Overview

Dataset statistics

Number of variables9
Number of observations40
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.2 KiB
Average record size in memory81.3 B

Variable types

DateTime1
Numeric6
Categorical1
Text1

Dataset

Description국가보훈부 보훈대상자별 (성별) 인원현황 자료1. 적용 대상 국가유공자는 「국가유공자 등 예우 및 지원에 관한 법률」 제4조 참조2. 참전유공자는 「참전유공자예우 및 단체설립에 관한 법률」제2조에 의거 등록된 대상자 현황<참고>* 제적(국적상실), 등급기준 미달자, 단순 수훈자, 희생자력 제외* 합계는 등록대상별 현황의 합계임 (실인원이 아님)* (고엽제후유증)은 국가유공자예우법상 "전몰·전상·순직·공상군경"에 포함(중복합산을 하지 않음)
Author국가보훈부
URLhttps://www.data.go.kr/data/15072655/fileData.do

Alerts

기준일 has constant value ""Constant
순서 is highly overall correlated with 유족(남) and 1 other fieldsHigh correlation
합계 is highly overall correlated with 본인(남) and 1 other fieldsHigh correlation
본인(남) is highly overall correlated with 합계 and 1 other fieldsHigh correlation
본인(여) is highly overall correlated with 합계 and 2 other fieldsHigh correlation
유족(남) is highly overall correlated with 순서 and 1 other fieldsHigh correlation
유족(여) is highly overall correlated with 유족(남)High correlation
대상구분(대) is highly overall correlated with 순서 and 1 other fieldsHigh correlation
순서 has unique valuesUnique
대상구분 has unique valuesUnique
합계 has unique valuesUnique
본인(남) has 15 (37.5%) zerosZeros
본인(여) has 20 (50.0%) zerosZeros
유족(남) has 6 (15.0%) zerosZeros
유족(여) has 6 (15.0%) zerosZeros

Reproduction

Analysis started2024-04-21 01:39:54.960452
Analysis finished2024-04-21 01:40:00.073871
Duration5.11 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준일
Date

CONSTANT 

Distinct1
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
Minimum2024-03-31 00:00:00
Maximum2024-03-31 00:00:00
2024-04-21T10:40:00.330482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:40:00.445369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

순서
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.5
Minimum1
Maximum40
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2024-04-21T10:40:00.566027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.95
Q110.75
median20.5
Q330.25
95-th percentile38.05
Maximum40
Range39
Interquartile range (IQR)19.5

Descriptive statistics

Standard deviation11.690452
Coefficient of variation (CV)0.57026595
Kurtosis-1.2
Mean20.5
Median Absolute Deviation (MAD)10
Skewness0
Sum820
Variance136.66667
MonotonicityStrictly increasing
2024-04-21T10:40:00.708318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
1 1
 
2.5%
22 1
 
2.5%
24 1
 
2.5%
25 1
 
2.5%
26 1
 
2.5%
27 1
 
2.5%
28 1
 
2.5%
29 1
 
2.5%
30 1
 
2.5%
31 1
 
2.5%
Other values (30) 30
75.0%
ValueCountFrequency (%)
1 1
2.5%
2 1
2.5%
3 1
2.5%
4 1
2.5%
5 1
2.5%
6 1
2.5%
7 1
2.5%
8 1
2.5%
9 1
2.5%
10 1
2.5%
ValueCountFrequency (%)
40 1
2.5%
39 1
2.5%
38 1
2.5%
37 1
2.5%
36 1
2.5%
35 1
2.5%
34 1
2.5%
33 1
2.5%
32 1
2.5%
31 1
2.5%

대상구분(대)
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
국가유공자
13 
독립유공자
6 
지원대상
4 
보훈보상대상자
4 
참전유공자
3 
Other values (5)
10 

Length

Max length9
Median length5
Mean length5.4
Min length3

Unique

Unique2 ?
Unique (%)5.0%

Sample

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

Common Values

ValueCountFrequency (%)
국가유공자 13
32.5%
독립유공자 6
15.0%
지원대상 4
 
10.0%
보훈보상대상자 4
 
10.0%
참전유공자 3
 
7.5%
5.18민주유공자 3
 
7.5%
특수임무유공자 3
 
7.5%
고엽제 2
 
5.0%
준용대상 1
 
2.5%
제대군인 1
 
2.5%

Length

2024-04-21T10:40:00.868412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:40:00.996707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국가유공자 13
32.5%
독립유공자 6
15.0%
지원대상 4
 
10.0%
보훈보상대상자 4
 
10.0%
참전유공자 3
 
7.5%
5.18민주유공자 3
 
7.5%
특수임무유공자 3
 
7.5%
고엽제 2
 
5.0%
준용대상 1
 
2.5%
제대군인 1
 
2.5%

대상구분
Text

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
2024-04-21T10:40:01.235130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length7.85
Min length4

