Overview

Dataset statistics

Number of variables11
Number of observations24
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.4 KiB
Average record size in memory102.5 B

Variable types

Text1
Numeric4
Categorical5
DateTime1

Dataset

Description인천광역시 서구 동별빈집현황(동별 주택유형별 단독주택, 다세대주택, 연립주택, 아파트, 오피스텔 등 빈집현황)입니다.
Author인천광역시 서구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15043225&srcSe=7661IVAWM27C61E190

Alerts

데이터기준일자 has constant value ""Constant
단독주택 is highly overall correlated with 4등급High correlation
다세대주택 is highly overall correlated with 1등급 and 2 other fieldsHigh correlation
1등급 is highly overall correlated with 다세대주택 and 2 other fieldsHigh correlation
2등급 is highly overall correlated with 다세대주택 and 2 other fieldsHigh correlation
연립주택 is highly overall correlated with 다세대주택 and 1 other fieldsHigh correlation
아파트 is highly overall correlated with 2등급High correlation
4등급 is highly overall correlated with 단독주택High correlation
오피스텔 is highly imbalanced (75.0%)Imbalance
구분 has unique valuesUnique
단독주택 has 10 (41.7%) zerosZeros
다세대주택 has 8 (33.3%) zerosZeros
1등급 has 2 (8.3%) zerosZeros
2등급 has 6 (25.0%) zerosZeros

Reproduction

Analysis started2024-03-18 05:29:31.672127
Analysis finished2024-03-18 05:29:34.151695
Duration2.48 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2024-03-18T14:29:34.262938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.4166667
Min length3

Characters and Unicode

Total characters82
Distinct characters36
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

Unique24 ?
Unique (%)100.0%

Sample

1st row가정1동
2nd row가정2동
3rd row가정3동
4th row가좌1동
5th row가좌2동
ValueCountFrequency (%)
가정1동 1
 
4.2%
가정2동 1
 
4.2%
왕길동 1
 
4.2%
오류동 1
 
4.2%
청라동 1
 
4.2%
연희동 1
 
4.2%
심곡동 1
 
4.2%
신현동 1
 
4.2%
석남3동 1
 
4.2%
석남2동 1
 
4.2%
Other values (14) 14
58.3%
2024-03-18T14:29:34.597770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 24
29.3%
가 7
 
8.5%
좌 4
 
4.9%
정 3
 
3.7%
남 3
 
3.7%
곡 3
 
3.7%
3 3
 
3.7%
2 3
 
3.7%
1 3
 
3.7%
석 3
 
3.7%
Other values (26) 26
31.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 72
87.8%
Decimal Number 10
 
12.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 24
33.3%
가 7
 
9.7%
좌 4
 
5.6%
정 3
 
4.2%
남 3
 
4.2%
곡 3
 
4.2%
석 3
 
4.2%
원 1
 
1.4%
길 1
 
1.4%
왕 1
 
1.4%
Other values (22) 22
30.6%
Decimal Number
ValueCountFrequency (%)
3 3
30.0%
2 3
30.0%
1 3
30.0%
4 1
 
10.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 72
87.8%
Common 10
 
12.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 24
33.3%
가 7
 
9.7%
좌 4
 
5.6%
정 3
 
4.2%
남 3
 
4.2%
곡 3
 
4.2%
석 3
 
4.2%
원 1
 
1.4%
길 1
 
1.4%
왕 1
 
1.4%
Other values (22) 22
30.6%
Common
ValueCountFrequency (%)
3 3
30.0%
2 3
30.0%
1 3
30.0%
4 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 72
87.8%
ASCII 10
 
12.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 24
33.3%
가 7
 
9.7%
좌 4
 
5.6%
정 3
 
4.2%
남 3
 
4.2%
곡 3
 
4.2%
석 3
 
4.2%
원 1
 
1.4%
길 1
 
1.4%
왕 1
 
1.4%
Other values (22) 22
30.6%
ASCII
ValueCountFrequency (%)
3 3
30.0%
2 3
30.0%
1 3
30.0%
4 1
 
