Overview

Dataset statistics

Number of variables17
Number of observations49
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.4 KiB
Average record size in memory154.7 B

Variable types

Text1
Numeric15
Categorical1

Dataset

Description공무원 직종별(정무직, 별정직, 일반직, 경찰, 소방, 교육, 법관검사, 기능직, 고용직 등) 연령별 퇴직연금수급자 현황 데이터(현재 연령기준)입니다.
URLhttps://www.data.go.kr/data/15052974/fileData.do

Alerts

is highly overall correlated with 정무직 and 13 other fieldsHigh correlation
정무직 is highly overall correlated with and 10 other fieldsHigh correlation
별정직 is highly overall correlated with and 9 other fieldsHigh correlation
일반직 is highly overall correlated with and 13 other fieldsHigh correlation
경찰 is highly overall correlated with and 11 other fieldsHigh correlation
소방 is highly overall correlated with and 13 other fieldsHigh correlation
교육직 is highly overall correlated with and 13 other fieldsHigh correlation
법관검사 is highly overall correlated with and 8 other fieldsHigh correlation
기능직 is highly overall correlated with and 10 other fieldsHigh correlation
공안직 is highly overall correlated with and 13 other fieldsHigh correlation
군무원 is highly overall correlated with and 11 other fieldsHigh correlation
연구직 is highly overall correlated with and 12 other fieldsHigh correlation
지도직 is highly overall correlated with and 12 other fieldsHigh correlation
계약직 is highly overall correlated with and 7 other fieldsHigh correlation
기타 is highly overall correlated with and 10 other fieldsHigh correlation
고용직 is highly overall correlated with 정무직 and 1 other fieldsHigh correlation
구분 has unique valuesUnique
has unique valuesUnique
일반직 has unique valuesUnique
교육직 has unique valuesUnique
정무직 has 15 (30.6%) zerosZeros
별정직 has 1 (2.0%) zerosZeros
법관검사 has 1 (2.0%) zerosZeros
기능직 has 3 (6.1%) zerosZeros
군무원 has 4 (8.2%) zerosZeros
지도직 has 5 (10.2%) zerosZeros

Reproduction

Analysis started2023-12-12 03:36:01.168804
Analysis finished2023-12-12 03:36:30.374925
Duration29.21 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Text

UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size524.0 B
2023-12-12T12:36:30.527051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.0816327
Min length5

Characters and Unicode

Total characters249
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)100.0%

Sample

1st row38세 미만
2nd row38세 이상
3rd row39세
4th row40세
5th row41세
ValueCountFrequency (%)
38세 2
 
3.8%
이상 2
 
3.8%
74세 1
 
1.9%
64세 1
 
1.9%
65세 1
 
1.9%
66세 1
 
1.9%
67세 1
 
1.9%
68세 1
 
1.9%
69세 1
 
1.9%
70세 1
 
1.9%
Other values (40) 40
76.9%
2023-12-12T12:36:30.928555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
96
38.6%
49
19.7%
4 15
 
6.0%
5 15
 
6.0%
6 14
 
5.6%
7 14
 
5.6%
8 12
 
4.8%
3 8
 
3.2%
9 5
 
2.0%
0 5
 
2.0%
Other values (6) 16
 
6.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 98
39.4%
Space Separator 96
38.6%
Other Letter 55
22.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 15
15.3%
5 15
15.3%
6 14
14.3%
7 14
14.3%
8 12
12.2%
3 8
8.2%
9 5
 
5.1%
0 5
 
5.1%
1 5
 
5.1%
2 5
 
5.1%
Other Letter
ValueCountFrequency (%)
49
89.1%
2
 
3.6%
2
 
3.6%
1
 
1.8%
1
 
1.8%
Space Separator
ValueCountFrequency (%)
96
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 194
77.9%
Hangul 55
 
22.1%

Most frequent character per script

Common
ValueCountFrequency (%)
96
49.5%
4 15
 
7.7%
5 15
 
7.7%
6 14
 
7.2%
7 14
 
7.2%
8 12
 
6.2%
3 8
 
4.1%
9 5
 
2.6%
0 5
 
2.6%
1 5
 
2.6%
Hangul
ValueCountFrequency (%)
49
89.1%
2
 
3.6%
2
 
3.6%
1
 
1.8%
1
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 194
77.9%
Hangul 55
 
22.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
96
49.5%
4 15
 
7.7%
5 15
 
7.7%
6 14
 
7.2%
7 14
 
7.2%
8 12
 
6.2%
3 8
 
4.1%
9 5
 
2.6%
0 5
 
2.6%
1 5
 
2.6%
Hangul
ValueCountFrequency (%)
49
89.1%
2
 
3.6%
2
 
3.6%
1
 
1.8%
1
 
1.8%


Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11143.061
Minimum104
Maximum32004
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-12T12:36:31.084448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum104
5-th percentile216.8
Q11522
median8525
Q316919
95-th percentile30099.2
Maximum32004
Range31900
Interquartile range (IQR)15397

