Overview

Dataset statistics

Number of variables6
Number of observations77
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.9 KiB
Average record size in memory51.7 B

Variable types

Numeric2
Text1
Categorical3

Dataset

Description부산광역시수영구_빈집정비계획대상빈집목록_20220803
Author부산광역시 수영구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15060082

Alerts

밀집구역포함여부 has constant value ""Constant
연번 has unique valuesUnique
소재지 has unique valuesUnique

Reproduction

Analysis started2023-12-10 17:47:10.333123
Analysis finished2023-12-10 17:47:11.924448
Duration1.59 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct77
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39
Minimum1
Maximum77
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size825.0 B
2023-12-11T02:47:12.101570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.8
Q120
median39
Q358
95-th percentile73.2
Maximum77
Range76
Interquartile range (IQR)38

Descriptive statistics

Standard deviation22.371857
Coefficient of variation (CV)0.57363737
Kurtosis-1.2
Mean39
Median Absolute Deviation (MAD)19
Skewness0
Sum3003
Variance500.5
MonotonicityStrictly increasing
2023-12-11T02:47:12.455023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.3%
50 1
 
1.3%
57 1
 
1.3%
56 1
 
1.3%
55 1
 
1.3%
54 1
 
1.3%
53 1
 
1.3%
52 1
 
1.3%
51 1
 
1.3%
49 1
 
1.3%
Other values (67) 67
87.0%
ValueCountFrequency (%)
1 1
1.3%
2 1
1.3%
3 1
1.3%
4 1
1.3%
5 1
1.3%
6 1
1.3%
7 1
1.3%
8 1
1.3%
9 1
1.3%
10 1
1.3%
ValueCountFrequency (%)
77 1
1.3%
76 1
1.3%
75 1
1.3%
74 1
1.3%
73 1
1.3%
72 1
1.3%
71 1
1.3%
70 1
1.3%
69 1
1.3%
68 1
1.3%

소재지
Text

UNIQUE 

Distinct77
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size748.0 B
2023-12-11T02:47:12.962690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length26
Mean length21.298701
Min length18

Characters and Unicode

Total characters1640
Distinct characters33
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique77 ?
Unique (%)100.0%

Sample

1st row부산광역시 수영구 민락동 141-38
2nd row부산광역시 수영구 민락동 141-14
3rd row부산광역시 수영구 민락동 714-16
4th row부산광역시 수영구 민락동 714-15
5th row부산광역시 수영구 망미동 441-23
ValueCountFrequency (%)
부산광역시 77
25.0%
수영구 77
25.0%
광안동 28
 
9.1%
민락동 20
 
6.5%
망미동 20
 
6.5%
수영동 8
 
2.6%
958-10 1
 
0.3%
806-15 1
 
0.3%
453-26 1
 
0.3%
453-28 1
 
0.3%
Other values (74) 74
24.0%
2023-12-11T02:47:13.682914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
231
 
14.1%
광 105
 
6.4%
1 91
 
5.5%
수 85
 
5.2%
영 85
 
5.2%
동 78
 
4.8%
부 77
 
4.7%
역 77
 
4.7%
시 77
 
4.7%
구 77
 
4.7%
Other values (23) 657
40.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 871
53.1%
Decimal Number 420
25.6%
Space Separator 231
 
14.1%
Dash Punctuation 76
 
4.6%
Open Punctuation 21
 
1.3%
Close Punctuation 21
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 105
12.1%
수 85
9.8%
영 85
9.8%
동 78
9.0%
부 77
8.8%
역 77
8.8%
시 77
8.8%
구 77
8.8%
산 77
8.8%
안 28
 
3.2%
Other values (9) 105
12.1%
Decimal Number
ValueCountFrequency (%)
1 91
21.7%
2 63
15.0%
3 51
12.1%
4 44
10.5%
5 42
10.0%
0 39
9.3%
9 27
 
