Overview

Dataset statistics

Number of variables17
Number of observations42
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.4 KiB
Average record size in memory155.1 B

Variable types

Text1
Numeric15
Categorical1

Dataset

Description공무원이 근무한 연수와 직종별(정무직,별정직,일반직,경찰,소방,교육직,연구직 등) 공무원연금 가입자 수 데이터입니다.
URLhttps://www.data.go.kr/data/15053031/fileData.do

Alerts

is highly overall correlated with 별정직 and 12 other fieldsHigh correlation
별정직 is highly overall correlated with and 12 other fieldsHigh correlation
일반직 is highly overall correlated with and 11 other fieldsHigh correlation
경찰 is highly overall correlated with and 10 other fieldsHigh correlation
소방 is highly overall correlated with and 11 other fieldsHigh correlation
교육직 is highly overall correlated with and 9 other fieldsHigh correlation
법관검사 is highly overall correlated with and 5 other fieldsHigh correlation
공안직 is highly overall correlated with and 11 other fieldsHigh correlation
군무원 is highly overall correlated with and 10 other fieldsHigh correlation
연구직 is highly overall correlated with and 12 other fieldsHigh correlation
지도직 is highly overall correlated with and 11 other fieldsHigh correlation
계약직 is highly overall correlated with and 12 other fieldsHigh correlation
공중보건의 is highly overall correlated with and 9 other fieldsHigh correlation
기타 is highly overall correlated with and 11 other fieldsHigh correlation
기능직 is highly imbalanced (54.4%)Imbalance
구분 has unique valuesUnique
has unique valuesUnique
일반직 has unique valuesUnique
경찰 has unique valuesUnique
소방 has unique valuesUnique
교육직 has unique valuesUnique
공안직 has unique valuesUnique
군무원 has unique valuesUnique
기타 has unique valuesUnique
정무직 has 17 (40.5%) zerosZeros
별정직 has 3 (7.1%) zerosZeros
지도직 has 1 (2.4%) zerosZeros
공중보건의 has 33 (78.6%) zerosZeros

Reproduction

Analysis started2023-12-12 04:09:16.110438
Analysis finished2023-12-12 04:09:42.550684
Duration26.44 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Text

UNIQUE 

Distinct42
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size468.0 B
2023-12-12T13:09:42.746960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3
Min length2

Characters and Unicode

Total characters126
Distinct characters17
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)100.0%

Sample

1st row1년미만
2nd row1년이상
3rd row2년
4th row3년
5th row4년
ValueCountFrequency (%)
1년미만 1
 
2.4%
30년 1
 
2.4%
39년 1
 
2.4%
23년 1
 
2.4%
24년 1
 
2.4%
25년 1
 
2.4%
26년 1
 
2.4%
27년 1
 
2.4%
28년 1
 
2.4%
29년 1
 
2.4%
Other values (32) 32
76.2%
2023-12-12T13:09:43.165125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
42
33.3%
3 16
 
12.7%
1 15
 
11.9%
2 14
 
11.1%
4 5
 
4.0%
6 4
 
3.2%
0 4
 
3.2%
8 4
 
3.2%
7 4
 
3.2%
5 4
 
3.2%
Other values (7) 14
 
11.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 74
58.7%
Other Letter 52
41.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 16
21.6%
1 15
20.3%
2 14
18.9%
4 5
 
6.8%
6 4
 
5.4%
0 4
 
5.4%
8 4
 
5.4%
7 4
 
5.4%
5 4
 
5.4%
9 4
 
5.4%
Other Letter
ValueCountFrequency (%)
42
80.8%
3
 
5.8%
3
 
5.8%
1
 
1.9%
1
 
1.9%
1
 
1.9%
1
 
1.9%

Most occurring scripts

ValueCountFrequency (%)
Common 74
58.7%
Hangul 52
41.3%

Most frequent character per script

Common
ValueCountFrequency (%)
3 16
21.6%
1 15
20.3%
2 14
18.9%
4 5
 
6.8%
6 4
 
5.4%
0 4
 
5.4%
8 4
 
5.4%
7 4
 
5.4%
5 4
 
5.4%
9 4
 
5.4%
Hangul
ValueCountFrequency (%)
42
80.8%
3
 
5.8%
3
 
5.8%
1
 
1.9%
1
 
1.9%
1
 
1.9%
1
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 74
58.7%
Hangul 52
41.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
42
80.8%
3
 