Descriptive statistics

Standard deviation10453.176
Coefficient of variation (CV)0.93808839
Kurtosis-0.88973665
Mean11143.061
Median Absolute Deviation (MAD)7656
Skewness0.67710385
Sum546010
Variance1.092689 × 108
MonotonicityNot monotonic
2023-12-12T12:36:31.238227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
139 1
 
2.0%
15925 1
 
2.0%
28669 1
 
2.0%
30056 1
 
2.0%
28256 1
 
2.0%
28376 1
 
2.0%
23383 1
 
2.0%
20472 1
 
2.0%
22338 1
 
2.0%
16156 1
 
2.0%
Other values (39) 39
79.6%
ValueCountFrequency (%)
104 1
2.0%
139 1
2.0%
180 1
2.0%
272 1
2.0%
359 1
2.0%
436 1
2.0%
482 1
2.0%
509 1
2.0%
589 1
2.0%
710 1
2.0%
ValueCountFrequency (%)
32004 1
2.0%
30632 1
2.0%
30128 1
2.0%
30056 1
2.0%
28669 1
2.0%
28376 1
2.0%
28256 1
2.0%
25621 1
2.0%
23383 1
2.0%
22858 1
2.0%

정무직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct28
Distinct (%)57.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.653061
Minimum0
Maximum221
Zeros15
Zeros (%)30.6%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-12T12:36:31.394026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median27
Q337
95-th percentile58.8
Maximum221
Range221
Interquartile range (IQR)37

Descriptive statistics

Standard deviation34.203771
Coefficient of variation (CV)1.2832962
Kurtosis21.643767
Mean26.653061
Median Absolute Deviation (MAD)16
Skewness3.8954467
Sum1306
Variance1169.898
MonotonicityNot monotonic
2023-12-12T12:36:31.543965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0 15
30.6%
30 3
 
6.1%
43 3
 
6.1%
37 2
 
4.1%
27 2
 
4.1%
36 2
 
4.1%
221 1
 
2.0%
32 1
 
2.0%
38 1
 
2.0%
29 1
 
2.0%
Other values (18) 18
36.7%
ValueCountFrequency (%)
0 15
30.6%
2 1
 
2.0%
3 1
 
2.0%
6 1
 
2.0%
15 1
 
2.0%
22 1
 
2.0%
23 1
 
2.0%
24 1
 
2.0%
25 1
 
2.0%
27 2
 
4.1%
ValueCountFrequency (%)
221 1
 
2.0%
65 1
 
2.0%
64 1
 
2.0%
51 1
 
2.0%
47 1
 
2.0%
43 3
6.1%
42 1
 
2.0%
40 1
 
2.0%
39 1
 
2.0%
38 1
 
2.0%

별정직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct41
Distinct (%)83.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean186.10204
Minimum0
Maximum1842
Zeros1
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-12T12:36:31.702502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q16
median39
Q3297
95-th percentile515.8
Maximum1842
Range1842
Interquartile range (IQR)291

Descriptive statistics

Standard deviation303.04663
Coefficient of variation (CV)1.6283896
Kurtosis18.148671
Mean186.10204
Median Absolute Deviation (MAD)38
Skewness3.6253177
Sum9119
Variance91837.26
MonotonicityNot monotonic
2023-12-12T12:36:31.869086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
3 3
 
6.1%
1 3
 
6.1%
2 2
 
4.1%
5 2
 
4.1%
9 2
 
4.1%
294 2
 
4.1%
341 1
 
2.0%
264 1
 
2.0%
352 1
 
2.0%
273 1
 
2.0%
Other values (31) 31
63.3%
ValueCountFrequency (%)
0 1
 
2.0%
1 3
6.1%
2 2
4.1%
3 3
6.1%
4 1
 
2.0%
5 2
4.1%
6 1
 
2.0%
7 1
 
2.0%
9 2
4.1%
10 1
 
2.0%
ValueCountFrequency (%)
1842 1
2.0%
616 1
2.0%
533 1
2.0%
490 1
2.0%
488 1
2.0%
476 1
2.0%
446 1
2.0%
366 1
2.0%
364 1
2.0%
360 1
2.0%

