Overview

Dataset statistics

Number of variables7
Number of observations25
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 KiB
Average record size in memory62.3 B

Variable types

Categorical3
Text2
Numeric1
DateTime1

Dataset

Description울산광역시 구군별(북구, 남구, 중구, 동구, 울주군) 주택현황 및 임대주택현황 현황 정보(단지명, 공급자명)를 제공하고 있습니다.
URLhttps://www.data.go.kr/data/15054790/fileData.do

Alerts

단지명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 08:20:58.088749
Analysis finished2023-12-12 08:20:58.868774
Duration0.78 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

공급자명
Categorical

Distinct2
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
LH공사
21 
울산도시공사
4 

Length

Max length6
Median length4
Mean length4.32
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
LH공사 21
84.0%
울산도시공사 4
 
16.0%

Length

2023-12-12T17:20:58.969071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:20:59.134577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
lh공사 21
84.0%
울산도시공사 4
 
16.0%

시군구
Categorical

Distinct5
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
북구
10 
울주군
5 
남구
4 
중구
3 
동구
3 

Length

Max length3
Median length2
Mean length2.2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row중구
2nd row중구
3rd row남구
4th row동구
5th row동구

Common Values

ValueCountFrequency (%)
북구 10
40.0%
울주군 5
20.0%
남구 4
 
16.0%
중구 3
 
12.0%
동구 3
 
12.0%

Length

2023-12-12T17:20:59.290070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:20:59.782854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
북구 10
40.0%
울주군 5
20.0%
남구 4
 
16.0%
중구 3
 
12.0%
동구 3
 
12.0%

읍면동
Text

Distinct21
Distinct (%)84.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-12T17:21:00.024273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length6
Mean length7.08
Min length5

Characters and Unicode

Total characters177
Distinct characters55
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)72.0%

Sample

1st row중구 우정혁신(A-1)
2nd row중구 우정혁신(A-3)
3rd row남구 달동
4th row동구 화정동
5th row동구 방어동
ValueCountFrequency (%)
북구 10
19.2%
울주군 4
 
7.7%
동구 3
 
5.8%
중구 3
 
5.8%
남구 3
 
5.8%
송정동 3
 
5.8%
방어동 2
 
3.8%
청량면 2
 
3.8%
야음동 1
 
1.9%
여천로 1
 
1.9%
Other values (20) 20
38.5%
2023-12-12T17:21:00.428751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
27
 
15.3%
동 21
 
11.9%
구 20
 
11.3%
북 10
 
5.6%
정 7
 
4.0%
주 4
 
2.3%
중 4
 
2.3%
군 4
 
2.3%
울 4
 
2.3%
신 3
 
1.7%
Other values (45) 73
41.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 133
75.1%
Space Separator 27
 
15.3%
Decimal Number 9
 
5.1%
Close Punctuation 2
 
1.1%
Open Punctuation 2
 
1.1%
Uppercase Letter 2
 
1.1%
Dash Punctuation 2
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 21
 
15.8%
구 20
 
15.0%
북 10
 
7.5%
정 7
 
5.3%
주 4
 
3.0%
중 4
 
3.0%
군 4
 
3.0%
울 4
 
3.0%
신 3
 
2.3%
남 3
 
2.3%
Other values (34) 53
39.8%
Decimal Number
ValueCountFrequency (%)
1 3
33.3%
5 2
22.2%
0 1
 
11.1%
2 1
 
11.1%
9 1
 
11.1%
3 1
 
11.1%
Space Separator
ValueCountFrequency (%)
27
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 133
75.1%
Common 42
 
23.7%
Latin 2
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 21
 
15.8%
구 20
 
15.0%
북 10
 
7.5%
정 7
 
5.3%
주 4
 
3.0%
중 4
 
3.0%
군 4
 
3.0%
울 4
 
3.0%
신 3
 
2.3%
남 3
 
2.3%
Other values (34) 53
39.8%
Common
ValueCountFrequency (%)
27
64.3%
1 3
 
7.1%
5 2
 
4.8%
) 2
 
4.8%
( 2
 
4.8%
- 2
 
4.8%
0 1
 
2.4%
2 1
 
2.4%
9 1
 
2.4%
3 1
 
2.4%
Latin
ValueCountFrequency (%)
A 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 133
75.1%
ASCII 44
 
24.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
27
61.4%
1 3
 
6.8%
5 2
 
4.5%
) 2
 
4.5%
( 2
 
4.5%
A 2
 
4.5%
- 2
 
4.5%
0 1
 
2.3%
2 1
 
2.3%
9 1
 
2.3%
Hangul
ValueCountFrequency (%)
동 21
 
15.8%
구 20
 
15.0%
북 10
 
7.5%
정 7
 
5.3%
주 4
 
3.0%
중 4
 
3.0%
군 4
 
3.0%
울 4
 
3.0%
신 3
 
2.3%
남 3
 
2.3%
Other values (34) 53
39.8%

단지명
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-12T17:21:00.670896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length6.68
Min length4

