Overview

Dataset statistics

Number of variables13
Number of observations121
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.0 KiB
Average record size in memory110.1 B

Variable types

Numeric5
Text4
Categorical2
DateTime2

Dataset

Description관내 공동주택(아파트) 단지 현황에 대한 데이터로 단지명, 도로명주소, 지번주소, 주택유형, 사용검사일, 동수, 층수, 세대수, 연면적, 관리사무소 전화번호 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/3076795/fileData.do

Alerts

관리기관명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
번호 is highly overall correlated with 층수 and 1 other fieldsHigh correlation
동수 is highly overall correlated with 세대수 and 1 other fieldsHigh correlation
층수 is highly overall correlated with 번호 and 2 other fieldsHigh correlation
세대수 is highly overall correlated with 동수 and 2 other fieldsHigh correlation
연면적 is highly overall correlated with 번호 and 3 other fieldsHigh correlation
주택유형 is highly imbalanced (56.0%)Imbalance
번호 has unique valuesUnique
단지명 has unique valuesUnique
도로명주소 has unique valuesUnique
지번주소 has unique valuesUnique

Reproduction

Analysis started2023-12-12 10:04:34.924290
Analysis finished2023-12-12 10:04:39.017619
Duration4.09 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct121
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean61
Minimum1
Maximum121
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T19:04:39.119589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7
Q131
median61
Q391
95-th percentile115
Maximum121
Range120
Interquartile range (IQR)60

Descriptive statistics

Standard deviation35.073732
Coefficient of variation (CV)0.57497921
Kurtosis-1.2
Mean61
Median Absolute Deviation (MAD)30
Skewness0
Sum7381
Variance1230.1667
MonotonicityStrictly increasing
2023-12-12T19:04:39.320620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.8%
92 1
 
0.8%
90 1
 
0.8%
89 1
 
0.8%
88 1
 
0.8%
87 1
 
0.8%
86 1
 
0.8%
85 1
 
0.8%
84 1
 
0.8%
83 1
 
0.8%
Other values (111) 111
91.7%
ValueCountFrequency (%)
1 1
0.8%
2 1
0.8%
3 1
0.8%
4 1
0.8%
5 1
0.8%
6 1
0.8%
7 1
0.8%
8 1
0.8%
9 1
0.8%
10 1
0.8%
ValueCountFrequency (%)
121 1
0.8%
120 1
0.8%
119 1
0.8%
118 1
0.8%
117 1
0.8%
116 1
0.8%
115 1
0.8%
114 1
0.8%
113 1
0.8%
112 1
0.8%

단지명
Text

UNIQUE 

Distinct121
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-12T19:04:39.634029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length19
Mean length8.5041322
Min length2

Characters and Unicode

Total characters1029
Distinct characters182
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique121 ?
Unique (%)100.0%

Sample

1st row금용1차
2nd row금용2차
3rd row융보
4th row세아1차
5th row신우
ValueCountFrequency (%)
양주옥정신도시 5
 
2.8%
이편한세상 4
 
2.2%
2차 3
 
1.7%
디에트르 3
 
1.7%
덕계역 2
 
1.1%
로제비앙 2
 
1.1%
메트로파크 2
 
1.1%
현진에버빌 2
 
1.1%
1차 2
 
1.1%
센텀시티 2
 
1.1%
Other values (138) 151
84.8%
2023-12-12T19:04:40.111765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
58
 
5.6%
지 49
 
4.8%
단 45
 
4.4%
양 32
 
3.1%
주 28
 
2.7%
차 28
 
2.7%
1 23
 
2.2%
정 22
 
2.1%
마 21
 
2.0%
을 21
 
2.0%
Other values (172) 702
68.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 829
80.6%
Decimal Number 81
 
