Overview

Dataset statistics

Number of variables6
Number of observations2275
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory113.4 KiB
Average record size in memory51.1 B

Variable types

Categorical3
Numeric3

Dataset

Description보건복지부에서 인체조직기증현황(남,녀 성별, 연령, 시도, 기증 년도, 기증 형태)에 대해서 정보를 제공합니다.
Author보건복지부
URLhttps://www.data.go.kr/data/15075225/fileData.do

Reproduction

Analysis started2023-12-23 07:02:16.932425
Analysis finished2023-12-23 07:02:22.792827
Duration5.86 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

성별
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.9 KiB
여자
1177 
남자
1098 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row남자
2nd row남자
3rd row여자
4th row남자
5th row남자

Common Values

ValueCountFrequency (%)
여자 1177
51.7%
남자 1098
48.3%

Length

2023-12-23T07:02:23.011973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-23T07:02:23.309824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여자 1177
51.7%
남자 1098
48.3%

연령
Real number (ℝ)

Distinct98
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean61.426813
Minimum-27
Maximum101
Zeros0
Zeros (%)0.0%
Negative12
Negative (%)0.5%
Memory size20.1 KiB
2023-12-23T07:02:23.691625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-27
5-th percentile31.7
Q150
median63
Q374
95-th percentile86
Maximum101
Range128
Interquartile range (IQR)24

Descriptive statistics

Standard deviation17.659819
Coefficient of variation (CV)0.28749365
Kurtosis0.95795752
Mean61.426813
Median Absolute Deviation (MAD)12
Skewness-0.70951133
Sum139746
Variance311.8692
MonotonicityNot monotonic
2023-12-23T07:02:24.369651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
63 63
 
2.8%
68 59
 
2.6%
72 58
 
2.5%
61 54
 
2.4%
59 54
 
2.4%
69 54
 
2.4%
62 51
 
2.2%
78 51
 
2.2%
71 51
 
2.2%
66 51
 
2.2%
Other values (88) 1729
76.0%
ValueCountFrequency (%)
-27 1
 
< 0.1%
-13 3
0.1%
-12 3
0.1%
-11 1
 
< 0.1%
-10 3
0.1%
-9 1
 
< 0.1%
2 1
 
< 0.1%
3 3
0.1%
5 1
 
< 0.1%
6 1
 
< 0.1%
ValueCountFrequency (%)
101 3
0.1%
100 1
 
< 0.1%
99 2
 
0.1%
98 2
 
0.1%
97 2
 
0.1%
96 1
 
< 0.1%
95 3
0.1%
94 7
0.3%
93 4
0.2%
92 7
0.3%

시도
Categorical

Distinct16
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size17.9 KiB
서울
851 
경기
424 
강원
217 
인천
179 
대구
170 
Other values (11)
434 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울
2nd row광주
3rd row충남
4th row서울
5th row경기

Common Values

ValueCountFrequency (%)
서울 851
37.4%
경기 424
18.6%
강원 217
 
9.5%
인천 179
 
7.9%
대구 170
 
7.5%
부산 85
 
3.7%
전북 72
 
3.2%
대전 67
 
2.9%
광주 59
 
2.6%
경남 43
 
1.9%
Other values (6) 108
 
4.7%

Length

2023-12-23T07:02:25.558196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울 851
37.4%
경기 424
18.6%
강원 217
 
9.5%
인천 179
 
7.9%
대구 170
 
7.5%
부산 85
 
3.7%
전북 72
 
3.2%
대전 67
 
2.9%
광주 59
 
2.6%
경남 43
 
1.9%
Other values (6) 108
 
4.7%

기증년
Real number (ℝ)

Distinct6
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2019.2299
Minimum2017
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size20.1 KiB
2023-12-23T07:02:27.109237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2017
5-th percentile2017
Q12018
median2019
Q32021
95-th percentile2022
Maximum2022
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.7513367
Coefficient of variation (CV)0.00086732901
Kurtosis-1.2636648
Mean2019.2299
Median Absolute Deviation (MAD)2
Skewness0.21181408
Sum4593748
Variance3.0671801
MonotonicityNot monotonic
2023-12-23T07:02:28.517077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2017 523
23.0%
2018 389
17.1%
2019 388
17.1%
2022 345
15.2%
2020 337
14.8%
2021 293
12.9%
ValueCountFrequency (%)
2017 523
23.0%
2018 389
17.1%
2019 388
17.1%
2020 337
14.8%
2021 293
12.9%
2022 345
15.2%
ValueCountFrequency (%)
2022 345
15.2%
2021 293
12.9%
2020 337
14.8%
2019 388
17.1%
2018 389
17.1%
2017 523
23.0%

