Overview

Dataset statistics

Number of variables8
Number of observations255
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory17.1 KiB
Average record size in memory68.5 B

Variable types

DateTime1
Categorical3
Numeric4

Dataset

Description대전광역시 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/15098579/fileData.do

Alerts

기준년월 has constant value ""Constant
지역명 has constant value ""Constant
순서 is highly overall correlated with 대상구분High correlation
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
대상구분 is highly overall correlated with 순서High correlation
합계 has 38 (14.9%) zerosZeros
본인 has 113 (44.3%) zerosZeros
유족 has 95 (37.3%) zerosZeros

Reproduction

Analysis started2024-03-16 04:12:26.744931
Analysis finished2024-03-16 04:12:30.832082
Duration4.09 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년월
Date

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
Minimum2023-12-31 00:00:00
Maximum2023-12-31 00:00:00
2024-03-16T13:12:30.901039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:31.031435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

지역명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
대전광역시
255 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대전광역시 255
100.0%

Length

2024-03-16T13:12:31.200300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T13:12:31.329198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대전광역시 255
100.0%

시군구명
Categorical

Distinct5
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
대덕구
51 
동구(대전)
51 
서구(대전)
51 
유성구
51 
중구(대전)
51 

Length

Max length6
Median length6
Mean length4.8
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대덕구 51
20.0%
동구(대전) 51
20.0%
서구(대전) 51
20.0%
유성구 51
20.0%
중구(대전) 51
20.0%

Length

2024-03-16T13:12:31.525254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T13:12:31.753574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대덕구 51
20.0%
동구(대전 51
20.0%
서구(대전 51
20.0%
유성구 51
20.0%
중구(대전 51
20.0%

순서
Real number (ℝ)

HIGH CORRELATION 

Distinct51
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26
Minimum1
Maximum51
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2024-03-16T13:12:32.009215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q113
median26
Q339
95-th percentile49
Maximum51
Range50
Interquartile range (IQR)26

Descriptive statistics

Standard deviation14.748549
Coefficient of variation (CV)0.56725187
Kurtosis-1.2009038
Mean26
Median Absolute Deviation (MAD)13
Skewness0
Sum6630
Variance217.51969
MonotonicityNot monotonic
2024-03-16T13:12:32.335430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 5
 
2.0%
2 5
 
2.0%
29 5
 
2.0%
30 5
 
2.0%
31 5
 
2.0%
32 5
 
2.0%
33 5
 
2.0%
34 5
 
2.0%
35 5
 
2.0%
36 5
 
2.0%
Other values (41) 205
80.4%
ValueCountFrequency (%)
1 5
2.0%
2 5
2.0%
3 5
2.0%
4 5
2.0%
5 5
2.0%
6 5
2.0%
7 5
2.0%
8 5
2.0%
9 5
2.0%
10 5
2.0%
ValueCountFrequency (%)
51 5
2.0%
50 5
2.0%
49 5
2.0%
48 5
2.0%
47 5
2.0%
46 5
2.0%
45 5
2.0%
44 5
2.0%
43 5
2.0%
42 5
2.0%

대상구분
Categorical

HIGH CORRELATION 

Distinct49
Distinct (%)19.2%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
건국포장
 
10
대통령표창
 
10
6·18자유상이자
 
5
고엽제후유증
 
5
지원순직군경
 
5
Other values (44)
220 

Length

Max length15
Median length11
Mean length7
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row[순국선열]
2nd row건국훈장
3rd row건국포장
4th row대통령표창
5th row[애국지사]

Common Values

ValueCountFrequency (%)
건국포장 10
 
3.9%
대통령표창 10
 
3.9%
6·18자유상이자 5
 
2.0%
고엽제후유증 5
 
2.0%
지원순직군경 5
 
2.0%
보국수훈자 5
 
2.0%
[애국지사] 5
 
2.0%
건국훈장 5
 
2.0%
[전몰·전상·순직·공상군경] 5
 
2.0%
전몰군경 5
 
2.0%
Other values (39) 195
76.5%

Length

2024-03-16T13:12:32.561779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
건국포장 10
 