10.0%

단독주택
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct7
Distinct (%)29.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.7083333
Minimum0
Maximum8
Zeros10
Zeros (%)41.7%
Negative0
Negative (%)0.0%
Memory size348.0 B
2024-03-18T14:29:34.699880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile4.85
Maximum8
Range8
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.0531877
Coefficient of variation (CV)1.201866
Kurtosis2.3917216
Mean1.7083333
Median Absolute Deviation (MAD)1
Skewness1.4490791
Sum41
Variance4.2155797
MonotonicityNot monotonic
2024-03-18T14:29:34.806216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 10
41.7%
2 4
 
16.7%
1 3
 
12.5%
3 3
 
12.5%
4 2
 
8.3%
8 1
 
4.2%
5 1
 
4.2%
ValueCountFrequency (%)
0 10
41.7%
1 3
 
12.5%
2 4
 
16.7%
3 3
 
12.5%
4 2
 
8.3%
5 1
 
4.2%
8 1
 
4.2%
ValueCountFrequency (%)
8 1
 
4.2%
5 1
 
4.2%
4 2
 
8.3%
3 3
 
12.5%
2 4
 
16.7%
1 3
 
12.5%
0 10
41.7%

다세대주택
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct13
Distinct (%)54.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.333333
Minimum0
Maximum46
Zeros8
Zeros (%)33.3%
Negative0
Negative (%)0.0%
Memory size348.0 B
2024-03-18T14:29:34.915226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3.5
Q317
95-th percentile43.9
Maximum46
Range46
Interquartile range (IQR)17

Descriptive statistics

Standard deviation14.496376
Coefficient of variation (CV)1.279092
Kurtosis0.86161082
Mean11.333333
Median Absolute Deviation (MAD)3.5
Skewness1.3365995
Sum272
Variance210.14493
MonotonicityNot monotonic
2024-03-18T14:29:35.036697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 8
33.3%
46 2
 
8.3%
2 2
 
8.3%
3 2
 
8.3%
11 2
 
8.3%
20 1
 
4.2%
16 1
 
4.2%
28 1
 
4.2%
8 1
 
4.2%
4 1
 
4.2%
Other values (3) 3
 
12.5%
ValueCountFrequency (%)
0 8
33.3%
2 2
 
8.3%
3 2
 
8.3%
4 1
 
4.2%
8 1
 
4.2%
11 2
 
8.3%
14 1
 
4.2%
16 1
 
4.2%
20 1
 
4.2%
26 1
 
4.2%
ValueCountFrequency (%)
46 2
8.3%
32 1
4.2%
28 1
4.2%
26 1
4.2%
20 1
4.2%
16 1
4.2%
14 1
4.2%
11 2
8.3%
8 1
4.2%
4 1
4.2%

연립주택
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size324.0 B
0
19 
1
3 
6
 
1
7
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)8.3%

Sample

1st row0
2nd row0
3rd row0
4th row6
5th row0

Common Values

ValueCountFrequency (%)
0 19
79.2%
1 3
 
12.5%
6 1
 
4.2%
7 1
 
4.2%

Length

2024-03-18T14:29:35.147370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T14:29:35.241776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 19
79.2%
1 3
 
12.5%
6 1
 
4.2%
7 1
 
4.2%

아파트
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size324.0 B
0
17 
1
4 
2
2 
13
 
1

Length

Max length2
Median length1
Mean length1.0416667
Min length1

Unique

Unique1 ?
Unique (%)4.2%

Sample

1st row0
2nd row13
3rd row0
4th row1
5th row0

Common Values

ValueCountFrequency (%)
0 17
70.8%
1 4
 
16.7%
2 2
 
8.3%
13 1
 
4.2%

Length

2024-03-18T14:29:35.328939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T14:29:35.410639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 17
70.8%
1 4
 
