Overview

Dataset statistics

Number of variables16
Number of observations41
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.9 KiB
Average record size in memory147.2 B

Variable types

Numeric16

Dataset

Description직종별(정무직, 별정직, 일반직, 경찰, 소방, 교육 등) 퇴직자 수에 대한 데이터입니다. 1982년부터 2022년까지 연 단위로 구분됩니다.
URLhttps://www.data.go.kr/data/15052999/fileData.do

Alerts

연도 is highly overall correlated with 정무직 and 11 other fieldsHigh correlation
정무직 is highly overall correlated with 연도 and 8 other fieldsHigh correlation
별정직 is highly overall correlated with 소방 and 5 other fieldsHigh correlation
일반직 is highly overall correlated with 경찰 and 2 other fieldsHigh correlation
경찰 is highly overall correlated with 일반직 and 1 other fieldsHigh correlation
소방 is highly overall correlated with 연도 and 9 other fieldsHigh correlation
교육 is highly overall correlated with 연도 and 9 other fieldsHigh correlation
법관검사 is highly overall correlated with 연도 and 9 other fieldsHigh correlation
기능직 is highly overall correlated with 연도 and 7 other fieldsHigh correlation
공안직 is highly overall correlated with 연도 and 12 other fieldsHigh correlation
군무원 is highly overall correlated with 연도 and 11 other fieldsHigh correlation
연구직 is highly overall correlated with 연도 and 11 other fieldsHigh correlation
지도직 is highly overall correlated with 연도 and 12 other fieldsHigh correlation
계약직 is highly overall correlated with 연도 and 11 other fieldsHigh correlation
공중보건의 is highly overall correlated with 연도 and 8 other fieldsHigh correlation
기타 is highly overall correlated with 연도 and 6 other fieldsHigh correlation
연도 has unique valuesUnique
별정직 has unique valuesUnique
일반직 has unique valuesUnique
교육 has unique valuesUnique
기능직 has unique valuesUnique
기타 has unique valuesUnique
정무직 has 19 (46.3%) zerosZeros
소방 has 29 (70.7%) zerosZeros
공안직 has 19 (46.3%) zerosZeros
군무원 has 19 (46.3%) zerosZeros
연구직 has 19 (46.3%) zerosZeros
지도직 has 19 (46.3%) zerosZeros
계약직 has 19 (46.3%) zerosZeros
공중보건의 has 19 (46.3%) zerosZeros

Reproduction

Analysis started2023-12-12 09:02:39.712312
Analysis finished2023-12-12 09:03:12.798202
Duration33.09 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2002
Minimum1982
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T18:03:12.872118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1982
5-th percentile1984
Q11992
median2002
Q32012
95-th percentile2020
Maximum2022
Range40
Interquartile range (IQR)20

Descriptive statistics

Standard deviation11.979149
Coefficient of variation (CV)0.0059835907
Kurtosis-1.2
Mean2002
Median Absolute Deviation (MAD)10
Skewness0
Sum82082
Variance143.5
MonotonicityStrictly increasing
2023-12-12T18:03:13.012038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
1982 1
 
2.4%
2013 1
 
2.4%
2005 1
 
2.4%
2006 1
 
2.4%
2007 1
 
2.4%
2008 1
 
2.4%
2009 1
 
2.4%
2010 1
 
2.4%
2011 1
 
2.4%
2012 1
 
2.4%
Other values (31) 31
75.6%
ValueCountFrequency (%)
1982 1
2.4%
1983 1
2.4%
1984 1
2.4%
1985 1
2.4%
1986 1
2.4%
1987 1
2.4%
1988 1
2.4%
1989 1
2.4%
1990 1
2.4%
1991 1
2.4%
ValueCountFrequency (%)
2022 1
2.4%
2021 1
2.4%
2020 1
2.4%
2019 1
2.4%
2018 1
2.4%
2017 1
2.4%
2016 1
2.4%
2015 1
2.4%
2014 1
2.4%
2013 1
2.4%

정무직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct23
Distinct (%)56.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean207.90244
Minimum0
Maximum1329
Zeros19
Zeros (%)46.3%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T18:03:13.219009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median62
Q3192
95-th percentile779
Maximum1329
Range1329
Interquartile range (IQR)192

Descriptive statistics

Standard deviation342.0081
Coefficient of variation (CV)1.6450413
Kurtosis3.3816418
Mean207.90244
Median Absolute Deviation (MAD)62
Skewness1.9476101
Sum8524
Variance116969.54
MonotonicityNot monotonic
2023-12-12T18:03:13.415749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 19
46.3%
446 1
 