일반직
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3960.7755
Minimum36
Maximum15180
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-12T12:36:32.067252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36
5-th percentile90.6
Q1387
median2119
Q34411
95-th percentile14280.8
Maximum15180
Range15144
Interquartile range (IQR)4024

Descriptive statistics

Standard deviation4679.1948
Coefficient of variation (CV)1.1813835
Kurtosis0.6119935
Mean3960.7755
Median Absolute Deviation (MAD)1881
Skewness1.3813977
Sum194078
Variance21894864
MonotonicityNot monotonic
2023-12-12T12:36:32.322204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
36 1
 
2.0%
4372 1
 
2.0%
13700 1
 
2.0%
13493 1
 
2.0%
12118 1
 
2.0%
11753 1
 
2.0%
8709 1
 
2.0%
5140 1
 
2.0%
5653 1
 
2.0%
4175 1
 
2.0%
Other values (39) 39
79.6%
ValueCountFrequency (%)
36 1
2.0%
37 1
2.0%
77 1
2.0%
111 1
2.0%
179 1
2.0%
214 1
2.0%
223 1
2.0%
238 1
2.0%
250 1
2.0%
261 1
2.0%
ValueCountFrequency (%)
15180 1
2.0%
14996 1
2.0%
14668 1
2.0%
13700 1
2.0%
13493 1
2.0%
12118 1
2.0%
12073 1
2.0%
11753 1
2.0%
8709 1
2.0%
6339 1
2.0%

경찰
Real number (ℝ)

HIGH CORRELATION 

Distinct46
Distinct (%)93.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean964.53061
Minimum5
Maximum3308
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-12T12:36:32.870560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile9.4
Q135
median641
Q31312
95-th percentile2802
Maximum3308
Range3303
Interquartile range (IQR)1277

Descriptive statistics

Standard deviation981.14001
Coefficient of variation (CV)1.0172202
Kurtosis-0.48027606
Mean964.53061
Median Absolute Deviation (MAD)622
Skewness0.81682108
Sum47262
Variance962635.71
MonotonicityNot monotonic
2023-12-12T12:36:33.064456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
13 2
 
4.1%
16 2
 
4.1%
5 2
 
4.1%
1950 1
 
2.0%
1222 1
 
2.0%
3308 1
 
2.0%
2902 1
 
2.0%
2323 1
 
2.0%
1991 1
 
2.0%
1967 1
 
2.0%
Other values (36) 36
73.5%
ValueCountFrequency (%)
5 2
4.1%
7 1
2.0%
13 2
4.1%
14 1
2.0%
15 1
2.0%
16 2
4.1%
19 1
2.0%
25 1
2.0%
33 1
2.0%
35 1
2.0%
ValueCountFrequency (%)
3308 1
2.0%
3057 1
2.0%
2902 1
2.0%
2652 1
2.0%
2561 1
2.0%
2448 1
2.0%
2323 1
2.0%
2191 1
2.0%
2075 1
2.0%
1991 1
2.0%

소방
Real number (ℝ)

HIGH CORRELATION 

Distinct39
Distinct (%)79.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean180.02041
Minimum2
Maximum832
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-12T12:36:33.276633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q110
median76
Q3219
95-th percentile685.6
Maximum832
Range830
Interquartile range (IQR)209

Descriptive statistics

Standard deviation231.00464
Coefficient of variation (CV)1.2832136
Kurtosis1.0293969
Mean180.02041
Median Absolute Deviation (MAD)71
Skewness1.4639695
Sum8821
Variance53363.145
MonotonicityNot monotonic
2023-12-12T12:36:33.458975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
2 5
 
10.2%
5 3
 
6.1%
50 2
 
4.1%
211 2
 
4.1%
73 2
 
4.1%
6 2
 
4.1%
44 1
 
2.0%
90 1
 
2.0%
319 1
 
2.0%
332 1
 
2.0%
Other values (29) 29
59.2%
ValueCountFrequency (%)
2 5
10.2%
5 3
6.1%
6 2
 
4.1%
7 1
 
2.0%
8 1
 
2.0%
10 1
 
2.0%
11 1
 
2.0%
14 1
 
2.0%
20 1
 
2.0%
34 1
 
2.0%
ValueCountFrequency (%)
832 1
2.0%
755 1
2.0%
710 1
2.0%
649 1
2.0%
567 1
2.0%
549 1
2.0%
537 1
2.0%
516 1
2.0%
441 1
2.0%
332 1
2.0%

