Overview

Dataset statistics

Number of variables16
Number of observations48
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.8 KiB
Average record size in memory145.8 B

Variable types

Text1
Numeric15

Dataset

Description공무원 직종별(정무직, 별정직, 일반직, 경찰, 소방, 교육 등) 연령별 신규가입자 현황에 대한 데이터입니다. 18세 이상부터 시작됩니다.
URLhttps://www.data.go.kr/data/15054022/fileData.do

Alerts

is highly overall correlated with 정무직 and 12 other fieldsHigh correlation
정무직 is highly overall correlated with and 8 other fieldsHigh correlation
별정직 is highly overall correlated with 계약직 and 1 other fieldsHigh correlation
일반직 is highly overall correlated with and 12 other fieldsHigh correlation
경찰직 is highly overall correlated with and 11 other fieldsHigh correlation
소방직 is highly overall correlated with and 11 other fieldsHigh correlation
교육 is highly overall correlated with and 12 other fieldsHigh correlation
법관검사 is highly overall correlated with and 11 other fieldsHigh correlation
공안직 is highly overall correlated with and 12 other fieldsHigh correlation
군무원 is highly overall correlated with and 12 other fieldsHigh correlation
연구직 is highly overall correlated with and 12 other fieldsHigh correlation
지도직 is highly overall correlated with and 12 other fieldsHigh correlation
계약직 is highly overall correlated with and 9 other fieldsHigh correlation
공중보건의 is highly overall correlated with and 10 other fieldsHigh correlation
기타 is highly overall correlated with and 12 other fieldsHigh correlation
구분 has unique valuesUnique
정무직 has 33 (68.8%) zerosZeros
별정직 has 4 (8.3%) zerosZeros
일반직 has 6 (12.5%) zerosZeros
경찰직 has 21 (43.8%) zerosZeros
소방직 has 18 (37.5%) zerosZeros
교육 has 6 (12.5%) zerosZeros
법관검사 has 23 (47.9%) zerosZeros
공안직 has 14 (29.2%) zerosZeros
군무원 has 8 (16.7%) zerosZeros
연구직 has 18 (37.5%) zerosZeros
지도직 has 20 (41.7%) zerosZeros
계약직 has 3 (6.2%) zerosZeros
공중보건의 has 37 (77.1%) zerosZeros
기타 has 2 (4.2%) zerosZeros

Reproduction

Analysis started2023-12-12 17:30:02.054029
Analysis finished2023-12-12 17:30:28.864284
Duration26.81 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
2023-12-13T02:30:29.049881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.0833333
Min length3

Characters and Unicode

Total characters148
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 row18세이상
2nd row19세
3rd row20세
4th row21세
5th row22세
ValueCountFrequency (%)
18세이상 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%
2023-12-13T02:30:29.444138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
48
32.4%
2 15
 
10.1%
3 15
 
10.1%
4 15
 
10.1%
5 15
 
10.1%
6 10
 
6.8%
1 7
 
4.7%
8 5
 
3.4%
9 5
 
3.4%
0 5
 
3.4%
Other values (3) 8
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 96
64.9%
Other Letter 52
35.1%

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
92.3%
2
 
3.8%
2
 
3.8%

Most occurring scripts

ValueCountFrequency (%)
Common 96
64.9%
Hangul 52
35.1%

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
92.3%
2
 
3.8%
2
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 96
64.9%
Hangul 52
35.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
48
92.3%
2
 
3.8%
2
 
3.8%
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 

Distinct46
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1480.0833
Minimum15
Maximum6779
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-13T02:30:29.623865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum15
5-th percentile93.35
Q1212.75
median644.5
Q31604.5
95-th percentile6131.6
Maximum6779
Range6764
Interquartile range (IQR)1391.75

Descriptive statistics

Standard deviation1922.4415
Coefficient of variation (CV)1.2988738
Kurtosis1.6452497
Mean1480.0833
Median Absolute Deviation (MAD)475
Skewness1.6780316
Sum71044
Variance3695781.4
MonotonicityNot monotonic
2023-12-13T02:30:29.777509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
161 2
 