2.4%
127 1
 
2.4%
92 1
 
2.4%
75 1
 
2.4%
62 1
 
2.4%
73 1
 
2.4%
109 1
 
2.4%
69 1
 
2.4%
55 1
 
2.4%
Other values (13) 13
31.7%
ValueCountFrequency (%)
0 19
46.3%
55 1
 
2.4%
62 1
 
2.4%
64 1
 
2.4%
69 1
 
2.4%
73 1
 
2.4%
75 1
 
2.4%
82 1
 
2.4%
92 1
 
2.4%
109 1
 
2.4%
ValueCountFrequency (%)
1329 1
2.4%
1262 1
2.4%
779 1
2.4%
671 1
2.4%
655 1
2.4%
603 1
2.4%
591 1
2.4%
565 1
2.4%
504 1
2.4%
446 1
2.4%

별정직
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1350.7561
Minimum347
Maximum3214
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T18:03:13.593924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum347
5-th percentile423
Q1716
median1322
Q31578
95-th percentile2834
Maximum3214
Range2867
Interquartile range (IQR)862

Descriptive statistics

Standard deviation727.19209
Coefficient of variation (CV)0.53835929
Kurtosis0.45744467
Mean1350.7561
Median Absolute Deviation (MAD)378
Skewness0.85886724
Sum55381
Variance528808.34
MonotonicityNot monotonic
2023-12-12T18:03:13.741105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
1048 1
 
2.4%
1251 1
 
2.4%
347 1
 
2.4%
1451 1
 
2.4%
1386 1
 
2.4%
1632 1
 
2.4%
1360 1
 
2.4%
1578 1
 
2.4%
1395 1
 
2.4%
1503 1
 
2.4%
Other values (31) 31
75.6%
ValueCountFrequency (%)
347 1
2.4%
409 1
2.4%
423 1
2.4%
443 1
2.4%
475 1
2.4%
556 1
2.4%
561 1
2.4%
612 1
2.4%
653 1
2.4%
698 1
2.4%
ValueCountFrequency (%)
3214 1
2.4%
2965 1
2.4%
2834 1
2.4%
2793 1
2.4%
2450 1
2.4%
2135 1
2.4%
1935 1
2.4%
1790 1
2.4%
1677 1
2.4%
1632 1
2.4%

일반직
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9680.4634
Minimum4831
Maximum21472
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T18:03:13.912729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4831
5-th percentile4944
Q16349
median7333
Q314172
95-th percentile19828
Maximum21472
Range16641
Interquartile range (IQR)7823

Descriptive statistics

Standard deviation4844.9401
Coefficient of variation (CV)0.50048638
Kurtosis-0.061788852
Mean9680.4634
Median Absolute Deviation (MAD)2255
Skewness1.065816
Sum396899
Variance23473444
MonotonicityNot monotonic
2023-12-12T18:03:14.088823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
9602 1
 
2.4%
6349 1
 
2.4%
8924 1
 
2.4%
7014 1
 
2.4%
6665 1
 
2.4%
7407 1
 
2.4%
5063 1
 
2.4%
5921 1
 
2.4%
4876 1
 
2.4%
7258 1
 
2.4%
Other values (31) 31
75.6%
ValueCountFrequency (%)
4831 1
2.4%
4876 1
2.4%
4944 1
2.4%
4973 1
2.4%
5063 1
2.4%
5078 1
2.4%
5495 1
2.4%
5921 1
2.4%
6023 1
2.4%
6183 1
2.4%
ValueCountFrequency (%)
21472 1
2.4%
20593 1
2.4%
19828 1
2.4%
18401 1
2.4%
15811 1
2.4%
15278 1
2.4%
15208 1
2.4%
14761 1
2.4%
14678 1
2.4%
14192 1
2.4%

경찰
Real number (ℝ)

HIGH CORRELATION 

Distinct40
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2792.7317
Minimum1250
Maximum7887
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T18:03:14.329311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1250
5-th percentile1454
Q12086
median2640
Q33102
95-th percentile4270
Maximum7887
Range6637
Interquartile range (IQR)1016

Descriptive statistics

Standard deviation1265.3978
Coefficient of variation (CV)0.45310398
Kurtosis7.4052428
Mean2792.7317
Median Absolute Deviation (MAD)529
Skewness2.353681
Sum114502
Variance1601231.7
MonotonicityNot monotonic
2023-12-12T18:03:14.516842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
3039 2
 