5.8%
3
 
5.8%
1
 
1.9%
1
 
1.9%
1
 
1.9%
1
 
1.9%
ASCII
ValueCountFrequency (%)
3 16
21.6%
1 15
20.3%
2 14
18.9%
4 5
 
6.8%
6 4
 
5.4%
0 4
 
5.4%
8 4
 
5.4%
7 4
 
5.4%
5 4
 
5.4%
9 4
 
5.4%


Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct42
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30499.857
Minimum1871
Maximum64070
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-12T13:09:43.696704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1871
5-th percentile3326.2
Q124209.5
median28052
Q337785.5
95-th percentile57381.55
Maximum64070
Range62199
Interquartile range (IQR)13576

Descriptive statistics

Standard deviation15242.84
Coefficient of variation (CV)0.4997676
Kurtosis0.007314927
Mean30499.857
Median Absolute Deviation (MAD)8546.5
Skewness0.16513203
Sum1280994
Variance2.3234418 × 108
MonotonicityNot monotonic
2023-12-12T13:09:43.923304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
50252 1
 
2.4%
26010 1
 
2.4%
17565 1
 
2.4%
26425 1
 
2.4%
24158 1
 
2.4%
27847 1
 
2.4%
26146 1
 
2.4%
24996 1
 
2.4%
31106 1
 
2.4%
27296 1
 
2.4%
Other values (32) 32
76.2%
ValueCountFrequency (%)
1871 1
2.4%
3108 1
2.4%
3194 1
2.4%
5838 1
2.4%
7187 1
2.4%
12151 1
2.4%
17565 1
2.4%
17934 1
2.4%
22488 1
2.4%
22584 1
2.4%
ValueCountFrequency (%)
64070 1
2.4%
61921 1
2.4%
57438 1
2.4%
56309 1
2.4%
50252 1
2.4%
46286 1
2.4%
45459 1
2.4%
44745 1
2.4%
42872 1
2.4%
38615 1
2.4%

정무직
Real number (ℝ)

ZEROS 

Distinct12
Distinct (%)28.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.1190476
Minimum0
Maximum51
Zeros17
Zeros (%)40.5%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-12T13:09:44.118708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile14.95
Maximum51
Range51
Interquartile range (IQR)3

Descriptive statistics

Standard deviation9.4099127
Coefficient of variation (CV)2.2844875
Kurtosis15.909862
Mean4.1190476
Median Absolute Deviation (MAD)1
Skewness3.7495069
Sum173
Variance88.546458
MonotonicityNot monotonic
2023-12-12T13:09:44.325054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 17
40.5%
1 12
28.6%
3 3
 
7.1%
4 2
 
4.8%
51 1
 
2.4%
30 1
 
2.4%
2 1
 
2.4%
14 1
 
2.4%
12 1
 
2.4%
9 1
 
2.4%
Other values (2) 2
 
4.8%
ValueCountFrequency (%)
0 17
40.5%
1 12
28.6%
2 1
 
2.4%
3 3
 
7.1%
4 2
 
4.8%
9 1
 
2.4%
11 1
 
2.4%
12 1
 
2.4%
14 1
 
2.4%
15 1
 
2.4%
ValueCountFrequency (%)
51 1
 
2.4%
30 1
 
2.4%
15 1
 
2.4%
14 1
 
2.4%
12 1
 
2.4%
11 1
 
2.4%
9 1
 
2.4%
4 2
4.8%
3 3
7.1%
2 1
 
2.4%

별정직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct26
Distinct (%)61.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39.119048
Minimum0
Maximum759
Zeros3
Zeros (%)7.1%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-12T13:09:44.508111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.05
Q15.25
median13.5
Q328.25
95-th percentile77.95
Maximum759
Range759
Interquartile range (IQR)23

Descriptive statistics

Standard deviation116.32423
Coefficient of variation (CV)2.9735957
Kurtosis38.190356
Mean39.119048
Median Absolute Deviation (MAD)9.5
Skewness6.0590253
Sum1643
Variance13531.327
MonotonicityNot monotonic
2023-12-12T13:09:44.698830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
6 4
 
9.5%
17 4
 
9.5%
0 3
 
7.1%
8 3
 
7.1%
54 2
 
4.8%
4 2
 
4.8%
26 2
 
4.8%
5 2
 
4.8%
15 2
 
4.8%
2 2
 
4.8%
Other values (16) 16
38.1%
ValueCountFrequency (%)
0 3
7.1%
1 1
 
2.4%
2 2
4.8%
3 1
 
2.4%
4 2
4.8%
5 2
4.8%
6 4
9.5%
8 3
7.1%
10 1
 
2.4%
11 1
 
2.4%
ValueCountFrequency (%)
759 1
2.4%
88 1
2.4%
78 1
2.4%
77 1
2.4%
74 1
2.4%
57 1
2.4%
54 2
4.8%
50 1
2.4%
30 1
2.4%
29 1
2.4%

