Overview

Dataset statistics

Number of variables16
Number of observations232
Missing cells42
Missing cells (%)1.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory29.8 KiB
Average record size in memory131.6 B

Variable types

Categorical6
Text5
DateTime2
Numeric3

Dataset

Description파주시 관내 준공된 공동주택에 대한 데이터로서 관리구부(의무, 임의), 분양임대, 주소, 단지명 주택종류, 사용검사일 ,세대수 등의 정보를 제공합니다.
Author경기도 파주시
URLhttps://www.data.go.kr/data/15022129/fileData.do

Alerts

관리기관명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
동수 is highly overall correlated with 세대수 High correlation
세대수 is highly overall correlated with 동수 High correlation
우편번호 is highly overall correlated with 행정구역 and 1 other fieldsHigh correlation
행정구역 is highly overall correlated with 우편번호 and 1 other fieldsHigh correlation
관리기관전화번호 is highly overall correlated with 우편번호 and 1 other fieldsHigh correlation
분양임대 is highly imbalanced (50.2%)Imbalance
관리사무소전화번호 has 42 (18.1%) missing valuesMissing

Reproduction

Analysis started2023-12-12 00:24:07.599735
Analysis finished2023-12-12 00:24:09.977332
Duration2.38 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리구분
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
의무
124 
임의
108 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row의무
2nd row의무
3rd row임의
4th row임의
5th row임의

Common Values

ValueCountFrequency (%)
의무 124
53.4%
임의 108
46.6%

Length

2023-12-12T09:24:10.031580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:24:10.110201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
의무 124
53.4%
임의 108
46.6%

분양임대
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
분양
191 
임대
34 
혼합
 
7

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
분양 191
82.3%
임대 34
 
14.7%
혼합 7
 
3.0%

Length

2023-12-12T09:24:10.212418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:24:10.308658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
분양 191
82.3%
임대 34
 
14.7%
혼합 7
 
3.0%

행정구역
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
문산읍
35 
금촌1동
28 
조리읍
24 
운정1동
20 
운정5동
20 
Other values (13)
105 

Length

Max length4
Median length4
Mean length3.6336207
Min length3

Unique

Unique3 ?
Unique (%)1.3%

Sample

1st row문산읍
2nd row문산읍
3rd row문산읍
4th row금촌1동
5th row금촌1동

Common Values

ValueCountFrequency (%)
문산읍 35
15.1%
금촌1동 28
12.1%
조리읍 24
10.3%
운정1동 20
8.6%
운정5동 20
8.6%
운정2동 18
7.8%
금촌2동 18
7.8%
금촌3동 17
7.3%
운정3동 16
6.9%
운정6동 10
 
4.3%
Other values (8) 26
11.2%

Length

2023-12-12T09:24:10.426197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
문산읍 35
15.1%
금촌1동 28
12.1%
조리읍 24
10.3%
운정1동 20
8.6%
운정5동 20
8.6%
운정2동 18
7.8%
금촌2동 18
7.8%
금촌3동 17
7.3%
운정3동 16
6.9%
운정6동 10
 
4.3%
Other values (8) 26
11.2%

소재지도로명주소
Text

Distinct228
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-12T09:24:10.690647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length37
Mean length25.176724
Min length13

Characters and Unicode

Total characters5841
Distinct characters221
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique224 ?
Unique (%)96.6%

Sample

1st row경기도 파주시 문산읍 문산로26번길 35
2nd row경기도 파주시 문산읍 문산로26번길 35
3rd row경기도 파주시 문산읍 독서울5길 5
4th row경기도 파주시 금정6길 11 (금촌동, 동산연립)
5th row경기도 파주시 금정4길 21-6 (금촌동, 동산연립)
ValueCountFrequency (%)
경기도 232
 
18.6%
파주시 232
 
18.6%
문산읍 35
 
2.8%
금촌동 26
 
2.1%
조리읍 23
 
1.8%
파주운정3 16
 
1.3%
동패동 14
 
1.1%
와동동 13
 
1.0%
책향기로 11
 
0.9%
정담길 9
 
0.7%
Other values (406) 637
51.0%
2023-12-12T09:24:11.217231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1018
 
