Overview

Dataset statistics

Number of variables6
Number of observations1140
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory58.0 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, 독거노인가구비율(퍼센트), 65세 이상 1인가구(가구), 전체 일반가구(가구)로 구성되어 있습니다. 김해시 중심의 통계지수로서, 데이터 수집, 가공 등의 어려움으로 김해시 외 지역의 정보는 누락될 수 있습니다.
Author경상남도 김해시
URLhttps://www.data.go.kr/data/15110116/fileData.do

Alerts

독거노인가구비율(퍼센트) is highly overall correlated with 65세 이상 1인가구(가구) and 1 other fieldsHigh correlation
65세 이상 1인가구(가구) is highly overall correlated with 독거노인가구비율(퍼센트) and 1 other fieldsHigh correlation
전체 일반가구(가구) is highly overall correlated with 독거노인가구비율(퍼센트) and 1 other fieldsHigh correlation

Reproduction

Analysis started2023-12-11 23:45:47.685592
Analysis finished2023-12-11 23:45:49.263363
Duration1.58 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

통계연도
Categorical

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
2017
228 
2018
228 
2019
228 
2020
228 
2021
228 

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 228
20.0%
2018 228
20.0%
2019 228
20.0%
2020 228
20.0%
2021 228
20.0%

Length

2023-12-12T08:45:49.322469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:45:49.419709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017 228
20.0%
2018 228
20.0%
2019 228
20.0%
2020 228
20.0%
2021 228
20.0%

시도명
Categorical

Distinct16
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
경기도
155 
서울특별시
125 
경상북도
115 
전라남도
110 
강원도
90 
Other values (11)
545 

Length

Max length7
Median length5
Mean length4.1359649
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 155
13.6%
서울특별시 125
11.0%
경상북도 115
10.1%
전라남도 110
9.6%
강원도 90
7.9%
경상남도 90
7.9%
부산광역시 80
7.0%
충청남도 75
6.6%
전라북도 70
 
6.1%
충청북도 55
 
4.8%
Other values (6) 175
15.4%

Length

2023-12-12T08:45:49.540362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 155
13.6%
서울특별시 125
11.0%
경상북도 115
10.1%
전라남도 110
9.6%
강원도 90
7.9%
경상남도 90
7.9%
부산광역시 80
7.0%
충청남도 75
6.6%
전라북도 70
 
6.1%
충청북도 55
 
4.8%
Other values (6) 175
15.4%
Distinct206
Distinct (%)18.1%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
2023-12-12T08:45:49.852560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.9324561
Min length2

Characters and Unicode

Total characters3343
Distinct characters132
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 (%)
동구 30
 
2.6%
중구 30
 
2.6%
서구 25
 
2.2%
남구 21
 
1.8%
북구 20
 
1.8%
고성군 10
 
0.9%
강서구 10
 
0.9%
완주군 5
 
0.4%
무주군 5
 
0.4%
진안군 5
 
0.4%
Other values (196) 979
85.9%
2023-12-12T08:45:50.552465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
425
 
12.7%
390
 
11.7%
370
 
11.1%
110
 
3.3%
100
 
3.0%
90
 
2.7%
90
 
2.7%
85
 
2.5%
80
 
2.4%
65
 
1.9%
Other values (122) 1538
46.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3343
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
425
 
12.7%
390
 
11.7%
370
 
11.1%
110
 
3.3%
100
 
3.0%
90
 
2.7%
90
 
2.7%
85
 
2.5%
80
 
2.4%
65
 
1.9%
Other values (122) 1538
46.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3343
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
425
 
12.7%
390
 
11.7%
370
 
11.1%
110
 
3.3%
100
 
3.0%
90
 
2.7%
90
 
2.7%
85
 
2.5%
80
 
2.4%
65
 
1.9%
Other values (122) 1538
46.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3343
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
425
 
12.7%
390
 
11.7%
370
 
11.1%
110
 
3.3%
100
 
3.0%
90
 
2.7%
90
 
2.7%
85
 
2.5%
80
 
2.4%
65
 
1.9%
Other values (122) 1538
46.0%

독거노인가구비율(퍼센트)
Real number (ℝ)

HIGH CORRELATION 

Distinct213
Distinct (%)18.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.280263
Minimum3.1
Maximum26.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.1 KiB
2023-12-12T08:45:50.686227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.1
5-th percentile4.495
Q16.5
median9.5
Q315.8
95-th percentile21.905
Maximum26.2
Range23.1
Interquartile range (IQR)9.3