일반직
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct42
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12270.738
Minimum927
Maximum28631
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-12T13:09:44.869479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum927
5-th percentile1095.95
Q18453.75
median12123
Q316457.75
95-th percentile25627.3
Maximum28631
Range27704
Interquartile range (IQR)8004

Descriptive statistics

Standard deviation7141.7015
Coefficient of variation (CV)0.58201075
Kurtosis-0.050781982
Mean12270.738
Median Absolute Deviation (MAD)3750
Skewness0.44546902
Sum515371
Variance51003900
MonotonicityNot monotonic
2023-12-12T13:09:45.037121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
17714 1
 
2.4%
12200 1
 
2.4%
4335 1
 
2.4%
8440 1
 
2.4%
8789 1
 
2.4%
12205 1
 
2.4%
12046 1
 
2.4%
11859 1
 
2.4%
16689 1
 
2.4%
14379 1
 
2.4%
Other values (32) 32
76.2%
ValueCountFrequency (%)
927 1
2.4%
944 1
2.4%
1071 1
2.4%
1570 1
2.4%
2561 1
2.4%
4115 1
2.4%
4335 1
2.4%
4990 1
2.4%
5556 1
2.4%
8306 1
2.4%
ValueCountFrequency (%)
28631 1
2.4%
27907 1
2.4%
25630 1
2.4%
25576 1
2.4%
20985 1
2.4%
19795 1
2.4%
18885 1
2.4%
17714 1
2.4%
17202 1
2.4%
16848 1
2.4%

경찰
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct42
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3422.881
Minimum75
Maximum6826
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-12T13:09:45.186479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum75
5-th percentile614.7
Q12269.75
median3376
Q34322.5
95-th percentile6179.5
Maximum6826
Range6751
Interquartile range (IQR)2052.75

Descriptive statistics

Standard deviation1673.8084
Coefficient of variation (CV)0.48900573
Kurtosis-0.47285268
Mean3422.881
Median Absolute Deviation (MAD)1087.5
Skewness0.088625902
Sum143761
Variance2801634.5
MonotonicityNot monotonic
2023-12-12T13:09:45.346293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
3354 1
 
2.4%
3179 1
 
2.4%
1979 1
 
2.4%
5656 1
 
2.4%
4261 1
 
2.4%
4147 1
 
2.4%
3211 1
 
2.4%
2105 1
 
2.4%
2583 1
 
2.4%
2142 1
 
2.4%
Other values (32) 32
76.2%
ValueCountFrequency (%)
75 1
2.4%
277 1
2.4%
598 1
2.4%
932 1
2.4%
1546 1
2.4%
1855 1
2.4%
1979 1
2.4%
2105 1
2.4%
2121 1
2.4%
2142 1
2.4%
ValueCountFrequency (%)
6826 1
2.4%
6348 1
2.4%
6190 1
2.4%
5980 1
2.4%
5866 1
2.4%
5656 1
2.4%
5323 1
2.4%
5215 1
2.4%
4965 1
2.4%
4745 1
2.4%

소방
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct42
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1526.7619
Minimum10
Maximum4069
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-12T13:09:45.570104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile94.1
Q1812
median1460
Q32086.5
95-th percentile3514.05
Maximum4069
Range4059
Interquartile range (IQR)1274.5

Descriptive statistics

Standard deviation1023.2589
Coefficient of variation (CV)0.67021509
Kurtosis0.14997627
Mean1526.7619
Median Absolute Deviation (MAD)683.5
Skewness0.67295817
Sum64124
Variance1047058.7
MonotonicityNot monotonic
2023-12-12T13:09:45.741360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
2169 1
 
2.4%
1425 1
 
2.4%
661 1
 
2.4%
746 1
 
2.4%
554 1
 
2.4%
1129 1
 
2.4%
1561 1
 
2.4%
1448 1
 
2.4%
1575 1
 
2.4%
1500 1
 
2.4%
Other values (32) 32
76.2%
ValueCountFrequency (%)
10 1
2.4%
22 1
2.4%
94 1
2.4%
96 1
2.4%
188 1
2.4%
312 1
2.4%
459 1
2.4%
554 1
2.4%
661 1
2.4%
746 1
2.4%
ValueCountFrequency (%)
4069 1
2.4%
3748 1
2.4%
3524 1
2.4%
3325 1
2.4%
3131 1
2.4%
2777 1
2.4%
2441 1
2.4%
2365 1
2.4%
2185 1
2.4%
2173 1
2.4%