16.7%
2 2
 
8.3%
13 1
 
4.2%

오피스텔
Categorical

IMBALANCE 

Distinct2
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size324.0 B
0
23 
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)4.2%

Sample

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

Common Values

ValueCountFrequency (%)
0 23
95.8%
1 1
 
4.2%

Length

2024-03-18T14:29:35.531584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T14:29:35.621972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 23
95.8%
1 1
 
4.2%

1등급
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct13
Distinct (%)54.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.0416667
Minimum0
Maximum34
Zeros2
Zeros (%)8.3%
Negative0
Negative (%)0.0%
Memory size348.0 B
2024-03-18T14:29:35.703524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.15
Q12
median3
Q37.25
95-th percentile17.1
Maximum34
Range34
Interquartile range (IQR)5.25

Descriptive statistics

Standard deviation7.3984673
Coefficient of variation (CV)1.2245739
Kurtosis8.6130867
Mean6.0416667
Median Absolute Deviation (MAD)2
Skewness2.6703194
Sum145
Variance54.737319
MonotonicityNot monotonic
2024-03-18T14:29:35.796145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
3 5
20.8%
2 5
20.8%
0 2
 
8.3%
1 2
 
8.3%
7 2
 
8.3%
5 1
 
4.2%
34 1
 
4.2%
18 1
 
4.2%
10 1
 
4.2%
8 1
 
4.2%
Other values (3) 3
12.5%
ValueCountFrequency (%)
0 2
 
8.3%
1 2
 
8.3%
2 5
20.8%
3 5
20.8%
5 1
 
4.2%
6 1
 
4.2%
7 2
 
8.3%
8 1
 
4.2%
10 1
 
4.2%
11 1
 
4.2%
ValueCountFrequency (%)
34 1
 
4.2%
18 1
 
4.2%
12 1
 
4.2%
11 1
 
4.2%
10 1
 
4.2%
8 1
 
4.2%
7 2
 
8.3%
6 1
 
4.2%
5 1
 
4.2%
3 5
20.8%

2등급
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct15
Distinct (%)62.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.8333333
Minimum0
Maximum37
Zeros6
Zeros (%)25.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2024-03-18T14:29:35.890268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.75
median3
Q310
95-th percentile27.7
Maximum37
Range37
Interquartile range (IQR)9.25

Descriptive statistics

Standard deviation10.361579
Coefficient of variation (CV)1.3227548
Kurtosis1.7729546
Mean7.8333333
Median Absolute Deviation (MAD)3
Skewness1.5943021
Sum188
Variance107.36232
MonotonicityNot monotonic
2024-03-18T14:29:36.002423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 6
25.0%
2 3
12.5%
1 2
 
8.3%
3 2
 
8.3%
15 1
 
4.2%
13 1
 
4.2%
9 1
 
4.2%
7 1
 
4.2%
26 1
 
4.2%
6 1
 
4.2%
Other values (5) 5
20.8%
ValueCountFrequency (%)
0 6
25.0%
1 2
 
8.3%
2 3
12.5%
3 2
 
8.3%
4 1
 
4.2%
6 1
 
4.2%
7 1
 
4.2%
8 1
 
4.2%
9 1
 
4.2%
13 1
 
4.2%
ValueCountFrequency (%)
37 1
4.2%
28 1
4.2%
26 1
4.2%
21 1
4.2%
15 1
4.2%
13 1
4.2%
9 1
4.2%
8 1
4.2%
7 1
4.2%
6 1
4.2%

3등급
Categorical

Distinct3
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size324.0 B
0
17 
1
5 
3
2 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row3
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 17
70.8%
1 5
 
20.8%
3 2
 
8.3%

Length

2024-03-18T14:29:36.109464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T14:29:36.187891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 17
70.8%
1 5
 
20.8%
3 2
 
8.3%

4등급
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size324.0 B
0
18 
1
5 
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)4.2%

