Overview

Dataset statistics

Number of variables4
Number of observations36
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 KiB
Average record size in memory38.7 B

Variable types

Numeric3
Categorical1

Dataset

Description한국보훈복지의료공단 대구보훈병원 2011년부터 2022년까지 년도별 국가유공자의 진료인원을 국비/감변별로 자연인원과 연인원을 제공합니다.
URLhttps://www.data.go.kr/data/15067088/fileData.do

Alerts

연인원 is highly overall correlated with 구분High correlation
구분 is highly overall correlated with 연인원High correlation
자연인 has unique valuesUnique
연인원 has unique valuesUnique

Reproduction

Analysis started2023-12-12 14:03:58.330840
Analysis finished2023-12-12 14:03:59.879555
Duration1.55 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년도
Real number (ℝ)

Distinct12
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2016.5
Minimum2011
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-12T23:03:59.927856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2011
5-th percentile2011
Q12013.75
median2016.5
Q32019.25
95-th percentile2022
Maximum2022
Range11
Interquartile range (IQR)5.5

Descriptive statistics

Standard deviation3.5010203
Coefficient of variation (CV)0.0017361866
Kurtosis-1.217232
Mean2016.5
Median Absolute Deviation (MAD)3
Skewness0
Sum72594
Variance12.257143
MonotonicityIncreasing
2023-12-12T23:04:00.052338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
2011 3
8.3%
2012 3
8.3%
2013 3
8.3%
2014 3
8.3%
2015 3
8.3%
2016 3
8.3%
2017 3
8.3%
2018 3
8.3%
2019 3
8.3%
2020 3
8.3%
Other values (2) 6
16.7%
ValueCountFrequency (%)
2011 3
8.3%
2012 3
8.3%
2013 3
8.3%
2014 3
8.3%
2015 3
8.3%
2016 3
8.3%
2017 3
8.3%
2018 3
8.3%
2019 3
8.3%
2020 3
8.3%
ValueCountFrequency (%)
2022 3
8.3%
2021 3
8.3%
2020 3
8.3%
2019 3
8.3%
2018 3
8.3%
2017 3
8.3%
2016 3
8.3%
2015 3
8.3%
2014 3
8.3%
2013 3
8.3%

구분
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size420.0 B
감면
12 
국비
12 
일반
12 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row감면
2nd row국비
3rd row일반
4th row감면
5th row국비

Common Values

ValueCountFrequency (%)
감면 12
33.3%
국비 12
33.3%
일반 12
33.3%

Length

2023-12-12T23:04:00.197763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:04:00.314292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
감면 12
33.3%
국비 12
33.3%
일반 12
33.3%

자연인
Real number (ℝ)

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14168.444
Minimum8758
Maximum17995
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-12T23:04:00.436250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8758
5-th percentile11767.5
Q113569.25
median14398
Q314918.25
95-th percentile15973.25
Maximum17995
Range9237
Interquartile range (IQR)1349

Descriptive statistics

Standard deviation1588.7089
Coefficient of variation (CV)0.11213009
Kurtosis4.0162845
Mean14168.444
Median Absolute Deviation (MAD)658
Skewness-1.0867516
Sum510064
Variance2523996.1
MonotonicityNot monotonic
2023-12-12T23:04:00.905768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
14095 1
 
2.8%
14546 1
 
2.8%
15350 1
 
2.8%
14172 1
 
2.8%
14554 1
 
2.8%
14909 1
 
2.8%
14071 1
 
2.8%
10350 1
 
2.8%
13487 1
 
2.8%
12930 1
 
2.8%
Other values (26) 26
72.2%
ValueCountFrequency (%)
8758 1
2.8%
10350 1
2.8%
12240 1
2.8%
12707 1
2.8%
12767 1
2.8%
12930 1
2.8%
13487 1
2.8%
13522 1
2.8%
13558 1
2.8%
13573 1
2.8%
ValueCountFrequency (%)
17995 1
2.8%
16757 1
2.8%
15712 1
2.8%
15494 1
2.8%
15386 1
2.8%
15350 1
2.8%
15062 1
2.8%
15032 1
2.8%
14946 1
2.8%
14909 1
2.8%

연인원
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean205686.92
Minimum41458
Maximum438524
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-12T23:04:01.064533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41458
5-th percentile45648.5
Q151268.5
median156904
Q3382680
95-th percentile433910.75
Maximum438524
Range397066
Interquartile range (IQR)331411.5

Descriptive statistics

Standard deviation154124.58
Coefficient of variation (CV)0.7493164
Kurtosis-1.4358571
Mean205686.92
Median Absolute Deviation (MAD)109543
Skewness0.51137295
Sum7404729
Variance2.3754386 × 1010
MonotonicityNot monotonic
2023-12-12T23:04:01.264062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
149644 1
 
2.8%
435032 1
 
2.8%
168926 1
 
2.8%
418535 1
 
2.8%
46946 1
 
2.8%
171881 1
 
2.8%
419075 1
 
2.8%
43268 1
 
2.8%
144335 1
 
2.8%
352053 1
 
2.8%
Other values (26) 26
72.2%
ValueCountFrequency (%)
41458 1
2.8%
43268 1
2.8%
46442 1
2.8%
46946 1
2.8%
47119 1
2.8%
47312 1
2.8%
47410 1
2.8%
49051 1
2.8%
50604 1
2.8%
51490 1
2.8%
ValueCountFrequency (%)
438524 1
2.8%
435032 1
2.8%
433537 1
2.8%
430932 1
2.8%
426653 1
2.8%
423016 1
2.8%
419075 1
2.8%
418535 1
2.8%
418221 1
2.8%
370833 1
2.8%

Interactions

2023-12-12T23:03:59.217702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:58.490502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:58.853768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:59.348459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:58.619020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:58.969089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:59.490925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:58.734149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:03:59.072938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:04:01.409412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도구분자연인연인원
년도1.0000.0000.0000.000
구분0.0001.0000.4871.000
자연인0.0000.4871.0000.547
연인원0.0001.0000.5471.000
2023-12-12T23:04:01.535017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도자연인연인원구분
년도1.000-0.399-0.0060.000
자연인-0.3991.0000.3230.310
연인원-0.0060.3231.0000.953
구분0.0000.3100.9531.000

Missing values

2023-12-12T23:03:59.723879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:03:59.848994image/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

년도구분자연인연인원
02011감면14095149644
12011국비15032418221
22011일반1470451490
32012감면14231151995
42012국비15386423016
52012일반1352247410
62013감면14252151991
72013국비14946426653
82013일반1396347312
92014감면14544152226
년도구분자연인연인원
262019일반1035043268
272020감면13487144335
282020국비12930352053
292020일반875841458
302021감면13573162020
312021국비12767370833
322021일반1224056357
332022감면13720156970
342022국비12707352250
352022일반1799577419