Overview

Dataset statistics

Number of variables17
Number of observations39
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.9 KiB
Average record size in memory155.4 B

Variable types

Text1
Numeric15
Categorical1

Dataset

Description직종별(정무직, 별정직, 일반직, 소방, 경찰, 교육직 등), 연령별 퇴직연금수급자 현황(퇴직당시 연령기준)에 대한 데이터입니다.
URLhttps://www.data.go.kr/data/15054107/fileData.do

Alerts

is highly overall correlated with 정무직 and 14 other fieldsHigh correlation
정무직 is highly overall correlated with and 10 other fieldsHigh correlation
별정직 is highly overall correlated with and 13 other fieldsHigh correlation
일반직 is highly overall correlated with and 13 other fieldsHigh correlation
경찰 is highly overall correlated with and 14 other fieldsHigh correlation
소방 is highly overall correlated with and 14 other fieldsHigh correlation
교육직 is highly overall correlated with and 12 other fieldsHigh correlation
법관_검사 is highly overall correlated with and 12 other fieldsHigh correlation
기능직 is highly overall correlated with and 11 other fieldsHigh correlation
공안직 is highly overall correlated with and 14 other fieldsHigh correlation
군무원 is highly overall correlated with and 13 other fieldsHigh correlation
연구직 is highly overall correlated with and 13 other fieldsHigh correlation
지도직 is highly overall correlated with and 13 other fieldsHigh correlation
계약직 is highly overall correlated with and 13 other fieldsHigh correlation
기타 is highly overall correlated with and 13 other fieldsHigh correlation
고용직 is highly overall correlated with and 4 other fieldsHigh correlation
구분 has unique valuesUnique
has unique valuesUnique
정무직 has 2 (5.1%) zerosZeros
별정직 has 4 (10.3%) zerosZeros
일반직 has 6 (15.4%) zerosZeros
경찰 has 12 (30.8%) zerosZeros
소방 has 14 (35.9%) zerosZeros
교육직 has 9 (23.1%) zerosZeros
법관_검사 has 7 (17.9%) zerosZeros
기능직 has 13 (33.3%) zerosZeros
공안직 has 12 (30.8%) zerosZeros
군무원 has 14 (35.9%) zerosZeros
연구직 has 13 (33.3%) zerosZeros
지도직 has 14 (35.9%) zerosZeros

Reproduction

Analysis started2023-12-12 05:14:21.821979
Analysis finished2023-12-12 05:14:50.151761
Duration28.33 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Text

UNIQUE 

Distinct39
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size444.0 B
2023-12-12T14:14:50.327944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.1538462
Min length3

Characters and Unicode

Total characters123
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

Unique39 ?
Unique (%)100.0%

Sample

1st row38세미만
2nd row38세이상
3rd row39세
4th row40세
5th row41세
ValueCountFrequency (%)
38세미만 1
 
2.6%
57세 1
 
2.6%
59세 1
 
2.6%
60세 1
 
2.6%
61세 1
 
2.6%
62세 1
 
2.6%
63세 1
 
2.6%
64세 1
 
2.6%
65세 1
 
2.6%
58세 1
 
2.6%
Other values (29) 29
74.4%
2023-12-12T14:14:50.772445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
39
31.7%
4 14
 
11.4%
5 14
 
11.4%
6 13
 
10.6%
7 9
 
7.3%
3 7
 
5.7%
8 5
 
4.1%
9 4
 
3.3%
0 4
 
3.3%
1 4
 
3.3%
Other values (5) 10
 
8.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 78
63.4%
Other Letter 45
36.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 14
17.9%
5 14
17.9%
6 13
16.7%
7 9
11.5%
3 7
9.0%
8 5
 
6.4%
9 4
 
5.1%
0 4
 
5.1%
1 4
 
5.1%
2 4
 
5.1%
Other Letter
ValueCountFrequency (%)
39
86.7%
2
 
4.4%
2
 
4.4%
1
 
2.2%
1
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
Common 78
63.4%
Hangul 45
36.6%

Most frequent character per script

Common
ValueCountFrequency (%)
4 14
17.9%
5 14
17.9%
6 13
16.7%
7 9
11.5%
3 7
9.0%
8 5
 
6.4%
9 4
 
5.1%
0 4
 
5.1%
1 4
 
5.1%
2 4
 
5.1%
Hangul
ValueCountFrequency (%)
39
86.7%
2
 
4.4%
2
 
4.4%
1
 
2.2%
1
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 78
63.4%
Hangul 45
36.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
39
86.7%
2
 
