Overview

Dataset statistics

Number of variables18
Number of observations30
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.8 KiB
Average record size in memory164.4 B

Variable types

Text1
Categorical1
Numeric16

Dataset

Description공무원 직종별(정무직, 별정직, 일반직, 경찰, 소방, 교육직 등), 재직년수별(20년미만부터 33년 이상)퇴직연금수급자 현황 데이터로 연 단위로 구분됩니다.
URLhttps://www.data.go.kr/data/15052966/fileData.do

Alerts

is highly overall correlated with 정무직 and 11 other fieldsHigh correlation
정무직 is highly overall correlated with and 12 other fieldsHigh correlation
별정직 is highly overall correlated with and 13 other fieldsHigh correlation
일반직 is highly overall correlated with and 12 other fieldsHigh correlation
경찰 is highly overall correlated with and 12 other fieldsHigh correlation
소방 is highly overall correlated with and 12 other fieldsHigh correlation
교육직 is highly overall correlated with 법관검사 and 1 other fieldsHigh correlation
법관검사 is highly overall correlated with 정무직 and 14 other fieldsHigh correlation
기능직 is highly overall correlated with and 14 other fieldsHigh correlation
고용직 is highly overall correlated with 교육직 and 2 other fieldsHigh correlation
공안직 is highly overall correlated with and 12 other fieldsHigh correlation
군무원 is highly overall correlated with and 12 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 12 other fieldsHigh correlation
기타 is highly overall correlated with and 13 other fieldsHigh correlation
남여구분 is highly overall correlated with 별정직 and 3 other fieldsHigh correlation
has unique valuesUnique
별정직 has unique valuesUnique
교육직 has unique valuesUnique
기능직 has unique valuesUnique
정무직 has 6 (20.0%) zerosZeros
소방 has 2 (6.7%) zerosZeros
법관검사 has 1 (3.3%) zerosZeros
고용직 has 19 (63.3%) zerosZeros

Reproduction

Analysis started2023-12-12 20:05:00.160533
Analysis finished2023-12-12 20:05:28.182960
Duration28.02 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Text

Distinct15
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-13T05:05:28.285579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.2666667
Min length3

Characters and Unicode

Total characters98
Distinct characters15
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

Unique0 ?
Unique (%)0.0%

Sample

1st row20년미만
2nd row20년미만
3rd row20년
4th row20년
5th row21년
ValueCountFrequency (%)
20년미만 2
 
6.7%
20년 2
 
6.7%
21년 2
 
6.7%
22년 2
 
6.7%
23년 2
 
6.7%
24년 2
 
6.7%
25년 2
 
6.7%
26년 2
 
6.7%
27년 2
 
6.7%
28년 2
 
6.7%
Other values (5) 10
33.3%
2023-12-13T05:05:28.641228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
30
30.6%
2 26
26.5%
3 12
 
12.2%
0 6
 
6.1%
1 4
 
4.1%
2
 
2.0%
2
 
2.0%
4 2
 
2.0%
5 2
 
2.0%
6 2
 
2.0%
Other values (5) 10
 
10.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60
61.2%
Other Letter 38
38.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 26
43.3%
3 12
20.0%
0 6
 
10.0%
1 4
 
6.7%
4 2
 
3.3%
5 2
 
3.3%
6 2
 
3.3%
7 2
 
3.3%
8 2
 
3.3%
9 2
 
3.3%
Other Letter
ValueCountFrequency (%)
30
78.9%
2
 
5.3%
2
 
5.3%
2
 
5.3%
2
 
5.3%

Most occurring scripts

ValueCountFrequency (%)
Common 60
61.2%
Hangul 38
38.8%

Most frequent character per script

Common
ValueCountFrequency (%)
2 26
43.3%
3 12
20.0%
0 6
 
10.0%
1 4
 
6.7%
4 2
 
3.3%
5 2
 
3.3%
6 2
 
3.3%
7 2
 
3.3%
8 2
 
3.3%
9 2
 
3.3%
Hangul
ValueCountFrequency (%)
30
78.9%
2
 
5.3%
2
 
5.3%
2
 
5.3%
2
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 60
61.2%
Hangul 38
38.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
30
78.9%
2
 
5.3%
2
 
5.3%
2
 
5.3%
2
 
5.3%
ASCII
ValueCountFrequency (%)
2 26
43.3%
3 12
20.0%
0 6
 
10.0%
1 4
 
6.7%
4 2
 
3.3%
5 2
 
3.3%
6 2
 
3.3%
7 2
 
3.3%
8 2
 
3.3%
9 2
 
3.3%

남여구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
15 
15 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
15
50.0%
15
50.0%

Length

2023-12-13T05:05:28.811280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:05:28.925527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
15
50.0%
15
50.0%


Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18200.333
Minimum2780
Maximum246270
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-13T05:05:29.043624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2780
5-th percentile2819.15
Q13522.5
median6956
Q312473.25
95-th percentile45653.15
Maximum246270
Range243490
Interquartile range (IQR)8950.75

Descriptive statistics

Standard deviation44638.285
Coefficient of variation (CV)2.4526081
Kurtosis25.62171
Mean18200.333
Median Absolute Deviation (MAD)3768
Skewness4.9457356
Sum546010
Variance1.9925765 × 109
MonotonicityNot monotonic
2023-12-13T05:05:29.207760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
3472 1
 
3.3%
11304 1
 
3.3%
63425 1
 
3.3%
246270 1
 
3.3%
7022 1
 
3.3%
23932 1
 
3.3%
6822 1
 
3.3%
21083 1
 
3.3%
6546 1
 
3.3%
18739 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
2780 1
3.3%
2807 1
3.3%
2834 1
3.3%
3003 1
3.3%
3077 1
3.3%
3145 1
3.3%
3231 1
3.3%
3472 1
3.3%
3674 1
3.3%
4282 1
3.3%
ValueCountFrequency (%)
246270 1
3.3%
63425 1
3.3%
23932 1
3.3%
21319 1
3.3%
21083 1
3.3%
18739 1
3.3%
15193 1
3.3%
12863 1
3.3%
11304 1
3.3%
10126 1
3.3%

정무직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct20
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean43.533333
Minimum0
Maximum453
Zeros6
Zeros (%)20.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-13T05:05:29.361001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.25
median7
Q336
95-th percentile146.45
Maximum453
Range453
Interquartile range (IQR)34.75

Descriptive statistics

Standard deviation89.297926
Coefficient of variation (CV)2.051254
Kurtosis15.658064
Mean43.533333
Median Absolute Deviation (MAD)7
Skewness3.6606788
Sum1306
Variance7974.1195
MonotonicityNot monotonic
2023-12-13T05:05:29.528678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0 6
20.0%
3 3
 
10.0%
2 3
 
10.0%
1 2
 
6.7%
10 1
 
3.3%
83 1
 
3.3%
4 1
 
3.3%
453 1
 
3.3%
125 1
 
3.3%
164 1
 
3.3%
Other values (10) 10
33.3%
ValueCountFrequency (%)
0 6
20.0%
1 2
 
6.7%
2 3
10.0%
3 3
10.0%
4 1
 
3.3%
10 1
 
3.3%
19 1
 
3.3%
21 1
 
3.3%
22 1
 
3.3%
23 1
 
3.3%
ValueCountFrequency (%)
453 1
3.3%
164 1
3.3%
125 1
3.3%
120 1
3.3%
112 1
3.3%
83 1
3.3%
40 1
3.3%
38 1
3.3%
30 1
3.3%
25 1
3.3%

별정직
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean303.96667
Minimum14
Maximum2581
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-13T05:05:29.710905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum14
5-th percentile15.45
Q152
median94.5
Q3399.5
95-th percentile670.35
Maximum2581
Range2567
Interquartile range (IQR)347.5

Descriptive statistics

Standard deviation483.68916
Coefficient of variation (CV)1.5912573
Kurtosis17.596179
Mean303.96667
Median Absolute Deviation (MAD)80
Skewness3.823801
Sum9119
Variance233955.21
MonotonicityNot monotonic
2023-12-13T05:05:29.863292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
101 1
 
3.3%
488 1
 
3.3%
88 1
 
3.3%
2581 1
 
3.3%
14 1
 
3.3%
641 1
 
3.3%
25 1
 
3.3%
678 1
 
3.3%
15 1
 
3.3%
661 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
14 1
3.3%
15 1
3.3%
16 1
3.3%
25 1
3.3%
27 1
3.3%
31 1
3.3%
42 1
3.3%
51 1
3.3%
55 1
3.3%
56 1
3.3%
ValueCountFrequency (%)
2581 1
3.3%
678 1
3.3%
661 1
3.3%
641 1
3.3%
580 1
3.3%
518 1
3.3%
488 1
3.3%
402 1
3.3%
392 1
3.3%
319 1
3.3%

일반직
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6469.2667
Minimum838
Maximum98980
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-13T05:05:29.992793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum838
5-th percentile892.95
Q1983.25
median1924.5
Q34767.5
95-th percentile12093.2
Maximum98980
Range98142
Interquartile range (IQR)3784.25

Descriptive statistics

Standard deviation17767.491
Coefficient of variation (CV)2.7464458
Kurtosis27.846537
Mean6469.2667
Median Absolute Deviation (MAD)983
Skewness5.2006459
Sum194078
Variance3.1568372 × 108
MonotonicityNot monotonic
2023-12-13T05:05:30.136692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
970 2
 