4.2%
422 2
 
4.2%
15 1
 
2.1%
261 1
 
2.1%
656 1
 
2.1%
690 1
 
2.1%
633 1
 
2.1%
519 1
 
2.1%
481 1
 
2.1%
523 1
 
2.1%
Other values (36) 36
75.0%
ValueCountFrequency (%)
15 1
2.1%
64 1
2.1%
79 1
2.1%
120 1
2.1%
125 1
2.1%
148 1
2.1%
158 1
2.1%
161 2
4.2%
178 1
2.1%
187 1
2.1%
ValueCountFrequency (%)
6779 1
2.1%
6502 1
2.1%
6371 1
2.1%
5687 1
2.1%
5047 1
2.1%
4872 1
2.1%
4216 1
2.1%
3281 1
2.1%
3137 1
2.1%
2620 1
2.1%

정무직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct10
Distinct (%)20.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.6041667
Minimum0
Maximum12
Zeros33
Zeros (%)68.8%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-13T02:30:29.932629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32.25
95-th percentile7.65
Maximum12
Range12
Interquartile range (IQR)2.25

Descriptive statistics

Standard deviation2.9080928
Coefficient of variation (CV)1.8128371
Kurtosis2.7995434
Mean1.6041667
Median Absolute Deviation (MAD)0
Skewness1.846983
Sum77
Variance8.4570035
MonotonicityNot monotonic
2023-12-13T02:30:30.439504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 33
68.8%
5 3
 
6.2%
1 2
 
4.2%
3 2
 
4.2%
8 2
 
4.2%
7 2
 
4.2%
2 1
 
2.1%
4 1
 
2.1%
6 1
 
2.1%
12 1
 
2.1%
ValueCountFrequency (%)
0 33
68.8%
1 2
 
4.2%
2 1
 
2.1%
3 2
 
4.2%
4 1
 
2.1%
5 3
 
6.2%
6 1
 
2.1%
7 2
 
4.2%
8 2
 
4.2%
12 1
 
2.1%
ValueCountFrequency (%)
12 1
 
2.1%
8 2
 
4.2%
7 2
 
4.2%
6 1
 
2.1%
5 3
 
6.2%
4 1
 
2.1%
3 2
 
4.2%
2 1
 
2.1%
1 2
 
4.2%
0 33
68.8%

별정직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct24
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.625
Minimum0
Maximum38
Zeros4
Zeros (%)8.3%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-13T02:30:30.595228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q115.75
median21.5
Q326
95-th percentile32.65
Maximum38
Range38
Interquartile range (IQR)10.25

Descriptive statistics

Standard deviation9.6284706
Coefficient of variation (CV)0.49062271
Kurtosis-0.23659282
Mean19.625
Median Absolute Deviation (MAD)4.5
Skewness-0.65447531
Sum942
Variance92.707447
MonotonicityNot monotonic
2023-12-13T02:30:30.796129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0 4
 
8.3%
26 4
 
8.3%
20 4
 
8.3%
21 3
 
6.2%
24 3
 
6.2%
28 3
 
6.2%
25 3
 
6.2%
23 3
 
6.2%
19 3
 
6.2%
9 2
 
4.2%
Other values (14) 16
33.3%
ValueCountFrequency (%)
0 4
8.3%
4 1
 
2.1%
5 2
4.2%
8 1
 
2.1%
9 2
4.2%
11 1
 
2.1%
12 1
 
2.1%
17 1
 
2.1%
18 1
 
2.1%
19 3
6.2%
ValueCountFrequency (%)
38 1
 
2.1%
34 1
 
2.1%
33 1
 
2.1%
32 1
 
2.1%
30 1
 
2.1%
29 1
 
2.1%
28 3
6.2%
26 4
8.3%
25 3
6.2%
24 3
6.2%

일반직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct42
Distinct (%)87.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean601.45833
Minimum0
Maximum3161
Zeros6
Zeros (%)12.5%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-13T02:30:30.982963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q126
median184
Q3654.75
95-th percentile2836.4
Maximum3161
Range3161
Interquartile range (IQR)628.75

Descriptive statistics

Standard deviation894.21883
Coefficient of variation (CV)1.4867511
Kurtosis2.0766245
Mean601.45833
Median Absolute Deviation (MAD)184
Skewness1.7893518
Sum28870
Variance799627.32
MonotonicityNot monotonic
2023-12-13T02:30:31.162404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
0 6
 