17.4%
파 303
 
5.2%
주 278
 
4.8%
기 250
 
4.3%
시 243
 
4.2%
경 234
 
4.0%
도 232
 
4.0%
동 187
 
3.2%
로 175
 
3.0%
1 173
 
3.0%
Other values (211) 2748
47.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3647
62.4%
Space Separator 1018
 
17.4%
Decimal Number 783
 
13.4%
Open Punctuation 120
 
2.1%
Close Punctuation 119
 
2.0%
Other Punctuation 110
 
1.9%
Dash Punctuation 22
 
0.4%
Uppercase Letter 22
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
파 303
 
8.3%
주 278
 
7.6%
기 250
 
6.9%
시 243
 
6.7%
경 234
 
6.4%
도 232
 
6.4%
동 187
 
5.1%
로 175
 
4.8%
길 77
 
2.1%
읍 72
 
2.0%
Other values (193) 1596
43.8%
Decimal Number
ValueCountFrequency (%)
1 173
22.1%
2 121
15.5%
3 107
13.7%
0 96
12.3%
5 70
8.9%
6 61
 
7.8%
4 53
 
6.8%
7 42
 
5.4%
9 31
 
4.0%
8 29
 
3.7%
Other Punctuation
ValueCountFrequency (%)
, 106
96.4%
· 4
 
3.6%
Uppercase Letter
ValueCountFrequency (%)
A 20
90.9%
B 2
 
9.1%
Space Separator
ValueCountFrequency (%)
1018
100.0%
Open Punctuation
ValueCountFrequency (%)
( 120
100.0%
Close Punctuation
ValueCountFrequency (%)
) 119
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3647
62.4%
Common 2172
37.2%
Latin 22
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
파 303
 
8.3%
주 278
 
7.6%
기 250
 
6.9%
시 243
 
6.7%
경 234
 
6.4%
도 232
 
6.4%
동 187
 
5.1%
로 175
 
4.8%
길 77
 
2.1%
읍 72
 
2.0%
Other values (193) 1596
43.8%
Common
ValueCountFrequency (%)
1018
46.9%
1 173
 
8.0%
2 121
 
5.6%
( 120
 
5.5%
) 119
 
5.5%
3 107
 
4.9%
, 106
 
4.9%
0 96
 
4.4%
5 70
 
3.2%
6 61
 
2.8%
Other values (6) 181
 
8.3%
Latin
ValueCountFrequency (%)
A 20
90.9%
B 2
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3647
62.4%
ASCII 2190
37.5%
None 4
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1018
46.5%
1 173
 
7.9%
2 121
 
5.5%
( 120
 
5.5%
) 119
 
5.4%
3 107
 
4.9%
, 106
 
4.8%
0 96
 
4.4%
5 70
 
3.2%
6 61
 
2.8%
Other values (7) 199
 
9.1%
Hangul
ValueCountFrequency (%)
파 303
 
8.3%
주 278
 
7.6%
기 250
 
6.9%
시 243
 
6.7%
경 234
 
6.4%
도 232
 
6.4%
동 187
 
5.1%
로 175
 
4.8%
길 77
 
2.1%
읍 72
 
2.0%
Other values (193) 1596
43.8%
None
ValueCountFrequency (%)
· 4
100.0%

소재지지번주소
Text

Distinct231
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-12T09:24:11.558665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length35
Mean length20.107759
Min length14

Characters and Unicode

Total characters4665
Distinct characters86
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

Unique230 ?
Unique (%)99.1%

Sample

1st row경기도 파주시 문산읍 문산리 31-1
2nd row경기도 파주시 문산읍 문산리 31-1
3rd row경기도 파주시 문산읍 선유리 426-10
4th row경기도 파주시 금촌동 773-6
5th row경기도 파주시 금촌동 775-2
ValueCountFrequency (%)
경기도 232
22.1%
파주시 232
22.1%
금촌동 43
 
4.1%
문산읍 35
 
3.3%
동패동 24
 
2.3%
조리읍 24
 
2.3%
봉일천리 22
 
2.1%
목동동 19
 
1.8%
와동동 17
 
1.6%
아동동 14
 
1.3%
Other values (290) 389
37.0%
2023-12-12T09:24:12.062411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
819
17.6%
도 254
 
