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

Description서울특별시 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/15098572/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
본인 has 16 (31.4%) zerosZeros
유족 has 8 (15.7%) zerosZeros

Reproduction

Analysis started2024-03-14 23:23:56.062193
Analysis finished2024-03-14 23:24:01.198948
Duration5.14 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
2024-03-15T08:24:01.348352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:24:01.649376image/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
서울특별시
51 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서울특별시 51
100.0%

Length

2024-03-15T08:24:02.004827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T08:24:02.299512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 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
2024-03-15T08:24:02.640937image/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
2024-03-15T08:24:03.122708image/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
2024-03-15T08:24:04.096451image/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%
2024-03-15T08:24:05.284606image/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 

Distinct47
Distinct (%)92.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4655.2745
Minimum2
Maximum41876
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size587.0 B
2024-03-15T08:24:05.703386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile10.5
Q171
median359
Q32363
95-th percentile27753
Maximum41876
Range41874
Interquartile range (IQR)2292

Descriptive statistics

Standard deviation9820.4795
Coefficient of variation (CV)2.1095382
Kurtosis7.1371675
Mean4655.2745
Median Absolute Deviation (MAD)344
Skewness2.7349713
Sum237419
Variance96441818
MonotonicityNot monotonic
2024-03-15T08:24:06.213849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
11 3
 
5.9%
29 2
 
3.9%
51 2
 
3.9%
229 1
 
2.0%
359 1
 
2.0%
31 1
 
2.0%
1338 1
 
2.0%
214 1
 
2.0%
1080 1
 
2.0%
15 1
 
2.0%
Other values (37) 37
72.5%
ValueCountFrequency (%)
2 1
 
2.0%
8 1
 
2.0%
10 1
 
2.0%
11 3
5.9%
15 1
 
2.0%
28 1
 
2.0%
29 2
3.9%
31 1
 
2.0%
51 2
3.9%
91 1
 
2.0%
ValueCountFrequency (%)
41876 1
2.0%
40056 1
2.0%
32471 1
2.0%
23035 1
2.0%
17281 1
2.0%
15750 1
2.0%
10422 1
2.0%
10382 1
2.0%
7702 1
2.0%
7226 1
2.0%

본인
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct33
Distinct (%)64.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3073.1373
Minimum0
Maximum40056
Zeros16
Zeros (%)31.4%
Negative0
Negative (%)0.0%
Memory size587.0 B
2024-03-15T08:24:06.609345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median124
Q3744.5
95-th percentile16198
Maximum40056
Range40056
Interquartile range (IQR)744.5

Descriptive statistics

Standard deviation7784.5938
Coefficient of variation (CV)2.5331097
Kurtosis13.285537
Mean3073.1373
Median Absolute Deviation (MAD)124
Skewness3.5299554
Sum156730
Variance60599901
MonotonicityNot monotonic
2024-03-15T08:24:06.981271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
0 16
31.4%
1 3
 
5.9%
332 2
 
3.9%
29 1
 
2.0%
40056 1
 
2.0%
7226 1
 
2.0%
32471 1
 
2.0%
359 1
 
2.0%
7147 1
 
2.0%
476 1
 
2.0%
Other values (23) 23
45.1%
ValueCountFrequency (%)
0 16
31.4%
1 3
 
5.9%
2 1
 
2.0%
8 1
 
2.0%
15 1
 
2.0%
29 1
 
2.0%
37 1
 
2.0%
44 1
 
2.0%
124 1
 
2.0%
135 1
 
2.0%
ValueCountFrequency (%)
40056 1
2.0%
32471 1
2.0%
16646 1
2.0%
15750 1
2.0%
8923 1
2.0%
7723 1
2.0%
7226 1
2.0%
7147 1
2.0%
6208 1
2.0%
5927 1
2.0%

유족
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct39
Distinct (%)76.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1582.1373
Minimum0
Maximum25230
Zeros8
Zeros (%)15.7%
Negative0
Negative (%)0.0%
Memory size587.0 B
2024-03-15T08:24:07.584792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q111
median78
Q3458.5
95-th percentile9988
Maximum25230
Range25230
Interquartile range (IQR)447.5

Descriptive statistics

Standard deviation4467.756
Coefficient of variation (CV)2.8238738
Kurtosis17.476981
Mean1582.1373
Median Absolute Deviation (MAD)78
Skewness4.0331793
Sum80689
Variance19960844
MonotonicityNot monotonic
2024-03-15T08:24:07.979120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
0 8
 
15.7%
29 3
 
5.9%
11 3
 
5.9%
78 2
 
3.9%
214 1
 
2.0%
83 1
 
2.0%
28 1
 
2.0%
12 1
 
2.0%
31 1
 
2.0%
7 1
 
2.0%
Other values (29) 29
56.9%
ValueCountFrequency (%)
0 8
15.7%
2 1
 
2.0%
7 1
 
2.0%
8 1
 
2.0%
10 1
 
2.0%
11 3
 
5.9%
12 1
 
2.0%
28 1
 
2.0%
29 3
 
5.9%
31 1
 
2.0%
ValueCountFrequency (%)
25230 1
2.0%
14417 1
2.0%
14112 1
2.0%
5864 1
2.0%
4495 1
2.0%
2659 1
2.0%
2595 1
2.0%
1970 1
2.0%
1799 1
2.0%
1494 1
2.0%

Interactions

2024-03-15T08:23:59.535762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:23:56.438335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:23:57.306276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:23:58.400120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:23:59.773968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:23:56.652302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:23:57.616257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:23:58.718932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:24:00.011807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:23:56.793936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:23:57.859412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:23:59.009831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:24:00.275911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:23:57.062838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:23:58.129493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:23:59.286303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T08:24:08.241909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순서대상구분합계본인유족
순서1.0000.7700.4710.3710.794
대상구분0.7701.0001.0001.0001.000
합계0.4711.0001.0000.9530.844
본인0.3711.0000.9531.0000.738
유족0.7941.0000.8440.7381.000
2024-03-15T08:24:08.468080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순서합계본인유족
순서1.000-0.1010.292-0.603
합계-0.1011.0000.7500.466
본인0.2920.7501.0000.035
유족-0.6030.4660.0351.000

Missing values

2024-03-15T08:24:00.664267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T08:24:01.047780image/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
02023-12-31서울특별시1[순국선열]2290229
12023-12-31서울특별시2건국훈장2070207
22023-12-31서울특별시3건국포장11011
32023-12-31서울특별시4대통령표창11011
42023-12-31서울특별시5[애국지사]197221970
52023-12-31서울특별시6건국훈장120311202
62023-12-31서울특별시7건국포장2000200
72023-12-31서울특별시8대통령표창5691568
82023-12-31서울특별시9[전몰·전상·순직·공상군경]418761664625230
92023-12-31서울특별시10전몰군경586405864
기준년월지역명순서대상구분합계본인유족
412023-12-31서울특별시42고엽제후유증2세29290
422023-12-31서울특별시43[5·18민주유공자]57147695
432023-12-31서울특별시445·18사망자 또는 행불자808
442023-12-31서울특별시455·18부상자28923158
452023-12-31서울특별시465·18희생자27424529
462023-12-31서울특별시47[특수임무유공자]566389177
472023-12-31서울특별시48특수임무사망자 또는 행불자202
482023-12-31서울특별시49특수임무부상자16413529
492023-12-31서울특별시50특수임무공로자400254146
502023-12-31서울특별시51중·장기복무제대군인15750157500