12.5%
4 2
 
4.2%
15 1
 
2.1%
114 1
 
2.1%
291 1
 
2.1%
234 1
 
2.1%
195 1
 
2.1%
173 1
 
2.1%
133 1
 
2.1%
124 1
 
2.1%
Other values (32) 32
66.7%
ValueCountFrequency (%)
0 6
12.5%
4 2
 
4.2%
6 1
 
2.1%
11 1
 
2.1%
15 1
 
2.1%
17 1
 
2.1%
29 1
 
2.1%
40 1
 
2.1%
55 1
 
2.1%
65 1
 
2.1%
ValueCountFrequency (%)
3161 1
2.1%
2958 1
2.1%
2870 1
2.1%
2774 1
2.1%
2307 1
2.1%
1895 1
2.1%
1866 1
2.1%
1533 1
2.1%
1162 1
2.1%
910 1
2.1%

경찰직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct25
Distinct (%)52.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean117.33333
Minimum0
Maximum700
Zeros21
Zeros (%)43.8%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-13T02:30:31.319599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2.5
Q3115.5
95-th percentile598
Maximum700
Range700
Interquartile range (IQR)115.5

Descriptive statistics

Standard deviation208.75501
Coefficient of variation (CV)1.779162
Kurtosis1.8703453
Mean117.33333
Median Absolute Deviation (MAD)2.5
Skewness1.7878852
Sum5632
Variance43578.652
MonotonicityNot monotonic
2023-12-13T02:30:31.494175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0 21
43.8%
2 3
 
6.2%
598 2
 
4.2%
144 1
 
2.1%
5 1
 
2.1%
9 1
 
2.1%
3 1
 
2.1%
16 1
 
2.1%
20 1
 
2.1%
29 1
 
2.1%
Other values (15) 15
31.2%
ValueCountFrequency (%)
0 21
43.8%
2 3
 
6.2%
3 1
 
2.1%
5 1
 
2.1%
9 1
 
2.1%
11 1
 
2.1%
16 1
 
2.1%
20 1
 
2.1%
29 1
 
2.1%
32 1
 
2.1%
ValueCountFrequency (%)
700 1
2.1%
690 1
2.1%
598 2
4.2%
533 1
2.1%
493 1
2.1%
444 1
2.1%
320 1
2.1%
262 1
2.1%
219 1
2.1%
187 1
2.1%

소방직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct26
Distinct (%)54.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean81.75
Minimum0
Maximum516
Zeros18
Zeros (%)37.5%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-13T02:30:31.683753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q376.75
95-th percentile445.95
Maximum516
Range516
Interquartile range (IQR)76.75

Descriptive statistics

Standard deviation147.41323
Coefficient of variation (CV)1.8032199
Kurtosis2.7529589
Mean81.75
Median Absolute Deviation (MAD)5
Skewness1.9687709
Sum3924
Variance21730.66
MonotonicityNot monotonic
2023-12-13T02:30:31.828534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 18
37.5%
3 3
 
6.2%
8 2
 
4.2%
36 2
 
4.2%
1 2
 
4.2%
162 1
 
2.1%
4 1
 
2.1%
7 1
 
2.1%
6 1
 
2.1%
20 1
 
2.1%
Other values (16) 16
33.3%
ValueCountFrequency (%)
0 18
37.5%
1 2
 
4.2%
3 3
 
6.2%
4 1
 
2.1%
6 1
 
2.1%
7 1
 
2.1%
8 2
 
4.2%
20 1
 
2.1%
25 1
 
2.1%
35 1
 
2.1%
ValueCountFrequency (%)
516 1
2.1%
512 1
2.1%
468 1
2.1%
405 1
2.1%
391 1
2.1%
273 1
2.1%
271 1
2.1%
206 1
2.1%
167 1
2.1%
162 1
2.1%

교육
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct40
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean281.45833
Minimum0
Maximum1963
Zeros6
Zeros (%)12.5%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-13T02:30:32.009715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16.75
median79
Q3224.75
95-th percentile1648.55
Maximum1963
Range1963
Interquartile range (IQR)218