교육직
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3467.4694
Minimum37
Maximum8813
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-12T12:36:33.638973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37
5-th percentile61
Q1146
median3395
Q36222
95-th percentile8204.2
Maximum8813
Range8776
Interquartile range (IQR)6076

Descriptive statistics

Standard deviation3073.2381
Coefficient of variation (CV)0.88630576
Kurtosis-1.4326075
Mean3467.4694
Median Absolute Deviation (MAD)3179
Skewness0.26183623
Sum169906
Variance9444792.3
MonotonicityNot monotonic
2023-12-12T12:36:33.860785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
48 1
 
2.0%
5518 1
 
2.0%
7088 1
 
2.0%
7742 1
 
2.0%
7393 1
 
2.0%
8188 1
 
2.0%
7439 1
 
2.0%
7307 1
 
2.0%
8012 1
 
2.0%
5899 1
 
2.0%
Other values (39) 39
79.6%
ValueCountFrequency (%)
37 1
2.0%
48 1
2.0%
53 1
2.0%
73 1
2.0%
79 1
2.0%
94 1
2.0%
106 1
2.0%
115 1
2.0%
120 1
2.0%
124 1
2.0%
ValueCountFrequency (%)
8813 1
2.0%
8617 1
2.0%
8215 1
2.0%
8188 1
2.0%
8012 1
2.0%
7742 1
2.0%
7439 1
2.0%
7393 1
2.0%
7307 1
2.0%
7088 1
2.0%

법관검사
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct38
Distinct (%)77.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42.489796
Minimum0
Maximum99
Zeros1
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-12T12:36:34.033289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.4
Q124
median37
Q366
95-th percentile86.2
Maximum99
Range99
Interquartile range (IQR)42

Descriptive statistics

Standard deviation27.107904
Coefficient of variation (CV)0.6379862
Kurtosis-0.99013395
Mean42.489796
Median Absolute Deviation (MAD)21
Skewness0.24659937
Sum2082
Variance734.83844
MonotonicityNot monotonic
2023-12-12T12:36:34.207056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
28 3
 
6.1%
57 2
 
4.1%
67 2
 
4.1%
9 2
 
4.1%
2 2
 
4.1%
24 2
 
4.1%
31 2
 
4.1%
29 2
 
4.1%
30 2
 
4.1%
22 2
 
4.1%
Other values (28) 28
57.1%
ValueCountFrequency (%)
0 1
2.0%
2 2
4.1%
3 1
2.0%
6 1
2.0%
9 2
4.1%
11 1
2.0%
14 1
2.0%
17 1
2.0%
22 2
4.1%
24 2
4.1%
ValueCountFrequency (%)
99 1
2.0%
91 1
2.0%
87 1
2.0%
85 1
2.0%
84 1
2.0%
81 1
2.0%
74 1
2.0%
71 1
2.0%
69 1
2.0%
68 1
2.0%

기능직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct47
Distinct (%)95.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1162.2449
Minimum0
Maximum3589
Zeros3
Zeros (%)6.1%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-12T12:36:34.419185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.4
Q1734
median1000
Q31534
95-th percentile2669.4
Maximum3589
Range3589
Interquartile range (IQR)800

Descriptive statistics

Standard deviation916.09906
Coefficient of variation (CV)0.78821517
Kurtosis0.1181207
Mean1162.2449
Median Absolute Deviation (MAD)499
Skewness0.76544436
Sum56950
Variance839237.48
MonotonicityNot monotonic
2023-12-12T12:36:34.624546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
0 3
 
6.1%
1 1
 
2.0%
1339 1
 
2.0%
1346 1
 
2.0%
1534 1
 
2.0%
1404 1
 
2.0%
3270 1
 
2.0%
3589 1
 
2.0%
2596 1
 
2.0%
2661 1
 
2.0%
Other values (37) 37
75.5%
ValueCountFrequency (%)
0 3
6.1%
1 1
 
2.0%
7 1
 
2.0%
17 1
 
2.0%
28 1
 
2.0%
40 1
 
2.0%
79 1
 
2.0%
163 1
 
2.0%
312 1
 
2.0%
501 1
 
2.0%
ValueCountFrequency (%)
3589 1
2.0%
3270 1
2.0%
2675 1
2.0%
2661 1
2.0%
2637 1
2.0%
2596 1
2.0%
2573 1
2.0%
2488 1
2.0%
2047 1
2.0%
1692 1
2.0%

고용직
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)10.2%
Missing0
Missing (%)0.0%
Memory size524.0 B
0
35 
1
2
 
3
3
 
2
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)2.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 35
71.4%
1 8
 