4.9%
2133 1
 
2.4%
1570 1
 
2.4%
2577 1
 
2.4%
2111 1
 
2.4%
3102 1
 
2.4%
1250 1
 
2.4%
2367 1
 
2.4%
1454 1
 
2.4%
2086 1
 
2.4%
Other values (30) 30
73.2%
ValueCountFrequency (%)
1250 1
2.4%
1390 1
2.4%
1454 1
2.4%
1528 1
2.4%
1570 1
2.4%
1718 1
2.4%
1877 1
2.4%
1899 1
2.4%
1937 1
2.4%
2016 1
2.4%
ValueCountFrequency (%)
7887 1
2.4%
6706 1
2.4%
4270 1
2.4%
4140 1
2.4%
3732 1
2.4%
3601 1
2.4%
3258 1
2.4%
3247 1
2.4%
3233 1
2.4%
3114 1
2.4%

소방
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct13
Distinct (%)31.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean203.12195
Minimum0
Maximum1200
Zeros29
Zeros (%)70.7%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T18:03:14.697285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3354
95-th percentile841
Maximum1200
Range1200
Interquartile range (IQR)354

Descriptive statistics

Standard deviation347.61014
Coefficient of variation (CV)1.7113371
Kurtosis0.65329654
Mean203.12195
Median Absolute Deviation (MAD)0
Skewness1.4250105
Sum8328
Variance120832.81
MonotonicityNot monotonic
2023-12-12T18:03:14.871413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 29
70.7%
258 1
 
2.4%
409 1
 
2.4%
354 1
 
2.4%
754 1
 
2.4%
660 1
 
2.4%
668 1
 
2.4%
683 1
 
2.4%
769 1
 
2.4%
794 1
 
2.4%
Other values (3) 3
 
7.3%
ValueCountFrequency (%)
0 29
70.7%
258 1
 
2.4%
354 1
 
2.4%
409 1
 
2.4%
660 1
 
2.4%
668 1
 
2.4%
683 1
 
2.4%
754 1
 
2.4%
769 1
 
2.4%
794 1
 
2.4%
ValueCountFrequency (%)
1200 1
2.4%
938 1
2.4%
841 1
2.4%
794 1
2.4%
769 1
2.4%
754 1
2.4%
683 1
2.4%
668 1
2.4%
660 1
2.4%
409 1
2.4%

교육
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8451.2195
Minimum4046
Maximum28872
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T18:03:15.081123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4046
5-th percentile4213
Q15461
median7220
Q310623
95-th percentile12907
Maximum28872
Range24826
Interquartile range (IQR)5162

Descriptive statistics

Standard deviation4333.6191
Coefficient of variation (CV)0.51278033
Kurtosis11.482944
Mean8451.2195
Median Absolute Deviation (MAD)2106
Skewness2.7071798
Sum346500
Variance18780254
MonotonicityNot monotonic
2023-12-12T18:03:15.311772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
5263 1
 
2.4%
10284 1
 
2.4%
6360 1
 
2.4%
6783 1
 
2.4%
9048 1
 
2.4%
11433 1
 
2.4%
7714 1
 
2.4%
8653 1
 
2.4%
8995 1
 
2.4%
11798 1
 
2.4%
Other values (31) 31
75.6%
ValueCountFrequency (%)
4046 1
2.4%
4051 1
2.4%
4213 1
2.4%
4346 1
2.4%
4372 1
2.4%
5014 1
2.4%
5114 1
2.4%
5229 1
2.4%
5263 1
2.4%
5351 1
2.4%
ValueCountFrequency (%)
28872 1
2.4%
14162 1
2.4%
12907 1
2.4%
12652 1
2.4%
11805 1
2.4%
11798 1
2.4%
11546 1
2.4%
11433 1
2.4%
11357 1
2.4%
11114 1
2.4%

법관검사
Real number (ℝ)

HIGH CORRELATION 

Distinct39
Distinct (%)95.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.68293
Minimum19
Maximum330
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T18:03:15.490379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19
5-th percentile26
Q174
median136
Q3166
95-th percentile214
Maximum330
Range311
Interquartile range (IQR)92

Descriptive statistics

Standard deviation67.904506
Coefficient of variation (CV)0.5360194
Kurtosis0.51243021
Mean126.68293
Median Absolute Deviation (MAD)46
Skewness0.35525696
Sum5194
Variance4611.022
MonotonicityNot monotonic
2023-12-12T18:03:15.679085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
149 2
 
