Overview

Dataset statistics

Number of variables7
Number of observations51
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.1 KiB
Average record size in memory62.5 B

Variable types

DateTime1
Categorical1
Numeric4
Text1

Dataset

Description경상남도 보훈대상자별 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/15087447/fileData.do

Alerts

기준년월 has constant value ""Constant
지역명 has constant value ""Constant
순서 is highly overall correlated with 유족High correlation
합계 is highly overall correlated with 본인High correlation
본인 is highly overall correlated with 합계High correlation
유족 is highly overall correlated with 순서High correlation
순서 has unique valuesUnique
합계 has 1 (2.0%) zerosZeros
본인 has 21 (41.2%) zerosZeros
유족 has 9 (17.6%) zerosZeros

Reproduction

Analysis started2024-03-14 23:39:13.059908
Analysis finished2024-03-14 23:39:17.671618
Duration4.61 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년월
Date

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size536.0 B
Minimum2023-12-31 00:00:00
Maximum2023-12-31 00:00:00
2024-03-15T08:39:17.753580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:39:17.933015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

지역명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size536.0 B
경상남도
51 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경상남도 51
100.0%

Length

2024-03-15T08:39:18.131421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T08:39:18.379011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상남도 51
100.0%

순서
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct51
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26
Minimum1
Maximum51
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size587.0 B
2024-03-15T08:39:18.715262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.5
Q113.5
median26
Q338.5
95-th percentile48.5
Maximum51
Range50
Interquartile range (IQR)25

Descriptive statistics

Standard deviation14.866069
Coefficient of variation (CV)0.57177187
Kurtosis-1.2
Mean26
Median Absolute Deviation (MAD)13
Skewness0
Sum1326
Variance221
MonotonicityStrictly increasing
2024-03-15T08:39:19.059933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
2.0%
2 1
 
2.0%
29 1
 
2.0%
30 1
 
2.0%
31 1
 
2.0%
32 1
 
2.0%
33 1
 
2.0%
34 1
 
2.0%
35 1
 
2.0%
36 1
 
2.0%
Other values (41) 41
80.4%
ValueCountFrequency (%)
1 1
2.0%
2 1
2.0%
3 1
2.0%
4 1
2.0%
5 1
2.0%
6 1
2.0%
7 1
2.0%
8 1
2.0%
9 1
2.0%
10 1
2.0%
ValueCountFrequency (%)
51 1
2.0%
50 1
2.0%
49 1
2.0%
48 1
2.0%
47 1
2.0%
46 1
2.0%
45 1
2.0%
44 1
2.0%
43 1
2.0%
42 1
2.0%

대상구분
Text

Distinct48
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Memory size536.0 B
2024-03-15T08:39:19.927397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11
Mean length6.9411765
Min length4

Characters and Unicode

Total characters354
Distinct characters80
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)88.2%

Sample

1st row[순국선열]
2nd row건국훈장
3rd row건국포장
4th row대통령표창
5th row[애국지사]
ValueCountFrequency (%)
건국훈장 2
 
3.6%
행불자 2
 
3.6%
또는 2
 
3.6%
대통령표창 2
 
3.6%
건국포장 2
 
3.6%
특수임무유공자 1
 
1.8%
참전유공자 1
 
1.8%
특수임무부상자 1
 
1.8%
6.25및월남전쟁 1
 
1.8%
지원공상공무원 1
 
1.8%
Other values (40) 40
72.7%
2024-03-15T08:39:21.330841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
자 21
 
5.9%
공 19
 
5.4%
상 16
 
4.5%
· 14
 
4.0%
무 13
 
3.7%
원 12
 
3.4%
군 11
 
3.1%
[ 10
 
2.8%
] 10
 
2.8%
경 9
 
2.5%
Other values (70) 219
61.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 281
79.4%
Decimal Number 34
 
9.6%
Other Punctuation 15
 
4.2%
Open Punctuation 10
 
2.8%
Close Punctuation 10
 
2.8%
Space Separator 4
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
자 21
 
7.5%
공 19
 
6.8%
상 16
 
5.7%
무 13
 
4.6%
원 12
 
4.3%
군 11
 
3.9%
경 9
 
3.2%
전 8
 
2.8%
유 7
 
2.5%
국 7
 
2.5%
Other values (58) 158
56.2%
Decimal Number
ValueCountFrequency (%)
1 9
26.5%
5 6
17.6%
8 5
14.7%
9 4
11.8%
4 4
11.8%
6 3
 
