Overview

Dataset statistics

Number of variables4
Number of observations31
Missing cells8
Missing cells (%)6.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 KiB
Average record size in memory38.3 B

Variable types

DateTime2
Numeric1
Categorical1

Dataset

Description이 데이터는 충청남도 금산군 코로나19 확진자 및 사망자에 대한 2020년 1월부터 2022년 7월까지의 현황을 제공합니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=109&beforeMenuCd=DOM_000000201001001000&publicdatapk=15098724

Alerts

데이터기준일자 has constant value ""Constant
사망자 is highly imbalanced (53.5%)Imbalance
확진자 has 8 (25.8%) missing valuesMissing
연월 has unique valuesUnique

Reproduction

Analysis started2024-01-09 22:12:29.502168
Analysis finished2024-01-09 22:12:29.781051
Duration0.28 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연월
Date

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
Minimum2020-01-01 00:00:00
Maximum2022-07-01 00:00:00
2024-01-10T07:12:29.827333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:12:29.926756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)

확진자
Real number (ℝ)

MISSING 

Distinct20
Distinct (%)87.0%
Missing8
Missing (%)25.8%
Infinite0
Infinite (%)0.0%
Mean686.43478
Minimum1
Maximum7357
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-01-10T07:12:30.020035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.1
Q15.5
median41
Q3165.5
95-th percentile4018.1
Maximum7357
Range7356
Interquartile range (IQR)160

Descriptive statistics

Standard deviation1733.5258
Coefficient of variation (CV)2.5254049
Kurtosis10.75415
Mean686.43478
Median Absolute Deviation (MAD)40
Skewness3.2405708
Sum15788
Variance3005111.5
MonotonicityNot monotonic
2024-01-10T07:12:30.114181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
6 3
 
9.7%
1 2
 
6.5%
3 1
 
3.2%
14 1
 
3.2%
746 1
 
3.2%
156 1
 
3.2%
834 1
 
3.2%
4262 1
 
3.2%
7357 1
 
3.2%
1823 1
 
3.2%
Other values (10) 10
32.3%
(Missing) 8
25.8%
ValueCountFrequency (%)
1 2
6.5%
2 1
 
3.2%
3 1
 
3.2%
4 1
 
3.2%
5 1
 
3.2%
6 3
9.7%
14 1
 
3.2%
30 1
 
3.2%
41 1
 
3.2%
46 1
 
3.2%
ValueCountFrequency (%)
7357 1
3.2%
4262 1
3.2%
1823 1
3.2%
834 1
3.2%
746 1
3.2%
175 1
3.2%
156 1
3.2%
94 1
3.2%
93 1
3.2%
83 1
3.2%

사망자
Categorical

IMBALANCE 

Distinct5
Distinct (%)16.1%
Missing0
Missing (%)0.0%
Memory size380.0 B
<NA>
25 
1
 
2
2
 
2
16
 
1
10
 
1

Length

Max length4
Median length4
Mean length3.483871
Min length1

Unique

Unique2 ?
Unique (%)6.5%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 25
80.6%
1 2
 
6.5%
2 2
 
6.5%
16 1
 
3.2%
10 1
 
3.2%

Length

2024-01-10T07:12:30.224209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:12:30.307249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 25
80.6%
1 2
 
6.5%
2 2
 
6.5%
16 1
 
3.2%
10 1
 
3.2%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size380.0 B
Minimum2022-08-09 00:00:00
Maximum2022-08-09 00:00:00
2024-01-10T07:12:30.374454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:12:30.443634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-01-10T07:12:29.596693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T07:12:30.496275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연월확진자사망자
연월1.0001.0001.000
확진자1.0001.0000.759
사망자1.0000.7591.000
2024-01-10T07:12:30.568460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
확진자사망자
확진자1.0000.354
사망자0.3541.000

Missing values

2024-01-10T07:12:29.690808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T07:12:29.754879image/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

연월확진자사망자데이터기준일자
02020-01<NA><NA>2022-08-09
12020-02<NA><NA>2022-08-09
22020-03<NA><NA>2022-08-09
32020-04<NA><NA>2022-08-09
42020-05<NA><NA>2022-08-09
52020-061<NA>2022-08-09
62020-075<NA>2022-08-09
72020-08<NA><NA>2022-08-09
82020-091412022-08-09
92020-10<NA><NA>2022-08-09
연월확진자사망자데이터기준일자
212021-1094<NA>2022-08-09
222021-11175<NA>2022-08-09
232021-124622022-08-09
242022-0193<NA>2022-08-09
252022-02182322022-08-09
262022-037357162022-08-09
272022-044262102022-08-09
282022-0583412022-08-09
292022-06156<NA>2022-08-09
302022-07746<NA>2022-08-09