4.9%
147 2
 
4.9%
224 1
 
2.4%
178 1
 
2.4%
148 1
 
2.4%
206 1
 
2.4%
212 1
 
2.4%
330 1
 
2.4%
185 1
 
2.4%
189 1
 
2.4%
Other values (29) 29
70.7%
ValueCountFrequency (%)
19 1
2.4%
22 1
2.4%
26 1
2.4%
30 1
2.4%
35 1
2.4%
37 1
2.4%
38 1
2.4%
48 1
2.4%
57 1
2.4%
60 1
2.4%
ValueCountFrequency (%)
330 1
2.4%
224 1
2.4%
214 1
2.4%
212 1
2.4%
206 1
2.4%
189 1
2.4%
188 1
2.4%
185 1
2.4%
178 1
2.4%
170 1
2.4%

기능직
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6155.2927
Minimum149
Maximum27801
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T18:03:15.853621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum149
5-th percentile363
Q12859
median4981
Q38622
95-th percentile15130
Maximum27801
Range27652
Interquartile range (IQR)5763

Descriptive statistics

Standard deviation5330.3275
Coefficient of variation (CV)0.86597466
Kurtosis5.6571183
Mean6155.2927
Median Absolute Deviation (MAD)3229
Skewness1.8912825
Sum252367
Variance28412391
MonotonicityNot monotonic
2023-12-12T18:03:16.025069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
6428 1
 
2.4%
3395 1
 
2.4%
11733 1
 
2.4%
5592 1
 
2.4%
5112 1
 
2.4%
5693 1
 
2.4%
2859 1
 
2.4%
4981 1
 
2.4%
3209 1
 
2.4%
5163 1
 
2.4%
Other values (31) 31
75.6%
ValueCountFrequency (%)
149 1
2.4%
268 1
2.4%
363 1
2.4%
368 1
2.4%
525 1
2.4%
891 1
2.4%
1051 1
2.4%
1528 1
2.4%
1752 1
2.4%
2801 1
2.4%
ValueCountFrequency (%)
27801 1
2.4%
15608 1
2.4%
15130 1
2.4%
13121 1
2.4%
11733 1
2.4%
11443 1
2.4%
9908 1
2.4%
9725 1
2.4%
8900 1
2.4%
8846 1
2.4%

공안직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct23
Distinct (%)56.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean451.41463
Minimum0
Maximum1365
Zeros19
Zeros (%)46.3%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T18:03:16.166075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median569
Q3873
95-th percentile1047
Maximum1365
Range1365
Interquartile range (IQR)873

Descriptive statistics

Standard deviation451.54374
Coefficient of variation (CV)1.000286
Kurtosis-1.5124039
Mean451.41463
Median Absolute Deviation (MAD)569
Skewness0.22098727
Sum18508
Variance203891.75
MonotonicityNot monotonic
2023-12-12T18:03:16.329079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 19
46.3%
704 1
 
2.4%
1365 1
 
2.4%
1047 1
 
2.4%
1018 1
 
2.4%
888 1
 
2.4%
800 1
 
2.4%
908 1
 
2.4%
881 1
 
2.4%
994 1
 
2.4%
Other values (13) 13
31.7%
ValueCountFrequency (%)
0 19
46.3%
497 1
 
2.4%
569 1
 
2.4%
593 1
 
2.4%
620 1
 
2.4%
639 1
 
2.4%
665 1
 
2.4%
704 1
 
2.4%
764 1
 
2.4%
800 1
 
2.4%
ValueCountFrequency (%)
1365 1
2.4%
1234 1
2.4%
1047 1
2.4%
1018 1
2.4%
994 1
2.4%
908 1
2.4%
889 1
2.4%
888 1
2.4%
881 1
2.4%
879 1
2.4%

군무원
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct23
Distinct (%)56.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean503.21951
Minimum0
Maximum1674
Zeros19
Zeros (%)46.3%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T18:03:16.527719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median615
Q3957
95-th percentile1172
Maximum1674
Range1674
Interquartile range (IQR)957

Descriptive statistics

Standard deviation509.16066
Coefficient of variation (CV)1.0118063
Kurtosis-1.370859
Mean503.21951
Median Absolute Deviation (MAD)602
Skewness0.27585463
Sum20632
Variance259244.58
MonotonicityNot monotonic
2023-12-12T18:03:16.707631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 19
46.3%
376 1
 