Descriptive statistics

Standard deviation501.46865
Coefficient of variation (CV)1.7816799
Kurtosis5.19845
Mean281.45833
Median Absolute Deviation (MAD)79
Skewness2.445567
Sum13510
Variance251470.81
MonotonicityNot monotonic
2023-12-13T02:30:32.188111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
0 6
 
12.5%
212 2
 
4.2%
5 2
 
4.2%
36 2
 
4.2%
27 1
 
2.1%
97 1
 
2.1%
70 1
 
2.1%
88 1
 
2.1%
53 1
 
2.1%
51 1
 
2.1%
Other values (30) 30
62.5%
ValueCountFrequency (%)
0 6
12.5%
1 1
 
2.1%
2 1
 
2.1%
3 1
 
2.1%
5 2
 
4.2%
6 1
 
2.1%
7 1
 
2.1%
11 1
 
2.1%
12 1
 
2.1%
13 1
 
2.1%
ValueCountFrequency (%)
1963 1
2.1%
1890 1
2.1%
1791 1
2.1%
1384 1
2.1%
1086 1
2.1%
767 1
2.1%
600 1
2.1%
469 1
2.1%
370 1
2.1%
308 1
2.1%

법관검사
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct15
Distinct (%)31.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.1458333
Minimum0
Maximum23
Zeros23
Zeros (%)47.9%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-13T02:30:32.345885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q37
95-th percentile16.65
Maximum23
Range23
Interquartile range (IQR)7

Descriptive statistics

Standard deviation6.2602752
Coefficient of variation (CV)1.5100161
Kurtosis1.0900959
Mean4.1458333
Median Absolute Deviation (MAD)1
Skewness1.4826933
Sum199
Variance39.191046
MonotonicityNot monotonic
2023-12-13T02:30:32.485090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 23
47.9%
1 6
 
12.5%
5 2
 
4.2%
11 2
 
4.2%
15 2
 
4.2%
7 2
 
4.2%
2 2
 
4.2%
3 2
 
4.2%
14 1
 
2.1%
16 1
 
2.1%
Other values (5) 5
 
10.4%
ValueCountFrequency (%)
0 23
47.9%
1 6
 
12.5%
2 2
 
4.2%
3 2
 
4.2%
5 2
 
4.2%
7 2
 
4.2%
8 1
 
2.1%
10 1
 
2.1%
11 2
 
4.2%
14 1
 
2.1%
ValueCountFrequency (%)
23 1
2.1%
19 1
2.1%
17 1
2.1%
16 1
2.1%
15 2
4.2%
14 1
2.1%
11 2
4.2%
10 1
2.1%
8 1
2.1%
7 2
4.2%

공안직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct27
Distinct (%)56.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.0625
Minimum0
Maximum187
Zeros14
Zeros (%)29.2%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-13T02:30:32.625644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5.5
Q341.5
95-th percentile162.85
Maximum187
Range187
Interquartile range (IQR)41.5

Descriptive statistics

Standard deviation53.408664
Coefficient of variation (CV)1.5232417
Kurtosis1.4892143
Mean35.0625
Median Absolute Deviation (MAD)5.5
Skewness1.6247345
Sum1683
Variance2852.4854
MonotonicityNot monotonic
2023-12-13T02:30:32.782511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 14
29.2%
1 4
 
8.3%
30 2
 
4.2%
4 2
 
4.2%
3 2
 
4.2%
166 2
 
4.2%
2 2
 
4.2%
7 1
 
2.1%
9 1
 
2.1%
16 1
 
2.1%
Other values (17) 17
35.4%
ValueCountFrequency (%)
0 14
29.2%
1 4
 
8.3%
2 2
 
4.2%
3 2
 
4.2%
4 2
 
4.2%
7 1
 
2.1%
9 1
 
2.1%
14 1
 
2.1%
15 1
 
2.1%
16 1
 
2.1%
ValueCountFrequency (%)
187 1
2.1%
166 2
4.2%
157 1
2.1%
139 1
2.1%
120 1
2.1%
93 1
2.1%
92 1
2.1%
88 1
2.1%
76 1
2.1%
65 1
2.1%

군무원
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct40
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean53.8125
Minimum0
Maximum213
Zeros8
Zeros (%)16.7%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-13T02:30:32.985562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14.75
median36
Q380.5
95-th percentile184.25
Maximum213
Range213
Interquartile range (IQR)75.75

