Overview

Dataset statistics

Number of variables5
Number of observations36
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.7 KiB
Average record size in memory47.7 B

Variable types

Numeric3
Categorical1
DateTime1

Dataset

Description인천광역시 중구 코로나19 월별 사망자수 현황에 대한 파일 데이터 연번, 연월, 코로나19 사망자 수 및 데이터 기준일자 입력 종합 현황표
Author인천광역시 중구
URLhttps://www.data.go.kr/data/15098738/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
연번 is highly overall correlated with 코로나19 사망자 수 and 1 other fieldsHigh correlation
코로나19 사망자 수 is highly overall correlated with 연번High correlation
날짜(년) is highly overall correlated with 연번High correlation
연번 has unique valuesUnique
코로나19 사망자 수 has 18 (50.0%) zerosZeros

Reproduction

Analysis started2024-06-15 09:45:43.501062
Analysis finished2024-06-15 09:45:47.351021
Duration3.85 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.5
Minimum1
Maximum36
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2024-06-15T18:45:47.805522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.75
Q19.75
median18.5
Q327.25
95-th percentile34.25
Maximum36
Range35
Interquartile range (IQR)17.5

Descriptive statistics

Standard deviation10.535654
Coefficient of variation (CV)0.5694948
Kurtosis-1.2
Mean18.5
Median Absolute Deviation (MAD)9
Skewness0
Sum666
Variance111
MonotonicityStrictly increasing
2024-06-15T18:45:48.324111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
1 1
 
2.8%
20 1
 
2.8%
22 1
 
2.8%
23 1
 
2.8%
24 1
 
2.8%
25 1
 
2.8%
26 1
 
2.8%
27 1
 
2.8%
28 1
 
2.8%
29 1
 
2.8%
Other values (26) 26
72.2%
ValueCountFrequency (%)
1 1
2.8%
2 1
2.8%
3 1
2.8%
4 1
2.8%
5 1
2.8%
6 1
2.8%
7 1
2.8%
8 1
2.8%
9 1
2.8%
10 1
2.8%
ValueCountFrequency (%)
36 1
2.8%
35 1
2.8%
34 1
2.8%
33 1
2.8%
32 1
2.8%
31 1
2.8%
30 1
2.8%
29 1
2.8%
28 1
2.8%
27 1
2.8%

날짜(년)
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size420.0 B
2021
12 
2022
12 
2020
10 
2023

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 (%)
2021 12
33.3%
2022 12
33.3%
2020 10
27.8%
2023 2
 
5.6%

Length

2024-06-15T18:45:48.837272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-06-15T18:45:49.186876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 12
33.3%
2022 12
33.3%
2020 10
27.8%
2023 2
 
5.6%

날짜(월)
Real number (ℝ)

Distinct12
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.5
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2024-06-15T18:45:49.611587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13.75
median6.5
Q39.25
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)5.5

Descriptive statistics

Standard deviation3.5010203
Coefficient of variation (CV)0.5386185
Kurtosis-1.217232
Mean6.5
Median Absolute Deviation (MAD)3
Skewness0
Sum234
Variance12.257143
MonotonicityNot monotonic
2024-06-15T18:45:50.153336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
3 3
8.3%
4 3
8.3%
5 3
8.3%
6 3
8.3%
7 3
8.3%
8 3
8.3%
9 3
8.3%
10 3
8.3%
11 3
8.3%
12 3
8.3%
Other values (2) 6
16.7%
ValueCountFrequency (%)
1 3
8.3%
2 3
8.3%
3 3
8.3%
4 3
8.3%
5 3
8.3%
6 3
8.3%
7 3
8.3%
8 3
8.3%
9 3
8.3%
10 3
8.3%
ValueCountFrequency (%)
12 3
8.3%
11 3
8.3%
10 3
8.3%
9 3
8.3%
8 3
8.3%
7 3
8.3%
6 3
8.3%
5 3
8.3%
4 3
8.3%
3 3
8.3%

코로나19 사망자 수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct13
Distinct (%)36.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.1111111
Minimum0
Maximum61
Zeros18
Zeros (%)50.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2024-06-15T18:45:50.651716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.5
Q35
95-th percentile20.75
Maximum61
Range61
Interquartile range (IQR)5

Descriptive statistics

Standard deviation11.702937
Coefficient of variation (CV)2.289705
Kurtosis15.866703
Mean5.1111111
Median Absolute Deviation (MAD)0.5
Skewness3.7831297
Sum184
Variance136.95873
MonotonicityNot monotonic
2024-06-15T18:45:51.125355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 18
50.0%
1 3
 
8.3%
2 3
 
8.3%
8 2
 
5.6%
5 2
 
5.6%
7 1
 
2.8%
61 1
 
2.8%
35 1
 
2.8%
3 1
 
2.8%
11 1
 
2.8%
Other values (3) 3
 
8.3%
ValueCountFrequency (%)
0 18
50.0%
1 3
 
8.3%
2 3
 
8.3%
3 1
 
2.8%
4 1
 
2.8%
5 2
 
5.6%
7 1
 
2.8%
8 2
 
5.6%
11 1
 
2.8%
12 1
 
2.8%
ValueCountFrequency (%)
61 1
2.8%
35 1
2.8%
16 1
2.8%
12 1
2.8%
11 1
2.8%
8 2
5.6%
7 1
2.8%
5 2
5.6%
4 1
2.8%
3 1
2.8%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
Minimum2023-02-21 00:00:00
Maximum2023-02-21 00:00:00
2024-06-15T18:45:51.591074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-15T18:45:52.015449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-06-15T18:45:45.667638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-15T18:45:43.785212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-15T18:45:44.755466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-15T18:45:45.966367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-15T18:45:44.093281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-15T18:45:45.031692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-15T18:45:46.259168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-15T18:45:44.449645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-06-15T18:45:45.339140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-06-15T18:45:52.265821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번날짜(년)날짜(월)코로나19 사망자 수
연번1.0000.9050.0000.525
날짜(년)0.9051.0000.0000.485
날짜(월)0.0000.0001.0000.328
코로나19 사망자 수0.5250.4850.3281.000
2024-06-15T18:45:52.640751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번날짜(월)코로나19 사망자 수날짜(년)
연번1.0000.0530.8270.745
날짜(월)0.0531.000-0.0810.000
코로나19 사망자 수0.827-0.0811.0000.405
날짜(년)0.7450.0000.4051.000

Missing values

2024-06-15T18:45:46.603105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-06-15T18:45:47.117964image/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

연번날짜(년)날짜(월)코로나19 사망자 수데이터기준일자
012020302023-02-21
122020402023-02-21
232020502023-02-21
342020602023-02-21
452020702023-02-21
562020802023-02-21
672020902023-02-21
7820201002023-02-21
8920201102023-02-21
91020201202023-02-21
연번날짜(년)날짜(월)코로나19 사망자 수데이터기준일자
26272022522023-02-21
27282022622023-02-21
28292022722023-02-21
29302022852023-02-21
30312022982023-02-21
313220221032023-02-21
3233202211112023-02-21
3334202212122023-02-21
343520231162023-02-21
35362023242023-02-21