2.4%
1674 1
 
2.4%
1045 1
 
2.4%
993 1
 
2.4%
936 1
 
2.4%
866 1
 
2.4%
895 1
 
2.4%
836 1
 
2.4%
1090 1
 
2.4%
Other values (13) 13
31.7%
ValueCountFrequency (%)
0 19
46.3%
376 1
 
2.4%
615 1
 
2.4%
634 1
 
2.4%
684 1
 
2.4%
695 1
 
2.4%
836 1
 
2.4%
866 1
 
2.4%
895 1
 
2.4%
910 1
 
2.4%
ValueCountFrequency (%)
1674 1
2.4%
1217 1
2.4%
1172 1
2.4%
1090 1
2.4%
1072 1
2.4%
1045 1
2.4%
1042 1
2.4%
1000 1
2.4%
999 1
2.4%
993 1
2.4%

연구직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct23
Distinct (%)56.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean109.14634
Minimum0
Maximum394
Zeros19
Zeros (%)46.3%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T18:03:16.885321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median127
Q3188
95-th percentile293
Maximum394
Range394
Interquartile range (IQR)188

Descriptive statistics

Standard deviation115.5473
Coefficient of variation (CV)1.0586456
Kurtosis-0.8416079
Mean109.14634
Median Absolute Deviation (MAD)127
Skewness0.54705362
Sum4475
Variance13351.178
MonotonicityNot monotonic
2023-12-12T18:03:17.059551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 19
46.3%
169 1
 
2.4%
394 1
 
2.4%
263 1
 
2.4%
314 1
 
2.4%
256 1
 
2.4%
252 1
 
2.4%
245 1
 
2.4%
227 1
 
2.4%
204 1
 
2.4%
Other values (13) 13
31.7%
ValueCountFrequency (%)
0 19
46.3%
113 1
 
2.4%
127 1
 
2.4%
130 1
 
2.4%
132 1
 
2.4%
134 1
 
2.4%
140 1
 
2.4%
146 1
 
2.4%
147 1
 
2.4%
169 1
 
2.4%
ValueCountFrequency (%)
394 1
2.4%
314 1
2.4%
293 1
2.4%
263 1
2.4%
256 1
2.4%
252 1
2.4%
248 1
2.4%
245 1
2.4%
227 1
2.4%
204 1
2.4%

지도직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct22
Distinct (%)53.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean100.78049
Minimum0
Maximum273
Zeros19
Zeros (%)46.3%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T18:03:17.222912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median101
Q3199
95-th percentile253
Maximum273
Range273
Interquartile range (IQR)199

Descriptive statistics

Standard deviation102.53914
Coefficient of variation (CV)1.0174503
Kurtosis-1.6374374
Mean100.78049
Median Absolute Deviation (MAD)101
Skewness0.25048802
Sum4132
Variance10514.276
MonotonicityNot monotonic
2023-12-12T18:03:17.400455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 19
46.3%
214 2
 
4.9%
148 1
 
2.4%
202 1
 
2.4%
267 1
 
2.4%
247 1
 
2.4%
242 1
 
2.4%
196 1
 
2.4%
199 1
 
2.4%
273 1
 
2.4%
Other values (12) 12
29.3%
ValueCountFrequency (%)
0 19
46.3%
92 1
 
2.4%
101 1
 
2.4%
107 1
 
2.4%
127 1
 
2.4%
135 1
 
2.4%
148 1
 
2.4%
155 1
 
2.4%
163 1
 
2.4%
174 1
 
2.4%
ValueCountFrequency (%)
273 1
2.4%
267 1
2.4%
253 1
2.4%
247 1
2.4%
242 1
2.4%
226 1
2.4%
214 2
4.9%
204 1
2.4%
202 1
2.4%
199 1
2.4%

계약직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct23
Distinct (%)56.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean626.29268
Minimum0
Maximum3378
Zeros19
Zeros (%)46.3%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T18:03:17.576928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median427
Q31114
95-th percentile2054
Maximum3378
Range3378
Interquartile range (IQR)1114

Descriptive statistics

Standard deviation791.83474
Coefficient of variation (CV)1.2643206
Kurtosis2.3638623
Mean626.29268
Median Absolute Deviation (MAD)427
Skewness1.4465811
Sum25678
Variance627002.26
MonotonicityNot monotonic
2023-12-12T18:03:17.711130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 19
46.3%
78 1
 