교육직
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct42
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9016.881
Minimum81
Maximum13742
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-12T13:09:45.899617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum81
5-th percentile1912.45
Q16803.5
median9661
Q312057
95-th percentile13356.2
Maximum13742
Range13661
Interquartile range (IQR)5253.5

Descriptive statistics

Standard deviation3608.6068
Coefficient of variation (CV)0.40020566
Kurtosis-0.14703287
Mean9016.881
Median Absolute Deviation (MAD)2509.5
Skewness-0.79948191
Sum378709
Variance13022043
MonotonicityNot monotonic
2023-12-12T13:09:46.045546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
12300 1
 
2.4%
6650 1
 
2.4%
8095 1
 
2.4%
8623 1
 
2.4%
7449 1
 
2.4%
7207 1
 
2.4%
5943 1
 
2.4%
6669 1
 
2.4%
7314 1
 
2.4%
6448 1
 
2.4%
Other values (32) 32
76.2%
ValueCountFrequency (%)
81 1
2.4%
1707 1
2.4%
1894 1
2.4%
2263 1
2.4%
2989 1
2.4%
4619 1
2.4%
5943 1
2.4%
6448 1
2.4%
6533 1
2.4%
6650 1
2.4%
ValueCountFrequency (%)
13742 1
2.4%
13649 1
2.4%
13394 1
2.4%
12638 1
2.4%
12541 1
2.4%
12454 1
2.4%
12409 1
2.4%
12401 1
2.4%
12300 1
2.4%
12226 1
2.4%

법관검사
Real number (ℝ)

HIGH CORRELATION 

Distinct41
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.2619
Minimum1
Maximum268
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-12T13:09:46.243055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.05
Q142.5
median142.5
Q3197.25
95-th percentile247.65
Maximum268
Range267
Interquartile range (IQR)154.75

Descriptive statistics

Standard deviation84.08447
Coefficient of variation (CV)0.65049691
Kurtosis-1.2709188
Mean129.2619
Median Absolute Deviation (MAD)72.5
Skewness-0.12333377
Sum5429
Variance7070.198
MonotonicityNot monotonic
2023-12-12T13:09:46.406876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
9 2
 
4.8%
141 1
 
2.4%
42 1
 
2.4%
174 1
 
2.4%
155 1
 
2.4%
139 1
 
2.4%
107 1
 
2.4%
87 1
 
2.4%
79 1
 
2.4%
55 1
 
2.4%
Other values (31) 31
73.8%
ValueCountFrequency (%)
1 1
2.4%
7 1
2.4%
8 1
2.4%
9 2
4.8%
14 1
2.4%
20 1
2.4%
23 1
2.4%
32 1
2.4%
35 1
2.4%
42 1
2.4%
ValueCountFrequency (%)
268 1
2.4%
265 1
2.4%
248 1
2.4%
241 1
2.4%
234 1
2.4%
231 1
2.4%
226 1
2.4%
223 1
2.4%
207 1
2.4%
200 1
2.4%

기능직
Categorical

IMBALANCE 

Distinct5
Distinct (%)11.9%
Missing0
Missing (%)0.0%
Memory size468.0 B
0
33 
1
2
 
1
52
 
1
4
 
1

Length

Max length2
Median length1
Mean length1.0238095
Min length1

Unique

Unique3 ?
Unique (%)7.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 33
78.6%
1 6
 
14.3%
2 1
 
2.4%
52 1
 
2.4%
4 1
 
2.4%

Length

2023-12-12T13:09:46.559184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:09:46.701270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 33
78.6%
1 6
 
14.3%
2 1
 
2.4%
52 1
 
2.4%
4 1
 
2.4%

공안직
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct42
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean896.71429
Minimum3
Maximum1771
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-12T13:09:46.846959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile19.6
Q1597.25
median963
Q31274.25
95-th percentile1536.1
Maximum1771
Range1768
Interquartile range (IQR)677

Descriptive statistics

Standard deviation486.74751
Coefficient of variation (CV)0.54281226
Kurtosis-0.63121746
Mean896.71429
Median Absolute Deviation (MAD)338.5
Skewness-0.39281876
Sum37662
Variance236923.14
MonotonicityNot monotonic
2023-12-12T13:09:47.006176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
1116 1
 
2.4%
585 1
 
2.4%
966 1
 
2.4%
869 1
 
2.4%
811 1
 
2.4%
704 1
 
2.4%
700 1
 
2.4%
565 1
 
2.4%
569 1
 
2.4%
634 1
 
2.4%
Other values (32) 32
76.2%
ValueCountFrequency (%)
3 1
2.4%
5 1
2.4%
19 1
2.4%
31 1
2.4%
43 1
2.4%
98 1
2.4%
356 1
2.4%
486 1
2.4%
565 1
2.4%
569 1
2.4%
ValueCountFrequency (%)
1771 1
2.4%
1682 1
2.4%
1540 1
2.4%
1462 1
2.4%
1439 1
2.4%
1413 1
2.4%
1387 1
2.4%
1381 1
2.4%
1380 1
2.4%
1311 1
2.4%