Descriptive statistics

Standard deviation60.47706
Coefficient of variation (CV)1.1238478
Kurtosis0.64187118
Mean53.8125
Median Absolute Deviation (MAD)34
Skewness1.2335246
Sum2583
Variance3657.4747
MonotonicityNot monotonic
2023-12-13T02:30:33.167546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
0 8
 
16.7%
9 2
 
4.2%
18 1
 
2.1%
31 1
 
2.1%
54 1
 
2.1%
52 1
 
2.1%
46 1
 
2.1%
87 1
 
2.1%
82 1
 
2.1%
42 1
 
2.1%
Other values (30) 30
62.5%
ValueCountFrequency (%)
0 8
16.7%
1 1
 
2.1%
2 1
 
2.1%
3 1
 
2.1%
4 1
 
2.1%
5 1
 
2.1%
6 1
 
2.1%
9 2
 
4.2%
10 1
 
2.1%
11 1
 
2.1%
ValueCountFrequency (%)
213 1
2.1%
200 1
2.1%
186 1
2.1%
181 1
2.1%
173 1
2.1%
151 1
2.1%
123 1
2.1%
105 1
2.1%
102 1
2.1%
95 1
2.1%

연구직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct23
Distinct (%)47.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.770833
Minimum0
Maximum55
Zeros18
Zeros (%)37.5%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-13T02:30:33.310736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4.5
Q323
95-th percentile45.3
Maximum55
Range55
Interquartile range (IQR)23

Descriptive statistics

Standard deviation16.564817
Coefficient of variation (CV)1.2970819
Kurtosis0.082205208
Mean12.770833
Median Absolute Deviation (MAD)4.5
Skewness1.1618902
Sum613
Variance274.39317
MonotonicityNot monotonic
2023-12-13T02:30:33.438006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 18
37.5%
8 3
 
6.2%
3 3
 
6.2%
23 2
 
4.2%
19 2
 
4.2%
5 2
 
4.2%
37 2
 
4.2%
4 1
 
2.1%
1 1
 
2.1%
2 1
 
2.1%
Other values (13) 13
27.1%
ValueCountFrequency (%)
0 18
37.5%
1 1
 
2.1%
2 1
 
2.1%
3 3
 
6.2%
4 1
 
2.1%
5 2
 
4.2%
6 1
 
2.1%
7 1
 
2.1%
8 3
 
6.2%
10 1
 
2.1%
ValueCountFrequency (%)
55 1
2.1%
53 1
2.1%
46 1
2.1%
44 1
2.1%
38 1
2.1%
37 2
4.2%
35 1
2.1%
34 1
2.1%
31 1
2.1%
24 1
2.1%

지도직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct13
Distinct (%)27.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.75
Minimum0
Maximum43
Zeros20
Zeros (%)41.7%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-13T02:30:33.586167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32.25
95-th percentile28.85
Maximum43
Range43
Interquartile range (IQR)2.25

Descriptive statistics

Standard deviation9.9177468
Coefficient of variation (CV)2.0879467
Kurtosis6.6691673
Mean4.75
Median Absolute Deviation (MAD)1
Skewness2.6740958
Sum228
Variance98.361702
MonotonicityNot monotonic
2023-12-13T02:30:33.713923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 20
41.7%
1 11
22.9%
2 5
 
10.4%
15 2
 
4.2%
4 2
 
4.2%
5 1
 
2.1%
43 1
 
2.1%
32 1
 
2.1%
37 1
 
2.1%
23 1
 
2.1%
Other values (3) 3
 
6.2%
ValueCountFrequency (%)
0 20
41.7%
1 11
22.9%
2 5
 
10.4%
3 1
 
2.1%
4 2
 
4.2%
5 1
 
2.1%
8 1
 
2.1%
15 2
 
4.2%
18 1
 
2.1%
23 1
 
2.1%
ValueCountFrequency (%)
43 1
2.1%
37 1
2.1%
32 1
2.1%
23 1
2.1%
18 1
2.1%
15 2
4.2%
8 1
2.1%
5 1
2.1%
4 2
4.2%
3 1
2.1%

