Overview

Dataset statistics

Number of variables18
Number of observations34
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.4 KiB
Average record size in memory163.8 B

Variable types

Text1
Categorical2
Numeric15

Dataset

Description직종별(정무직, 별정직, 일반직, 소방, 경찰 등), 지역별(서울 부산 등 광역시, 도) 퇴직연금수급자 현황에 대한 데이터입니다.
Author공공데이터포털
URLhttps://www.data.go.kr/data/15054110/fileData.do

Alerts

is highly overall correlated with 정무직 and 15 other fieldsHigh correlation
정무직 is highly overall correlated with and 14 other fieldsHigh correlation
별정직 is highly overall correlated with and 15 other fieldsHigh correlation
일반직 is highly overall correlated with and 15 other fieldsHigh correlation
경찰 is highly overall correlated with and 15 other fieldsHigh correlation
소방 is highly overall correlated with and 15 other fieldsHigh correlation
교육직 is highly overall correlated with and 14 other fieldsHigh correlation
법관검사 is highly overall correlated with and 14 other fieldsHigh correlation
기능직 is highly overall correlated with and 15 other fieldsHigh correlation
공안직 is highly overall correlated with and 15 other fieldsHigh correlation
군무원 is highly overall correlated with and 15 other fieldsHigh correlation
연구직 is highly overall correlated with and 14 other fieldsHigh correlation
지도직 is highly overall correlated with and 15 other fieldsHigh correlation
계약직 is highly overall correlated with and 14 other fieldsHigh correlation
기타 is highly overall correlated with and 15 other fieldsHigh correlation
남녀구분 is highly overall correlated with and 10 other fieldsHigh correlation
고용직 is highly overall correlated with and 13 other fieldsHigh correlation
has unique valuesUnique
일반직 has unique valuesUnique
교육직 has unique valuesUnique
기능직 has unique valuesUnique
공안직 has unique valuesUnique
군무원 has unique valuesUnique
정무직 has 14 (41.2%) zerosZeros
법관검사 has 10 (29.4%) zerosZeros
연구직 has 1 (2.9%) zerosZeros

Reproduction

Analysis started2024-04-20 23:18:24.424926
Analysis finished2024-04-20 23:19:13.463593
Duration49.04 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지역
Text

Distinct17
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size400.0 B
2024-04-21T08:19:13.971236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters68
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울
2nd row서울
3rd row부산
4th row부산
5th row대구
ValueCountFrequency (%)
서울 2
 
5.9%
강원 2
 
5.9%
전남 2
 
5.9%
전북 2
 
5.9%
경남 2
 
5.9%
경북 2
 
5.9%
충남 2
 
5.9%
충북 2
 
5.9%
경기 2
 
5.9%
부산 2
 
5.9%
Other values (7) 14
41.2%
2024-04-21T08:19:14.818522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6
 
8.8%
6
 
8.8%
6
 
8.8%
6
 
8.8%
4
 
5.9%
4
 
5.9%
4
 
5.9%
4
 
5.9%
4
 
5.9%
2
 
2.9%
Other values (11) 22
32.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 68
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6
 
8.8%
6
 
8.8%
6
 
8.8%
6
 
8.8%
4
 
5.9%
4
 
5.9%
4
 
5.9%
4
 
5.9%
4
 
5.9%
2
 
2.9%
Other values (11) 22
32.4%

Most occurring scripts

ValueCountFrequency (%)
Hangul 68
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6
 
8.8%
6
 
8.8%
6
 
8.8%
6
 
8.8%
4
 
5.9%
4
 
5.9%
4
 
5.9%
4
 
5.9%
4
 
5.9%
2
 
2.9%
Other values (11) 22
32.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 68
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
6
 
8.8%
6
 
8.8%
6
 
8.8%
6
 
8.8%
4
 
5.9%
4
 
5.9%
4
 
5.9%
4
 
5.9%
4
 
5.9%
2
 
2.9%
Other values (11) 22
32.4%

남녀구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size400.0 B
17 
17 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
17
50.0%
17
50.0%

Length

2024-04-21T08:19:15.037755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T08:19:15.206881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
17
50.0%
17
50.0%


Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16059.118
Minimum1089
Maximum79520
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size434.0 B
2024-04-21T08:19:15.395316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1089
5-th percentile1869.1
Q14222.75
median8794.5
Q323272.75
95-th percentile42392.05
Maximum79520
Range78431
Interquartile range (IQR)19050

Descriptive statistics

Standard deviation17338.42
Coefficient of variation (CV)1.0796621
Kurtosis6.1282108
Mean16059.118
Median Absolute Deviation (MAD)6927.5
Skewness2.2695083
Sum546010
Variance3.0062081 × 108
MonotonicityNot monotonic
2024-04-21T08:19:15.628965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
67003 1
 