군무원
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct42
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean831.21429
Minimum28
Maximum4265
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-12T13:09:47.175851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum28
5-th percentile81.9
Q1497.5
median684.5
Q3876.75
95-th percentile2265.2
Maximum4265
Range4237
Interquartile range (IQR)379.25

Descriptive statistics

Standard deviation777.11563
Coefficient of variation (CV)0.93491612
Kurtosis9.5246578
Mean831.21429
Median Absolute Deviation (MAD)198
Skewness2.7937525
Sum34911
Variance603908.71
MonotonicityNot monotonic
2023-12-12T13:09:47.327761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
2117 1
 
2.4%
514 1
 
2.4%
770 1
 
2.4%
1129 1
 
2.4%
910 1
 
2.4%
795 1
 
2.4%
902 1
 
2.4%
689 1
 
2.4%
704 1
 
2.4%
616 1
 
2.4%
Other values (32) 32
76.2%
ValueCountFrequency (%)
28 1
2.4%
37 1
2.4%
79 1
2.4%
137 1
2.4%
176 1
2.4%
276 1
2.4%
285 1
2.4%
384 1
2.4%
407 1
2.4%
426 1
2.4%
ValueCountFrequency (%)
4265 1
2.4%
2854 1
2.4%
2273 1
2.4%
2117 1
2.4%
1257 1
2.4%
1198 1
2.4%
1129 1
2.4%
910 1
2.4%
905 1
2.4%
902 1
2.4%

연구직
Real number (ℝ)

HIGH CORRELATION 

Distinct40
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean262.09524
Minimum1
Maximum633
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-12T13:09:47.474782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.55
Q1136
median272
Q3374.5
95-th percentile506.85
Maximum633
Range632
Interquartile range (IQR)238.5

Descriptive statistics

Standard deviation168.56508
Coefficient of variation (CV)0.64314438
Kurtosis-0.59405833
Mean262.09524
Median Absolute Deviation (MAD)116.5
Skewness0.20637347
Sum11008
Variance28414.186
MonotonicityNot monotonic
2023-12-12T13:09:47.603076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
1 2
 
4.8%
289 2
 
4.8%
347 1
 
2.4%
246 1
 
2.4%
132 1
 
2.4%
114 1
 
2.4%
149 1
 
2.4%
173 1
 
2.4%
220 1
 
2.4%
209 1
 
2.4%
Other values (30) 30
71.4%
ValueCountFrequency (%)
1 2
4.8%
2 1
2.4%
13 1
2.4%
18 1
2.4%
38 1
2.4%
41 1
2.4%
107 1
2.4%
114 1
2.4%
120 1
2.4%
132 1
2.4%
ValueCountFrequency (%)
633 1
2.4%
601 1
2.4%
507 1
2.4%
504 1
2.4%
502 1
2.4%
470 1
2.4%
450 1
2.4%
424 1
2.4%
382 1
2.4%
380 1
2.4%

지도직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct41
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean116.14286
Minimum0
Maximum282
Zeros1
Zeros (%)2.4%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-12T13:09:47.729143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.65
Q150
median104.5
Q3168
95-th percentile262.3
Maximum282
Range282
Interquartile range (IQR)118

Descriptive statistics

Standard deviation78.133273
Coefficient of variation (CV)0.67273421
Kurtosis-0.65408797
Mean116.14286
Median Absolute Deviation (MAD)63
Skewness0.45231532
Sum4878
Variance6104.8084
MonotonicityNot monotonic
2023-12-12T13:09:47.859907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
168 2
 
4.8%
93 1
 
2.4%
1 1
 
2.4%
38 1
 
2.4%
74 1
 
2.4%
131 1
 
2.4%
194 1
 
2.4%
126 1
 
2.4%
42 1
 
2.4%
100 1
 
2.4%
Other values (31) 31
73.8%
ValueCountFrequency (%)
0 1
2.4%
1 1
2.4%
3 1
2.4%
16 1
2.4%
28 1
2.4%
36 1
2.4%
37 1
2.4%
38 1
2.4%
39 1
2.4%
42 1
2.4%
ValueCountFrequency (%)
282 1
2.4%
272 1
2.4%
263 1
2.4%
249 1
2.4%
225 1
2.4%
213 1
2.4%
196 1
2.4%
194 1
2.4%
186 1
2.4%
172 1
2.4%