계약직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct40
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean73.916667
Minimum0
Maximum159
Zeros3
Zeros (%)6.2%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-13T02:30:33.859787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.7
Q139.5
median79
Q3107.25
95-th percentile135.3
Maximum159
Range159
Interquartile range (IQR)67.75

Descriptive statistics

Standard deviation43.835201
Coefficient of variation (CV)0.59303541
Kurtosis-0.99973989
Mean73.916667
Median Absolute Deviation (MAD)32.5
Skewness-0.18644825
Sum3548
Variance1921.5248
MonotonicityNot monotonic
2023-12-13T02:30:34.015344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
0 3
 
6.2%
96 2
 
4.2%
120 2
 
4.2%
48 2
 
4.2%
87 2
 
4.2%
23 2
 
4.2%
16 2
 
4.2%
12 1
 
2.1%
77 1
 
2.1%
104 1
 
2.1%
Other values (30) 30
62.5%
ValueCountFrequency (%)
0 3
6.2%
2 1
 
2.1%
5 1
 
2.1%
12 1
 
2.1%
16 2
4.2%
23 2
4.2%
37 1
 
2.1%
38 1
 
2.1%
40 1
 
2.1%
48 2
4.2%
ValueCountFrequency (%)
159 1
2.1%
138 1
2.1%
136 1
2.1%
134 1
2.1%
132 1
2.1%
127 1
2.1%
120 2
4.2%
118 1
2.1%
116 1
2.1%
112 1
2.1%

공중보건의
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct12
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.854167
Minimum0
Maximum238
Zeros37
Zeros (%)77.1%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-13T02:30:34.150115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile136.1
Maximum238
Range238
Interquartile range (IQR)0

Descriptive statistics

Standard deviation54.361669
Coefficient of variation (CV)2.4874739
Kurtosis7.042108
Mean21.854167
Median Absolute Deviation (MAD)0
Skewness2.7394589
Sum1049
Variance2955.191
MonotonicityNot monotonic
2023-12-13T02:30:34.263941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 37
77.1%
16 1
 
2.1%
141 1
 
2.1%
238 1
 
2.1%
202 1
 
2.1%
125 1
 
2.1%
127 1
 
2.1%
86 1
 
2.1%
60 1
 
2.1%
34 1
 
2.1%
Other values (2) 2
 
4.2%
ValueCountFrequency (%)
0 37
77.1%
2 1
 
2.1%
16 1
 
2.1%
18 1
 
2.1%
34 1
 
2.1%
60 1
 
2.1%
86 1
 
2.1%
125 1
 
2.1%
127 1
 
2.1%
141 1
 
2.1%
ValueCountFrequency (%)
238 1
2.1%
202 1
2.1%
141 1
2.1%
127 1
2.1%
125 1
2.1%
86 1
2.1%
60 1
2.1%
34 1
2.1%
18 1
2.1%
16 1
2.1%

기타
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct44
Distinct (%)91.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean170.54167
Minimum0
Maximum380
Zeros2
Zeros (%)4.2%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-13T02:30:34.409999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile6.9
Q185
median185.5
Q3228.25
95-th percentile359.95
Maximum380
Range380
Interquartile range (IQR)143.25

Descriptive statistics

Standard deviation102.13778
Coefficient of variation (CV)0.5989022
Kurtosis-0.49297399
Mean170.54167
Median Absolute Deviation (MAD)65.5
Skewness0.20614016
Sum8186
Variance10432.126
MonotonicityNot monotonic
2023-12-13T02:30:34.608253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
0 2
 
4.2%
209 2
 
4.2%
233 2
 
4.2%
345 2
 
4.2%
123 1
 
2.1%
192 1
 
2.1%
217 1
 
2.1%
180 1
 
2.1%
202 1
 
2.1%
188 1
 
2.1%
Other values (34) 34
70.8%
ValueCountFrequency (%)
0 2
4.2%
2 1
2.1%
16 1
2.1%
37 1
2.1%
44 1
2.1%
50 1
2.1%
59 1
2.1%
67 1
2.1%
68 1
2.1%
75 1
2.1%
ValueCountFrequency (%)
380 1
2.1%
379 1
2.1%
368 1
2.1%
345 2
4.2%
292 1
2.1%
278 1
2.1%
239 1
2.1%
235 1
2.1%
233 2
4.2%
232 1
2.1%

