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, 병정직, 일반직, 소방 , 경찰, 교육 등) 공무원연금 가입자수에 대한 데이터입니다. 1982년부터 2022년까지 연 단위로 구분되어 있습니다.
URLhttps://www.data.go.kr/data/15052955/fileData.do

Alerts

연도 is highly overall correlated with 정무직 and 13 other fieldsHigh correlation
정무직 is highly overall correlated with 연도 and 12 other fieldsHigh correlation
별정직 is highly overall correlated with 연도 and 13 other fieldsHigh correlation
일반직 is highly overall correlated with 연도 and 13 other fieldsHigh correlation
경찰 is highly overall correlated with 연도 and 12 other fieldsHigh correlation
소방 is highly overall correlated with 연도 and 9 other fieldsHigh correlation
교육 is highly overall correlated with 연도 and 13 other fieldsHigh correlation
법관검사 is highly overall correlated with 연도 and 13 other fieldsHigh correlation
기능직 is highly overall correlated with 별정직 and 5 other fieldsHigh correlation
공안직 is highly overall correlated with 연도 and 14 other fieldsHigh correlation
군무원 is highly overall correlated with 연도 and 14 other fieldsHigh correlation
연구직 is highly overall correlated with 연도 and 14 other fieldsHigh correlation
지도직 is highly overall correlated with 연도 and 12 other fieldsHigh correlation
계약직 is highly overall correlated with 연도 and 14 other fieldsHigh correlation
공중보건의 is highly overall correlated with 연도 and 12 other fieldsHigh correlation
기타 is highly overall correlated with 연도 and 11 other fieldsHigh correlation
연도 has unique valuesUnique
별정직 has unique valuesUnique
일반직 has unique valuesUnique
경찰 has unique valuesUnique
교육 has unique valuesUnique
법관검사 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 09:44:40.518144
Analysis finished2023-12-12 09:45:11.012773
Duration30.49 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
2023-12-12T18:45:11.098027image/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
2023-12-12T18:45:11.270457image/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 

Distinct21
Distinct (%)51.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean501.53659
Minimum0
Maximum2221
Zeros19
Zeros (%)46.3%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T18:45:11.426529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median141
Q3179
95-th percentile1932
Maximum2221
Range2221
Interquartile range (IQR)179

Descriptive statistics

Standard deviation796.84936
Coefficient of variation (CV)1.588816
Kurtosis-0.36525499
Mean501.53659
Median Absolute Deviation (MAD)141
Skewness1.2490107
Sum20563
Variance634968.9
MonotonicityNot monotonic
2023-12-12T18:45:11.584173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 19
46.3%
148 2
 
4.9%
144 2
 
4.9%
1678 1
 
2.4%
173 1
 
2.4%
179 1
 
2.4%
145 1
 
2.4%
141 1
 
2.4%
146 1
 
2.4%
142 1
 
2.4%
Other values (11) 11
26.8%
ValueCountFrequency (%)
0 19
46.3%
139 1
 
2.4%
141 1
 
2.4%
142 1
 
2.4%
144 2
 
4.9%
145 1
 
2.4%
146 1
 
2.4%
148 2
 
4.9%
150 1
 
2.4%
173 1
 
2.4%
ValueCountFrequency (%)
2221 1
2.4%
1938 1
2.4%
1932 1
2.4%
1916 1
2.4%
1906 1
2.4%
1905 1
2.4%
1871 1
2.4%
1703 1
2.4%
1694 1
2.4%
1678 1
2.4%

별정직
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16462.78
Minimum119
Maximum37598
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T18:45:11.786345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum119
5-th percentile1612
Q13060
median8505
Q331991
95-th percentile35994
Maximum37598
Range37479
Interquartile range (IQR)28931

Descriptive statistics

Standard deviation14062.941
Coefficient of variation (CV)0.85422634
Kurtosis-1.7385056
Mean16462.78
Median Absolute Deviation (MAD)6862
Skewness0.33205603
Sum674974
Variance1.977663 × 108
MonotonicityNot monotonic
2023-12-12T18:45:11.969665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
119 1
 
