Overview

Dataset statistics

Number of variables17
Number of observations48
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.3 KiB
Average record size in memory154.8 B

Variable types

Text1
Numeric16

Dataset

Description직종별(정무직, 별정직, 일반직, 경찰, 소방, 교육직 등) 연령별 퇴직자 현황에 대한 데이터입니다. 18세부터 시작됩니다.
URLhttps://www.data.go.kr/data/15054052/fileData.do

Alerts

is highly overall correlated with 정무직 and 6 other fieldsHigh correlation
정무직 is highly overall correlated with and 1 other fieldsHigh correlation
별정직 is highly overall correlated with 법관검사 and 3 other fieldsHigh correlation
일반직 is highly overall correlated with and 7 other fieldsHigh correlation
경찰 is highly overall correlated with and 7 other fieldsHigh correlation
소방 is highly overall correlated with and 8 other fieldsHigh correlation
교육직 is highly overall correlated with and 2 other fieldsHigh correlation
법관검사 is highly overall correlated with 별정직 and 1 other fieldsHigh correlation
기능직 is highly overall correlated with 별정직 and 2 other fieldsHigh correlation
공안직 is highly overall correlated with and 7 other fieldsHigh correlation
군무원 is highly overall correlated with 일반직 and 6 other fieldsHigh correlation
연구직 is highly overall correlated with 일반직 and 6 other fieldsHigh correlation
지도직 is highly overall correlated with 일반직 and 5 other fieldsHigh correlation
계약직 is highly overall correlated with 별정직 and 2 other fieldsHigh correlation
기타 is highly overall correlated with and 8 other fieldsHigh correlation
구분 has unique valuesUnique
정무직 has 31 (64.6%) zerosZeros
별정직 has 4 (8.3%) zerosZeros
일반직 has 4 (8.3%) zerosZeros
경찰 has 10 (20.8%) zerosZeros
소방 has 11 (22.9%) zerosZeros
교육직 has 4 (8.3%) zerosZeros
법관검사 has 15 (31.2%) zerosZeros
기능직 has 25 (52.1%) zerosZeros
공안직 has 8 (16.7%) zerosZeros
군무원 has 6 (12.5%) zerosZeros
연구직 has 11 (22.9%) zerosZeros
지도직 has 20 (41.7%) zerosZeros
계약직 has 4 (8.3%) zerosZeros
공중보건의 has 37 (77.1%) zerosZeros
기타 has 3 (6.2%) zerosZeros

Reproduction

Analysis started2023-12-12 11:48:23.111910
Analysis finished2023-12-12 11:48:53.351080
Duration30.24 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Text

UNIQUE 

Distinct48
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size516.0 B
2023-12-12T20:48:53.590614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.0416667
Min length3

Characters and Unicode

Total characters146
Distinct characters13
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

Unique48 ?
Unique (%)100.0%

Sample

1st row18세
2nd row19세
3rd row20세
4th row21세
5th row22세
ValueCountFrequency (%)
18세 1
 
2.1%
19세 1
 
2.1%
53세 1
 
2.1%
44세 1
 
2.1%
45세 1
 
2.1%
46세 1
 
2.1%
47세 1
 
2.1%
48세 1
 
2.1%
49세 1
 
2.1%
50세 1
 
2.1%
Other values (38) 38
79.2%
2023-12-12T20:48:54.102101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
48
32.9%
2 15
 
10.3%
3 15
 
10.3%
4 15
 
10.3%
5 15
 
10.3%
6 10
 
6.8%
1 7
 
4.8%
8 5
 
3.4%
9 5
 
3.4%
0 5
 
3.4%
Other values (3) 6
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 96
65.8%
Other Letter 50
34.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 15
15.6%
3 15
15.6%
4 15
15.6%
5 15
15.6%
6 10
10.4%
1 7
7.3%
8 5
 
5.2%
9 5
 
5.2%
0 5
 
5.2%
7 4
 
4.2%
Other Letter
ValueCountFrequency (%)
48
96.0%
1
 
2.0%
1
 
2.0%

Most occurring scripts

ValueCountFrequency (%)
Common 96
65.8%
Hangul 50
34.2%

Most frequent character per script

Common
ValueCountFrequency (%)
2 15
15.6%
3 15
15.6%
4 15
15.6%
5 15
15.6%
6 10
10.4%
1 7
7.3%
8 5
 
5.2%
9 5
 
5.2%
0 5
 
5.2%
7 4
 
4.2%
Hangul
ValueCountFrequency (%)
48
96.0%
1
 
2.0%
1
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 96
65.8%
Hangul 50
34.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
48
96.0%
1
 
2.0%
1
 
2.0%
ASCII
ValueCountFrequency (%)
2 15
15.6%
3 15
15.6%
4 15
15.6%
5 15
15.6%
6 10
10.4%
1 7
7.3%
8 5
 