5.4%
시 254
 
5.4%
동 254
 
5.4%
파 253
 
5.4%
주 253
 
5.4%
경 232
 
5.0%
기 232
 
5.0%
1 222
 
4.8%
2 132
 
2.8%
Other values (76) 1760
37.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2644
56.7%
Decimal Number 971
 
20.8%
Space Separator 819
 
17.6%
Dash Punctuation 115
 
2.5%
Uppercase Letter 36
 
0.8%
Open Punctuation 34
 
0.7%
Close Punctuation 34
 
0.7%
Other Punctuation 12
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 254
 
9.6%
시 254
 
9.6%
동 254
 
9.6%
파 253
 
9.6%
주 253
 
9.6%
경 232
 
8.8%
기 232
 
8.8%
리 109
 
4.1%
읍 73
 
2.8%
문 51
 
1.9%
Other values (55) 679
25.7%
Decimal Number
ValueCountFrequency (%)
1 222
22.9%
2 132
13.6%
9 94
9.7%
7 92
9.5%
3 83
 
8.5%
0 81
 
8.3%
5 74
 
7.6%
4 73
 
7.5%
8 64
 
6.6%
6 56
 
5.8%
Uppercase Letter
ValueCountFrequency (%)
A 31
86.1%
C 3
 
8.3%
L 1
 
2.8%
B 1
 
2.8%
Other Punctuation
ValueCountFrequency (%)
, 10
83.3%
/ 1
 
8.3%
. 1
 
8.3%
Space Separator
ValueCountFrequency (%)
819
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 115
100.0%
Open Punctuation
ValueCountFrequency (%)
( 34
100.0%
Close Punctuation
ValueCountFrequency (%)
) 34
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2644
56.7%
Common 1985
42.6%
Latin 36
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 254
 
9.6%
시 254
 
9.6%
동 254
 
9.6%
파 253
 
9.6%
주 253
 
9.6%
경 232
 
8.8%
기 232
 
8.8%
리 109
 
4.1%
읍 73
 
2.8%
문 51
 
1.9%
Other values (55) 679
25.7%
Common
ValueCountFrequency (%)
819
41.3%
1 222
 
11.2%
2 132
 
6.6%
- 115
 
5.8%
9 94
 
4.7%
7 92
 
4.6%
3 83
 
4.2%
0 81
 
4.1%
5 74
 
3.7%
4 73
 
3.7%
Other values (7) 200
 
10.1%
Latin
ValueCountFrequency (%)
A 31
86.1%
C 3
 
8.3%
L 1
 
2.8%
B 1
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2644
56.7%
ASCII 2021
43.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
819
40.5%
1 222
 
11.0%
2 132
 
6.5%
- 115
 
5.7%
9 94
 
4.7%
7 92
 
4.6%
3 83
 
4.1%
0 81
 
4.0%
5 74
 
3.7%
4 73
 
3.6%
Other values (11) 236
 
11.7%
Hangul
ValueCountFrequency (%)
도 254
 
9.6%
시 254
 
9.6%
동 254
 
9.6%
파 253
 
9.6%
주 253
 
9.6%
경 232
 
8.8%
기 232
 
8.8%
리 109
 
4.1%
읍 73
 
2.8%
문 51
 
1.9%
Other values (55) 679
25.7%

단지명
Text

Distinct224
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-12T09:24:12.300075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length19
Mean length8.9568966
Min length2

Characters and Unicode

Total characters2078
Distinct characters247
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

Unique218 ?
Unique (%)94.0%

Sample

1st row문산주공
2nd row문산주공
3rd row동산연립
4th row동산연립
5th row동산연립
ValueCountFrequency (%)
휴먼시아 9
 
2.9%
동문굿모닝힐 5
 
1.6%
동산연립 4
 
1.3%
한라비발디 3
 
1.0%
헤르만하우스 2
 
0.6%
후곡마을뜨란채 2
 
0.6%
무궁화(가,나동 2
 
0.6%
롯데캐슬 2
 
0.6%
삼부르네상스 2
 
0.6%
문산주공 2
 
0.6%
Other values (278) 279
89.4%
2023-12-12T09:24:12.648494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 98
 
4.7%
단 93
 
4.5%
을 92
 
4.4%
마 90
 
4.3%
80
 
3.8%
1 62
 
3.0%
동 41
 
2.0%
차 38
 
1.8%
산 35
 
1.7%
파 34
 
1.6%
Other values (237) 1415
68.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1771
85.2%
Decimal Number 175
 
