Overview

Dataset statistics

Number of variables6
Number of observations44
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.4 KiB
Average record size in memory55.9 B

Variable types

Numeric4
Categorical2

Dataset

Description경상북도 문경시의 코로나19 처음 확인자 발생월부터 확진자 및 사망자현황 데이터로 월별 확진자 및 사망자 현황을 제공합니다.
Author경상북도 문경시
URLhttps://www.data.go.kr/data/15098860/fileData.do

Alerts

데이터기준일 has constant value ""Constant
연변 is highly overall correlated with 코로나19 확진자수 and 2 other fieldsHigh correlation
코로나19 확진자수 is highly overall correlated with 연변 and 1 other fieldsHigh correlation
코로나19 사망자수 is highly overall correlated with 연변 and 1 other fieldsHigh correlation
날짜(년) is highly overall correlated with 연변High correlation
연변 has unique valuesUnique
코로나19 확진자수 has 6 (13.6%) zerosZeros
코로나19 사망자수 has 26 (59.1%) zerosZeros

Reproduction

Analysis started2024-03-14 18:17:12.232239
Analysis finished2024-03-14 18:17:16.645985
Duration4.41 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연변
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct44
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.5
Minimum1
Maximum44
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size524.0 B
2024-03-15T03:17:16.873686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.15
Q111.75
median22.5
Q333.25
95-th percentile41.85
Maximum44
Range43
Interquartile range (IQR)21.5

Descriptive statistics

Standard deviation12.845233
Coefficient of variation (CV)0.57089923
Kurtosis-1.2
Mean22.5
Median Absolute Deviation (MAD)11
Skewness0
Sum990
Variance165
MonotonicityStrictly increasing
2024-03-15T03:17:17.350093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
1 1
 
2.3%
24 1
 
2.3%
26 1
 
2.3%
27 1
 
2.3%
28 1
 
2.3%
29 1
 
2.3%
30 1
 
2.3%
31 1
 
2.3%
32 1
 
2.3%
33 1
 
2.3%
Other values (34) 34
77.3%
ValueCountFrequency (%)
1 1
2.3%
2 1
2.3%
3 1
2.3%
4 1
2.3%
5 1
2.3%
6 1
2.3%
7 1
2.3%
8 1
2.3%
9 1
2.3%
10 1
2.3%
ValueCountFrequency (%)
44 1
2.3%
43 1
2.3%
42 1
2.3%
41 1
2.3%
40 1
2.3%
39 1
2.3%
38 1
2.3%
37 1
2.3%
36 1
2.3%
35 1
2.3%

날짜(년)
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size480.0 B
2020
12 
2021
12 
2022
12 
2023
8 

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
27.3%
2021 12
27.3%
2022 12
27.3%
2023 8
18.2%

Length

2024-03-15T03:17:17.805109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T03:17:18.168333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 12
27.3%
2021 12
27.3%
2022 12
27.3%
2023 8
18.2%

날짜(월)
Real number (ℝ)

Distinct12
Distinct (%)27.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.1363636
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size524.0 B
2024-03-15T03:17:18.494210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median6
Q39
95-th percentile11.85
Maximum12
Range11
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.4003482
Coefficient of variation (CV)0.55413082
Kurtosis-1.1054834
Mean6.1363636
Median Absolute Deviation (MAD)3
Skewness0.14159343
Sum270
Variance11.562368
MonotonicityNot monotonic
2024-03-15T03:17:18.913737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 4
9.1%
2 4
9.1%
3 4
9.1%
4 4
9.1%
5 4
9.1%
6 4
9.1%
7 4
9.1%
8 4
9.1%
9 3
6.8%
10 3
6.8%
Other values (2) 6
13.6%
ValueCountFrequency (%)
1 4
9.1%
2 4
9.1%
3 4
9.1%
4 4
9.1%
5 4
9.1%
6 4
9.1%
7 4
9.1%
8 4
9.1%
9 3
6.8%
10 3
6.8%
ValueCountFrequency (%)
12 3
6.8%
11 3
6.8%
10 3
6.8%
9 3
6.8%
8 4
9.1%
7 4
9.1%
6 4
9.1%
5 4
9.1%
4 4
9.1%
3 4
9.1%

코로나19 확진자수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct32
Distinct (%)72.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean955.36364
Minimum0
Maximum10229
Zeros6
Zeros (%)13.6%
Negative0
Negative (%)0.0%
Memory size524.0 B
2024-03-15T03:17:19.279156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median41.5
Q31495.5
95-th percentile4414.75
Maximum10229
Range10229
Interquartile range (IQR)1493.5

Descriptive statistics

Standard deviation1902.0797
Coefficient of variation (CV)1.9909484
Kurtosis13.432021
Mean955.36364
Median Absolute Deviation (MAD)41.5
Skewness3.3589832
Sum42036
Variance3617907.2
MonotonicityNot monotonic
2024-03-15T03:17:19.655010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
0 6
 