4.4%
2
 
4.4%
1
 
2.2%
1
 
2.2%
ASCII
ValueCountFrequency (%)
4 14
17.9%
5 14
17.9%
6 13
16.7%
7 9
11.5%
3 7
9.0%
8 5
 
6.4%
9 4
 
5.1%
0 4
 
5.1%
1 4
 
5.1%
2 4
 
5.1%


Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct39
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14000.256
Minimum9
Maximum141145
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-12T14:14:50.979445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9
5-th percentile16.3
Q1610
median5754
Q313497.5
95-th percentile51883
Maximum141145
Range141136
Interquartile range (IQR)12887.5

Descriptive statistics

Standard deviation25816.037
Coefficient of variation (CV)1.8439689
Kurtosis15.516733
Mean14000.256
Median Absolute Deviation (MAD)5631
Skewness3.5940417
Sum546010
Variance6.6646778 × 108
MonotonicityNot monotonic
2023-12-12T14:14:51.119122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
670 1
 
2.6%
550 1
 
2.6%
50912 1
 
2.6%
141145 1
 
2.6%
16302 1
 
2.6%
48353 1
 
2.6%
21525 1
 
2.6%
1619 1
 
2.6%
7639 1
 
2.6%
3193 1
 
2.6%
Other values (29) 29
74.4%
ValueCountFrequency (%)
9 1
2.6%
10 1
2.6%
17 1
2.6%
21 1
2.6%
26 1
2.6%
51 1
2.6%
55 1
2.6%
99 1
2.6%
123 1
2.6%
550 1
2.6%
ValueCountFrequency (%)
141145 1
2.6%
60622 1
2.6%
50912 1
2.6%
48353 1
2.6%
42240 1
2.6%
24091 1
2.6%
21525 1
2.6%
19380 1
2.6%
16302 1
2.6%
14709 1
2.6%

정무직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct26
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.487179
Minimum0
Maximum153
Zeros2
Zeros (%)5.1%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-12T14:14:51.282102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.9
Q13
median10
Q343.5
95-th percentile132.9
Maximum153
Range153
Interquartile range (IQR)40.5

Descriptive statistics

Standard deviation46.320322
Coefficient of variation (CV)1.3832255
Kurtosis0.88975065
Mean33.487179
Median Absolute Deviation (MAD)9
Skewness1.4882117
Sum1306
Variance2145.5722
MonotonicityNot monotonic
2023-12-12T14:14:51.477415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
3 5
 
12.8%
1 5
 
12.8%
0 2
 
5.1%
5 2
 
5.1%
8 2
 
5.1%
16 2
 
5.1%
113 2
 
5.1%
94 1
 
2.6%
12 1
 
2.6%
13 1
 
2.6%
Other values (16) 16
41.0%
ValueCountFrequency (%)
0 2
 
5.1%
1 5
12.8%
3 5
12.8%
4 1
 
2.6%
5 2
 
5.1%
6 1
 
2.6%
7 1
 
2.6%
8 2
 
5.1%
10 1
 
2.6%
12 1
 
2.6%
ValueCountFrequency (%)
153 1
2.6%
150 1
2.6%
131 1
2.6%
113 2
5.1%
102 1
2.6%
94 1
2.6%
85 1
2.6%
52 1
2.6%
50 1
2.6%
37 1
2.6%

별정직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct31
Distinct (%)79.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean233.82051
Minimum0
Maximum1447
Zeros4
Zeros (%)10.3%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-12T14:14:51.664524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14.5
median67
Q3345.5
95-th percentile864.5
Maximum1447
Range1447
Interquartile range (IQR)341

Descriptive statistics

Standard deviation329.0347
Coefficient of variation (CV)1.4072106
Kurtosis3.9531851
Mean233.82051
Median Absolute Deviation (MAD)67
Skewness1.9010575
Sum9119
Variance108263.84
MonotonicityNot monotonic
2023-12-12T14:14:51.848644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0 4
 
10.3%
10 2
 
5.1%
3 2
 
5.1%
1 2
 
5.1%
4 2
 
5.1%
5 2
 
5.1%
28 1
 
2.6%
41 1
 
2.6%
489 1
 
2.6%
854 1
 
2.6%
Other values (21) 21
53.8%
ValueCountFrequency (%)
0 4
10.3%
1 2
5.1%
3 2
5.1%
4 2
5.1%
5 2
5.1%
10 2
5.1%
25 1
 
2.6%
28 1
 
2.6%
34 1
 
2.6%
41 1
 
2.6%
ValueCountFrequency (%)
1447 1
2.6%
959 1
2.6%
854 1
2.6%
694 1
2.6%
630 1
2.6%
615 1
2.6%
497 1
2.6%
489 1
2.6%
391 1
2.6%
362 1
2.6%