5.2%
9 5
 
5.2%
0 5
 
5.2%
7 4
 
4.2%


Real number (ℝ)

HIGH CORRELATION 

Distinct45
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1145.6875
Minimum1
Maximum16567
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-12T20:48:54.312761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile11.15
Q1532.75
median645.5
Q3979.25
95-th percentile2814.55
Maximum16567
Range16566
Interquartile range (IQR)446.5

Descriptive statistics

Standard deviation2376.8061
Coefficient of variation (CV)2.0745675
Kurtosis39.67925
Mean1145.6875
Median Absolute Deviation (MAD)296
Skewness6.0716653
Sum54993
Variance5649207.2
MonotonicityNot monotonic
2023-12-12T20:48:54.538604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
594 2
 
4.2%
532 2
 
4.2%
677 2
 
4.2%
596 1
 
2.1%
538 1
 
2.1%
590 1
 
2.1%
608 1
 
2.1%
710 1
 
2.1%
709 1
 
2.1%
715 1
 
2.1%
Other values (35) 35
72.9%
ValueCountFrequency (%)
1 1
2.1%
7 1
2.1%
8 1
2.1%
17 1
2.1%
39 1
2.1%
70 1
2.1%
84 1
2.1%
180 1
2.1%
344 1
2.1%
510 1
2.1%
ValueCountFrequency (%)
16567 1
2.1%
3266 1
2.1%
2971 1
2.1%
2524 1
2.1%
2104 1
2.1%
1499 1
2.1%
1401 1
2.1%
1349 1
2.1%
1140 1
2.1%
1111 1
2.1%

정무직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct13
Distinct (%)27.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.6458333
Minimum0
Maximum19
Zeros31
Zeros (%)64.6%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-12T20:48:54.712906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32.5
95-th percentile14.65
Maximum19
Range19
Interquartile range (IQR)2.5

Descriptive statistics

Standard deviation4.9871733
Coefficient of variation (CV)1.8849159
Kurtosis3.0469643
Mean2.6458333
Median Absolute Deviation (MAD)0
Skewness2.0066574
Sum127
Variance24.871897
MonotonicityNot monotonic
2023-12-12T20:48:54.892383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 31
64.6%
1 3
 
6.2%
2 2
 
4.2%
5 2
 
4.2%
6 2
 
4.2%
4 1
 
2.1%
13 1
 
2.1%
19 1
 
2.1%
15 1
 
2.1%
14 1
 
2.1%
Other values (3) 3
 
6.2%
ValueCountFrequency (%)
0 31
64.6%
1 3
 
6.2%
2 2
 
4.2%
4 1
 
2.1%
5 2
 
4.2%
6 2
 
4.2%
7 1
 
2.1%
10 1
 
2.1%
13 1
 
2.1%
14 1
 
2.1%
ValueCountFrequency (%)
19 1
2.1%
16 1
2.1%
15 1
2.1%
14 1
2.1%
13 1
2.1%
10 1
2.1%
7 1
2.1%
6 2
4.2%
5 2
4.2%
4 1
2.1%

별정직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct27
Distinct (%)56.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.666667
Minimum0
Maximum43
Zeros4
Zeros (%)8.3%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-12T20:48:55.080537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q111.5
median22
Q329
95-th percentile33
Maximum43
Range43
Interquartile range (IQR)17.5

Descriptive statistics

Standard deviation11.299281
Coefficient of variation (CV)0.57453973
Kurtosis-0.84341814
Mean19.666667
Median Absolute Deviation (MAD)8
Skewness-0.3576522
Sum944
Variance127.67376
MonotonicityNot monotonic
2023-12-12T20:48:55.239142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 4
 
8.3%
29 4
 
8.3%
26 3
 
6.2%
27 3
 
6.2%
30 3
 
6.2%
21 3
 
6.2%
23 2
 
4.2%
12 2
 
4.2%
7 2
 
4.2%
33 2
 
4.2%
Other values (17) 20
41.7%
ValueCountFrequency (%)
0 4
8.3%
1 1
 
2.1%
3 2
4.2%
4 1
 
2.1%
7 2
4.2%
8 1
 
2.1%
10 1
 
2.1%
12 2
4.2%
13 1
 
2.1%
14 1
 
2.1%
ValueCountFrequency (%)
43 1
 
2.1%
37 1
 
2.1%
33 2
4.2%
31 2
4.2%
30 3
6.2%
29 4
8.3%
28 1
 
2.1%
27 3
6.2%
26 3
6.2%
24 1
 
2.1%

일반직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct42
Distinct (%)87.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean413.08333
Minimum0
Maximum10203
Zeros4
Zeros (%)8.3%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-12T20:48:55.406846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1107.25
median167
Q3268.25
95-th percentile687.1
Maximum10203
Range10203
Interquartile range (IQR)161