2.9%
29140 1
 
2.9%
19086 1
 
2.9%
4017 1
 
2.9%
17898 1
 
2.9%
3990 1
 
2.9%
27552 1
 
2.9%
5272 1
 
2.9%
7320 1
 
2.9%
24447 1
 
2.9%
Other values (24) 24
70.6%
ValueCountFrequency (%)
1089 1
2.9%
1860 1
2.9%
1874 1
2.9%
3178 1
2.9%
3460 1
2.9%
3990 1
2.9%
4017 1
2.9%
4165 1
2.9%
4206 1
2.9%
4273 1
2.9%
ValueCountFrequency (%)
79520 1
2.9%
67003 1
2.9%
29140 1
2.9%
28704 1
2.9%
27552 1
2.9%
26859 1
2.9%
24983 1
2.9%
24447 1
2.9%
23531 1
2.9%
22498 1
2.9%

정무직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct13
Distinct (%)38.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.411765
Minimum0
Maximum821
Zeros14
Zeros (%)41.2%
Negative0
Negative (%)0.0%
Memory size434.0 B
2024-04-21T08:19:15.936320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3.5
Q310
95-th percentile131.2
Maximum821
Range821
Interquartile range (IQR)10

Descriptive statistics

Standard deviation150.31686
Coefficient of variation (CV)3.9133027
Kurtosis24.062676
Mean38.411765
Median Absolute Deviation (MAD)3.5
Skewness4.8093402
Sum1306
Variance22595.159
MonotonicityNot monotonic
2024-04-21T08:19:16.145544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 14
41.2%
10 3
 
8.8%
6 3
 
8.8%
11 2
 
5.9%
7 2
 
5.9%
1 2
 
5.9%
4 2
 
5.9%
821 1
 
2.9%
14 1
 
2.9%
12 1
 
2.9%
Other values (3) 3
 
8.8%
ValueCountFrequency (%)
0 14
41.2%
1 2
 
5.9%
3 1
 
2.9%
4 2
 
5.9%
6 3
 
8.8%
7 2
 
5.9%
10 3
 
8.8%
11 2
 
5.9%
12 1
 
2.9%
14 1
 
2.9%
ValueCountFrequency (%)
821 1
 
2.9%
347 1
 
2.9%
15 1
 
2.9%
14 1
 
2.9%
12 1
 
2.9%
11 2
5.9%
10 3
8.8%
7 2
5.9%
6 3
8.8%
4 2
5.9%

별정직
Real number (ℝ)

HIGH CORRELATION 

Distinct32
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean268.20588
Minimum3
Maximum1606
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size434.0 B
2024-04-21T08:19:16.368064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile10.85
Q129.5
median64
Q3262.5
95-th percentile1247.45
Maximum1606
Range1603
Interquartile range (IQR)233

Descriptive statistics

Standard deviation416.23724
Coefficient of variation (CV)1.5519318
Kurtosis4.6071649
Mean268.20588
Median Absolute Deviation (MAD)60
Skewness2.2665923
Sum9119
Variance173253.44
MonotonicityNot monotonic
2024-04-21T08:19:16.622757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
23 2
 
5.9%
27 2
 
5.9%
1538 1
 
2.9%
31 1
 
2.9%
37 1
 
2.9%
228 1
 
2.9%
34 1
 
2.9%
246 1
 
2.9%
412 1
 
2.9%
1091 1
 
2.9%
Other values (22) 22
64.7%
ValueCountFrequency (%)
3 1
2.9%
5 1
2.9%
14 1
2.9%
23 2
5.9%
24 1
2.9%
27 2
5.9%
29 1
2.9%
31 1
2.9%
33 1
2.9%
34 1
2.9%
ValueCountFrequency (%)
1606 1
2.9%
1538 1
2.9%
1091 1
2.9%
933 1
2.9%
555 1
2.9%
447 1
2.9%
412 1
2.9%
311 1
2.9%
268 1
2.9%
246 1
2.9%

일반직
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5708.1765
Minimum366
Maximum32636
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size434.0 B
2024-04-21T08:19:16.850251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum366
5-th percentile475.2
Q11297.75
median2309.5
Q37843
95-th percentile16651.8
Maximum32636
Range32270
Interquartile range (IQR)6545.25

Descriptive statistics

Standard deviation7040.2288
Coefficient of variation (CV)1.2333586
Kurtosis7.5606318
Mean5708.1765
Median Absolute Deviation (MAD)1924
Skewness2.567937
Sum194078
Variance49564821
MonotonicityNot monotonic
2024-04-21T08:19:17.070156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
26810 1
 