일반직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct32
Distinct (%)82.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4976.359
Minimum0
Maximum88635
Zeros6
Zeros (%)15.4%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-12T14:14:52.011935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14.5
median1587
Q32717
95-th percentile18171
Maximum88635
Range88635
Interquartile range (IQR)2712.5

Descriptive statistics

Standard deviation14638.553
Coefficient of variation (CV)2.9416192
Kurtosis29.737971
Mean4976.359
Median Absolute Deviation (MAD)1571
Skewness5.2404505
Sum194078
Variance2.1428724 × 108
MonotonicityNot monotonic
2023-12-12T14:14:52.153963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
0 6
 
15.4%
1 3
 
7.7%
231 1
 
2.6%
4035 1
 
2.6%
5 1
 
2.6%
4 1
 
2.6%
16 1
 
2.6%
20 1
 
2.6%
23 1
 
2.6%
2887 1
 
2.6%
Other values (22) 22
56.4%
ValueCountFrequency (%)
0 6
15.4%
1 3
7.7%
4 1
 
2.6%
5 1
 
2.6%
16 1
 
2.6%
20 1
 
2.6%
23 1
 
2.6%
231 1
 
2.6%
233 1
 
2.6%
775 1
 
2.6%
ValueCountFrequency (%)
88635 1
2.6%
23760 1
2.6%
17550 1
2.6%
14619 1
2.6%
6929 1
2.6%
5325 1
2.6%
4035 1
2.6%
3413 1
2.6%
2898 1
2.6%
2887 1
2.6%

경찰
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct28
Distinct (%)71.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1211.8462
Minimum0
Maximum16950
Zeros12
Zeros (%)30.8%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-12T14:14:52.308838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median90
Q3510
95-th percentile5656.5
Maximum16950
Range16950
Interquartile range (IQR)510

Descriptive statistics

Standard deviation3205.2619
Coefficient of variation (CV)2.6449413
Kurtosis16.483307
Mean1211.8462
Median Absolute Deviation (MAD)90
Skewness3.8969081
Sum47262
Variance10273704
MonotonicityNot monotonic
2023-12-12T14:14:52.513928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0 12
30.8%
51 1
 
2.6%
679 1
 
2.6%
1 1
 
2.6%
2 1
 
2.6%
449 1
 
2.6%
16950 1
 
2.6%
5181 1
 
2.6%
4689 1
 
2.6%
9936 1
 
2.6%
Other values (18) 18
46.2%
ValueCountFrequency (%)
0 12
30.8%
1 1
 
2.6%
2 1
 
2.6%
11 1
 
2.6%
17 1
 
2.6%
31 1
 
2.6%
51 1
 
2.6%
53 1
 
2.6%
90 1
 
2.6%
137 1
 
2.6%
ValueCountFrequency (%)
16950 1
2.6%
9936 1
2.6%
5181 1
2.6%
4689 1
2.6%
2341 1
2.6%
1791 1
2.6%
1218 1
2.6%
975 1
2.6%
679 1
2.6%
540 1
2.6%

소방
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct25
Distinct (%)64.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean226.17949
Minimum0
Maximum4754
Zeros14
Zeros (%)35.9%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-12T14:14:52.701939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median15
Q396.5
95-th percentile770
Maximum4754
Range4754
Interquartile range (IQR)96.5

Descriptive statistics

Standard deviation780.04483
Coefficient of variation (CV)3.4487868
Kurtosis31.814625
Mean226.17949
Median Absolute Deviation (MAD)15
Skewness5.4685284
Sum8821
Variance608469.94
MonotonicityNot monotonic
2023-12-12T14:14:52.868340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0 14
35.9%
15 2
 
5.1%
8 1
 
2.6%
112 1
 
2.6%
38 1
 
2.6%
4754 1
 
2.6%
725 1
 
2.6%
594 1
 
2.6%
1175 1
 
2.6%
307 1
 
2.6%
Other values (15) 15
38.5%
ValueCountFrequency (%)
0 14
35.9%
3 1
 
2.6%
4 1
 
2.6%
8 1
 
2.6%
12 1
 
2.6%
13 1
 
2.6%
15 2
 
5.1%
30 1
 
2.6%
36 1
 
2.6%
38 1
 
2.6%
ValueCountFrequency (%)
4754 1
2.6%
1175 1
2.6%
725 1
2.6%
594 1
2.6%
307 1
2.6%
251 1
2.6%
180 1
2.6%
134 1
2.6%
118 1
2.6%
112 1
2.6%

