Overview

Dataset statistics

Number of variables5
Number of observations636
Missing cells635
Missing cells (%)20.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory26.2 KiB
Average record size in memory42.2 B

Variable types

Categorical2
DateTime1
Numeric1
Text1

Dataset

Description전북특별자치도 진안군의 코로나19 확진자 및 사망자 현황에 관한 데이터입니다. 시군명, 연월일, 확진자수, 사망자수의 정보를 제공합니다.
Author전북특별자치도 진안군
URLhttps://www.data.go.kr/data/15098748/fileData.do

Alerts

시군명 has constant value ""Constant
비고 has constant value ""Constant
사망자 is highly imbalanced (90.3%)Imbalance
비고 has 635 (99.8%) missing valuesMissing
확진자 발생 연월일 has unique valuesUnique
확진자 has 22 (3.5%) zerosZeros

Reproduction

Analysis started2024-03-14 17:46:06.174945
Analysis finished2024-03-14 17:46:07.163565
Duration0.99 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
전북특별자치도 진안군
636 

Length

Max length11
Median length11
Mean length11
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row전북특별자치도 진안군
2nd row전북특별자치도 진안군
3rd row전북특별자치도 진안군
4th row전북특별자치도 진안군
5th row전북특별자치도 진안군

Common Values

ValueCountFrequency (%)
전북특별자치도 진안군 636
100.0%

Length

2024-03-15T02:46:07.379848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T02:46:07.695117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전북특별자치도 636
50.0%
진안군 636
50.0%

확진자 발생 연월일
Date

UNIQUE 

Distinct636
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
Minimum2020-12-25 00:00:00
Maximum2023-08-30 00:00:00
2024-03-15T02:46:07.990373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:46:08.451627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

확진자
Real number (ℝ)

ZEROS 

Distinct86
Distinct (%)13.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.757862
Minimum0
Maximum151
Zeros22
Zeros (%)3.5%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2024-03-15T02:46:08.848479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q13
median8
Q320
95-th percentile79.75
Maximum151
Range151
Interquartile range (IQR)17

Descriptive statistics

Standard deviation25.116632
Coefficient of variation (CV)1.4143951
Kurtosis7.6850398
Mean17.757862
Median Absolute Deviation (MAD)6
Skewness2.6783117
Sum11294
Variance630.84521
MonotonicityNot monotonic
2024-03-15T02:46:09.296312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 68
 
10.7%
2 44
 
6.9%
4 40
 
6.3%
5 35
 
5.5%
7 29
 
4.6%
6 29
 
4.6%
3 26
 
4.1%
8 26
 
4.1%
0 22
 
3.5%
14 21
 
3.3%
Other values (76) 296
46.5%
ValueCountFrequency (%)
0 22
 
3.5%
1 68
10.7%
2 44
6.9%
3 26
 
4.1%
4 40
6.3%
5 35
5.5%
6 29
4.6%
7 29
4.6%
8 26
 
4.1%
9 12
 
1.9%
ValueCountFrequency (%)
151 1
0.2%
148 2
0.3%
136 1
0.2%
126 1
0.2%
123 1
0.2%
122 1
0.2%
112 2
0.3%
111 1
0.2%
110 1
0.2%
108 1
0.2%

사망자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
0
628 
1
 
8

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row1
5th row0

Common Values

ValueCountFrequency (%)
0 628
98.7%
1 8
 
1.3%

Length

2024-03-15T02:46:09.720612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T02:46:10.037631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 628
98.7%
1 8
 
1.3%

비고
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing635
Missing (%)99.8%
Memory size5.1 KiB
2024-03-15T02:46:10.547083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters10
Distinct characters9
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row첫번째 확진자 사망
ValueCountFrequency (%)
첫번째 1
33.3%
확진자 1
33.3%
사망 1
33.3%
2024-03-15T02:46:11.219479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2
20.0%
첫 1
10.0%
번 1
10.0%
째 1
10.0%
확 1
10.0%
진 1
10.0%
자 1
10.0%
사 1
10.0%
망 1
10.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8
80.0%
Space Separator 2
 
20.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
첫 1
12.5%
번 1
12.5%
째 1
12.5%
확 1
12.5%
진 1
12.5%
자 1
12.5%
사 1
12.5%
망 1
12.5%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8
80.0%
Common 2
 
20.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
첫 1
12.5%
번 1
12.5%
째 1
12.5%
확 1
12.5%
진 1
12.5%
자 1
12.5%
사 1
12.5%
망 1
12.5%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8
80.0%
ASCII 2
 
20.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2
100.0%
Hangul
ValueCountFrequency (%)
첫 1
12.5%
번 1
12.5%
째 1
12.5%
확 1
12.5%
진 1
12.5%
자 1
12.5%
사 1
12.5%
망 1
12.5%

Interactions

2024-03-15T02:46:06.321421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T02:46:11.361059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
확진자사망자
확진자1.0000.412
사망자0.4121.000
2024-03-15T02:46:11.590285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
확진자사망자
확진자1.0000.315
사망자0.3151.000

Missing values

2024-03-15T02:46:06.714392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T02:46:07.037040image/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

시군명확진자 발생 연월일확진자사망자비고
0전북특별자치도 진안군2020-12-2510<NA>
1전북특별자치도 진안군2020-12-2610<NA>
2전북특별자치도 진안군2020-12-2810<NA>
3전북특별자치도 진안군2021-01-3101첫번째 확진자 사망
4전북특별자치도 진안군2021-02-0120<NA>
5전북특별자치도 진안군2021-04-0520<NA>
6전북특별자치도 진안군2021-04-0710<NA>
7전북특별자치도 진안군2021-04-2110<NA>
8전북특별자치도 진안군2021-04-2210<NA>
9전북특별자치도 진안군2021-04-2320<NA>
시군명확진자 발생 연월일확진자사망자비고
626전북특별자치도 진안군2023-08-21250<NA>
627전북특별자치도 진안군2023-08-22130<NA>
628전북특별자치도 진안군2023-08-23170<NA>
629전북특별자치도 진안군2023-08-24240<NA>
630전북특별자치도 진안군2023-08-25170<NA>
631전북특별자치도 진안군2023-08-26160<NA>
632전북특별자치도 진안군2023-08-2740<NA>
633전북특별자치도 진안군2023-08-28150<NA>
634전북특별자치도 진안군2023-08-29110<NA>
635전북특별자치도 진안군2023-08-30210<NA>