Overview

Dataset statistics

Number of variables7
Number of observations30
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.9 KiB
Average record size in memory64.4 B

Variable types

Categorical2
DateTime1
Numeric4

Dataset

Description2020년 2월부터의 대구광역시 북구 관내 코로나19 월별 확진자 및 사망자 현황(발생연도, 발생월, 확진자 수, 사망자 수, 누적 확진자 수, 누적 사망자 수 등) 정보를 제공합니다.
Author대구광역시 북구
URLhttps://www.data.go.kr/data/15098844/fileData.do

Alerts

시군구 has constant value ""Constant
데이터기준일자 has constant value ""Constant
확진자 수(명) is highly overall correlated with 사망자 수(명) and 2 other fieldsHigh correlation
사망자 수(명) is highly overall correlated with 확진자 수(명)High correlation
누적 확진자 수(명) is highly overall correlated with 확진자 수(명) and 1 other fieldsHigh correlation
누적 사망자 수(명) is highly overall correlated with 확진자 수(명) and 1 other fieldsHigh correlation
발생연월 has unique valuesUnique
누적 확진자 수(명) has unique valuesUnique
사망자 수(명) has 10 (33.3%) zerosZeros

Reproduction

Analysis started2023-12-12 15:52:24.170702
Analysis finished2023-12-12 15:52:26.240978
Duration2.07 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
대구광역시 북구
30 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대구광역시 북구
2nd row대구광역시 북구
3rd row대구광역시 북구
4th row대구광역시 북구
5th row대구광역시 북구

Common Values

ValueCountFrequency (%)
대구광역시 북구 30
100.0%

Length

2023-12-13T00:52:26.320560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:52:26.461445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대구광역시 30
50.0%
북구 30
50.0%

발생연월
Date

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2020-02-01 00:00:00
Maximum2022-07-01 00:00:00
2023-12-13T00:52:26.606289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:52:26.922968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)

확진자 수(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4372.7333
Minimum2
Maximum63188
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-13T00:52:27.123101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile5.35
Q120
median168.5
Q3659
95-th percentile22018.5
Maximum63188
Range63186
Interquartile range (IQR)639

Descriptive statistics

Standard deviation12626.11
Coefficient of variation (CV)2.8874639
Kurtosis17.3158
Mean4372.7333
Median Absolute Deviation (MAD)161
Skewness4.0056379
Sum131182
Variance1.5941864 × 108
MonotonicityNot monotonic
2023-12-13T00:52:27.317139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
8 2
 
6.7%
345 1
 
3.3%
222 1
 
3.3%
8902 1
 
3.3%
2788 1
 
3.3%
8939 1
 
3.3%
29421 1
 
3.3%
63188 1
 
3.3%
12971 1
 
3.3%
1383 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
2 1
3.3%
4 1
3.3%
7 1
3.3%
8 2
6.7%
9 1
3.3%
10 1
3.3%
11 1
3.3%
47 1
3.3%
51 1
3.3%
57 1
3.3%
ValueCountFrequency (%)
63188 1
3.3%
29421 1
3.3%
12971 1
3.3%
8939 1
3.3%
8902 1
3.3%
2788 1
3.3%
1383 1
3.3%
733 1
3.3%
437 1
3.3%
420 1
3.3%

사망자 수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct12
Distinct (%)40.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.1333333
Minimum0
Maximum108
Zeros10
Zeros (%)33.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-13T00:52:27.514925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q34
95-th percentile40.4
Maximum108
Range108
Interquartile range (IQR)4

Descriptive statistics

Standard deviation21.535429
Coefficient of variation (CV)2.6477987
Kurtosis17.107795
Mean8.1333333
Median Absolute Deviation (MAD)1
Skewness4.0040518
Sum244
Variance463.77471
MonotonicityNot monotonic
2023-12-13T00:52:27.685462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 10
33.3%
1 7
23.3%
3 3
 
10.0%
4 2
 
6.7%
9 1
 
3.3%
6 1
 
3.3%
2 1
 
3.3%
10 1
 
3.3%
25 1
 
3.3%
108 1
 
3.3%
Other values (2) 2
 
6.7%
ValueCountFrequency (%)
0 10
33.3%
1 7
23.3%
2 1
 
3.3%
3 3
 
10.0%
4 2
 
6.7%
6 1
 
3.3%
7 1
 
3.3%
9 1
 
3.3%
10 1
 
3.3%
25 1
 
3.3%
ValueCountFrequency (%)
108 1
 
3.3%
53 1
 
3.3%
25 1
 
3.3%
10 1
 
3.3%
9 1
 
3.3%
7 1
 
3.3%
6 1
 
3.3%
4 2
6.7%
3 3
10.0%
2 1
 
3.3%

누적 확진자 수(명)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20590.267
Minimum345
Maximum131182
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-13T00:52:27.888102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum345
5-th percentile786.5
Q1824.75
median1223.5
Q33406.75
95-th percentile121025.4
Maximum131182
Range130837
Interquartile range (IQR)2582

Descriptive statistics

Standard deviation42720.005
Coefficient of variation (CV)2.074767
Kurtosis2.1952681
Mean20590.267
Median Absolute Deviation (MAD)430.5
Skewness1.9676297
Sum617708
Variance1.8249988 × 109
MonotonicityStrictly increasing
2023-12-13T00:52:28.103951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
345 1
 