교육직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct31
Distinct (%)79.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4356.5641
Minimum0
Maximum47950
Zeros9
Zeros (%)23.1%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-12T14:14:53.062930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q196
median1177
Q35696.5
95-th percentile11897.6
Maximum47950
Range47950
Interquartile range (IQR)5600.5

Descriptive statistics

Standard deviation8493.6407
Coefficient of variation (CV)1.9496191
Kurtosis18.675434
Mean4356.5641
Median Absolute Deviation (MAD)1177
Skewness3.9425345
Sum169906
Variance72141933
MonotonicityNot monotonic
2023-12-12T14:14:53.213074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0 9
23.1%
194 1
 
2.6%
84 1
 
2.6%
3029 1
 
2.6%
7401 1
 
2.6%
1378 1
 
2.6%
21164 1
 
2.6%
47950 1
 
2.6%
10868 1
 
2.6%
9751 1
 
2.6%
Other values (21) 21
53.8%
ValueCountFrequency (%)
0 9
23.1%
84 1
 
2.6%
108 1
 
2.6%
175 1
 
2.6%
194 1
 
2.6%
287 1
 
2.6%
419 1
 
2.6%
614 1
 
2.6%
741 1
 
2.6%
842 1
 
2.6%
ValueCountFrequency (%)
47950 1
2.6%
21164 1
2.6%
10868 1
2.6%
10242 1
2.6%
9751 1
2.6%
9563 1
2.6%
9437 1
2.6%
7785 1
2.6%
7401 1
2.6%
6443 1
2.6%

법관_검사
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct31
Distinct (%)79.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean53.384615
Minimum0
Maximum186
Zeros7
Zeros (%)17.9%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-12T14:14:53.370338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15
median26
Q386
95-th percentile170.2
Maximum186
Range186
Interquartile range (IQR)81

Descriptive statistics

Standard deviation58.943155
Coefficient of variation (CV)1.1041225
Kurtosis-0.29566184
Mean53.384615
Median Absolute Deviation (MAD)26
Skewness0.97340852
Sum2082
Variance3474.2955
MonotonicityNot monotonic
2023-12-12T14:14:53.534785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0 7
 
17.9%
8 2
 
5.1%
56 2
 
5.1%
2 1
 
2.6%
3 1
 
2.6%
1 1
 
2.6%
26 1
 
2.6%
10 1
 
2.6%
22 1
 
2.6%
35 1
 
2.6%
Other values (21) 21
53.8%
ValueCountFrequency (%)
0 7
17.9%
1 1
 
2.6%
2 1
 
2.6%
3 1
 
2.6%
7 1
 
2.6%
8 2
 
5.1%
9 1
 
2.6%
10 1
 
2.6%
14 1
 
2.6%
15 1
 
2.6%
ValueCountFrequency (%)
186 1
2.6%
181 1
2.6%
169 1
2.6%
157 1
2.6%
149 1
2.6%
143 1
2.6%
119 1
2.6%
107 1
2.6%
104 1
2.6%
88 1
2.6%

기능직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct27
Distinct (%)69.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1460.2564
Minimum0
Maximum14332
Zeros13
Zeros (%)33.3%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-12T14:14:53.712975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1163
Q31814
95-th percentile4411.7
Maximum14332
Range14332
Interquartile range (IQR)1814

Descriptive statistics

Standard deviation2460.0045
Coefficient of variation (CV)1.6846387
Kurtosis20.219524
Mean1460.2564
Median Absolute Deviation (MAD)1130
Skewness4.0619838
Sum56950
Variance6051622
MonotonicityNot monotonic
2023-12-12T14:14:53.847585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 13
33.3%
33 1
 
2.6%
159 1
 
2.6%
1 1
 
2.6%
744 1
 
2.6%
1163 1
 
2.6%
5633 1
 
2.6%
4276 1
 
2.6%
14332 1
 
2.6%
2345 1
 
2.6%
Other values (17) 17
43.6%
ValueCountFrequency (%)
0 13
33.3%
1 1
 
2.6%
33 1
 
2.6%
159 1
 
2.6%
549 1
 
2.6%
744 1
 
2.6%
845 1
 
2.6%
1163 1
 
2.6%
1353 1
 
2.6%
1443 1
 
2.6%
ValueCountFrequency (%)
14332 1
2.6%
5633 1
2.6%
4276 1
2.6%
2390 1
2.6%
2345 1
2.6%
2281 1
2.6%
1971 1
2.6%
1965 1
2.6%
1849 1
2.6%
1823 1
2.6%

