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

Description대전보훈병원에서 개방하는 년도별 국가유공자 진료인원 데이터로 년도,구분,자연인,연인원이 포함된 데이터입니다.
URLhttps://www.data.go.kr/data/15067089/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 07:02:01.455761
Analysis finished2023-12-12 07:02:02.533035
Duration1.08 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
2023-12-12T16:02:02.599888image/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
2023-12-12T16:02:02.729170image/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
국비
12 
감면
12 
일반
12 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

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

Length

2023-12-12T16:02:02.958997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:02:03.091787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국비 12
33.3%
감면 12
33.3%
일반 12
33.3%

자연인
Real number (ℝ)

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10570.75
Minimum8299
Maximum17193
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-12T16:02:03.257007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8299
5-th percentile8567.25
Q19357.25
median10206
Q311532.25
95-th percentile13135
Maximum17193
Range8894
Interquartile range (IQR)2175

Descriptive statistics

Standard deviation1842.3767
Coefficient of variation (CV)0.17429006
Kurtosis3.4473108
Mean10570.75
Median Absolute Deviation (MAD)1005
Skewness1.5232048
Sum380547
Variance3394351.7
MonotonicityNot monotonic
2023-12-12T16:02:03.457365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
9395 1
 
2.8%
12274 1
 
2.8%
9208 1
 
2.8%
12585 1
 
2.8%
11205 1
 
2.8%
9343 1
 
2.8%
12799 1
 
2.8%
11662 1
 
2.8%
8739 1
 
2.8%
10964 1
 
2.8%
Other values (26) 26
72.2%
ValueCountFrequency (%)
8299 1
2.8%
8334 1
2.8%
8645 1
2.8%
8739 1
2.8%
8789 1
2.8%
8798 1
2.8%
9195 1
2.8%
9208 1
2.8%
9343 1
2.8%
9362 1
2.8%
ValueCountFrequency (%)
17193 1
2.8%
14143 1
2.8%
12799 1
2.8%
12594 1
2.8%
12585 1
2.8%
12274 1
2.8%
12223 1
2.8%
12057 1
2.8%
11662 1
2.8%
11489 1
2.8%

연인원
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean154125.14
Minimum28371
Maximum327887
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-12T16:02:03.617955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum28371
5-th percentile29616.75
Q143134
median120863.5
Q3284574.25
95-th percentile321099.5
Maximum327887
Range299516
Interquartile range (IQR)241440.25

Descriptive statistics

Standard deviation110910.24
Coefficient of variation (CV)0.71961162
Kurtosis-1.4769768
Mean154125.14
Median Absolute Deviation (MAD)83746
Skewness0.42515343
Sum5548505
Variance1.2301081 × 1010
MonotonicityNot monotonic
2023-12-12T16:02:03.773994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
273103 1
 
2.8%
120271 1
 
2.8%
320973 1
 
2.8%
142634 1
 
2.8%
41414 1
 
2.8%
327887 1
 
2.8%
156806 1
 
2.8%
41733 1
 
2.8%
291756 1
 
2.8%
140670 1
 
2.8%
Other values (26) 26
72.2%
ValueCountFrequency (%)
28371 1
2.8%
29385 1
2.8%
29694 1
2.8%
30067 1
2.8%
31805 1
2.8%
35117 1
2.8%
39118 1
2.8%
41414 1
2.8%
41733 1
2.8%
43601 1
2.8%
ValueCountFrequency (%)
327887 1
2.8%
321479 1
2.8%
320973 1
2.8%
313059 1
2.8%
309641 1
2.8%
295493 1
2.8%
295276 1
2.8%
291756 1
2.8%
285919 1
2.8%
284126 1
2.8%

Interactions

2023-12-12T16:02:02.122040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:01.582436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:01.843128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:02.217656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:01.685955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:01.931999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:02.302332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:01.762092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:02.026093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T16:02:03.906735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도구분자연인연인원
년도1.0000.0000.0000.000
구분0.0001.0000.6540.943
자연인0.0000.6541.0000.778
연인원0.0000.9430.7781.000
2023-12-12T16:02:04.023368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도자연인연인원구분
년도1.0000.2590.2040.000
자연인0.2591.000-0.1870.475
연인원0.204-0.1871.0000.905
구분0.0000.4750.9051.000

Missing values

2023-12-12T16:02:02.408074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:02:02.495072image/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
02011국비9395273103
12011감면1001787940
22011일반919530067
32012국비9628285919
42012감면1040696619
52012일반879828371
62013국비9665295276
72013감면11294103473
82013일반864529385
92014국비9507295493
년도구분자연인연인원
262019일반1166241733
272020국비8739291756
282020감면10964140670
292020일반1259443601
302021국비8299284126
312021감면10636143567
322021일반1719374640
332022국비8334270779
342022감면10657139067
352022일반1414360943