8.4%
Space Separator 80
 
3.8%
Open Punctuation 17
 
0.8%
Close Punctuation 17
 
0.8%
Other Punctuation 9
 
0.4%
Uppercase Letter 8
 
0.4%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 98
 
5.5%
단 93
 
5.3%
을 92
 
5.2%
마 90
 
5.1%
동 41
 
2.3%
차 38
 
2.1%
산 35
 
2.0%
파 34
 
1.9%
연 32
 
1.8%
주 30
 
1.7%
Other values (214) 1188
67.1%
Decimal Number
ValueCountFrequency (%)
1 62
35.4%
2 27
15.4%
3 21
 
12.0%
6 11
 
6.3%
0 11
 
6.3%
5 10
 
5.7%
4 10
 
5.7%
7 9
 
5.1%
8 8
 
4.6%
9 6
 
3.4%
Uppercase Letter
ValueCountFrequency (%)
S 1
12.5%
I 1
12.5%
L 1
12.5%
H 1
12.5%
K 1
12.5%
R 1
12.5%
A 1
12.5%
P 1
12.5%
Space Separator
ValueCountFrequency (%)
80
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Other Punctuation
ValueCountFrequency (%)
, 9
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1771
85.2%
Common 298
 
14.3%
Latin 9
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 98
 
5.5%
단 93
 
5.3%
을 92
 
5.2%
마 90
 
5.1%
동 41
 
2.3%
차 38
 
2.1%
산 35
 
2.0%
파 34
 
1.9%
연 32
 
1.8%
주 30
 
1.7%
Other values (214) 1188
67.1%
Common
ValueCountFrequency (%)
80
26.8%
1 62
20.8%
2 27
 
9.1%
3 21
 
7.0%
( 17
 
5.7%
) 17
 
5.7%
6 11
 
3.7%
0 11
 
3.7%
5 10
 
3.4%
4 10
 
3.4%
Other values (4) 32
 
10.7%
Latin
ValueCountFrequency (%)
S 1
11.1%
I 1
11.1%
L 1
11.1%
H 1
11.1%
e 1
11.1%
K 1
11.1%
R 1
11.1%
A 1
11.1%
P 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1771
85.2%
ASCII 307
 
14.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 98
 
5.5%
단 93
 
5.3%
을 92
 
5.2%
마 90
 
5.1%
동 41
 
2.3%
차 38
 
2.1%
산 35
 
2.0%
파 34
 
1.9%
연 32
 
1.8%
주 30
 
1.7%
Other values (214) 1188
67.1%
ASCII
ValueCountFrequency (%)
80
26.1%
1 62
20.2%
2 27
 
8.8%
3 21
 
6.8%
( 17
 
5.5%
) 17
 
5.5%
6 11
 
3.6%
0 11
 
3.6%
5 10
 
3.3%
4 10
 
3.3%
Other values (13) 41
13.4%

주택종류
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
아파트
192 
연립
40 

Length

Max length3
Median length3
Mean length2.8275862
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row아파트
2nd row아파트
3rd row연립
4th row연립
5th row연립

Common Values

ValueCountFrequency (%)
아파트 192
82.8%
연립 40
 
17.2%

Length

2023-12-12T09:24:12.768474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:24:12.854117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
아파트 192
82.8%
연립 40
 
17.2%

사용검사일
Date

Distinct212
Distinct (%)91.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
Minimum1980-01-23 00:00:00
Maximum2023-08-31 00:00:00
2023-12-12T09:24:12.950465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:24:13.070461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

층수
Text

Distinct82
Distinct (%)35.3%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-12T09:24:13.323123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length3.2672414
Min length2

Characters and Unicode

Total characters758
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique54 ?
Unique (%)23.3%

Sample

1st row05
2nd row05
3rd row03
4th row03
5th row03
ValueCountFrequency (%)
15 35
 
15.1%
03 33
 
14.2%
05 17
 
7.3%
18 7
 
3.0%
14 6
 
2.6%
15~25 6
 
2.6%
10~15 6
 
2.6%
04 5
 
2.2%
08 5
 
2.2%
14~15 5
 
2.2%
Other values (72) 107
46.1%
2023-12-12T09:24:13.724315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 176
23.2%
0 124
16.4%
5 112
14.8%
2 96
12.7%
~ 95
12.5%
3 57
 