Descriptive statistics

Standard deviation1459.5536
Coefficient of variation (CV)3.5333153
Kurtosis45.737143
Mean413.08333
Median Absolute Deviation (MAD)93.5
Skewness6.6967488
Sum19828
Variance2130296.8
MonotonicityNot monotonic
2023-12-12T20:48:55.599169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
0 4
 
8.3%
143 2
 
4.2%
164 2
 
4.2%
210 2
 
4.2%
1 1
 
2.1%
230 1
 
2.1%
140 1
 
2.1%
117 1
 
2.1%
133 1
 
2.1%
147 1
 
2.1%
Other values (32) 32
66.7%
ValueCountFrequency (%)
0 4
8.3%
1 1
 
2.1%
2 1
 
2.1%
6 1
 
2.1%
7 1
 
2.1%
12 1
 
2.1%
22 1
 
2.1%
35 1
 
2.1%
78 1
 
2.1%
117 1
 
2.1%
ValueCountFrequency (%)
10203 1
2.1%
1282 1
2.1%
762 1
2.1%
548 1
2.1%
424 1
2.1%
381 1
2.1%
347 1
2.1%
324 1
2.1%
318 1
2.1%
303 1
2.1%

경찰
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct28
Distinct (%)58.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean77.75
Minimum0
Maximum2192
Zeros10
Zeros (%)20.8%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-12T20:48:55.753271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q18.5
median15.5
Q326.25
95-th percentile152.65
Maximum2192
Range2192
Interquartile range (IQR)17.75

Descriptive statistics

Standard deviation316.57714
Coefficient of variation (CV)4.0717317
Kurtosis44.900028
Mean77.75
Median Absolute Deviation (MAD)10.5
Skewness6.6145756
Sum3732
Variance100221.09
MonotonicityNot monotonic
2023-12-12T20:48:55.899132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0 10
20.8%
13 3
 
6.2%
10 3
 
6.2%
15 2
 
4.2%
18 2
 
4.2%
21 2
 
4.2%
26 2
 
4.2%
12 2
 
4.2%
16 2
 
4.2%
9 2
 
4.2%
Other values (18) 18
37.5%
ValueCountFrequency (%)
0 10
20.8%
2 1
 
2.1%
7 1
 
2.1%
9 2
 
4.2%
10 3
 
6.2%
12 2
 
4.2%
13 3
 
6.2%
15 2
 
4.2%
16 2
 
4.2%
17 1
 
2.1%
ValueCountFrequency (%)
2192 1
2.1%
310 1
2.1%
153 1
2.1%
152 1
2.1%
120 1
2.1%
111 1
2.1%
105 1
2.1%
64 1
2.1%
38 1
2.1%
37 1
2.1%

소방
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct22
Distinct (%)45.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25
Minimum0
Maximum716
Zeros11
Zeros (%)22.9%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-12T20:48:56.038721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12.5
median7.5
Q313.5
95-th percentile38.6
Maximum716
Range716
Interquartile range (IQR)11

Descriptive statistics

Standard deviation102.52493
Coefficient of variation (CV)4.1009973
Kurtosis46.684543
Mean25
Median Absolute Deviation (MAD)6
Skewness6.7912211
Sum1200
Variance10511.362
MonotonicityNot monotonic
2023-12-12T20:48:56.193510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 11
22.9%
6 6
12.5%
11 5
10.4%
8 3
 
6.2%
5 2
 
4.2%
15 2
 
4.2%
16 2
 
4.2%
4 2
 
4.2%
9 2
 
4.2%
36 1
 
2.1%
Other values (12) 12
25.0%
ValueCountFrequency (%)
0 11
22.9%
1 1
 
2.1%
3 1
 
2.1%
4 2
 
4.2%
5 2
 
4.2%
6 6
12.5%
7 1
 
2.1%
8 3
 
6.2%
9 2
 
4.2%
10 1
 
2.1%
ValueCountFrequency (%)
716 1
2.1%
55 1
2.1%
40 1
2.1%
36 1
2.1%
32 1
2.1%
30 1
2.1%
25 1
2.1%
19 1
2.1%
16 2
4.2%
15 2
4.2%

교육직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct37
Distinct (%)77.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean263.58333
Minimum0
Maximum3118
Zeros4
Zeros (%)8.3%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-12T20:48:56.348298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q144
median58.5
Q385.25
95-th percentile1044.85
Maximum3118
Range3118
Interquartile range (IQR)41.25