Characters and Unicode

Total characters314
Distinct characters77
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)100.0%

Sample

1st row건국훈장(순국선열)
2nd row건국포장(순국선열)
3rd row대통령표창(순국선열)
4th row건국훈장(애국지사)
5th row건국포장(애국지사)
ValueCountFrequency (%)
월남참전유공자 2
 
4.4%
건국포장(순국선열 1
 
2.2%
지원공상공무원 1
 
2.2%
재해사망군경유족 1
 
2.2%
재해부상군경 1
 
2.2%
재해사망공무원유족 1
 
2.2%
재해부상공무원 1
 
2.2%
6.25참전유공자 1
 
2.2%
6.25 1
 
2.2%
및 1
 
2.2%
Other values (34) 34
75.6%
2024-04-21T10:40:01.588679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
자 18
 
5.7%
공 17
 
5.4%
상 11
 
3.5%
국 11
 
3.5%
. 11
 
3.5%
무 11
 
3.5%
군 10
 
3.2%
원 10
 
3.2%
경 8
 
2.5%
유 8
 
2.5%
Other values (67) 199
63.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 258
82.2%
Decimal Number 28
 
8.9%
Other Punctuation 11
 
3.5%
Close Punctuation 6
 
1.9%
Open Punctuation 6
 
1.9%
Space Separator 5
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
자 18
 
7.0%
공 17
 
6.6%
상 11
 
4.3%
국 11
 
4.3%
무 11
 
4.3%
군 10
 
3.9%
원 10
 
3.9%
경 8
 
3.1%
유 8
 
3.1%
순 8
 
3.1%
Other values (56) 146
56.6%
Decimal Number
ValueCountFrequency (%)
1 7
25.0%
5 5
17.9%
8 4
14.3%
2 3
10.7%
6 3
10.7%
4 3
10.7%
9 3
10.7%
Other Punctuation
ValueCountFrequency (%)
. 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 258
82.2%
Common 56
 
17.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
자 18
 
7.0%
공 17
 
6.6%
상 11
 
4.3%
국 11
 
4.3%
무 11
 
4.3%
군 10
 
3.9%
원 10
 
3.9%
경 8
 
3.1%
유 8
 
3.1%
순 8
 
3.1%
Other values (56) 146
56.6%
Common
ValueCountFrequency (%)
. 11
19.6%
1 7
12.5%
) 6
10.7%
( 6
10.7%
5
8.9%
5 5
8.9%
8 4
 
7.1%
2 3
 
5.4%
6 3
 
5.4%
4 3
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 258
82.2%
ASCII 56
 
17.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
자 18
 
7.0%
공 17
 
6.6%
상 11
 
4.3%
국 11
 
4.3%
무 11
 
4.3%
군 10
 
3.9%
원 10
 
3.9%
경 8
 
3.1%
유 8
 
3.1%
순 8
 
3.1%
Other values (56) 146
56.6%
ASCII
ValueCountFrequency (%)
. 11
19.6%
1 7
12.5%
) 6
10.7%
( 6
10.7%
5
8.9%
5 5
8.9%
8 4
 
7.1%
2 3
 
5.4%
6 3
 
5.4%
4 3
 
5.4%

합계
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20804.025
Minimum16
Maximum172940
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2024-04-21T10:40:01.730110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum16
5-th percentile28.55
Q1243.5
median1378
Q310259.5
95-th percentile117105
Maximum172940
Range172924
Interquartile range (IQR)10016

Descriptive statistics

Standard deviation42487.659
Coefficient of variation (CV)2.0422807
Kurtosis5.7401318
Mean20804.025
Median Absolute Deviation (MAD)1333
Skewness2.485264
Sum832161
Variance1.8052012 × 109
MonotonicityNot monotonic
2024-04-21T10:40:01.869487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
785 1
 
2.5%
1849 1
 
2.5%
582 1
 
2.5%
1460 1
 
2.5%
6372 1
 
2.5%
252 1
 
2.5%
218 1
 
2.5%
39239 1
 
2.5%
172940 1
 
2.5%
1144 1
 
2.5%
Other values (30) 30
75.0%
ValueCountFrequency (%)
16 1
2.5%
20 1
2.5%
29 1
2.5%
31 1
2.5%
59 1
2.5%
159 1
2.5%
178 1
2.5%
179 1
2.5%
216 1
2.5%
218 1
2.5%
ValueCountFrequency (%)
172940 1
2.5%
155922 1
2.5%
115062 1
2.5%
88216 1
2.5%
67264 1
2.5%
49273 1
2.5%
48047 1
2.5%
39239 1
2.5%
35186 1
2.5%
15139 1
2.5%

