Overview

Dataset statistics

Number of variables4
Number of observations1059
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory35.3 KiB
Average record size in memory34.1 B

Variable types

DateTime2
Numeric2

Dataset

Description인천광역시 남동구 일별 코로나19 확진자수 현황(날짜, 확진자수, 누적확진자수, 데이터기준일자) 자료입니다.
Author인천광역시 남동구
URLhttps://www.data.go.kr/data/15084724/fileData.do

Alerts

확진자수 is highly overall correlated with 누적확진자수High correlation
누적확진자수 is highly overall correlated with 확진자수High correlation
날짜 has unique valuesUnique
확진자수 has 183 (17.3%) zerosZeros

Reproduction

Analysis started2023-12-12 22:30:36.221244
Analysis finished2023-12-12 22:30:37.310730
Duration1.09 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

날짜
Date

UNIQUE 

Distinct1059
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size8.4 KiB
Minimum2020-03-09 00:00:00
Maximum2023-01-31 00:00:00
2023-12-13T07:30:37.636254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:30:37.992623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

확진자수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct373
Distinct (%)35.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean277.91029
Minimum0
Maximum5582
Zeros183
Zeros (%)17.3%
Negative0
Negative (%)0.0%
Memory size9.4 KiB
2023-12-13T07:30:38.154234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median16
Q3263
95-th percentile1313.1
Maximum5582
Range5582
Interquartile range (IQR)262

Descriptive statistics

Standard deviation638.15299
Coefficient of variation (CV)2.2962553
Kurtosis18.673614
Mean277.91029
Median Absolute Deviation (MAD)16
Skewness3.9223209
Sum294307
Variance407239.23
MonotonicityNot monotonic
2023-12-13T07:30:38.286005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 183
 
17.3%
1 93
 
8.8%
2 51
 
4.8%
3 44
 
4.2%
4 26
 
2.5%
5 26
 
2.5%
7 20
 
1.9%
6 14
 
1.3%
12 13
 
1.2%
9 12
 
1.1%
Other values (363) 577
54.5%
ValueCountFrequency (%)
0 183
17.3%
1 93
8.8%
2 51
 
4.8%
3 44
 
4.2%
4 26
 
2.5%
5 26
 
2.5%
6 14
 
1.3%
7 20
 
1.9%
8 10
 
0.9%
9 12
 
1.1%
ValueCountFrequency (%)
5582 1
0.1%
4883 1
0.1%
4702 1
0.1%
4105 1
0.1%
4054 1
0.1%
3990 1
0.1%
3887 1
0.1%
3667 1
0.1%
3504 1
0.1%
3495 1
0.1%

누적확진자수
Real number (ℝ)

HIGH CORRELATION 

Distinct875
Distinct (%)82.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean67088.788
Minimum1
Maximum293599
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.4 KiB
2023-12-13T07:30:38.411384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile13.9
Q1243.5
median1787
Q3173627
95-th percentile266357.3
Maximum293599
Range293598
Interquartile range (IQR)173383.5

Descriptive statistics

Standard deviation100586.82
Coefficient of variation (CV)1.499309
Kurtosis-0.61451413
Mean67088.788
Median Absolute Deviation (MAD)1763
Skewness1.0518462
Sum71047026
Variance1.0117709 × 1010
MonotonicityIncreasing
2023-12-13T07:30:38.597722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
48 23
 
2.2%
4 11
 
1.0%
14 11
 
1.0%
49 10
 
0.9%
127 9
 
0.8%
12 9
 
0.8%
9 9
 
0.8%
44 8
 
0.8%
120 6
 
0.6%
50 6
 
0.6%
Other values (865) 957
90.4%
ValueCountFrequency (%)
1 3
 
0.3%
2 2
 
0.2%
3 1
 
0.1%
4 11
1.0%
5 2
 
0.2%
6 2
 
0.2%
8 1
 
0.1%
9 9
0.8%
10 4
 
0.4%
11 5
0.5%
ValueCountFrequency (%)
293599 1
0.1%
293384 1
0.1%
293206 1
0.1%
293135 1
0.1%
292923 1
0.1%
292698 1
0.1%
292350 1
0.1%
292017 1
0.1%
291810 1
0.1%
291647 1
0.1%

데이터기준일
Date

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.4 KiB
Minimum2022-09-28 00:00:00
Maximum2023-01-31 00:00:00
2023-12-13T07:30:38.745216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:30:38.856597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)

Interactions

2023-12-13T07:30:36.502288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:30:36.328948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:30:36.907935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:30:36.414130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T07:30:38.942548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
확진자수누적확진자수데이터기준일
확진자수1.0000.8720.485
누적확진자수0.8721.0000.998
데이터기준일0.4850.9981.000
2023-12-13T07:30:39.054036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
확진자수누적확진자수
확진자수1.0000.900
누적확진자수0.9001.000

Missing values

2023-12-13T07:30:37.036268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:30:37.168008image/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

날짜확진자수누적확진자수데이터기준일
02020-03-09112022-09-28
12020-03-10012022-09-28
22020-03-11012022-09-28
32020-03-12122022-09-28
42020-03-13022022-09-28
52020-03-14132022-09-28
62020-03-15142022-09-28
72020-03-16042022-09-28
82020-03-17042022-09-28
92020-03-18042022-09-28
날짜확진자수누적확진자수데이터기준일
10492023-01-22972916472023-01-31
10502023-01-231632918102023-01-31
10512023-01-242072920172023-01-31
10522023-01-253332923502023-01-31
10532023-01-263482926982023-01-31
10542023-01-272252929232023-01-31
10552023-01-282122931352023-01-31
10562023-01-29712932062023-01-31
10572023-01-301782933842023-01-31
10582023-01-312152935992023-01-31