Descriptive statistics

Standard deviation5.7226984
Coefficient of variation (CV)0.50731958
Kurtosis-0.7335855
Mean11.280263
Median Absolute Deviation (MAD)3.8
Skewness0.65543315
Sum12859.5
Variance32.749276
MonotonicityNot monotonic
2023-12-12T08:45:50.812320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6.0 18
 
1.6%
5.1 18
 
1.6%
6.7 16
 
1.4%
6.5 16
 
1.4%
4.8 16
 
1.4%
5.8 15
 
1.3%
8.4 15
 
1.3%
8.8 15
 
1.3%
4.4 14
 
1.2%
6.2 13
 
1.1%
Other values (203) 984
86.3%
ValueCountFrequency (%)
3.1 1
 
0.1%
3.3 4
0.4%
3.4 2
 
0.2%
3.5 2
 
0.2%
3.6 4
0.4%
3.7 2
 
0.2%
3.8 5
0.4%
3.9 6
0.5%
4.0 6
0.5%
4.1 4
0.4%
ValueCountFrequency (%)
26.2 1
 
0.1%
26.1 1
 
0.1%
25.6 1
 
0.1%
25.1 1
 
0.1%
25.0 3
0.3%
24.8 2
0.2%
24.7 3
0.3%
24.5 3
0.3%
24.2 2
0.2%
24.0 3
0.3%

65세 이상 1인가구(가구)
Real number (ℝ)

HIGH CORRELATION 

Distinct1093
Distinct (%)95.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6848.9482
Minimum407
Maximum34661
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.1 KiB
2023-12-12T08:45:50.933516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum407
5-th percentile1896.3
Q13567.25
median5652
Q39165.25
95-th percentile15478
Maximum34661
Range34254
Interquartile range (IQR)5598

Descriptive statistics

Standard deviation4625.2509
Coefficient of variation (CV)0.67532279
Kurtosis3.6995088
Mean6848.9482
Median Absolute Deviation (MAD)2551.5
Skewness1.5962205
Sum7807801
Variance21392946
MonotonicityNot monotonic
2023-12-12T08:45:51.075011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4996 3
 
0.3%
2625 2
 
0.2%
4531 2
 
0.2%
2956 2
 
0.2%
3907 2
 
0.2%
12188 2
 
0.2%
3690 2
 
0.2%
3721 2
 
0.2%
7220 2
 
0.2%
7236 2
 
0.2%
Other values (1083) 1119
98.2%
ValueCountFrequency (%)
407 1
0.1%
444 1
0.1%
445 1
0.1%
507 1
0.1%
520 1
0.1%
688 1
0.1%
764 1
0.1%
842 1
0.1%
853 1
0.1%
903 1
0.1%
ValueCountFrequency (%)
34661 1
0.1%
30993 1
0.1%
27845 1
0.1%
26737 1
0.1%
26098 1
0.1%
25893 1
0.1%
25880 1
0.1%
25449 1
0.1%
24388 1
0.1%
24010 1
0.1%

전체 일반가구(가구)
Real number (ℝ)

HIGH CORRELATION 

Distinct1135
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean89240.355
Minimum4061
Maximum480566
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.1 KiB
2023-12-12T08:45:51.211050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4061
5-th percentile11518
Q122246.5
median59019
Q3133394.5
95-th percentile251695.2
Maximum480566
Range476505
Interquartile range (IQR)111148

Descriptive statistics

Standard deviation84734.837
Coefficient of variation (CV)0.94951255
Kurtosis2.83091
Mean89240.355
Median Absolute Deviation (MAD)42102
Skewness1.5750502
Sum1.01734 × 108
Variance7.1799926 × 109
MonotonicityNot monotonic
2023-12-12T08:45:51.344584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128012 2
 
0.2%
11518 2
 
0.2%
14044 2
 
0.2%
11723 2
 
0.2%
19431 2
 
0.2%
369585 1
 
0.1%
213185 1
 
0.1%
111383 1
 
0.1%
315696 1
 
0.1%
203441 1
 
0.1%
Other values (1125) 1125
98.7%
ValueCountFrequency (%)
4061 1
0.1%
4072 1
0.1%
4116 1
0.1%
4135 1
0.1%
4145 1
0.1%
7539 1
0.1%
7565 1
0.1%
7585 1
0.1%
7661 1
0.1%
7723 1
0.1%
ValueCountFrequency (%)
480566 1
0.1%
466089 1
0.1%
457351 1
0.1%
450819 1
0.1%
445309 1
0.1%
421845 1
0.1%
411137 1
0.1%
409688 1
0.1%
403524 1
0.1%
399353 1
0.1%

Interactions

2023-12-12T08:45:48.728667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:47.992250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:48.361848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:48.841293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:48.102829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:48.506537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:45:48.936725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/