Overview

Dataset statistics

Number of variables6
Number of observations1300
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory66.1 KiB
Average record size in memory52.1 B

Variable types

Categorical2
Text1
Numeric3

Dataset

Description김해시에서 통계기반 도시현황 파악을 위해 개발한 통계지수 중 하나로서, 통계연도, 시도명, 시군구명, 총사망자수(명), 안전사고 사망자수(명), 안전사고 사망률(퍼센트)로 구성되어 있습니다. 김해시 중심의 통계지수로서, 데이터 수집, 가공 등의 어려움으로 김해시 외 지역의 정보는 누락될 수 있습니다.
Author경상남도 김해시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15110161

Alerts

총사망자수(명) is highly overall correlated with 안전사고 사망자수(명) and 1 other fieldsHigh correlation
안전사고 사망자수(명) is highly overall correlated with 총사망자수(명)High correlation
안전사고 사망률(퍼센트) is highly overall correlated with 총사망자수(명)High correlation

Reproduction

Analysis started2023-12-11 00:02:29.567050
Analysis finished2023-12-11 00:02:31.153043
Duration1.59 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

통계연도
Categorical

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size10.3 KiB
2016
260 
2017
260 
2018
260 
2019
260 
2020
260 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2016
2nd row2016
3rd row2016
4th row2016
5th row2016

Common Values

ValueCountFrequency (%)
2016 260
20.0%
2017 260
20.0%
2018 260
20.0%
2019 260
20.0%
2020 260
20.0%

Length

2023-12-11T09:02:31.220546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:02:31.329761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2016 260
20.0%
2017 260
20.0%
2018 260
20.0%
2019 260
20.0%
2020 260
20.0%

시도명
Categorical

Distinct16
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size10.3 KiB
경기도
240 
서울특별시
125 
경상북도
125 
경상남도
115 
전라남도
110 
Other values (11)
585 

Length

Max length7
Median length5
Mean length4.0538462
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 240
18.5%
서울특별시 125
9.6%
경상북도 125
9.6%
경상남도 115
8.8%
전라남도 110
8.5%
강원도 90
 
6.9%
충청남도 85
 
6.5%
부산광역시 80
 
6.2%
전라북도 80
 
6.2%
충청북도 75
 
5.8%
Other values (6) 175
13.5%

Length

2023-12-11T09:02:31.462434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 240
18.5%
서울특별시 125
9.6%
경상북도 125
9.6%
경상남도 115
8.8%
전라남도 110
8.5%
강원도 90
 
6.9%
충청남도 85
 
6.5%
부산광역시 80
 
6.2%
전라북도 80
 
6.2%
충청북도 75
 
5.8%
Other values (6) 175
13.5%
Distinct236
Distinct (%)18.2%
Missing0
Missing (%)0.0%
Memory size10.3 KiB
2023-12-11T09:02:31.820021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.9623077
Min length2

Characters and Unicode

Total characters3851
Distinct characters141
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row종로구
2nd row중구
3rd row용산구
4th row성동구
5th row광진구
ValueCountFrequency (%)
중구 30
 
2.3%
동구 30
 
2.3%
남구 27
 
2.1%
북구 25
 
1.9%
서구 25
 
1.9%
강서구 10
 
0.8%
고성군 10
 
0.8%
남원시 5
 
0.4%
덕진구 5
 
0.4%
군산시 5
 
0.4%
Other values (226) 1128
86.8%
2023-12-11T09:02:32.279944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
530
 
13.8%
425
 
11.0%
390
 
10.1%
110
 
2.9%
110
 
2.9%
100
 
2.6%
100
 
2.6%
95
 
2.5%
95
 
2.5%
80
 
2.1%
Other values (131) 1816
47.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3851
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
530
 
13.8%
425
 
11.0%
390
 
10.1%
110
 
2.9%
110
 
2.9%
100
 
2.6%
100
 
2.6%
95
 
2.5%
95
 
2.5%
80
 
2.1%
Other values (131) 1816
47.2%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3851
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
530
 
13.8%
425
 
11.0%
390
 
10.1%
110
 
2.9%
110
 
2.9%
100
 
2.6%
100
 
2.6%
95
 
2.5%
95
 
2.5%
80
 
2.1%
Other values (131) 1816
47.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3851
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
530
 
13.8%
425
 
11.0%
390
 
10.1%
110
 
2.9%
110
 
2.9%
100
 
2.6%
100
 
2.6%
95
 
2.5%
95
 
2.5%
80
 
2.1%
Other values (131) 1816
47.2%

총사망자수(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct987
Distinct (%)75.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1283.8631
Minimum63
Maximum5627
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.6 KiB
2023-12-11T09:02:32.420074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum63
5-th percentile328.8
Q1647.75
median1134
Q31659
95-th percentile2760.35
Maximum5627
Range5564
Interquartile range (IQR)1011.25

