Overview

Dataset statistics

Number of variables6
Number of observations28
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.6 KiB
Average record size in memory58.7 B

Variable types

Numeric6

Dataset

Description대한적십자사 혈액정보관리시스템을 통한 조혈모세포기증자 통계 자료입니다. 연령대 별 조혈모세포 기증, 1994년부터 2021년까지 정보로 구성되어 있습니다.
URLhttps://www.data.go.kr/data/15022335/fileData.do

Alerts

구분 연도 is highly overall correlated with 18-19세 and 4 other fieldsHigh correlation
18-19세 is highly overall correlated with 구분 연도 and 3 other fieldsHigh correlation
20-29세 is highly overall correlated with 구분 연도 and 4 other fieldsHigh correlation
30-39세 is highly overall correlated with 구분 연도 and 2 other fieldsHigh correlation
40-49세 is highly overall correlated with 구분 연도 and 3 other fieldsHigh correlation
50세이상 is highly overall correlated with 구분 연도 and 2 other fieldsHigh correlation
구분 연도 has unique valuesUnique
18-19세 has unique valuesUnique
20-29세 has unique valuesUnique
18-19세 has 1 (3.6%) zerosZeros
40-49세 has 12 (42.9%) zerosZeros
50세이상 has 21 (75.0%) zerosZeros

Reproduction

Analysis started2023-12-12 17:57:51.000177
Analysis finished2023-12-12 17:57:54.961597
Duration3.96 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분 연도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2007.5
Minimum1994
Maximum2021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-13T02:57:55.034221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1994
5-th percentile1995.35
Q12000.75
median2007.5
Q32014.25
95-th percentile2019.65
Maximum2021
Range27
Interquartile range (IQR)13.5

Descriptive statistics

Standard deviation8.2259751
Coefficient of variation (CV)0.0040976215
Kurtosis-1.2
Mean2007.5
Median Absolute Deviation (MAD)7
Skewness0
Sum56210
Variance67.666667
MonotonicityStrictly decreasing
2023-12-13T02:57:55.554796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
2021 1
 
3.6%
2006 1
 
3.6%
1994 1
 
3.6%
1995 1
 
3.6%
1996 1
 
3.6%
1997 1
 
3.6%
1998 1
 
3.6%
1999 1
 
3.6%
2000 1
 
3.6%
2001 1
 
3.6%
Other values (18) 18
64.3%
ValueCountFrequency (%)
1994 1
3.6%
1995 1
3.6%
1996 1
3.6%
1997 1
3.6%
1998 1
3.6%
1999 1
3.6%
2000 1
3.6%
2001 1
3.6%
2002 1
3.6%
2003 1
3.6%
ValueCountFrequency (%)
2021 1
3.6%
2020 1
3.6%
2019 1
3.6%
2018 1
3.6%
2017 1
3.6%
2016 1
3.6%
2015 1
3.6%
2014 1
3.6%
2013 1
3.6%
2012 1
3.6%

18-19세
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean536.89286
Minimum0
Maximum1110
Zeros1
Zeros (%)3.6%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-13T02:57:55.719580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.05
Q1238.5
median559
Q3800
95-th percentile1060.55
Maximum1110
Range1110
Interquartile range (IQR)561.5

Descriptive statistics

Standard deviation344.57223
Coefficient of variation (CV)0.64178957
Kurtosis-1.0530245
Mean536.89286
Median Absolute Deviation (MAD)270
Skewness-0.10667801
Sum15033
Variance118730.03
MonotonicityNot monotonic
2023-12-13T02:57:55.878636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
1030 1
 
3.6%
287 1
 
3.6%
0 1
 
3.6%
2 1
 
3.6%
63 1
 
3.6%
5 1
 
3.6%
479 1
 
3.6%
539 1
 
3.6%
209 1
 
3.6%
219 1
 
3.6%
Other values (18) 18
64.3%
ValueCountFrequency (%)
0 1
3.6%
2 1
3.6%
5 1
3.6%
62 1
3.6%
63 1
3.6%
209 1
3.6%
219 1
3.6%
245 1
3.6%
287 1
3.6%
384 1
3.6%
ValueCountFrequency (%)
1110 1
3.6%
1077 1
3.6%
1030 1
3.6%
970 1
3.6%
896 1
3.6%
827 1
3.6%
812 1
3.6%
796 1
3.6%
754 1
3.6%
686 1
3.6%