계약직
Real number (ℝ)

HIGH CORRELATION 

Distinct37
Distinct (%)88.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean378.04762
Minimum3
Maximum2795
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-12T13:09:47.993164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile4.05
Q156.75
median122
Q3385.75
95-th percentile1784.05
Maximum2795
Range2792
Interquartile range (IQR)329

Descriptive statistics

Standard deviation621.31505
Coefficient of variation (CV)1.6434836
Kurtosis6.177647
Mean378.04762
Median Absolute Deviation (MAD)102
Skewness2.5212033
Sum15878
Variance386032.39
MonotonicityNot monotonic
2023-12-12T13:09:48.117836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
140 2
 
4.8%
76 2
 
4.8%
4 2
 
4.8%
63 2
 
4.8%
62 2
 
4.8%
44 1
 
2.4%
66 1
 
2.4%
70 1
 
2.4%
69 1
 
2.4%
55 1
 
2.4%
Other values (27) 27
64.3%
ValueCountFrequency (%)
3 1
2.4%
4 2
4.8%
5 1
2.4%
14 1
2.4%
20 1
2.4%
23 1
2.4%
35 1
2.4%
44 1
2.4%
53 1
2.4%
55 1
2.4%
ValueCountFrequency (%)
2795 1
2.4%
2069 1
2.4%
1791 1
2.4%
1652 1
2.4%
1197 1
2.4%
690 1
2.4%
659 1
2.4%
559 1
2.4%
475 1
2.4%
429 1
2.4%

공중보건의
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct10
Distinct (%)23.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean80.261905
Minimum0
Maximum976
Zeros33
Zeros (%)78.6%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-12T13:09:48.228371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile870.6
Maximum976
Range976
Interquartile range (IQR)0

Descriptive statistics

Standard deviation246.88815
Coefficient of variation (CV)3.0760315
Kurtosis9.9542498
Mean80.261905
Median Absolute Deviation (MAD)0
Skewness3.3492695
Sum3371
Variance60953.759
MonotonicityNot monotonic
2023-12-12T13:09:48.333829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 33
78.6%
909 1
 
2.4%
967 1
 
2.4%
976 1
 
2.4%
141 1
 
2.4%
54 1
 
2.4%
89 1
 
2.4%
127 1
 
2.4%
93 1
 
2.4%
15 1
 
2.4%
ValueCountFrequency (%)
0 33
78.6%
15 1
 
2.4%
54 1
 
2.4%
89 1
 
2.4%
93 1
 
2.4%
127 1
 
2.4%
141 1
 
2.4%
909 1
 
2.4%
967 1
 
2.4%
976 1
 
2.4%
ValueCountFrequency (%)
976 1
 
2.4%
967 1
 
2.4%
909 1
 
2.4%
141 1
 
2.4%
127 1
 
2.4%
93 1
 
2.4%
89 1
 
2.4%
54 1
 
2.4%
15 1
 
2.4%
0 33
78.6%

기타
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct42
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1524.0952
Minimum70
Maximum6387
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-12T13:09:48.448617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum70
5-th percentile93.05
Q1716.75
median1192.5
Q31565
95-th percentile4852.2
Maximum6387
Range6317
Interquartile range (IQR)848.25

Descriptive statistics

Standard deviation1472.5367
Coefficient of variation (CV)0.96617107
Kurtosis3.0650088
Mean1524.0952
Median Absolute Deviation (MAD)461
Skewness1.8802748
Sum64012
Variance2168364.4
MonotonicityNot monotonic
2023-12-12T13:09:48.581320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
6387 1
 
2.4%
1012 1
 
2.4%
359 1
 
2.4%
565 1
 
2.4%
884 1
 
2.4%
1194 1
 
2.4%
1212 1
 
2.4%
1191 1
 
2.4%
1233 1
 
2.4%
1119 1
 
2.4%
Other values (32) 32
76.2%
ValueCountFrequency (%)
70 1
2.4%
77 1
2.4%
89 1
2.4%
170 1
2.4%
230 1
2.4%
297 1
2.4%
359 1
2.4%
465 1
2.4%
562 1
2.4%
565 1
2.4%
ValueCountFrequency (%)
6387 1
2.4%
5134 1
2.4%
4860 1
2.4%
4704 1
2.4%
4313 1
2.4%
2960 1
2.4%
2501 1
2.4%
1840 1
2.4%
1828 1
2.4%
1756 1
2.4%

