1
3.2%
3344 1
3.2%

유족연금수급기간
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.535484
Minimum0.5
Maximum33
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-12T23:03:15.266986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.5
5-th percentile1.9
Q17.95
median15.5
Q322.95
95-th percentile28.9
Maximum33
Range32.5
Interquartile range (IQR)15

Descriptive statistics

Standard deviation9.2306572
Coefficient of variation (CV)0.59416606
Kurtosis-1.0879113
Mean15.535484
Median Absolute Deviation (MAD)7.9
Skewness0.060619377
Sum481.6
Variance85.205032
MonotonicityStrictly increasing
2023-12-12T23:03:15.381695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0.5 1
 
3.2%
1.4 1
 
3.2%
33.0 1
 
3.2%
29.4 1
 
3.2%
28.4 1
 
3.2%
27.4 1
 
3.2%
26.5 1
 
3.2%
25.5 1
 
3.2%
24.4 1
 
3.2%
23.4 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
0.5 1
3.2%
1.4 1
3.2%
2.4 1
3.2%
3.5 1
3.2%
4.5 1
3.2%
5.4 1
3.2%
6.5 1
3.2%
7.5 1
3.2%
8.4 1
3.2%
9.5 1
3.2%
ValueCountFrequency (%)
33.0 1
3.2%
29.4 1
3.2%
28.4 1
3.2%
27.4 1
3.2%
26.5 1
3.2%
25.5 1
3.2%
24.4 1
3.2%
23.4 1
3.2%
22.5 1
3.2%
21.4 1
3.2%

장해연금(인원)
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean120.70968
Minimum19
Maximum400
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-12T23:03:15.501872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19
5-th percentile31
Q182
median115
Q3146.5
95-th percentile208.5
Maximum400
Range381
Interquartile range (IQR)64.5

Descriptive statistics

Standard deviation71.637138
Coefficient of variation (CV)0.5934664
Kurtosis6.8478993
Mean120.70968
Median Absolute Deviation (MAD)32
Skewness1.8946921
Sum3742
Variance5131.8796
MonotonicityNot monotonic
2023-12-12T23:03:15.975045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
135 2
 
6.5%
146 2
 
6.5%
105 1
 
3.2%
221 1
 
3.2%
113 1
 
3.2%
19 1
 
3.2%
29 1
 
3.2%
41 1
 
3.2%
33 1
 
3.2%
36 1
 
3.2%
Other values (19) 19
61.3%
ValueCountFrequency (%)
19 1
3.2%
29 1
3.2%
33 1
3.2%
36 1
3.2%
41 1
3.2%
69 1
3.2%
78 1
3.2%
81 1
3.2%
83 1
3.2%
85 1
3.2%
ValueCountFrequency (%)
400 1
3.2%
221 1
3.2%
196 1
3.2%
174 1
3.2%
163 1
3.2%
156 1
3.2%
148 1
3.2%
147 1
3.2%
146 2
6.5%
143 1
3.2%

장해연금수급기간
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.554839
Minimum0.6
Maximum34.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-12T23:03:16.140449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.6
5-th percentile2
Q17.9
median15.4
Q322.95
95-th percentile28.95
Maximum34.4
Range33.8
Interquartile range (IQR)15.05

Descriptive statistics

Standard deviation9.3014636
Coefficient of variation (CV)0.59797879
Kurtosis-0.99052807
Mean15.554839
Median Absolute Deviation (MAD)8
Skewness0.11610572
Sum482.2
Variance86.517226
MonotonicityStrictly increasing
2023-12-12T23:03:16.269646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0.6 1
 
3.2%
1.5 1
 
3.2%
34.4 1
 
3.2%
29.5 1
 
3.2%
28.4 1
 
3.2%
27.4 1
 
3.2%
26.3 1
 
3.2%
25.4 1
 
3.2%
24.3 1
 
3.2%
23.5 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
0.6 1
3.2%
1.5 1
3.2%
2.5 1
3.2%
3.4 1
3.2%
4.5 1
3.2%
5.5 1
3.2%
6.4 1
3.2%
7.4 1
3.2%
8.4 1
3.2%
9.5 1
3.2%
ValueCountFrequency (%)
34.4 1
3.2%
29.5 1
3.2%
28.4 1
3.2%
27.4 1
3.2%
26.3 1
3.2%
25.4 1
3.2%
24.3 1
3.2%
23.5 1
3.2%
22.4 1
3.2%
21.4 1
3.2%

