Overview

Dataset statistics

Number of variables5
Number of observations1140
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory46.9 KiB
Average record size in memory42.1 B

Variable types

DateTime2
Numeric2
Categorical1

Dataset

Description이 파일은 일별, 누적별로 대구광역시 달서구 코로나19 확진자 발생 현황을 날짜 및 확진자 수로 설명함. (작성날짜 기준)
URLhttps://www.data.go.kr/data/15080620/fileData.do

Alerts

관리부서 has constant value ""Constant
기준일자 has constant value ""Constant
확진자수 is highly overall correlated with 누적확진자수High correlation
누적확진자수 is highly overall correlated with 확진자수High correlation
날짜 has unique valuesUnique
확진자수 has 214 (18.8%) zerosZeros

Reproduction

Analysis started2023-12-12 07:55:18.568481
Analysis finished2023-12-12 07:55:19.256034
Duration0.69 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

날짜
Date

UNIQUE 

Distinct1140
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
Minimum2020-02-20 00:00:00
Maximum2023-04-04 00:00:00
2023-12-12T16:55:19.323137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:55:19.762877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

확진자수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct408
Distinct (%)35.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean269.92018
Minimum0
Maximum5952
Zeros214
Zeros (%)18.8%
Negative0
Negative (%)0.0%
Memory size10.1 KiB
2023-12-12T16:55:19.900373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median13
Q3250.25
95-th percentile1356.65
Maximum5952
Range5952
Interquartile range (IQR)249.25

Descriptive statistics

Standard deviation615.42864
Coefficient of variation (CV)2.2800394
Kurtosis19.967776
Mean269.92018
Median Absolute Deviation (MAD)13
Skewness3.98728
Sum307709
Variance378752.41
MonotonicityNot monotonic
2023-12-12T16:55:20.010038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 214
 
18.8%
1 97
 
8.5%
2 49
 
4.3%
3 36
 
3.2%
4 35
 
3.1%
5 27
 
2.4%
9 23
 
2.0%
7 18
 
1.6%
10 16
 
1.4%
6 16
 
1.4%
Other values (398) 609
53.4%
ValueCountFrequency (%)
0 214
18.8%
1 97
8.5%
2 49
 
4.3%
3 36
 
3.2%
4 35
 
3.1%
5 27
 
2.4%
6 16
 
1.4%
7 18
 
1.6%
8 14
 
1.2%
9 23
 
2.0%
ValueCountFrequency (%)
5952 1
0.1%
4766 1
0.1%
4511 1
0.1%
4107 1
0.1%
4080 1
0.1%
3503 1
0.1%
3454 1
0.1%
3439 1
0.1%
3400 1
0.1%
3394 1
0.1%

누적확진자수
Real number (ℝ)

HIGH CORRELATION 

Distinct926
Distinct (%)81.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean80057.163
Minimum13
Maximum307709
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.1 KiB
2023-12-12T16:55:20.122350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum13
5-th percentile1606
Q11690.5
median3284
Q3176408
95-th percentile301536.85
Maximum307709
Range307696
Interquartile range (IQR)174717.5

Descriptive statistics

Standard deviation112711.55
Coefficient of variation (CV)1.4078884
Kurtosis-0.81105716
Mean80057.163
Median Absolute Deviation (MAD)1657.5
Skewness0.95399128
Sum91265166
Variance1.2703893 × 1010
MonotonicityIncreasing
2023-12-12T16:55:20.236730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1674 22
 
1.9%
1640 13
 
1.1%
1644 13
 
1.1%
1682 12
 
1.1%
1645 11
 
1.0%
1672 10
 
0.9%
1634 9
 
0.8%
1673 9
 
0.8%
1621 8
 
0.7%
1606 6
 
0.5%
Other values (916) 1027
90.1%
ValueCountFrequency (%)
13 1
0.1%
28 1
0.1%
43 1
0.1%
52 1
0.1%
90 1
0.1%
145 1
0.1%
226 1
0.1%
234 1
0.1%
308 1
0.1%
459 1
0.1%
ValueCountFrequency (%)
307709 1
0.1%
307600 1
0.1%
307573 1
0.1%
307483 1
0.1%
307387 1
0.1%
307289 1
0.1%
307202 1
0.1%
307117 1
0.1%
307006 1
0.1%
306985 1
0.1%

관리부서
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
보건행정과
1140 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
보건행정과 1140
100.0%

Length

2023-12-12T16:55:20.348684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:55:20.436748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
보건행정과 1140
100.0%

기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
Minimum2023-04-04 00:00:00
Maximum2023-04-04 00:00:00
2023-12-12T16:55:20.504875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:55:20.623667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T16:55:18.908212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:55:18.693118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:55:18.995113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:55:18.791168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T16:55:20.692724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
확진자수누적확진자수
확진자수1.0000.859
누적확진자수0.8591.000
2023-12-12T16:55:20.769181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
확진자수누적확진자수
확진자수1.0000.820
누적확진자수0.8201.000

Missing values

2023-12-12T16:55:19.110909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:55:19.214991image/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

날짜확진자수누적확진자수관리부서기준일자
02020-02-201313보건행정과2023-04-04
12020-02-211528보건행정과2023-04-04
22020-02-221543보건행정과2023-04-04
32020-02-23952보건행정과2023-04-04
42020-02-243890보건행정과2023-04-04
52020-02-2555145보건행정과2023-04-04
62020-02-2681226보건행정과2023-04-04
72020-02-278234보건행정과2023-04-04
82020-02-2874308보건행정과2023-04-04
92020-02-29151459보건행정과2023-04-04
날짜확진자수누적확진자수관리부서기준일자
11302023-03-2678306985보건행정과2023-04-04
11312023-03-2721307006보건행정과2023-04-04
11322023-03-28111307117보건행정과2023-04-04
11332023-03-2985307202보건행정과2023-04-04
11342023-03-3087307289보건행정과2023-04-04
11352023-03-3198307387보건행정과2023-04-04
11362023-04-0196307483보건행정과2023-04-04
11372023-04-0290307573보건행정과2023-04-04
11382023-04-0327307600보건행정과2023-04-04
11392023-04-04109307709보건행정과2023-04-04