2.4%
3060 1
 
2.4%
6734 1
 
2.4%
8505 1
 
2.4%
8701 1
 
2.4%
8678 1
 
2.4%
7980 1
 
2.4%
7540 1
 
2.4%
7676 1
 
2.4%
6007 1
 
2.4%
Other values (31) 31
75.6%
ValueCountFrequency (%)
119 1
2.4%
1604 1
2.4%
1612 1
2.4%
1643 1
2.4%
1649 1
2.4%
1705 1
2.4%
1736 1
2.4%
1756 1
2.4%
1942 1
2.4%
2155 1
2.4%
ValueCountFrequency (%)
37598 1
2.4%
36624 1
2.4%
35994 1
2.4%
35755 1
2.4%
35679 1
2.4%
35627 1
2.4%
33405 1
2.4%
32599 1
2.4%
32588 1
2.4%
32325 1
2.4%

일반직
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean304949.83
Minimum195540
Maximum515371
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T18:45:12.166423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum195540
5-th percentile204523
Q1247652
median268578
Q3328206
95-th percentile479562
Maximum515371
Range319831
Interquartile range (IQR)80554

Descriptive statistics

Standard deviation93081.44
Coefficient of variation (CV)0.30523526
Kurtosis-0.32150292
Mean304949.83
Median Absolute Deviation (MAD)39292
Skewness0.98708307
Sum12502943
Variance8.6641544 × 109
MonotonicityNot monotonic
2023-12-12T18:45:12.340635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
221795 1
 
2.4%
392690 1
 
2.4%
281379 1
 
2.4%
289695 1
 
2.4%
293397 1
 
2.4%
297968 1
 
2.4%
305816 1
 
2.4%
307915 1
 
2.4%
315207 1
 
2.4%
328206 1
 
2.4%
Other values (31) 31
75.6%
ValueCountFrequency (%)
195540 1
2.4%
204521 1
2.4%
204523 1
2.4%
205675 1
2.4%
210023 1
2.4%
213018 1
2.4%
221795 1
2.4%
229286 1
2.4%
234152 1
2.4%
239387 1
2.4%
ValueCountFrequency (%)
515371 1
2.4%
500652 1
2.4%
479562 1
2.4%
467747 1
2.4%
455878 1
2.4%
444293 1
2.4%
436636 1
2.4%
429242 1
2.4%
424150 1
2.4%
392690 1
2.4%

경찰
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean112712.93
Minimum69045
Maximum143913
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T18:45:12.523388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum69045
5-th percentile72061
Q1103846
median117520
Q3129185
95-th percentile141923
Maximum143913
Range74868
Interquartile range (IQR)25339

Descriptive statistics

Standard deviation22397.812
Coefficient of variation (CV)0.19871556
Kurtosis-0.68212889
Mean112712.93
Median Absolute Deviation (MAD)13490
Skewness-0.6474723
Sum4621230
Variance5.01662 × 108
MonotonicityNot monotonic
2023-12-12T18:45:12.711509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
77888 1
 
2.4%
111765 1
 
2.4%
128406 1
 
2.4%
131010 1
 
2.4%
132541 1
 
2.4%
135302 1
 
2.4%
140055 1
 
2.4%
143913 1
 
2.4%
108836 1
 
2.4%
110715 1
 
2.4%
Other values (31) 31
75.6%
ValueCountFrequency (%)
69045 1
2.4%
69947 1
2.4%
72061 1
2.4%
75323 1
2.4%
77307 1
2.4%
77888 1
2.4%
78511 1
2.4%
81163 1
2.4%
88677 1
2.4%
96212 1
2.4%
ValueCountFrequency (%)
143913 1
2.4%
143761 1
2.4%
141923 1
2.4%
140055 1
2.4%
137488 1
2.4%
135302 1
2.4%
134240 1
2.4%
132541 1
2.4%
131154 1
2.4%
131010 1
2.4%

소방
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct13
Distinct (%)31.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13959.976
Minimum0
Maximum64124
Zeros29
Zeros (%)70.7%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T18:45:12.878909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q338303
95-th percentile57107
Maximum64124
Range64124
Interquartile range (IQR)38303

Descriptive statistics

Standard deviation22516.744
Coefficient of variation (CV)1.6129501
Kurtosis-0.52289016
Mean13959.976
Median Absolute Deviation (MAD)0
Skewness1.1157878
Sum572359
Variance5.0700374 × 108
MonotonicityIncreasing
2023-12-12T18:45:13.017724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 29
70.7%
36962 1
 
