Overview

Dataset statistics

Number of variables12
Number of observations45
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.8 KiB
Average record size in memory109.9 B

Variable types

Text1
Numeric11

Dataset

Description공무원으로 임용되기 전의 경력(군인경력,공무원경력, 사립학교교직원경력)을 현재의 근무기간에 합산한 공무원 수 데이터입니다.
URLhttps://www.data.go.kr/data/15053042/fileData.do

Alerts

합계 is highly overall correlated with 공무원경력(계) and 3 other fieldsHigh correlation
공무원경력(계) is highly overall correlated with 합계 and 1 other fieldsHigh correlation
공무원경력(퇴직연금해당자) is highly overall correlated with 공무원경력(퇴직일시금미수령자) and 3 other fieldsHigh correlation
공무원경력(퇴직일시금미수령자) is highly overall correlated with 공무원경력(퇴직연금해당자) and 4 other fieldsHigh correlation
공무원경력(퇴직일시금수령자) is highly overall correlated with 합계 and 3 other fieldsHigh correlation
군경력(계) is highly overall correlated with 합계 and 1 other fieldsHigh correlation
군경력(퇴직연금해당자) is highly overall correlated with 사립학교경력(퇴직연금해당자)High correlation
군경력(퇴직일시금해당자) is highly overall correlated with 합계 and 1 other fieldsHigh correlation
사립학교경력(계) is highly overall correlated with 공무원경력(퇴직연금해당자) and 3 other fieldsHigh correlation
사립학교경력(퇴직연금해당자) is highly overall correlated with 공무원경력(퇴직연금해당자) and 5 other fieldsHigh correlation
사립학교경력(퇴직일시금해당자) is highly overall correlated with 공무원경력(퇴직연금해당자) and 3 other fieldsHigh correlation
구분 has unique valuesUnique
합계 has unique valuesUnique
공무원경력(퇴직일시금수령자) has unique valuesUnique
군경력(퇴직일시금해당자) has unique valuesUnique
공무원경력(퇴직연금해당자) has 1 (2.2%) zerosZeros
군경력(퇴직연금해당자) has 1 (2.2%) zerosZeros
사립학교경력(계) has 3 (6.7%) zerosZeros
사립학교경력(퇴직연금해당자) has 21 (46.7%) zerosZeros
사립학교경력(퇴직일시금해당자) has 3 (6.7%) zerosZeros

Reproduction

Analysis started2023-12-12 05:44:40.412287
Analysis finished2023-12-12 05:44:53.311539
Duration12.9 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Text

UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size492.0 B
2023-12-12T14:44:53.471840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length3.8666667
Min length1

Characters and Unicode

Total characters174
Distinct characters12
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

Unique45 ?
Unique (%)100.0%

Sample

1st row1980
2nd row1981
3rd row1982
4th row1983
5th row1984
ValueCountFrequency (%)
1980 1
 
2.2%
2003 1
 
2.2%
2005 1
 
2.2%
2006 1
 
2.2%
2007 1
 
2.2%
2008 1
 
2.2%
2009 1
 
2.2%
2010 1
 
2.2%
2011 1
 
2.2%
2012 1
 
2.2%
Other values (35) 35
77.8%
2023-12-12T14:44:53.904836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 38
21.8%
1 35
20.1%
9 34
19.5%
2 31
17.8%
8 14
 
8.0%
3 4
 
2.3%
4 4
 
2.3%
5 4
 
2.3%
6 4
 
2.3%
7 4
 
2.3%
Other values (2) 2
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 172
98.9%
Other Letter 2
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 38
22.1%
1 35
20.3%
9 34
19.8%
2 31
18.0%
8 14
 
8.1%
3 4
 
2.3%
4 4
 
2.3%
5 4
 
2.3%
6 4
 
2.3%
7 4
 
2.3%
Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 172
98.9%
Hangul 2
 
1.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 38
22.1%
1 35
20.3%
9 34
19.8%
2 31
18.0%
8 14
 