Descriptive statistics

Standard deviation536.32242
Coefficient of variation (CV)2.0347357
Kurtosis16.894128
Mean263.58333
Median Absolute Deviation (MAD)14.5
Skewness3.6895309
Sum12652
Variance287641.74
MonotonicityNot monotonic
2023-12-12T20:48:56.485308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
0 4
 
8.3%
61 3
 
6.2%
60 2
 
4.2%
65 2
 
4.2%
49 2
 
4.2%
50 2
 
4.2%
44 2
 
4.2%
67 2
 
4.2%
961 1
 
2.1%
3118 1
 
2.1%
Other values (27) 27
56.2%
ValueCountFrequency (%)
0 4
8.3%
2 1
 
2.1%
6 1
 
2.1%
10 1
 
2.1%
32 1
 
2.1%
38 1
 
2.1%
42 1
 
2.1%
43 1
 
2.1%
44 2
4.2%
45 1
 
2.1%
ValueCountFrequency (%)
3118 1
2.1%
1301 1
2.1%
1090 1
2.1%
961 1
2.1%
895 1
2.1%
884 1
2.1%
823 1
2.1%
684 1
2.1%
492 1
2.1%
427 1
2.1%

법관검사
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct15
Distinct (%)31.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.6666667
Minimum0
Maximum18
Zeros15
Zeros (%)31.2%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-12T20:48:56.649023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q37
95-th percentile14
Maximum18
Range18
Interquartile range (IQR)7

Descriptive statistics

Standard deviation4.8655687
Coefficient of variation (CV)1.0426219
Kurtosis0.24422277
Mean4.6666667
Median Absolute Deviation (MAD)4
Skewness0.97036756
Sum224
Variance23.673759
MonotonicityNot monotonic
2023-12-12T20:48:56.818609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 15
31.2%
6 7
14.6%
1 4
 
8.3%
4 4
 
8.3%
8 3
 
6.2%
2 2
 
4.2%
5 2
 
4.2%
14 2
 
4.2%
12 2
 
4.2%
7 2
 
4.2%
Other values (5) 5
 
10.4%
ValueCountFrequency (%)
0 15
31.2%
1 4
 
8.3%
2 2
 
4.2%
3 1
 
2.1%
4 4
 
8.3%
5 2
 
4.2%
6 7
14.6%
7 2
 
4.2%
8 3
 
6.2%
10 1
 
2.1%
ValueCountFrequency (%)
18 1
 
2.1%
16 1
 
2.1%
14 2
 
4.2%
12 2
 
4.2%
11 1
 
2.1%
10 1
 
2.1%
8 3
6.2%
7 2
 
4.2%
6 7
14.6%
5 2
 
4.2%

기능직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct14
Distinct (%)29.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.1041667
Minimum0
Maximum17
Zeros25
Zeros (%)52.1%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-12T20:48:56.970968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q36
95-th percentile13.95
Maximum17
Range17
Interquartile range (IQR)6

Descriptive statistics

Standard deviation4.8913279
Coefficient of variation (CV)1.5757298
Kurtosis1.2731835
Mean3.1041667
Median Absolute Deviation (MAD)0
Skewness1.5495186
Sum149
Variance23.925089
MonotonicityNot monotonic
2023-12-12T20:48:57.099354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 25
52.1%
1 7
 
14.6%
6 3
 
6.2%
11 2
 
4.2%
3 2
 
4.2%
7 1
 
2.1%
10 1
 
2.1%
9 1
 
2.1%
16 1
 
2.1%
12 1
 
2.1%
Other values (4) 4
 
8.3%
ValueCountFrequency (%)
0 25
52.1%
1 7
 
14.6%
2 1
 
2.1%
3 2
 
4.2%
6 3
 
6.2%
7 1
 
2.1%
8 1
 
2.1%
9 1
 
2.1%
10 1
 
2.1%
11 2
 
4.2%
ValueCountFrequency (%)
17 1
 
2.1%
16 1
 
2.1%
15 1
 
2.1%
12 1
 
2.1%
11 2
4.2%
10 1
 
2.1%
9 1
 
2.1%
8 1
 
2.1%
7 1
 
2.1%
6 3
6.2%

공안직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct25
Distinct (%)52.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.4375
Minimum0
Maximum364
Zeros8
Zeros (%)16.7%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-12T20:48:57.228393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15
median10.5
Q319
95-th percentile131.5
Maximum364
Range364
Interquartile range (IQR)14

Descriptive statistics

Standard deviation59.67426
Coefficient of variation (CV)2.0984355
Kurtosis21.691763
Mean28.4375
Median Absolute Deviation (MAD)8.5
Skewness4.2874138
Sum1365
Variance3561.0173
MonotonicityNot monotonic
2023-12-12T20:48:57.372873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0 8
16.7%
12 5
 