2.4%
38303 1
 
2.4%
39277 1
 
2.4%
39819 1
 
2.4%
41871 1
 
2.4%
43989 1
 
2.4%
46003 1
 
2.4%
49596 1
 
2.4%
54233 1
 
2.4%
Other values (3) 3
 
7.3%
ValueCountFrequency (%)
0 29
70.7%
36962 1
 
2.4%
38303 1
 
2.4%
39277 1
 
2.4%
39819 1
 
2.4%
41871 1
 
2.4%
43989 1
 
2.4%
46003 1
 
2.4%
49596 1
 
2.4%
54233 1
 
2.4%
ValueCountFrequency (%)
64124 1
2.4%
61075 1
2.4%
57107 1
2.4%
54233 1
2.4%
49596 1
2.4%
46003 1
2.4%
43989 1
2.4%
41871 1
2.4%
39819 1
2.4%
39277 1
2.4%

교육
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean307415.46
Minimum197387
Maximum378709
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T18:45:13.164753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum197387
5-th percentile212423
Q1276021
median300474
Q3357528
95-th percentile375767
Maximum378709
Range181322
Interquartile range (IQR)81507

Descriptive statistics

Standard deviation54662.923
Coefficient of variation (CV)0.17781449
Kurtosis-1.0536252
Mean307415.46
Median Absolute Deviation (MAD)54469
Skewness-0.35391758
Sum12604034
Variance2.9880352 × 109
MonotonicityNot monotonic
2023-12-12T18:45:13.295607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
197387 1
 
2.4%
360218 1
 
2.4%
331394 1
 
2.4%
340679 1
 
2.4%
347961 1
 
2.4%
350715 1
 
2.4%
354943 1
 
2.4%
356336 1
 
2.4%
357271 1
 
2.4%
357528 1
 
2.4%
Other values (31) 31
75.6%
ValueCountFrequency (%)
197387 1
2.4%
206296 1
2.4%
212423 1
2.4%
220190 1
2.4%
228283 1
2.4%
237625 1
2.4%
245071 1
2.4%
259266 1
2.4%
267337 1
2.4%
272337 1
2.4%
ValueCountFrequency (%)
378709 1
2.4%
377849 1
2.4%
375767 1
2.4%
373114 1
2.4%
371024 1
2.4%
367009 1
2.4%
365809 1
2.4%
363092 1
2.4%
362587 1
2.4%
360218 1
2.4%

법관검사
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3245.4634
Minimum1022
Maximum5430
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T18:45:13.505312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1022
5-th percentile1157
Q11980
median3204
Q34606
95-th percentile5326
Maximum5430
Range4408
Interquartile range (IQR)2626

Descriptive statistics

Standard deviation1446.0306
Coefficient of variation (CV)0.44555443
Kurtosis-1.4327521
Mean3245.4634
Median Absolute Deviation (MAD)1333
Skewness0.050734876
Sum133064
Variance2091004.5
MonotonicityNot monotonic
2023-12-12T18:45:13.683594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
1026 1
 
2.4%
4717 1
 
2.4%
3665 1
 
2.4%
3798 1
 
2.4%
3935 1
 
2.4%
4057 1
 
2.4%
4177 1
 
2.4%
4336 1
 
2.4%
4442 1
 
2.4%
4606 1
 
2.4%
Other values (31) 31
75.6%
ValueCountFrequency (%)
1022 1
2.4%
1026 1
2.4%
1157 1
2.4%
1336 1
2.4%
1468 1
2.4%
1506 1
2.4%
1633 1
2.4%
1720 1
2.4%
1816 1
2.4%
1871 1
2.4%
ValueCountFrequency (%)
5430 1
2.4%
5429 1
2.4%
5326 1
2.4%
5197 1
2.4%
5157 1
2.4%
5144 1
2.4%
5025 1
2.4%
4933 1
2.4%
4837 1
2.4%
4717 1
2.4%

기능직
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean106190.8
Minimum64
Maximum197907
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T18:45:13.850257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum64
5-th percentile353
Q148681
median139677
Q3158090
95-th percentile196655
Maximum197907
Range197843
Interquartile range (IQR)109409

Descriptive statistics

Standard deviation71696.766
Coefficient of variation (CV)0.67516925
Kurtosis-1.461769
Mean106190.8
Median Absolute Deviation (MAD)55586
Skewness-0.330395
Sum4353823
Variance5.1404262 × 109
MonotonicityNot monotonic
2023-12-12T18:45:14.034210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
66204 1
 