7.9%
Space Separator 58
 
5.6%
Uppercase Letter 24
 
2.3%
Close Punctuation 17
 
1.7%
Open Punctuation 17
 
1.7%
Dash Punctuation 2
 
0.2%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 49
 
5.9%
단 45
 
5.4%
양 32
 
3.9%
주 28
 
3.4%
차 28
 
3.4%
정 22
 
2.7%
마 21
 
2.5%
을 21
 
2.5%
시 20
 
2.4%
옥 18
 
2.2%
Other values (151) 545
65.7%
Decimal Number
ValueCountFrequency (%)
1 23
28.4%
2 17
21.0%
3 14
17.3%
6 6
 
7.4%
4 6
 
7.4%
5 5
 
6.2%
7 5
 
6.2%
8 4
 
4.9%
9 1
 
1.2%
Uppercase Letter
ValueCountFrequency (%)
S 6
25.0%
H 5
20.8%
N 4
16.7%
F 4
16.7%
T 3
12.5%
G 1
 
4.2%
L 1
 
4.2%
Space Separator
ValueCountFrequency (%)
58
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
s 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 829
80.6%
Common 175
 
17.0%
Latin 25
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 49
 
5.9%
단 45
 
5.4%
양 32
 
3.9%
주 28
 
3.4%
차 28
 
3.4%
정 22
 
2.7%
마 21
 
2.5%
을 21
 
2.5%
시 20
 
2.4%
옥 18
 
2.2%
Other values (151) 545
65.7%
Common
ValueCountFrequency (%)
58
33.1%
1 23
 
13.1%
) 17
 
9.7%
2 17
 
9.7%
( 17
 
9.7%
3 14
 
8.0%
6 6
 
3.4%
4 6
 
3.4%
5 5
 
2.9%
7 5
 
2.9%
Other values (3) 7
 
4.0%
Latin
ValueCountFrequency (%)
S 6
24.0%
H 5
20.0%
N 4
16.0%
F 4
16.0%
T 3
12.0%
s 1
 
4.0%
G 1
 
4.0%
L 1
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 829
80.6%
ASCII 200
 
19.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
58
29.0%
1 23
 
11.5%
) 17
 
8.5%
2 17
 
8.5%
( 17
 
8.5%
3 14
 
7.0%
6 6
 
3.0%
4 6
 
3.0%
S 6
 
3.0%
H 5
 
2.5%
Other values (11) 31
15.5%
Hangul
ValueCountFrequency (%)
지 49
 
5.9%
단 45
 
5.4%
양 32
 
3.9%
주 28
 
3.4%
차 28
 
3.4%
정 22
 
2.7%
마 21
 
2.5%
을 21
 
2.5%
시 20
 
2.4%
옥 18
 
2.2%
Other values (151) 545
65.7%

도로명주소
Text

UNIQUE 

Distinct121
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-12T19:04:40.475893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length28
Mean length22.429752
Min length6

Characters and Unicode

Total characters2714
Distinct characters175
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique121 ?
Unique (%)100.0%

Sample

1st row평화로1429번길 43-10 (덕계동, 금용아파트)
2nd row평화로 1552-19 (회정동, 금융아파트)
3rd row독바위로 55 (덕정동, 융보아파트)
4th row백석읍 꿈나무로 136 (세아1차 아파트)
5th row평화로1416번길 14 (덕계동, 신우아파트)
ValueCountFrequency (%)
백석읍 16
 
3.7%
덕계동 14
 
3.2%
부흥로 10
 
2.3%
삼숭동 10
 
2.3%
고암길 8
 
1.8%
옥정동로 8
 
1.8%
꿈나무로 8
 
1.8%
고읍동 7
 
1.6%
고읍로 6
 
1.4%
만송동 6
 
1.4%
Other values (267) 341
78.6%
2023-12-12T19:04:41.039909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
467
 
17.2%
1 122
 
4.5%
로 109
 
4.0%
) 92
 
3.4%
( 91
 
3.4%
아 82
 
3.0%
2 78
 
2.9%
동 78
 
2.9%
트 77
 
2.8%
파 72
 
2.7%
Other values (165) 1446
53.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1424
52.5%
Decimal Number 534
 
19.7%
Space Separator 467
 
17.2%
Close Punctuation 92
 
3.4%
Open Punctuation 91
 
3.4%
Other Punctuation 58
 
2.1%
Dash Punctuation 37
 
1.4%
Uppercase Letter 11
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 109
 
