Overview

Dataset statistics

Number of variables5
Number of observations30
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 KiB
Average record size in memory46.4 B

Variable types

DateTime1
Numeric2
Categorical2

Dataset

Description국가보훈부에서 제공하는 재가복지서비스의 지원을 받는 대상자 현황 자료 ※ 보훈재가복지서비스란? ‘재가복지’란 각 가정에 방문하여 제공하는 복지 서비스를 뜻하는 말로, 요양시설 등에서 이루어지는 ‘시설복지’와 구분되는 개념이다. 국가보훈처에서 실시하는 ‘보훈재가복지서비스’는 생활이 어려운 독거·노인부부세대 중 거동이 불편한 사람을 대상으로 하는 찾아가는 복지서비스이다. 전문 인력인 ‘보훈섬김이’가 각 가정으로 찾아가 가사활동, 건강관리, 편의지원 등을 제공한다.
URLhttps://www.data.go.kr/data/15072656/fileData.do

Alerts

기준년월 has constant value ""Constant
순서 is highly overall correlated with 관리지방청High correlation
관리지방청 is highly overall correlated with 순서High correlation
순서 has unique valuesUnique
인원수 has 1 (3.3%) zerosZeros

Reproduction

Analysis started2023-12-12 21:52:01.363650
Analysis finished2023-12-12 21:52:02.143698
Duration0.78 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년월
Date

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2023-06-30 00:00:00
Maximum2023-06-30 00:00:00
2023-12-13T06:52:02.225972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:52:02.381008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

순서
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.5
Minimum1
Maximum30
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-13T06:52:02.569604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.45
Q18.25
median15.5
Q322.75
95-th percentile28.55
Maximum30
Range29
Interquartile range (IQR)14.5

Descriptive statistics

Standard deviation8.8034084
Coefficient of variation (CV)0.56796183
Kurtosis-1.2
Mean15.5
Median Absolute Deviation (MAD)7.5
Skewness0
Sum465
Variance77.5
MonotonicityStrictly increasing
2023-12-13T06:52:02.803900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
1 1
 
3.3%
17 1
 
3.3%
30 1
 
3.3%
29 1
 
3.3%
28 1
 
3.3%
27 1
 
3.3%
26 1
 
3.3%
25 1
 
3.3%
24 1
 
3.3%
23 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
1 1
3.3%
2 1
3.3%
3 1
3.3%
4 1
3.3%
5 1
3.3%
6 1
3.3%
7 1
3.3%
8 1
3.3%
9 1
3.3%
10 1
3.3%
ValueCountFrequency (%)
30 1
3.3%
29 1
3.3%
28 1
3.3%
27 1
3.3%
26 1
3.3%
25 1
3.3%
24 1
3.3%
23 1
3.3%
22 1
3.3%
21 1
3.3%

관리지방청
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
서울지방보훈청
5 
대전지방보훈청
5 
대구지방보훈청
5 
부산지방보훈청
5 
광주지방보훈청
5 

Length

Max length10
Median length7
Mean length7.5
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서울지방보훈청 5
16.7%
대전지방보훈청 5
16.7%
대구지방보훈청 5
16.7%
부산지방보훈청 5
16.7%
광주지방보훈청 5
16.7%
제주특별자치도보훈청 5
16.7%

Length

2023-12-13T06:52:03.021343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:52:03.193978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울지방보훈청 5
16.7%
대전지방보훈청 5
16.7%
대구지방보훈청 5
16.7%
부산지방보훈청 5
16.7%
광주지방보훈청 5
16.7%
제주특별자치도보훈청 5
16.7%

지원대상인력
Categorical

Distinct5
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
본인
6 
배우자
6 
부모
6 
자녀
6 
기타
6 

Length

Max length3
Median length2
Mean length2.2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row본인
2nd row배우자
3rd row부모
4th row자녀
5th row기타

Common Values

ValueCountFrequency (%)
본인 6
20.0%
배우자 6
20.0%
부모 6
20.0%
자녀 6
20.0%
기타 6
20.0%

Length

2023-12-13T06:52:03.377096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:52:03.503656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
본인 6
20.0%
배우자 6
20.0%
부모 6
20.0%
자녀 6
20.0%
기타 6
20.0%

인원수
Real number (ℝ)

ZEROS 

Distinct28
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean313.7
Minimum0
Maximum1850
Zeros1
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-13T06:52:03.629247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.25
Q117.25
median55.5
Q3653
95-th percentile1025.35
Maximum1850
Range1850
Interquartile range (IQR)635.75

Descriptive statistics

Standard deviation455.13281
Coefficient of variation (CV)1.4508537
Kurtosis3.0778437
Mean313.7
Median Absolute Deviation (MAD)48.5
Skewness1.7182239
Sum9411
Variance207145.87
MonotonicityNot monotonic
2023-12-13T06:52:03.754184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
33 2
 
6.7%
6 2
 
6.7%
1850 1
 
3.3%
748 1
 
3.3%
1 1
 
3.3%
0 1
 
3.3%
52 1
 
3.3%
65 1
 
3.3%
61 1
 
3.3%
11 1
 
3.3%
Other values (18) 18
60.0%
ValueCountFrequency (%)
0 1
3.3%
1 1
3.3%
6 2
6.7%
8 1
3.3%
11 1
3.3%
15 1
3.3%
17 1
3.3%
18 1
3.3%
20 1
3.3%
33 2
6.7%
ValueCountFrequency (%)
1850 1
3.3%
1159 1
3.3%
862 1
3.3%
797 1
3.3%
795 1
3.3%
748 1
3.3%
672 1
3.3%
655 1
3.3%
647 1
3.3%
530 1
3.3%

Interactions

2023-12-13T06:52:01.666274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:52:01.494136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:52:01.760346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:52:01.571189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:52:04.183395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순서관리지방청지원대상인력인원수
순서1.0000.9350.0000.517
관리지방청0.9351.0000.0000.538
지원대상인력0.0000.0001.0000.455
인원수0.5170.5380.4551.000
2023-12-13T06:52:04.285110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지원대상인력관리지방청
지원대상인력1.0000.000
관리지방청0.0001.000
2023-12-13T06:52:04.371166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순서인원수관리지방청지원대상인력
순서1.000-0.3960.7590.000
인원수-0.3961.0000.2030.313
관리지방청0.7590.2031.0000.000
지원대상인력0.0000.3130.0001.000

Missing values

2023-12-13T06:52:01.913774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:52:02.074887image/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

기준년월순서관리지방청지원대상인력인원수
02023-06-301서울지방보훈청본인1850
12023-06-302서울지방보훈청배우자1159
22023-06-303서울지방보훈청부모46
32023-06-304서울지방보훈청자녀18
42023-06-305서울지방보훈청기타131
52023-06-306대전지방보훈청본인672
62023-06-307대전지방보훈청배우자530
72023-06-308대전지방보훈청부모33
82023-06-309대전지방보훈청자녀6
92023-06-3010대전지방보훈청기타67
기준년월순서관리지방청지원대상인력인원수
202023-06-3021광주지방보훈청본인862
212023-06-3022광주지방보훈청배우자795
222023-06-3023광주지방보훈청부모33
232023-06-3024광주지방보훈청자녀11
242023-06-3025광주지방보훈청기타61
252023-06-3026제주특별자치도보훈청본인65
262023-06-3027제주특별자치도보훈청배우자52
272023-06-3028제주특별자치도보훈청부모0
282023-06-3029제주특별자치도보훈청자녀1
292023-06-3030제주특별자치도보훈청기타6