6.7%
1073 1
 
3.3%
935 1
 
3.3%
13967 1
 
3.3%
98980 1
 
3.3%
1141 1
 
3.3%
9803 1
 
3.3%
1211 1
 
3.3%
8739 1
 
3.3%
1400 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
838 1
3.3%
861 1
3.3%
932 1
3.3%
935 1
3.3%
948 1
3.3%
962 1
3.3%
970 2
6.7%
1023 1
3.3%
1073 1
3.3%
1141 1
3.3%
ValueCountFrequency (%)
98980 1
3.3%
13967 1
3.3%
9803 1
3.3%
8739 1
3.3%
7784 1
3.3%
6395 1
3.3%
5350 1
3.3%
4832 1
3.3%
4574 1
3.3%
3996 1
3.3%

경찰
Real number (ℝ)

HIGH CORRELATION 

Distinct26
Distinct (%)86.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1575.4
Minimum9
Maximum33280
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-13T05:05:30.279556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9
5-th percentile10
Q115
median197.5
Q3605.25
95-th percentile2763.6
Maximum33280
Range33271
Interquartile range (IQR)590.25

Descriptive statistics

Standard deviation6035.1728
Coefficient of variation (CV)3.8308828
Kurtosis28.972958
Mean1575.4
Median Absolute Deviation (MAD)185.5
Skewness5.3452873
Sum47262
Variance36423310
MonotonicityNot monotonic
2023-12-13T05:05:30.437389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
18 2
 
6.7%
15 2
 
6.7%
10 2
 
6.7%
13 2
 
6.7%
125 1
 
3.3%
851 1
 
3.3%
270 1
 
3.3%
33280 1
 
3.3%
14 1
 
3.3%
3147 1
 
3.3%
Other values (16) 16
53.3%
ValueCountFrequency (%)
9 1
3.3%
10 2
6.7%
11 1
3.3%
13 2
6.7%
14 1
3.3%
15 2
6.7%
17 1
3.3%
18 2
6.7%
24 1
3.3%
26 1
3.3%
ValueCountFrequency (%)
33280 1
3.3%
3147 1
3.3%
2295 1
3.3%
1822 1
3.3%
1278 1
3.3%
870 1
3.3%
851 1
3.3%
619 1
3.3%
564 1
3.3%
522 1
3.3%

소방
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct24
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean294.03333
Minimum0
Maximum4993
Zeros2
Zeros (%)6.7%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-13T05:05:30.615559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.45
Q15
median37.5
Q3185
95-th percentile707.9
Maximum4993
Range4993
Interquartile range (IQR)180

Descriptive statistics

Standard deviation909.12859
Coefficient of variation (CV)3.0919236
Kurtosis26.947634
Mean294.03333
Median Absolute Deviation (MAD)37.5
Skewness5.0887272
Sum8821
Variance826514.79
MonotonicityNot monotonic
2023-12-13T05:05:30.744965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
5 4
 
13.3%
6 3
 
10.0%
0 2
 
6.7%
195 1
 
3.3%
37 1
 
3.3%
4993 1
 
3.3%
1 1
 
3.3%
743 1
 
3.3%
665 1
 
3.3%
488 1
 
3.3%
Other values (14) 14
46.7%
ValueCountFrequency (%)
0 2
6.7%
1 1
 
3.3%
3 1
 
3.3%
4 1
 
3.3%
5 4
13.3%
6 3
10.0%
11 1
 
3.3%
12 1
 
3.3%
37 1
 
3.3%
38 1
 
3.3%
ValueCountFrequency (%)
4993 1
3.3%
743 1
3.3%
665 1
3.3%
488 1
3.3%
371 1
3.3%
274 1
3.3%
239 1
3.3%
195 1
3.3%
155 1
3.3%
152 1
3.3%

교육직
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5663.5333
Minimum365
Maximum71787
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-13T05:05:30.858804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum365
5-th percentile410.05
Q1892.75
median1405.5
Q32939.5
95-th percentile27570.6
Maximum71787
Range71422
Interquartile range (IQR)2046.75

Descriptive statistics

Standard deviation14892.083
Coefficient of variation (CV)2.6294687
Kurtosis15.361481
Mean5663.5333
Median Absolute Deviation (MAD)851
Skewness3.925352
Sum169906
Variance2.2177415 × 108
MonotonicityNot monotonic
2023-12-13T05:05:31.002053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
365 1
 