3.3%
1368 1
 
3.3%
131182 1
 
3.3%
122280 1
 
3.3%
119492 1
 
3.3%
110553 1
 
3.3%
81132 1
 
3.3%
17944 1
 
3.3%
4973 1
 
3.3%
3590 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
345 1
3.3%
782 1
3.3%
792 1
3.3%
794 1
3.3%
802 1
3.3%
806 1
3.3%
815 1
3.3%
822 1
3.3%
833 1
3.3%
841 1
3.3%
ValueCountFrequency (%)
131182 1
3.3%
122280 1
3.3%
119492 1
3.3%
110553 1
3.3%
81132 1
3.3%
17944 1
3.3%
4973 1
3.3%
3590 1
3.3%
2857 1
3.3%
2437 1
3.3%

누적 사망자 수(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59.666667
Minimum1
Maximum248
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-13T00:52:28.316311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile12.7
Q119
median26.5
Q342
95-th percentile242.2
Maximum248
Range247
Interquartile range (IQR)23

Descriptive statistics

Standard deviation78.72621
Coefficient of variation (CV)1.3194337
Kurtosis1.7860996
Mean59.666667
Median Absolute Deviation (MAD)7.5
Skewness1.8488147
Sum1790
Variance6197.8161
MonotonicityIncreasing
2023-12-13T00:52:28.497296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
19 6
20.0%
28 4
 
13.3%
42 2
 
6.7%
20 2
 
6.7%
1 1
 
3.3%
248 1
 
3.3%
244 1
 
3.3%
240 1
 
3.3%
233 1
 
3.3%
180 1
 
3.3%
Other values (10) 10
33.3%
ValueCountFrequency (%)
1 1
 
3.3%
10 1
 
3.3%
16 1
 
3.3%
18 1
 
3.3%
19 6
20.0%
20 2
 
6.7%
21 1
 
3.3%
24 1
 
3.3%
25 1
 
3.3%
28 4
13.3%
ValueCountFrequency (%)
248 1
3.3%
244 1
3.3%
240 1
3.3%
233 1
3.3%
180 1
3.3%
72 1
3.3%
47 1
3.3%
42 2
6.7%
32 1
3.3%
29 1
3.3%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2022-08-18
30 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-08-18
2nd row2022-08-18
3rd row2022-08-18
4th row2022-08-18
5th row2022-08-18

Common Values

ValueCountFrequency (%)
2022-08-18 30
100.0%

Length

2023-12-13T00:52:28.685051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:52:28.837107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-08-18 30
100.0%

Interactions

2023-12-13T00:52:25.538879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:52:24.308250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:52:24.649485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:52:25.072067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:52:25.671658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:52:24.380672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:52:24.737758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:52:25.176769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:52:25.791566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:52:24.462856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:52:24.846998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:52:25.279832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:52:25.920886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:52:24.552423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:52:24.974009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:52:25.404095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:52:28.918775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
발생연월확진자 수(명)사망자 수(명)누적 확진자 수(명)누적 사망자 수(명)
발생연월1.0001.0001.0001.0001.000
확진자 수(명)1.0001.0001.0000.9990.980
사망자 수(명)1.0001.0001.0001.0000.856
누적 확진자 수(명)1.0000.9991.0001.0000.988
누적 사망자 수(명)1.0000.9800.8560.9881.000
2023-12-13T00:52:29.056343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
확진자 수(명)사망자 수(명)누적 확진자 수(명)누적 사망자 수(명)
확진자 수(명)1.0000.5840.7730.769
사망자 수(명)0.5841.0000.3870.416
누적 확진자 수(명)0.7730.3871.0000.995
누적 사망자 수(명)0.7690.4160.9951.000

Missing values

2023-12-13T00:52:26.057124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:52:26.191160image/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

시군구발생연월확진자 수(명)사망자 수(명)누적 확진자 수(명)누적 사망자 수(명)데이터기준일자
0대구광역시 북구2020-02345134512022-08-18
1대구광역시 북구2020-034379782102022-08-18
2대구광역시 북구2020-04106792162022-08-18
3대구광역시 북구2020-0522794182022-08-18
4대구광역시 북구2020-0681802192022-08-18
5대구광역시 북구2020-0740806192022-08-18
6대구광역시 북구2020-0890815192022-08-18
7대구광역시 북구2020-0970822192022-08-18
8대구광역시 북구2020-10110833192022-08-18
9대구광역시 북구2020-1180841192022-08-18
시군구발생연월확진자 수(명)사망자 수(명)누적 확진자 수(명)누적 사망자 수(명)데이터기준일자
20대구광역시 북구2021-1024332437322022-08-18
21대구광역시 북구2021-11420102857422022-08-18
22대구광역시 북구2021-1273303590422022-08-18
23대구광역시 북구2022-01138314973472022-08-18
24대구광역시 북구2022-02129712517944722022-08-18
25대구광역시 북구2022-0363188108811321802022-08-18
26대구광역시 북구2022-0429421531105532332022-08-18
27대구광역시 북구2022-05893971194922402022-08-18
28대구광역시 북구2022-06278841222802442022-08-18
29대구광역시 북구2022-07890241311822482022-08-18