2.9%
10790 1
 
2.9%
7174 1
 
2.9%
1074 1
 
2.9%
6923 1
 
2.9%
1286 1
 
2.9%
11182 1
 
2.9%
1718 1
 
2.9%
1953 1
 
2.9%
9409 1
 
2.9%
Other values (24) 24
70.6%
ValueCountFrequency (%)
366 1
2.9%
405 1
2.9%
513 1
2.9%
1014 1
2.9%
1074 1
2.9%
1096 1
2.9%
1152 1
2.9%
1264 1
2.9%
1286 1
2.9%
1333 1
2.9%
ValueCountFrequency (%)
32636 1
2.9%
26810 1
2.9%
11182 1
2.9%
10790 1
2.9%
9906 1
2.9%
9409 1
2.9%
8899 1
2.9%
8104 1
2.9%
8066 1
2.9%
7174 1
2.9%

경찰
Real number (ℝ)

HIGH CORRELATION 

Distinct31
Distinct (%)91.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1390.0588
Minimum4
Maximum9169
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size434.0 B
2024-04-21T08:19:17.293278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile7.6
Q115.75
median162.5
Q32184.75
95-th percentile5408.6
Maximum9169
Range9165
Interquartile range (IQR)2169

Descriptive statistics

Standard deviation2199.2505
Coefficient of variation (CV)1.5821276
Kurtosis6.4218804
Mean1390.0588
Median Absolute Deviation (MAD)158
Skewness2.4258454
Sum47262
Variance4836702.5
MonotonicityNot monotonic
2024-04-21T08:19:17.534829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
9 3
 
8.8%
13 2
 
5.9%
9169 1
 
2.9%
15 1
 
2.9%
18 1
 
2.9%
1748 1
 
2.9%
1578 1
 
2.9%
2543 1
 
2.9%
3058 1
 
2.9%
102 1
 
2.9%
Other values (21) 21
61.8%
ValueCountFrequency (%)
4 1
 
2.9%
5 1
 
2.9%
9 3
8.8%
11 1
 
2.9%
13 2
5.9%
15 1
 
2.9%
18 1
 
2.9%
19 1
 
2.9%
20 1
 
2.9%
24 1
 
2.9%
ValueCountFrequency (%)
9169 1
2.9%
8448 1
2.9%
3772 1
2.9%
3058 1
2.9%
2697 1
2.9%
2543 1
2.9%
2396 1
2.9%
2356 1
2.9%
2242 1
2.9%
2013 1
2.9%

소방
Real number (ℝ)

HIGH CORRELATION 

Distinct27
Distinct (%)79.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean259.44118
Minimum1
Maximum2074
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size434.0 B
2024-04-21T08:19:17.760032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median36
Q3398.25
95-th percentile857.75
Maximum2074
Range2073
Interquartile range (IQR)394.25

Descriptive statistics

Standard deviation420.6766
Coefficient of variation (CV)1.621472
Kurtosis10.383133
Mean259.44118
Median Absolute Deviation (MAD)35
Skewness2.893268
Sum8821
Variance176968.8
MonotonicityNot monotonic
2024-04-21T08:19:17.994512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
4 5
 
14.7%
1 3
 
8.8%
2 2
 
5.9%
1212 1
 
2.9%
320 1
 
2.9%
187 1
 
2.9%
327 1
 
2.9%
3 1
 
2.9%
387 1
 
2.9%
7 1
 
2.9%
Other values (17) 17
50.0%
ValueCountFrequency (%)
1 3
8.8%
2 2
 
5.9%
3 1
 
2.9%
4 5
14.7%
6 1
 
2.9%
7 1
 
2.9%
9 1
 
2.9%
12 1
 
2.9%
20 1
 
2.9%
22 1
 
2.9%
ValueCountFrequency (%)
2074 1
2.9%
1212 1
2.9%
667 1
2.9%
546 1
2.9%
540 1
2.9%
491 1
2.9%
436 1
2.9%
406 1
2.9%
402 1
2.9%
387 1
2.9%

교육직
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4997.2353
Minimum557
Maximum20224
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size434.0 B
2024-04-21T08:19:18.236531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum557
5-th percentile937.05
Q12425
median4212.5
Q35704.25
95-th percentile14428.3
Maximum20224
Range19667
Interquartile range (IQR)3279.25

Descriptive statistics

Standard deviation4376.2043
Coefficient of variation (CV)0.87572507
Kurtosis4.7178126
Mean4997.2353
Median Absolute Deviation (MAD)1779.5
Skewness2.1062713
Sum169906
Variance19151164
MonotonicityNot monotonic
2024-04-21T08:19:18.497687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
11044 1
 
