Overview

Dataset statistics

Number of variables4
Number of observations1315
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory43.8 KiB
Average record size in memory34.1 B

Variable types

Categorical2
Text1
Numeric1

Dataset

Description김해시에서 통계기반 도시현황 파악을 위해 개발한 통계지수 중 하나로서, 통계연도, 시도명, 시군구명, 아동 예방접종률(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=15110153

Reproduction

Analysis started2023-12-11 00:39:12.602522
Analysis finished2023-12-11 00:39:13.108110
Duration0.51 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

통계연도
Categorical

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size10.4 KiB
2017
263 
2018
263 
2019
263 
2020
263 
2021
263 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2017
2nd row2017
3rd row2017
4th row2017
5th row2017

Common Values

ValueCountFrequency (%)
2017 263
20.0%
2018 263
20.0%
2019 263
20.0%
2020 263
20.0%
2021 263
20.0%

Length

2023-12-11T09:39:13.467581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:39:13.585388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017 263
20.0%
2018 263
20.0%
2019 263
20.0%
2020 263
20.0%
2021 263
20.0%

시도명
Categorical

Distinct16
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size10.4 KiB
경기도
255 
서울특별시
125 
경상북도
125 
경상남도
115 
전라남도
110 
Other values (11)
585 

Length

Max length7
Median length5
Mean length4.0418251
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 255
19.4%
서울특별시 125
9.5%
경상북도 125
9.5%
경상남도 115
8.7%
전라남도 110
8.4%
강원도 90
 
6.8%
충청남도 85
 
6.5%
부산광역시 80
 
6.1%
전라북도 80
 
6.1%
충청북도 75
 
5.7%
Other values (6) 175
13.3%

Length

2023-12-11T09:39:13.734696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 255
19.4%
서울특별시 125
9.5%
경상북도 125
9.5%
경상남도 115
8.7%
전라남도 110
8.4%
강원도 90
 
6.8%
충청남도 85
 
6.5%
부산광역시 80
 
6.1%
전라북도 80
 
6.1%
충청북도 75
 
5.7%
Other values (6) 175
13.3%

시군구명
Text

Distinct241
Distinct (%)18.3%
Missing0
Missing (%)0.0%
Memory size10.4 KiB
2023-12-11T09:39:14.100222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length3
Mean length3.4904943
Min length2

Characters and Unicode

Total characters4590
Distinct characters143
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
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
 
2.0%
동구 30
 
2.0%
창원시 30
 
2.0%
서구 25
 
1.7%
북구 25
 
1.7%
남구 25
 
1.7%
청주시 25
 
1.7%
수원시 25
 
1.7%
고양시 20
 
1.3%
성남시 20
 
1.3%
Other values (229) 1235
82.9%
2023-12-11T09:39:14.581218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 565
 
12.3%
구 540
 
11.8%
군 430
 
9.4%
175
 
3.8%
천 135
 
2.9%
주 130
 
2.8%
산 120
 
2.6%
양 120
 
2.6%
성 110
 
2.4%
원 105
 
2.3%
Other values (133) 2160
47.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4415
96.2%
Space Separator 175
 
3.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 565
 
12.8%
구 540
 
12.2%
군 430
 
9.7%
천 135
 
3.1%
주 130
 
2.9%
산 120
 
2.7%
양 120
 
2.7%
성 110
 
2.5%
원 105
 
2.4%
안 100
 
2.3%
Other values (132) 2060
46.7%
Space Separator
ValueCountFrequency (%)
175
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4415
96.2%
Common 175
 
3.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 565
 
12.8%
구 540
 
12.2%
군 430
 
9.7%
천 135
 
3.1%
주 130
 
2.9%
산 120
 
2.7%
양 120
 
2.7%
성 110
 
2.5%
원 105
 
2.4%
안 100
 
2.3%
Other values (132) 2060
46.7%
Common
ValueCountFrequency (%)
175
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4415
96.2%
ASCII 175
 
3.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 565
 
12.8%
구 540
 
12.2%
군 430
 
9.7%
천 135
 
3.1%
주 130
 
2.9%
산 120
 
2.7%
양 120
 
2.7%
성 110
 
2.5%
원 105
 
2.4%
안 100
 
2.3%
Other values (132) 2060
46.7%
ASCII
ValueCountFrequency (%)
175
100.0%

아동 예방접종률(퍼센트)
Real number (ℝ)

Distinct160
Distinct (%)12.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean90.180837
Minimum70.1
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.7 KiB
2023-12-11T09:39:14.755444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum70.1
5-th percentile84.47
Q189.1
median90.6
Q392.1
95-th percentile93.9
Maximum100
Range29.9
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.993562
Coefficient of variation (CV)0.033195101
Kurtosis3.7739629
Mean90.180837
Median Absolute Deviation (MAD)1.5
Skewness-1.3417783
Sum118587.8
Variance8.9614133
MonotonicityNot monotonic
2023-12-11T09:39:14.894589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
90.6 34
 
2.6%
90.9 31
 
2.4%
91.0 31
 
2.4%
90.5 29
 
2.2%
91.3 28
 
2.1%
91.2 28
 
2.1%
89.8 26
 
2.0%
90.1 26
 
2.0%
91.9 25
 
1.9%
91.1 25
 
1.9%
Other values (150) 1032
78.5%
ValueCountFrequency (%)
70.1 1
0.1%
76.5 1
0.1%
77.2 1
0.1%
77.4 2
0.2%
78.4 2
0.2%
78.8 2
0.2%
79.1 1
0.1%
79.2 1
0.1%
79.4 1
0.1%
79.5 1
0.1%
ValueCountFrequency (%)
100.0 2
0.2%
97.8 1
0.1%
96.8 2
0.2%
96.4 2
0.2%
96.3 1
0.1%
96.2 1
0.1%
96.1 1
0.1%
95.8 2
0.2%
95.7 1
0.1%
95.5 2
0.2%

Interactions

2023-12-11T09:39:12.796626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T09:39:14.991409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
통계연도시도명아동 예방접종률(퍼센트)
통계연도1.0000.0000.172
시도명0.0001.0000.355
아동 예방접종률(퍼센트)0.1720.3551.000
2023-12-11T09:39:15.075781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
통계연도시도명
통계연도1.0000.000
시도명0.0001.000
2023-12-11T09:39:15.174759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
아동 예방접종률(퍼센트)통계연도시도명
아동 예방접종률(퍼센트)1.0000.1000.154
통계연도0.1001.0000.000
시도명0.1540.0001.000

Missing values

2023-12-11T09:39:12.958549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:39:13.068851image/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

통계연도시도명시군구명아동 예방접종률(퍼센트)
02017서울특별시종로구85.7
12017서울특별시중구90.5
22017서울특별시용산구84.5
32017서울특별시성동구90.3
42017서울특별시광진구90.9
52017서울특별시동대문구91.1
62017서울특별시중랑구91.4
72017서울특별시성북구89.5
82017서울특별시강북구89.5
92017서울특별시도봉구91.8
통계연도시도명시군구명아동 예방접종률(퍼센트)
13052021경상남도창녕군89.9
13062021경상남도고성군91.5
13072021경상남도남해군89.0
13082021경상남도하동군76.5
13092021경상남도산청군85.1
13102021경상남도함양군92.1
13112021경상남도거창군86.2
13122021경상남도합천군80.7
13132021제주특별자치도제주시89.0
13142021제주특별자치도서귀포시89.6