7.7%
아 82
 
5.8%
동 78
 
5.5%
트 77
 
5.4%
파 72
 
5.1%
길 50
 
3.5%
고 48
 
3.4%
읍 39
 
2.7%
정 39
 
2.7%
지 36
 
2.5%
Other values (143) 794
55.8%
Decimal Number
ValueCountFrequency (%)
1 122
22.8%
2 78
14.6%
3 58
10.9%
5 51
9.6%
4 43
 
8.1%
8 40
 
7.5%
6 40
 
7.5%
0 39
 
7.3%
9 33
 
6.2%
7 30
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
T 3
27.3%
S 3
27.3%
R 1
 
9.1%
A 1
 
9.1%
P 1
 
9.1%
I 1
 
9.1%
K 1
 
9.1%
Space Separator
ValueCountFrequency (%)
467
100.0%
Close Punctuation
ValueCountFrequency (%)
) 92
100.0%
Open Punctuation
ValueCountFrequency (%)
( 91
100.0%
Other Punctuation
ValueCountFrequency (%)
, 58
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 37
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1424
52.5%
Common 1279
47.1%
Latin 11
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 109
 
7.7%
아 82
 
5.8%
동 78
 
5.5%
트 77
 
5.4%
파 72
 
5.1%
길 50
 
3.5%
고 48
 
3.4%
읍 39
 
2.7%
정 39
 
2.7%
지 36
 
2.5%
Other values (143) 794
55.8%
Common
ValueCountFrequency (%)
467
36.5%
1 122
 
9.5%
) 92
 
7.2%
( 91
 
7.1%
2 78
 
6.1%
, 58
 
4.5%
3 58
 
4.5%
5 51
 
4.0%
4 43
 
3.4%
8 40
 
3.1%
Other values (5) 179
 
14.0%
Latin
ValueCountFrequency (%)
T 3
27.3%
S 3
27.3%
R 1
 
9.1%
A 1
 
9.1%
P 1
 
9.1%
I 1
 
9.1%
K 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1424
52.5%
ASCII 1290
47.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
467
36.2%
1 122
 
9.5%
) 92
 
7.1%
( 91
 
7.1%
2 78
 
6.0%
, 58
 
4.5%
3 58
 
4.5%
5 51
 
4.0%
4 43
 
3.3%
8 40
 
3.1%
Other values (12) 190
14.7%
Hangul
ValueCountFrequency (%)
로 109
 
7.7%
아 82
 
5.8%
동 78
 
5.5%
트 77
 
5.4%
파 72
 
5.1%
길 50
 
3.5%
고 48
 
3.4%
읍 39
 
2.7%
정 39
 
2.7%
지 36
 
2.5%
Other values (143) 794
55.8%

지번주소
Text

UNIQUE 

Distinct121
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-12T19:04:41.410164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length7
Mean length8.322314
Min length5

Characters and Unicode

Total characters1007
Distinct characters51
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique121 ?
Unique (%)100.0%

Sample

1st row덕계동 670
2nd row회정동 871
3rd row덕정동 280-5
4th row백석읍 오산리 107-2
5th row덕계동 417-1
ValueCountFrequency (%)
옥정동 29
 
11.0%
덕계동 19
 
7.2%
백석읍 15
 
5.7%
삼숭동 11
 
4.2%
복지리 8
 
3.0%
고읍동 7
 
2.7%
고암동 7
 
2.7%
광사동 7
 
2.7%
덕정동 6
 
2.3%
만송동 6
 
2.3%
Other values (133) 148
56.3%
2023-12-12T19:04:41.832034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
142
 
14.1%
동 97
 
9.6%
1 63
 
6.3%
6 45
 
4.5%
9 45
 
4.5%
8 39
 
3.9%
5 38
 
3.8%
정 38
 
3.8%
2 37
 
3.7%
4 37
 
3.7%
Other values (41) 426
42.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 434
43.1%
Decimal Number 399
39.6%
Space Separator 142
 