Interactions

2023-12-13T02:30:26.745380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:02.849262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:04.673352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:06.237155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:07.805931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:09.788768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:11.471014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:12.972975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:14.780635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:16.820869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:18.552509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:20.239524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:21.671537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:23.128188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:25.178026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:26.879902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:02.967977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:04.780312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:06.354509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:07.903800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:09.928040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:11.574283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:13.098102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:14.911331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:16.919887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:18.679836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:20.334381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:21.775958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:23.235248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:25.296626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:26.998874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:03.092205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:04.872565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:06.461694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:08.015582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:10.047800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:11.663767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:13.201412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:15.026156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:17.034217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:18.802956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:20.430642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:21.888477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:23.343882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:25.395768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:27.126272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:03.198803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:04.975125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:06.550703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:08.112761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:10.173320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:11.766016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:13.316664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:15.166475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:17.149471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:18.913203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:20.524177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:22.036018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:23.733054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:25.497965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:27.247582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:03.320661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:05.089996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:06.634400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:08.223309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:10.267222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:11.861467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:13.427520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:15.294660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:17.258166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:19.015948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:20.612245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:22.141997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:23.830601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:25.606191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:27.376312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:03.457015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:05.212380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:06.732596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:08.337240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:10.392953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:11.957825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:13.541731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:15.424837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:17.358182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:19.131801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:20.713450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:22.234588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:23.966976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:25.727904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:27.507454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:03.576030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:05.338421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:06.840801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:08.435933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:10.495273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:12.052279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:13.657763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:15.530369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:17.483543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:19.240857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:20.793873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:22.348748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:24.100525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:25.837630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:27.640507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:03.704889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:05.450459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:06.938394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:08.554402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:10.603783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:12.182859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:13.751578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:15.656910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:17.598291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:19.383081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:20.889910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:22.458416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:24.229905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:25.950397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:27.759861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:03.822799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:05.537050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:07.023928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:08.668712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:10.707931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:12.277958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:13.830937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:15.751092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:17.709350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:19.493160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:20.985650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:22.533372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:24.337672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:26.034055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:27.881045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:03.942984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:05.627584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:07.111987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:08.817440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:10.842988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