6.4%
7 27
 
6.4%
8 22
 
5.2%
6 14
 
3.3%
Space Separator
ValueCountFrequency (%)
231
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 76
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 871
53.1%
Common 769
46.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 105
12.1%
수 85
9.8%
영 85
9.8%
동 78
9.0%
부 77
8.8%
역 77
8.8%
시 77
8.8%
구 77
8.8%
산 77
8.8%
안 28
 
3.2%
Other values (9) 105
12.1%
Common
ValueCountFrequency (%)
231
30.0%
1 91
 
11.8%
- 76
 
9.9%
2 63
 
8.2%
3 51
 
6.6%
4 44
 
5.7%
5 42
 
5.5%
0 39
 
5.1%
9 27
 
3.5%
7 27
 
3.5%
Other values (4) 78
 
10.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 871
53.1%
ASCII 769
46.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
231
30.0%
1 91
 
11.8%
- 76
 
9.9%
2 63
 
8.2%
3 51
 
6.6%
4 44
 
5.7%
5 42
 
5.5%
0 39
 
5.1%
9 27
 
3.5%
7 27
 
3.5%
Other values (4) 78
 
10.1%
Hangul
ValueCountFrequency (%)
광 105
12.1%
수 85
9.8%
영 85
9.8%
동 78
9.0%
부 77
8.8%
역 77
8.8%
시 77
8.8%
구 77
8.8%
산 77
8.8%
안 28
 
3.2%
Other values (9) 105
12.1%

주택유형
Categorical

Distinct5
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size748.0 B
단독
55 
다세대
10 
아파트
9 
연립
 
2
다가구
 
1

Length

Max length3
Median length2
Mean length2.2597403
Min length2

Unique

Unique1 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
단독 55
71.4%
다세대 10
 
13.0%
아파트 9
 
11.7%
연립 2
 
2.6%
다가구 1
 
1.3%

Length

2023-12-11T02:47:13.944458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:47:14.162129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
단독 55
71.4%
다세대 10
 
13.0%
아파트 9
 
11.7%
연립 2
 
2.6%
다가구 1
 
1.3%

용도지역
Categorical

Distinct5
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size748.0 B
제2종일반주거지역
46 
제3종일반주거지역
15 
준주거지역
8 
일반상업지역
7 
준공업지역
 
1

Length

Max length9
Median length9
Mean length8.2597403
Min length5

Unique

Unique1 ?
Unique (%)1.3%

Sample

1st row제2종일반주거지역
2nd row제2종일반주거지역
3rd row제3종일반주거지역
4th row제3종일반주거지역
5th row제2종일반주거지역

Common Values

ValueCountFrequency (%)
제2종일반주거지역 46
59.7%
제3종일반주거지역 15
 
19.5%
준주거지역 8
 
10.4%
일반상업지역 7
 
9.1%
준공업지역 1
 
1.3%

Length

2023-12-11T02:47:14.408765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:47:14.668162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제2종일반주거지역 46
59.7%
제3종일반주거지역 15
 
19.5%
준주거지역 8
 
10.4%
일반상업지역 7
 
9.1%
준공업지역 1
 
1.3%

전용면적(제곱미터)
Real number (ℝ)

Distinct68
Distinct (%)88.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean117.06753
Minimum21.4
Maximum412.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size825.0 B
2023-12-11T02:47:14.928301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21.4
5-th percentile26
Q147.8
median100.2
Q3157
95-th percentile289.76
Maximum412.2
Range390.8
Interquartile range (IQR)109.2

Descriptive statistics

Standard deviation86.724126
Coefficient of variation (CV)0.74080426
Kurtosis2.2746033
Mean117.06753
Median Absolute Deviation (MAD)54.7
Skewness1.4306818
Sum9014.2
Variance7521.0741
MonotonicityNot monotonic
2023-12-11T02:47:15.236184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
84.9 4
 
