Overview

Dataset statistics

Number of variables8
Number of observations21
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 KiB
Average record size in memory75.3 B

Variable types

Categorical5
Text1
Numeric2

Dataset

Description인천광역시 부평구 동별 빈집 현황으로 동명, 주택 등의 정보를 제공합니다<br/>예) 인천광역시 부평구,갈산1동,2,0,5,1,0,2021-04-17<br/>
Author인천광역시 부평구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15043444&srcSe=7661IVAWM27C61E190

Alerts

시군구명 has constant value ""Constant
아파트 has constant value ""Constant
데이터기준일자 has constant value ""Constant
단독주택 is highly overall correlated with 다가구주택High correlation
다가구주택 is highly overall correlated with 단독주택High correlation
구분 has unique valuesUnique
단독주택 has 3 (14.3%) zerosZeros
다세대주택 has 3 (14.3%) zerosZeros

Reproduction

Analysis started2024-04-29 13:36:50.166638
Analysis finished2024-04-29 13:36:51.083895
Duration0.92 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
인천광역시 부평구
21 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row인천광역시 부평구
2nd row인천광역시 부평구
3rd row인천광역시 부평구
4th row인천광역시 부평구
5th row인천광역시 부평구

Common Values

ValueCountFrequency (%)
인천광역시 부평구 21
100.0%

Length

2024-04-29T22:36:51.143583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T22:36:51.245996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인천광역시 21
50.0%
부평구 21
50.0%

구분
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2024-04-29T22:36:51.391303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length3.952381
Min length3

Characters and Unicode

Total characters83
Distinct characters20
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

Unique21 ?
Unique (%)100.0%

Sample

1st row갈산1동
2nd row갈산2동
3rd row부개1동
4th row부개2동
5th row부개3동
ValueCountFrequency (%)
갈산1동 1
 
4.8%
산곡1동 1
 
4.8%
청천1동 1
 
4.8%
일신동 1
 
4.8%
십정2동 1
 
4.8%
십정1동 1
 
4.8%
삼산1동 1
 
4.8%
산곡4동 1
 
4.8%
산곡3동 1
 
4.8%
산곡2동 1
 
4.8%
Other values (11) 11
52.4%
2024-04-29T22:36:51.676367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 21
25.3%
부 9
10.8%
1 7
 
8.4%
산 7
 
8.4%
2 6
 
7.2%
평 6
 
7.2%
곡 4
 
4.8%
개 3
 
3.6%
3 3
 
3.6%
갈 2
 
2.4%
Other values (10) 15
18.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 63
75.9%
Decimal Number 20
 
24.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 21
33.3%
부 9
14.3%
산 7
 
11.1%
평 6
 
9.5%
곡 4
 
6.3%
개 3
 
4.8%
갈 2
 
3.2%
십 2
 
3.2%
청 2
 
3.2%
정 2
 
3.2%
Other values (4) 5
 
7.9%
Decimal Number
ValueCountFrequency (%)
1 7
35.0%
2 6
30.0%
3 3
15.0%
4 2
 
10.0%
6 1
 
5.0%
5 1
 
5.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 63
75.9%
Common 20
 
24.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 21
33.3%
부 9
14.3%
산 7
 
11.1%
평 6
 
9.5%
곡 4
 
6.3%
개 3
 
4.8%
갈 2
 
3.2%
십 2
 
3.2%
청 2
 
3.2%
정 2
 
3.2%
Other values (4) 5
 
7.9%
Common
ValueCountFrequency (%)
1 7
35.0%
2 6
30.0%
3 3
15.0%
4 2
 
10.0%
6 1
 
5.0%
5 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 63
75.9%
ASCII 20
 
24.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 21
33.3%
부 9
14.3%
산 7
 
11.1%
평 6
 
9.5%
곡 4
 
6.3%
개 3
 
4.8%
갈 2
 
3.2%
십 2
 
3.2%
청 2
 
3.2%
정 2
 
3.2%
Other values (4) 5
 
7.9%
ASCII
ValueCountFrequency (%)
1 7
35.0%
2 6
30.0%
3 3
15.0%
4 2
 
10.0%
6 1
 
5.0%
5 1
 
5.0%

단독주택
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct13
Distinct (%)61.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.047619
Minimum0
Maximum218
Zeros3
Zeros (%)14.3%
Negative0
Negative (%)0.0%
Memory size321.0 B
2024-04-29T22:36:51.780329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q37
95-th percentile24
Maximum218
Range218
Interquartile range (IQR)6

Descriptive statistics

Standard deviation46.867341
Coefficient of variation (CV)3.1146018
Kurtosis20.248835
Mean15.047619
Median Absolute Deviation (MAD)2
Skewness4.4691929
Sum316
Variance2196.5476
MonotonicityNot monotonic
2024-04-29T22:36:51.877554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
1 4
19.0%
0 3
14.3%
3 3
14.3%
2 2
9.5%
7 1
 
4.8%
9 1
 
4.8%
12 1
 
4.8%
24 1
 
4.8%
14 1
 
4.8%
4 1
 
4.8%
Other values (3) 3
14.3%
ValueCountFrequency (%)
0 3
14.3%
1 4
19.0%
2 2
9.5%
3 3
14.3%
4 1
 