2.4%
37521 1
 
2.4%
146997 1
 
2.4%
145568 1
 
2.4%
143354 1
 
2.4%
140462 1
 
2.4%
139677 1
 
2.4%
135240 1
 
2.4%
131336 1
 
2.4%
120128 1
 
2.4%
Other values (31) 31
75.6%
ValueCountFrequency (%)
64 1
2.4%
158 1
2.4%
353 1
2.4%
674 1
2.4%
991 1
2.4%
3741 1
2.4%
4637 1
2.4%
6326 1
2.4%
7131 1
2.4%
37521 1
2.4%
ValueCountFrequency (%)
197907 1
2.4%
197112 1
2.4%
196655 1
2.4%
195263 1
2.4%
195259 1
2.4%
190278 1
2.4%
183865 1
2.4%
181356 1
2.4%
169580 1
2.4%
162159 1
2.4%

공안직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct23
Distinct (%)56.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17812.293
Minimum0
Maximum37662
Zeros19
Zeros (%)46.3%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T18:45:14.193060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median26935
Q334761
95-th percentile36856
Maximum37662
Range37662
Interquartile range (IQR)34761

Descriptive statistics

Standard deviation16969.542
Coefficient of variation (CV)0.95268715
Kurtosis-2.0064067
Mean17812.293
Median Absolute Deviation (MAD)10431
Skewness-0.079479759
Sum730304
Variance2.8796537 × 108
MonotonicityNot monotonic
2023-12-12T18:45:14.335716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 19
46.3%
26414 1
 
2.4%
37662 1
 
2.4%
37366 1
 
2.4%
36856 1
 
2.4%
36791 1
 
2.4%
35970 1
 
2.4%
35029 1
 
2.4%
36228 1
 
2.4%
36400 1
 
2.4%
Other values (13) 13
31.7%
ValueCountFrequency (%)
0 19
46.3%
26414 1
 
2.4%
26935 1
 
2.4%
27402 1
 
2.4%
28331 1
 
2.4%
28834 1
 
2.4%
30391 1
 
2.4%
31415 1
 
2.4%
31773 1
 
2.4%
32875 1
 
2.4%
ValueCountFrequency (%)
37662 1
2.4%
37366 1
2.4%
36856 1
2.4%
36791 1
2.4%
36400 1
2.4%
36228 1
2.4%
35970 1
2.4%
35666 1
2.4%
35657 1
2.4%
35029 1
2.4%

군무원
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct23
Distinct (%)56.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12165.341
Minimum0
Maximum34911
Zeros19
Zeros (%)46.3%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T18:45:14.466188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median19744
Q321008
95-th percentile28856
Maximum34911
Range34911
Interquartile range (IQR)21008

Descriptive statistics

Standard deviation11887.856
Coefficient of variation (CV)0.9771905
Kurtosis-1.5816936
Mean12165.341
Median Absolute Deviation (MAD)14232
Skewness0.1198755
Sum498779
Variance1.4132112 × 108
MonotonicityNot monotonic
2023-12-12T18:45:14.608945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 19
46.3%
19732 1
 
2.4%
34911 1
 
2.4%
33976 1
 
2.4%
28856 1
 
2.4%
26214 1
 
2.4%
24147 1
 
2.4%
22158 1
 
2.4%
22024 1
 
2.4%
21712 1
 
2.4%
Other values (13) 13
31.7%
ValueCountFrequency (%)
0 19
46.3%
19732 1
 
2.4%
19744 1
 
2.4%
19751 1
 
2.4%
19780 1
 
2.4%
20047 1
 
2.4%
20187 1
 
2.4%
20220 1
 
2.4%
20310 1
 
2.4%
20332 1
 
2.4%
ValueCountFrequency (%)
34911 1
2.4%
33976 1
2.4%
28856 1
2.4%
26214 1
2.4%
24147 1
2.4%
22158 1
2.4%
22024 1
2.4%
21712 1
2.4%
21423 1
2.4%
21402 1
2.4%

연구직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct23
Distinct (%)56.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4273.6585
Minimum0
Maximum11008
Zeros19
Zeros (%)46.3%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T18:45:14.798605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5670
Q37899
95-th percentile10148
Maximum11008
Range11008
Interquartile range (IQR)7899

