Overview

Dataset statistics

Number of variables5
Number of observations35
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 KiB
Average record size in memory43.8 B

Variable types

Text3
DateTime2

Dataset

Description경기도 포천시에서 제공하는 아파트 현황으로 아파트명, 아파트도로명주소, 아파트세대수, 사용승인일, 데이터 기준일 등을 제공합니다.
Author경기도 포천시
URLhttps://www.data.go.kr/data/15101357/fileData.do

Alerts

데이터기준일 has constant value ""Constant
아파트명 has unique valuesUnique
세대수 has unique valuesUnique

Reproduction

Analysis started2023-12-12 17:14:15.008514
Analysis finished2023-12-12 17:14:15.382066
Duration0.37 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아파트명
Text

UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size412.0 B
2023-12-13T02:14:15.546742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length8.0285714
Min length5

Characters and Unicode

Total characters281
Distinct characters95
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)100.0%

Sample

1st row일신건영아파트
2nd row원일1차아파트
3rd row한국개나리아파트
4th row원일2차아파트
5th row신포천아파트
ValueCountFrequency (%)
일신건영아파트 1
 
2.6%
포천신읍코아루더스카이1단지 1
 
2.6%
기산베스트빌아파트 1
 
2.6%
세창선단마을 1
 
2.6%
연봉마을(영화 1
 
2.6%
송천마을(주공2 1
 
2.6%
태봉마을(주공3 1
 
2.6%
상운아파트 1
 
2.6%
우정아파트 1
 
2.6%
포천신읍코아루더스카이2단지 1
 
2.6%
Other values (29) 29
74.4%
2023-12-13T02:14:15.928331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 22
 
7.8%
파 18
 
6.4%
트 17
 
6.0%
) 8
 
2.8%
( 8
 
2.8%
천 8
 
2.8%
신 8
 
2.8%
포 8
 
2.8%
차 7
 
2.5%
스 7
 
2.5%
Other values (85) 170
60.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 246
87.5%
Decimal Number 15
 
5.3%
Close Punctuation 8
 
2.8%
Open Punctuation 8
 
2.8%
Space Separator 4
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 22
 
8.9%
파 18
 
7.3%
트 17
 
6.9%
천 8
 
3.3%
신 8
 
3.3%
포 8
 
3.3%
차 7
 
2.8%
스 7
 
2.8%
마 6
 
2.4%
을 6
 
2.4%
Other values (77) 139
56.5%
Decimal Number
ValueCountFrequency (%)
2 7
46.7%
1 5
33.3%
5 1
 
6.7%
4 1
 
6.7%
3 1
 
6.7%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 246
87.5%
Common 35
 
12.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 22
 
8.9%
파 18
 
7.3%
트 17
 
6.9%
천 8
 
3.3%
신 8
 
3.3%
포 8
 
3.3%
차 7
 
2.8%
스 7
 
2.8%
마 6
 
2.4%
을 6
 
2.4%
Other values (77) 139
56.5%
Common
ValueCountFrequency (%)
) 8
22.9%
( 8
22.9%
2 7
20.0%
1 5
14.3%
4
11.4%
5 1
 
2.9%
4 1
 
2.9%
3 1
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 246
87.5%
ASCII 35
 
12.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 22
 
8.9%
파 18
 
7.3%
트 17
 
6.9%
천 8
 
3.3%
신 8
 
3.3%
포 8
 
3.3%
차 7
 
2.8%
스 7
 
2.8%
마 6
 
2.4%
을 6
 
2.4%
Other values (77) 139
56.5%
ASCII
ValueCountFrequency (%)
) 8
22.9%
( 8
22.9%
2 7
20.0%
1 5
14.3%
4
11.4%
5 1
 
2.9%
4 1
 
2.9%
3 1
 
2.9%

아파트도로명주소
Text

Distinct34
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size412.0 B
2023-12-13T02:14:16.163365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length23
Mean length19.828571
Min length14

Characters and Unicode

Total characters694
Distinct characters61
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)94.3%

Sample

1st row경기도 포천시 소흘읍 솔모루로 13-14, 16
2nd row경기도 포천시 소흘읍 봉솔로2길 15
3rd row경기도 포천시 소흘읍 솔모루로81번길 27
4th row경기도 포천시 소흘읍 봉솔로2길 5-9
5th row경기도 포천시 신북면 호국로 2135-11
ValueCountFrequency (%)
포천시 35
21.7%
경기도 34
21.1%
소흘읍 14
 
8.7%
태봉로 5
 
3.1%
호국로 4
 
2.5%
신북면 4
 
2.5%
군내면 3
 
1.9%
왕방로130번길 3
 
1.9%
29 2
 
1.2%
봉솔로2길 2
 
1.2%
Other values (51) 55
34.2%
2023-12-13T02:14:16.516006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
126
18.2%
포 36
 