20-29세
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3704.4286
Minimum1769
Maximum6561
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-13T02:57:56.107150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1769
5-th percentile1970.8
Q12851
median3708
Q34535.5
95-th percentile5098.65
Maximum6561
Range4792
Interquartile range (IQR)1684.5

Descriptive statistics

Standard deviation1145.9198
Coefficient of variation (CV)0.30933781
Kurtosis-0.084096513
Mean3704.4286
Median Absolute Deviation (MAD)862
Skewness0.18571738
Sum103724
Variance1313132.3
MonotonicityNot monotonic
2023-12-13T02:57:56.327553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
4462 1
 
3.6%
4407 1
 
3.6%
1769 1
 
3.6%
3513 1
 
3.6%
2522 1
 
3.6%
3284 1
 
3.6%
2212 1
 
3.6%
2028 1
 
3.6%
1940 1
 
3.6%
2367 1
 
3.6%
Other values (18) 18
64.3%
ValueCountFrequency (%)
1769 1
3.6%
1940 1
3.6%
2028 1
3.6%
2212 1
3.6%
2367 1
3.6%
2522 1
3.6%
2602 1
3.6%
2934 1
3.6%
3284 1
3.6%
3322 1
3.6%
ValueCountFrequency (%)
6561 1
3.6%
5169 1
3.6%
4968 1
3.6%
4729 1
3.6%
4695 1
3.6%
4690 1
3.6%
4639 1
3.6%
4501 1
3.6%
4462 1
3.6%
4407 1
3.6%

30-39세
Real number (ℝ)

HIGH CORRELATION 

Distinct27
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1127.2143
Minimum161
Maximum1935
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-13T02:57:56.501930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum161
5-th percentile465.7
Q1789
median1236
Q31411.75
95-th percentile1708
Maximum1935
Range1774
Interquartile range (IQR)622.75

Descriptive statistics

Standard deviation449.13112
Coefficient of variation (CV)0.39844343
Kurtosis-0.67719156
Mean1127.2143
Median Absolute Deviation (MAD)317
Skewness-0.31499237
Sum31562
Variance201718.77
MonotonicityNot monotonic
2023-12-13T02:57:56.682868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
1708 2
 
7.1%
1674 1
 
3.6%
822 1
 
3.6%
161 1
 
3.6%
679 1
 
3.6%
423 1
 
3.6%
561 1
 
3.6%
557 1
 
3.6%
864 1
 
3.6%
545 1
 
3.6%
Other values (17) 17
60.7%
ValueCountFrequency (%)
161 1
3.6%
423 1
3.6%
545 1
3.6%
557 1
3.6%
561 1
3.6%
679 1
3.6%
690 1
3.6%
822 1
3.6%
864 1
3.6%
925 1
3.6%
ValueCountFrequency (%)
1935 1
3.6%
1708 2
7.1%
1674 1
3.6%
1559 1
3.6%
1518 1
3.6%
1438 1
3.6%
1403 1
3.6%
1401 1
3.6%
1359 1
3.6%
1356 1
3.6%

40-49세
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct14
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46.285714
Minimum0
Maximum400
Zeros12
Zeros (%)42.9%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-13T02:57:56.852926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median16
Q347.75
95-th percentile189.85
Maximum400
Range400
Interquartile range (IQR)47.75

Descriptive statistics

Standard deviation86.615308
Coefficient of variation (CV)1.8713184
Kurtosis10.244578
Mean46.285714
Median Absolute Deviation (MAD)16
Skewness3.0050537
Sum1296
Variance7502.2116
MonotonicityNot monotonic
2023-12-13T02:57:57.003824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 12
42.9%
22 2
 