3.3%
1000 1
 
3.3%
45639 1
 
3.3%
71787 1
 
3.3%
5487 1
 
3.3%
3619 1
 
3.3%
5167 1
 
3.3%
2845 1
 
3.3%
4598 1
 
3.3%
2212 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
365 1
3.3%
406 1
3.3%
415 1
3.3%
467 1
3.3%
517 1
3.3%
592 1
3.3%
667 1
3.3%
857 1
3.3%
1000 1
3.3%
1158 1
3.3%
ValueCountFrequency (%)
71787 1
3.3%
45639 1
3.3%
5487 1
3.3%
5167 1
3.3%
4598 1
3.3%
3931 1
3.3%
3619 1
3.3%
2971 1
3.3%
2845 1
3.3%
2301 1
3.3%

법관검사
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct24
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean69.4
Minimum0
Maximum228
Zeros1
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-13T05:05:31.128808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q13.25
median38
Q3126.25
95-th percentile206.2
Maximum228
Range228
Interquartile range (IQR)123

Descriptive statistics

Standard deviation77.497319
Coefficient of variation (CV)1.1166761
Kurtosis-0.87938243
Mean69.4
Median Absolute Deviation (MAD)37
Skewness0.76619828
Sum2082
Variance6005.8345
MonotonicityNot monotonic
2023-12-13T05:05:31.253072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1 4
 
13.3%
4 2
 
6.7%
5 2
 
6.7%
2 2
 
6.7%
121 1
 
3.3%
84 1
 
3.3%
193 1
 
3.3%
45 1
 
3.3%
0 1
 
3.3%
61 1
 
3.3%
Other values (14) 14
46.7%
ValueCountFrequency (%)
0 1
 
3.3%
1 4
13.3%
2 2
6.7%
3 1
 
3.3%
4 2
6.7%
5 2
6.7%
6 1
 
3.3%
12 1
 
3.3%
31 1
 
3.3%
45 1
 
3.3%
ValueCountFrequency (%)
228 1
3.3%
217 1
3.3%
193 1
3.3%
188 1
3.3%
177 1
3.3%
159 1
3.3%
158 1
3.3%
128 1
3.3%
121 1
3.3%
94 1
3.3%

기능직
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1898.3333
Minimum15
Maximum14033
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-13T05:05:31.677576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum15
5-th percentile73.65
Q1243.5
median1209.5
Q32365.75
95-th percentile5600.6
Maximum14033
Range14018
Interquartile range (IQR)2122.25

Descriptive statistics

Standard deviation2795.9527
Coefficient of variation (CV)1.472846
Kurtosis12.734213
Mean1898.3333
Median Absolute Deviation (MAD)1060.5
Skewness3.293087
Sum56950
Variance7817351.7
MonotonicityNot monotonic
2023-12-13T05:05:31.791974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
30 1
 
3.3%
2246 1
 
3.3%
669 1
 
3.3%
7973 1
 
3.3%
127 1
 
3.3%
2271 1
 
3.3%
178 1
 
3.3%
2346 1
 
3.3%
260 1
 
3.3%
2701 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
15 1
3.3%
30 1
3.3%
127 1
3.3%
178 1
3.3%
190 1
3.3%
193 1
3.3%
232 1
3.3%
238 1
3.3%
260 1
3.3%
356 1
3.3%
ValueCountFrequency (%)
14033 1
3.3%
7973 1
3.3%
2701 1
3.3%
2552 1
3.3%
2524 1
3.3%
2512 1
3.3%
2406 1
3.3%
2370 1
3.3%
2353 1
3.3%
2346 1
3.3%

고용직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct6
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.8
Minimum0
Maximum5
Zeros19
Zeros (%)63.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-13T05:05:31.910569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile3.55
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.3235272
Coefficient of variation (CV)1.6544089
Kurtosis2.9599991
Mean0.8
Median Absolute Deviation (MAD)0
Skewness1.8281246
Sum24
Variance1.7517241
MonotonicityNot monotonic
2023-12-13T05:05:32.013298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 19
63.3%
2 4
 
13.3%
1 4
 
13.3%
4 1
 
3.3%
5 1
 
3.3%
3 1
 
3.3%
ValueCountFrequency (%)
0 19
63.3%
1 4
 
13.3%
2 4
 
13.3%
3 1
 
3.3%
4 1
 
3.3%
5 1
 
3.3%
ValueCountFrequency (%)
5 1
 
3.3%
4 1
 
3.3%
3 1
 
3.3%
2 4
 
13.3%
1 4
 
13.3%
0 19
63.3%

공안직
Real number (ℝ)

HIGH CORRELATION 

Distinct26
Distinct (%)86.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean483.06667
Minimum8
Maximum7036
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-13T05:05:32.161087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile9
Q119
median116.5
Q3373.25
95-th percentile1162.2
Maximum7036
Range7028
Interquartile range (IQR)354.25