8.8%
2 3
 
8.8%
Other Punctuation
ValueCountFrequency (%)
· 14
93.3%
. 1
 
6.7%
Open Punctuation
ValueCountFrequency (%)
[ 10
100.0%
Close Punctuation
ValueCountFrequency (%)
] 10
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 281
79.4%
Common 73
 
20.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
자 21
 
7.5%
공 19
 
6.8%
상 16
 
5.7%
무 13
 
4.6%
원 12
 
4.3%
군 11
 
3.9%
경 9
 
3.2%
전 8
 
2.8%
유 7
 
2.5%
국 7
 
2.5%
Other values (58) 158
56.2%
Common
ValueCountFrequency (%)
· 14
19.2%
[ 10
13.7%
] 10
13.7%
1 9
12.3%
5 6
8.2%
8 5
 
6.8%
4
 
5.5%
9 4
 
5.5%
4 4
 
5.5%
6 3
 
4.1%
Other values (2) 4
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 281
79.4%
ASCII 59
 
16.7%
None 14
 
4.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
자 21
 
7.5%
공 19
 
6.8%
상 16
 
5.7%
무 13
 
4.6%
원 12
 
4.3%
군 11
 
3.9%
경 9
 
3.2%
전 8
 
2.8%
유 7
 
2.5%
국 7
 
2.5%
Other values (58) 158
56.2%
None
ValueCountFrequency (%)
· 14
100.0%
ASCII
ValueCountFrequency (%)
[ 10
16.9%
] 10
16.9%
1 9
15.3%
5 6
10.2%
8 5
8.5%
4
 
6.8%
9 4
 
6.8%
4 4
 
6.8%
6 3
 
5.1%
2 3
 
5.1%

합계
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct46
Distinct (%)90.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1897.3137
Minimum0
Maximum19315
Zeros1
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size587.0 B
2024-03-15T08:39:21.578725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q122
median109
Q31003.5
95-th percentile11501.5
Maximum19315
Range19315
Interquartile range (IQR)981.5

Descriptive statistics

Standard deviation4055.9122
Coefficient of variation (CV)2.137713
Kurtosis7.7950741
Mean1897.3137
Median Absolute Deviation (MAD)106
Skewness2.7695158
Sum96763
Variance16450424
MonotonicityNot monotonic
2024-03-15T08:39:21.860338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
1 3
 
5.9%
37 2
 
3.9%
33 2
 
3.9%
15 2
 
3.9%
45 1
 
2.0%
528 1
 
2.0%
109 1
 
2.0%
375 1
 
2.0%
18 1
 
2.0%
26 1
 
2.0%
Other values (36) 36
70.6%
ValueCountFrequency (%)
0 1
 
2.0%
1 3
5.9%
2 1
 
2.0%
3 1
 
2.0%
4 1
 
2.0%
7 1
 
2.0%
15 2
3.9%
16 1
 
2.0%
17 1
 
2.0%
18 1
 
2.0%
ValueCountFrequency (%)
19315 1
2.0%
13907 1
2.0%
11680 1
2.0%
11323 1
2.0%
7819 1
2.0%
5468 1
2.0%
4726 1
2.0%
4436 1
2.0%
3915 1
2.0%
3511 1
2.0%

본인
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct30
Distinct (%)58.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1205.451
Minimum0
Maximum13907
Zeros21
Zeros (%)41.2%
Negative0
Negative (%)0.0%
Memory size587.0 B
2024-03-15T08:39:22.094641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median21
Q3301.5
95-th percentile7192.5
Maximum13907
Range13907
Interquartile range (IQR)301.5

Descriptive statistics

Standard deviation2904.9227
Coefficient of variation (CV)2.4098223
Kurtosis9.802557
Mean1205.451
Median Absolute Deviation (MAD)21
Skewness3.0892503
Sum61478
Variance8438575.7
MonotonicityNot monotonic
2024-03-15T08:39:22.414214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0 21
41.2%
267 2
 
