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

Description전라남도 시군구별 보훈대상자 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/15098584/fileData.do

Alerts

기준년월 has constant value ""Constant
지역명 has constant value ""Constant
합계 is highly overall correlated with 본인 and 1 other fieldsHigh correlation
본인 is highly overall correlated with 합계High correlation
유족 is highly overall correlated with 합계High correlation
순서 has unique valuesUnique
합계 has 3 (5.9%) zerosZeros
본인 has 20 (39.2%) zerosZeros
유족 has 10 (19.6%) zerosZeros

Reproduction

Analysis started2024-03-14 18:30:18.376468
Analysis finished2024-03-14 18:30:22.668420
Duration4.29 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
2024-03-15T03:30:22.764780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:30:22.923459image/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
전라남도
51 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전라남도 51
100.0%

Length

2024-03-15T03:30:23.254004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T03:30:23.552075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라남도 51
100.0%

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 size587.0 B
2024-03-15T03:30:23.894818image/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
2024-03-15T03:30:24.236191image/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
2024-03-15T03:30:25.095194image/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%
2024-03-15T03:30:26.406382image/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 

Distinct45
Distinct (%)88.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1219.9216
Minimum0
Maximum13168
Zeros3
Zeros (%)5.9%
Negative0
Negative (%)0.0%
Memory size587.0 B
2024-03-15T03:30:26.816029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.5
Q110.5
median87
Q3759
95-th percentile7560
Maximum13168
Range13168
Interquartile range (IQR)748.5

Descriptive statistics

Standard deviation2653.1276
Coefficient of variation (CV)2.1748346
Kurtosis9.5463128
Mean1219.9216
Median Absolute Deviation (MAD)86
Skewness3.027243
Sum62216
Variance7039086.3
MonotonicityNot monotonic
2024-03-15T03:30:27.266454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
2 3
 
5.9%
10 3
 
5.9%
0 3
 
5.9%
26 1
 
2.0%
7471 1
 
2.0%
41 1
 
2.0%
328 1
 
2.0%
73 1
 
2.0%
230 1
 
2.0%
15 1
 
2.0%
Other values (35) 35
68.6%
ValueCountFrequency (%)
0 3
5.9%
1 1
 
2.0%
2 3
5.9%
3 1
 
2.0%
6 1
 
2.0%
7 1
 
2.0%
10 3
5.9%
11 1
 
2.0%
15 1
 
2.0%
16 1
 
2.0%
ValueCountFrequency (%)
13168 1
2.0%
9296 1
2.0%
7649 1
2.0%
7471 1
2.0%
3165 1
2.0%
3031 1
2.0%
3028 1
2.0%
2863 1
2.0%
2797 1
2.0%
1823 1
2.0%

본인
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct30
Distinct (%)58.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean790.98039
Minimum0
Maximum9296
Zeros20
Zeros (%)39.2%
Negative0
Negative (%)0.0%
Memory size587.0 B
2024-03-15T03:30:27.768589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6
Q3286.5
95-th percentile4057.5
Maximum9296
Range9296
Interquartile range (IQR)286.5

Descriptive statistics

Standard deviation1875.9977
Coefficient of variation (CV)2.3717373
Kurtosis10.741555
Mean790.98039
Median Absolute Deviation (MAD)6
Skewness3.1914329
Sum40340
Variance3519367.4
MonotonicityNot monotonic
2024-03-15T03:30:28.250413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0 20
39.2%
1 2
 
3.9%
218 2
 
3.9%
9296 1
 
2.0%
3031 1
 
2.0%
57 1
 
2.0%
41 1
 
2.0%
98 1
 
2.0%
215 1
 
2.0%
355 1
 
2.0%
Other values (20) 20
39.2%
ValueCountFrequency (%)
0 20
39.2%
1 2
 
3.9%
2 1
 
2.0%
4 1
 
2.0%
5 1
 
2.0%
6 1
 
2.0%
8 1
 
2.0%
35 1
 
2.0%
41 1
 
2.0%
57 1
 
2.0%
ValueCountFrequency (%)
9296 1
2.0%
7471 1
2.0%
5084 1
2.0%
3031 1
2.0%
3028 1
2.0%
2855 1
2.0%
2229 1
2.0%
1857 1
2.0%
1823 1
2.0%
803 1
2.0%

