Overview

Dataset statistics

Number of variables7
Number of observations80
Missing cells1
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.7 KiB
Average record size in memory59.6 B

Variable types

Numeric2
Categorical4
DateTime1

Dataset

Description서울시 양천구 관내의 빈집현황 정보 제공(행정동, 주택유형, 승인일자 등)
Author서울특별시 양천구
URLhttps://www.data.go.kr/data/15043291/fileData.do

Alerts

시도 has constant value ""Constant
시군구 has constant value ""Constant
기준일자 has constant value ""Constant
연번 is highly overall correlated with 동명 and 1 other fieldsHigh correlation
사용승인 is highly overall correlated with 유형High correlation
동명 is highly overall correlated with 연번High correlation
유형 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
사용승인 has 1 (1.2%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 06:39:07.013840
Analysis finished2023-12-12 06:39:07.754247
Duration0.74 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct80
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40.5
Minimum1
Maximum80
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size852.0 B
2023-12-12T15:39:07.843821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.95
Q120.75
median40.5
Q360.25
95-th percentile76.05
Maximum80
Range79
Interquartile range (IQR)39.5

Descriptive statistics

Standard deviation23.2379
Coefficient of variation (CV)0.57377531
Kurtosis-1.2
Mean40.5
Median Absolute Deviation (MAD)20
Skewness0
Sum3240
Variance540
MonotonicityStrictly increasing
2023-12-12T15:39:08.061359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.2%
42 1
 
1.2%
60 1
 
1.2%
59 1
 
1.2%
58 1
 
1.2%
57 1
 
1.2%
56 1
 
1.2%
55 1
 
1.2%
54 1
 
1.2%
53 1
 
1.2%
Other values (70) 70
87.5%
ValueCountFrequency (%)
1 1
1.2%
2 1
1.2%
3 1
1.2%
4 1
1.2%
5 1
1.2%
6 1
1.2%
7 1
1.2%
8 1
1.2%
9 1
1.2%
10 1
1.2%
ValueCountFrequency (%)
80 1
1.2%
79 1
1.2%
78 1
1.2%
77 1
1.2%
76 1
1.2%
75 1
1.2%
74 1
1.2%
73 1
1.2%
72 1
1.2%
71 1
1.2%

시도
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size772.0 B
서울특별시
80 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서울특별시 80
100.0%

Length

2023-12-12T15:39:08.251886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:39:08.363070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 80
100.0%

시군구
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size772.0 B
양천구
80 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
양천구 80
100.0%

Length

2023-12-12T15:39:08.495749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:39:08.613389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
양천구 80
100.0%

동명
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size772.0 B
신월동
48 
신정동
24 
목동
8 

Length

Max length3
Median length3
Mean length2.9
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row목동
2nd row목동
3rd row목동
4th row신월동
5th row신월동

Common Values

ValueCountFrequency (%)
신월동 48
60.0%
신정동 24
30.0%
목동 8
 
10.0%

Length

2023-12-12T15:39:08.753478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:39:08.897207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신월동 48
60.0%
신정동 24
30.0%
목동 8
 
10.0%

유형
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size772.0 B
다세대
33 
단독주택
26 
아파트
11 
연립
10 

Length

Max length4
Median length3
Mean length3.2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
다세대 33
41.2%
단독주택 26
32.5%
아파트 11
 
13.8%
연립 10
 
12.5%

Length

2023-12-12T15:39:09.064672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:39:09.233182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
다세대 33
41.2%
단독주택 26
32.5%
아파트 11
 
13.8%
연립 10
 
12.5%

사용승인
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct25
Distinct (%)31.6%
Missing1
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean1986.7595
Minimum1971
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size852.0 B
2023-12-12T15:39:09.402894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1971
5-th percentile1974
Q11982
median1986
Q31988
95-th percentile2008.2
Maximum2020
Range49
Interquartile range (IQR)6

Descriptive statistics

Standard deviation9.0486083
Coefficient of variation (CV)0.0045544558
Kurtosis3.8380254
Mean1986.7595
Median Absolute Deviation (MAD)3
Skewness1.5611104
Sum156954
Variance81.877313
MonotonicityNot monotonic
2023-12-12T15:39:09.550686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
1986 14
17.5%
1988 11
13.8%
1987 9
 
11.2%
1982 4
 
5.0%
1981 4
 
5.0%
1994 3
 
3.8%
1984 3
 
3.8%
1989 3
 
3.8%
1974 3
 
3.8%
1976 2
 
2.5%
Other values (15) 23
28.7%
ValueCountFrequency (%)
1971 1
 
1.2%
1973 1
 
1.2%
1974 3
3.8%
1975 2
2.5%
1976 2
2.5%
1977 2
2.5%
1978 2
2.5%
1981 4
5.0%
1982 4
5.0%
1983 2
2.5%
ValueCountFrequency (%)
2020 1
 
1.2%
2015 2
2.5%
2010 1
 
1.2%
2008 1
 
1.2%
2004 1
 
1.2%
1994 3
3.8%
1993 2
2.5%
1992 1
 
1.2%
1991 2
2.5%
1989 3
3.8%

기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size772.0 B
Minimum2020-03-31 00:00:00
Maximum2020-03-31 00:00:00
2023-12-12T15:39:09.659307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:39:09.774451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T15:39:07.392183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:39:07.187634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:39:07.478924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:39:07.294165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T15:39:09.862044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번동명유형사용승인
연번1.0000.8210.8100.329
동명0.8211.0000.3820.424
유형0.8100.3821.0000.770
사용승인0.3290.4240.7701.000
2023-12-12T15:39:09.983161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
동명유형
동명1.0000.369
유형0.3691.000
2023-12-12T15:39:10.111593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번사용승인동명유형
연번1.0000.0300.6880.611
사용승인0.0301.0000.2200.603
동명0.6880.2201.0000.369
유형0.6110.6030.3691.000

Missing values

2023-12-12T15:39:07.587564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:39:07.694889image/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

연번시도시군구동명유형사용승인기준일자
01서울특별시양천구목동단독주택19842020-03-31
12서울특별시양천구목동단독주택19782020-03-31
23서울특별시양천구목동단독주택19862020-03-31
34서울특별시양천구신월동단독주택19782020-03-31
45서울특별시양천구신월동단독주택<NA>2020-03-31
56서울특별시양천구신정동단독주택19742020-03-31
67서울특별시양천구신정동단독주택19712020-03-31
78서울특별시양천구신정동단독주택20152020-03-31
89서울특별시양천구신정동단독주택20152020-03-31
910서울특별시양천구목동다세대19892020-03-31
연번시도시군구동명유형사용승인기준일자
7071서울특별시양천구신정동단독주택19742020-03-31
7172서울특별시양천구신정동단독주택19762020-03-31
7273서울특별시양천구신정동단독주택19772020-03-31
7374서울특별시양천구신정동아파트20042020-03-31
7475서울특별시양천구신정동아파트19872020-03-31
7576서울특별시양천구신정동아파트19872020-03-31
7677서울특별시양천구신정동아파트19872020-03-31
7778서울특별시양천구신정동아파트19872020-03-31
7879서울특별시양천구신정동아파트19882020-03-31
7980서울특별시양천구신정동아파트19882020-03-31