5.2%
38.4 3
 
3.9%
47.8 2
 
2.6%
30.0 2
 
2.6%
33.0 2
 
2.6%
26.0 2
 
2.6%
101.2 1
 
1.3%
43.0 1
 
1.3%
185.8 1
 
1.3%
27.0 1
 
1.3%
Other values (58) 58
75.3%
ValueCountFrequency (%)
21.4 1
 
1.3%
21.7 1
 
1.3%
23.1 1
 
1.3%
26.0 2
2.6%
27.0 1
 
1.3%
30.0 2
2.6%
33.0 2
2.6%
36.0 1
 
1.3%
38.4 3
3.9%
40.0 1
 
1.3%
ValueCountFrequency (%)
412.2 1
1.3%
402.0 1
1.3%
341.9 1
1.3%
322.0 1
1.3%
281.7 1
1.3%
255.0 1
1.3%
249.0 1
1.3%
226.8 1
1.3%
222.0 1
1.3%
207.6 1
1.3%

밀집구역포함여부
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size748.0 B
미포함
77 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
미포함 77
100.0%

Length

2023-12-11T02:47:15.528149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:47:15.722115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미포함 77
100.0%

Interactions

2023-12-11T02:47:11.177107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:47:10.767967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:47:11.373143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:47:10.967782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T02:47:15.865043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번소재지주택유형용도지역전용면적(제곱미터)
연번1.0001.0000.5910.6960.513
소재지1.0001.0001.0001.0001.000
주택유형0.5911.0001.0000.6690.472
용도지역0.6961.0000.6691.0000.562
전용면적(제곱미터)0.5131.0000.4720.5621.000
2023-12-11T02:47:16.037170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주택유형용도지역
주택유형1.0000.305
용도지역0.3051.000
2023-12-11T02:47:16.219465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번전용면적(제곱미터)주택유형용도지역
연번1.0000.0120.2720.346
전용면적(제곱미터)0.0121.0000.2030.255
주택유형0.2720.2031.0000.305
용도지역0.3460.2550.3051.000

Missing values

2023-12-11T02:47:11.609923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T02:47:11.823440image/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

연번소재지주택유형용도지역전용면적(제곱미터)밀집구역포함여부
01부산광역시 수영구 민락동 141-38단독제2종일반주거지역164.0미포함
12부산광역시 수영구 민락동 141-14단독제2종일반주거지역173.2미포함
23부산광역시 수영구 민락동 714-16단독제3종일반주거지역30.0미포함
34부산광역시 수영구 민락동 714-15단독제3종일반주거지역30.0미포함
45부산광역시 수영구 망미동 441-23단독제2종일반주거지역144.3미포함
56부산광역시 수영구 민락동 223-14단독제3종일반주거지역33.0미포함
67부산광역시 수영구 민락동 715-13단독제3종일반주거지역26.0미포함
78부산광역시 수영구 민락동 716-22단독제3종일반주거지역26.0미포함
89부산광역시 수영구 민락동 121-9단독준주거지역322.0미포함
910부산광역시 수영구 광안동 1065-9단독제2종일반주거지역281.7미포함
연번소재지주택유형용도지역전용면적(제곱미터)밀집구역포함여부
6768부산광역시 수영구 민락동 225-3(404호)연립제3종일반주거지역21.4미포함
6869부산광역시 수영구 망미동 391-5단독제2종일반주거지역128.7미포함
6970부산광역시 수영구 망미동 119(501호)다세대제2종일반주거지역23.1미포함
7071부산광역시 수영구 망미동 109-5다가구제2종일반주거지역151.0미포함
7172부산광역시 수영구 망미동 453-3(가503호)아파트제2종일반주거지역49.0미포함
7273부산광역시 수영구 망미동 453-3(나205호)아파트제2종일반주거지역45.5미포함
7374부산광역시 수영구 광안동 775-4(501호)아파트일반상업지역56.0미포함
7475부산광역시 수영구 망미동 438-23단독제2종일반주거지역100.2미포함
7576부산광역시 수영구 광안동 94-2(203호)연립제2종일반주거지역47.8미포함
7677부산광역시 수영구 망미동 937-24(101호)다세대제2종일반주거지역54.3미포함