4.8%
5 1
 
4.8%
6 1
 
4.8%
7 1
 
4.8%
9 1
 
4.8%
12 1
 
4.8%
ValueCountFrequency (%)
218 1
 
4.8%
24 1
 
4.8%
14 1
 
4.8%
12 1
 
4.8%
9 1
 
4.8%
7 1
 
4.8%
6 1
 
4.8%
5 1
 
4.8%
4 1
 
4.8%
3 3
14.3%

다가구주택
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size300.0 B
0
16 
1
4 
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)4.8%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 16
76.2%
1 4
 
19.0%
4 1
 
4.8%

Length

2024-04-29T22:36:51.987805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T22:36:52.078591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 16
76.2%
1 4
 
19.0%
4 1
 
4.8%

다세대주택
Real number (ℝ)

ZEROS 

Distinct13
Distinct (%)61.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.8095238
Minimum0
Maximum22
Zeros3
Zeros (%)14.3%
Negative0
Negative (%)0.0%
Memory size321.0 B
2024-04-29T22:36:52.169919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q37
95-th percentile11
Maximum22
Range22
Interquartile range (IQR)6

Descriptive statistics

Standard deviation5.1828472
Coefficient of variation (CV)1.0776217
Kurtosis5.137222
Mean4.8095238
Median Absolute Deviation (MAD)2
Skewness1.9875592
Sum101
Variance26.861905
MonotonicityNot monotonic
2024-04-29T22:36:52.272113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
3 4
19.0%
0 3
14.3%
1 3
14.3%
2 2
9.5%
7 1
 
4.8%
11 1
 
4.8%
5 1
 
4.8%
4 1
 
4.8%
10 1
 
4.8%
8 1
 
4.8%
Other values (3) 3
14.3%
ValueCountFrequency (%)
0 3
14.3%
1 3
14.3%
2 2
9.5%
3 4
19.0%
4 1
 
4.8%
5 1
 
4.8%
6 1
 
4.8%
7 1
 
4.8%
8 1
 
4.8%
9 1
 
4.8%
ValueCountFrequency (%)
22 1
 
4.8%
11 1
 
4.8%
10 1
 
4.8%
9 1
 
4.8%
8 1
 
4.8%
7 1
 
4.8%
6 1
 
4.8%
5 1
 
4.8%
4 1
 
4.8%
3 4
19.0%

연립주택
Categorical

Distinct5
Distinct (%)23.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
0
15 
1
3 
4
 
1
3
 
1
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique3 ?
Unique (%)14.3%

Sample

1st row1
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 15
71.4%
1 3
 
14.3%
4 1
 
4.8%
3 1
 
4.8%
2 1
 
4.8%

Length

2024-04-29T22:36:52.396734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T22:36:52.695293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 15
71.4%
1 3
 
14.3%
4 1
 
4.8%
3 1
 
4.8%
2 1
 
4.8%

아파트
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
0
21 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 21
100.0%

Length

2024-04-29T22:36:52.805514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T22:36:52.902698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 21
100.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-04-14
21 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-04-14
2nd row2023-04-14
3rd row2023-04-14
4th row2023-04-14
5th row2023-04-14

Common Values

ValueCountFrequency (%)
2023-04-14 21
100.0%

Length

2024-04-29T22:36:52.997062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T22:36:53.079939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-04-14 21
100.0%

Interactions

2024-04-29T22:36:50.745359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:50.604876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:50.819669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:50.675469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-29T22:36:53.138694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분단독주택다가구주택다세대주택연립주택
구분1.0001.0001.0001.0001.000
단독주택1.0001.0000.9290.7200.000
다가구주택1.0000.9291.0000.0000.000
다세대주택1.0000.7200.0001.0000.000
연립주택1.0000.0000.0000.0001.000
2024-04-29T22:36:53.224196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
다가구주택연립주택
다가구주택1.0000.000
연립주택0.0001.000
2024-04-29T22:36:53.303628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
단독주택다세대주택다가구주택연립주택
단독주택1.0000.1100.6720.000
다세대주택0.1101.0000.0000.000
다가구주택0.6720.0001.0000.000
연립주택0.0000.0000.0001.000

Missing values

2024-04-29T22:36:50.921113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-29T22:36:51.038961image/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

시군구명구분단독주택다가구주택다세대주택연립주택아파트데이터기준일자
0인천광역시 부평구갈산1동707102023-04-14
1인천광역시 부평구갈산2동000002023-04-14
2인천광역시 부평구부개1동903002023-04-14
3인천광역시 부평구부개2동103002023-04-14
4인천광역시 부평구부개3동001002023-04-14
5인천광역시 부평구부평1동1211002023-04-14
6인천광역시 부평구부평2동24011002023-04-14
7인천광역시 부평구부평3동1410002023-04-14
8인천광역시 부평구부평4동400402023-04-14
9인천광역시 부평구부평5동315302023-04-14
시군구명구분단독주택다가구주택다세대주택연립주택아파트데이터기준일자
11인천광역시 부평구산곡1동21844002023-04-14
12인천광역시 부평구산곡2동503002023-04-14
13인천광역시 부평구산곡3동6010002023-04-14
14인천광역시 부평구산곡4동103002023-04-14
15인천광역시 부평구삼산1동108002023-04-14
16인천광역시 부평구십정1동009002023-04-14
17인천광역시 부평구십정2동3022002023-04-14
18인천광역시 부평구일신동301202023-04-14
19인천광역시 부평구청천1동202002023-04-14
20인천광역시 부평구청천2동206102023-04-14