14.1%
Dash Punctuation 32
 
3.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 97
22.4%
정 38
 
8.8%
옥 29
 
6.7%
덕 26
 
6.0%
리 24
 
5.5%
읍 22
 
5.1%
계 19
 
4.4%
석 17
 
3.9%
백 15
 
3.5%
고 14
 
3.2%
Other values (29) 133
30.6%
Decimal Number
ValueCountFrequency (%)
1 63
15.8%
6 45
11.3%
9 45
11.3%
8 39
9.8%
5 38
9.5%
2 37
9.3%
4 37
9.3%
0 37
9.3%
7 30
7.5%
3 28
7.0%
Space Separator
ValueCountFrequency (%)
142
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 573
56.9%
Hangul 434
43.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 97
22.4%
정 38
 
8.8%
옥 29
 
6.7%
덕 26
 
6.0%
리 24
 
5.5%
읍 22
 
5.1%
계 19
 
4.4%
석 17
 
3.9%
백 15
 
3.5%
고 14
 
3.2%
Other values (29) 133
30.6%
Common
ValueCountFrequency (%)
142
24.8%
1 63
11.0%
6 45
 
7.9%
9 45
 
7.9%
8 39
 
6.8%
5 38
 
6.6%
2 37
 
6.5%
4 37
 
6.5%
0 37
 
6.5%
- 32
 
5.6%
Other values (2) 58
10.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 573
56.9%
Hangul 434
43.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
142
24.8%
1 63
11.0%
6 45
 
7.9%
9 45
 
7.9%
8 39
 
6.8%
5 38
 
6.6%
2 37
 
6.5%
4 37
 
6.5%
0 37
 
6.5%
- 32
 
5.6%
Other values (2) 58
10.1%
Hangul
ValueCountFrequency (%)
동 97
22.4%
정 38
 
8.8%
옥 29
 
6.7%
덕 26
 
6.0%
리 24
 
5.5%
읍 22
 
5.1%
계 19
 
4.4%
석 17
 
3.9%
백 15
 
3.5%
고 14
 
3.2%
Other values (29) 133
30.6%

주택유형
Categorical

IMBALANCE 

Distinct5
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
분양
97 
임대
15 
공공임대리츠
 
4
행복주택
 
3
기업형임대주택
 
2

Length

Max length7
Median length2
Mean length2.2644628
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
분양 97
80.2%
임대 15
 
12.4%
공공임대리츠 4
 
3.3%
행복주택 3
 
2.5%
기업형임대주택 2
 
1.7%

Length

2023-12-12T19:04:41.950289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:04:42.040217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
분양 97
80.2%
임대 15
 
12.4%
공공임대리츠 4
 
3.3%
행복주택 3
 
2.5%
기업형임대주택 2
 
1.7%

사용검사일
Date

Distinct107
Distinct (%)88.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum1991-06-15 00:00:00
Maximum2023-05-12 00:00:00
2023-12-12T19:04:42.142920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:04:42.270424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

동수
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)16.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.1735537
Minimum1
Maximum28
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T19:04:42.389504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q15
median8
Q310
95-th percentile17
Maximum28
Range27
Interquartile range (IQR)5

Descriptive statistics

Standard deviation4.6738237
Coefficient of variation (CV)0.57182272
Kurtosis2.8392911
Mean8.1735537
Median Absolute Deviation (MAD)3
Skewness1.2333993
Sum989
Variance21.844628
MonotonicityNot monotonic
2023-12-12T19:04:42.492632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
9 16
13.2%
8 13
10.7%
5 12
9.9%
7 10
8.3%
4 9
 
7.4%
6 9
 
7.4%
11 8
 
6.6%
2 8
 
6.6%
10 7
 
5.8%
13 5
 
4.1%
Other values (10) 24
19.8%
ValueCountFrequency (%)
1 4
 
3.3%
2 8
6.6%
3 4
 
3.3%
4 9
7.4%
5 12
9.9%
6 9
7.4%
7 10
8.3%
8 13
10.7%
9 16
13.2%
10 7
5.8%
ValueCountFrequency (%)
28 1
 