기증형태
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.9 KiB
생존
1580 
뇌사
471 
사후
224 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row생존
2nd row뇌사
3rd row생존
4th row생존
5th row생존

Common Values

ValueCountFrequency (%)
생존 1580
69.5%
뇌사 471
 
20.7%
사후 224
 
9.8%

Length

2023-12-23T07:02:29.359593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-23T07:02:29.868901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
생존 1580
69.5%
뇌사 471
 
20.7%
사후 224
 
9.8%

건수
Real number (ℝ)

Distinct26
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.1534066
Minimum1
Maximum30
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size20.1 KiB
2023-12-23T07:02:30.612642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q34
95-th percentile9
Maximum30
Range29
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.2494815
Coefficient of variation (CV)1.030467
Kurtosis13.108138
Mean3.1534066
Median Absolute Deviation (MAD)1
Skewness3.0952794
Sum7174
Variance10.55913
MonotonicityNot monotonic
2023-12-23T07:02:31.298464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
1 902
39.6%
2 373
16.4%
4 316
 
13.9%
3 254
 
11.2%
5 157
 
6.9%
6 80
 
3.5%
7 36
 
1.6%
9 27
 
1.2%
8 25
 
1.1%
10 16
 
0.7%
Other values (16) 89
 
3.9%
ValueCountFrequency (%)
1 902
39.6%
2 373
16.4%
3 254
 
11.2%
4 316
 
13.9%
5 157
 
6.9%
6 80
 
3.5%
7 36
 
1.6%
8 25
 
1.1%
9 27
 
1.2%
10 16
 
0.7%
ValueCountFrequency (%)
30 1
 
< 0.1%
26 2
 
0.1%
25 1
 
< 0.1%
23 2
 
0.1%
22 6
0.3%
21 2
 
0.1%
20 2
 
0.1%
19 2
 
0.1%
18 3
0.1%
17 6
0.3%

Interactions

2023-12-23T07:02:20.810606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T07:02:18.055180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T07:02:19.483614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T07:02:21.271081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T07:02:18.523815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T07:02:19.878154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T07:02:21.731222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T07:02:19.110703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T07:02:20.384241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-23T07:02:31.727121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
성별연령시도기증년기증형태건수
성별1.0000.2950.2560.0490.1970.246
연령0.2951.0000.2590.0000.3980.276
시도0.2560.2591.0000.1300.5410.298
기증년0.0490.0000.1301.0000.1130.000
기증형태0.1970.3980.5410.1131.0000.479
건수0.2460.2760.2980.0000.4791.000
2023-12-23T07:02:32.221944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시도기증형태성별
시도1.0000.3500.200
기증형태0.3501.0000.324
성별0.2000.3241.000
2023-12-23T07:02:32.663306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연령기증년건수성별시도기증형태
연령1.000-0.054-0.1120.2270.1050.260
기증년-0.0541.0000.0870.0580.0950.102
건수-0.1120.0871.0000.1880.1210.328
성별0.2270.0580.1881.0000.2000.324
시도0.1050.0950.1210.2001.0000.350
기증형태0.2600.1020.3280.3240.3501.000

Missing values

2023-12-23T07:02:22.184267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-23T07:02:22.586227image/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

성별연령시도기증년기증형태건수
0남자34서울2017생존3
1남자58광주2017뇌사2
2여자31충남2017생존3
3남자76서울2017생존2
4남자61경기2017생존1
5남자43경기2017생존1
6여자86서울2017생존6
7남자52서울2017생존1
8여자71대구2017생존1
9여자6서울2017생존1
성별연령시도기증년기증형태건수
2265남자71울산2022사후3
2266여자77대구2022생존1
2267여자58충남2022뇌사5
2268남자51대구2022사후4
2269남자59강원2022뇌사5
2270남자29인천2022뇌사4
2271남자32부산2022뇌사4
2272남자60부산2022뇌사1
2273남자69경기2022생존1
2274남자79서울2022생존1