본인(남)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct26
Distinct (%)65.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13721.95
Minimum0
Maximum172633
Zeros15
Zeros (%)37.5%
Negative0
Negative (%)0.0%
Memory size492.0 B
2024-04-21T10:40:01.990561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median126
Q32264.75
95-th percentile58352.55
Maximum172633
Range172633
Interquartile range (IQR)2264.75

Descriptive statistics

Standard deviation34317.428
Coefficient of variation (CV)2.5009148
Kurtosis12.632898
Mean13721.95
Median Absolute Deviation (MAD)126
Skewness3.3818049
Sum548878
Variance1.1776859 × 109
MonotonicityNot monotonic
2024-04-21T10:40:02.108366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 15
37.5%
5830 1
 
2.5%
111259 1
 
2.5%
1711 1
 
2.5%
1131 1
 
2.5%
1253 1
 
2.5%
1987 1
 
2.5%
127 1
 
2.5%
49221 1
 
2.5%
1137 1
 
2.5%
Other values (16) 16
40.0%
ValueCountFrequency (%)
0 15
37.5%
1 1
 
2.5%
3 1
 
2.5%
7 1
 
2.5%
19 1
 
2.5%
125 1
 
2.5%
127 1
 
2.5%
176 1
 
2.5%
249 1
 
2.5%
435 1
 
2.5%
ValueCountFrequency (%)
172633 1
2.5%
111259 1
2.5%
55568 1
2.5%
49221 1
2.5%
49084 1
2.5%
40929 1
2.5%
38215 1
2.5%
12940 1
2.5%
5830 1
2.5%
3098 1
2.5%

본인(여)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct21
Distinct (%)52.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean168.45
Minimum0
Maximum3803
Zeros20
Zeros (%)50.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2024-04-21T10:40:02.233806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.5
Q351.25
95-th percentile806.45
Maximum3803
Range3803
Interquartile range (IQR)51.25

Descriptive statistics

Standard deviation623.92656
Coefficient of variation (CV)3.7039274
Kurtosis31.335074
Mean168.45
Median Absolute Deviation (MAD)0.5
Skewness5.4177934
Sum6738
Variance389284.36
MonotonicityNot monotonic
2024-04-21T10:40:02.370214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 20
50.0%
1 1
 
2.5%
3803 1
 
2.5%
4 1
 
2.5%
71 1
 
2.5%
129 1
 
2.5%
51 1
 
2.5%
52 1
 
2.5%
7 1
 
2.5%
307 1
 
2.5%
Other values (11) 11
27.5%
ValueCountFrequency (%)
0 20
50.0%
1 1
 
2.5%
4 1
 
2.5%
7 1
 
2.5%
13 1
 
2.5%
14 1
 
2.5%
17 1
 
2.5%
25 1
 
2.5%
32 1
 
2.5%
43 1
 
2.5%
ValueCountFrequency (%)
3803 1
2.5%
1024 1
2.5%
795 1
2.5%
307 1
2.5%
181 1
2.5%
129 1
2.5%
109 1
2.5%
71 1
2.5%
60 1
2.5%
52 1
2.5%

유족(남)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct34
Distinct (%)85.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2564.75
Minimum0
Maximum33465
Zeros6
Zeros (%)15.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2024-04-21T10:40:02.516765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q112.75
median62
Q3592.25
95-th percentile18935.45
Maximum33465
Range33465
Interquartile range (IQR)579.5

Descriptive statistics

Standard deviation7519.5987
Coefficient of variation (CV)2.9319032
Kurtosis11.89434
Mean2564.75
Median Absolute Deviation (MAD)62
Skewness3.5352614
Sum102590
Variance56544365
MonotonicityNot monotonic
2024-04-21T10:40:02.651920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
0 6
 
15.0%
69 2
 
5.0%
508 1
 
2.5%
40 1
 
2.5%
18 1
 
2.5%
39 1
 
2.5%
4 1
 
2.5%
575 1
 
2.5%
154 1
 
2.5%
1 1
 
2.5%
Other values (24) 24
60.0%
ValueCountFrequency (%)
0 6
15.0%
1 1
 
2.5%
3 1
 
2.5%
4 1
 
2.5%
6 1
 
2.5%
15 1
 
2.5%
18 1
 
2.5%
20 1
 
2.5%
26 1
 
2.5%
32 1
 
2.5%
ValueCountFrequency (%)
33465 1
2.5%
30895 1
2.5%
18306 1
2.5%
4867 1
2.5%
4414 1
2.5%
2660 1
2.5%
1995 1
2.5%
1471 1
2.5%
1040 1
2.5%
644 1
2.5%

유족(여)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct33
Distinct (%)82.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4348.875
Minimum0
Maximum66857
Zeros6
Zeros (%)15.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2024-04-21T10:40:02.785818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q116
median176
Q3977.5
95-th percentile18252.9
Maximum66857
Range66857
Interquartile range (IQR)961.5