2.9%
6416 1
 
2.9%
4481 1
 
2.9%
2449 1
 
2.9%
4378 1
 
2.9%
2266 1
 
2.9%
4981 1
 
2.9%
3002 1
 
2.9%
4618 1
 
2.9%
5722 1
 
2.9%
Other values (24) 24
70.6%
ValueCountFrequency (%)
557 1
2.9%
666 1
2.9%
1083 1
2.9%
1183 1
2.9%
1413 1
2.9%
1851 1
2.9%
2050 1
2.9%
2266 1
2.9%
2417 1
2.9%
2449 1
2.9%
ValueCountFrequency (%)
20224 1
2.9%
16819 1
2.9%
13141 1
2.9%
11044 1
2.9%
7572 1
2.9%
6416 1
2.9%
6389 1
2.9%
6043 1
2.9%
5722 1
2.9%
5651 1
2.9%

법관검사
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct17
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean61.235294
Minimum0
Maximum1482
Zeros10
Zeros (%)29.4%
Negative0
Negative (%)0.0%
Memory size434.0 B
2024-04-21T08:19:18.931829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q310.75
95-th percentile140.25
Maximum1482
Range1482
Interquartile range (IQR)10.75

Descriptive statistics

Standard deviation255.19441
Coefficient of variation (CV)4.1674399
Kurtosis31.645303
Mean61.235294
Median Absolute Deviation (MAD)2
Skewness5.5595145
Sum2082
Variance65124.185
MonotonicityNot monotonic
2024-04-21T08:19:19.131350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 10
29.4%
1 5
14.7%
2 3
 
8.8%
9 2
 
5.9%
7 2
 
5.9%
1482 1
 
2.9%
10 1
 
2.9%
8 1
 
2.9%
11 1
 
2.9%
18 1
 
2.9%
Other values (7) 7
20.6%
ValueCountFrequency (%)
0 10
29.4%
1 5
14.7%
2 3
 
8.8%
3 1
 
2.9%
7 2
 
5.9%
8 1
 
2.9%
9 2
 
5.9%
10 1
 
2.9%
11 1
 
2.9%
18 1
 
2.9%
ValueCountFrequency (%)
1482 1
2.9%
254 1
2.9%
79 1
2.9%
62 1
2.9%
53 1
2.9%
40 1
2.9%
19 1
2.9%
18 1
2.9%
11 1
2.9%
10 1
2.9%

기능직
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1675
Minimum34
Maximum9087
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size434.0 B
2024-04-21T08:19:19.359453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34
5-th percentile62.3
Q1256.5
median477
Q32849.75
95-th percentile5509.65
Maximum9087
Range9053
Interquartile range (IQR)2593.25

Descriptive statistics

Standard deviation2059.1125
Coefficient of variation (CV)1.2293209
Kurtosis4.2243863
Mean1675
Median Absolute Deviation (MAD)436
Skewness1.8885799
Sum56950
Variance4239944.3
MonotonicityNot monotonic
2024-04-21T08:19:19.575739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
6289 1
 
2.9%
2783 1
 
2.9%
3146 1
 
2.9%
261 1
 
2.9%
2328 1
 
2.9%
192 1
 
2.9%
5090 1
 
2.9%
268 1
 
2.9%
310 1
 
2.9%
3204 1
 
2.9%
Other values (24) 24
70.6%
ValueCountFrequency (%)
34 1
2.9%
48 1
2.9%
70 1
2.9%
115 1
2.9%
192 1
2.9%
195 1
2.9%
208 1
2.9%
239 1
2.9%
255 1
2.9%
261 1
2.9%
ValueCountFrequency (%)
9087 1
2.9%
6289 1
2.9%
5090 1
2.9%
3570 1
2.9%
3204 1
2.9%
3146 1
2.9%
2900 1
2.9%
2885 1
2.9%
2872 1
2.9%
2783 1
2.9%

고용직
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)14.7%
Missing0
Missing (%)0.0%
Memory size400.0 B
0
20 
1
3
 
2
2
 
2
5
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)2.9%

Sample

1st row5
2nd row0
3rd row1
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 20
58.8%
1 9
26.5%
3 2
 
5.9%
2 2
 
5.9%
5 1
 
2.9%

Length

2024-04-21T08:19:19.804340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T08:19:20.054778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 20
58.8%
1 9
26.5%
3 2
 
5.9%
2 2
 
5.9%
5 1
 
2.9%

공안직
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean426.23529
Minimum1
Maximum3757
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size434.0 B
2024-04-21T08:19:20.306425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.3
Q116.25
median109
Q3518.25
95-th percentile1601.2
Maximum3757
Range3756
Interquartile range (IQR)502