Descriptive statistics

Standard deviation861.50198
Coefficient of variation (CV)0.67102325
Kurtosis4.1087583
Mean1283.8631
Median Absolute Deviation (MAD)500.5
Skewness1.663569
Sum1669022
Variance742185.66
MonotonicityNot monotonic
2023-12-11T09:02:32.543975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
994 5
 
0.4%
710 4
 
0.3%
1214 4
 
0.3%
1110 4
 
0.3%
1145 4
 
0.3%
897 4
 
0.3%
669 4
 
0.3%
1094 4
 
0.3%
1144 4
 
0.3%
1192 4
 
0.3%
Other values (977) 1259
96.8%
ValueCountFrequency (%)
63 1
0.1%
64 1
0.1%
67 1
0.1%
70 1
0.1%
76 1
0.1%
146 1
0.1%
167 1
0.1%
173 1
0.1%
174 1
0.1%
175 1
0.1%
ValueCountFrequency (%)
5627 1
0.1%
5615 1
0.1%
5473 1
0.1%
5362 1
0.1%
5294 1
0.1%
5119 1
0.1%
4993 1
0.1%
4939 1
0.1%
4913 1
0.1%
4857 1
0.1%

안전사고 사망자수(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct115
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.356154
Minimum0
Maximum170
Zeros1
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size11.6 KiB
2023-12-11T09:02:32.683502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10
Q120
median32
Q347
95-th percentile81
Maximum170
Range170
Interquartile range (IQR)27

Descriptive statistics

Standard deviation23.057616
Coefficient of variation (CV)0.63421494
Kurtosis4.4306855
Mean36.356154
Median Absolute Deviation (MAD)13
Skewness1.6580653
Sum47263
Variance531.65366
MonotonicityNot monotonic
2023-12-11T09:02:32.812917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24 41
 
3.2%
17 36
 
2.8%
21 36
 
2.8%
31 32
 
2.5%
37 32
 
2.5%
11 32
 
2.5%
20 30
 
2.3%
33 29
 
2.2%
26 29
 
2.2%
27 29
 
2.2%
Other values (105) 974
74.9%
ValueCountFrequency (%)
0 1
 
0.1%
1 1
 
0.1%
2 3
 
0.2%
3 1
 
0.1%
4 5
 
0.4%
5 4
 
0.3%
6 8
0.6%
7 11
0.8%
8 9
0.7%
9 15
1.2%
ValueCountFrequency (%)
170 1
0.1%
156 1
0.1%
155 1
0.1%
154 1
0.1%
153 1
0.1%
147 1
0.1%
144 1
0.1%
139 1
0.1%
133 2
0.2%
127 1
0.1%

안전사고 사망률(퍼센트)
Real number (ℝ)

HIGH CORRELATION 

Distinct1105
Distinct (%)85.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.642408
Minimum0
Maximum100.11
Zeros1
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size11.6 KiB
2023-12-11T09:02:32.958424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile7.768
Q112.4075
median18.165
Q334.455
95-th percentile58.6025
Maximum100.11
Range100.11
Interquartile range (IQR)22.0475

Descriptive statistics

Standard deviation16.21239
Coefficient of variation (CV)0.6579061
Kurtosis0.76967037
Mean24.642408
Median Absolute Deviation (MAD)7.735
Skewness1.1578204
Sum32035.13
Variance262.8416
MonotonicityNot monotonic
2023-12-11T09:02:33.097574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11.9 5
 
0.4%
12.79 5
 
0.4%
16.85 4
 
0.3%
11.59 4
 
0.3%
9.72 4
 
0.3%
11.96 4
 
0.3%
15.29 3
 
0.2%
13.56 3
 
0.2%
12.56 3
 
0.2%
17.97 3
 
0.2%
Other values (1095) 1262
97.1%
ValueCountFrequency (%)
0.0 1
0.1%
2.83 1
0.1%
3.54 1
0.1%
4.33 1
0.1%
4.37 1
0.1%
4.6 1
0.1%
4.63 1
0.1%
4.7 1
0.1%
4.75 2
0.2%
4.77 1
0.1%
ValueCountFrequency (%)
100.11 1
0.1%
88.03 1
0.1%
82.19 1
0.1%
80.21 1
0.1%
77.93 1
0.1%
77.92 1
0.1%
77.14 1
0.1%
75.51 1
0.1%
75.3 1
0.1%
74.62 1
0.1%

Interactions

2023-12-11T09:02:30.633868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:02:29.938471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:02:30.299855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:02:30.731490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:02:30.054911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:02:30.407763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:02:30.832117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/