8.1%
3 4
 
2.3%
4 4
 
2.3%
5 4
 
2.3%
6 4
 
2.3%
7 4
 
2.3%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 172
98.9%
Hangul 2
 
1.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 38
22.1%
1 35
20.3%
9 34
19.8%
2 31
18.0%
8 14
 
8.1%
3 4
 
2.3%
4 4
 
2.3%
5 4
 
2.3%
6 4
 
2.3%
7 4
 
2.3%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

합계
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6527.5778
Minimum2736
Maximum11349
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T14:44:54.079987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2736
5-th percentile3607.4
Q15291
median6321
Q37772
95-th percentile9540.4
Maximum11349
Range8613
Interquartile range (IQR)2481

Descriptive statistics

Standard deviation1837.0985
Coefficient of variation (CV)0.28143648
Kurtosis0.2319528
Mean6527.5778
Median Absolute Deviation (MAD)1217
Skewness0.28119564
Sum293741
Variance3374930.9
MonotonicityNot monotonic
2023-12-12T14:44:54.238070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
10164 1
 
2.2%
6321 1
 
2.2%
6047 1
 
2.2%
6053 1
 
2.2%
5171 1
 
2.2%
6672 1
 
2.2%
4630 1
 
2.2%
9570 1
 
2.2%
5291 1
 
2.2%
4953 1
 
2.2%
Other values (35) 35
77.8%
ValueCountFrequency (%)
2736 1
2.2%
2851 1
2.2%
3412 1
2.2%
4389 1
2.2%
4588 1
2.2%
4630 1
2.2%
4895 1
2.2%
4953 1
2.2%
4988 1
2.2%
5104 1
2.2%
ValueCountFrequency (%)
11349 1
2.2%
10164 1
2.2%
9570 1
2.2%
9422 1
2.2%
8508 1
2.2%
8486 1
2.2%
8331 1
2.2%
8172 1
2.2%
8119 1
2.2%
8097 1
2.2%

공무원경력(계)
Real number (ℝ)

HIGH CORRELATION 

Distinct44
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3706.3111
Minimum1051
Maximum9294
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T14:44:54.385099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1051
5-th percentile1937.2
Q12843
median3320
Q34628
95-th percentile5752.6
Maximum9294
Range8243
Interquartile range (IQR)1785

Descriptive statistics

Standard deviation1437.4667
Coefficient of variation (CV)0.38784297
Kurtosis3.8762221
Mean3706.3111
Median Absolute Deviation (MAD)881
Skewness1.3203034
Sum166784
Variance2066310.5
MonotonicityNot monotonic
2023-12-12T14:44:54.541706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
3320 2
 
4.4%
9294 1
 
2.2%
3310 1
 
2.2%
2945 1
 
2.2%
2283 1
 
2.2%
2707 1
 
2.2%
1990 1
 
2.2%
4651 1
 
2.2%
2521 1
 
2.2%
2403 1
 
2.2%
Other values (34) 34
75.6%
ValueCountFrequency (%)
1051 1
2.2%
1761 1
2.2%
1924 1
2.2%
1990 1
2.2%
2261 1
2.2%
2283 1
2.2%
2375 1
2.2%
2403 1
2.2%
2521 1
2.2%
2572 1
2.2%
ValueCountFrequency (%)
9294 1
2.2%
6102 1
2.2%
5839 1
2.2%
5407 1
2.2%
5236 1
2.2%
5217 1
2.2%
5118 1
2.2%
4964 1
2.2%
4799 1
2.2%
4719 1
2.2%

공무원경력(퇴직연금해당자)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct40
Distinct (%)88.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean78.955556
Minimum0
Maximum912
Zeros1
Zeros (%)2.2%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T14:44:54.685081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.4
Q122
median42
Q381
95-th percentile191
Maximum912
Range912
Interquartile range (IQR)59

Descriptive statistics

Standard deviation138.61506
Coefficient of variation (CV)1.7556087
Kurtosis30.840933
Mean78.955556
Median Absolute Deviation (MAD)25
Skewness5.1774175
Sum3553
Variance19214.134
MonotonicityNot monotonic
2023-12-12T14:44:54.808893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
67 2
 