Descriptive statistics

Standard deviation1280.0956
Coefficient of variation (CV)2.6499358
Kurtosis25.810417
Mean483.06667
Median Absolute Deviation (MAD)108
Skewness4.9408275
Sum14492
Variance1638644.8
MonotonicityNot monotonic
2023-12-13T05:05:32.276307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
19 3
 
10.0%
14 2
 
6.7%
9 2
 
6.7%
75 1
 
3.3%
561 1
 
3.3%
158 1
 
3.3%
7036 1
 
3.3%
35 1
 
3.3%
1218 1
 
3.3%
36 1
 
3.3%
Other values (16) 16
53.3%
ValueCountFrequency (%)
8 1
 
3.3%
9 2
6.7%
12 1
 
3.3%
14 2
6.7%
18 1
 
3.3%
19 3
10.0%
32 1
 
3.3%
35 1
 
3.3%
36 1
 
3.3%
37 1
 
3.3%
ValueCountFrequency (%)
7036 1
3.3%
1218 1
3.3%
1094 1
3.3%
820 1
3.3%
667 1
3.3%
561 1
3.3%
456 1
3.3%
389 1
3.3%
326 1
3.3%
315 1
3.3%

군무원
Real number (ℝ)

HIGH CORRELATION 

Distinct27
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean479.23333
Minimum21
Maximum7873
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-13T05:05:32.394927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21
5-th percentile28
Q138
median188
Q3366.25
95-th percentile746.5
Maximum7873
Range7852
Interquartile range (IQR)328.25

Descriptive statistics

Standard deviation1415.9173
Coefficient of variation (CV)2.9545467
Kurtosis28.209838
Mean479.23333
Median Absolute Deviation (MAD)150.5
Skewness5.2438048
Sum14377
Variance2004821.7
MonotonicityNot monotonic
2023-12-13T05:05:32.514336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
28 2
 
6.7%
34 2
 
6.7%
38 2
 
6.7%
204 1
 
3.3%
385 1
 
3.3%
570 1
 
3.3%
7873 1
 
3.3%
778 1
 
3.3%
44 1
 
3.3%
708 1
 
3.3%
Other values (17) 17
56.7%
ValueCountFrequency (%)
21 1
3.3%
28 2
6.7%
30 1
3.3%
34 2
6.7%
37 1
3.3%
38 2
6.7%
39 1
3.3%
40 1
3.3%
41 1
3.3%
44 1
3.3%
ValueCountFrequency (%)
7873 1
3.3%
778 1
3.3%
708 1
3.3%
694 1
3.3%
570 1
3.3%
528 1
3.3%
511 1
3.3%
385 1
3.3%
310 1
3.3%
270 1
3.3%

연구직
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)73.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean109
Minimum7
Maximum1596
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-13T05:05:32.628666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile9
Q114.25
median41.5
Q381
95-th percentile229.95
Maximum1596
Range1589
Interquartile range (IQR)66.75

Descriptive statistics

Standard deviation287.42591
Coefficient of variation (CV)2.636935
Kurtosis27.062075
Mean109
Median Absolute Deviation (MAD)28.5
Skewness5.1017069
Sum3270
Variance82613.655
MonotonicityNot monotonic
2023-12-13T05:05:32.746826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
9 3
 
10.0%
54 2
 
6.7%
19 2
 
6.7%
34 2
 
6.7%
17 2
 
6.7%
13 2
 
6.7%
49 2
 
6.7%
164 1
 
3.3%
83 1
 
3.3%
1596 1
 
3.3%
Other values (12) 12
40.0%
ValueCountFrequency (%)
7 1
 
3.3%
9 3
10.0%
11 1
 
3.3%
13 2
6.7%
14 1
 
3.3%
15 1
 
3.3%
17 2
6.7%
19 2
6.7%
34 2
6.7%
49 2
6.7%
ValueCountFrequency (%)
1596 1
3.3%
261 1
3.3%
192 1
3.3%
164 1
3.3%
137 1
3.3%
99 1
3.3%
97 1
3.3%
83 1
3.3%
75 1
3.3%
63 1
3.3%

지도직
Real number (ℝ)

HIGH CORRELATION 

Distinct24
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean153.76667
Minimum4
Maximum3220
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-13T05:05:32.876793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile4.45
Q17.25
median21.5
Q374.25
95-th percentile204.8
Maximum3220
Range3216
Interquartile range (IQR)67

Descriptive statistics

Standard deviation582.06462
Coefficient of variation (CV)3.7853758
Kurtosis29.331893
Mean153.76667
Median Absolute Deviation (MAD)15.5
Skewness5.3902706
Sum4613
Variance338799.22
MonotonicityNot monotonic
2023-12-13T05:05:33.005175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
7 4
 