3.6%
행불자 10
 
3.6%
또는 10
 
3.6%
건국훈장 10
 
3.6%
대통령표창 10
 
3.6%
5·18부상자 5
 
1.8%
참전유공자 5
 
1.8%
순국선열 5
 
1.8%
6.25및월남전쟁 5
 
1.8%
지원공상공무원 5
 
1.8%
Other values (40) 200
72.7%

합계
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct106
Distinct (%)41.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean158.49412
Minimum0
Maximum2212
Zeros38
Zeros (%)14.9%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2024-03-16T13:12:32.879909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median8
Q3119
95-th percentile864.2
Maximum2212
Range2212
Interquartile range (IQR)117

Descriptive statistics

Standard deviation346.95074
Coefficient of variation (CV)2.1890449
Kurtosis10.714106
Mean158.49412
Median Absolute Deviation (MAD)8
Skewness3.1205421
Sum40416
Variance120374.82
MonotonicityNot monotonic
2024-03-16T13:12:33.112836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 38
 
14.9%
2 27
 
10.6%
1 17
 
6.7%
3 11
 
4.3%
5 9
 
3.5%
4 9
 
3.5%
6 8
 
3.1%
7 6
 
2.4%
11 5
 
2.0%
16 3
 
1.2%
Other values (96) 122
47.8%
ValueCountFrequency (%)
0 38
14.9%
1 17
6.7%
2 27
10.6%
3 11
 
4.3%
4 9
 
3.5%
5 9
 
3.5%
6 8
 
3.1%
7 6
 
2.4%
8 3
 
1.2%
9 2
 
0.8%
ValueCountFrequency (%)
2212 1
0.4%
1887 1
0.4%
1660 1
0.4%
1546 1
0.4%
1500 1
0.4%
1411 1
0.4%
1324 1
0.4%
1293 1
0.4%
1141 1
0.4%
1078 1
0.4%

본인
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct79
Distinct (%)31.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean105.69804
Minimum0
Maximum1887
Zeros113
Zeros (%)44.3%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2024-03-16T13:12:33.312243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q335
95-th percentile647.9
Maximum1887
Range1887
Interquartile range (IQR)35

Descriptive statistics

Standard deviation271.60221
Coefficient of variation (CV)2.569605
Kurtosis16.292224
Mean105.69804
Median Absolute Deviation (MAD)2
Skewness3.7603515
Sum26953
Variance73767.763
MonotonicityNot monotonic
2024-03-16T13:12:33.529824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 113
44.3%
2 16
 
6.3%
1 8
 
3.1%
4 8
 
3.1%
6 6
 
2.4%
7 6
 
2.4%
3 6
 
2.4%
19 3
 
1.2%
13 3
 
1.2%
5 3
 
1.2%
Other values (69) 83
32.5%
ValueCountFrequency (%)
0 113
44.3%
1 8
 
3.1%
2 16
 
6.3%
3 6
 
2.4%
4 8
 
3.1%
5 3
 
1.2%
6 6
 
2.4%
7 6
 
2.4%
9 3
 
1.2%
10 1
 
0.4%
ValueCountFrequency (%)
1887 1
0.4%
1660 1
0.4%
1546 1
0.4%
1293 1
0.4%
1078 1
0.4%
1064 1
0.4%
937 1
0.4%
867 1
0.4%
863 1
0.4%
825 1
0.4%

유족
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct67
Distinct (%)26.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean52.796078
Minimum0
Maximum1275
Zeros95
Zeros (%)37.3%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2024-03-16T13:12:33.736198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q316.5
95-th percentile322.7
Maximum1275
Range1275
Interquartile range (IQR)16.5