4.4%
1 2
 
4.4%
43 2
 
4.4%
21 2
 
4.4%
35 2
 
4.4%
102 1
 
2.2%
36 1
 
2.2%
44 1
 
2.2%
58 1
 
2.2%
63 1
 
2.2%
Other values (30) 30
66.7%
ValueCountFrequency (%)
0 1
2.2%
1 2
4.4%
3 1
2.2%
7 1
2.2%
12 1
2.2%
14 1
2.2%
16 1
2.2%
17 1
2.2%
21 2
4.4%
22 1
2.2%
ValueCountFrequency (%)
912 1
2.2%
211 1
2.2%
193 1
2.2%
183 1
2.2%
169 1
2.2%
166 1
2.2%
154 1
2.2%
120 1
2.2%
106 1
2.2%
102 1
2.2%

공무원경력(퇴직일시금미수령자)
Real number (ℝ)

HIGH CORRELATION 

Distinct44
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean784.71111
Minimum147
Maximum2604
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T14:44:54.958759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum147
5-th percentile209
Q1278
median553
Q31132
95-th percentile2197.2
Maximum2604
Range2457
Interquartile range (IQR)854

Descriptive statistics

Standard deviation649.07342
Coefficient of variation (CV)0.82714952
Kurtosis0.89849855
Mean784.71111
Median Absolute Deviation (MAD)308
Skewness1.3065416
Sum35312
Variance421296.3
MonotonicityNot monotonic
2023-12-12T14:44:55.099232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
553 2
 
4.4%
217 1
 
2.2%
661 1
 
2.2%
869 1
 
2.2%
697 1
 
2.2%
652 1
 
2.2%
821 1
 
2.2%
665 1
 
2.2%
912 1
 
2.2%
1132 1
 
2.2%
Other values (34) 34
75.6%
ValueCountFrequency (%)
147 1
2.2%
171 1
2.2%
207 1
2.2%
217 1
2.2%
228 1
2.2%
237 1
2.2%
238 1
2.2%
243 1
2.2%
245 1
2.2%
255 1
2.2%
ValueCountFrequency (%)
2604 1
2.2%
2386 1
2.2%
2243 1
2.2%
2014 1
2.2%
1843 1
2.2%
1510 1
2.2%
1463 1
2.2%
1443 1
2.2%
1383 1
2.2%
1363 1
2.2%

공무원경력(퇴직일시금수령자)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2842.6444
Minimum659
Maximum9077
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T14:44:55.260632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum659
5-th percentile972.4
Q11736
median2349
Q33791
95-th percentile5407.4
Maximum9077
Range8418
Interquartile range (IQR)2055

Descriptive statistics

Standard deviation1646.7108
Coefficient of variation (CV)0.57928835
Kurtosis3.2159396
Mean2842.6444
Median Absolute Deviation (MAD)867
Skewness1.4779444
Sum127919
Variance2711656.5
MonotonicityNot monotonic
2023-12-12T14:44:55.420552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
9077 1
 
2.2%
1755 1
 
2.2%
2221 1
 
2.2%
2016 1
 
2.2%
1689 1
 
2.2%
1943 1
 
2.2%
1302 1
 
2.2%
3787 1
 
2.2%
1813 1
 
2.2%
1447 1
 
2.2%
Other values (35) 35
77.8%
ValueCountFrequency (%)
659 1
2.2%
843 1
2.2%
890 1
2.2%
1302 1
2.2%
1382 1
2.2%
1445 1
2.2%
1447 1
2.2%
1475 1
2.2%
1482 1
2.2%
1502 1
2.2%
ValueCountFrequency (%)
9077 1
2.2%
5753 1
2.2%
5516 1
2.2%
4973 1
2.2%
4920 1
2.2%
4915 1
2.2%
4838 1
2.2%
4452 1
2.2%
4162 1
2.2%
4135 1
2.2%

군경력(계)
Real number (ℝ)