13.6%
1 4
 
9.1%
4 3
 
6.8%
3 2
 
4.5%
2 2
 
4.5%
522 1
 
2.3%
1480 1
 
2.3%
2065 1
 
2.3%
2481 1
 
2.3%
1542 1
 
2.3%
Other values (22) 22
50.0%
ValueCountFrequency (%)
0 6
13.6%
1 4
9.1%
2 2
 
4.5%
3 2
 
4.5%
4 3
6.8%
8 1
 
2.3%
11 1
 
2.3%
13 1
 
2.3%
15 1
 
2.3%
19 1
 
2.3%
ValueCountFrequency (%)
10229 1
2.3%
5719 1
2.3%
4756 1
2.3%
2481 1
2.3%
2178 1
2.3%
2065 1
2.3%
1997 1
2.3%
1902 1
2.3%
1771 1
2.3%
1611 1
2.3%

코로나19 사망자수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct10
Distinct (%)22.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.75
Minimum0
Maximum14
Zeros26
Zeros (%)59.1%
Negative0
Negative (%)0.0%
Memory size524.0 B
2024-03-15T03:17:19.841950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile8.55
Maximum14
Range14
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.2070054
Coefficient of variation (CV)1.8325745
Kurtosis6.1751474
Mean1.75
Median Absolute Deviation (MAD)0
Skewness2.4577494
Sum77
Variance10.284884
MonotonicityNot monotonic
2024-03-15T03:17:20.064723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 26
59.1%
1 4
 
9.1%
2 4
 
9.1%
4 2
 
4.5%
3 2
 
4.5%
5 2
 
4.5%
6 1
 
2.3%
9 1
 
2.3%
12 1
 
2.3%
14 1
 
2.3%
ValueCountFrequency (%)
0 26
59.1%
1 4
 
9.1%
2 4
 
9.1%
3 2
 
4.5%
4 2
 
4.5%
5 2
 
4.5%
6 1
 
2.3%
9 1
 
2.3%
12 1
 
2.3%
14 1
 
2.3%
ValueCountFrequency (%)
14 1
 
2.3%
12 1
 
2.3%
9 1
 
2.3%
6 1
 
2.3%
5 2
 
4.5%
4 2
 
4.5%
3 2
 
4.5%
2 4
 
9.1%
1 4
 
9.1%
0 26
59.1%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size480.0 B
2024-02-23
44 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-02-23
2nd row2024-02-23
3rd row2024-02-23
4th row2024-02-23
5th row2024-02-23

Common Values

ValueCountFrequency (%)
2024-02-23 44
100.0%

Length

2024-03-15T03:17:20.442676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T03:17:20.629097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-02-23 44
100.0%

Interactions

2024-03-15T03:17:14.804146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:17:12.421141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:17:13.257361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:17:13.880824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:17:15.058390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:17:12.655006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:17:13.395063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:17:14.054744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:17:15.359367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:17:12.894740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:17:13.588150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:17:14.256755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:17:15.614931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:17:13.097000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:17:13.727826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:17:14.531577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T03:17:20.744303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연변날짜(년)날짜(월)코로나19 확진자수코로나19 사망자수
연변1.0000.9640.0000.2880.584
날짜(년)0.9641.0000.0000.5490.710
날짜(월)0.0000.0001.0000.1770.000
코로나19 확진자수0.2880.5490.1771.0000.860
코로나19 사망자수0.5840.7100.0000.8601.000
2024-03-15T03:17:20.918064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연변날짜(월)코로나19 확진자수코로나19 사망자수날짜(년)
연변1.0000.1010.8370.5000.830
날짜(월)0.1011.0000.185-0.0940.000
코로나19 확진자수0.8370.1851.0000.6840.373
코로나19 사망자수0.500-0.0940.6841.0000.359
날짜(년)0.8300.0000.3730.3591.000

Missing values

2024-03-15T03:17:15.976469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T03:17:16.497287image/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

연변날짜(년)날짜(월)코로나19 확진자수코로나19 사망자수데이터기준일
0120201002024-02-23
1220202202024-02-23
2320203112024-02-23
3420204102024-02-23
4520205002024-02-23
5620206002024-02-23
6720207002024-02-23
7820208302024-02-23
8920209302024-02-23
910202010102024-02-23
연변날짜(년)날짜(월)코로나19 확진자수코로나19 사망자수데이터기준일
3435202211206512024-02-23
3536202212248132024-02-23
363720231154242024-02-23
37382023252222024-02-23
38392023349502024-02-23
39402023439322024-02-23
40412023554702024-02-23
41422023653912024-02-23
424320237115102024-02-23
434420238177122024-02-23