Descriptive statistics

Standard deviation809.92013
Coefficient of variation (CV)1.9001714
Kurtosis11.408032
Mean426.23529
Median Absolute Deviation (MAD)102.5
Skewness3.3212347
Sum14492
Variance655970.61
MonotonicityNot monotonic
2024-04-21T08:19:20.575602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
3091 1
 
2.9%
652 1
 
2.9%
418 1
 
2.9%
14 1
 
2.9%
513 1
 
2.9%
9 1
 
2.9%
762 1
 
2.9%
17 1
 
2.9%
15 1
 
2.9%
525 1
 
2.9%
Other values (24) 24
70.6%
ValueCountFrequency (%)
1 1
2.9%
2 1
2.9%
4 1
2.9%
9 1
2.9%
11 1
2.9%
13 1
2.9%
14 1
2.9%
15 1
2.9%
16 1
2.9%
17 1
2.9%
ValueCountFrequency (%)
3757 1
2.9%
3091 1
2.9%
799 1
2.9%
762 1
2.9%
705 1
2.9%
652 1
2.9%
565 1
2.9%
525 1
2.9%
520 1
2.9%
513 1
2.9%

군무원
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean422.85294
Minimum1
Maximum2701
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size434.0 B
2024-04-21T08:19:20.808300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile9.3
Q149.75
median130
Q3502
95-th percentile1555.55
Maximum2701
Range2700
Interquartile range (IQR)452.25

Descriptive statistics

Standard deviation617.05464
Coefficient of variation (CV)1.4592653
Kurtosis5.6027238
Mean422.85294
Median Absolute Deviation (MAD)119
Skewness2.2824845
Sum14377
Variance380756.43
MonotonicityNot monotonic
2024-04-21T08:19:21.042894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
1285 1
 
2.9%
2058 1
 
2.9%
493 1
 
2.9%
45 1
 
2.9%
505 1
 
2.9%
65 1
 
2.9%
727 1
 
2.9%
35 1
 
2.9%
117 1
 
2.9%
913 1
 
2.9%
Other values (24) 24
70.6%
ValueCountFrequency (%)
1 1
2.9%
8 1
2.9%
10 1
2.9%
12 1
2.9%
16 1
2.9%
22 1
2.9%
29 1
2.9%
35 1
2.9%
45 1
2.9%
64 1
2.9%
ValueCountFrequency (%)
2701 1
2.9%
2058 1
2.9%
1285 1
2.9%
1156 1
2.9%
992 1
2.9%
913 1
2.9%
802 1
2.9%
727 1
2.9%
505 1
2.9%
493 1
2.9%

연구직
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct30
Distinct (%)88.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean96.176471
Minimum0
Maximum955
Zeros1
Zeros (%)2.9%
Negative0
Negative (%)0.0%
Memory size434.0 B
2024-04-21T08:19:21.266342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.3
Q18
median38
Q3131
95-th percentile285.95
Maximum955
Range955
Interquartile range (IQR)123

Descriptive statistics

Standard deviation175.29326
Coefficient of variation (CV)1.822621
Kurtosis18.161011
Mean96.176471
Median Absolute Deviation (MAD)34
Skewness3.9478423
Sum3270
Variance30727.725
MonotonicityNot monotonic
2024-04-21T08:19:21.488706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
11 3
 
8.8%
7 2
 
5.9%
8 2
 
5.9%
427 1
 
2.9%
146 1
 
2.9%
3 1
 
2.9%
87 1
 
2.9%
57 1
 
2.9%
210 1
 
2.9%
4 1
 
2.9%
Other values (20) 20
58.8%
ValueCountFrequency (%)
0 1
 
2.9%
1 1
 
2.9%
3 1
 
2.9%
4 1
 
2.9%
5 1
 
2.9%
6 1
 
2.9%
7 2
5.9%
8 2
5.9%
9 1
 
2.9%
11 3
8.8%
ValueCountFrequency (%)
955 1
2.9%
427 1
2.9%
210 1
2.9%
173 1
2.9%
157 1
2.9%
146 1
2.9%
138 1
2.9%
137 1
2.9%
132 1
2.9%
128 1
2.9%

지도직
Real number (ℝ)

HIGH CORRELATION 

Distinct30
Distinct (%)88.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean135.67647
Minimum2
Maximum544
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size434.0 B
2024-04-21T08:19:21.700282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2.65
Q114.25
median34
Q3235.5
95-th percentile526.6
Maximum544
Range542
Interquartile range (IQR)221.25

Descriptive statistics

Standard deviation181.69217
Coefficient of variation (CV)1.3391575
Kurtosis0.07667715
Mean135.67647
Median Absolute Deviation (MAD)30
Skewness1.2633186
Sum4613
Variance33012.044
MonotonicityNot monotonic
2024-04-21T08:19:21.928462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
2 2
 
