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, 빈집 비율(퍼센트), 빈집수(채), 주택수(채)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=15110146

Alerts

빈집수(채) is highly overall correlated with 주택수(채)High correlation
주택수(채) is highly overall correlated with 빈집수(채)High correlation

Reproduction

Analysis started2023-12-11 00:14:23.870184
Analysis finished2023-12-11 00:14:25.704193
Duration1.83 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

2023-12-11T09:14:25.765844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:14:25.870051image/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

2023-12-11T09:14:26.023939image/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
2023-12-11T09:14:26.383871image/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%
2023-12-11T09:14:26.878617image/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%

빈집 비율(퍼센트)
Real number (ℝ)

Distinct1020
Distinct (%)67.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.130669
Minimum0.21
Maximum26.06
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.4 KiB
2023-12-11T09:14:27.027988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.21
5-th percentile2.53
Q15.8775
median10.095
Q314.15
95-th percentile17.6355
Maximum26.06
Range25.85
Interquartile range (IQR)8.2725

Descriptive statistics

Standard deviation5.0018979
Coefficient of variation (CV)0.49373817
Kurtosis-0.75768926
Mean10.130669
Median Absolute Deviation (MAD)4.12
Skewness0.13775579
Sum15297.31
Variance25.018983
MonotonicityNot monotonic
2023-12-11T09:14:27.204113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6.35 5
 
0.3%
7.82 5
 
0.3%
11.96 5
 
0.3%
15.54 4
 
0.3%
5.48 4
 
0.3%
3.11 4
 
0.3%
14.86 4
 
0.3%
15.46 4
 
0.3%
10.7 4
 
0.3%
9.03 4
 
0.3%
Other values (1010) 1467
97.2%
ValueCountFrequency (%)
0.21 1
0.1%
0.44 1
0.1%
0.6 1
0.1%
0.61 1
0.1%
0.62 1
0.1%
0.66 2
0.1%
0.7 1
0.1%
0.73 1
0.1%
0.74 1
0.1%
0.79 1
0.1%
ValueCountFrequency (%)
26.06 1
0.1%
25.42 1
0.1%
25.38 1
0.1%
25.25 1
0.1%
23.88 1
0.1%
23.71 1
0.1%
22.81 1
0.1%
22.52 1
0.1%
22.03 1
0.1%
21.94 1
0.1%

빈집수(채)
Real number (ℝ)

HIGH CORRELATION 

Distinct1441
Distinct (%)95.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9461.8344
Minimum25
Maximum198712
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.4 KiB
2023-12-11T09:14:27.343155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum25
5-th percentile1238.6
Q12960
median5158
Q39620.75
95-th percentile32720.35
Maximum198712
Range198687
Interquartile range (IQR)6660.75

Descriptive statistics

Standard deviation15168.303
Coefficient of variation (CV)1.6031038
Kurtosis59.382534
Mean9461.8344
Median Absolute Deviation (MAD)2669
Skewness6.3260332
Sum14287370
Variance2.3007742 × 108
MonotonicityNot monotonic
2023-12-11T09:14:27.493431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6579 3
 
0.2%
2001 3
 
0.2%
2071 3
 
0.2%
1488 2
 
0.1%
4162 2
 
0.1%
1864 2
 
0.1%
2708 2
 
0.1%
6994 2
 
0.1%
5441 2
 
0.1%
8510 2
 
0.1%
Other values (1431) 1487
98.5%
ValueCountFrequency (%)
25 1
0.1%
81 1
0.1%
125 1
0.1%
149 1
0.1%
151 1
0.1%
155 1
0.1%
170 1
0.1%
181 1
0.1%
206 1
0.1%
224 1
0.1%
ValueCountFrequency (%)
198712 1
0.1%
195586 1
0.1%
181120 1
0.1%
176573 1
0.1%
142018 1
0.1%
107025 1
0.1%
104856 1
0.1%
96698 1
0.1%
94866 1
0.1%
89151 1
0.1%

주택수(채)
Real number (ℝ)

HIGH CORRELATION 

Distinct1497
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean115796.9
Minimum2996
Maximum3771104
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.4 KiB
2023-12-11T09:14:27.629017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2996
5-th percentile12515.05
Q127531.5
median71545.5
Q3127973.5
95-th percentile322035.7
Maximum3771104
Range3768108
Interquartile range (IQR)100442

Descriptive statistics

Standard deviation235971.6
Coefficient of variation (CV)2.0378058
Kurtosis147.68373
Mean115796.9
Median Absolute Deviation (MAD)47026.5
Skewness10.776684
Sum1.7485332 × 108
Variance5.5682596 × 1010
MonotonicityNot monotonic
2023-12-11T09:14:27.758379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
42343 2
 
0.1%
76688 2
 
0.1%
44017 2
 
0.1%
10940 2
 
0.1%
17241 2
 
0.1%
29323 2
 
0.1%
49245 2
 
0.1%
37736 2
 
0.1%
13460 2
 
0.1%
103740 2
 
0.1%
Other values (1487) 1490
98.7%
ValueCountFrequency (%)
2996 1
0.1%
3025 1
0.1%
3044 1
0.1%
3050 1
0.1%
3065 1
0.1%
6646 1
0.1%
6669 1
0.1%
6683 1
0.1%
7367 1
0.1%
7953 1
0.1%
ValueCountFrequency (%)
3771104 1
0.1%
3677426 1
0.1%
3564396 1
0.1%
3407404 1
0.1%
3218565 1
0.1%
1217721 1
0.1%
1210318 1
0.1%
1189929 1
0.1%
1162077 1
0.1%
1142880 1
0.1%

Interactions

2023-12-11T09:14:24.907611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:14:24.203701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:14:24.533056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:14:25.018795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:14:24.310028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:14:24.629760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:14:25.415583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/