Overview

Dataset statistics

Number of variables8
Number of observations459
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory30.6 KiB
Average record size in memory68.3 B

Variable types

DateTime1
Categorical3
Numeric4

Dataset

Description대구광역시 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/15098578/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 95 (20.7%) zerosZeros
본인 has 218 (47.5%) zerosZeros
유족 has 195 (42.5%) zerosZeros

Reproduction

Analysis started2024-04-13 13:30:17.143554
Analysis finished2024-04-13 13:30:23.607351
Duration6.46 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년월
Date

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
Minimum2023-12-31 00:00:00
Maximum2023-12-31 00:00:00
2024-04-13T22:30:23.763334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T22:30:24.053979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

지역명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
대구광역시
459 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대구광역시 459
100.0%

Length

2024-04-13T22:30:24.398419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-13T22:30:24.692401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대구광역시 459
100.0%

시군구명
Categorical

Distinct9
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
군위군
51 
남구(대구)
51 
달서구
51 
달성군(대구)
51 
동구(대구)
51 
Other values (4)
204 

Length

Max length7
Median length6
Mean length5.1111111
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
군위군 51
11.1%
남구(대구) 51
11.1%
달서구 51
11.1%
달성군(대구) 51
11.1%
동구(대구) 51
11.1%
북구(대구) 51
11.1%
서구(대구) 51
11.1%
수성구 51
11.1%
중구(대구) 51
11.1%

Length

2024-04-13T22:30:25.038777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-13T22:30:25.412524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
군위군 51
11.1%
남구(대구 51
11.1%
달서구 51
11.1%
달성군(대구 51
11.1%
동구(대구 51
11.1%
북구(대구 51
11.1%
서구(대구 51
11.1%
수성구 51
11.1%
중구(대구 51
11.1%

순서
Real number (ℝ)

HIGH CORRELATION 

Distinct51
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26
Minimum1
Maximum51
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2024-04-13T22:30:25.840453image/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 deviation14.735662
Coefficient of variation (CV)0.56675624
Kurtosis-1.2009217
Mean26
Median Absolute Deviation (MAD)13
Skewness0
Sum11934
Variance217.13974
MonotonicityNot monotonic
2024-04-13T22:30:26.425924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 9
 
2.0%
2 9
 
2.0%
29 9
 
2.0%
30 9
 
2.0%
31 9
 
2.0%
32 9
 
2.0%
33 9
 
2.0%
34 9
 
2.0%
35 9
 
2.0%
36 9
 
2.0%
Other values (41) 369
80.4%
ValueCountFrequency (%)
1 9
2.0%
2 9
2.0%
3 9
2.0%
4 9
2.0%
5 9
2.0%
6 9
2.0%
7 9
2.0%
8 9
2.0%
9 9
2.0%
10 9
2.0%
ValueCountFrequency (%)
51 9
2.0%
50 9
2.0%
49 9
2.0%
48 9
2.0%
47 9
2.0%
46 9
2.0%
45 9
2.0%
44 9
2.0%
43 9
2.0%
42 9
2.0%

대상구분
Categorical

HIGH CORRELATION 

Distinct49
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
건국포장
 
18
대통령표창
 
18
6·18자유상이자
 
9
고엽제후유증
 
9
지원순직군경
 
9
Other values (44)
396 

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 18
 
3.9%
대통령표창 18
 
3.9%
6·18자유상이자 9
 
2.0%
고엽제후유증 9
 
2.0%
지원순직군경 9
 
2.0%
보국수훈자 9
 
2.0%
[애국지사] 9
 
2.0%
건국훈장 9
 
2.0%
[전몰·전상·순직·공상군경] 9
 
2.0%
전몰군경 9
 
2.0%
Other values (39) 351
76.5%

Length

2024-04-13T22:30:26.864123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
건국포장 18
 
3.6%
행불자 18
 
3.6%
또는 18
 
3.6%
건국훈장 18
 
3.6%
대통령표창 18
 
3.6%
5·18부상자 9
 
1.8%
참전유공자 9
 
1.8%
순국선열 9
 
1.8%
6.25및월남전쟁 9
 
1.8%
지원공상공무원 9
 
1.8%
Other values (40) 360
72.7%

합계
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct158
Distinct (%)34.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean161.68845
Minimum0
Maximum3574
Zeros95
Zeros (%)20.7%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2024-04-13T22:30:27.244851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median7
Q373
95-th percentile860.5
Maximum3574
Range3574
Interquartile range (IQR)72

Descriptive statistics

Standard deviation416.70714
Coefficient of variation (CV)2.5772226
Kurtosis21.748303
Mean161.68845
Median Absolute Deviation (MAD)7
Skewness4.2049917
Sum74215
Variance173644.84
MonotonicityNot monotonic
2024-04-13T22:30:27.690100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 95
20.7%
1 42
 
9.2%
2 31
 
6.8%
3 21
 
4.6%
4 15
 
3.3%
7 12
 
2.6%
5 12
 
2.6%
6 9
 
2.0%
24 6
 
1.3%
8 6
 
1.3%
Other values (148) 210
45.8%
ValueCountFrequency (%)
0 95
20.7%
1 42
9.2%
2 31
 
6.8%
3 21
 
4.6%
4 15
 
3.3%
5 12
 
2.6%
6 9
 
2.0%
7 12
 
2.6%
8 6
 
1.3%
9 5
 
1.1%
ValueCountFrequency (%)
3574 1
0.2%
2888 1
0.2%
2773 1
0.2%
2526 1
0.2%
2173 1
0.2%
1814 1
0.2%
1753 1
0.2%
1726 1
0.2%
1574 1
0.2%
1559 1
0.2%