Descriptive statistics

Standard deviation4187.9882
Coefficient of variation (CV)0.97995386
Kurtosis-1.7785389
Mean4273.6585
Median Absolute Deviation (MAD)5024
Skewness0.088999311
Sum175220
Variance17539245
MonotonicityIncreasing
2023-12-12T18:45:14.950040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 19
46.3%
5493 1
 
2.4%
11008 1
 
2.4%
10694 1
 
2.4%
10148 1
 
2.4%
9722 1
 
2.4%
9391 1
 
2.4%
9106 1
 
2.4%
8851 1
 
2.4%
8657 1
 
2.4%
Other values (13) 13
31.7%
ValueCountFrequency (%)
0 19
46.3%
5493 1
 
2.4%
5670 1
 
2.4%
5788 1
 
2.4%
6024 1
 
2.4%
6340 1
 
2.4%
6874 1
 
2.4%
7208 1
 
2.4%
7222 1
 
2.4%
7316 1
 
2.4%
ValueCountFrequency (%)
11008 1
2.4%
10694 1
2.4%
10148 1
2.4%
9722 1
2.4%
9391 1
2.4%
9106 1
2.4%
8851 1
2.4%
8657 1
2.4%
8340 1
2.4%
8198 1
2.4%

지도직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct21
Distinct (%)51.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2583.5122
Minimum0
Maximum5149
Zeros19
Zeros (%)46.3%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T18:45:15.099845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4548
Q34779
95-th percentile5089
Maximum5149
Range5149
Interquartile range (IQR)4779

Descriptive statistics

Standard deviation2435.6587
Coefficient of variation (CV)0.94277035
Kurtosis-2.0661223
Mean2583.5122
Median Absolute Deviation (MAD)561
Skewness-0.13968324
Sum105924
Variance5932433.3
MonotonicityNot monotonic
2023-12-12T18:45:15.239791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 19
46.3%
4613 3
 
7.3%
5109 1
 
2.4%
4878 1
 
2.4%
4861 1
 
2.4%
4779 1
 
2.4%
4715 1
 
2.4%
4648 1
 
2.4%
4604 1
 
2.4%
4548 1
 
2.4%
Other values (11) 11
26.8%
ValueCountFrequency (%)
0 19
46.3%
4519 1
 
2.4%
4548 1
 
2.4%
4604 1
 
2.4%
4613 3
 
7.3%
4648 1
 
2.4%
4650 1
 
2.4%
4661 1
 
2.4%
4715 1
 
2.4%
4722 1
 
2.4%
ValueCountFrequency (%)
5149 1
2.4%
5109 1
2.4%
5089 1
2.4%
5082 1
2.4%
5080 1
2.4%
5059 1
2.4%
5028 1
2.4%
4904 1
2.4%
4878 1
2.4%
4861 1
2.4%

계약직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct23
Distinct (%)56.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4262.5854
Minimum0
Maximum15878
Zeros19
Zeros (%)46.3%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T18:45:15.733200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2544
Q37718
95-th percentile14743
Maximum15878
Range15878
Interquartile range (IQR)7718

Descriptive statistics

Standard deviation4998.6342
Coefficient of variation (CV)1.1726766
Kurtosis-0.30178149
Mean4262.5854
Median Absolute Deviation (MAD)2544
Skewness0.90171698
Sum174766
Variance24986344
MonotonicityNot monotonic
2023-12-12T18:45:15.855071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 19
46.3%
2334 1
 
2.4%
15878 1
 
2.4%
15112 1
 
2.4%
14743 1
 
2.4%
13517 1
 
2.4%
11291 1
 
2.4%
9754 1
 
2.4%
9308 1
 
2.4%
8611 1
 
2.4%
Other values (13) 13
31.7%
ValueCountFrequency (%)
0 19
46.3%
2334 1
 
2.4%
2544 1
 
2.4%
2806 1
 
2.4%
3469 1
 
2.4%
4100 1
 
2.4%
4758 1
 
2.4%
5650 1
 
2.4%
6010 1
 
2.4%
6297 1
 
2.4%
ValueCountFrequency (%)
15878 1
2.4%
15112 1
2.4%
14743 1
2.4%
13517 1
2.4%
11291 1
2.4%
9754 1
2.4%
9308 1
2.4%
8849 1
2.4%
8611 1
2.4%
8463 1
2.4%