Characters and Unicode

Total characters167
Distinct characters75
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)100.0%

Sample

1st row우정혁신 LH1단지
2nd row우정혁신 LH3단지
3rd row달동주공
4th row화정주공
5th row방어휴먼시아
ValueCountFrequency (%)
송정 3
 
9.7%
우정혁신 2
 
6.5%
국민임대 2
 
6.5%
구영주공1,2차 1
 
3.2%
3단지(1477-1 1
 
3.2%
2단지(1776-1 1
 
3.2%
병영삼일 1
 
3.2%
신정행복주택 1
 
3.2%
해피투게더타운 1
 
3.2%
hausd 1
 
3.2%
Other values (17) 17
54.8%
2023-12-12T17:21:01.079627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 10
 
6.0%
1 8
 
4.8%
공 8
 
4.8%
정 7
 
4.2%
6
 
3.6%
L 4
 
2.4%
H 4
 
2.4%
단 4
 
2.4%
지 4
 
2.4%
2 4
 
2.4%
Other values (65) 108
64.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 119
71.3%
Decimal Number 20
 
12.0%
Uppercase Letter 9
 
5.4%
Space Separator 6
 
3.6%
Lowercase Letter 4
 
2.4%
Other Punctuation 3
 
1.8%
Dash Punctuation 2
 
1.2%
Open Punctuation 2
 
1.2%
Close Punctuation 2
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 10
 
8.4%
공 8
 
6.7%
정 7
 
5.9%
단 4
 
3.4%
지 4
 
3.4%
우 3
 
2.5%
아 3
 
2.5%
운 3
 
2.5%
차 3
 
2.5%
송 3
 
2.5%
Other values (47) 71
59.7%
Decimal Number
ValueCountFrequency (%)
1 8
40.0%
2 4
20.0%
7 4
20.0%
3 2
 
10.0%
4 1
 
5.0%
6 1
 
5.0%
Lowercase Letter
ValueCountFrequency (%)
a 1
25.0%
h 1
25.0%
u 1
25.0%
s 1
25.0%
Uppercase Letter
ValueCountFrequency (%)
L 4
44.4%
H 4
44.4%
D 1
 
11.1%
Space Separator
ValueCountFrequency (%)
6
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 119
71.3%
Common 35
 
21.0%
Latin 13
 
7.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 10
 
8.4%
공 8
 
6.7%
정 7
 
5.9%
단 4
 
3.4%
지 4
 
3.4%
우 3
 
2.5%
아 3
 
2.5%
운 3
 
2.5%
차 3
 
2.5%
송 3
 
2.5%
Other values (47) 71
59.7%
Common
ValueCountFrequency (%)
1 8
22.9%
6
17.1%
2 4
11.4%
7 4
11.4%
, 3
 
8.6%
- 2
 
5.7%
3 2
 
5.7%
( 2
 
5.7%
) 2
 
5.7%
4 1
 
2.9%
Latin
ValueCountFrequency (%)
L 4
30.8%
H 4
30.8%
a 1
 
7.7%
h 1
 
7.7%
u 1
 
7.7%
s 1
 
7.7%
D 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 119
71.3%
ASCII 48
28.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 10
 
8.4%
공 8
 
6.7%
정 7
 
5.9%
단 4
 
3.4%
지 4
 
3.4%
우 3
 
2.5%
아 3
 
2.5%
운 3
 
2.5%
차 3
 
2.5%
송 3
 
2.5%
Other values (47) 71
59.7%
ASCII
ValueCountFrequency (%)
1 8
16.7%
6
12.5%
L 4
8.3%
H 4
8.3%
2 4
8.3%
7 4
8.3%
, 3
 
6.2%
- 2
 
4.2%
3 2
 
4.2%
( 2
 
4.2%
Other values (8) 9
18.8%

임대주택종류
Categorical

Distinct5
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
국민임대
15 
행복주택
4 
10년임대
3 
영구임대
2 
50년 임대
 
1

Length

Max length6
Median length4
Mean length4.2
Min length4

Unique

Unique1 ?
Unique (%)4.0%

Sample

1st row국민임대
2nd row10년임대
3rd row영구임대
4th row영구임대
5th row국민임대

Common Values

ValueCountFrequency (%)
국민임대 15
60.0%
행복주택 4
 
16.0%
10년임대 3
 
12.0%
영구임대 2
 
8.0%
50년 임대 1
 
4.0%

Length

2023-12-12T17:21:01.249499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:21:01.389869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국민임대 15
57.7%
행복주택 4
 