10.4%
10 4
 
8.3%
9 3
 
6.2%
1 3
 
6.2%
7 2
 
4.2%
19 2
 
4.2%
8 2
 
4.2%
16 2
 
4.2%
24 2
 
4.2%
Other values (15) 15
31.2%
ValueCountFrequency (%)
0 8
16.7%
1 3
 
6.2%
2 1
 
2.1%
6 1
 
2.1%
7 2
 
4.2%
8 2
 
4.2%
9 3
 
6.2%
10 4
8.3%
11 1
 
2.1%
12 5
10.4%
ValueCountFrequency (%)
364 1
2.1%
137 1
2.1%
135 1
2.1%
125 1
2.1%
86 1
2.1%
67 1
2.1%
52 1
2.1%
34 1
2.1%
24 2
4.2%
21 1
2.1%

군무원
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct32
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.875
Minimum0
Maximum635
Zeros6
Zeros (%)12.5%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-12T20:48:57.516047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q18.25
median18
Q331.5
95-th percentile66
Maximum635
Range635
Interquartile range (IQR)23.25

Descriptive statistics

Standard deviation90.606144
Coefficient of variation (CV)2.5980256
Kurtosis43.333752
Mean34.875
Median Absolute Deviation (MAD)12.5
Skewness6.437503
Sum1674
Variance8209.4734
MonotonicityNot monotonic
2023-12-12T20:48:57.675971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
0 6
 
12.5%
16 3
 
6.2%
24 2
 
4.2%
28 2
 
4.2%
10 2
 
4.2%
13 2
 
4.2%
18 2
 
4.2%
20 2
 
4.2%
1 2
 
4.2%
15 2
 
4.2%
Other values (22) 23
47.9%
ValueCountFrequency (%)
0 6
12.5%
1 2
 
4.2%
2 1
 
2.1%
3 1
 
2.1%
4 1
 
2.1%
6 1
 
2.1%
9 1
 
2.1%
10 2
 
4.2%
11 1
 
2.1%
13 2
 
4.2%
ValueCountFrequency (%)
635 1
2.1%
70 1
2.1%
66 2
4.2%
64 1
2.1%
53 1
2.1%
52 1
2.1%
48 1
2.1%
43 1
2.1%
41 1
2.1%
40 1
2.1%

연구직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct13
Distinct (%)27.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.2083333
Minimum0
Maximum203
Zeros11
Zeros (%)22.9%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-12T20:48:57.806270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median4
Q36
95-th percentile13.95
Maximum203
Range203
Interquartile range (IQR)5

Descriptive statistics

Standard deviation28.97024
Coefficient of variation (CV)3.5293694
Kurtosis46.21449
Mean8.2083333
Median Absolute Deviation (MAD)2.5
Skewness6.7415519
Sum394
Variance839.27482
MonotonicityNot monotonic
2023-12-12T20:48:57.960242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 11
22.9%
6 8
16.7%
5 7
14.6%
1 5
10.4%
4 4
 
8.3%
3 3
 
6.2%
7 3
 
6.2%
2 2
 
4.2%
8 1
 
2.1%
12 1
 
2.1%
Other values (3) 3
 
6.2%
ValueCountFrequency (%)
0 11
22.9%
1 5
10.4%
2 2
 
4.2%
3 3
 
6.2%
4 4
 
8.3%
5 7
14.6%
6 8
16.7%
7 3
 
6.2%
8 1
 
2.1%
12 1
 
2.1%
ValueCountFrequency (%)
203 1
 
2.1%
18 1
 
2.1%
15 1
 
2.1%
12 1
 
2.1%
8 1
 
2.1%
7 3
 
6.2%
6 8
16.7%
5 7
14.6%
4 4
8.3%
3 3
 
6.2%

지도직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct10
Distinct (%)20.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.4583333
Minimum0
Maximum137
Zeros20
Zeros (%)41.7%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-12T20:48:58.098524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile7.3
Maximum137
Range137
Interquartile range (IQR)2

Descriptive statistics

Standard deviation19.676056
Coefficient of variation (CV)4.4133209
Kurtosis46.577179
Mean4.4583333
Median Absolute Deviation (MAD)1
Skewness6.7805069
Sum214
Variance387.14716
MonotonicityNot monotonic
2023-12-12T20:48:58.200031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 20
41.7%
2 10
20.8%
1 9
18.8%
5 2
 