Descriptive statistics

Standard deviation154.46429
Coefficient of variation (CV)2.9256774
Kurtosis24.990287
Mean52.796078
Median Absolute Deviation (MAD)2
Skewness4.6254403
Sum13463
Variance23859.218
MonotonicityNot monotonic
2024-03-16T13:12:33.976155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 95
37.3%
2 26
 
10.2%
1 22
 
8.6%
3 16
 
6.3%
4 6
 
2.4%
5 6
 
2.4%
16 4
 
1.6%
11 3
 
1.2%
76 3
 
1.2%
17 3
 
1.2%
Other values (57) 71
27.8%
ValueCountFrequency (%)
0 95
37.3%
1 22
 
8.6%
2 26
 
10.2%
3 16
 
6.3%
4 6
 
2.4%
5 6
 
2.4%
6 2
 
0.8%
7 2
 
0.8%
8 1
 
0.4%
9 1
 
0.4%
ValueCountFrequency (%)
1275 1
0.4%
880 1
0.4%
879 1
0.4%
814 1
0.4%
696 1
0.4%
598 1
0.4%
524 1
0.4%
491 1
0.4%
482 1
0.4%
481 1
0.4%

Interactions

2024-03-16T13:12:29.927129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:27.451453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:28.339586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:29.130081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:30.047128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:27.593516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:28.770546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:29.299291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:30.203060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:27.765951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:28.882302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:29.543293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:30.359546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:28.042015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:29.001435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:29.797955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-16T13:12:34.242506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구명순서대상구분합계본인유족
시군구명1.0000.0000.0000.0000.0000.000
순서0.0001.0000.9980.6350.4570.483
대상구분0.0000.9981.0000.7860.7790.819
합계0.0000.6350.7861.0000.9010.827
본인0.0000.4570.7790.9011.0000.543
유족0.0000.4830.8190.8270.5431.000
2024-03-16T13:12:34.470317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대상구분시군구명
대상구분1.0000.000
시군구명0.0001.000
2024-03-16T13:12:34.671560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순서합계본인유족시군구명대상구분
순서1.000-0.0590.312-0.4980.0000.894
합계-0.0591.0000.7450.5730.0000.368
본인0.3120.7451.0000.1150.0000.377
유족-0.4980.5730.1151.0000.0000.436
시군구명0.0000.0000.0000.0001.0000.000
대상구분0.8940.3680.3770.4360.0001.000

Missing values

2024-03-16T13:12:30.576620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-16T13:12:30.762937image/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

기준년월지역명시군구명순서대상구분합계본인유족
02023-12-31대전광역시대덕구1[순국선열]202
12023-12-31대전광역시대덕구2건국훈장202
22023-12-31대전광역시대덕구3건국포장000
32023-12-31대전광역시대덕구4대통령표창000
42023-12-31대전광역시대덕구5[애국지사]18018
52023-12-31대전광역시대덕구6건국훈장13013
62023-12-31대전광역시대덕구7건국포장202
72023-12-31대전광역시대덕구8대통령표창303
82023-12-31대전광역시대덕구9[전몰·전상·순직·공상군경]1023425598
92023-12-31대전광역시대덕구10전몰군경1160116
기준년월지역명시군구명순서대상구분합계본인유족
2452023-12-31대전광역시중구(대전)42고엽제후유증2세220
2462023-12-31대전광역시중구(대전)43[5·18민주유공자]633
2472023-12-31대전광역시중구(대전)445·18사망자 또는 행불자000
2482023-12-31대전광역시중구(대전)455·18부상자532
2492023-12-31대전광역시중구(대전)465·18희생자101
2502023-12-31대전광역시중구(대전)47[특수임무유공자]1174
2512023-12-31대전광역시중구(대전)48특수임무사망자 또는 행불자000
2522023-12-31대전광역시중구(대전)49특수임무부상자651
2532023-12-31대전광역시중구(대전)50특수임무공로자523
2542023-12-31대전광역시중구(대전)51중·장기복무제대군인5675670