Overview

Dataset statistics

Number of variables6
Number of observations1510
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory76.8 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, 평균연령(세), 남자 평균 연령(세), 여자 평균 연령(세)으로 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=15110129

Alerts

평균연령(세) is highly overall correlated with 남자 평균 연령(세) and 1 other fieldsHigh correlation
남자 평균 연령(세) is highly overall correlated with 평균연령(세) and 1 other fieldsHigh correlation
여자 평균 연령(세) is highly overall correlated with 평균연령(세) and 1 other fieldsHigh correlation

Reproduction

Analysis started2023-12-11 00:32:52.056729
Analysis finished2023-12-11 00:32:53.357083
Duration1.3 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

통계연도
Categorical

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size11.9 KiB
2017
302 
2018
302 
2019
302 
2020
302 
2021
302 

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 302
20.0%
2018 302
20.0%
2019 302
20.0%
2020 302
20.0%
2021 302
20.0%

Length

2023-12-11T09:32:53.435585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:32:53.566046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017 302
20.0%
2018 302
20.0%
2019 302
20.0%
2020 302
20.0%
2021 302
20.0%

시도명
Categorical

Distinct17
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size11.9 KiB
경기도
255 
경상북도
140 
경상남도
130 
전라남도
125 
서울특별시
125 
Other values (12)
735 

Length

Max length7
Median length5
Mean length4.1258278
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 255
16.9%
경상북도 140
9.3%
경상남도 130
8.6%
전라남도 125
8.3%
서울특별시 125
8.3%
강원도 105
7.0%
충청남도 100
 
6.6%
전라북도 95
 
6.3%
부산광역시 95
 
6.3%
충청북도 90
 
6.0%
Other values (7) 250
16.6%

Length

2023-12-11T09:32:53.987228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 255
16.9%
경상북도 140
9.3%
경상남도 130
8.6%
전라남도 125
8.3%
서울특별시 125
8.3%
강원도 105
7.0%
충청남도 100
 
6.6%
부산광역시 95
 
6.3%
전라북도 95
 
6.3%
충청북도 90
 
6.0%
Other values (7) 250
16.6%
Distinct239
Distinct (%)15.8%
Missing0
Missing (%)0.0%
Memory size11.9 KiB
2023-12-11T09:32:54.365943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.8231788
Min length2

Characters and Unicode

Total characters4263
Distinct characters142
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 (%)
면부 70
 
4.6%
읍부 70
 
4.6%
동부 70
 
4.6%
동구 30
 
2.0%
중구 30
 
2.0%
남구 26
 
1.7%
북구 25
 
1.7%
서구 25
 
1.7%
강서구 10
 
0.7%
고성군 10
 
0.7%
Other values (229) 1144
75.8%
2023-12-11T09:32:54.907591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
530
 
12.4%
425
 
10.0%
390
 
9.1%
240
 
5.6%
170
 
4.0%
110
 
2.6%
110
 
2.6%
100
 
2.3%
95
 
2.2%
95
 
2.2%
Other values (132) 1998
46.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4263
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
530
 
12.4%
425
 
10.0%
390
 
9.1%
240
 
5.6%
170
 
4.0%
110
 
2.6%
110
 
2.6%
100
 
2.3%
95
 
2.2%
95
 
2.2%
Other values (132) 1998
46.9%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4263
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
530
 
12.4%
425
 
10.0%
390
 
9.1%
240
 
5.6%
170
 
4.0%
110
 
2.6%
110
 
2.6%
100
 
2.3%
95
 
2.2%
95
 
2.2%
Other values (132) 1998
46.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4263
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
530
 
12.4%
425
 
10.0%
390
 
9.1%
240
 
5.6%
170
 
4.0%
110
 
2.6%
110
 
2.6%
100
 
2.3%
95
 
2.2%
95
 
2.2%
Other values (132) 1998
46.9%

평균연령(세)
Real number (ℝ)

HIGH CORRELATION 

Distinct213
Distinct (%)14.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44.930265
Minimum32.4
Maximum58.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.4 KiB
2023-12-11T09:32:55.053870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum32.4
5-th percentile38.7
Q141.3
median43.6
Q348.7
95-th percentile53.8
Maximum58.3
Range25.9
Interquartile range (IQR)7.4

Descriptive statistics

Standard deviation4.7999328
Coefficient of variation (CV)0.10683073
Kurtosis-0.54719434
Mean44.930265
Median Absolute Deviation (MAD)2.9
Skewness0.5647679
Sum67844.7
Variance23.039355
MonotonicityNot monotonic
2023-12-11T09:32:55.188763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
42.5 24
 