유족
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct36
Distinct (%)70.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean428.94118
Minimum0
Maximum8084
Zeros10
Zeros (%)19.6%
Negative0
Negative (%)0.0%
Memory size587.0 B
2024-03-15T03:30:28.772544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median15
Q3108.5
95-th percentile2005
Maximum8084
Range8084
Interquartile range (IQR)106.5

Descriptive statistics

Standard deviation1343.4585
Coefficient of variation (CV)3.1320344
Kurtosis23.215655
Mean428.94118
Median Absolute Deviation (MAD)15
Skewness4.6214862
Sum21876
Variance1804880.8
MonotonicityNot monotonic
2024-03-15T03:30:29.239337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
0 10
 
19.6%
2 3
 
5.9%
1 2
 
3.9%
5 2
 
3.9%
15 2
 
3.9%
3 2
 
3.9%
14 1
 
2.0%
33 1
 
2.0%
97 1
 
2.0%
35 1
 
2.0%
Other values (26) 26
51.0%
ValueCountFrequency (%)
0 10
19.6%
1 2
 
3.9%
2 3
 
5.9%
3 2
 
3.9%
5 2
 
3.9%
6 1
 
2.0%
10 1
 
2.0%
11 1
 
2.0%
12 1
 
2.0%
14 1
 
2.0%
ValueCountFrequency (%)
8084 1
2.0%
4794 1
2.0%
2351 1
2.0%
1659 1
2.0%
1006 1
2.0%
936 1
2.0%
695 1
2.0%
565 1
2.0%
419 1
2.0%
205 1
2.0%

Interactions

2024-03-15T03:30:21.365983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:30:18.617697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:30:19.300943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:30:20.301672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:30:21.516414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:30:18.860091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:30:19.538733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:30:20.536499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:30:21.680836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:30:19.008706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:30:19.786331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:30:20.776367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:30:22.020476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:30:19.143836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:30:20.032290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:30:21.022958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T03:30:29.576587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순서대상구분합계본인유족
순서1.0000.7700.4480.2070.576
대상구분0.7701.0001.0001.0001.000
합계0.4481.0001.0000.9050.814
본인0.2071.0000.9051.0000.794
유족0.5761.0000.8140.7941.000
2024-03-15T03:30:29.813912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순서합계본인유족
순서1.0000.0350.351-0.418
합계0.0351.0000.7370.525
본인0.3510.7371.0000.084
유족-0.4180.5250.0841.000

Missing values

2024-03-15T03:30:22.273766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T03:30:22.590800image/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
02023-12-31전라남도1[순국선열]26026
12023-12-31전라남도2건국훈장21021
22023-12-31전라남도3건국포장202
32023-12-31전라남도4대통령표창303
42023-12-31전라남도5[애국지사]2050205
52023-12-31전라남도6건국훈장87087
62023-12-31전라남도7건국포장22022
72023-12-31전라남도8대통령표창96096
82023-12-31전라남도9[전몰·전상·순직·공상군경]1316850848084
92023-12-31전라남도10전몰군경165901659
기준년월지역명순서대상구분합계본인유족
412023-12-31전라남도42고엽제후유증2세660
422023-12-31전라남도43[5·18민주유공자]735570165
432023-12-31전라남도445·18사망자 또는 행불자35035
442023-12-31전라남도455·18부상자45235597
452023-12-31전라남도465·18희생자24821533
462023-12-31전라남도47[특수임무유공자]1129814
472023-12-31전라남도48특수임무사망자 또는 행불자000
482023-12-31전라남도49특수임무부상자43412
492023-12-31전라남도50특수임무공로자695712
502023-12-31전라남도51중·장기복무제대군인303130310