고용직
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)12.8%
Missing0
Missing (%)0.0%
Memory size444.0 B
0
27 
1
2
3
 
2
5
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)2.6%

Sample

1st row2
2nd row1
3rd row2
4th row3
5th row1

Common Values

ValueCountFrequency (%)
0 27
69.2%
1 5
 
12.8%
2 4
 
10.3%
3 2
 
5.1%
5 1
 
2.6%

Length

2023-12-12T14:14:54.030138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:14:54.151709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 27
69.2%
1 5
 
12.8%
2 4
 
10.3%
3 2
 
5.1%
5 1
 
2.6%

공안직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct27
Distinct (%)69.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean371.58974
Minimum0
Maximum3382
Zeros12
Zeros (%)30.8%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-12T14:14:54.286345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median67
Q3338
95-th percentile1568
Maximum3382
Range3382
Interquartile range (IQR)338

Descriptive statistics

Standard deviation699.68909
Coefficient of variation (CV)1.8829613
Kurtosis9.3517789
Mean371.58974
Median Absolute Deviation (MAD)67
Skewness2.8934687
Sum14492
Variance489564.83
MonotonicityNot monotonic
2023-12-12T14:14:54.438174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 12
30.8%
1 2
 
5.1%
10 1
 
2.6%
6 1
 
2.6%
67 1
 
2.6%
3382 1
 
2.6%
1271 1
 
2.6%
1490 1
 
2.6%
2270 1
 
2.6%
1042 1
 
2.6%
Other values (17) 17
43.6%
ValueCountFrequency (%)
0 12
30.8%
1 2
 
5.1%
6 1
 
2.6%
10 1
 
2.6%
18 1
 
2.6%
19 1
 
2.6%
46 1
 
2.6%
67 1
 
2.6%
82 1
 
2.6%
110 1
 
2.6%
ValueCountFrequency (%)
3382 1
2.6%
2270 1
2.6%
1490 1
2.6%
1271 1
2.6%
1042 1
2.6%
922 1
2.6%
698 1
2.6%
601 1
2.6%
473 1
2.6%
378 1
2.6%

군무원
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct23
Distinct (%)59.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean368.64103
Minimum0
Maximum3675
Zeros14
Zeros (%)35.9%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-12T14:14:54.591791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median14
Q3201
95-th percentile2493.8
Maximum3675
Range3675
Interquartile range (IQR)201

Descriptive statistics

Standard deviation821.78085
Coefficient of variation (CV)2.229217
Kurtosis8.0429241
Mean368.64103
Median Absolute Deviation (MAD)14
Skewness2.8579763
Sum14377
Variance675323.76
MonotonicityNot monotonic
2023-12-12T14:14:54.717858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 14
35.9%
12 2
 
5.1%
57 2
 
5.1%
1 2
 
5.1%
324 1
 
2.6%
3675 1
 
2.6%
991 1
 
2.6%
2636 1
 
2.6%
2478 1
 
2.6%
1280 1
 
2.6%
Other values (13) 13
33.3%
ValueCountFrequency (%)
0 14
35.9%
1 2
 
5.1%
9 1
 
2.6%
12 2
 
5.1%
14 1
 
2.6%
20 1
 
2.6%
27 1
 
2.6%
32 1
 
2.6%
57 2
 
5.1%
70 1
 
2.6%
ValueCountFrequency (%)
3675 1
2.6%
2636 1
2.6%
2478 1
2.6%
1280 1
2.6%
991 1
2.6%
961 1
2.6%
629 1
2.6%
443 1
2.6%
324 1
2.6%
220 1
2.6%

연구직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct26
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean83.846154
Minimum0
Maximum1581
Zeros13
Zeros (%)33.3%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-12T14:14:54.837018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median11
Q338
95-th percentile292.4
Maximum1581
Range1581
Interquartile range (IQR)38

Descriptive statistics

Standard deviation259.79724
Coefficient of variation (CV)3.0984992
Kurtosis30.811674
Mean83.846154
Median Absolute Deviation (MAD)11
Skewness5.3483593
Sum3270
Variance67494.607
MonotonicityNot monotonic
2023-12-12T14:14:54.961862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 13
33.3%
19 2
 
5.1%
5 1
 
2.6%
34 1
 
2.6%
1 1
 
2.6%
104 1
 
2.6%
1581 1
 
2.6%
377 1
 
2.6%
283 1
 
2.6%
252 1
 
2.6%
Other values (16) 16
41.0%
ValueCountFrequency (%)
0 13
33.3%
1 1
 
2.6%
4 1
 
2.6%
5 1
 
2.6%
7 1
 
2.6%
9 1
 
2.6%
10 1
 
2.6%
11 1
 
2.6%
13 1
 
2.6%
19 2
 
5.1%
ValueCountFrequency (%)
1581 1
2.6%
377 1
2.6%
283 1
2.6%
252 1
2.6%
136 1
2.6%
104 1
2.6%
84 1
2.6%
70 1
2.6%
61 1
2.6%
39 1
2.6%