공중보건의
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct23
Distinct (%)56.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2256.9756
Minimum0
Maximum5281
Zeros19
Zeros (%)46.3%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T18:45:15.978833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3493
Q34062
95-th percentile5173
Maximum5281
Range5281
Interquartile range (IQR)4062

Descriptive statistics

Standard deviation2182.4601
Coefficient of variation (CV)0.96698436
Kurtosis-1.871347
Mean2256.9756
Median Absolute Deviation (MAD)1689
Skewness0.015971574
Sum92536
Variance4763132.1
MonotonicityNot monotonic
2023-12-12T18:45:16.104000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 19
46.3%
3691 1
 
2.4%
3371 1
 
2.4%
3525 1
 
2.4%
3494 1
 
2.4%
3547 1
 
2.4%
3544 1
 
2.4%
3625 1
 
2.4%
3493 1
 
2.4%
3634 1
 
2.4%
Other values (13) 13
31.7%
ValueCountFrequency (%)
0 19
46.3%
3371 1
 
2.4%
3493 1
 
2.4%
3494 1
 
2.4%
3525 1
 
2.4%
3544 1
 
2.4%
3547 1
 
2.4%
3625 1
 
2.4%
3634 1
 
2.4%
3691 1
 
2.4%
ValueCountFrequency (%)
5281 1
2.4%
5182 1
2.4%
5173 1
2.4%
5141 1
2.4%
5027 1
2.4%
5020 1
2.4%
4760 1
2.4%
4642 1
2.4%
4556 1
2.4%
4077 1
2.4%

기타
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean56891.854
Minimum7878
Maximum139153
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T18:45:16.227419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7878
5-th percentile15920
Q118359
median61823
Q366615
95-th percentile123826
Maximum139153
Range131275
Interquartile range (IQR)48256

Descriptive statistics

Standard deviation36027.116
Coefficient of variation (CV)0.63325615
Kurtosis-0.21865618
Mean56891.854
Median Absolute Deviation (MAD)19753
Skewness0.62933096
Sum2332566
Variance1.2979531 × 109
MonotonicityNot monotonic
2023-12-12T18:45:16.362399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
103135 1
 
2.4%
40987 1
 
2.4%
15920 1
 
2.4%
16099 1
 
2.4%
16164 1
 
2.4%
16460 1
 
2.4%
16577 1
 
2.4%
16737 1
 
2.4%
18243 1
 
2.4%
18359 1
 
2.4%
Other values (31) 31
75.6%
ValueCountFrequency (%)
7878 1
2.4%
9222 1
2.4%
15920 1
2.4%
16099 1
2.4%
16164 1
2.4%
16460 1
2.4%
16577 1
2.4%
16737 1
2.4%
17401 1
2.4%
18243 1
2.4%
ValueCountFrequency (%)
139153 1
2.4%
133067 1
2.4%
123826 1
2.4%
121237 1
2.4%
114242 1
2.4%
107692 1
2.4%
103135 1
2.4%
67732 1
2.4%
67017 1
2.4%
66967 1
2.4%