16.3%
2 3
 
6.1%
3 2
 
4.1%
4 1
 
2.0%

Length

2023-12-12T12:36:34.789745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:36:34.933199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 35
71.4%
1 8
 
16.3%
2 3
 
6.1%
3 2
 
4.1%
4 1
 
2.0%

공안직
Real number (ℝ)

HIGH CORRELATION 

Distinct45
Distinct (%)91.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean295.7551
Minimum1
Maximum804
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-12T12:36:35.058690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.8
Q126
median211
Q3511
95-th percentile755.4
Maximum804
Range803
Interquartile range (IQR)485

Descriptive statistics

Standard deviation265.67293
Coefficient of variation (CV)0.89828689
Kurtosis-1.2266743
Mean295.7551
Median Absolute Deviation (MAD)203
Skewness0.4447429
Sum14492
Variance70582.105
MonotonicityNot monotonic
2023-12-12T12:36:35.222324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
7 2
 
4.1%
12 2
 
4.1%
468 2
 
4.1%
511 2
 
4.1%
1 1
 
2.0%
489 1
 
2.0%
774 1
 
2.0%
699 1
 
2.0%
586 1
 
2.0%
535 1
 
2.0%
Other values (35) 35
71.4%
ValueCountFrequency (%)
1 1
2.0%
2 1
2.0%
3 1
2.0%
5 1
2.0%
7 2
4.1%
8 1
2.0%
11 1
2.0%
12 2
4.1%
19 1
2.0%
20 1
2.0%
ValueCountFrequency (%)
804 1
2.0%
774 1
2.0%
761 1
2.0%
747 1
2.0%
699 1
2.0%
672 1
2.0%
654 1
2.0%
635 1
2.0%
622 1
2.0%
586 1
2.0%

군무원
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct41
Distinct (%)83.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean293.40816
Minimum0
Maximum924
Zeros4
Zeros (%)8.2%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-12T12:36:35.414589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q19
median85
Q3649
95-th percentile906.8
Maximum924
Range924
Interquartile range (IQR)640

Descriptive statistics

Standard deviation355.52941
Coefficient of variation (CV)1.211723
Kurtosis-1.1101803
Mean293.40816
Median Absolute Deviation (MAD)85
Skewness0.80808589
Sum14377
Variance126401.16
MonotonicityNot monotonic
2023-12-12T12:36:35.598173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
0 4
 
8.2%
1 2
 
4.1%
7 2
 
4.1%
914 2
 
4.1%
4 2
 
4.1%
10 2
 
4.1%
2 1
 
2.0%
697 1
 
2.0%
924 1
 
2.0%
868 1
 
2.0%
Other values (31) 31
63.3%
ValueCountFrequency (%)
0 4
8.2%
1 2
4.1%
2 1
 
2.0%
4 2
4.1%
7 2
4.1%
8 1
 
2.0%
9 1
 
2.0%
10 2
4.1%
11 1
 
2.0%
15 1
 
2.0%
ValueCountFrequency (%)
924 1
2.0%
914 2
4.1%
896 1
2.0%
871 1
2.0%
868 1
2.0%
862 1
2.0%
860 1
2.0%
858 1
2.0%
781 1
2.0%
721 1
2.0%

연구직
Real number (ℝ)

HIGH CORRELATION 

Distinct40
Distinct (%)81.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean66.734694
Minimum1
Maximum260
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-12T12:36:35.771811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q19
median46
Q386
95-th percentile217.2
Maximum260
Range259
Interquartile range (IQR)77

Descriptive statistics

Standard deviation72.239698
Coefficient of variation (CV)1.0824909
Kurtosis0.41755117
Mean66.734694
Median Absolute Deviation (MAD)38
Skewness1.2285257
Sum3270
Variance5218.574
MonotonicityNot monotonic
2023-12-12T12:36:35.947686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
7 4
 
8.2%
1 2
 
4.1%
4 2
 
4.1%
9 2
 
4.1%
3 2
 
4.1%
41 2
 
4.1%
31 2
 
4.1%
76 1
 
2.0%
98 1
 
2.0%
60 1
 
2.0%
Other values (30) 30
61.2%
ValueCountFrequency (%)
1 2
4.1%
3 2
4.1%
4 2
4.1%
6 1
 
2.0%
7 4
8.2%
8 1
 
2.0%
9 2
4.1%
10 1
 
2.0%
11 1
 
2.0%
13 1
 
2.0%
ValueCountFrequency (%)
260 1
2.0%
219 1
2.0%
218 1
2.0%
216 1
2.0%
212 1
2.0%
199 1
2.0%
158 1
2.0%
155 1
2.0%
152 1
2.0%
142 1
2.0%