3.9%
24 1
 
2.0%
7819 1
 
2.0%
132 1
 
2.0%
98 1
 
2.0%
230 1
 
2.0%
17 1
 
2.0%
21 1
 
2.0%
38 1
 
2.0%
Other values (20) 20
39.2%
ValueCountFrequency (%)
0 21
41.2%
7 1
 
2.0%
12 1
 
2.0%
15 1
 
2.0%
17 1
 
2.0%
21 1
 
2.0%
24 1
 
2.0%
27 1
 
2.0%
38 1
 
2.0%
43 1
 
2.0%
ValueCountFrequency (%)
13907 1
2.0%
11680 1
2.0%
7819 1
2.0%
6566 1
2.0%
4181 1
2.0%
3511 1
2.0%
3378 1
2.0%
3188 1
2.0%
2208 1
2.0%
2182 1
2.0%

유족
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct35
Distinct (%)68.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean691.86275
Minimum0
Maximum12749
Zeros9
Zeros (%)17.6%
Negative0
Negative (%)0.0%
Memory size587.0 B
2024-03-15T08:39:22.651231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median18
Q3158.5
95-th percentile3659.5
Maximum12749
Range12749
Interquartile range (IQR)156.5

Descriptive statistics

Standard deviation2179.4787
Coefficient of variation (CV)3.1501605
Kurtosis21.006056
Mean691.86275
Median Absolute Deviation (MAD)18
Skewness4.4226577
Sum35285
Variance4750127.5
MonotonicityNot monotonic
2024-03-15T08:39:22.921482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
0 9
 
17.6%
1 3
 
5.9%
18 2
 
3.9%
33 2
 
3.9%
44 2
 
3.9%
15 2
 
3.9%
8 2
 
3.9%
2 2
 
3.9%
39 1
 
2.0%
109 1
 
2.0%
Other values (25) 25
49.0%
ValueCountFrequency (%)
0 9
17.6%
1 3
 
5.9%
2 2
 
3.9%
3 1
 
2.0%
4 1
 
2.0%
5 1
 
2.0%
8 2
 
3.9%
10 1
 
2.0%
12 1
 
2.0%
15 2
 
3.9%
ValueCountFrequency (%)
12749 1
2.0%
7945 1
2.0%
4808 1
2.0%
2511 1
2.0%
1707 1
2.0%
1248 1
2.0%
1045 1
2.0%
695 1
2.0%
545 1
2.0%
524 1
2.0%

Interactions

2024-03-15T08:39:15.994901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:39:13.347920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:39:14.197860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:39:15.197685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:39:16.248092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:39:13.586158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:39:14.407974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:39:15.349010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:39:16.518752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:39:13.847192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:39:14.674892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:39:15.515122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:39:16.930218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:39:14.050872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:39:14.940619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:39:15.738720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T08:39:23.149919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순서대상구분합계본인유족
순서1.0000.7700.5350.3620.264
대상구분0.7701.0001.0001.0001.000
합계0.5351.0001.0000.9880.859
본인0.3621.0000.9881.0000.710
유족0.2641.0000.8590.7101.000
2024-03-15T08:39:23.450925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순서합계본인유족
순서1.000-0.0670.314-0.565
합계-0.0671.0000.7490.492
본인0.3140.7491.0000.062
유족-0.5650.4920.0621.000

Missing values

2024-03-15T08:39:17.131349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T08:39:17.481100image/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

기준년월지역명순서대상구분합계본인유족
02023-12-31경상남도1[순국선열]37037
12023-12-31경상남도2건국훈장33033
22023-12-31경상남도3건국포장303
32023-12-31경상남도4대통령표창101
42023-12-31경상남도5[애국지사]3120312
52023-12-31경상남도6건국훈장1490149
62023-12-31경상남도7건국포장40040
72023-12-31경상남도8대통령표창1230123
82023-12-31경상남도9[전몰·전상·순직·공상군경]19315656612749
92023-12-31경상남도10전몰군경251102511
기준년월지역명순서대상구분합계본인유족
412023-12-31경상남도42고엽제후유증2세770
422023-12-31경상남도43[5·18민주유공자]503812
432023-12-31경상남도445·18사망자 또는 행불자202
442023-12-31경상남도455·18부상자312110
452023-12-31경상남도465·18희생자17170
462023-12-31경상남도47[특수임무유공자]27223042
472023-12-31경상남도48특수임무사망자 또는 행불자101
482023-12-31경상남도49특수임무부상자106988
492023-12-31경상남도50특수임무공로자16513233
502023-12-31경상남도51중·장기복무제대군인781978190