2.4%
3378 1
 
2.4%
2346 1
 
2.4%
2054 1
 
2.4%
1413 1
 
2.4%
1611 1
 
2.4%
1381 1
 
2.4%
1370 1
 
2.4%
1124 1
 
2.4%
Other values (13) 13
31.7%
ValueCountFrequency (%)
0 19
46.3%
78 1
 
2.4%
427 1
 
2.4%
448 1
 
2.4%
476 1
 
2.4%
537 1
 
2.4%
645 1
 
2.4%
709 1
 
2.4%
887 1
 
2.4%
991 1
 
2.4%
ValueCountFrequency (%)
3378 1
2.4%
2346 1
2.4%
2054 1
2.4%
1611 1
2.4%
1413 1
2.4%
1381 1
2.4%
1378 1
2.4%
1370 1
2.4%
1144 1
2.4%
1124 1
2.4%

공중보건의
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct23
Distinct (%)56.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean754.7561
Minimum0
Maximum1933
Zeros19
Zeros (%)46.3%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T18:03:17.865235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1063
Q31358
95-th percentile1725
Maximum1933
Range1933
Interquartile range (IQR)1358

Descriptive statistics

Standard deviation736.70485
Coefficient of variation (CV)0.97608334
Kurtosis-1.7921188
Mean754.7561
Median Absolute Deviation (MAD)804
Skewness0.071300996
Sum30945
Variance542734.04
MonotonicityNot monotonic
2023-12-12T18:03:18.022006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 19
46.3%
1063 1
 
2.4%
1247 1
 
2.4%
1024 1
 
2.4%
1376 1
 
2.4%
1177 1
 
2.4%
1086 1
 
2.4%
1234 1
 
2.4%
1358 1
 
2.4%
1229 1
 
2.4%
Other values (13) 13
31.7%
ValueCountFrequency (%)
0 19
46.3%
1024 1
 
2.4%
1063 1
 
2.4%
1086 1
 
2.4%
1099 1
 
2.4%
1177 1
 
2.4%
1192 1
 
2.4%
1229 1
 
2.4%
1234 1
 
2.4%
1247 1
 
2.4%
ValueCountFrequency (%)
1933 1
2.4%
1867 1
2.4%
1725 1
2.4%
1707 1
2.4%
1673 1
2.4%
1660 1
2.4%
1610 1
2.4%
1531 1
2.4%
1479 1
2.4%
1376 1
2.4%

기타
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4995.6585
Minimum858
Maximum14351
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T18:03:18.207754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum858
5-th percentile873
Q11701
median5081
Q36682
95-th percentile11584
Maximum14351
Range13493
Interquartile range (IQR)4981

Descriptive statistics

Standard deviation3596.2712
Coefficient of variation (CV)0.71987931
Kurtosis-0.11069019
Mean4995.6585
Median Absolute Deviation (MAD)2784
Skewness0.75222449
Sum204822
Variance12933167
MonotonicityNot monotonic
2023-12-12T18:03:18.370936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
14351 1
 
2.4%
1701 1
 
2.4%
1138 1
 
2.4%
858 1
 
2.4%
924 1
 
2.4%
891 1
 
2.4%
1057 1
 
2.4%
873 1
 
2.4%
1169 1
 
2.4%
2187 1
 
2.4%
Other values (31) 31
75.6%
ValueCountFrequency (%)
858 1
2.4%
865 1
2.4%
873 1
2.4%
891 1
2.4%
924 1
2.4%
1057 1
2.4%
1123 1
2.4%
1138 1
2.4%
1169 1
2.4%
1559 1
2.4%
ValueCountFrequency (%)
14351 1
2.4%
12061 1
2.4%
11584 1
2.4%
11170 1
2.4%
10047 1
2.4%
9731 1
2.4%
9462 1
2.4%
7865 1
2.4%
7615 1
2.4%
6705 1
2.4%