4.2%
6 2
 
4.2%
4 1
 
2.1%
3 1
 
2.1%
11 1
 
2.1%
8 1
 
2.1%
137 1
 
2.1%
ValueCountFrequency (%)
0 20
41.7%
1 9
18.8%
2 10
20.8%
3 1
 
2.1%
4 1
 
2.1%
5 2
 
4.2%
6 2
 
4.2%
8 1
 
2.1%
11 1
 
2.1%
137 1
 
2.1%
ValueCountFrequency (%)
137 1
 
2.1%
11 1
 
2.1%
8 1
 
2.1%
6 2
 
4.2%
5 2
 
4.2%
4 1
 
2.1%
3 1
 
2.1%
2 10
20.8%
1 9
18.8%
0 20
41.7%

계약직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct38
Distinct (%)79.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean70.375
Minimum0
Maximum126
Zeros4
Zeros (%)8.3%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-12T20:48:58.315079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q143.5
median85.5
Q3100
95-th percentile121.95
Maximum126
Range126
Interquartile range (IQR)56.5

Descriptive statistics

Standard deviation40.231577
Coefficient of variation (CV)0.57167427
Kurtosis-0.92456756
Mean70.375
Median Absolute Deviation (MAD)21.5
Skewness-0.6356678
Sum3378
Variance1618.5798
MonotonicityNot monotonic
2023-12-12T20:48:58.456617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
0 4
 
8.3%
94 3
 
6.2%
73 2
 
4.2%
108 2
 
4.2%
100 2
 
4.2%
92 2
 
4.2%
107 2
 
4.2%
51 1
 
2.1%
30 1
 
2.1%
84 1
 
2.1%
Other values (28) 28
58.3%
ValueCountFrequency (%)
0 4
8.3%
1 1
 
2.1%
3 1
 
2.1%
6 1
 
2.1%
7 1
 
2.1%
14 1
 
2.1%
22 1
 
2.1%
29 1
 
2.1%
30 1
 
2.1%
48 1
 
2.1%
ValueCountFrequency (%)
126 1
2.1%
125 1
2.1%
123 1
2.1%
120 1
2.1%
110 1
2.1%
108 2
4.2%
107 2
4.2%
105 1
2.1%
103 1
2.1%
100 2
4.2%

공중보건의
Real number (ℝ)

ZEROS 

Distinct12
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.979167
Minimum0
Maximum222
Zeros37
Zeros (%)77.1%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-12T20:48:58.599954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile191.75
Maximum222
Range222
Interquartile range (IQR)0

Descriptive statistics

Standard deviation62.920581
Coefficient of variation (CV)2.421963
Kurtosis3.9909456
Mean25.979167
Median Absolute Deviation (MAD)0
Skewness2.3404146
Sum1247
Variance3958.9996
MonotonicityNot monotonic
2023-12-12T20:48:59.046255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 37
77.1%
2 1
 
2.1%
15 1
 
2.1%
158 1
 
2.1%
222 1
 
2.1%
210 1
 
2.1%
157 1
 
2.1%
204 1
 
2.1%
169 1
 
2.1%
61 1
 
2.1%
Other values (2) 2
 
4.2%
ValueCountFrequency (%)
0 37
77.1%
2 1
 
2.1%
15 1
 
2.1%
16 1
 
2.1%
33 1
 
2.1%
61 1
 
2.1%
157 1
 
2.1%
158 1
 
2.1%
169 1
 
2.1%
204 1
 
2.1%
ValueCountFrequency (%)
222 1
2.1%
210 1
2.1%
204 1
2.1%
169 1
2.1%
158 1
2.1%
157 1
2.1%
61 1
2.1%
33 1
2.1%
16 1
2.1%
15 1
2.1%

기타
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct41
Distinct (%)85.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean163.85417
Minimum0
Maximum1172
Zeros3
Zeros (%)6.2%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-12T20:48:59.193834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.05
Q181
median170.5
Q3190.25
95-th percentile239.65
Maximum1172
Range1172
Interquartile range (IQR)109.25

Descriptive statistics

Standard deviation165.29393
Coefficient of variation (CV)1.0087869
Kurtosis30.414574
Mean163.85417
Median Absolute Deviation (MAD)21
Skewness4.8871594
Sum7865
Variance27322.085
MonotonicityNot monotonic
2023-12-12T20:48:59.350078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
0 3
 
6.2%
177 2
 
4.2%
191 2
 
4.2%
170 2
 
4.2%
171 2
 
4.2%
192 2
 
4.2%
193 1
 
2.1%
181 1
 
2.1%
187 1
 
2.1%
183 1
 
2.1%
Other values (31) 31
64.6%
ValueCountFrequency (%)
0 3
6.2%
3 1
 
2.1%
9 1
 
2.1%
16 1
 
2.1%
33 1
 
2.1%
46 1
 
2.1%
51 1
 
2.1%
64 1
 
2.1%
66 1
 
2.1%
69 1
 
2.1%
ValueCountFrequency (%)
1172 1
2.1%
264 1
2.1%
240 1
2.1%
239 1
2.1%
226 1
2.1%
203 1
2.1%
201 1
2.1%
193 1
2.1%
192 2
4.2%
191 2
4.2%