본인
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct120
Distinct (%)26.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean99.026144
Minimum0
Maximum1814
Zeros218
Zeros (%)47.5%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2024-04-13T22:30:28.103095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q325
95-th percentile641.4
Maximum1814
Range1814
Interquartile range (IQR)25

Descriptive statistics

Standard deviation267.24333
Coefficient of variation (CV)2.6987149
Kurtosis15.428974
Mean99.026144
Median Absolute Deviation (MAD)1
Skewness3.7479634
Sum45453
Variance71418.995
MonotonicityNot monotonic
2024-04-13T22:30:28.547779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 218
47.5%
1 30
 
6.5%
3 13
 
2.8%
4 12
 
2.6%
2 12
 
2.6%
5 10
 
2.2%
6 6
 
1.3%
9 6
 
1.3%
14 4
 
0.9%
178 4
 
0.9%
Other values (110) 144
31.4%
ValueCountFrequency (%)
0 218
47.5%
1 30
 
6.5%
2 12
 
2.6%
3 13
 
2.8%
4 12
 
2.6%
5 10
 
2.2%
6 6
 
1.3%
7 2
 
0.4%
8 2
 
0.4%
9 6
 
1.3%
ValueCountFrequency (%)
1814 1
0.2%
1726 1
0.2%
1559 1
0.2%
1510 1
0.2%
1430 1
0.2%
1411 1
0.2%
1364 1
0.2%
1324 1
0.2%
1211 1
0.2%
1176 1
0.2%

유족
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct103
Distinct (%)22.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean62.662309
Minimum0
Maximum2210
Zeros195
Zeros (%)42.5%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2024-04-13T22:30:28.976902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q312
95-th percentile337.4
Maximum2210
Range2210
Interquartile range (IQR)12

Descriptive statistics

Standard deviation227.99192
Coefficient of variation (CV)3.6384219
Kurtosis39.587037
Mean62.662309
Median Absolute Deviation (MAD)1
Skewness5.8475842
Sum28762
Variance51980.316
MonotonicityNot monotonic
2024-04-13T22:30:29.388260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 195
42.5%
1 52
 
11.3%
2 29
 
6.3%
3 16
 
3.5%
4 12
 
2.6%
7 10
 
2.2%
6 9
 
2.0%
5 7
 
1.5%
8 6
 
1.3%
10 3
 
0.7%
Other values (93) 120
26.1%
ValueCountFrequency (%)
0 195
42.5%
1 52
 
11.3%
2 29
 
6.3%
3 16
 
3.5%
4 12
 
2.6%
5 7
 
1.5%
6 9
 
2.0%
7 10
 
2.2%
8 6
 
1.3%
9 1
 
0.2%
ValueCountFrequency (%)
2210 1
0.2%
1810 1
0.2%
1745 1
0.2%
1618 1
0.2%
1364 1
0.2%
1108 1
0.2%
1035 1
0.2%
998 1
0.2%
951 1
0.2%
804 1
0.2%

Interactions

2024-04-13T22:30:21.941652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T22:30:18.870793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T22:30:19.880499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T22:30:20.914755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T22:30:22.184975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T22:30:19.124629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T22:30:20.134846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T22:30:21.167082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T22:30:22.439560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T22:30:19.385282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T22:30:20.404351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T22:30:21.433225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T22:30:22.693591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T22:30:19.641679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T22:30:20.669538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T22:30:21.697716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-13T22:30:29.643481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구명순서대상구분합계본인유족
시군구명1.0000.0000.0000.0430.0000.000
순서0.0001.0000.9980.5100.5590.474
대상구분0.0000.9981.0000.6740.7390.659
합계0.0430.5100.6741.0000.9500.980
본인0.0000.5590.7390.9501.0000.858
유족0.0000.4740.6590.9800.8581.000
2024-04-13T22:30:29.902149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구명대상구분
시군구명1.0000.000
대상구분0.0001.000
2024-04-13T22:30:30.146939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순서합계본인유족시군구명대상구분
순서1.000-0.0810.268-0.4950.0000.934
합계-0.0811.0000.7430.6010.0180.286
본인0.2680.7431.0000.1400.0000.338
유족-0.4950.6010.1401.0000.0000.275
시군구명0.0000.0180.0000.0001.0000.000
대상구분0.9340.2860.3380.2750.0001.000

Missing values

2024-04-13T22:30:23.023506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-13T22:30:23.435736image/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
02023-12-31대구광역시군위군1[순국선열]000
12023-12-31대구광역시군위군2건국훈장000
22023-12-31대구광역시군위군3건국포장000
32023-12-31대구광역시군위군4대통령표창000
42023-12-31대구광역시군위군5[애국지사]404
52023-12-31대구광역시군위군6건국훈장303
62023-12-31대구광역시군위군7건국포장000
72023-12-31대구광역시군위군8대통령표창101
82023-12-31대구광역시군위군9[전몰·전상·순직·공상군경]355130225
92023-12-31대구광역시군위군10전몰군경46046
기준년월지역명시군구명순서대상구분합계본인유족
4492023-12-31대구광역시중구(대구)42고엽제후유증2세330
4502023-12-31대구광역시중구(대구)43[5·18민주유공자]211
4512023-12-31대구광역시중구(대구)445·18사망자 또는 행불자000
4522023-12-31대구광역시중구(대구)455·18부상자110
4532023-12-31대구광역시중구(대구)465·18희생자101
4542023-12-31대구광역시중구(대구)47[특수임무유공자]642
4552023-12-31대구광역시중구(대구)48특수임무사망자 또는 행불자000
4562023-12-31대구광역시중구(대구)49특수임무부상자431
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