7.5%
4 28
 
3.7%
8 26
 
3.4%
9 23
 
3.0%
7 14
 
1.8%
Other values (2) 7
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 660
87.1%
Math Symbol 95
 
12.5%
Dash Punctuation 3
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 176
26.7%
0 124
18.8%
5 112
17.0%
2 96
14.5%
3 57
 
8.6%
4 28
 
4.2%
8 26
 
3.9%
9 23
 
3.5%
7 14
 
2.1%
6 4
 
0.6%
Math Symbol
ValueCountFrequency (%)
~ 95
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 758
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 176
23.2%
0 124
16.4%
5 112
14.8%
2 96
12.7%
~ 95
12.5%
3 57
 
7.5%
4 28
 
3.7%
8 26
 
3.4%
9 23
 
3.0%
7 14
 
1.8%
Other values (2) 7
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 758
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 176
23.2%
0 124
16.4%
5 112
14.8%
2 96
12.7%
~ 95
12.5%
3 57
 
7.5%
4 28
 
3.7%
8 26
 
3.4%
9 23
 
3.0%
7 14
 
1.8%
Other values (2) 7
 
0.9%

동수
Real number (ℝ)

HIGH CORRELATION 

Distinct27
Distinct (%)11.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.7068966
Minimum1
Maximum50
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-12T09:24:13.870466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median6
Q311.25
95-th percentile20
Maximum50
Range49
Interquartile range (IQR)9.25

Descriptive statistics

Standard deviation6.9469446
Coefficient of variation (CV)0.90139325
Kurtosis5.8361634
Mean7.7068966
Median Absolute Deviation (MAD)4
Skewness1.7533607
Sum1788
Variance48.260039
MonotonicityNot monotonic
2023-12-12T09:24:13.988401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
2 45
19.4%
1 34
14.7%
5 14
 
6.0%
9 14
 
6.0%
3 13
 
5.6%
8 13
 
5.6%
7 10
 
4.3%
13 10
 
4.3%
10 10
 
4.3%
11 9
 
3.9%
Other values (17) 60
25.9%
ValueCountFrequency (%)
1 34
14.7%
2 45
19.4%
3 13
 
5.6%
4 7
 
3.0%
5 14
 
6.0%
6 5
 
2.2%
7 10
 
4.3%
8 13
 
5.6%
9 14
 
6.0%
10 10
 
4.3%
ValueCountFrequency (%)
50 1
 
0.4%
33 1
 
0.4%
31 1
 
0.4%
25 1
 
0.4%
24 2
0.9%
22 1
 
0.4%
21 3
1.3%
20 3
1.3%
19 4
1.7%
18 3
1.3%

세대수
Real number (ℝ)

HIGH CORRELATION 

Distinct198
Distinct (%)85.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean557.44828
Minimum12
Maximum3042
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-12T09:24:14.104951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12
5-th percentile32.55
Q1109.5
median366.5
Q3850.75
95-th percentile1597.3
Maximum3042
Range3030
Interquartile range (IQR)741.25

Descriptive statistics

Standard deviation568.37168
Coefficient of variation (CV)1.0195954
Kurtosis3.2375564
Mean557.44828
Median Absolute Deviation (MAD)300
Skewness1.5887422
Sum129328
Variance323046.37
MonotonicityNot monotonic
2023-12-12T09:24:14.276762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36 6
 
2.6%
80 4
 
1.7%
300 3
 
1.3%
180 3
 
1.3%
33 3
 
1.3%
12 2
 
0.9%
148 2
 
0.9%
138 2
 
0.9%
320 2
 
0.9%
227 2
 
0.9%
Other values (188) 203
87.5%
ValueCountFrequency (%)
12 2
 
0.9%
20 1
 
0.4%
21 2
 
0.9%
24 2
 
0.9%
27 1
 
0.4%
28 1
 
0.4%
30 2
 
0.9%
32 1
 
0.4%
33 3
1.3%
36 6
2.6%
ValueCountFrequency (%)
3042 1
0.4%
2998 1
0.4%
2944 1
0.4%
2190 1
0.4%
1956 1
0.4%
1880 1
0.4%
1818 1
0.4%
1810 1
0.4%
1759 1
0.4%
1745 1
0.4%

