Overview

Dataset statistics

Number of variables6
Number of observations51
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.7 KiB
Average record size in memory54.6 B

Variable types

DateTime1
Numeric4
Text1

Dataset

Description국가보훈부 보훈대상자별 총괄 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/15072653/fileData.do

Alerts

기준일 has constant value ""Constant
합계 is highly overall correlated with 본 인High correlation
본 인 is highly overall correlated with 합계High correlation
순서 has unique valuesUnique
합계 has unique valuesUnique
본 인 has 16 (31.4%) zerosZeros
유 족 has 7 (13.7%) zerosZeros

Reproduction

Analysis started2024-04-21 01:39:36.614223
Analysis finished2024-04-21 01:39:39.727052
Duration3.11 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준일
Date

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size540.0 B
Minimum2024-03-31 00:00:00
Maximum2024-03-31 00:00:00
2024-04-21T10:39:39.765918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:39.846955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

순서
Real number (ℝ)

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 size591.0 B
2024-04-21T10:39:39.949806image/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
2024-04-21T10:39:40.103312image/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 size540.0 B
2024-04-21T10:39:40.350022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11
Mean length6.9803922
Min length4

Characters and Unicode

Total characters356
Distinct characters82
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%
2024-04-21T10:39:40.681708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
자 21
 
5.9%
공 19
 
5.3%
상 16
 
4.5%
· 14
 
3.9%
무 13
 
3.7%
원 12
 
3.4%
군 11
 
3.1%
] 10
 
2.8%
[ 10
 
2.8%
경 9
 
2.5%
Other values (72) 221
62.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 281
78.9%
Decimal Number 34
 
9.6%
Other Punctuation 15
 
4.2%
Close Punctuation 11
 
3.1%
Open Punctuation 11
 
3.1%
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%
순 7
 
2.5%
유 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%
Close Punctuation
ValueCountFrequency (%)
] 10
90.9%
) 1
 
9.1%
Open Punctuation
ValueCountFrequency (%)
[ 10
90.9%
( 1
 
9.1%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 281
78.9%
Common 75
 
21.1%

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%
순 7
 
2.5%
유 7
 
2.5%
Other values (58) 158
56.2%
Common
ValueCountFrequency (%)
· 14
18.7%
] 10
13.3%
[ 10
13.3%
1 9
12.0%
5 6
8.0%
8 5
 
6.7%
4
 
5.3%
9 4
 
5.3%
4 4
 
5.3%
6 3
 
4.0%
Other values (4) 6
8.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 281
78.9%
ASCII 61
 
17.1%
None 14
 
3.9%

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%
순 7
 
2.5%
유 7
 
2.5%
Other values (58) 158
56.2%
None
ValueCountFrequency (%)
· 14
100.0%
ASCII
ValueCountFrequency (%)
] 10
16.4%
[ 10
16.4%
1 9
14.8%
5 6
9.8%
8 5
8.2%
4
 
6.6%
9 4
 
6.6%
4 4
 
6.6%
6 3
 
4.9%
2 3
 
4.9%
Other values (3) 3
 
4.9%

합계
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct51
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25484.431
Minimum-63170
Maximum273511
Zeros0
Zeros (%)0.0%
Negative1
Negative (%)2.0%
Memory size591.0 B
2024-04-21T10:39:40.800681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-63170
5-th percentile24.5
Q1316.5
median1849
Q311621.5
95-th percentile164431
Maximum273511
Range336681
Interquartile range (IQR)11305

Descriptive statistics

Standard deviation59881.475
Coefficient of variation (CV)2.3497277
Kurtosis7.2445232
Mean25484.431
Median Absolute Deviation (MAD)1818
Skewness2.6355476
Sum1299706
Variance3.5857911 × 109
MonotonicityNot monotonic
2024-04-21T10:39:40.914776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
873 1
 
2.0%
785 1
 
2.0%
1849 1
 
2.0%
216 1
 
2.0%
582 1
 
2.0%
8302 1
 
2.0%
1460 1
 
2.0%
6372 1
 
2.0%
252 1
 
2.0%
218 1
 
2.0%
Other values (41) 41
80.4%
ValueCountFrequency (%)
-63170 1
2.0%
16 1
2.0%
20 1
2.0%
29 1
2.0%
31 1
2.0%
59 1
2.0%
159 1
2.0%
178 1
2.0%
179 1
2.0%
216 1
2.0%
ValueCountFrequency (%)
273511 1
2.0%
213323 1
2.0%
172940 1
2.0%
155922 1
2.0%
115062 1
2.0%
88216 1
2.0%
67264 1
2.0%
49273 1
2.0%
48047 1
2.0%
39239 1
2.0%

본 인
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct35
Distinct (%)68.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16771.314
Minimum-36649
Maximum213323
Zeros16
Zeros (%)31.4%
Negative1
Negative (%)2.0%
Memory size591.0 B
2024-04-21T10:39:41.034618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-36649
5-th percentile0
Q10
median266
Q33359.5
95-th percentile109927.5
Maximum213323
Range249972
Interquartile range (IQR)3359.5

