Overview

Dataset statistics

Number of variables7
Number of observations23
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 KiB
Average record size in memory64.7 B

Variable types

Categorical5
Text1
Numeric1

Dataset

Description2020, 2021, 2022년 각 동별로 나타내는 무연고 사망자 수를 집계하는 통계자료임.(구분, 동별, 2020년, 2021, 2022년)
Author대구광역시 달서구
URLhttps://www.data.go.kr/data/15107648/fileData.do

Alerts

구분 has constant value ""Constant
관리부서 has constant value ""Constant
기준일자 has constant value ""Constant
동별 has unique valuesUnique
2022년 has 8 (34.8%) zerosZeros

Reproduction

Analysis started2023-12-12 17:53:20.526349
Analysis finished2023-12-12 17:53:21.175589
Duration0.65 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

CONSTANT 

Distinct1
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
무연고 사망자
23 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row무연고 사망자
2nd row무연고 사망자
3rd row무연고 사망자
4th row무연고 사망자
5th row무연고 사망자

Common Values

ValueCountFrequency (%)
무연고 사망자 23
100.0%

Length

2023-12-13T02:53:21.582782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:53:21.715090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
무연고 23
50.0%
사망자 23
50.0%

동별
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-13T02:53:21.940571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length3.6086957
Min length2

Characters and Unicode

Total characters83
Distinct characters32
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)100.0%

Sample

1st row성당동
2nd row두류1.2동
3rd row두류3동
4th row본리동
5th row감삼동
ValueCountFrequency (%)
성당동 1
 
4.3%
월성1동 1
 
4.3%
송현2동 1
 
4.3%
송현1동 1
 
4.3%
도원동 1
 
4.3%
상인3동 1
 
4.3%
상인2동 1
 
4.3%
상인1동 1
 
4.3%
유천동 1
 
4.3%
진천동 1
 
4.3%
Other values (13) 13
56.5%
2023-12-13T02:53:22.371535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 23
27.7%
1 6
 
7.2%
2 6
 
7.2%
성 3
 
3.6%
인 3
 
3.6%
상 3
 
3.6%
당 2
 
2.4%
송 2
 
2.4%
천 2
 
2.4%
월 2
 
2.4%
Other values (22) 31
37.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 68
81.9%
Decimal Number 14
 
16.9%
Other Punctuation 1
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 23
33.8%
성 3
 
4.4%
인 3
 
4.4%
상 3
 
4.4%
당 2
 
2.9%
송 2
 
2.9%
천 2
 
2.9%
월 2
 
2.9%
곡 2
 
2.9%
이 2
 
2.9%
Other values (18) 24
35.3%
Decimal Number
ValueCountFrequency (%)
1 6
42.9%
2 6
42.9%
3 2
 
14.3%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 68
81.9%
Common 15
 
18.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 23
33.8%
성 3
 
4.4%
인 3
 
4.4%
상 3
 
4.4%
당 2
 
2.9%
송 2
 
2.9%
천 2
 
2.9%
월 2
 
2.9%
곡 2
 
2.9%
이 2
 
2.9%
Other values (18) 24
35.3%
Common
ValueCountFrequency (%)
1 6
40.0%
2 6
40.0%
3 2
 
13.3%
. 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 68
81.9%
ASCII 15
 
18.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 23
33.8%
성 3
 
4.4%
인 3
 
4.4%
상 3
 
4.4%
당 2
 
2.9%
송 2
 
2.9%
천 2
 
2.9%
월 2
 
2.9%
곡 2
 
2.9%
이 2
 
2.9%
Other values (18) 24
35.3%
ASCII
ValueCountFrequency (%)
1 6
40.0%
2 6
40.0%
3 2
 
13.3%
. 1
 
6.7%

2020년
Categorical

Distinct5
Distinct (%)21.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
1
9 
0
9 
5
2 
2
2 
3
1 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)4.3%

Sample

1st row1
2nd row5
3rd row0
4th row1
5th row0

Common Values

ValueCountFrequency (%)
1 9
39.1%
0 9
39.1%
5 2
 
8.7%
2 2
 
8.7%
3 1
 
4.3%

Length

2023-12-13T02:53:22.526523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:53:22.634934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 9
39.1%
0 9
39.1%
5 2
 