지도직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct26
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean118.28205
Minimum0
Maximum1625
Zeros14
Zeros (%)35.9%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-12T14:14:55.092091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median14
Q359.5
95-th percentile660.3
Maximum1625
Range1625
Interquartile range (IQR)59.5

Descriptive statistics

Standard deviation303.05636
Coefficient of variation (CV)2.56215
Kurtosis16.577035
Mean118.28205
Median Absolute Deviation (MAD)14
Skewness3.8470329
Sum4613
Variance91843.155
MonotonicityNot monotonic
2023-12-12T14:14:55.212961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 14
35.9%
51 1
 
2.6%
1 1
 
2.6%
205 1
 
2.6%
1625 1
 
2.6%
651 1
 
2.6%
551 1
 
2.6%
744 1
 
2.6%
172 1
 
2.6%
117 1
 
2.6%
Other values (16) 16
41.0%
ValueCountFrequency (%)
0 14
35.9%
1 1
 
2.6%
3 1
 
2.6%
4 1
 
2.6%
8 1
 
2.6%
11 1
 
2.6%
14 1
 
2.6%
15 1
 
2.6%
16 1
 
2.6%
17 1
 
2.6%
ValueCountFrequency (%)
1625 1
2.6%
744 1
2.6%
651 1
2.6%
551 1
2.6%
205 1
2.6%
172 1
2.6%
117 1
2.6%
91 1
2.6%
75 1
2.6%
68 1
2.6%

계약직
Real number (ℝ)

HIGH CORRELATION 

Distinct34
Distinct (%)87.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean62.666667
Minimum1
Maximum277
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-12T14:14:55.333296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.5
Q122.5
median43
Q373.5
95-th percentile158.1
Maximum277
Range276
Interquartile range (IQR)51

Descriptive statistics

Standard deviation59.8715
Coefficient of variation (CV)0.95539627
Kurtosis4.330082
Mean62.666667
Median Absolute Deviation (MAD)25
Skewness1.9370186
Sum2444
Variance3584.5965
MonotonicityNot monotonic
2023-12-12T14:14:55.481027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
66 2
 
5.1%
36 2
 
5.1%
21 2
 
5.1%
43 2
 
5.1%
74 2
 
5.1%
7 1
 
2.6%
40 1
 
2.6%
59 1
 
2.6%
32 1
 
2.6%
24 1
 
2.6%
Other values (24) 24
61.5%
ValueCountFrequency (%)
1 1
2.6%
2 1
2.6%
7 1
2.6%
8 1
2.6%
10 1
2.6%
11 1
2.6%
12 1
2.6%
17 1
2.6%
21 2
5.1%
24 1
2.6%
ValueCountFrequency (%)
277 1
2.6%
231 1
2.6%
150 1
2.6%
148 1
2.6%
141 1
2.6%
119 1
2.6%
105 1
2.6%
88 1
2.6%
74 2
5.1%
73 1
2.6%

기타
Real number (ℝ)

HIGH CORRELATION 

Distinct37
Distinct (%)94.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean442.71795
Minimum2
Maximum8361
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-12T14:14:55.649575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile5.8
Q135
median93
Q3198
95-th percentile1170.9
Maximum8361
Range8359
Interquartile range (IQR)163

Descriptive statistics

Standard deviation1355.5851
Coefficient of variation (CV)3.0619609
Kurtosis32.673411
Mean442.71795
Median Absolute Deviation (MAD)69
Skewness5.5477547
Sum17266
Variance1837610.8
MonotonicityNot monotonic
2023-12-12T14:14:55.780779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
105 2
 
5.1%
35 2
 
5.1%
57 1
 
2.6%
1863 1
 
2.6%
8361 1
 
2.6%
180 1
 
2.6%
171 1
 
2.6%
163 1
 
2.6%
140 1
 
2.6%
125 1
 
2.6%
Other values (27) 27
69.2%
ValueCountFrequency (%)
2 1
2.6%
4 1
2.6%
6 1
2.6%
8 1
2.6%
10 1
2.6%
13 1
2.6%
24 1
2.6%
29 1
2.6%
33 1
2.6%
35 2
5.1%
ValueCountFrequency (%)
8361 1
2.6%
1863 1
2.6%
1094 1
2.6%
989 1
2.6%
801 1
2.6%
681 1
2.6%
521 1
2.6%
419 1
2.6%
311 1
2.6%
216 1
2.6%