:12.396846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:13.932971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:15.867573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:17.831570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:19.620480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:21.107435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:22.615227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:24.471838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:26.132079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:27.978520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:04.055176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:05.734330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:07.195275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:08.957111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:10.935221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:12.492346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:14.062250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:15.949724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:17.961199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:19.700303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:21.202968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:22.687977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:24.580534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:26.224078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:28.092314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:04.172616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:05.842407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:07.288193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:09.064105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:11.026505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:12.585991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:14.167306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:16.046172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:18.068490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:19.790497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:21.282719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:22.766253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:24.693120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:26.327972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:28.199221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:04.288020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:05.931725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:07.411309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:09.171580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:11.138636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:12.667584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:14.281888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:16.140966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:18.181933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:19.890222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:21.385902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:22.839262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:24.805995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:26.454784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:28.331476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:04.419251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:06.045241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:07.539871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:09.564440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:11.241487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:12.763775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:14.455698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:16.612129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:18.309433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:20.013770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:21.487718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:22.956611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:24.937040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:26.571876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:28.422687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:04.536971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:06.146291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:07.661816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:09.642581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:11.338016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:12.862132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:14.608752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:16.718303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:18.422567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:20.113216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:21.570938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:23.043104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:25.034066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:26.647233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T02:30:34.762314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분정무직별정직일반직경찰직소방직교육법관검사공안직군무원연구직지도직계약직공중보건의기타
구분1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
1.0001.0000.0000.0000.9790.9690.8660.8780.8910.8910.9610.9150.9360.6040.8470.799
정무직1.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.4470.0000.522
별정직1.0000.0000.0001.0000.0000.5340.0000.0000.0000.0000.5310.0000.0000.8010.0000.670
일반직1.0000.9790.0000.0001.0000.9790.8290.8290.9170.8410.9290.9430.8780.7170.8980.753
경찰직1.0000.9690.0000.5340.9791.0000.8860.8630.8800.8390.9540.9230.8840.5210.8910.819
소방직1.0000.8660.0000.0000.8290.8861.0000.9470.8080.9230.8000.7800.8230.2640.9360.770
교육1.0000.8780.0000.0000.8290.8630.9471.0000.6750.9130.8730.8020.9360.5730.9820.535
법관검사1.0000.8910.0000.0000.9170.8800.8080.6751.0000.8080.7530.8840.4860.4090.7620.485
공안직1.0000.8910.0000.0000.8410.8390.9230.9130.8081.0000.8820.7620.9700.4760.8840.670
군무원1.0000.9610.0000.5310.9290.9540.8000.8730.7530.8821.0000.8610.8500.5160.8660.800
연구직1.0000.9150.0000.0000.9430.9230.7800.8020.8840.7620.8611.0000.8190.7000.7950.656
지도직1.0000.9360.0000.0000.8780.8840.8230.9360.4860.9700.8500.8191.0000.4160.9280.597
계약직1.0000.6040.4470.8010.7170.5210.2640.5730.4090.4760.5160.7000.4161.0000.4050.696
공중보건의1.0000.8470.0000.0000.8980.8910.9360.9820.7620.8840.8660.7950.9280.4051.0000.607
기타1.0000.7990.5220.6700.7530.8190.7700.5350.4850.6700.8000.6560.5970.6960.6071.000
2023-12-13T02:30:34.973365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정무직별정직일반직경찰직소방직교육법관검사공안직군무원연구직지도직계약직공중보건의기타
1.000-0.7160.3570.9650.9140.9130.9660.6330.9530.9640.8860.8620.6270.7250.795
정무직-0.7161.000-0.234-0.792-0.671-0.733-0.654-0.341-0.751-0.732-0.654-0.612-0.438-0.355-0.480
별정직0.357-0.2341.0000.2270.1220.1290.3550.4560.2720.3770.4900.2950.7290.0660.609
일반직0.965-0.7920.2271.0000.9270.9520.8960.6020.9400.9350.8440.8340.5260.7330.696
경찰직0.914-0.6710.1220.9271.0000.9750.9000.6090.9560.8910.8340.8170.4850.7620.651
소방직0.913-0.7330.1290.9520.9751.0000.8640.6080.9500.8980.8270.7940.4930.7540.645
교육0.966-0.6540.3550.8960.9000.8641.0000.5960.9340.9290.8450.8570.6030.6980.761
법관검사0.633-0.3410.4560.6020.6090.6080.5961.0000.6420.6180.7510.5810.7980.5210.701
공안직0.953-0.7510.2720.9400.9560.9500.9340.6421.0000.9360.8980.8450.6140.7450.763
군무원0.964-0.7320.3770.9350.8910.8980.9290.6180.9361.0000.8750.8220.6470.7310.794
연구직0.886-0.6540.4900.8440.8340.8270.8450.7510.8980.8751.0000.7970.7860.6990.864
지도직0.862-0.6120.2950.8340.8170.7940.8570.5810.8450.8220.7971.0000.5350.7490.755
계약직0.627-0.4380.7290.5260.4850.4930.6030.7980.6140.6470.7860.5351.0000.3800.824
공중보건의0.725-0.3550.0660.7330.7620.7540.6980.5210.7450.7310.6990.7490.3801.0000.655
기타0.795-0.4800.6090.6960.6510.6450.7610.7010.7630.7940.8640.7550.8240.6551.000

Missing values

2023-12-13T02:30:28.590303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:30:28.789873image/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

구분정무직별정직일반직경찰직소방직교육법관검사공안직군무원연구직지도직계약직공중보건의기타
018세이상15001500000000000
119세49800485030001000000
220세1780015928002500002
321세2130012811366049012016
422세69404292623521201433005037
523세313705855219761791036643516067
624세4872012186644416719630881238152316147
725세6502019287059827318900139181194351141278
826세6779020316169040513845187213383261238345
927세63710232958700468108611166200443796202380
구분정무직별정직일반직경찰직소방직교육법관검사공안직군무원연구직지도직계약직공중보건의기타
3856세2124201100121110069093
3957세18771960051030059087
4058세16171940051020048075
4159세12551740020000038059
4260세14852000070000048068
4361세16189000300000370104
4462세12061100010000023079
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