지도직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct35
Distinct (%)71.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean94.142857
Minimum0
Maximum399
Zeros5
Zeros (%)10.2%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-12T12:36:36.120226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median77
Q3164
95-th percentile271.2
Maximum399
Range399
Interquartile range (IQR)162

Descriptive statistics

Standard deviation100.11868
Coefficient of variation (CV)1.0634761
Kurtosis0.2717746
Mean94.142857
Median Absolute Deviation (MAD)75
Skewness0.89971612
Sum4613
Variance10023.75
MonotonicityNot monotonic
2023-12-12T12:36:36.326017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
1 6
 
12.2%
0 5
 
10.2%
2 3
 
6.1%
107 2
 
4.1%
5 2
 
4.1%
10 2
 
4.1%
133 1
 
2.0%
164 1
 
2.0%
175 1
 
2.0%
218 1
 
2.0%
Other values (25) 25
51.0%
ValueCountFrequency (%)
0 5
10.2%
1 6
12.2%
2 3
6.1%
5 2
 
4.1%
7 1
 
2.0%
10 2
 
4.1%
13 1
 
2.0%
18 1
 
2.0%
25 1
 
2.0%
28 1
 
2.0%
ValueCountFrequency (%)
399 1
2.0%
285 1
2.0%
280 1
2.0%
258 1
2.0%
255 1
2.0%
218 1
2.0%
205 1
2.0%
200 1
2.0%
190 1
2.0%
175 1
2.0%

계약직
Real number (ℝ)

HIGH CORRELATION 

Distinct44
Distinct (%)89.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49.877551
Minimum1
Maximum137
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-12T12:36:36.556085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q120
median40
Q366
95-th percentile132
Maximum137
Range136
Interquartile range (IQR)46

Descriptive statistics

Standard deviation39.767361
Coefficient of variation (CV)0.7972998
Kurtosis-0.057932913
Mean49.877551
Median Absolute Deviation (MAD)23
Skewness0.95586551
Sum2444
Variance1581.443
MonotonicityNot monotonic
2023-12-12T12:36:36.764221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
44 2
 
4.1%
3 2
 
4.1%
24 2
 
4.1%
34 2
 
4.1%
52 2
 
4.1%
26 1
 
2.0%
100 1
 
2.0%
111 1
 
2.0%
89 1
 
2.0%
75 1
 
2.0%
Other values (34) 34
69.4%
ValueCountFrequency (%)
1 1
2.0%
2 1
2.0%
3 2
4.1%
5 1
2.0%
9 1
2.0%
11 1
2.0%
12 1
2.0%
14 1
2.0%
15 1
2.0%
16 1
2.0%
ValueCountFrequency (%)
137 1
2.0%
135 1
2.0%
134 1
2.0%
129 1
2.0%
127 1
2.0%
126 1
2.0%
111 1
2.0%
100 1
2.0%
89 1
2.0%
80 1
2.0%

기타
Real number (ℝ)

HIGH CORRELATION 

Distinct45
Distinct (%)91.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean352.36735
Minimum7
Maximum1745
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-12T12:36:36.974095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile8.4
Q122
median101
Q3422
95-th percentile1444.2
Maximum1745
Range1738
Interquartile range (IQR)400

Descriptive statistics

Standard deviation510.86453
Coefficient of variation (CV)1.4498067
Kurtosis1.2042731
Mean352.36735
Median Absolute Deviation (MAD)92
Skewness1.6013358
Sum17266
Variance260982.57
MonotonicityNot monotonic
2023-12-12T12:36:37.138469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
8 2
 
4.1%
18 2
 
4.1%
9 2
 
4.1%
204 2
 
4.1%
19 1
 
2.0%
294 1
 
2.0%
1365 1
 
2.0%
1230 1
 
2.0%
1170 1
 
2.0%
956 1
 
2.0%
Other values (35) 35
71.4%
ValueCountFrequency (%)
7 1
2.0%
8 2
4.1%
9 2
4.1%
12 1
2.0%
15 1
2.0%
18 2
4.1%
19 1
2.0%
20 1
2.0%
21 1
2.0%
22 1
2.0%
ValueCountFrequency (%)
1745 1
2.0%
1674 1
2.0%
1497 1
2.0%
1365 1
2.0%
1314 1
2.0%
1298 1
2.0%
1230 1
2.0%
1170 1
2.0%
956 1
2.0%
477 1
2.0%