HIGH CORRELATION 

Distinct43
Distinct (%)95.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1885.4667
Minimum120
Maximum3938
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T14:44:55.594879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum120
5-th percentile641.2
Q11621
median1948
Q32277
95-th percentile2932.2
Maximum3938
Range3818
Interquartile range (IQR)656

Descriptive statistics

Standard deviation711.52249
Coefficient of variation (CV)0.37737209
Kurtosis1.3679413
Mean1885.4667
Median Absolute Deviation (MAD)329
Skewness-0.13965071
Sum84846
Variance506264.25
MonotonicityNot monotonic
2023-12-12T14:44:55.757219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
1760 2
 
4.4%
2200 2
 
4.4%
870 1
 
2.2%
1983 1
 
2.2%
1911 1
 
2.2%
1676 1
 
2.2%
2277 1
 
2.2%
1765 1
 
2.2%
3058 1
 
2.2%
1836 1
 
2.2%
Other values (33) 33
73.3%
ValueCountFrequency (%)
120 1
2.2%
264 1
2.2%
584 1
2.2%
870 1
2.2%
914 1
2.2%
1020 1
2.2%
1093 1
2.2%
1209 1
2.2%
1372 1
2.2%
1451 1
2.2%
ValueCountFrequency (%)
3938 1
2.2%
3058 1
2.2%
2996 1
2.2%
2677 1
2.2%
2602 1
2.2%
2581 1
2.2%
2379 1
2.2%
2370 1
2.2%
2359 1
2.2%
2355 1
2.2%

군경력(퇴직연금해당자)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct35
Distinct (%)77.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean92.8
Minimum0
Maximum246
Zeros1
Zeros (%)2.2%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T14:44:55.907434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile31
Q153
median88
Q3124
95-th percentile172.4
Maximum246
Range246
Interquartile range (IQR)71

Descriptive statistics

Standard deviation50.703954
Coefficient of variation (CV)0.54637881
Kurtosis0.5133898
Mean92.8
Median Absolute Deviation (MAD)36
Skewness0.71930638
Sum4176
Variance2570.8909
MonotonicityNot monotonic
2023-12-12T14:44:56.062498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
140 3
 
6.7%
62 2
 
4.4%
122 2
 
4.4%
78 2
 
4.4%
136 2
 
4.4%
56 2
 
4.4%
39 2
 
4.4%
50 2
 
4.4%
63 2
 
4.4%
53 1
 
2.2%
Other values (25) 25
55.6%
ValueCountFrequency (%)
0 1
2.2%
26 1
2.2%
30 1
2.2%
35 1
2.2%
39 2
4.4%
44 1
2.2%
47 1
2.2%
49 1
2.2%
50 2
4.4%
53 1
2.2%
ValueCountFrequency (%)
246 1
 
2.2%
194 1
 
2.2%
175 1
 
2.2%
162 1
 
2.2%
160 1
 
2.2%
146 1
 
2.2%
140 3
6.7%
136 2
4.4%
124 1
 
2.2%
122 2
4.4%

군경력(퇴직일시금해당자)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1792.6667
Minimum70
Maximum3867
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T14:44:56.210492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum70
5-th percentile569
Q11543
median1885
Q32161
95-th percentile2845
Maximum3867
Range3797
Interquartile range (IQR)618

Descriptive statistics

Standard deviation709.233
Coefficient of variation (CV)0.39563016
Kurtosis1.4565201
Mean1792.6667
Median Absolute Deviation (MAD)328
Skewness-0.1065536
Sum80670
Variance503011.45
MonotonicityNot monotonic
2023-12-12T14:44:56.388277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
757 1
 
