Overview

Dataset statistics

Number of variables5
Number of observations41
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.9 KiB
Average record size in memory47.2 B

Variable types

Categorical2
Numeric3

Dataset

Description코로나19가 발생한 이후(2020년 1월부터) 춘천시 확진자 및 코로나19로 인한 사망자의 월별 데이터. 읍면동 단위의 경우 "확진환자의 이동경로 등 정보공개 지침"에 따라 공개할수 없음
URLhttps://www.data.go.kr/data/15085780/fileData.do

Alerts

데이터기준일 has constant value ""Constant
확진자 수 is highly overall correlated with 사망자High correlation
사망자 is highly overall correlated with 확진자 수High correlation
확진자 수 has 3 (7.3%) zerosZeros
사망자 has 15 (36.6%) zerosZeros

Reproduction

Analysis started2023-12-12 23:00:00.855841
Analysis finished2023-12-12 23:00:02.015888
Duration1.16 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년
Categorical

Distinct4
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Memory size460.0 B
2020
12 
2021
12 
2022
12 
2023
5 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020
2nd row2020
3rd row2020
4th row2020
5th row2020

Common Values

ValueCountFrequency (%)
2020 12
29.3%
2021 12
29.3%
2022 12
29.3%
2023 5
12.2%

Length

2023-12-13T08:00:02.073870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:00:02.189147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 12
29.3%
2021 12
29.3%
2022 12
29.3%
2023 5
12.2%

월
Real number (ℝ)

Distinct12
Distinct (%)29.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.0731707
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-13T08:00:02.303627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median6
Q39
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.5099163
Coefficient of variation (CV)0.57793802
Kurtosis-1.2037235
Mean6.0731707
Median Absolute Deviation (MAD)3
Skewness0.19134676
Sum249
Variance12.319512
MonotonicityNot monotonic
2023-12-13T08:00:02.444346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 4
9.8%
2 4
9.8%
3 4
9.8%
4 4
9.8%
5 4
9.8%
6 3
7.3%
7 3
7.3%
8 3
7.3%
9 3
7.3%
10 3
7.3%
Other values (2) 6
14.6%
ValueCountFrequency (%)
1 4
9.8%
2 4
9.8%
3 4
9.8%
4 4
9.8%
5 4
9.8%
6 3
7.3%
7 3
7.3%
8 3
7.3%
9 3
7.3%
10 3
7.3%
ValueCountFrequency (%)
12 3
7.3%
11 3
7.3%
10 3
7.3%
9 3
7.3%
8 3
7.3%
7 3
7.3%
6 3
7.3%
5 4
9.8%
4 4
9.8%
3 4
9.8%

확진자 수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct35
Distinct (%)85.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4562.2927
Minimum0
Maximum60487
Zeros3
Zeros (%)7.3%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-13T08:00:02.595131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q119
median142
Q35696
95-th percentile20238
Maximum60487
Range60487
Interquartile range (IQR)5677

Descriptive statistics

Standard deviation10636.675
Coefficient of variation (CV)2.331432
Kurtosis19.662755
Mean4562.2927
Median Absolute Deviation (MAD)142
Skewness4.1029947
Sum187054
Variance1.1313886 × 108
MonotonicityNot monotonic
2023-12-13T08:00:02.728116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
0 3
 
7.3%
3 3
 
7.3%
77 2
 
4.9%
2 2
 
4.9%
2327 1
 
2.4%
1742 1
 
2.4%
3217 1
 
2.4%
1440 1
 
2.4%
5696 1
 
2.4%
60487 1
 
2.4%
Other values (25) 25
61.0%
ValueCountFrequency (%)
0 3
7.3%
1 1
 
2.4%
2 2
4.9%
3 3
7.3%
17 1
 
2.4%
19 1
 
2.4%
24 1
 
2.4%
28 1
 
2.4%
34 1
 
2.4%
54 1
 
2.4%
ValueCountFrequency (%)
60487 1
2.4%
26596 1
2.4%
20238 1
2.4%
10406 1
2.4%
10176 1
2.4%
9753 1
2.4%
9631 1
2.4%
8395 1
2.4%
6495 1
2.4%
5721 1
2.4%

사망자
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct12
Distinct (%)29.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.1219512
Minimum0
Maximum60
Zeros15
Zeros (%)36.6%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-13T08:00:02.834629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q34
95-th percentile18
Maximum60
Range60
Interquartile range (IQR)4

Descriptive statistics

Standard deviation11.623672
Coefficient of variation (CV)2.2693836
Kurtosis14.899153
Mean5.1219512
Median Absolute Deviation (MAD)1
Skewness3.7478619
Sum210
Variance135.10976
MonotonicityNot monotonic
2023-12-13T08:00:02.930124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 15
36.6%
1 9
22.0%
2 5
 
12.2%
10 3
 
7.3%
4 2
 
4.9%
8 1
 
2.4%
60 1
 
2.4%
44 1
 
2.4%
18 1
 
2.4%
11 1
 
2.4%
Other values (2) 2
 
4.9%
ValueCountFrequency (%)
0 15
36.6%
1 9
22.0%
2 5
 
12.2%
4 2
 
4.9%
5 1
 
2.4%
7 1
 
2.4%
8 1
 
2.4%
10 3
 
7.3%
11 1
 
2.4%
18 1
 
2.4%
ValueCountFrequency (%)
60 1
 
2.4%
44 1
 
2.4%
18 1
 
2.4%
11 1
 
2.4%
10 3
7.3%
8 1
 
2.4%
7 1
 
2.4%
5 1
 
2.4%
4 2
 
4.9%
2 5
12.2%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size460.0 B
2023-06-30
41 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-06-30
2nd row2023-06-30
3rd row2023-06-30
4th row2023-06-30
5th row2023-06-30

Common Values

ValueCountFrequency (%)
2023-06-30 41
100.0%

Length

2023-12-13T08:00:03.044958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:00:03.155163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-06-30 41
100.0%

Interactions

2023-12-13T08:00:01.613897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:00:01.004336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:00:01.321767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:00:01.695579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:00:01.109390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:00:01.424667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:00:01.776566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:00:01.215170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:00:01.527189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:00:03.219170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년월확진자 수사망자
년1.0000.0000.4460.332
월0.0001.0000.3070.463
확진자 수0.4460.3071.0000.996
사망자0.3320.4630.9961.000
2023-12-13T08:00:03.311012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
월확진자 수사망자년
월1.0000.1090.0350.000
확진자 수0.1091.0000.8290.370
사망자0.0350.8291.0000.268
년0.0000.3700.2681.000

Missing values

2023-12-13T08:00:01.890163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:00:01.982879image/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

년월확진자 수사망자데이터기준일
020201002023-06-30
120202202023-06-30
220203302023-06-30
320204202023-06-30
420205002023-06-30
520206302023-06-30
620207002023-06-30
7202081702023-06-30
820209302023-06-30
9202010102023-06-30
년월확진자 수사망자데이터기준일
312022820238182023-06-30
32202299631102023-06-30
33202210649542023-06-30
342022119753112023-06-30
352022121040672023-06-30
3620231569622023-06-30
3720232144012023-06-30
3820233174252023-06-30
3920234232722023-06-30
4020235321742023-06-30