Overview

Dataset statistics

Number of variables4
Number of observations37
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 KiB
Average record size in memory38.6 B

Variable types

Numeric3
Categorical1

Dataset

Description한국보훈복지의료공단 부산보훈병원에서 2011년부터 2021년까지 년도별 국가유공자의 진료인원을 국비/감변별로 자연인원과 연인원을 제공합니다. 자연인 : 년도별 진료본 사람의 수 연인원 : 년도별 진료본 사람의 진료일수
URLhttps://www.data.go.kr/data/15067091/fileData.do

Alerts

자연인 is highly overall correlated with 연인원 and 1 other fieldsHigh correlation
연인원 is highly overall correlated with 자연인 and 1 other fieldsHigh correlation
구분 is highly overall correlated with 자연인 and 1 other fieldsHigh correlation
자연인 has unique valuesUnique
연인원 has unique valuesUnique
연인원 has 1 (2.7%) zerosZeros

Reproduction

Analysis started2023-12-12 20:40:12.271740
Analysis finished2023-12-12 20:40:13.510831
Duration1.24 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년도
Real number (ℝ)

Distinct13
Distinct (%)35.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2016.3243
Minimum2010
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2023-12-13T05:40:13.873620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2010
5-th percentile2011
Q12013
median2016
Q32019
95-th percentile2022
Maximum2022
Range12
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.6136628
Coefficient of variation (CV)0.0017922031
Kurtosis-1.1895036
Mean2016.3243
Median Absolute Deviation (MAD)3
Skewness-0.016593016
Sum74604
Variance13.058559
MonotonicityIncreasing
2023-12-13T05:40:14.036367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
2011 3
8.1%
2012 3
8.1%
2013 3
8.1%
2014 3
8.1%
2015 3
8.1%
2016 3
8.1%
2017 3
8.1%
2018 3
8.1%
2019 3
8.1%
2020 3
8.1%
Other values (3) 7
18.9%
ValueCountFrequency (%)
2010 1
 
2.7%
2011 3
8.1%
2012 3
8.1%
2013 3
8.1%
2014 3
8.1%
2015 3
8.1%
2016 3
8.1%
2017 3
8.1%
2018 3
8.1%
2019 3
8.1%
ValueCountFrequency (%)
2022 3
8.1%
2021 3
8.1%
2020 3
8.1%
2019 3
8.1%
2018 3
8.1%
2017 3
8.1%
2016 3
8.1%
2015 3
8.1%
2014 3
8.1%
2013 3
8.1%

구분
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)8.1%
Missing0
Missing (%)0.0%
Memory size428.0 B
감면
13 
국비
12 
일반
12 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
감면 13
35.1%
국비 12
32.4%
일반 12
32.4%

Length

2023-12-13T05:40:14.182954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:40:14.312365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
감면 13
35.1%
국비 12
32.4%
일반 12
32.4%

자연인
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct37
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13935.324
Minimum1
Maximum20766
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2023-12-13T05:40:14.425953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7816.4
Q19509
median14633
Q318539
95-th percentile19105.4
Maximum20766
Range20765
Interquartile range (IQR)9030

Descriptive statistics

Standard deviation4826.0863
Coefficient of variation (CV)0.34632035
Kurtosis0.13031743
Mean13935.324
Median Absolute Deviation (MAD)4174
Skewness-0.72084254
Sum515607
Variance23291109
MonotonicityNot monotonic
2023-12-13T05:40:14.571440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
1 1
 
2.7%
13834 1
 
2.7%
8457 1
 
2.7%
15353 1
 
2.7%
18807 1
 
2.7%
8859 1
 
2.7%
15040 1
 
2.7%
19195 1
 
2.7%
9509 1
 
2.7%
17906 1
 
2.7%
Other values (27) 27
73.0%
ValueCountFrequency (%)
1 1
2.7%
7366 1
2.7%
7929 1
2.7%
8060 1
2.7%
8085 1
2.7%
8176 1
2.7%
8457 1
2.7%
8488 1
2.7%
8859 1
2.7%
9509 1
2.7%
ValueCountFrequency (%)
20766 1
2.7%
19195 1
2.7%
19083 1
2.7%
18967 1
2.7%
18952 1
2.7%
18930 1
2.7%
18854 1
2.7%
18807 1
2.7%
18673 1
2.7%
18539 1
2.7%

연인원
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct37
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean220704.32
Minimum0
Maximum519910
Zeros1
Zeros (%)2.7%
Negative0
Negative (%)0.0%
Memory size465.0 B
2023-12-13T05:40:14.710469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile34125.6
Q141200
median148095
Q3463604
95-th percentile501327.2
Maximum519910
Range519910
Interquartile range (IQR)422404

Descriptive statistics

Standard deviation191365.6
Coefficient of variation (CV)0.86706776
Kurtosis-1.4348205
Mean220704.32
Median Absolute Deviation (MAD)111996
Skewness0.58155948
Sum8166060
Variance3.6620795 × 1010
MonotonicityNot monotonic
2023-12-13T05:40:14.859821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
0 1
 
2.7%
171090 1
 
2.7%
36099 1
 
2.7%
170804 1
 
2.7%
498270 1
 
2.7%
37903 1
 
2.7%
178479 1
 
2.7%
497290 1
 
2.7%
42345 1
 
2.7%
472134 1
 
2.7%
Other values (27) 27
73.0%
ValueCountFrequency (%)
0 1
2.7%
32492 1
2.7%
34534 1
2.7%
34730 1
2.7%
35810 1
2.7%
35953 1
2.7%
36099 1
2.7%
37804 1
2.7%
37903 1
2.7%
41200 1
2.7%
ValueCountFrequency (%)
519910 1
2.7%
513556 1
2.7%
498270 1
2.7%
497979 1
2.7%
497290 1
2.7%
497267 1
2.7%
481008 1
2.7%
473001 1
2.7%
472134 1
2.7%
463604 1
2.7%

Interactions

2023-12-13T05:40:13.055538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:40:12.429417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:40:12.791150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:40:13.188570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:40:12.567754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:40:12.887155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:40:13.276577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:40:12.687406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:40:12.965596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:40:14.971013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도구분자연인연인원
년도1.0000.0000.0000.000
구분0.0001.0000.9130.999
자연인0.0000.9131.0000.788
연인원0.0000.9990.7881.000
2023-12-13T05:40:15.086723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도자연인연인원구분
년도1.0000.3350.2450.000
자연인0.3351.0000.8460.866
연인원0.2450.8461.0000.914
구분0.0000.8660.9141.000

Missing values

2023-12-13T05:40:13.399181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:40:13.477873image/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
02010감면10
12011감면12530137085
22011국비18437463604
32011일반736632492
42012감면13096136915
52012국비19083473001
62012일반792934534
72013감면13271140239
82013국비18539481008
92013일반808534730
년도구분자연인연인원
272019일반950942345
282020감면13834171090
292020국비17906472134
302020일반958641200
312021감면13729169109
322021국비17669452168
332021일반2076672066
342022감면13444163731
352022국비17328428822
362022일반1893070335