관리사무소전화번호
Text

MISSING 

Distinct182
Distinct (%)95.8%
Missing42
Missing (%)18.1%
Memory size1.9 KiB
2023-12-12T09:24:14.519978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.021053
Min length12

Characters and Unicode

Total characters2284
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

Unique176 ?
Unique (%)92.6%

Sample

1st row031-952-3563
2nd row031-953-2816
3rd row031-943-2158
4th row031-943-2158
5th row031-944-9855
ValueCountFrequency (%)
031-944-9855 3
 
1.6%
031-953-0226 3
 
1.6%
031-945-7473 2
 
1.1%
031-955-8688 2
 
1.1%
031-957-8067 2
 
1.1%
031-943-2158 2
 
1.1%
031-952-2633 1
 
0.5%
031-952-5093 1
 
0.5%
031-941-6585 1
 
0.5%
031-957-7795 1
 
0.5%
Other values (172) 172
90.5%
2023-12-12T09:24:14.861602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 380
16.6%
3 313
13.7%
1 283
12.4%
0 281
12.3%
9 263
11.5%
4 219
9.6%
5 152
 
6.7%
2 112
 
4.9%
7 97
 
4.2%
8 92
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1904
83.4%
Dash Punctuation 380
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 313
16.4%
1 283
14.9%
0 281
14.8%
9 263
13.8%
4 219
11.5%
5 152
8.0%
2 112
 
5.9%
7 97
 
5.1%
8 92
 
4.8%
6 92
 
4.8%
Dash Punctuation
ValueCountFrequency (%)
- 380
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2284
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 380
16.6%
3 313
13.7%
1 283
12.4%
0 281
12.3%
9 263
11.5%
4 219
9.6%
5 152
 
6.7%
2 112
 
4.9%
7 97
 
4.2%
8 92
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2284
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 380
16.6%
3 313
13.7%
1 283
12.4%
0 281
12.3%
9 263
11.5%
4 219
9.6%
5 152
 
6.7%
2 112
 
4.9%
7 97
 
4.2%
8 92
 
4.0%

우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct76
Distinct (%)32.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10884.453
Minimum10803
Maximum10948
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-12T09:24:15.021769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10803
5-th percentile10813
Q110852
median10892
Q310923
95-th percentile10938
Maximum10948
Range145
Interquartile range (IQR)71

Descriptive statistics

Standard deviation42.047874
Coefficient of variation (CV)0.0038631134
Kurtosis-1.1303693
Mean10884.453
Median Absolute Deviation (MAD)33.5
Skewness-0.35737572
Sum2525193
Variance1768.0237
MonotonicityNot monotonic
2023-12-12T09:24:15.158345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10937 11
 
4.7%
10852 9
 
3.9%
10938 9
 
3.9%
10932 8
 
3.4%
10921 7
 
3.0%
10888 7
 
3.0%
10819 7
 
3.0%
10895 7
 
3.0%
10826 7
 
3.0%
10874 6
 
2.6%
Other values (66) 154
66.4%
ValueCountFrequency (%)
10803 1
 
0.4%
10811 1
 
0.4%
10812 5
2.2%
10813 6
2.6%
10814 2
 
0.9%
10815 3
1.3%
10819 7
3.0%
10820 3
1.3%
10821 1
 
0.4%
10822 1
 
0.4%
ValueCountFrequency (%)
10948 3
 
1.3%
10945 1
 
0.4%
10944 1
 
0.4%
10943 1
 
0.4%
10939 2
 
0.9%
10938 9
3.9%
10937 11
4.7%
10936 1
 
0.4%
10932 8
3.4%
10931 3
 
1.3%

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
경기도 파주시청
232 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경기도 파주시청
2nd row경기도 파주시청
3rd row경기도 파주시청
4th row경기도 파주시청
5th row경기도 파주시청

Common Values

ValueCountFrequency (%)
경기도 파주시청 232
100.0%

Length

2023-12-12T09:24:15.268842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:24:15.345956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 232
50.0%
파주시청 232
50.0%

관리기관전화번호
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
031-940-4720
145 
031-940-4945
36 
031-940-4942
23 
031-940-4952
17 
031-940-4943
 