1.6%
41.8 24
 
1.6%
42.1 22
 
1.5%
41.0 22
 
1.5%
41.3 22
 
1.5%
42.9 20
 
1.3%
41.5 20
 
1.3%
43.0 20
 
1.3%
41.2 20
 
1.3%
42.0 19
 
1.3%
Other values (203) 1297
85.9%
ValueCountFrequency (%)
32.4 1
0.1%
32.9 1
0.1%
33.5 1
0.1%
33.9 1
0.1%
34.5 1
0.1%
35.3 1
0.1%
35.9 1
0.1%
36.2 1
0.1%
36.3 2
0.1%
36.4 2
0.1%
ValueCountFrequency (%)
58.3 1
0.1%
57.9 1
0.1%
57.4 1
0.1%
57.1 1
0.1%
57.0 1
0.1%
56.9 1
0.1%
56.8 1
0.1%
56.6 1
0.1%
56.4 1
0.1%
56.3 2
0.1%

남자 평균 연령(세)
Real number (ℝ)

HIGH CORRELATION 

Distinct191
Distinct (%)12.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean43.334702
Minimum32
Maximum55.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.4 KiB
2023-12-11T09:32:55.356807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum32
5-th percentile37.9
Q140.3
median42.3
Q346.4
95-th percentile51.2
Maximum55.4
Range23.4
Interquartile range (IQR)6.1

Descriptive statistics

Standard deviation4.1767971
Coefficient of variation (CV)0.096384581
Kurtosis-0.43713195
Mean43.334702
Median Absolute Deviation (MAD)2.6
Skewness0.56359579
Sum65435.4
Variance17.445634
MonotonicityNot monotonic
2023-12-11T09:32:55.528141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
40.3 28
 
1.9%
40.8 25
 
1.7%
40.2 24
 
1.6%
42.3 24
 
1.6%
41.4 22
 
1.5%
42.2 21
 
1.4%
39.7 21
 
1.4%
41.6 21
 
1.4%
42.0 21
 
1.4%
42.7 20
 
1.3%
Other values (181) 1283
85.0%
ValueCountFrequency (%)
32.0 1
0.1%
32.6 1
0.1%
33.1 1
0.1%
33.5 1
0.1%
34.1 1
0.1%
34.7 1
0.1%
35.3 1
0.1%
35.4 1
0.1%
35.5 1
0.1%
35.6 1
0.1%
ValueCountFrequency (%)
55.4 1
 
0.1%
55.1 1
 
0.1%
54.5 1
 
0.1%
54.1 1
 
0.1%
54.0 3
0.2%
53.9 1
 
0.1%
53.7 2
0.1%
53.5 1
 
0.1%
53.3 4
0.3%
53.2 2
0.1%

여자 평균 연령(세)
Real number (ℝ)

HIGH CORRELATION 

Distinct236
Distinct (%)15.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46.552119
Minimum32.8
Maximum61
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.4 KiB
2023-12-11T09:32:55.683240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum32.8
5-th percentile39.6
Q142.3
median45
Q350.9
95-th percentile56.5
Maximum61
Range28.2
Interquartile range (IQR)8.6

Descriptive statistics

Standard deviation5.4498392
Coefficient of variation (CV)0.11706963
Kurtosis-0.65078484
Mean46.552119
Median Absolute Deviation (MAD)3.4
Skewness0.55795158
Sum70293.7
Variance29.700748
MonotonicityNot monotonic
2023-12-11T09:32:55.843617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
43.5 25
 
1.7%
42.2 22
 
1.5%
43.1 22
 
1.5%
42.7 21
 
1.4%
42.3 21
 
1.4%
42.8 21
 
1.4%
41.5 19
 
1.3%
43.7 18
 
1.2%
43.8 18
 
1.2%
44.1 18
 
1.2%
Other values (226) 1305
86.4%
ValueCountFrequency (%)
32.8 1
 
0.1%
33.3 1
 
0.1%
33.8 1
 
0.1%
34.3 1
 
0.1%
34.9 1
 
0.1%
36.0 1
 
0.1%
36.6 1
 
0.1%
36.7 1
 
0.1%
37.0 1
 
0.1%
37.1 3
0.2%
ValueCountFrequency (%)
61.0 1
0.1%
60.8 1
0.1%
60.3 1
0.1%
60.2 1
0.1%
60.0 1
0.1%
59.9 1
0.1%
59.6 1
0.1%
59.4 1
0.1%
59.3 1
0.1%
59.2 2
0.1%

Interactions

2023-12-11T09:32:52.926293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:32:52.376457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:32:52.670381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:32:53.015863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:32:52.464777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:32:52.751452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:32:53.094868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:32:52.574003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/