Interactions

2023-12-12T18:03:10.059002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:40.271626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:42.422319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:44.793389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:46.662323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:48.435077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:50.202946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:52.399485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:54.062731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:55.925359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:58.164085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:59.812662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:01.843774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:03.990550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:06.112164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:08.007706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:10.184250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:40.386209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:42.529231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:44.910798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:46.790530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:48.547836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:50.327127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:52.511374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:54.164711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:56.081328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:58.271461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:59.911592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:02.001918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:04.129136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:06.229553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:08.151440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:10.305932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:40.567759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:42.632524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:45.038252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:46.916210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:48.644931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:50.773300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:52.618811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:54.255168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:56.218046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:58.369649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:00.040040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:02.146416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:04.249703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:06.334496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:08.269483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:10.435195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:40.762901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:42.726292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:45.168160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:47.021957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:48.752421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:50.889137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:52.721216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:54.347042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:56.331617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:58.468403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:00.166371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:02.252293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:04.374257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:06.479990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:08.407922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:10.541852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:40.915214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:42.834230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:45.285793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:47.124959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:48.853593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:51.021718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:52.815270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:54.469585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:56.458189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:58.567299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:00.301470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:02.388524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:04.479577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:06.604229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:08.554615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:10.669844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:41.080723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:42.935127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:45.402868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:47.243011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:48.967310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:51.135618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:52.910261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:54.612999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:56.570469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:58.664211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:00.441439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:02.537114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:04.587933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:06.715605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:08.698507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:10.797221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:41.257417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:43.375583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:45.519194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:47.331886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:49.078649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:51.239322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:52.999330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:54.715280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:56.680660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:58.754063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:00.569628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:02.676122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:04.687801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:06.815298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:08.825093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:10.910659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:41.413443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:43.521588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:45.625337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:47.429471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:49.197884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:51.337176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:53.096241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:54.812975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:56.779147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:58.870221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:00.713888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:02.806897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:05.165627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:06.906656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:08.949002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:11.022372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:41.515249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:43.643467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:45.738279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:47.535204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:49.304862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:51.438809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:53.222639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:54.925955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:56.879978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:58.976924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:00.838005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:02.930501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:05.261882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:07.021114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:09.078428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:11.143904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:41.624193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:43.764310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:45.856378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:47.622128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:49.403543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:51.532881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:53.321759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:55.066556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:56.994266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:59.100148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:00.956038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:03.045466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:05.362603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:07.138047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:09.190030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:11.298426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:41.735471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