0.8%
24 1
 
0.8%
20 2
 
1.7%
18 2
 
1.7%
17 1
 
0.8%
15 1
 
0.8%
14 5
4.1%
13 5
4.1%
12 3
 
2.5%
11 8
6.6%

층수
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)17.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.380165
Minimum8
Maximum37
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T19:04:42.623138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile13
Q115
median15
Q325
95-th percentile29
Maximum37
Range29
Interquartile range (IQR)10

Descriptive statistics

Standard deviation6.3799898
Coefficient of variation (CV)0.32920203
Kurtosis0.017972311
Mean19.380165
Median Absolute Deviation (MAD)2
Skewness0.94774673
Sum2345
Variance40.70427
MonotonicityNot monotonic
2023-12-12T19:04:42.735995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
15 55
45.5%
25 11
 
9.1%
29 10
 
8.3%
20 8
 
6.6%
27 4
 
3.3%
28 3
 
2.5%
21 3
 
2.5%
12 3
 
2.5%
18 3
 
2.5%
19 3
 
2.5%
Other values (11) 18
 
14.9%
ValueCountFrequency (%)
8 1
 
0.8%
10 1
 
0.8%
12 3
 
2.5%
13 3
 
2.5%
14 3
 
2.5%
15 55
45.5%
17 1
 
0.8%
18 3
 
2.5%
19 3
 
2.5%
20 8
 
6.6%
ValueCountFrequency (%)
37 3
 
2.5%
35 1
 
0.8%
34 1
 
0.8%
29 10
8.3%
28 3
 
2.5%
27 4
 
3.3%
26 1
 
0.8%
25 11
9.1%
24 2
 
1.7%
23 1
 
0.8%

세대수
Real number (ℝ)

HIGH CORRELATION 

Distinct113
Distinct (%)93.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean669.55372
Minimum152
Maximum2038
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T19:04:42.863684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum152
5-th percentile204
Q1376
median514
Q3860
95-th percentile1566
Maximum2038
Range1886
Interquartile range (IQR)484

Descriptive statistics

Standard deviation420.75713
Coefficient of variation (CV)0.6284143
Kurtosis1.4171706
Mean669.55372
Median Absolute Deviation (MAD)230
Skewness1.3119762
Sum81016
Variance177036.57
MonotonicityNot monotonic
2023-12-12T19:04:43.019452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
498 3
 
2.5%
499 3
 
2.5%
619 2
 
1.7%
608 2
 
1.7%
492 2
 
1.7%
320 2
 
1.7%
188 1
 
0.8%
1618 1
 
0.8%
1256 1
 
0.8%
1862 1
 
0.8%
Other values (103) 103
85.1%
ValueCountFrequency (%)
152 1
0.8%
156 1
0.8%
184 1
0.8%
188 1
0.8%
195 1
0.8%
203 1
0.8%
204 1
0.8%
205 1
0.8%
207 1
0.8%
210 1
0.8%
ValueCountFrequency (%)
2038 1
0.8%
1935 1
0.8%
1862 1
0.8%
1859 1
0.8%
1732 1
0.8%
1618 1
0.8%
1566 1
0.8%
1550 1
0.8%
1500 1
0.8%
1483 1
0.8%

연면적
Real number (ℝ)

HIGH CORRELATION 

Distinct120
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean83111.041
Minimum11732
Maximum305874
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T19:04:43.169507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11732
5-th percentile21035
Q141679
median68752
Q3106220
95-th percentile198965
Maximum305874
Range294142
Interquartile range (IQR)64541

Descriptive statistics

Standard deviation57404.091
Coefficient of variation (CV)0.69069151
Kurtosis2.8102225
Mean83111.041
Median Absolute Deviation (MAD)30063
Skewness1.5115225
Sum10056436
Variance3.2952297 × 109
MonotonicityNot monotonic
2023-12-12T19:04:43.351213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
72319 2
 