Interactions

2023-12-12T23:03:11.484808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:02.223940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:03.159440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:04.457322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:05.378021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:06.251919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:07.187114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:08.130829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:09.109097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:10.455174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:11.571627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:02.313092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:03.549292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:04.533934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:05.464178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:06.335159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:07.264431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:08.228350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:09.220236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:10.567318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:11.665509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:02.413149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:03.642545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:04.630684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:05.567174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:06.466834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:07.390173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:08.336926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:09.328990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:10.685916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:11.757134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:02.503086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:03.770612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:04.704378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:05.652355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:06.562189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:07.472474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:08.416945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:09.428652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:10.777591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:11.861711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:02.586969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:03.863123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:04.791595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:05.730746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:06.665244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:07.556551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:08.506762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:09.859475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:10.884106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:11.954715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:02.680541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:03.957347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:04.877227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:05.805744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:06.753592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:07.638907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:08.593558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:09.936662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:10.979505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:12.043929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:02.771418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:04.069633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:04.977048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:05.905174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:06.849563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:07.727245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:08.690388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:10.027219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:11.084045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:12.126552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:02.860612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:04.177409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:05.078013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:05.986267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:06.928546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:07.810400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:08.791258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:10.139490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:11.190035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:12.209560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:02.958916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:04.261718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:05.173507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:06.077298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:07.001935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:07.904209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:08.909244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:10.236446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:11.281978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:12.303437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:03.071989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:04.365686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:05.274847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:06.167955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:07.093464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:08.034866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:09.010057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:10.347455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:11.381567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:03:16.379047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분인원(계)평균수급기간퇴직연금(인원)퇴직연금(수급기간)유족연금인원(퇴직연금수급기간포함)유족연금수급기간(퇴직연금수급기간포함)유족연금수급기간(인원)유족연금수급기간장해연금(인원)장해연금수급기간
구분1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
인원(계)1.0001.0000.6620.9990.6520.6090.5300.6090.6500.6270.652
평균수급기간1.0000.6621.0000.6831.0000.8810.9710.8810.9930.6851.000
퇴직연금(인원)1.0000.9990.6831.0000.6750.6220.5810.6220.6870.6350.675
퇴직연금(수급기간)1.0000.6521.0000.6751.0000.8810.9700.8810.9910.6771.000
유족연금인원(퇴직연금수급기간포함)1.0000.6090.8810.6220.8811.0000.8891.0000.9290.6660.881
유족연금수급기간(퇴직연금수급기간포함)1.0000.5300.9710.5810.9700.8891.0000.8890.9770.5740.970
유족연금수급기간(인원)1.0000.6090.8810.6220.8811.0000.8891.0000.9290.6660.881
유족연금수급기간1.0000.6500.9930.6870.9910.9290.9770.9291.0000.7430.991
장해연금(인원)1.0000.6270.6850.6350.6770.6660.5740.6660.7431.0000.677
장해연금수급기간1.0000.6521.0000.6751.0000.8810.9700.8810.9910.6771.000
2023-12-12T23:03:16.560544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인원(계)평균수급기간퇴직연금(인원)퇴직연금(수급기간)유족연금인원(퇴직연금수급기간포함)유족연금수급기간(퇴직연금수급기간포함)유족연금수급기간(인원)유족연금수급기간장해연금(인원)장해연금수급기간
인원(계)1.000-0.8700.998-0.8700.869-0.8620.869-0.8700.640-0.870
평균수급기간-0.8701.000-0.8561.000-0.9760.999-0.9761.000-0.5101.000
퇴직연금(인원)0.998-0.8561.000-0.8560.854-0.8480.854-0.8560.655-0.856
퇴직연금(수급기간)-0.8701.000-0.8561.000-0.9760.999-0.9761.000-0.5101.000
유족연금인원(퇴직연금수급기간포함)0.869-0.9760.854-0.9761.000-0.9751.000-0.9760.530-0.976
유족연금수급기간(퇴직연금수급기간포함)-0.8620.999-0.8480.999-0.9751.000-0.9750.999-0.5080.999
유족연금수급기간(인원)0.869-0.9760.854-0.9761.000-0.9751.000-0.9760.530-0.976
유족연금수급기간-0.8701.000-0.8561.000-0.9760.999-0.9761.000-0.5101.000
장해연금(인원)0.640-0.5100.655-0.5100.530-0.5080.530-0.5101.000-0.510
장해연금수급기간-0.8701.000-0.8561.000-0.9760.999-0.9761.000-0.5101.000

Missing values

2023-12-12T23:03:12.446230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:03:12.599443image/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

구분인원(계)평균수급기간퇴직연금(인원)퇴직연금(수급기간)유족연금인원(퇴직연금수급기간포함)유족연금수급기간(퇴직연금수급기간포함)유족연금수급기간(인원)유족연금수급기간장해연금(인원)장해연금수급기간
01년미만551560.3486770.3637419.463740.51050.6
12년387691.4327691.4583719.358371.41631.5
23년372252.4316952.4533419.853342.41962.5
34년357323.4304903.4506820.250683.51743.4
45년323924.4275054.4475220.547524.51354.5
56년306035.4261115.4437720.543775.41155.5
67년285716.4244796.4396320.939636.51296.4
78년327877.5289587.5368321.136837.51467.4
89년343528.4307588.4344821.534488.41468.4
910년188979.5154689.5334421.533449.5859.5
구분인원(계)평균수급기간퇴직연금(인원)퇴직연금(수급기간)유족연금인원(퇴직연금수급기간포함)유족연금수급기간(퇴직연금수급기간포함)유족연금수급기간(인원)유족연금수급기간장해연금(인원)장해연금수급기간
2122년787521.4652821.4126926.6126921.47821.4
2223년1642522.51527522.5106927.3106922.58122.4
2324년2526723.42423623.489628.189623.413523.5
2425년1670324.21592024.266129.566124.412224.3
2526년568525.4498525.466429.866425.53625.4
2627년481326.4422326.455730.555726.53326.3
2728년437027.4388527.444431.044427.44127.4
2829년424828.4377328.444631.644628.42928.4
2930년299829.4253029.444932.044929.41929.5
3030년이상1177934.11020634.3146034.9146033.011334.4