13.3%
8 2
 
6.7%
5 2
 
6.7%
4 2
 
6.7%
12 1
 
3.3%
72 1
 
3.3%
150 1
 
3.3%
3220 1
 
3.3%
11 1
 
3.3%
221 1
 
3.3%
Other values (14) 14
46.7%
ValueCountFrequency (%)
4 2
6.7%
5 2
6.7%
7 4
13.3%
8 2
6.7%
9 1
 
3.3%
10 1
 
3.3%
11 1
 
3.3%
12 1
 
3.3%
14 1
 
3.3%
29 1
 
3.3%
ValueCountFrequency (%)
3220 1
3.3%
221 1
3.3%
185 1
3.3%
150 1
3.3%
145 1
3.3%
102 1
3.3%
78 1
3.3%
75 1
3.3%
72 1
3.3%
62 1
3.3%

계약직
Real number (ℝ)

HIGH CORRELATION 

Distinct24
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean81.466667
Minimum6
Maximum684
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-13T05:05:33.122893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile6.9
Q113.25
median38.5
Q354.5
95-th percentile437.35
Maximum684
Range678
Interquartile range (IQR)41.25

Descriptive statistics

Standard deviation155.86151
Coefficient of variation (CV)1.9131936
Kurtosis9.6357051
Mean81.466667
Median Absolute Deviation (MAD)25
Skewness3.1645629
Sum2444
Variance24292.809
MonotonicityNot monotonic
2023-12-13T05:05:33.258475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
40 2
 
6.7%
46 2
 
6.7%
14 2
 
6.7%
8 2
 
6.7%
10 2
 
6.7%
6 2
 
6.7%
544 1
 
3.3%
56 1
 
3.3%
35 1
 
3.3%
684 1
 
3.3%
Other values (14) 14
46.7%
ValueCountFrequency (%)
6 2
6.7%
8 2
6.7%
10 2
6.7%
11 1
3.3%
13 1
3.3%
14 2
6.7%
18 1
3.3%
25 1
3.3%
27 1
3.3%
35 1
3.3%
ValueCountFrequency (%)
684 1
3.3%
544 1
3.3%
307 1
3.3%
92 1
3.3%
73 1
3.3%
72 1
3.3%
68 1
3.3%
56 1
3.3%
50 1
3.3%
46 2
6.7%

기타
Real number (ℝ)

HIGH CORRELATION 

Distinct28
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean575.53333
Minimum39
Maximum5619
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-13T05:05:33.371586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum39
5-th percentile40.9
Q154
median273.5
Q3714.75
95-th percentile1434.05
Maximum5619
Range5580
Interquartile range (IQR)660.75

Descriptive statistics

Standard deviation1041.5452
Coefficient of variation (CV)1.8097044
Kurtosis20.092887
Mean575.53333
Median Absolute Deviation (MAD)229.5
Skewness4.1962576
Sum17266
Variance1084816.4
MonotonicityNot monotonic
2023-12-13T05:05:33.488013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
44 2
 
6.7%
42 2
 
6.7%
720 1
 
3.3%
828 1
 
3.3%
1754 1
 
3.3%
5619 1
 
3.3%
131 1
 
3.3%
968 1
 
3.3%
114 1
 
3.3%
1043 1
 
3.3%
Other values (18) 18
60.0%
ValueCountFrequency (%)
39 1
3.3%
40 1
3.3%
42 2
6.7%
44 2
6.7%
49 1
3.3%
53 1
3.3%
57 1
3.3%
64 1
3.3%
105 1
3.3%
114 1
3.3%
ValueCountFrequency (%)
5619 1
3.3%
1754 1
3.3%
1043 1
3.3%
996 1
3.3%
968 1
3.3%
915 1
3.3%
828 1
3.3%
720 1
3.3%
699 1
3.3%
551 1
3.3%