8.7%
2 2
 
8.7%
3 1
 
4.3%

2021년
Categorical

Distinct5
Distinct (%)21.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
0
13 
3
4 
2
3 
1
2 
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)4.3%

Sample

1st row3
2nd row3
3rd row1
4th row1
5th row3

Common Values

ValueCountFrequency (%)
0 13
56.5%
3 4
 
17.4%
2 3
 
13.0%
1 2
 
8.7%
4 1
 
4.3%

Length

2023-12-13T02:53:22.751840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:53:22.870230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 13
56.5%
3 4
 
17.4%
2 3
 
13.0%
1 2
 
8.7%
4 1
 
4.3%

2022년
Real number (ℝ)

ZEROS 

Distinct7
Distinct (%)30.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.826087
Minimum0
Maximum7
Zeros8
Zeros (%)34.8%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-13T02:53:22.981717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile4.9
Maximum7
Range7
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.9224079
Coefficient of variation (CV)1.0527472
Kurtosis0.74705505
Mean1.826087
Median Absolute Deviation (MAD)1
Skewness1.0268507
Sum42
Variance3.6956522
MonotonicityNot monotonic
2023-12-13T02:53:23.085596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 8
34.8%
1 4
17.4%
3 4
17.4%
2 3
 
13.0%
4 2
 
8.7%
5 1
 
4.3%
7 1
 
4.3%
ValueCountFrequency (%)
0 8
34.8%
1 4
17.4%
2 3
 
13.0%
3 4
17.4%
4 2
 
8.7%
5 1
 
4.3%
7 1
 
4.3%
ValueCountFrequency (%)
7 1
 
4.3%
5 1
 
4.3%
4 2
 
8.7%
3 4
17.4%
2 3
 
13.0%
1 4
17.4%
0 8
34.8%

관리부서
Categorical

CONSTANT 

Distinct1
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
복지정책과
23 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
복지정책과 23
100.0%

Length

2023-12-13T02:53:23.238433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:53:23.367615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
복지정책과 23
100.0%

기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-03-20
23 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-03-20
2nd row2023-03-20
3rd row2023-03-20
4th row2023-03-20
5th row2023-03-20

Common Values

ValueCountFrequency (%)
2023-03-20 23
100.0%

Length

2023-12-13T02:53:23.472181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:53:23.558228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-03-20 23
100.0%

Interactions

2023-12-13T02:53:20.776525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T02:53:23.626920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
동별2020년2021년2022년
동별1.0001.0001.0001.000
2020년1.0001.0000.2860.488
2021년1.0000.2861.0000.639
2022년1.0000.4880.6391.000
2023-12-13T02:53:23.759631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2020년2021년
2020년1.0000.051
2021년0.0511.000
2023-12-13T02:53:23.856115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2022년2020년2021년
2022년1.0000.2990.440
2020년0.2991.0000.051
2021년0.4400.0511.000

Missing values

2023-12-13T02:53:20.953544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:53:21.107829image/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

구분동별2020년2021년2022년관리부서기준일자
0무연고 사망자성당동135복지정책과2023-03-20
1무연고 사망자두류1.2동532복지정책과2023-03-20
2무연고 사망자두류3동011복지정책과2023-03-20
3무연고 사망자본리동110복지정책과2023-03-20
4무연고 사망자감삼동033복지정책과2023-03-20
5무연고 사망자죽전동100복지정책과2023-03-20
6무연고 사망자장기동104복지정책과2023-03-20
7무연고 사망자용산1동003복지정책과2023-03-20
8무연고 사망자용산2동101복지정책과2023-03-20
9무연고 사망자이곡1동101복지정책과2023-03-20
구분동별2020년2021년2022년관리부서기준일자
13무연고 사망자월성2동522복지정책과2023-03-20
14무연고 사망자진천동001복지정책과2023-03-20
15무연고 사망자유천동000복지정책과2023-03-20
16무연고 사망자상인1동100복지정책과2023-03-20
17무연고 사망자상인2동100복지정책과2023-03-20
18무연고 사망자상인3동233복지정책과2023-03-20
19무연고 사망자도원동020복지정책과2023-03-20
20무연고 사망자송현1동102복지정책과2023-03-20
21무연고 사망자송현2동323복지정책과2023-03-20
22무연고 사망자본동204복지정책과2023-03-20