5.9%
17 2
 
5.9%
4 2
 
5.9%
14 2
 
5.9%
85 1
 
2.9%
521 1
 
2.9%
9 1
 
2.9%
344 1
 
2.9%
537 1
 
2.9%
24 1
 
2.9%
Other values (20) 20
58.8%
ValueCountFrequency (%)
2 2
5.9%
3 1
2.9%
4 2
5.9%
5 1
2.9%
9 1
2.9%
14 2
5.9%
15 1
2.9%
17 2
5.9%
22 1
2.9%
23 1
2.9%
ValueCountFrequency (%)
544 1
2.9%
537 1
2.9%
521 1
2.9%
447 1
2.9%
410 1
2.9%
363 1
2.9%
344 1
2.9%
325 1
2.9%
250 1
2.9%
192 1
2.9%

계약직
Real number (ℝ)

HIGH CORRELATION 

Distinct28
Distinct (%)82.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean71.882353
Minimum7
Maximum552
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size434.0 B
2024-04-21T08:19:22.143330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile7.65
Q111.25
median31
Q365.75
95-th percentile325.15
Maximum552
Range545
Interquartile range (IQR)54.5

Descriptive statistics

Standard deviation126.08289
Coefficient of variation (CV)1.7540173
Kurtosis10.563037
Mean71.882353
Median Absolute Deviation (MAD)21
Skewness3.2757819
Sum2444
Variance15896.895
MonotonicityNot monotonic
2024-04-21T08:19:22.372114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
11 3
 
8.8%
65 2
 
5.9%
10 2
 
5.9%
12 2
 
5.9%
7 2
 
5.9%
552 1
 
2.9%
122 1
 
2.9%
30 1
 
2.9%
9 1
 
2.9%
32 1
 
2.9%
Other values (18) 18
52.9%
ValueCountFrequency (%)
7 2
5.9%
8 1
 
2.9%
9 1
 
2.9%
10 2
5.9%
11 3
8.8%
12 2
5.9%
13 1
 
2.9%
16 1
 
2.9%
18 1
 
2.9%
22 1
 
2.9%
ValueCountFrequency (%)
552 1
2.9%
526 1
2.9%
217 1
2.9%
122 1
2.9%
105 1
2.9%
79 1
2.9%
74 1
2.9%
71 1
2.9%
66 1
2.9%
65 2
5.9%

기타
Real number (ℝ)

HIGH CORRELATION 

Distinct33
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean507.82353
Minimum26
Maximum3441
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size434.0 B
2024-04-21T08:19:22.589255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum26
5-th percentile40.7
Q1114.25
median196
Q3584.75
95-th percentile1669.4
Maximum3441
Range3415
Interquartile range (IQR)470.5

Descriptive statistics

Standard deviation758.13381
Coefficient of variation (CV)1.492908
Kurtosis10.625742
Mean507.82353
Median Absolute Deviation (MAD)168.5
Skewness3.2209975
Sum17266
Variance574766.88
MonotonicityNot monotonic
2024-04-21T08:19:22.818512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
517 2
 
5.9%
3193 1
 
2.9%
179 1
 
2.9%
552 1
 
2.9%
98 1
 
2.9%
99 1
 
2.9%
651 1
 
2.9%
142 1
 
2.9%
846 1
 
2.9%
788 1
 
2.9%
Other values (23) 23
67.6%
ValueCountFrequency (%)
26 1
2.9%
29 1
2.9%
47 1
2.9%
73 1
2.9%
98 1
2.9%
99 1
2.9%
103 1
2.9%
110 1
2.9%
114 1
2.9%
115 1
2.9%
ValueCountFrequency (%)
3441 1
2.9%
3193 1
2.9%
849 1
2.9%
846 1
2.9%
788 1
2.9%
651 1
2.9%
635 1
2.9%
630 1
2.9%
586 1
2.9%
581 1
2.9%