Interactions

2023-12-13T05:05:26.443568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:00.712725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:02.293103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:04.068859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:06.077296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:07.930374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:09.662761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:11.210207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:12.662917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:14.464061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:16.123133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:17.461354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:19.435481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:21.325711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:23.054285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:24.635972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:26.520374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:00.817573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:02.403676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:04.223957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:06.180433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:08.018337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:09.785592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:11.318431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:13.004143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:14.575895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:16.222522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:17.548580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:19.550127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:21.426516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:23.151912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:24.720961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:26.597587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:00.890871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:02.504610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:04.360178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:06.283315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:08.115239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:09.872535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:11.423208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:13.072891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:14.655345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:16.317596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:17.632199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:19.659870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:21.529756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:23.247120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:24.822051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:26.671319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:00.967971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:02.598412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:04.488456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:06.388208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:08.206436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:09.971774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:11.532693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:13.146739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:14.749408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:16.395002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:17.710414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:19.761108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:21.636431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:23.337569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:24.914475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:26.748191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:01.056423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:02.703779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:04.637540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:06.776551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:08.294360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:10.066609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:11.630764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:13.223759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:14.831771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:16.481373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:17.794481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:19.865370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:21.727039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:23.427034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:24.996495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:26.832445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:01.150371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:02.810599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:04.817784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:06.867347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:08.408442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:10.163316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:11.710426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:13.327785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:14.926670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:16.554675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:17.875433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:19.999434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:21.818925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:23.536522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:25.076380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:26.905318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:01.230015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:02.912426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:04.963059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:06.966170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:08.509502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:10.246994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:11.786731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:13.413677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:15.010178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:16.643037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:17.961074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:20.121766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:21.947007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:23.630568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:25.463566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:27.000341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:01.331174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:03.002316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:05.090320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:07.053944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:08.611193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:10.342807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:11.871958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:13.501887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:15.107151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:16.730126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:18.051296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:20.229877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:22.086817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:23.723053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:25.550171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:27.074236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:01.443906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:03.090266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:05.201103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:07.131830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:08.706603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:10.419224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:11.952780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:13.575328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:15.184031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:16.798064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:18.136415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:20.337083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:22.194859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:23.821709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:25.643081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:27.171751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:01.566499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:03.189018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:05.311303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:07.224302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:08.815524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:10.528907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:12.040281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:13.664786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:15.278469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:16.884559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:18.234288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:20.461336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:22.289349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:23.927119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:25.757705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:27.256675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:01.675395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:03.290369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:05.414226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:07.309713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