2.2%
1921 1
 
2.2%
1647 1
 
2.2%
1736 1
 
2.2%
1575 1
 
2.2%
2031 1
 
2.2%
1603 1
 
2.2%
2965 1
 
2.2%
1773 1
 
2.2%
1784 1
 
2.2%
Other values (35) 35
77.8%
ValueCountFrequency (%)
70 1
2.2%
120 1
2.2%
522 1
2.2%
757 1
2.2%
879 1
2.2%
953 1
2.2%
994 1
2.2%
1131 1
2.2%
1327 1
2.2%
1342 1
2.2%
ValueCountFrequency (%)
3867 1
2.2%
2965 1
2.2%
2901 1
2.2%
2621 1
2.2%
2466 1
2.2%
2435 1
2.2%
2331 1
2.2%
2329 1
2.2%
2253 1
2.2%
2223 1
2.2%

사립학교경력(계)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct43
Distinct (%)95.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean935.8
Minimum0
Maximum1861
Zeros3
Zeros (%)6.7%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T14:44:56.532894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile71.4
Q1671
median917
Q31252
95-th percentile1644
Maximum1861
Range1861
Interquartile range (IQR)581

Descriptive statistics

Standard deviation448.55645
Coefficient of variation (CV)0.4793294
Kurtosis-0.20845509
Mean935.8
Median Absolute Deviation (MAD)295
Skewness-0.11373392
Sum42111
Variance201202.89
MonotonicityNot monotonic
2023-12-12T14:44:56.658301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
0 3
 
6.7%
1309 1
 
2.2%
1197 1
 
2.2%
1212 1
 
2.2%
1688 1
 
2.2%
875 1
 
2.2%
1861 1
 
2.2%
934 1
 
2.2%
713 1
 
2.2%
795 1
 
2.2%
Other values (33) 33
73.3%
ValueCountFrequency (%)
0 3
6.7%
357 1
 
2.2%
414 1
 
2.2%
460 1
 
2.2%
483 1
 
2.2%
530 1
 
2.2%
536 1
 
2.2%
587 1
 
2.2%
665 1
 
2.2%
671 1
 
2.2%
ValueCountFrequency (%)
1861 1
2.2%
1688 1
2.2%
1654 1
2.2%
1604 1
2.2%
1577 1
2.2%
1513 1
2.2%
1509 1
2.2%
1337 1
2.2%
1309 1
2.2%
1301 1
2.2%

사립학교경력(퇴직연금해당자)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct18
Distinct (%)40.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.2
Minimum0
Maximum69
Zeros21
Zeros (%)46.7%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T14:44:56.783901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q316
95-th percentile49
Maximum69
Range69
Interquartile range (IQR)16

Descriptive statistics

Standard deviation17.639831
Coefficient of variation (CV)1.5749849
Kurtosis2.601963
Mean11.2
Median Absolute Deviation (MAD)3
Skewness1.8286595
Sum504
Variance311.16364
MonotonicityNot monotonic
2023-12-12T14:44:56.901029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 21
46.7%
8 4
 
8.9%
4 2
 
4.4%
3 2
 
4.4%
16 2
 
4.4%
7 2
 
4.4%
6 1
 
2.2%
23 1
 
2.2%
19 1
 
2.2%
5 1
 
2.2%
Other values (8) 8
 
17.8%
ValueCountFrequency (%)
0 21
46.7%
3 2
 
4.4%
4 2
 
4.4%
5 1
 
2.2%
6 1
 
2.2%
7 2
 
4.4%
8 4
 
8.9%
16 2
 
4.4%
19 1
 
2.2%
23 1
 
2.2%
ValueCountFrequency (%)
69 1
2.2%
59 1
2.2%
51 1
2.2%
41 1
2.2%
40 1
2.2%
38 1
2.2%
35 1
2.2%
26 1
2.2%
23 1
2.2%
19 1
2.2%

사립학교경력(퇴직일시금해당자)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct42
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean924.6
Minimum0
Maximum1858
Zeros3
Zeros (%)6.7%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T14:44:57.057934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile71.4
Q1671
median891
Q31248
95-th percentile1605.8
Maximum1858
Range1858
Interquartile range (IQR)577