Interactions

2024-04-21T08:19:10.418212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:25.534189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:29.251610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:32.968723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:36.719127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:40.387367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:43.717849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:47.280854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:51.090553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:55.029974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:57.395853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:59.618565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:02.530053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:05.890615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:08.307128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:10.578352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:25.800123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:29.414940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:33.235474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:36.975495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:40.637127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:43.972610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:47.550574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:51.353503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:55.282189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:57.562294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:59.775272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:02.685206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:06.146928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:08.463563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:10.925512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:26.038875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:29.849928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:33.473881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:37.208363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:40.864359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:44.197147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:47.793316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:51.588044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:55.505275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:57.697036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:59.902533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:02.811659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:06.367458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:08.590595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:11.085877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:26.302631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:30.115646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:33.735334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:37.467346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:41.271681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:44.450376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:48.060424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:51.846184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:55.757940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:57.861202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:00.101416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:03.003444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:06.623105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:08.746532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:11.241212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:26.555595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:30.386668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:33.988800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:37.713961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:41.411854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:44.688703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:48.316337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:52.096161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:55.896988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:58.013318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:00.343356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:03.250194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:06.781486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:08.887507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:11.374679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:26.793045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:30.611018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:34.226383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:37.944844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:41.535062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:44.913372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:48.556381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:52.331151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:56.020428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:58.149851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:00.574848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:03.483210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:06.909541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:09.017896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:11.510261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:27.033963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:30.842501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:34.464917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:38.180472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:41.663556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:45.139967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:48.799303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:52.775799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:56.148138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:58.286452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:00.801482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:03.710970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:07.039079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:09.145857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:11.673863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:27.299670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:31.092511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:34.728874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:38.441780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:41.851257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:45.390959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:49.061585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:53.042641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:56.304327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:58.447647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:01.056841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:03.969822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:07.193211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:09.303791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:11.829629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:27.557963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:31.337696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:34.985421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:38.695139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:42.074190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:45.637908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:49.322062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:53.296070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:56.452836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:58.605374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:01.305004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:04.216245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:07.340730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:09.450694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:11.966410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:27.797739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:31.560089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:35.223045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:38.928711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:42.298877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:45.863040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:49.561335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:53.535022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:56.574757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:58.741473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:01.692940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:04.446980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:07.470239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:09.579642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:12.117