Descriptive statistics

Standard deviation44306.785
Coefficient of variation (CV)2.6418196
Kurtosis10.016059
Mean16771.314
Median Absolute Deviation (MAD)266
Skewness3.0806567
Sum855337
Variance1.9630912 × 109
MonotonicityNot monotonic
2024-04-21T10:39:41.137190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
0 16
31.4%
3279 2
 
3.9%
6044 1
 
2.0%
201 1
 
2.0%
213323 1
 
2.0%
39239 1
 
2.0%
172940 1
 
2.0%
1144 1
 
2.0%
49273 1
 
2.0%
178 1
 
2.0%
Other values (25) 25
49.0%
ValueCountFrequency (%)
-36649 1
 
2.0%
0 16
31.4%
1 1
 
2.0%
4 1
 
2.0%
5 1
 
2.0%
7 1
 
2.0%
19 1
 
2.0%
139 1
 
2.0%
178 1
 
2.0%
201 1
 
2.0%
ValueCountFrequency (%)
213323 1
2.0%
172940 1
2.0%
115062 1
2.0%
104793 1
2.0%
55600 1
2.0%
49273 1
2.0%
49193 1
2.0%
41724 1
2.0%
39239 1
2.0%
12983 1
2.0%

유 족
Real number (ℝ)

ZEROS 

Distinct45
Distinct (%)88.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8713.1176
Minimum-26521
Maximum168718
Zeros7
Zeros (%)13.7%
Negative1
Negative (%)2.0%
Memory size591.0 B
2024-04-21T10:39:41.249654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-26521
5-th percentile0
Q145
median349
Q32478
95-th percentile55209.5
Maximum168718
Range195239
Interquartile range (IQR)2433

Descriptive statistics

Standard deviation29384.146
Coefficient of variation (CV)3.3724032
Kurtosis19.427797
Mean8713.1176
Median Absolute Deviation (MAD)349
Skewness4.1953149
Sum444369
Variance8.6342805 × 108
MonotonicityNot monotonic
2024-04-21T10:39:41.380510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
0 7
 
13.7%
873 1
 
2.0%
252 1
 
2.0%
349 1
 
2.0%
591 1
 
2.0%
179 1
 
2.0%
109 1
 
2.0%
216 1
 
2.0%
87 1
 
2.0%
2258 1
 
2.0%
Other values (35) 35
68.6%
ValueCountFrequency (%)
-26521 1
 
2.0%
0 7
13.7%
16 1
 
2.0%
17 1
 
2.0%
20 1
 
2.0%
29 1
 
2.0%
31 1
 
2.0%
59 1
 
2.0%
87 1
 
2.0%
109 1
 
2.0%
ValueCountFrequency (%)
168718 1
2.0%
100322 1
2.0%
75233 1
2.0%
35186 1
2.0%
18071 1
2.0%
15139 1
2.0%
11331 1
2.0%
8633 1
2.0%
8001 1
2.0%
6323 1
2.0%

Interactions

2024-04-21T10:39:39.251900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:38.311720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:38.654340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:38.952226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:39.326562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:38.437081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:38.722395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:39.026376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:39.402806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:38.511567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:38.792464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:39.108150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:39.477612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:38.577300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:38.867668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:39:39.175469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T10:39:41.486731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순서대상구분합계본 인유 족
순서1.0000.7700.4380.3940.564
대상구분0.7701.0000.9941.0001.000
합계0.4380.9941.0001.0000.926
본 인0.3941.0001.0001.0000.804
유 족0.5641.0000.9260.8041.000
2024-04-21T10:39:41.583048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순서합계본 인유 족
순서1.0000.0110.344-0.458
합계0.0111.0000.7580.479
본 인0.3440.7581.0000.087
유 족-0.4580.4790.0871.000

Missing values

2024-04-21T10:39:39.598282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T10:39:39.688401image/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

기준일순서대상구분합계본 인유 족
02024-03-311[순국선열]8730873
12024-03-312건국훈장7850785
22024-03-313건국포장29029
32024-03-314대통령표창59059
42024-03-315[애국지사]800658001
52024-03-316건국훈장449344489
62024-03-317건국포장7860786
72024-03-318대통령표창272712726
82024-03-319[전몰·전상·순직·공상군경]273511104793168718
92024-03-3110전몰군경35186035186
기준일순서대상구분합계본 인유 족
412024-03-3142고엽제후유증2세1781780
422024-03-3143[5·18민주유공자]447834401038
432024-03-31445·18사망자 또는 행불자1590159
442024-03-31455·18부상자27652116649
452024-03-31465·18희생자15541324230
462024-03-3147[특수임무유공자]389928461053
472024-03-3148특수임무사망자 또는 행불자20020
482024-03-3149특수임무부상자12961131165
492024-03-3150특수임무공로자25831715868
502024-03-3151중·장기복무제대군인1150621150620