Descriptive statistics

Standard deviation440.24721
Coefficient of variation (CV)0.47614884
Kurtosis-0.16137921
Mean924.6
Median Absolute Deviation (MAD)304
Skewness-0.13254639
Sum41607
Variance193817.61
MonotonicityNot monotonic
2023-12-12T14:44:57.233093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
0 3
 
6.7%
1058 2
 
4.4%
1275 1
 
2.2%
1193 1
 
2.2%
1204 1
 
2.2%
1665 1
 
2.2%
868 1
 
2.2%
1858 1
 
2.2%
926 1
 
2.2%
705 1
 
2.2%
Other values (32) 32
71.1%
ValueCountFrequency (%)
0 3
6.7%
357 1
 
2.2%
414 1
 
2.2%
460 1
 
2.2%
483 1
 
2.2%
495 1
 
2.2%
536 1
 
2.2%
587 1
 
2.2%
665 1
 
2.2%
671 1
 
2.2%
ValueCountFrequency (%)
1858 1
2.2%
1665 1
2.2%
1613 1
2.2%
1577 1
2.2%
1535 1
2.2%
1471 1
2.2%
1454 1
2.2%
1309 1
2.2%
1296 1
2.2%
1286 1
2.2%

Interactions

2023-12-12T14:44:51.626275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:40.745914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:41.779613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:42.833539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:43.947898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:45.088727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:46.082191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:47.449580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:48.386811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:49.396101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:50.420177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:51.722969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:40.811563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:41.857424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:42.945334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:44.057154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:45.172413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:46.174495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:47.510008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:48.466331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:49.488019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:50.519685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:51.846189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:40.899936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:41.927722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:43.034886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:44.143140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:45.261632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:46.265694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:47.589385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:48.544407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:49.570099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:50.624286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:51.946327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:41.005108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:42.025004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:43.127980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:44.239496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:45.348387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:46.351251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:47.680143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:48.632128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:49.644081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:50.726089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:52.054685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:41.099998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:42.135379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:43.218900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:44.348109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:45.434551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:46.436899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:47.767950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:48.723275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:49.725218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:50.814445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:52.140059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:41.188835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:42.240542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:43.321722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:44.469510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:45.504591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:46.543255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:47.854065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:48.809343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:49.809353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:50.920991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:52.267515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:41.308851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:42.333855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:43.446648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:44.562282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:45.613701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:46.656401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:47.949908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:48.912180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:49.933232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:51.044348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:52.360717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:41.409570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:42.415997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:43.543308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:44.653839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:45.707893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:46.758128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:48.026405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:49.001707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:50.023335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:51.153215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:52.467001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:41.496071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:42.524083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:43.670553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:44.768801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:45.803647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:46.867868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:48.108539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:49.106244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:50.117581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:51.273633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:52.592411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:41.578027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:42.617282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:43.776772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:44.866101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:45.892601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:47.257861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:48.194088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:49.196763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:50.213999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:51.403755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:52.695546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:41.684201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:42.729895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:43.862849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:44.989237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:45.981579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:47.347231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:48.295597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:49.300236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:50.318134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:44:51.521842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:44:57.328581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분합계공무원경력(계)공무원경력(퇴직연금해당자)공무원경력(퇴직일시금미수령자)공무원경력(퇴직일시금수령자)군경력(계)군경력(퇴직연금해당자)군경력(퇴직일시금해당자)사립학교경력(계)사립학교경력(퇴직연금해당자)사립학교경력(퇴직일시금해당자)
구분1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
합계1.0001.0000.8820.0000.0000.8070.8380.5070.8380.6930.3120.653
공무원경력(계)1.0000.8821.0000.0000.0000.9740.7330.0000.7390.5810.0000.530
공무원경력(퇴직연금해당자)1.0000.0000.0001.0000.7200.0000.0000.2090.0000.5840.9270.434
공무원경력(퇴직일시금미수령자)1.0000.0000.0000.7201.0000.0000.0000.0000.0000.6350.8930.597
공무원경력(퇴직일시금수령자)1.0000.8070.9740.0000.0001.0000.7210.0000.7130.6130.0000.571
군경력(계)1.0000.8380.7330.0000.0000.7211.0000.6601.0000.6190.0000.649
군경력(퇴직연금해당자)1.0000.5070.0000.2090.0000.0000.6601.0000.7120.3860.4950.000
군경력(퇴직일시금해당자)1.0000.8380.7390.0000.0000.7131.0000.7121.0000.6410.0000.663
사립학교경력(계)1.0000.6930.5810.5840.6350.6130.6190.3860.6411.0000.4220.994
사립학교경력(퇴직연금해당자)1.0000.3120.0000.9270.8930.0000.0000.4950.0000.4221.0000.000
사립학교경력(퇴직일시금해당자)1.0000.6530.5300.4340.5970.5710.6490.0000.6630.9940.0001.000
2023-12-12T14:44:57.515207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
합계공무원경력(계)공무원경력(퇴직연금해당자)공무원경력(퇴직일시금미수령자)공무원경력(퇴직일시금수령자)군경력(계)군경력(퇴직연금해당자)군경력(퇴직일시금해당자)사립학교경력(계)사립학교경력(퇴직연금해당자)사립학교경력(퇴직일시금해당자)
합계1.0000.8470.1820.1860.5780.7210.0790.7130.337-0.0350.338
공무원경력(계)0.8471.000-0.105-0.0530.7940.449-0.0540.458-0.029-0.306-0.026
공무원경력(퇴직연금해당자)0.182-0.1051.0000.766-0.4710.2430.4650.1880.6200.8050.605
공무원경력(퇴직일시금미수령자)0.186-0.0530.7661.000-0.5440.2790.3720.2390.5770.8620.562
공무원경력(퇴직일시금수령자)0.5780.794-0.471-0.5441.0000.263-0.2030.286-0.242-0.717-0.229
군경력(계)0.7210.4490.2430.2790.2631.0000.0850.9940.2990.0670.299
군경력(퇴직연금해당자)0.079-0.0540.4650.372-0.2030.0851.0000.0080.3660.5350.358
군경력(퇴직일시금해당자)0.7130.4580.1880.2390.2860.9940.0081.0000.2560.0190.256
사립학교경력(계)0.337-0.0290.6200.577-0.2420.2990.3660.2561.0000.5750.999
사립학교경력(퇴직연금해당자)-0.035-0.3060.8050.862-0.7170.0670.5350.0190.5751.0000.556
사립학교경력(퇴직일시금해당자)0.338-0.0260.6050.562-0.2290.2990.3580.2560.9990.5561.000