Interactions

2023-12-12T12:36:28.459066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:01.800760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:04.025522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:06.141791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:07.888317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:09.458808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:11.384375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:12.970595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:14.698625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:16.658493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:18.841708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:20.779634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:22.460109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:24.135236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:26.403081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:28.597365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:01.899080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:04.167455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:06.288973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:08.001209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:09.562735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:11.510426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:13.066265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:14.838892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:16.773429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:18.957781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:20.919850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:22.553834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:24.240213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:26.529957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:28.701691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:01.981879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:04.284991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:06.416101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:08.115536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:09.641078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:11.631577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:13.162540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:14.971635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:16.870687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:19.084822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:21.038786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:22.637175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:24.334954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:26.629465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:28.826510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:02.089558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:04.415192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:06.540400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:08.242173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:09.733579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:11.762595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:13.267180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:15.096012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:16.985500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:19.236147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:21.171010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:22.783526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:24.438676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:26.762264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:28.933888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:02.211774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:04.559111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:06.677900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:08.345031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:09.816383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:11.875992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:13.384166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:15.220116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:17.122481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:19.361435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:21.294214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:22.909038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:24.567159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:26.909127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:29.065374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:02.371694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:04.692683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:06.789343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:08.450505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:09.891176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:11.980370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:13.497708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:15.347097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:17.254036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:19.477058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:21.402775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:23.011556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:24.670862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:27.050871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:29.170033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:02.507342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:04.827359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:06.899049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:08.571051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:09.961156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:12.085103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:13.590801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:15.465969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:17.361330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:19.576981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:21.497432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:23.120662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:24.780144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:27.153684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:29.262471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:02.602096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:04.946044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:07.014004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:08.664875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:10.039270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:12.183588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:13.671727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:15.586596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:17.520486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:19.699434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:21.602325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:23.216060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:24.889711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:27.279836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:29.348446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:02.720209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:05.078936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:07.122211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:08.755023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:10.135277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:12.281659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:13.768189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:15.720291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:17.634967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:19.817136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:21.716494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:23.328262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:25.024324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:27.416076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:29.447929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:02.862866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:05.229606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:07.213301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:08.855945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:10.241409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:12.378113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:13.896491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:15.853744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:17.778737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