:08.948472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:10.623160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:12.123761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:13.782978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:15.378547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:16.953191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:18.328488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:20.587806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:22.383359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:24.035498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:25.848592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:27.376957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:01.781395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:03.401258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:05.519645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:07.407120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:09.061610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:10.721714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:12.214308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:13.880324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:15.558895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:17.037407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:18.436800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:20.715241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:22.505167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:24.148397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:25.960762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:27.481586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:01.886234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:03.551607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:05.639067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:07.508099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:09.187602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:10.819096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:12.303231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:13.999316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:15.672904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:17.133960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:18.591205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:20.841655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:22.615626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:24.252912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:26.061713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:27.576078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:01.984288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:03.688372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:05.765999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:07.630542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:09.308264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:10.922013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:12.398906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:14.109771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:15.799273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:17.217106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:18.709079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:20.971346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:22.716773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:24.356262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:26.154318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:27.655412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:02.075454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:03.804813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:05.874219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:07.722600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:09.411927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:11.006369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:12.494136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:14.230686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:15.907274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:17.293639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:19.151069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:21.090503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:22.844486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:24.443021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:26.242954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:27.749936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:02.180612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:03.932669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:05.985791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:07.814652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:09.526990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:11.103579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:12.585515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:14.342049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:16.021212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:17.375898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:19.325075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:21.220379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:22.955689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:24.549551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:05:26.360781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:05:33.596701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분남여구분정무직별정직일반직경찰소방교육직법관검사기능직고용직공안직군무원연구직지도직계약직기타
구분1.0000.0000.3710.1460.0000.3710.1910.2200.3710.0000.0000.2410.0000.1910.2200.1910.4550.000
남여구분0.0001.0000.0080.3010.9110.0080.0000.1320.0080.9970.9730.1560.1860.0000.1320.0000.0630.764
0.3710.0081.0000.6770.6491.0001.0000.9321.0000.0000.6550.0000.9321.0000.9321.0000.6761.000
정무직0.1460.3010.6771.0000.8410.6771.0000.8520.6770.9380.6440.0000.8801.0000.8521.0000.8430.749
별정직0.0000.9110.6490.8411.0000.6491.0000.7800.6490.8310.9520.1410.8481.0000.7801.0000.6440.946
일반직0.3710.0081.0000.6770.6491.0001.0000.9321.0000.0000.6550.0000.9321.0000.9321.0000.6761.000
경찰0.1910.0001.0001.0001.0001.0001.0001.0001.0000.6571.0000.3651.0000.6551.0000.6551.0001.000
소방0.2200.1320.9320.8520.7800.9321.0001.0000.9320.6480.6740.0000.9931.0001.0001.0000.8130.717
교육직0.3710.0081.0000.6770.6491.0001.0000.9321.0000.0000.6550.0000.9321.0000.9321.0000.6431.000
법관검사0.0000.9970.0000.9380.8310.0000.6570.6480.0001.0000.7790.7470.8090.6570.6480.6570.8550.642
기능직0.0000.9730.6550.6440.9520.6551.0000.6740.6550.7791.0000.7760.6891.0000.6741.0000.5950.901
고용직0.2410.1560.0000.0000.1410.0000.3650.0000.0000.7470.7761.0000.0000.3650.0000.3650.0000.000
공안직0.0000.1860.9320.8800.8480.9321.0000.9930.9320.8090.6890.0001.0001.0000.9931.0000.7690.753
군무원0.1910.0001.0001.0001.0001.0000.6551.0001.0000.6571.0000.3651.0001.0001.0000.6551.0001.000
연구직0.2200.1320.9320.8520.7800.9321.0001.0000.9320.6480.6740.0000.9931.0001.0001.0000.8130.717
지도직0.1910.0001.0001.0001.0001.0000.6551.0001.0000.6571.0000.3651.0000.6551.0001.0001.0001.000
계약직0.4550.0630.6760.8430.6440.6761.0000.8130.6430.8550.5950.0000.7691.0000.8131.0001.0000.640
기타0.0000.7641.0000.7490.9461.0001.0000.7171.0000.6420.9010.0000.7531.0000.7171.0000.6401.000
2023-12-13T05:05:33.817768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정무직별정직일반직경찰소방교육직법관검사기능직고용직공안직군무원연구직지도직계약직기타남여구분
1.0000.8750.7110.9350.8540.7660.1990.4430.6520.1650.9100.8650.8380.8480.5610.8890.000
정무직0.8751.0000.8760.8700.9250.872-0.0320.6500.7240.2260.9350.8570.8610.8470.6750.8750.341
별정직0.7110.8761.0000.7910.8600.915-0.2190.7280.8180.2890.8180.8160.8560.8550.7260.7590.702
일반직0.9350.8700.7911.0000.8970.8310.0670.5360.6980.2200.9210.8680.9030.8950.6930.9150.000
경찰0.8540.9250.8600.8971.0000.939-0.0770.6720.7020.2220.9520.8570.9090.8560.7300.9060.000
소방0.7660.8720.9150.8310.9391.000-0.1740.7370.7360.2050.8880.8660.9080.8800.7660.8260.209
교육직0.199-0.032-0.2190.067-0.077-0.1741.000-0.668-0.313-0.535-0.0200.056-0.0370.018-0.3520.0590.000
법관검사0.4430.6500.7280.5360.6720.737-0.6681.0000.7680.6670.6390.5160.6080.5570.7120.5020.803
기능직0.6520.7240.8180.6980.7020.736-0.3130.7681.0000.6500.6890.6240.6230.7190.5340.5290.820
고용직0.1650.2260.2890.2200.2220.205-0.5350.6670.6501.0000.2010.0180.1150.1300.2700.0610.070
공안직0.9100.9350.8180.9210.9520.888-0.0200.6390.6890.2011.0000.8810.8990.8710.7250.9110.296
군무원0.8650.8570.8160.8680.8570.8660.0560.5160.6240.0180.8811.0000.8900.9100.6310.8930.000
연구직0.8380.8610.8560.9030.9090.908-0.0370.6080.6230.1150.8990.8901.0000.8720.7710.9070.209
지도직0.8480.8470.8550.8950.8560.8800.0180.5570.7190.1300.8710.9100.8721.0000.6060.8560.000
계약직0.5610.6750.7260.6930.7300.766-0.3520.7120.5340.2700.7250.6310.7710.6061.0000.7230.023
기타0.8890.8750.7590.9150.9060.8260.0590.5020.5290.0610.9110.8930.9070.8560.7231.0000.533
남여구분0.0000.3410.7020.0000.0000.2090.0000.8030.8200.0700.2960.0000.2090.0000.0230.5331.000

Missing values

2023-12-13T05:05:27.870939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:05:28.093100image/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

구분남여구분정무직별정직일반직경찰소방교육직법관검사기능직고용직공안직군무원연구직지도직계약직기타
020년미만347210101107312538365121300752045412544720
120년미만3231016130624121158311503238495307238
220년2131923263483230789517217140334389221543173266
320년5038387148318111514121750219211983853
421년69312224924003167740622823705283187343340281
521년307705597015412724616119281772544
622년698119254236635312641515924063259189342946323
722년27800619481051209542201434991440
823년759025281262543011046715825522260206493646343
923년2834173970133120854451930951844
구분남여구분정무직별정직일반직경찰소방교육직법관검사기능직고용직공안직군무원연구직지도직계약직기타
2029년15193120580639512783711696832277066752813710244915
2129년5339327102315039311190018391341164
2230년18739112661778418224882212682701082069416414572996
2330년65462151400266459822600376411146105
2431년2108316467887392295665284561234601094708192185681043
2531년6822225121113051670178036441778114
2632년239321256419803314774336194522710121877826122192968
2732년702221411411415487112703534141110131
2833년이상246270453258198980332804993717871937973270367873159632206845619
2933년이상634254881396727037456391669015857083150351754