Interactions

2023-12-12T20:48:50.861305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:23.609863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:25.606421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:27.332166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:29.041969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:30.906501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:32.775800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:34.559443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:36.164602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:37.623234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:39.406329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:41.412899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:43.108324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:45.329304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:47.168042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:49.034516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:51.002870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:23.697742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:25.705410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:27.445733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:29.159895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:30.997741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:32.882929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:34.663169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:36.256402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:37.735422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:39.525158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:41.521382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:43.259679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:45.441433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:47.290317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:49.135443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:51.140565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:23.806767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:25.813739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:27.548272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:29.273091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:31.101704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:33.028649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:34.764935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:36.345487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:37.836979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:39.639590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:41.626571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:43.360659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:45.552133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:47.397855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:49.252005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:51.242566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:23.897892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:25.919282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:27.632083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:29.388134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:31.188116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:33.141084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:34.852583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:36.419377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:37.929696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:39.758430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:41.721274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:43.461477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:45.648889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:47.490405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:49.354064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:51.361490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:23.983031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:26.016992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:27.729166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:29.488076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:31.290870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:33.259907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:34.950399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:36.503057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:38.012787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:39.875723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:41.816524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:43.559516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:45.765729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:47.598524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:49.458758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:51.460256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:24.089035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:26.115310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:27.839821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:29.607025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:31.377961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:33.378269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:35.051262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:36.590085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:38.380191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:40.004413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:41.908145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:43.678151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:45.882917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:47.706437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:49.569225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:51.563657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:24.184870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:26.222289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:27.965430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:29.723393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:31.486821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:33.485206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:35.166472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:36.681393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:38.463457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:40.147763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:42.022593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:43.810836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:46.002146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:47.817893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:49.693109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:51.665961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:24.293611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:26.336609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:28.077714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:29.842640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:31.588331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:33.587863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:35.261140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:36.762819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:38.555252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:40.288670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:42.120762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:43.933039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:46.121501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:47.950805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:49.795168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:51.788826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:24.396617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:26.454216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:28.176664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:29.952902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:31.682841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:33.705555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:35.358880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:36.865617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:38.644108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:40.438585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:42.232670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:44.054402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:46.251855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:48.076354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:49.933478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:52.212273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:24.506291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:26.569172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:28.288491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:30.062859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:31.784315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:33.826072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:35.463804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:36.966429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:38.731215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:40.583443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:42.335499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:44.178976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:46.374111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:48.208286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