:44.013603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:45.973158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:47.716074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:49.545771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:51.655974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:53.425163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:55.181436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:57.143620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:59.215880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:01.074379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:03.185878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:05.460856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:07.254462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:09.319670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:11.422374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:41.863439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:44.132885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:46.100111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:47.828382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:49.709467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:51.789793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:53.520656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:55.317900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:57.282085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:59.319461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:01.213911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:03.329336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:05.570829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:07.399561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:09.423480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:11.581470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:41.983489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:44.252553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:46.223382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:47.963508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:49.807643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:51.926687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:53.624877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:55.433861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:57.401859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:59.425127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:01.370539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:03.474899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:05.688961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:07.527426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:09.551302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:11.692829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:42.086683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:44.379624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:46.333774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:48.082259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:49.897618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:52.025259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:53.716429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:55.552773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:57.505119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:59.522413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:01.486130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:03.592371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:05.794225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:07.619152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:09.649261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:11.828458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:42.205823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:44.514807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:46.442461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:48.193167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:50.003770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:52.139585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:53.820734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:55.672340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:57.638749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:59.629470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:01.611836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:03.730536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:05.904218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:07.734141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:09.774471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:12.336427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:42.314413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:44.661065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:46.555099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:48.312293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:50.114883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:52.266282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:53.945355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:55.802960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:58.067882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:59.722615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:01.730268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:03.854898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:06.019083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:07.881063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:03:09.902950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:03:18.797648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도정무직별정직일반직경찰소방교육법관검사기능직공안직군무원연구직지도직계약직공중보건의기타
연도1.0000.3960.8120.7200.4930.7410.6060.7070.6580.6260.5880.6950.6230.8570.5470.837
정무직0.3961.0000.0000.0000.0000.0000.0000.5000.0000.7530.7440.5190.6400.5540.8390.000
별정직0.8120.0001.0000.5860.6590.0000.6890.5080.7600.0000.0000.1630.0000.0000.1540.691
일반직0.7200.0000.5861.0000.4160.7180.5580.0000.7240.3020.2950.8160.5540.6110.0000.858
경찰0.4930.0000.6590.4161.0000.0880.6940.2970.9100.2900.0000.2920.0000.0000.0000.551
소방0.7410.0000.0000.7180.0881.0000.3400.0000.3030.9070.7810.8110.5830.9660.5690.761
교육0.6060.0000.6890.5580.6940.3401.0000.3250.7430.4500.3340.1500.3300.4060.3470.000
법관검사0.7070.5000.5080.0000.2970.0000.3251.0000.4800.3730.7700.7510.5130.6190.6210.567
기능직0.6580.0000.7600.7240.9100.3030.7430.4801.0000.0000.3280.7330.0000.4670.2090.633
공안직0.6260.7530.0000.3020.2900.9070.4500.3730.0001.0000.8230.7890.7780.9150.8210.597
군무원0.5880.7440.0000.2950.0000.7810.3340.7700.3280.8231.0000.9170.8710.8010.7620.235
연구직0.6950.5190.1630.8160.2920.8110.1500.7510.7330.7890.9171.0000.9220.8400.6760.700
지도직0.6230.6400.0000.5540.0000.5830.3300.5130.0000.7780.8710.9221.0000.6610.7300.549
계약직0.8570.5540.0000.6110.0000.9660.4060.6190.4670.9150.8010.8400.6611.0000.6650.763
공중보건의0.5470.8390.1540.0000.0000.5690.3470.6210.2090.8210.7620.6760.7300.6651.0000.454
기타0.8370.0000.6910.8580.5510.7610.0000.5670.6330.5970.2350.7000.5490.7630.4541.000
2023-12-12T18:03:19.006111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도정무직별정직일반직경찰소방교육법관검사기능직공안직군무원연구직지도직계약직공중보건의기타
연도1.0000.671-0.4230.4110.2060.8020.7820.778-0.5820.8860.8330.9230.8600.9450.753-0.536
정무직0.6711.000-0.446-0.100-0.1980.2480.2860.731-0.3710.7600.8340.7210.7700.7170.895-0.807
별정직-0.423-0.4461.000-0.1250.319-0.5060.034-0.1690.658-0.600-0.466-0.562-0.586-0.580-0.3740.110
일반직0.411-0.100-0.1251.0000.6870.5120.6550.315-0.0250.3320.2000.3300.3300.316-0.0300.218
경찰0.206-0.1980.3190.6871.0000.1450.5420.1550.2900.1130.0220.0630.0810.015-0.2080.039
소방0.8020.248-0.5060.5120.1451.0000.6210.380-0.7410.7180.5680.8070.6780.8300.435-0.036
교육0.7820.2860.0340.6550.5420.6211.0000.696-0.1720.5580.5540.6030.5240.6140.448-0.286
법관검사0.7780.731-0.1690.3150.1550.3800.6961.000-0.1940.6500.7040.6570.6720.6760.740-0.607
기능직-0.582-0.3710.658-0.0250.290-0.741-0.172-0.1941.000-0.688-0.581-0.727-0.630-0.741-0.4280.050
공안직0.8860.760-0.6000.3320.1130.7180.5580.650-0.6881.0000.9390.9390.9610.9360.768-0.501
군무원0.8330.834-0.4660.2000.0220.5680.5540.704-0.5810.9391.0000.8860.9200.8840.849-0.608
연구직0.9230.721-0.5620.3300.0630.8070.6030.657-0.7270.9390.8861.0000.9290.9740.773-0.475
지도직0.8600.770-0.5860.3300.0810.6780.5240.672-0.6300.9610.9200.9291.0000.9090.790-0.555
계약직0.9450.717-0.5800.3160.0150.8300.6140.676-0.7410.9360.8840.9740.9091.0000.791-0.474
공중보건의0.7530.895-0.374-0.030-0.2080.4350.4480.740-0.4280.7680.8490.7730.7900.7911.000-0.760
기타-0.536-0.8070.1100.2180.039-0.036-0.286-0.6070.050-0.501-0.608-0.475-0.555-0.474-0.7601.000

Missing values

2023-12-12T18:03:12.483375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:03:12.718007image/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

연도정무직별정직일반직경찰소방교육법관검사기능직공안직군무원연구직지도직계약직공중보건의기타
0198201048960221330526319642800000014351
119830912986623570501448634600000012061
2198401322733319370434622822400000011584
3198501424702118770421337307800000011170
4198601498483113900404638280100000010047
519870149049441528040513540790000009462
619880120050781899043723048190000009731
719890107149732016051142636810000007615
819900126161832768052296069710000005394
919910153965302946057719888460000005081
연도정무직별정직일반직경찰소방교육법관검사기능직공안직군무원연구직지도직계약직공중보건의기타
312013119125163491570354102841493395639634147135110615311701
32201464129315278427075411546135152812341042293273137813303592
33201555698141723114660129071258919941090204199112412292878
3420166965314192324766896581371752881836227196137013583154
35201710955614761297768390111661051908895245242138112342840
362018737161467826527699878149525800866252214161110863441
3720196242315208231679411114154368888936256247141311774425
38202075443184012875938113571633631018993314267205413766682
392021924091581126408411180517826810471045263202234610246705
40202212794419828373212001265222414913651674394214337812477865