7.1%
29 2
 
7.1%
16 2
 
7.1%
4 1
 
3.6%
28 1
 
3.6%
193 1
 
3.6%
79 1
 
3.6%
61 1
 
3.6%
44 1
 
3.6%
Other values (4) 4
 
14.3%
ValueCountFrequency (%)
0 12
42.9%
4 1
 
3.6%
16 2
 
7.1%
22 2
 
7.1%
28 1
 
3.6%
29 2
 
7.1%
44 1
 
3.6%
59 1
 
3.6%
61 1
 
3.6%
79 1
 
3.6%
ValueCountFrequency (%)
400 1
3.6%
193 1
3.6%
184 1
3.6%
110 1
3.6%
79 1
3.6%
61 1
3.6%
59 1
3.6%
44 1
3.6%
29 2
7.1%
28 1
3.6%

50세이상
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct6
Distinct (%)21.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.1785714
Minimum0
Maximum96
Zeros21
Zeros (%)75.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-13T02:57:57.163552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.25
95-th percentile18
Maximum96
Range96
Interquartile range (IQR)0.25

Descriptive statistics

Standard deviation18.427141
Coefficient of variation (CV)3.5583445
Kurtosis23.965669
Mean5.1785714
Median Absolute Deviation (MAD)0
Skewness4.7830356
Sum145
Variance339.55952
MonotonicityNot monotonic
2023-12-13T02:57:57.290199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 21
75.0%
5 2
 
7.1%
18 2
 
7.1%
1 1
 
3.6%
2 1
 
3.6%
96 1
 
3.6%
ValueCountFrequency (%)
0 21
75.0%
1 1
 
3.6%
2 1
 
3.6%
5 2
 
7.1%
18 2
 
7.1%
96 1
 
3.6%
ValueCountFrequency (%)
96 1
 
3.6%
18 2
 
7.1%
5 2
 
7.1%
2 1
 
3.6%
1 1
 
3.6%
0 21
75.0%

Interactions

2023-12-13T02:57:54.237622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:51.252407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:51.958157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:52.619253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:53.110639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:53.632504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:54.336318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:51.376845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:52.067454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:52.702591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:53.208677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:53.728173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:54.421408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:51.489029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:52.173724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:52.783826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:53.303744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:53.829494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:54.500023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:51.592458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:52.283592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:52.857252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:53.385633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:53.926003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:54.586693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:51.713254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:52.415125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:52.948605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:53.467092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:54.024756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:54.665195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:51.847616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:52.537489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:53.036917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:53.553090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:54.117592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T02:57:57.391738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분 연도18-19세20-29세30-39세40-49세50세이상
구분 연도1.0000.8110.6650.2840.4240.306
18-19세0.8111.0000.5700.2900.0000.000
20-29세0.6650.5701.0000.8220.3830.000
30-39세0.2840.2900.8221.0000.7440.851
40-49세0.4240.0000.3830.7441.0000.873
50세이상0.3060.0000.0000.8510.8731.000
2023-12-13T02:57:57.569657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분 연도18-19세20-29세30-39세40-49세50세이상
구분 연도1.0000.7070.5450.821-0.770-0.641
18-19세0.7071.0000.8060.715-0.547-0.490
20-29세0.5450.8061.0000.616-0.504-0.598
30-39세0.8210.7150.6161.000-0.455-0.424
40-49세-0.770-0.547-0.504-0.4551.0000.729
50세이상-0.641-0.490-0.598-0.4240.7291.000

Missing values

2023-12-13T02:57:54.773286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:57:54.913049image/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

구분 연도18-19세20-29세30-39세40-49세50세이상
0202110304462170800
120206863840167400
220195463322151800
320185243360135900
420175723404140100
520166793743143800
620157544272114000
720147964501140300
820138124695124300
920128964729135600
구분 연도18-19세20-29세30-39세40-49세50세이상
182003622934925790
19200224526021092610
2020012192367545220
2120002091940864441
2219995392028557292
2319984792212561595
2419975328442311018
25199663252267918418
2619952351316100
2719940176982240096