:50.064085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:52.308428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:24.633517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:26.679395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:28.403440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:30.169408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:32.189497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:33.929121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:35.569209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:37.057514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:38.820702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:40.724251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:42.452575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:44.284634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:46.490880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:48.321109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:50.182195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:52.404922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:25.052037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:26.795675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:28.503222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:30.299185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:32.278757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:34.008649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:35.660079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:37.144860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:38.900910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:40.834708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:42.555721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:44.712336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:46.610882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:48.442746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:50.289185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:52.492958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:25.157508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:26.908090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:28.611880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:30.443854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:32.383138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:34.123563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:35.794320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:37.252529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:38.998872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:40.948896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:42.673253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:44.868397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:46.731284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:48.578031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:50.423024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:52.574735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:25.285348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:27.016331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:28.728416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:30.551018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:32.473173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:34.263824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:35.902472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:37.356279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:39.104026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:41.074364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:42.788150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:44.990379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:46.834580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:48.697116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:50.538670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:52.660349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:25.401904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:27.120525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:28.844646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:30.679880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:32.578142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:34.360642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:35.985841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:37.448819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:39.192071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:41.176148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:42.907579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:45.104389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:46.933829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:48.808023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:50.661406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:52.769416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:25.502108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:27.206019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:28.936271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:30.781213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:32.675540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:34.443691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:36.060054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:37.530771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:39.286570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:41.296677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:43.013183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:45.216907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:47.041414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:48.915766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:48:50.753919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T20:48:59.474570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분정무직별정직일반직경찰소방교육직법관검사기능직공안직군무원연구직지도직계약직공중보건의기타
구분1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
1.0001.0000.9310.0000.9660.9661.0000.8850.2270.0000.8790.9411.0001.0000.7160.0000.659
정무직1.0000.9311.0000.6370.9620.9620.4270.8990.0000.0000.9190.4860.4270.4270.6280.0000.000
별정직1.0000.0000.6371.0000.0000.0000.0000.4990.8230.6820.1420.0000.0000.0000.8890.0000.558
일반직1.0000.9660.9620.0001.0001.0001.0000.7070.3690.0000.7800.9371.0001.0000.5390.0000.660
경찰1.0000.9660.9620.0001.0001.0001.0000.7070.3690.0000.7800.9371.0001.0000.5390.0000.660
소방1.0001.0000.4270.0001.0001.0001.0000.5260.5220.0001.0001.0000.6760.6760.7730.0001.000
교육직1.0000.8850.8990.4990.7070.7070.5261.0000.0000.0000.6770.4450.5260.5260.7550.0000.286
법관검사1.0000.2270.0000.8230.3690.3690.5220.0001.0000.8270.6350.3280.5220.5220.5440.0000.493
기능직1.0000.0000.0000.6820.0000.0000.0000.0000.8271.0000.0000.0000.0000.0000.0000.0000.000
공안직1.0000.8790.9190.1420.7800.7801.0000.6770.6350.0001.0000.7111.0001.0000.7930.0000.620
군무원1.0000.9410.4860.0000.9370.9371.0000.4450.3280.0000.7111.0001.0001.0000.7170.0000.745
연구직1.0001.0000.4270.0001.0001.0000.6760.5260.5220.0001.0001.0001.0000.6760.7730.0001.000
지도직1.0001.0000.4270.0001.0001.0000.6760.5260.5220.0001.0001.0000.6761.0000.7730.0001.000
계약직1.0000.7160.6280.8890.5390.5390.7730.7550.5440.0000.7930.7170.7730.7731.0000.0000.808
공중보건의1.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.405
기타1.0000.6590.0000.5580.6600.6601.0000.2860.4930.0000.6200.7451.0001.0000.8080.4051.000
2023-12-12T20:48:59.663713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정무직별정직일반직경찰소방교육직법관검사기능직공안직군무원연구직지도직계약직공중보건의기타
1.0000.6440.2400.6020.5960.6220.8250.3350.0640.5950.4560.4790.4780.1910.1590.542
정무직0.6441.000-0.1260.2440.3640.2980.6390.4630.0910.3730.0750.1040.385-0.205-0.3870.006
별정직0.240-0.1261.0000.2900.4390.3400.1030.5010.5810.4430.1740.4910.1590.8490.1630.674
일반직0.6020.2440.2901.0000.8710.9000.4660.2040.2390.8740.8800.7600.7700.2300.2810.635
경찰0.5960.3640.4390.8711.0000.8830.4420.4760.4240.9200.7550.6790.7190.3170.1750.653
소방0.6220.2980.3400.9000.8831.0000.5150.3390.2700.8640.8130.8120.7130.2590.2680.652
교육직0.8250.6390.1030.4660.4420.5151.0000.3710.1110.4050.3500.3670.4260.032-0.0310.278
법관검사0.3350.4630.5010.2040.4760.3390.3711.0000.7390.4640.0050.2580.4250.458-0.4480.281
기능직0.0640.0910.5810.2390.4240.2700.1110.7391.0000.4200.0690.1980.3300.525-0.3740.278
공안직0.5950.3730.4430.8740.9200.8640.4050.4640.4201.0000.7600.7160.7270.3730.1310.637
군무원0.4560.0750.1740.8800.7550.8130.3500.0050.0690.7601.0000.6510.6630.1220.4440.575
연구직0.4790.1040.4910.7600.6790.8120.3670.2580.1980.7160.6511.0000.5940.4980.2060.606
지도직0.4780.3850.1590.7700.7190.7130.4260.4250.3300.7270.6630.5941.0000.166-0.0120.395
계약직0.191-0.2050.8490.2300.3170.2590.0320.4580.5250.3730.1220.4980.1661.0000.1590.631
공중보건의0.159-0.3870.1630.2810.1750.268-0.031-0.448-0.3740.1310.4440.206-0.0120.1591.0000.474
기타0.5420.0060.6740.6350.6530.6520.2780.2810.2780.6370.5750.6060.3950.6310.4741.000

Missing values

2023-12-12T20:48:52.927338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T20:48:53.241236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

구분정무직별정직일반직경찰소방교육직법관검사기능직공안직군무원연구직지도직계약직공중보건의기타
018세1001000000000000
119세7006000000100000
220세8007000000100000
321세170012000000200003
422세390122002001300109
523세7003352060014003016
624세1800478713200216106033
725세34403170954200733117066
826세510010234166680010532222285
927세66508265161167011866323015163
구분정무직별정직일반직경찰소방교육직법관검사기능직공안직군무원연구직지도직계약직공중보건의기타
3856세1499192142412030492818648126730159
3957세2104152054815232884831256665480192
4058세252414776215340109070135431811720172
4159세297110131282310558955113731158710138
4260세16567726102032192716823203646352031378701172
4361세111161420096140000060064
4462세3266519000311810000054069
4563세1401212000130160000029051
4664세84670001010000014046
4765세이상9721612000684601000840169