Sample

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

Common Values

ValueCountFrequency (%)
0 18
75.0%
1 5
 
20.8%
2 1
 
4.2%

Length

2024-03-18T14:29:36.274101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T14:29:36.353268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 18
75.0%
1 5
 
20.8%
2 1
 
4.2%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
Minimum2023-03-23 00:00:00
Maximum2023-03-23 00:00:00
2024-03-18T14:29:36.422389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:29:36.516512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-03-18T14:29:33.531542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:29:32.144544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:29:32.651519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:29:32.993007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:29:33.664005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:29:32.284515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:29:32.740558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:29:33.169189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:29:33.756005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:29:32.391446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:29:32.821391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:29:33.311948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:29:33.839455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:29:32.509327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:29:32.914460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:29:33.436472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-18T14:29:36.612767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분단독주택다세대주택연립주택아파트오피스텔1등급2등급3등급4등급
구분1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
단독주택1.0001.0000.0000.1230.0000.0000.0000.0000.5770.885
다세대주택1.0000.0001.0000.9320.0000.0000.8500.9710.5010.000
연립주택1.0000.1230.9321.0000.0000.0000.7720.8310.4290.000
아파트1.0000.0000.0000.0001.0000.0000.0690.8860.0000.000
오피스텔1.0000.0000.0000.0000.0001.0000.0000.0000.0000.000
1등급1.0000.0000.8500.7720.0690.0001.0000.8100.7160.000
2등급1.0000.0000.9710.8310.8860.0000.8101.0000.3670.000
3등급1.0000.5770.5010.4290.0000.0000.7160.3671.0000.427
4등급1.0000.8850.0000.0000.0000.0000.0000.0000.4271.000
2024-03-18T14:29:36.747423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
아파트4등급오피스텔연립주택3등급
아파트1.0000.0000.0000.0000.000
4등급0.0001.0000.0000.0000.149
오피스텔0.0000.0001.0000.0000.000
연립주택0.0000.0000.0001.0000.406
3등급0.0000.1490.0000.4061.000
2024-03-18T14:29:36.837416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
단독주택다세대주택1등급2등급연립주택아파트오피스텔3등급4등급
단독주택1.000-0.167-0.1090.0090.0000.0000.0000.4100.789
다세대주택-0.1671.0000.8800.8120.5850.0000.0000.3020.000
1등급-0.1090.8801.0000.5990.5760.0000.0000.3560.000
2등급0.0090.8120.5991.0000.4360.5060.0000.1880.000
연립주택0.0000.5850.5760.4361.0000.0000.0000.4060.000
아파트0.0000.0000.0000.5060.0001.0000.0000.0000.000
오피스텔0.0000.0000.0000.0000.0000.0001.0000.0000.000
3등급0.4100.3020.3560.1880.4060.0000.0001.0000.149
4등급0.7890.0000.0000.0000.0000.0000.0000.1491.000

Missing values

2024-03-18T14:29:33.965678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T14:29:34.101282image/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

구분단독주택다세대주택연립주택아파트오피스텔1등급2등급3등급4등급데이터기준일자
0가정1동020000515002023-03-23
1가정2동000130013002023-03-23
2가정3동046000349302023-03-23
3가좌1동216610187002023-03-23
4가좌2동0200011002023-03-23
5가좌3동1287001026002023-03-23
6가좌4동1810036102023-03-23
7경서동0400031002023-03-23
8금곡동3300033002023-03-23
9당하동0201030002023-03-23
구분단독주택다세대주택연립주택아파트오피스텔1등급2등급3등급4등급데이터기준일자
14석남1동332100728102023-03-23
15석남2동226110821102023-03-23
16석남3동4460101237112023-03-23
17신현동01400068002023-03-23
18심곡동01100074002023-03-23
19연희동011020112002023-03-23
20청라동2000130002023-03-23
21오류동4000012012023-03-23
22왕길동8000022312023-03-23
23원창동5000020122023-03-23