Overview

Dataset statistics

Number of variables3
Number of observations1186
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory30.2 KiB
Average record size in memory26.1 B

Variable types

DateTime1
Numeric2

Dataset

Description공식집계일(20월 4월 1일)부터 23년 6월 30일까지의 질병관리청 코로나19 정보관리시스템에 신고된 확진자의 경과를 지속 관찰하여 위중증 여부를 모니터링한 것*위중증 : 고유량(high flow) 산소요법, 인공호흡기, ECMO(체외막산소공급) CRRT(지속적신대체요법) 등으로 격리 치료
Author질병관리청
URLhttps://www.data.go.kr/data/15117594/fileData.do

Alerts

전국 위중증 환자 is highly overall correlated with 경기지역 위중증 환자High correlation
경기지역 위중증 환자 is highly overall correlated with 전국 위중증 환자High correlation
집계일 has unique valuesUnique
전국 위중증 환자 has 59 (5.0%) zerosZeros
경기지역 위중증 환자 has 152 (12.8%) zerosZeros

Reproduction

Analysis started2023-12-12 15:40:32.010828
Analysis finished2023-12-12 15:40:32.707045
Duration0.7 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

집계일
Date

UNIQUE 

Distinct1186
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
Minimum2020-04-01 00:00:00
Maximum2023-06-30 00:00:00
2023-12-13T00:40:32.795675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:40:32.957253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

전국 위중증 환자
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct137
Distinct (%)11.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30.6543
Minimum0
Maximum199
Zeros59
Zeros (%)5.0%
Negative0
Negative (%)0.0%
Memory size10.6 KiB
2023-12-13T00:40:33.096348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q18.25
median19
Q341
95-th percentile96.5
Maximum199
Range199
Interquartile range (IQR)32.75

Descriptive statistics

Standard deviation33.076822
Coefficient of variation (CV)1.0790272
Kurtosis4.180661
Mean30.6543
Median Absolute Deviation (MAD)14
Skewness1.924887
Sum36356
Variance1094.0762
MonotonicityNot monotonic
2023-12-13T00:40:33.327018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 59
 
5.0%
9 44
 
3.7%
1 43
 
3.6%
2 36
 
3.0%
12 36
 
3.0%
7 30
 
2.5%
15 30
 
2.5%
4 29
 
2.4%
14 28
 
2.4%
3 28
 
2.4%
Other values (127) 823
69.4%
ValueCountFrequency (%)
0 59
5.0%
1 43
3.6%
2 36
3.0%
3 28
2.4%
4 29
2.4%
5 26
2.2%
6 22
 
1.9%
7 30
2.5%
8 24
2.0%
9 44
3.7%
ValueCountFrequency (%)
199 1
0.1%
182 1
0.1%
175 1
0.1%
173 2
0.2%
171 1
0.1%
170 1
0.1%
165 1
0.1%
162 2
0.2%
161 1
0.1%
160 1
0.1%

경기지역 위중증 환자
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct49
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.4038786
Minimum0
Maximum55
Zeros152
Zeros (%)12.8%
Negative0
Negative (%)0.0%
Memory size10.6 KiB
2023-12-13T00:40:33.556545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median5
Q312
95-th percentile27
Maximum55
Range55
Interquartile range (IQR)10

Descriptive statistics

Standard deviation9.2429717
Coefficient of variation (CV)1.0998459
Kurtosis3.4147542
Mean8.4038786
Median Absolute Deviation (MAD)4
Skewness1.7518774
Sum9967
Variance85.432525
MonotonicityNot monotonic
2023-12-13T00:40:33.740171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
0 152
 
12.8%
1 117
 
9.9%
3 98
 
8.3%
2 91
 
7.7%
4 88
 
7.4%
5 82
 
6.9%
6 61
 
5.1%
7 46
 
3.9%
9 36
 
3.0%
10 35
 
3.0%
Other values (39) 380
32.0%
ValueCountFrequency (%)
0 152
12.8%
1 117
9.9%
2 91
7.7%
3 98
8.3%
4 88
7.4%
5 82
6.9%
6 61
5.1%
7 46
 
3.9%
8 31
 
2.6%
9 36
 
3.0%
ValueCountFrequency (%)
55 2
0.2%
51 1
 
0.1%
47 1
 
0.1%
46 2
0.2%
44 2
0.2%
43 4
0.3%
42 1
 
0.1%
41 2
0.2%
40 1
 
0.1%
39 4
0.3%

Interactions

2023-12-13T00:40:32.305824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:40:32.097044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:40:32.430447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:40:32.210682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:40:33.856599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
전국 위중증 환자경기지역 위중증 환자
전국 위중증 환자1.0000.933
경기지역 위중증 환자0.9331.000
2023-12-13T00:40:33.952640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
전국 위중증 환자경기지역 위중증 환자
전국 위중증 환자1.0000.942
경기지역 위중증 환자0.9421.000

Missing values

2023-12-13T00:40:32.583074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:40:32.671260image/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

집계일전국 위중증 환자경기지역 위중증 환자
02020-04-0141
12020-04-0221
22020-04-0331
32020-04-0431
42020-04-0500
52020-04-0620
62020-04-0721
72020-04-0820
82020-04-0910
92020-04-1000
집계일전국 위중증 환자경기지역 위중증 환자
11762023-06-21195
11772023-06-22173
11782023-06-23172
11792023-06-24153
11802023-06-25194
11812023-06-26152
11822023-06-27181
11832023-06-28203
11842023-06-29172
11852023-06-30226