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

Categorical2
Numeric4
Text1

Dataset

Description부산광역시 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/15087457/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 8 (15.7%) zerosZeros

Reproduction

Analysis started2024-03-14 15:28:21.893505
Analysis finished2024-03-14 15:28:26.175428
Duration4.28 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년월
Categorical

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size536.0 B
2023-12-31
51 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-12-31
2nd row2023-12-31
3rd row2023-12-31
4th row2023-12-31
5th row2023-12-31

Common Values

ValueCountFrequency (%)
2023-12-31 51
100.0%

Length

2024-03-15T00:28:26.386128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T00:28:26.686957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-12-31 51
100.0%

지역명
Categorical

CONSTANT 

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

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부산광역시 51
100.0%

Length

2024-03-15T00:28:27.006151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T00:28:27.303887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 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
2024-03-15T00:28:27.651415image/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
2024-03-15T00:28:27.986599image/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
2024-03-15T00:28:28.835459image/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%
2024-03-15T00:28:29.904121image/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 

Distinct47
Distinct (%)92.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2106.4314
Minimum0
Maximum21858
Zeros1
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size587.0 B
2024-03-15T00:28:30.145718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.5
Q121
median119
Q31007
95-th percentile14280.5
Maximum21858
Range21858
Interquartile range (IQR)986

Descriptive statistics

Standard deviation4752.8144
Coefficient of variation (CV)2.2563348
Kurtosis8.1640152
Mean2106.4314
Median Absolute Deviation (MAD)116
Skewness2.9049809
Sum107428
Variance22589244
MonotonicityNot monotonic
2024-03-15T00:28:30.385369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
48 2
 
3.9%
3 2
 
3.9%
1 2
 
3.9%
22 2
 
3.9%
15364 1
 
2.0%
13 1
 
2.0%
38 1
 
2.0%
527 1
 
2.0%
99 1
 
2.0%
395 1
 
2.0%
Other values (37) 37
72.5%
ValueCountFrequency (%)
0 1
2.0%
1 2
3.9%
2 1
2.0%
3 2
3.9%
11 1
2.0%
13 1
2.0%
14 1
2.0%
15 1
2.0%
18 1
2.0%
19 1
2.0%
ValueCountFrequency (%)
21858 1
2.0%
17592 1
2.0%
15364 1
2.0%
13197 1
2.0%
5870 1
2.0%
5742 1
2.0%
5024 1
2.0%
4943 1
2.0%
4745 1
2.0%
2709 1
2.0%

본인
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct30
Distinct (%)58.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1374.8039
Minimum0
Maximum17592
Zeros21
Zeros (%)41.2%
Negative0
Negative (%)0.0%
Memory size587.0 B
2024-03-15T00:28:30.593757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median17
Q3314
95-th percentile6808
Maximum17592
Range17592
Interquartile range (IQR)314

Descriptive statistics

Standard deviation3545.3565
Coefficient of variation (CV)2.5788088
Kurtosis12.629592
Mean1374.8039
Median Absolute Deviation (MAD)17
Skewness3.4751866
Sum70115
Variance12569552
MonotonicityNot monotonic
2024-03-15T00:28:30.914911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0 21
41.2%
263 2
 
3.9%
9 1
 
2.0%
4745 1
 
2.0%
92 1
 
2.0%
152 1
 
2.0%
244 1
 
2.0%
19 1
 
2.0%
24 1
 
2.0%
43 1
 
2.0%
Other values (20) 20
39.2%
ValueCountFrequency (%)
0 21
41.2%
7 1
 
2.0%
9 1
 
2.0%
10 1
 
2.0%
14 1
 
2.0%
17 1
 
2.0%
19 1
 
2.0%
24 1
 
2.0%
32 1
 
2.0%
43 1
 
2.0%
ValueCountFrequency (%)
17592 1
2.0%
15364 1
2.0%
8592 1
2.0%
5024 1
2.0%
5002 1
2.0%
4745 1
2.0%
3590 1
2.0%
3409 1
2.0%
2170 1
2.0%
1463 1
2.0%