15.4%
10년임대 3
 
11.5%
영구임대 2
 
7.7%
50년 1
 
3.8%
임대 1
 
3.8%

세대수
Real number (ℝ)

Distinct22
Distinct (%)88.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean598.6
Minimum69
Maximum1378
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T17:21:01.526203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum69
5-th percentile88.8
Q1250
median534
Q3946
95-th percentile1236.8
Maximum1378
Range1309
Interquartile range (IQR)696

Descriptive statistics

Standard deviation418.10545
Coefficient of variation (CV)0.69847218
Kurtosis-1.2595815
Mean598.6
Median Absolute Deviation (MAD)398
Skewness0.26167889
Sum14965
Variance174812.17
MonotonicityNot monotonic
2023-12-12T17:21:01.719661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
100 3
 
12.0%
946 2
 
8.0%
736 1
 
4.0%
693 1
 
4.0%
437 1
 
4.0%
416 1
 
4.0%
250 1
 
4.0%
888 1
 
4.0%
404 1
 
4.0%
300 1
 
4.0%
Other values (12) 12
48.0%
ValueCountFrequency (%)
69 1
 
4.0%
86 1
 
4.0%
100 3
12.0%
136 1
 
4.0%
250 1
 
4.0%
266 1
 
4.0%
300 1
 
4.0%
404 1
 
4.0%
416 1
 
4.0%
437 1
 
4.0%
ValueCountFrequency (%)
1378 1
4.0%
1247 1
4.0%
1196 1
4.0%
1115 1
4.0%
984 1
4.0%
946 2
8.0%
918 1
4.0%
888 1
4.0%
736 1
4.0%
720 1
4.0%

준공일
Date

Distinct23
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
Minimum1991-07-01 00:00:00
Maximum2022-12-01 00:00:00
2023-12-12T17:21:01.894257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:21:02.035579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)

Interactions

2023-12-12T17:20:58.466215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:21:02.159594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공급자명시군구읍면동단지명임대주택종류세대수준공일
공급자명1.0000.1151.0001.0000.3170.1161.000
시군구0.1151.0001.0001.0000.7770.6581.000
읍면동1.0001.0001.0001.0000.7220.9270.975
단지명1.0001.0001.0001.0001.0001.0001.000
임대주택종류0.3170.7770.7221.0001.0000.0000.923
세대수0.1160.6580.9271.0000.0001.0000.968
준공일1.0001.0000.9751.0000.9230.9681.000
2023-12-12T17:21:02.291110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구공급자명임대주택종류
시군구1.0000.1020.390
공급자명0.1021.0000.352
임대주택종류0.3900.3521.000
2023-12-12T17:21:02.401091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세대수공급자명시군구임대주택종류
세대수1.0000.0000.2580.000
공급자명0.0001.0000.1020.352
시군구0.2580.1021.0000.390
임대주택종류0.0000.3520.3901.000

Missing values

2023-12-12T17:20:58.627476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:20:58.804555image/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

공급자명시군구읍면동단지명임대주택종류세대수준공일
0LH공사중구중구 우정혁신(A-1)우정혁신 LH1단지국민임대7362014-08-01
1LH공사중구중구 우정혁신(A-3)우정혁신 LH3단지10년임대1362014-09-01
2LH공사남구남구 달동달동주공영구임대13781994-02-01
3LH공사동구동구 화정동화정주공영구임대9841991-07-01
4LH공사동구동구 방어동방어휴먼시아국민임대9182011-12-01
5LH공사동구동구 방어동우진주공국민임대2661998-01-01
6LH공사북구북구 명촌동명촌주공국민임대5342003-04-01
7LH공사북구북구 호계동호계주공1,2차국민임대11962004-08-01
8LH공사북구북구 화봉동화봉휴먼시아1,2차국민임대12472009-04-01
9LH공사북구북구 매곡동매곡주공국민임대7202010-04-01
공급자명시군구읍면동단지명임대주택종류세대수준공일
15LH공사남구여천로 12번길 50LH해피투게더타운행복주택1002018-12-01
16LH공사북구북구 송정동송정 행복주택행복주택9462019-09-01
17LH공사북구북구 송정동송정 국민임대국민임대9462020-12-01
18LH공사북구북구 송정동송정 hausD10년임대4042020-02-01
19LH공사남구남구 야음동해피투게더타운행복주택1002018-12-01
20LH공사남구남구 신정동신정행복주택행복주택1002022-12-01
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