:19.930279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:21.829834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:23.469256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:25.166826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:27.575515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:29.552485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:03.351763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:05.423726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:07.338048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:08.973008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:10.713339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:12.462473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:14.036004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:16.027907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:17.905338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:20.053288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:21.949436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:23.579151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:25.292884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:27.738299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:29.636648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:03.467337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:05.571041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:07.436726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:09.070511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:10.834716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:12.540701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:14.147105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:16.155725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:18.008894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:20.182618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:22.049631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:23.663949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:25.411611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:27.858968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:29.728506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:03.611133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:05.694202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:07.534593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:09.158460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:10.981695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:12.626502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:14.265603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:16.297469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:18.126740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:20.315850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:22.156925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:23.764527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:25.536679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:27.990652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:29.835273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:03.759459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:05.839679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:07.642410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:09.250340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:11.115433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:12.748270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:14.396405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:16.418887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:18.246259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:20.491342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:22.258181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:23.907063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:25.685598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:28.138282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:29.938145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:03.885943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:06.006299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:07.774486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:09.360307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:11.252182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:12.858487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:14.548302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:16.540828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:18.373965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:20.633904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:22.358667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:24.037188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:25.830665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:36:28.289862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T12:36:37.269545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분정무직별정직일반직경찰소방교육직법관검사기능직고용직공안직군무원연구직지도직계약직기타
구분1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
1.0001.0000.8180.9090.9010.8100.8850.9430.6540.8480.7450.9040.8690.9250.7830.8660.820
정무직1.0000.8181.0000.7130.9360.8950.6940.7820.4460.6240.6560.7660.5470.9520.8750.6620.713
별정직1.0000.9090.7131.0000.8160.7730.4750.8410.6080.6260.8180.8140.2610.9460.8210.0000.000
일반직1.0000.9010.9360.8161.0000.9620.9650.7280.5660.9060.6830.8040.8450.9360.9390.8230.862
경찰1.0000.8100.8950.7730.9621.0000.9170.8110.6480.8530.4610.7400.7760.8750.8760.7670.780
소방1.0000.8850.6940.4750.9650.9171.0000.7100.6040.8770.3710.8040.9010.8290.8680.7760.932
교육직1.0000.9430.7820.8410.7280.8110.7101.0000.6610.7240.3600.8920.7670.8570.6110.7200.697
법관검사1.0000.6540.4460.6080.5660.6480.6040.6611.0000.5490.3030.7880.2990.7490.3780.7160.593
기능직1.0000.8480.6240.6260.9060.8530.8770.7240.5491.0000.5940.7450.9250.7030.8670.6200.628
고용직1.0000.7450.6560.8180.6830.4610.3710.3600.3030.5941.0000.6110.6450.7970.7950.0000.000
공안직1.0000.9040.7660.8140.8040.7400.8040.8920.7880.7450.6111.0000.7730.8490.6530.8320.774
군무원1.0000.8690.5470.2610.8450.7760.9010.7670.2990.9250.6450.7731.0000.7640.7840.6760.660
연구직1.0000.9250.9520.9460.9360.8750.8290.8570.7490.7030.7970.8490.7641.0000.8630.8670.759
지도직1.0000.7830.8750.8210.9390.8760.8680.6110.3780.8670.7950.6530.7840.8631.0000.5850.728
계약직1.0000.8660.6620.0000.8230.7670.7760.7200.7160.6200.0000.8320.6760.8670.5851.0000.897
기타1.0000.8200.7130.0000.8620.7800.9320.6970.5930.6280.0000.7740.6600.7590.7280.8971.000
2023-12-12T12:36:37.473957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정무직별정직일반직경찰소방교육직법관검사기능직공안직군무원연구직지도직계약직기타고용직
1.0000.8160.6810.9980.9740.9710.9820.5450.8090.9630.7880.9850.9440.5550.7510.375
정무직0.8161.0000.8550.8120.8480.7590.8360.3090.8010.7750.4790.8330.8690.1350.3810.580
별정직0.6810.8551.0000.6700.7250.5890.7070.1620.8250.5910.2570.7010.764-0.1400.1210.442
일반직0.9980.8120.6701.0000.9690.9720.9790.5590.7980.9660.7880.9840.9380.5630.7550.457
경찰0.9740.8480.7250.9691.0000.9410.9490.4950.8230.9410.7600.9710.9310.4810.6870.268
소방0.9710.7590.5890.9720.9411.0000.9410.5810.7580.9790.8540.9500.8930.6440.8290.206
교육직0.9820.8360.7070.9790.9490.9411.0000.5370.8330.9390.7470.9600.9350.5070.7140.134
법관검사0.5450.3090.1620.5590.4950.5810.5371.0000.2700.6270.5390.5020.4220.7040.7040.105
기능직0.8090.8010.8250.7980.8230.7580.8330.2701.0000.7350.6110.8030.8140.1940.4530.373
공안직0.9630.7750.5910.9660.9410.9790.9390.6270.7351.0000.8440.9410.8850.6560.8270.274
군무원0.7880.4790.2570.7880.7600.8540.7470.5390.6110.8441.0000.7380.6420.8090.9190.419
연구직0.9850.8330.7010.9840.9710.9500.9600.5020.8030.9410.7381.0000.9460.4940.6960.423
지도직0.9440.8690.7640.9380.9310.8930.9350.4220.8140.8850.6420.9461.0000.3660.6040.588
계약직0.5550.135-0.1400.5630.4810.6440.5070.7040.1940.6560.8090.4940.3661.0000.9300.000
기타0.7510.3810.1210.7550.6870.8290.7140.7040.4530.8270.9190.6960.6040.9301.0000.000
고용직0.3750.5800.4420.4570.2680.2060.1340.1050.3730.2740.4190.4230.5880.0000.0001.000

Missing values

2023-12-12T12:36:30.095978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:36:30.300291image/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

구분정무직별정직일반직경찰소방교육직법관검사기능직고용직공안직군무원연구직지도직계약직기타
038세 미만13903361324800011101519
138세 이상10401375237200211097
239세180007752533005430208
340세2720211116579210710411618
441세35904179192731170311402422
542세43601214136949170124713325
643세509012501510115628077713230
744세482032381421069400128802418
845세589022617612017790119323735
946세7100327316514631163087713020
구분정무직별정직일반직경찰소방교육직법관검사기능직고용직공안직군무원연구직지도직계약직기타
3976세127943536433191273152440522204734013247620026147
4077세10253313412578116310436232816800258247551071424
4178세101623336024641120763843241692119918251771228
4279세9439374902348107980352826143612054553721821
4380세109624261627001191734193301686022310651071115
4481세8525294882119816573395281233017824112928
4582세6976384461777596612873378490128048106512
4683세7142325331867687442603241004015904613139
4784세606143476153861634221914839011604111519
4885세 이상2285822118426339195090881367257343760158399323