1.7%
15755 1
 
0.8%
41281 1
 
0.8%
86613 1
 
0.8%
165978 1
 
0.8%
81553 1
 
0.8%
59062 1
 
0.8%
98807 1
 
0.8%
98815 1
 
0.8%
149525 1
 
0.8%
Other values (110) 110
90.9%
ValueCountFrequency (%)
11732 1
0.8%
14286 1
0.8%
15755 1
0.8%
16788 1
0.8%
18038 1
0.8%
18630 1
0.8%
21035 1
0.8%
21244 1
0.8%
22195 1
0.8%
22468 1
0.8%
ValueCountFrequency (%)
305874 1
0.8%
302497 1
0.8%
238889 1
0.8%
229330 1
0.8%
209556 1
0.8%
208663 1
0.8%
198965 1
0.8%
190023 1
0.8%
166396 1
0.8%
165978 1
0.8%

관리사무소 전화번호
Text

Distinct120
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-12T19:04:43.627468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters1452
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique119 ?
Unique (%)98.3%

Sample

1st row031-864-4349
2nd row031-858-0575
3rd row031-858-5822
4th row031-879-3740
5th row031-865-0377
ValueCountFrequency (%)
031-857-5438 2
 
1.7%
031-864-4349 1
 
0.8%
031-862-3200 1
 
0.8%
031-865-9866 1
 
0.8%
031-866-9007 1
 
0.8%
031-857-8990 1
 
0.8%
031-878-0055 1
 
0.8%
031-866-1613 1
 
0.8%
031-862-9988 1
 
0.8%
031-857-5069 1
 
0.8%
Other values (110) 110
90.9%
2023-12-12T19:04:44.060317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 242
16.7%
0 198
13.6%
1 191
13.2%
8 184
12.7%
3 182
12.5%
7 96
 
6.6%
2 86
 
5.9%
5 81
 
5.6%
6 68
 
4.7%
4 66
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1210
83.3%
Dash Punctuation 242
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 198
16.4%
1 191
15.8%
8 184
15.2%
3 182
15.0%
7 96
7.9%
2 86
7.1%
5 81
6.7%
6 68
 
5.6%
4 66
 
5.5%
9 58
 
4.8%
Dash Punctuation
ValueCountFrequency (%)
- 242
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1452
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 242
16.7%
0 198
13.6%
1 191
13.2%
8 184
12.7%
3 182
12.5%
7 96
 
6.6%
2 86
 
5.9%
5 81
 
5.6%
6 68
 
4.7%
4 66
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1452
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 242
16.7%
0 198
13.6%
1 191
13.2%
8 184
12.7%
3 182
12.5%
7 96
 
6.6%
2 86
 
5.9%
5 81
 
5.6%
6 68
 
4.7%
4 66
 
4.5%

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
양주시 주택과
121 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row양주시 주택과
2nd row양주시 주택과
3rd row양주시 주택과
4th row양주시 주택과
5th row양주시 주택과

Common Values

ValueCountFrequency (%)
양주시 주택과 121
100.0%

Length

2023-12-12T19:04:44.228665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:04:44.348334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
양주시 121
50.0%
주택과 121
50.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2023-06-22 00:00:00
Maximum2023-06-22 00:00:00
2023-12-12T19:04:44.425899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:04:44.535298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T19:04:37.856625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:04:35.553422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:04:36.178657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:04:36.719806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:04:37.299260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:04:37.956605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:04:35.678363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:04:36.287595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:04:36.829583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:04:37.421534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:04:38.348522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:04:35.794380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:04:36.392255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:04:36.938763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:04:37.542244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:04:38.449188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:04:35.912392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:04:36.493772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:04:37.070135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:04:37.660616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:04:38.554932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:04:36.040454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:04:36.614010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:04:37.202162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:04:37.757168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T19:04:44.612292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호주택유형동수층수세대수연면적
번호1.0000.6610.6510.6740.5840.511
주택유형0.6611.0000.0000.7080.0000.038
동수0.6510.0001.0000.6630.8900.792
층수0.6740.7080.6631.0000.5580.647
세대수0.5840.0000.8900.5581.0000.822
연면적0.5110.0380.7920.6470.8221.000
2023-12-12T19:04:44.756508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호동수층수세대수연면적주택유형
번호1.0000.4130.5320.4950.5420.326
동수0.4131.0000.3810.8430.8690.000
층수0.5320.3811.0000.5770.6430.361
세대수0.4950.8430.5771.0000.9150.000
연면적0.5420.8690.6430.9151.0000.000
주택유형0.3260.0000.3610.0000.0001.000