Interactions

2023-12-12T18:45:08.528602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:40.959328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:43.158459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:44.906707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:46.519134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:48.255508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:50.337760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:51.995341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:53.910015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:55.677517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:57.878015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:59.723902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:01.509582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:03.444034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:05.003653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:06.927018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:08.628135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:41.059792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:43.293518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:45.029453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:46.642893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:48.368740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:50.468554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:52.121322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:54.015657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:55.797736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:57.992872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:59.850030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:01.603851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:03.557008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:05.118560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:07.034654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:08.713089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:41.201763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:43.390093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:45.116696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:46.766633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:48.453080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:50.553302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:52.267108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:54.090486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:55.897932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:58.114241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:59.954770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:01.688350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:03.638236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:05.222012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:07.140946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:08.811357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:41.334788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:43.505409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:45.241279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:46.863682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:48.555193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:50.648646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:52.429591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:54.202576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:56.342248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:58.219074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:00.098248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:01.809837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:03.730545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:05.356158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:07.274117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:08.949807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:41.465150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:43.615779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:45.367092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:46.947713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:48.655944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:50.750184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:52.548456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:54.311167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:56.463487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:58.347198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:00.207824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:01.907143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:03.826031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:05.485079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:07.375893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:09.097383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:41.607829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:43.729862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:45.484754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:47.044366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:48.773631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:50.859797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:52.656612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:54.432780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:56.581570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:58.464170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:00.339624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:01.995394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:03.941606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:05.609306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:07.479461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:09.204704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:41.736154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:43.809951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:45.574063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:47.139522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:48.895984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:50.950274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:52.765483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:54.547192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:56.701221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:58.561694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:00.442949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:02.080182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:04.049748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:05.728349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:07.571539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:09.627354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:41.856248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:43.906155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:45.673825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:47.237506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:49.338853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:51.056737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:52.876502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:54.698365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:56.815879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:58.697113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:00.559244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:02.167009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:04.143862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:05.841999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:07.676386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:09.705503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:41.959686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:44.006506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:45.767871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:47.319280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:49.420960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:51.162565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:52.990755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:54.785080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:56.910916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:58.800932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:00.648166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:02.271742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:04.226627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:05.936746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:07.768788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:09.799180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:42.083047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:44.116305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:45.865578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:47.411725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:49.521529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:51.282976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:53.112274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:54.915883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:57.029887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:58.933630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:00.758061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:02.402291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:04.326530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:06.074543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:07.876631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:09.929847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:42.187155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:44.228411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:45.959917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:47.512969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:49.660463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:51.403353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:53.241672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:55.030186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:57.136546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:59.067743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:00.879065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:02.493906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:04.449842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:06.188502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:07.968214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:10.023936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:42.633755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:44.336443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:46.047616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:47.656529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:49.809895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:51.512161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:53.358955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:55.133075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:57.254138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:59.181132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:00.981883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:02.894119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:04.567466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:06.315903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:08.079472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:10.108442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:42.721209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:44.452741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:46.132292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:47.788723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:49.915194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:51.603982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:53.453317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:55.227132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:57.366382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:59.282062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:01.069306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:02.988668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:04.656794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:06.413213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:08.171026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:10.193184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:42.828436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:44.589747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:46.225872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:47.893991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:50.036132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:51.700021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:53.554492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:55.336376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:57.481239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:59.383231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:01.153874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:03.089932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:04.732659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:06.515114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:08.254219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:10.300755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:42.957616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:44.719317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:46.337177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:48.006341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:50.149874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:51.800703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:53.673204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:55.496969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:57.620032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:59.502270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:01.261052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:03.219410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:04.826992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:06.656546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:08.353741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:10.422171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:43.059006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:44.807087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:46.432480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:48.111164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:50.243633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:51.892206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:53.790823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:55.589162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:57.763546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:44:59.613796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:01.407593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:03.323745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:04.908570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:06.772610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:45:08.434636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:45:16.465633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도정무직별정직일반직경찰소방교육법관검사기능직공안직군무원연구직지도직계약직공중보건의기타
연도1.0000.7440.8040.8840.8790.8060.9600.9670.8670.9260.8310.8950.8920.9310.9670.829
정무직0.7441.0000.7500.3350.3020.0000.7170.8100.8090.9210.6110.7760.4450.9320.6540.482
별정직0.8040.7501.0000.6410.6110.3130.8680.8720.8950.9770.6760.7170.7780.6090.7070.763
일반직0.8840.3350.6411.0000.5020.9290.7800.8040.8570.8590.9030.7980.9860.8490.7880.769
경찰0.8790.3020.6110.5021.0000.2770.7880.8940.7370.6250.5720.6960.7350.5360.5350.579
소방0.8060.0000.3130.9290.2771.0000.2170.6270.6950.6650.9670.7890.9220.9460.6300.583
교육0.9600.7170.8680.7800.7880.2171.0000.9380.8490.9260.6170.7720.7640.8440.9110.878
법관검사0.9670.8100.8720.8040.8940.6270.9381.0000.8120.9940.7600.8930.9040.8880.9650.757
기능직0.8670.8090.8950.8570.7370.6950.8490.8121.0000.9520.6770.6850.7820.7620.7480.776
공안직0.9260.9210.9770.8590.6250.6650.9260.9940.9521.0000.9040.9570.7620.9670.7930.718
군무원0.8310.6110.6760.9030.5720.9670.6170.7600.6770.9041.0000.8580.9980.9370.7530.685
연구직0.8950.7760.7170.7980.6960.7890.7720.8930.6850.9570.8581.0000.8790.9190.8440.641
지도직0.8920.4450.7780.9860.7350.9220.7640.9040.7820.7620.9980.8791.0000.9540.7900.830
계약직0.9310.9320.6090.8490.5360.9460.8440.8880.7620.9670.9370.9190.9541.0000.9570.756
공중보건의0.9670.6540.7070.7880.5350.6300.9110.9650.7480.7930.7530.8440.7900.9571.0000.628
기타0.8290.4820.7630.7690.5790.5830.8780.7570.7760.7180.6850.6410.8300.7560.6281.000
2023-12-12T18:45:16.646339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도정무직별정직일반직경찰소방교육법관검사기능직공안직군무원연구직지도직계약직공중보건의기타
연도1.0000.679-0.6960.9750.8110.8040.9911.000-0.4930.9460.9330.9490.6840.9490.664-0.572
정무직0.6791.000-0.5930.6240.7870.2590.6750.680-0.2640.7200.7130.7160.9460.7160.961-0.817
별정직-0.696-0.5931.000-0.665-0.513-0.732-0.676-0.7010.795-0.835-0.856-0.838-0.632-0.838-0.5730.358
일반직0.9750.624-0.6651.0000.7780.8040.9870.976-0.4560.9190.8980.9230.6150.9230.613-0.507
경찰0.8110.787-0.5130.7781.0000.3910.7980.812-0.1910.7230.7270.7260.7960.7250.705-0.667
소방0.8040.259-0.7320.8040.3911.0000.8040.804-0.7570.8400.8330.8470.3140.8470.242-0.094
교육0.9910.675-0.6760.9870.7980.8041.0000.990-0.4790.9440.9310.9470.6790.9470.661-0.548
법관검사1.0000.680-0.7010.9760.8120.8040.9901.000-0.4930.9460.9320.9490.6840.9490.665-0.571
기능직-0.493-0.2640.795-0.456-0.191-0.757-0.479-0.4931.000-0.690-0.673-0.693-0.277-0.693-0.242-0.060
공안직0.9460.720-0.8350.9190.7230.8400.9440.946-0.6901.0000.9800.9970.7180.9960.703-0.517
군무원0.9330.713-0.8560.8980.7270.8330.9310.932-0.6730.9801.0000.9830.7430.9820.696-0.520
연구직0.9490.716-0.8380.9230.7260.8470.9470.949-0.6930.9970.9831.0000.7211.0000.700-0.512
지도직0.6840.946-0.6320.6150.7960.3140.6790.684-0.2770.7180.7430.7211.0000.7210.896-0.789
계약직0.9490.716-0.8380.9230.7250.8470.9470.949-0.6930.9960.9821.0000.7211.0000.700-0.512
공중보건의0.6640.961-0.5730.6130.7050.2420.6610.665-0.2420.7030.6960.7000.8960.7001.000-0.856
기타-0.572-0.8170.358-0.507-0.667-0.094-0.548-0.571-0.060-0.517-0.520-0.512-0.789-0.512-0.8561.000