10

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row031-940-4664
2nd row031-940-4720
3rd row031-940-4720
4th row031-940-4720
5th row031-940-4720

Common Values

ValueCountFrequency (%)
031-940-4720 145
62.5%
031-940-4945 36
 
15.5%
031-940-4942 23
 
9.9%
031-940-4952 17
 
7.3%
031-940-4943 10
 
4.3%
031-940-4664 1
 
0.4%

Length

2023-12-12T09:24:15.426308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:24:15.513371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
031-940-4720 145
62.5%
031-940-4945 36
 
15.5%
031-940-4942 23
 
9.9%
031-940-4952 17
 
7.3%
031-940-4943 10
 
4.3%
031-940-4664 1
 
0.4%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
Minimum2023-11-10 00:00:00
Maximum2023-11-10 00:00:00
2023-12-12T09:24:15.634495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:24:15.756797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T09:24:09.059378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:24:08.494039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:24:08.799240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:24:09.141330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:24:08.602203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:24:08.886214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:24:09.226077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:24:08.692537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:24:08.968241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T09:24:15.830885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리구분분양임대행정구역주택종류층수동수세대수우편번호관리기관전화번호
관리구분1.0000.2810.4000.6510.7790.3700.4850.3600.221
분양임대0.2811.0000.4690.1150.9070.2610.5970.4120.588
행정구역0.4000.4691.0000.6240.0000.5430.5000.9600.993
주택종류0.6510.1150.6241.0000.9910.2800.4600.3770.188
층수0.7790.9070.0000.9911.0000.8960.9470.6810.749
동수0.3700.2610.5430.2800.8961.0000.7670.4930.499
세대수0.4850.5970.5000.4600.9470.7671.0000.4920.547
우편번호0.3600.4120.9600.3770.6810.4930.4921.0000.835
관리기관전화번호0.2210.5880.9930.1880.7490.4990.5470.8351.000
2023-12-12T09:24:15.964600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주택종류관리기관전화번호행정구역분양임대관리구분
주택종류1.0000.1340.4800.1900.451
관리기관전화번호0.1341.0000.8510.2930.158
행정구역0.4800.8511.0000.2370.304
분양임대0.1900.2930.2371.0000.455
관리구분0.4510.1580.3040.4551.000
2023-12-12T09:24:16.088824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
동수세대수우편번호관리구분분양임대행정구역주택종류관리기관전화번호
동수1.0000.868-0.1610.3920.1790.2700.2960.325
세대수0.8681.000-0.1360.4790.3190.1840.4530.306
우편번호-0.161-0.1361.0000.2740.2670.8080.2770.634
관리구분0.3920.4790.2741.0000.4550.3040.4510.158
분양임대0.1790.3190.2670.4551.0000.2370.1900.293
행정구역0.2700.1840.8080.3040.2371.0000.4800.851
주택종류0.2960.4530.2770.4510.1900.4801.0000.134
관리기관전화번호0.3250.3060.6340.1580.2930.8510.1341.000

Missing values

2023-12-12T09:24:09.697328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:24:09.905832image/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