유족
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct36
Distinct (%)70.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean731.62745
Minimum0
Maximum13266
Zeros8
Zeros (%)15.7%
Negative0
Negative (%)0.0%
Memory size587.0 B
2024-03-15T00:28:31.307879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median21
Q3191.5
95-th percentile3831.5
Maximum13266
Range13266
Interquartile range (IQR)188.5

Descriptive statistics

Standard deviation2268.8615
Coefficient of variation (CV)3.1011158
Kurtosis20.755288
Mean731.62745
Median Absolute Deviation (MAD)21
Skewness4.381796
Sum37313
Variance5147732.4
MonotonicityNot monotonic
2024-03-15T00:28:31.662419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
0 8
 
15.7%
3 3
 
5.9%
48 2
 
3.9%
2 2
 
3.9%
13 2
 
3.9%
1 2
 
3.9%
35 2
 
3.9%
19 2
 
3.9%
6 1
 
2.0%
38 1
 
2.0%
Other values (26) 26
51.0%
ValueCountFrequency (%)
0 8
15.7%
1 2
 
3.9%
2 2
 
3.9%
3 3
 
5.9%
4 1
 
2.0%
6 1
 
2.0%
10 1
 
2.0%
13 2
 
3.9%
14 1
 
2.0%
15 1
 
2.0%
ValueCountFrequency (%)
13266 1
2.0%
8195 1
2.0%
4954 1
2.0%
2709 1
2.0%
2333 1
2.0%
1353 1
2.0%
1009 1
2.0%
742 1
2.0%
542 1
2.0%
494 1
2.0%

Interactions

2024-03-15T00:28:25.031888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:28:22.119385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:28:23.093859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:28:24.042135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:28:25.266031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:28:22.354917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:28:23.327311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:28:24.286757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:28:25.404424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:28:22.587874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:28:23.552851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:28:24.524771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:28:25.559367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:28:22.850098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:28:23.797941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:28:24.778830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T00:28:31.923043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순서대상구분합계본인유족
순서1.0000.7700.4380.3280.452
대상구분0.7701.0001.0001.0001.000
합계0.4381.0001.0000.9260.913
본인0.3281.0000.9261.0000.867
유족0.4521.0000.9130.8671.000
2024-03-15T00:28:32.397985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순서합계본인유족
순서1.000-0.0930.322-0.569
합계-0.0931.0000.7190.487
본인0.3220.7191.0000.025
유족-0.5690.4870.0251.000

Missing values

2024-03-15T00:28:25.756609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T00:28:26.031565image/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
02023-12-31부산광역시1[순국선열]48048
12023-12-31부산광역시2건국훈장43043
22023-12-31부산광역시3건국포장303
32023-12-31부산광역시4대통령표창202
42023-12-31부산광역시5[애국지사]4940494
52023-12-31부산광역시6건국훈장2630263
62023-12-31부산광역시7건국포장48048
72023-12-31부산광역시8대통령표창1830183
82023-12-31부산광역시9[전몰·전상·순직·공상군경]21858859213266
92023-12-31부산광역시10전몰군경270902709
기준년월지역명순서대상구분합계본인유족
412023-12-31부산광역시42고엽제후유증2세14140
422023-12-31부산광역시43[5·18민주유공자]574314
432023-12-31부산광역시445·18사망자 또는 행불자101
442023-12-31부산광역시455·18부상자342410
452023-12-31부산광역시465·18희생자22193
462023-12-31부산광역시47[특수임무유공자]30124457
472023-12-31부산광역시48특수임무사망자 또는 행불자101
482023-12-31부산광역시49특수임무부상자17315221
492023-12-31부산광역시50특수임무공로자1279235
502023-12-31부산광역시51중·장기복무제대군인474547450