Interactions

2023-12-12T13:09:40.252074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:16.768827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:18.571209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:20.061821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:21.539260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:23.529109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:24.997736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:26.569389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:28.151085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:29.915314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:31.537207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:33.213449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:34.775862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:36.926818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:38.669344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:40.419498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:16.880512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:18.687635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:20.167519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:21.629602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:23.619181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:25.111893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:26.677789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:28.255166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:30.026825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:31.626475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:33.336933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:34.908204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:37.037866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:38.794028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:40.553660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:16.993186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:18.780449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:20.256078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:21.718328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:23.710385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:25.210287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:26.776232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:28.367449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:30.127275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:31.718994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:33.452057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:35.020481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:37.153526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:38.878547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:40.685818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:17.123494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:18.896077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:20.351472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:21.824102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:23.815295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:25.324248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:26.896008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:28.800122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:30.268221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:31.827708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:33.552319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:35.129031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:37.285509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:38.983617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:40.813519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:17.237805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:18.995147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:20.457367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:21.948868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:23.914695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:25.466460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:26.996346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:28.905926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:30.383005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:31.947773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:33.655057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:35.258519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:37.403767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:39.095611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:40.940193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:17.338697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:19.098011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:20.553087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:22.052957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:24.012680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:25.569608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:27.105107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:29.006947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:30.495755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:32.074783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:33.748040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:35.708724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:37.530161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:39.206231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:41.067939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:17.486633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:19.198083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:20.658932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:22.171820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:24.133344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:25.679313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:27.222266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:29.114565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:30.602027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:32.185754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:33.861397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:35.833682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:37.655024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:39.292217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:41.204206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:17.616738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:19.286955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:20.753107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:22.659324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:24.252917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:25.815851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:27.321428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:29.215904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:30.712205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:32.381568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:33.975431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:35.982415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:37.762875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:39.410088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:41.318482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:17.723624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:19.381819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:20.843998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:22.776024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:24.343752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:25.912626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:27.412255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:29.296674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:30.796813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:32.478532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:34.070445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:36.113995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:37.875141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:39.519652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:41.425362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:17.842448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:19.482931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:20.967083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:22.921389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:24.445267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:26.020692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:27.517687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:29.390598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:30.924041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:32.588032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:34.179625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:36.242559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:37.987823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:39.608557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:41.521189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:17.970176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:19.582480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:21.076720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:23.029643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:24.539538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:26.112347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:27.628744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:29.468750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:31.033325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:32.682122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:34.274854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:36.368027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:38.095312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:39.689108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:41.619973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:18.089759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:19.686420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:21.180077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:23.129770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:24.634384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:26.208422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:27.743388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:29.557588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:31.142456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:32.780745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:34.375433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:36.485875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:38.211544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:39.783478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:41.722882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:18.212003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:19.772670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:21.265664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:23.228862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:24.737180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:26.310831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:27.849242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:29.643535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:31.239142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:32.898403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:34.473279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:36.596901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:38.326803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:39.890415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:41.835171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:18.309643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:19.858054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:21.356736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:23.329123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:24.820444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:26.395279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:27.940210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:29.731714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:31.333188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:33.007849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:34.579823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:36.715202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:38.450590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:40.000992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:41.941490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:18.421179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:19.958790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:21.445122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:23.424776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:24.903717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:26.483653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:28.034179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:29.821094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:31.438514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:33.115130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:34.675398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:36.814520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:38.567313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:09:40.127892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:09:48.710797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분정무직별정직일반직경찰소방교육직법관검사기능직공안직군무원연구직지도직계약직공중보건의기타
구분1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
1.0001.0000.5700.5900.9650.7730.9070.7820.6370.0000.8380.7930.8910.8610.8200.6510.867
정무직1.0000.5701.0000.7790.5270.0000.0000.0000.0000.0000.6880.7870.3150.3980.7910.5640.715
별정직1.0000.5900.7791.0000.5900.4590.6500.0000.0000.0000.0000.8570.4870.7890.9380.8240.998
일반직1.0000.9650.5270.5901.0000.7710.9020.7250.5740.0000.7800.8000.8710.9100.7950.6510.893
경찰1.0000.7730.0000.4590.7711.0000.8160.8450.6310.0000.0000.5350.7360.7220.6140.2500.663
소방1.0000.9070.0000.6500.9020.8161.0000.6980.8650.0000.8800.8340.9080.8940.8560.8270.897
교육직1.0000.7820.0000.0000.7250.8450.6981.0000.6480.0000.7460.0000.6220.5700.0000.0000.000
법관검사1.0000.6370.0000.0000.5740.6310.8650.6481.0000.4970.7880.6230.8710.7330.3440.4400.452
기능직1.0000.0000.0000.0000.0000.0000.0000.0000.4971.0000.0000.0000.3680.0000.0000.0000.000
공안직1.0000.8380.6880.0000.7800.0000.8800.7460.7880.0001.0000.5920.8400.7470.3070.1630.534
군무원1.0000.7930.7870.8570.8000.5350.8340.0000.6230.0000.5921.0000.8620.6920.9330.8710.881
연구직1.0000.8910.3150.4870.8710.7360.9080.6220.8710.3680.8400.8621.0000.8140.7960.8370.757
지도직1.0000.8610.3980.7890.9100.7220.8940.5700.7330.0000.7470.6920.8141.0000.7640.5790.821
계약직1.0000.8200.7910.9380.7950.6140.8560.0000.3440.0000.3070.9330.7960.7641.0000.9210.952
공중보건의1.0000.6510.5640.8240.6510.2500.8270.0000.4400.0000.1630.8710.8370.5790.9211.0000.987
기타1.0000.8670.7150.9980.8930.6630.8970.0000.4520.0000.5340.8810.7570.8210.9520.9871.000
2023-12-12T13:09:49.246359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정무직별정직일반직경찰소방교육직법관검사공안직군무원연구직지도직계약직공중보건의기타기능직
1.0000.1450.9310.9470.7190.9030.7540.5320.8340.7850.9520.8360.9090.7130.9420.000
정무직0.1451.0000.0610.2810.2550.196-0.053-0.262-0.1490.2700.0840.2010.0740.2850.2400.000
별정직0.9310.0611.0000.8460.6580.8770.7140.6100.8480.7470.9230.7440.9520.7110.9030.000
일반직0.9470.2810.8461.0000.6610.8840.6040.3930.7450.7730.9270.8590.8140.7110.9350.000
경찰0.7190.2550.6580.6611.0000.6480.4500.2470.5750.7210.6500.7020.6480.5530.6630.000
소방0.9030.1960.8770.8840.6481.0000.6110.4950.7380.7550.9110.7810.8800.6810.8940.000
교육직0.754-0.0530.7140.6040.4500.6111.0000.7250.7360.4680.7040.5730.7500.4060.6550.000
법관검사0.532-0.2620.6100.3930.2470.4950.7251.0000.7510.3350.5930.3910.6540.0170.4680.199
공안직0.834-0.1490.8480.7450.5750.7380.7360.7511.0000.6680.8770.6980.8710.4880.7290.000
군무원0.7850.2700.7470.7730.7210.7550.4680.3350.6681.0000.7530.7710.7830.6810.7680.000
연구직0.9520.0840.9230.9270.6500.9110.7040.5930.8770.7531.0000.8430.9280.6860.9170.130
지도직0.8360.2010.7440.8590.7020.7810.5730.3910.6980.7710.8431.0000.7610.6210.8470.000
계약직0.9090.0740.9520.8140.6480.8800.7500.6540.8710.7830.9280.7611.0000.7140.8860.000
공중보건의0.7130.2850.7110.7110.5530.6810.4060.0170.4880.6810.6860.6210.7141.0000.7020.000
기타0.9420.2400.9030.9350.6630.8940.6550.4680.7290.7680.9170.8470.8860.7021.0000.000
기능직0.0000.0000.0000.0000.0000.0000.0000.1990.0000.0000.1300.0000.0000.0000.0001.000