Missing values

2023-12-12T18:45:10.652738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:45:10.921098image/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
019820119221795778880197387102666204000000103135
11983013707195540699470206296102259395000000123826
21984023861205675690450212423115755878000000114242
31985027201213018720610220190133655453000000107692
41986029224204521773070228283146854589000000121237
51987030877204523753230237625150648681000000139153
61988031335210023785110245071163367483000000133067
71989031991229286811630259266172014070100000065942
81990032588239387886770267337181615809000000055367
91991032599234152962120272337187118135600000066121
연도정무직별정직일반직경찰소방교육법관검사기능직공안직군무원연구직지도직계약직공중보건의기타
3120131443060392690111765392773602184717375213566621402819846138463388940987
322014148215542415011587739819362587483771313565721008834045198849380242268
332015148194242924211979241871363092493363263640021712865745488611363442130
342016139170543663612345443989365809502546373622822024885146049308349342070
352017142164944429312571446003367009514437413502922158910646139754362542478
362018146175645587812827549596371024515799135970241479391464811291354458772
372019141173646774713424054233373114519767436791262149722471513517354763463
3820201451612479562137488571073757675326353368562885610148477914743349465086
3920211791604500652141923610753778495430158373663397610694486115112352567017
402022173164351537114376164124378709542964376623491111008487815878337164012