Missing values

2023-12-12T19:04:38.714010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:04:38.924167image/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

번호단지명도로명주소지번주소주택유형사용검사일동수층수세대수연면적관리사무소 전화번호관리기관명데이터기준일자
01금용1차평화로1429번길 43-10 (덕계동, 금용아파트)덕계동 670분양1991-06-1511218815755031-864-4349양주시 주택과2023-06-22
12금용2차평화로 1552-19 (회정동, 금융아파트)회정동 871분양1992-10-1921518418038031-858-0575양주시 주택과2023-06-22
23융보독바위로 55 (덕정동, 융보아파트)덕정동 280-5분양1992-12-1911519521244031-858-5822양주시 주택과2023-06-22
34세아1차백석읍 꿈나무로 136 (세아1차 아파트)백석읍 오산리 107-2분양1993-09-2021728231341031-879-3740양주시 주택과2023-06-22
45신우평화로1416번길 14 (덕계동, 신우아파트)덕계동 417-1분양1994-12-0531549148607031-865-0377양주시 주택과2023-06-22
56삼희고덕로139번길 248-30 (덕계동, 삼희아파트)덕계동 271-44분양1996-09-0311321011732031-865-2324양주시 주택과2023-06-22
67희망광적면 광적로 85-18 (희망아파트)광적면 광석리 1-1분양1996-12-2141543639278031-837-3742양주시 주택과2023-06-22
78세아2차백석읍 꿈나무로 31-4 (세아2차 아파트)백석읍 방성리 162-4분양1997-07-0121415616788031-879-3459양주시 주택과2023-06-22
89덕계현대고덕로139번길 361-21 (덕계동, 현대아파트)덕계동 203-6분양1997-07-0922035035777031-862-8240양주시 주택과2023-06-22
910가야2차백석읍 호명로 77 (가야 2차 아파트)백석읍 복지리 93-3분양1997-07-2531528925834031-879-4334양주시 주택과2023-06-22
번호단지명도로명주소지번주소주택유형사용검사일동수층수세대수연면적관리사무소 전화번호관리기관명데이터기준일자
111112덕계역 금강펜테리움 센트럴파크고덕로 15덕계동 915분양2023-01-25629935112698031-857-4563양주시 주택과2023-06-22
112113양주옥정 유림노르웨이숲옥정로2길 229옥정동 1097분양2023-01-2614351140190023031-868-2982양주시 주택과2023-06-22
113114양주옥정더원파크빌리지독바위로 287번길 51옥정동 893분양2023-01-272810930164596031-857-9901양주시 주택과2023-06-22
114115양주회천 14단지회천중앙로 281덕계동 792임대2023-02-1672095771895031-857-3317양주시 주택과2023-06-22
115116양주옥정신도시 제일풍경채 레이크시티 2단지옥정동로 190옥정동 1043-1분양2023-04-0713291228209556031-868-9122양주시 주택과2023-06-22
116117덕계역 대광로제비앙 더 메트로팰리스덕계로 137덕계동 937분양2023-04-1962942481269031-868-9909양주시 주택과2023-06-22
117118양주옥정신도시 한신더휴옥정서로 1길 65옥정동 938분양2023-04-19929767134614031-857-2227양주시 주택과2023-06-22
118119양주고읍 14단지고읍남로 80광사동 716행복주택2023-04-2041537226926031-843-7161양주시 주택과2023-06-22
119120양주옥정신도시 디에트르 에듀포레(대방3차)옥정서로 5길 55옥정동 869분양2023-05-118371086166396031-857-3600양주시 주택과2023-06-22
120121양주옥정신도시 제일풍경채 레이크시티 1단지옥정동로 212옥정동 1043분양2023-05-1213281246208663031-863-3005양주시 주택과2023-06-22