Interactions

2023-12-12T14:14:47.742599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:22.392924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:24.170260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:26.030177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:27.521266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:29.356031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:31.072129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:32.427109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:34.018993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:36.163851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:38.213386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:40.541773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:42.136332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:44.258574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:46.162457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:47.866967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:22.504844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:24.283290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:26.179497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:27.603869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:29.489075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:31.167978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:32.516697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:34.141606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:36.282926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:38.346244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:40.679957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:42.243117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:44.390924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:46.259161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:47.970168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:22.618697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:24.398602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:26.337289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:27.712070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:29.594783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:31.257334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:32.621622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:34.264966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:36.466708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:38.479595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:40.789168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:42.383029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:44.515069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:46.357764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:48.074302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:22.725361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:24.536285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:26.437621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:27.809636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:29.727715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:31.357044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:32.706887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:34.386936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:36.622566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:38.614225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:40.895158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:42.503631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:44.663715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:46.448548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:48.172952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:22.803373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:24.644923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:26.528078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:27.898108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:29.834728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:31.444883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:32.780758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:34.511724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:36.731926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:38.733550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:40.970209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:42.908313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:44.775180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:46.537020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:48.305332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:22.902117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:24.766472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:26.623094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:27.975167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:29.944984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:31.549161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:32.867913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:34.641099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:36.896826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:38.863691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:41.063922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:43.033892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:44.926433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:46.634873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:48.378904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:23.003619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:24.878975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:26.714159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:28.048611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:30.051427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:31.623646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:32.985476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:34.743741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:37.047848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:38.993987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:41.147277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:43.159042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:45.043430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:46.763758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:48.463587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:23.132636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:24.986721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:26.836362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:28.129891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:30.173266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:31.697876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:33.076229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:34.857735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:37.177553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:39.151908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:41.268925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:43.271884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:45.150725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:46.854514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:48.585463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:23.303725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:25.150298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:26.930751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:28.544608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:30.281544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:31.797666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:33.218985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:34.979100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:37.318590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:39.386159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:41.376882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:43.397442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:45.277973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:46.966499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:48.707698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:23.426483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:25.292992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:27.020481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:28.656952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:30.392147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:31.883001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:33.336072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:35.440935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