Missing values

2023-12-12T14:44:53.069148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:44:53.246403image/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

구분합계공무원경력(계)공무원경력(퇴직연금해당자)공무원경력(퇴직일시금미수령자)공무원경력(퇴직일시금수령자)군경력(계)군경력(퇴직연금해당자)군경력(퇴직일시금해당자)사립학교경력(계)사립학교경력(퇴직연금해당자)사립학교경력(퇴직일시금해당자)
0198010164929402179077870113757000
11981548152171243497326419470000
21982489543111333397758462522000
31983113496102734257533938713867130901309
41984547228433238260221698820814600460
519855860332016305299921267820484140414
6198669054067212553791235510222534830483
719875104298712171280417605617043570357
819889422583945278551629969529015870587
919898331511835245483826775626215360536
구분합계공무원경력(계)공무원경력(퇴직연금해당자)공무원경력(퇴직일시금미수령자)공무원경력(퇴직일시금수령자)군경력(계)군경력(퇴직연금해당자)군경력(퇴직일시금해당자)사립학교경력(계)사립학교경력(퇴직연금해당자)사립학교경력(퇴직일시금해당자)
35201569063310641510173625811462435101516999
3620166545354081201414452088103198591726891
372017608929601021383147521061191987102340983
3820188172415991214631784235913622231654411613
3920198097398221118431928260213624661513591454
4020208119420118322431775231412221921604691535
4120218508479916623862247220012220781509381471
4220227439429919326041502180314016631337511286
434588237516913638431683140154353035495
4428511924241241659120012080716791