Descriptive statistics

Standard deviation12749.366
Coefficient of variation (CV)2.9316469
Kurtosis16.979586
Mean4348.875
Median Absolute Deviation (MAD)176
Skewness4.0232027
Sum173955
Variance1.6254633 × 108
MonotonicityNot monotonic
2024-04-21T10:40:02.920032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
0 6
 
15.0%
139 2
 
5.0%
16 2
 
5.0%
277 1
 
2.5%
885 1
 
2.5%
110 1
 
2.5%
91 1
 
2.5%
177 1
 
2.5%
83 1
 
2.5%
375 1
 
2.5%
Other values (23) 23
57.5%
ValueCountFrequency (%)
0 6
15.0%
9 1
 
2.5%
13 1
 
2.5%
14 1
 
2.5%
16 2
 
5.0%
27 1
 
2.5%
83 1
 
2.5%
91 1
 
2.5%
106 1
 
2.5%
110 1
 
2.5%
ValueCountFrequency (%)
66857 1
2.5%
44338 1
2.5%
16880 1
2.5%
13657 1
2.5%
10272 1
2.5%
6638 1
2.5%
5283 1
2.5%
2054 1
2.5%
1829 1
2.5%
1255 1
2.5%

Interactions

2024-04-21T10:39:59.353779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:56.786996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:57.355257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:57.866550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:58.347455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:58.869487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:59.434983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:56.925372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:57.453366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:57.949039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:58.428051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:58.951523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:59.518182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:57.003884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:57.530906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:58.026759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:58.527804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:59.031394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:59.598066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:57.090664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:57.605932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:58.103625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:58.619772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:59.119805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:59.680507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:57.178617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:57.697022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:58.190113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:58.706388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:59.198963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:59.785881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:57.259243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:57.784558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:58.267986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:58.792760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:59.275657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T10:40:03.031929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순서대상구분(대)대상구분합계본인(남)본인(여)유족(남)유족(여)
순서1.0000.9751.0000.3520.5910.0000.5280.296
대상구분(대)0.9751.0001.0000.5310.8140.7910.0000.000
대상구분1.0001.0001.0001.0001.0001.0001.0001.000
합계0.3520.5311.0001.0000.8800.9820.7940.790
본인(남)0.5910.8141.0000.8801.0000.8150.3880.816
본인(여)0.0000.7911.0000.9820.8151.0000.0000.000
유족(남)0.5280.0001.0000.7940.3880.0001.0000.865
유족(여)0.2960.0001.0000.7900.8160.0000.8651.000
2024-04-21T10:40:03.174038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순서합계본인(남)본인(여)유족(남)유족(여)대상구분(대)
순서1.000-0.0110.3370.323-0.571-0.4730.723
합계-0.0111.0000.7060.5790.3850.4350.285
본인(남)0.3370.7061.0000.855-0.105-0.0270.431
본인(여)0.3230.5790.8551.000-0.157-0.0870.608
유족(남)-0.5710.385-0.105-0.1571.0000.9720.000
유족(여)-0.4730.435-0.027-0.0870.9721.0000.000
대상구분(대)0.7230.2850.4310.6080.0000.0001.000

Missing values

2024-04-21T10:39:59.909887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T10:40:00.021510image/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

기준일순서대상구분(대)대상구분합계본인(남)본인(여)유족(남)유족(여)
02024-03-311독립유공자건국훈장(순국선열)78500508277
12024-03-312독립유공자건국포장(순국선열)2900209
22024-03-313독립유공자대통령표창(순국선열)59003227
32024-03-314독립유공자건국훈장(애국지사)44933126601829
42024-03-315독립유공자건국포장(애국지사)78600426360
52024-03-316독립유공자대통령표창(애국지사)27271014711255
62024-03-317국가유공자전몰군경35186001830616880
72024-03-318국가유공자전상군경15592255568323346566857
82024-03-319국가유공자순직군경1513900486710272
92024-03-3110국가유공자공상군경6726449084109441413657
기준일순서대상구분(대)대상구분합계본인(남)본인(여)유족(남)유족(여)
302024-03-3131참전유공자6.25 및 월남참전유공자11441137700
312024-03-3132고엽제고엽제후유의증49273492215200
322024-03-3133고엽제고엽제 후유증 2세 환자1781275100
332024-03-31345.18민주유공자5.18사망행불자1590053106
342024-03-31355.18민주유공자5.18부상자27651987129172477
352024-03-31365.18민주유공자5.18희생자155412537155175
362024-03-3137특수임무유공자특수임무사망.행방불명자2000614
372024-03-3138특수임무유공자특수임무부상자12961131026139
382024-03-3139특수임무유공자특수임무공로자258317114264604
392024-03-3140제대군인중.장기복무제대군인115062111259380300