853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:28.055532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:31.805151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:35.481640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:39.182050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:42.543977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:46.109332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:49.823759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:53.791926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:56.720309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:58.895234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:01.838219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:04.694984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:07.619687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:09.725725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:12.259751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:28.302390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:32.034792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:35.727886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:39.421338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:42.773895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:46.339057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:50.073374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:54.041771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:56.850456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:59.035261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:01.973986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:04.932468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:07.753631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:09.861574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:12.401713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:28.550256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:32.265388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:35.970241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:39.658239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:43.007008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:46.572597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:50.320221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:54.284241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:56.985490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:59.179970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:02.108688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:05.166029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:07.890810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:09.994589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:12.554060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:28.800073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:32.494299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:36.216481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:39.897245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:43.238809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:46.803322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:50.575653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:54.532425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:57.117030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:59.322226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:02.246775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:05.403980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:08.023372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:10.128858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:12.699440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:29.058902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:32.726364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:36.460888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:40.134965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:43.473656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:47.037906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:50.827839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:54.776540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:57.252738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:18:59.466579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:02.381161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:05.638335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:08.159810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:19:10.270756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T08:19:23.008624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역남녀구분정무직별정직일반직경찰소방교육직법관검사기능직고용직공안직군무원연구직지도직계약직기타
지역1.0000.0000.0000.2880.0000.0000.0000.0000.3740.2880.0000.0000.0000.0000.0000.0000.0000.000
남녀구분0.0001.0000.8340.0380.7360.9160.9520.9520.4920.0380.6550.2550.6800.7360.3970.7620.4540.878
0.0000.8341.0001.0000.7630.9880.9180.9720.8951.0000.8860.7360.9160.8220.8560.6370.7080.888
정무직0.2880.0381.0001.0000.7091.0000.9121.0001.0001.0001.0000.8151.0000.8521.0000.4320.6820.648
별정직0.0000.7360.7630.7091.0000.8070.9470.9360.5620.7090.9290.7180.8610.9830.6790.7670.7010.873
일반직0.0000.9160.9881.0000.8071.0000.9340.9820.8811.0000.9450.7750.9050.8600.8530.7240.7740.921
경찰0.0000.9520.9180.9120.9470.9341.0000.9790.6590.9120.7340.6790.8400.8900.6770.6970.6770.922
소방0.0000.9520.9721.0000.9360.9820.9791.0000.8401.0000.8700.8290.9360.9470.8510.7480.6610.908
교육직0.3740.4920.8951.0000.5620.8810.6590.8401.0001.0000.8050.7050.8550.6680.8470.0000.9200.940
법관검사0.2880.0381.0001.0000.7091.0000.9121.0001.0001.0001.0000.8151.0000.8521.0000.4320.6820.648
기능직0.0000.6550.8861.0000.9290.9450.7340.8700.8051.0001.0000.7690.9260.9400.8580.7040.7690.890
고용직0.0000.2550.7360.8150.7180.7750.6790.8290.7050.8150.7691.0000.9300.7400.9460.8110.7070.615
공안직0.0000.6800.9161.0000.8610.9050.8400.9360.8551.0000.9260.9301.0000.8890.9700.6380.8820.793
군무원0.0000.7360.8220.8520.9830.8600.8900.9470.6680.8520.9400.7400.8891.0000.7840.7300.5570.827
연구직0.0000.3970.8561.0000.6790.8530.6770.8510.8471.0000.8580.9460.9700.7841.0000.7610.8730.783
지도직0.0000.7620.6370.4320.7670.7240.6970.7480.0000.4320.7040.8110.6380.7300.7611.0000.0000.674
계약직0.0000.4540.7080.6820.7010.7740.6770.6610.9200.6820.7690.7070.8820.5570.8730.0001.0000.733
기타0.0000.8780.8880.6480.8730.9210.9220.9080.9400.6480.8900.6150.7930.8270.7830.6740.7331.000
2024-04-21T08:19:23.285910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
남녀구분고용직
남녀구분1.0000.291
고용직0.2911.000
2024-04-21T08:19:23.452222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정무직별정직일반직경찰소방교육직법관검사기능직공안직군무원연구직지도직계약직기타남녀구분고용직
1.0000.7260.9250.9310.8520.8290.9080.8350.9100.8720.8580.8490.7650.8550.9440.6070.598
정무직0.7261.0000.7700.7810.8300.8390.5270.8030.7840.8240.8260.8190.6940.8510.7860.0440.813
별정직0.9250.7701.0000.9530.9270.9130.7830.8390.9570.9370.9460.8940.8390.8670.9210.7310.546
일반직0.9310.7810.9531.0000.9320.9410.7590.8320.9620.9430.9280.8870.8990.8460.9650.7010.645
경찰0.8520.8300.9270.9321.0000.9400.6590.8750.9040.9620.9090.8860.8520.8130.9050.7520.529
소방0.8290.8390.9130.9410.9401.0000.6290.8120.8930.9170.9180.8740.8670.8080.8820.7520.715
교육직0.9080.5270.7830.7590.6590.6291.0000.7030.7380.6910.7050.7160.5410.7510.7820.3470.505
법관검사0.8350.8030.8390.8320.8750.8120.7031.0000.8350.8910.8390.8930.6750.8800.8370.0440.813
기능직0.9100.7840.9570.9620.9040.8930.7380.8351.0000.9360.9280.8790.8400.8610.9360.6470.612
공안직0.8720.8240.9370.9430.9620.9170.6910.8910.9361.0000.9280.9100.8610.8650.9100.7730.630
군무원0.8580.8260.9460.9280.9090.9180.7050.8390.9280.9281.0000.8740.8230.8880.8740.7310.574
연구직0.8490.8190.8940.8870.8860.8740.7160.8930.8790.9100.8741.0000.7730.8870.8810.4570.672
지도직0.7650.6940.8390.8990.8520.8670.5410.6750.8400.8610.8230.7731.0000.7140.8600.6870.592
계약직0.8550.8510.8670.8460.8130.8080.7510.8800.8610.8650.8880.8870.7141.0000.8680.5230.330
기타0.9440.7860.9210.9650.9050.8820.7820.8370.9360.9100.8740.8810.8600.8681.0000.6600.532
남녀구분0.6070.0440.7310.7010.7520.7520.3470.0440.6470.7730.7310.4570.6870.5230.6601.0000.291
고용직0.5980.8130.5460.6450.5290.7150.5050.8130.6120.6300.5740.6720.5920.3300.5320.2911.000

Missing values

2024-04-21T08:19:12.940497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T08:19:13.324437image/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

지역남녀구분정무직별정직일반직경찰소방교육직법관검사기능직고용직공안직군무원연구직지도직계약직기타
0서울67003821153826810916912121104414826289530911285427855523193
1서울287041416154151492220224621449010617411015217586
2부산2685911933990637725465165793570179911561734865635
3부산1026904517723012757224950219226225175
4대구224987555806626974915651532397070599213819271483
5대구650103515151944369129902366111713129
6인천1486210221551522424063306916520396406506666517
7인천42731271014244288701950131674873
8광주187554207689619552976043401618056532712825048377
9광주47970291264331304312080202261411145
지역남녀구분정무직별정직일반직경찰소방교육직법관검사기능직고용직공안직군무원연구직지도직계약직기타
24경북275521041211182254354049819509017627276353744651
25경북52720311718159300202680173512410142
26경남291406109110790305866764161827833652205815752174846
27경남732004719532074618031011511743712179
28전북235314268889923963876389112872252031021041065788
29전북521102716651132965028001812112316180
30전남1962932018104201332741388288514553285744732630
31전남3460023109613420501115011108179103
32제주6627681266671818718517459019174876430206
33제주1860014513511183070118341047