관리구분분양임대행정구역소재지도로명주소소재지지번주소단지명주택종류사용검사일층수동수세대수관리사무소전화번호우편번호관리기관명관리기관전화번호데이터기준일자
0의무분양문산읍경기도 파주시 문산읍 문산로26번길 35경기도 파주시 문산읍 문산리 31-1문산주공아파트1980-01-23057300<NA>10823경기도 파주시청031-940-46642023-11-10
1의무분양문산읍경기도 파주시 문산읍 문산로26번길 35경기도 파주시 문산읍 문산리 31-1문산주공아파트1980-01-23057300031-952-356310823경기도 파주시청031-940-47202023-11-10
2임의분양문산읍경기도 파주시 문산읍 독서울5길 5경기도 파주시 문산읍 선유리 426-10동산연립연립1983-12-3003228<NA>10811경기도 파주시청031-940-47202023-11-10
3임의분양금촌1동경기도 파주시 금정6길 11 (금촌동, 동산연립)경기도 파주시 금촌동 773-6동산연립연립1984-09-1103221<NA>10923경기도 파주시청031-940-47202023-11-10
4임의분양금촌1동경기도 파주시 금정4길 21-6 (금촌동, 동산연립)경기도 파주시 금촌동 775-2동산연립연립1984-09-1103332<NA>10923경기도 파주시청031-940-47202023-11-10
5임의분양금촌1동경기도 파주시 금정로 9 (금촌동, 장안연립)경기도 파주시 금촌동 787-5장안연립연립1984-11-1903127<NA>10924경기도 파주시청031-940-47202023-11-10
6임의분양금촌1동경기도 파주시 금정4길 19-5 (금촌동, 대진연립)경기도 파주시 금촌동 774-4대진연립연립1984-12-2603336<NA>10923경기도 파주시청031-940-47202023-11-10
7임의분양금촌1동경기도 파주시 새꽃로 242-3 (아동동, 우촌연립)경기도 파주시 아동동 354-6우촌연립연립1985-01-0903130<NA>10931경기도 파주시청031-940-47202023-11-10
8임의분양조리읍경기도 파주시 조리읍 순비골길 10경기도 파주시 조리읍 봉일천리 139-17태양연립(가,나동)연립1985-01-1503248<NA>10937경기도 파주시청031-940-47202023-11-10
9임의분양운정1동경기도 파주시 운정로 2 (상지석동, 경안주택)경기도 파주시 상지석동 977-7경안주택연립1985-02-1803696<NA>10910경기도 파주시청031-940-49452023-11-10
관리구분분양임대행정구역소재지도로명주소소재지지번주소단지명주택종류사용검사일층수동수세대수관리사무소전화번호우편번호관리기관명관리기관전화번호데이터기준일자
222임의임대운정6동경기도 파주시 초롱꽃로 17(동패동, 파주운정3 A34)경기도 파주시 동패동 2070초롱꽃마을3단지 휴먼하우징아파트2022-08-2207~15121448031-943-302410887경기도 파주시청031-940-49432023-11-10
223의무분양운정5동경기도 파주시 청암로 82 (다율동, 파주운정3 A13)경기도 파주시 다율동 1035해오름마을14단지 운정신도시푸르지오파르세나아파트2022-08-2315~25201745031-948-446610865경기도 파주시청031-940-49422023-11-10
224임의분양운정1동경기도 파주시 가온로 210(와동동, 파주운정1·2 B2)경기도 파주시 와동동 1409해솔마을9단지 누메르연립2022-08-3103338<NA>10897경기도 파주시청031-940-49452023-11-10
225의무분양파주읍경기도 파주시 파주읍 주락길 69경기도 파주시 파주읍 연풍리 484파주연풍양우내안애에코하임아파트2022-09-0613~249475031-954-224610865경기도 파주시청031-940-47202023-11-10
226임의임대운정6동경기도 파주시 초롱꽃로 118(동패동, 파주운정3 A31)경기도 파주시 동패동 2118초롱꽃마을9단지 우미린센터포레아파트2023-01-19159522031-949-513010888경기도 파주시청031-940-49432023-11-10
227임의임대운정5동경기도 파주시 노을빛로 41(문발동, 파주교하 A16)경기도 파주시 문발동 558노을빛마을16단지아파트2023-02-03085320031-943-837210879경기도 파주시청031-940-49422023-11-10
228임의임대운정6동경기도 파주시 운정중앙로 200(목동동, 파주운정3 A37)경기도 파주시 목동동 385물향기마을1단지아파트2023-02-1615~2481810031-941-658510873경기도 파주시청031-940-49432023-11-10
229의무분양운정2동경기도 파주시 산내로 89(목동동, 파주운정1·2 A37)경기도 파주시 목동동 1009산내마을13단지 파주운정신도시디에트르라포레아파트2023-02-2310~156297031-949-231210892경기도 파주시청031-940-49452023-11-10
230의무혼합운정1동경기도 파주시 가람로134번길 24(와동동, 파주와동 A1)경기도 파주시 와동동 1521가람마을12단지 별숲오르트아파트2023-07-1417~275434031-941-873210896경기도 파주시청031-940-49452023-11-10
231의무분양운정2동경기도 파주시 산내로 90(목동동, 파주운정1·2 A35)경기도 파주시 목동동 989산내마을12단지 디에트르더클래스아파트2023-08-3110~159512031-943-301110892경기도 파주시청031-940-49452023-11-10