Missing values

2023-12-12T13:09:42.123400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:09:42.442966image/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

구분정무직별정직일반직경찰소방교육직법관검사기능직공안직군무원연구직지도직계약직공중보건의기타
01년미만50252517591771433542169123001410111621173479327959096387
11년이상64070308828631532335241190414701682426563322517919674860
22년574384742563047452777124091400991285460127216529764313
33년6192145427907682637481189413101381227350728220691414704
44년563090772557643434069124011200138711985042491197545134
55년4628605720985521533259370160014131257502263690892960
66년45459178197954965313111051144014399054502136591272501
77년4474515018885598023651210815801164888470196559931828
88년4287215417202619021731222615401233843382168475151756
99년386151261369063482185117661980112469337517242901608
구분정무직별정직일반직경찰소방교육직법관검사기능직공안직군무원연구직지도직계약직공중보건의기타
3232년2601036122003179142566503205855142221384401012
3333년18710094459894811031281815070
3433년초과2436415892413737802845935064042614839530761
3534년이상2258411383064204842742123148638410759350702
3635년17934155556415745965332003562853836230465
3736년121510241152326312461980982764137200297
3837년7187042561932188298990431761328140230
3938년583801157015469622631401913721640170
4039년31080092727722170770579133077
4140년이상31941010717510189490337104089