:37.462108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:39.569405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:41.483341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:43.538131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:45.404137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:47.082255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:48.806437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:23.563183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:25.421451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:27.108201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:28.762445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:30.534633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:31.974812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:33.440863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:35.570081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:37.611054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:39.704881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:41.607930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:43.659342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:45.532720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:47.236190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:48.920397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:23.721977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:25.554514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:27.193895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:28.856570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:30.632911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:32.075374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:33.557930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:35.689490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:37.736202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:39.886956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:41.710547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:43.788471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:45.666108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:47.339629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:49.050929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:23.823353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:25.664439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:27.285698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:28.968040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:30.740479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:32.156086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:33.667256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:35.822069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:37.874431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:40.091198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:41.819304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:43.913111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:45.817597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:47.432265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:49.171451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:23.933648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:25.818467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:27.371965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:29.094221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:30.843105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:32.251282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:33.827788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:35.952859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:38.018921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:40.289855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:41.943713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:44.039314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:45.946245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:47.549598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:49.299051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:24.062991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:25.929547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:27.445974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:29.245275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:30.956276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:32.337076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:33.919675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:36.053666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:38.111663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:40.412959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:42.053477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:44.155495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:46.065838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:14:47.648581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:14:55.894694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분정무직별정직일반직경찰소방교육직법관_검사기능직고용직공안직군무원연구직지도직계약직기타
구분1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
1.0001.0000.8830.9330.9750.9910.9940.7660.6370.8510.6630.9180.9100.9750.9100.8480.975
정무직1.0000.8831.0000.8410.7540.8700.8600.8620.7120.7210.6000.8540.8350.7540.8280.8550.754
별정직1.0000.9330.8411.0000.9880.9460.9970.6870.7940.8890.6980.9400.9240.9880.9080.9280.988
일반직1.0000.9750.7540.9881.0001.0000.9890.4460.6910.8280.4940.9200.9201.0000.8640.9971.000
경찰1.0000.9910.8700.9461.0001.0001.0000.6070.6540.9110.6750.9370.9521.0000.9210.9011.000
소방1.0000.9940.8600.9970.9891.0001.0000.4460.6530.8280.6660.9500.9500.9890.8640.9690.989
교육직1.0000.7660.8620.6870.4460.6070.4461.0000.6220.6450.0000.6580.6260.4460.8380.7470.446
법관_검사1.0000.6370.7120.7940.6910.6540.6530.6221.0000.8450.0000.7100.7220.6910.7070.6760.691
기능직1.0000.8510.7210.8890.8280.9110.8280.6450.8451.0000.8470.8720.8600.8280.9450.8000.828
고용직1.0000.6630.6000.6980.4940.6750.6660.0000.0000.8471.0000.7260.6900.4940.7530.3670.494
공안직1.0000.9180.8540.9400.9200.9370.9500.6580.7100.8720.7261.0000.9880.9200.8950.8370.920
군무원1.0000.9100.8350.9240.9200.9520.9500.6260.7220.8600.6900.9881.0000.9200.9170.8720.920
연구직1.0000.9750.7540.9881.0001.0000.9890.4460.6910.8280.4940.9200.9201.0000.8640.9971.000
지도직1.0000.9100.8280.9080.8640.9210.8640.8380.7070.9450.7530.8950.9170.8641.0000.8690.864
계약직1.0000.8480.8550.9280.9970.9010.9690.7470.6760.8000.3670.8370.8720.9970.8691.0000.997
기타1.0000.9750.7540.9881.0001.0000.9890.4460.6910.8280.4940.9200.9201.0000.8640.9971.000
2023-12-12T14:14:56.487033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정무직별정직일반직경찰소방교육직법관_검사기능직공안직군무원연구직지도직계약직기타고용직
1.0000.7700.8950.8620.8290.7620.9510.7540.6060.7760.7340.7800.8090.9700.9170.513
정무직0.7701.0000.6740.6150.5770.5440.7680.4970.3000.5400.4980.5550.5950.7700.8770.369
별정직0.8950.6741.0000.9800.9660.9440.7790.8170.8130.9470.9190.9390.9540.9020.8540.498
일반직0.8620.6150.9801.0000.9850.9700.7350.8060.8350.9670.9510.9680.9700.8710.8150.414
경찰0.8290.5770.9660.9851.0000.9870.6840.7900.8410.9820.9710.9720.9750.8440.7650.527
소방0.7620.5440.9440.9700.9871.0000.6040.7720.8630.9870.9860.9740.9670.7760.7170.588
교육직0.9510.7680.7790.7350.6840.6041.0000.6710.4460.6060.5650.6450.6690.9310.8890.000
법관_검사0.7540.4970.8170.8060.7900.7720.6711.0000.7370.7800.7670.7440.7460.7290.6870.000
기능직0.6060.3000.8130.8350.8410.8630.4460.7371.0000.8640.8690.8330.8170.6040.5040.479
공안직0.7760.5400.9470.9670.9820.9870.6060.7800.8641.0000.9870.9540.9580.7820.7270.560
군무원0.7340.4980.9190.9510.9710.9860.5650.7670.8690.9871.0000.9480.9330.7420.6920.518
연구직0.7800.5550.9390.9680.9720.9740.6450.7440.8330.9540.9481.0000.9720.8010.7260.414
지도직0.8090.5950.9540.9700.9750.9670.6690.7460.8170.9580.9330.9721.0000.8090.7350.371
계약직0.9700.7700.9020.8710.8440.7760.9310.7290.6040.7820.7420.8010.8091.0000.9300.213
기타0.9170.8770.8540.8150.7650.7170.8890.6870.5040.7270.6920.7260.7350.9301.0000.414
고용직0.5130.3690.4980.4140.5270.5880.0000.0000.4790.5600.5180.4140.3710.2130.4141.000

Missing values

2023-12-12T14:14:49.789632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:14:50.048760image/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

구분정무직별정직일반직경찰소방교육직법관_검사기능직고용직공안직군무원연구직지도직계약직기타
038세미만67001023151819483321012504957
138세이상55013233113842159161932113
239세15791257751741087549218141042124
340세24751341260311217598453199483629
441세3514051158753132871513531461213152741
542세402216715639015419141657082207163635
643세482539017061371561424197131102719144151
744세5562511817371833974164239001363220173842
845세5810313118332013084284228101975711116465
946세57547170182926446965104196502135719224350
구분정무직별정직일반직경찰소방교육직법관_검사기능직고용직공안직군무원연구직지도직계약직기타
2966세31931045003029800000032105
3067세123134100000000002481
3168세99125100010010001762
3269세558110003000000735
3370세5151000000000001233
3471세2633000000000001010
3572세10100000000000018
3673세17300000000000086
3774세9300000000000024
3875세이상218000000000000112