5.2%
천 36
 
5.2%
경 35
 
5.0%
시 35
 
5.0%
1 35
 
5.0%
도 34
 
4.9%
기 34
 
4.9%
로 32
 
4.6%
2 20
 
2.9%
Other values (51) 271
39.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 413
59.5%
Decimal Number 137
 
19.7%
Space Separator 126
 
18.2%
Dash Punctuation 12
 
1.7%
Other Punctuation 2
 
0.3%
Close Punctuation 2
 
0.3%
Open Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
포 36
 
8.7%
천 36
 
8.7%
경 35
 
8.5%
시 35
 
8.5%
도 34
 
8.2%
기 34
 
8.2%
로 32
 
7.7%
읍 16
 
3.9%
흘 14
 
3.4%
길 14
 
3.4%
Other values (36) 127
30.8%
Decimal Number
ValueCountFrequency (%)
1 35
25.5%
2 20
14.6%
5 14
 
10.2%
3 14
 
10.2%
4 12
 
8.8%
6 12
 
8.8%
8 10
 
7.3%
7 8
 
5.8%
9 6
 
4.4%
0 6
 
4.4%
Space Separator
ValueCountFrequency (%)
126
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 413
59.5%
Common 281
40.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
포 36
 
8.7%
천 36
 
8.7%
경 35
 
8.5%
시 35
 
8.5%
도 34
 
8.2%
기 34
 
8.2%
로 32
 
7.7%
읍 16
 
3.9%
흘 14
 
3.4%
길 14
 
3.4%
Other values (36) 127
30.8%
Common
ValueCountFrequency (%)
126
44.8%
1 35
 
12.5%
2 20
 
7.1%
5 14
 
5.0%
3 14
 
5.0%
4 12
 
4.3%
- 12
 
4.3%
6 12
 
4.3%
8 10
 
3.6%
7 8
 
2.8%
Other values (5) 18
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 413
59.5%
ASCII 281
40.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
126
44.8%
1 35
 
12.5%
2 20
 
7.1%
5 14
 
5.0%
3 14
 
5.0%
4 12
 
4.3%
- 12
 
4.3%
6 12
 
4.3%
8 10
 
3.6%
7 8
 
2.8%
Other values (5) 18
 
6.4%
Hangul
ValueCountFrequency (%)
포 36
 
8.7%
천 36
 
8.7%
경 35
 
8.5%
시 35
 
8.5%
도 34
 
8.2%
기 34
 
8.2%
로 32
 
7.7%
읍 16
 
3.9%
흘 14
 
3.4%
길 14
 
3.4%
Other values (36) 127
30.8%

세대수
Text

UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size412.0 B
2023-12-13T02:14:16.715068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.3428571
Min length3

Characters and Unicode

Total characters117
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

Unique35 ?
Unique (%)100.0%

Sample

1st row176
2nd row489
3rd row292
4th row160
5th row299
ValueCountFrequency (%)
176 1
 
2.9%
998 1
 
2.9%
672 1
 
2.9%
212 1
 
2.9%
398 1
 
2.9%
310 1
 
2.9%
1,184 1
 
2.9%
1,803 1
 
2.9%
908 1
 
2.9%
498 1
 
2.9%
Other values (25) 25
71.4%
2023-12-13T02:14:17.054481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
13.7%
2 15
12.8%
6 14
12.0%
9 14
12.0%
8 12
10.3%
4 10
8.5%
3 9
7.7%
8
6.8%
7 6
 
5.1%
0 6
 
5.1%
Other values (2) 7
6.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 107
91.5%
Space Separator 8
 
6.8%
Other Punctuation 2
 
1.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
15.0%
2 15
14.0%
6 14
13.1%
9 14
13.1%
8 12
11.2%
4 10
9.3%
3 9
8.4%
7 6
 
5.6%
0 6
 
5.6%
5 5
 
4.7%
Space Separator
ValueCountFrequency (%)
8
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 117
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
13.7%
2 15
12.8%
6 14
12.0%
9 14
12.0%
8 12
10.3%
4 10
8.5%
3 9
7.7%
8
6.8%
7 6
 
5.1%
0 6
 
5.1%
Other values (2) 7
6.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 117
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 16
13.7%
2 15
12.8%
6 14
12.0%
9 14
12.0%
8 12
10.3%
4 10
8.5%
3 9
7.7%
8
6.8%
7 6
 
5.1%
0 6
 
5.1%
Other values (2) 7
6.0%

사용승인일
Date

Distinct33
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Memory size412.0 B
Minimum1993-03-17 00:00:00
Maximum2021-05-21 00:00:00
2023-12-13T02:14:17.201710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:14:17.364046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size412.0 B
Minimum2022-06-20 00:00:00
Maximum2022-06-20 00:00:00
2023-12-13T02:14:17.478131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:14:17.583030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Correlations

2023-12-13T02:14:17.664268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
아파트명아파트도로명주소세대수사용승인일
아파트명1.0001.0001.0001.000
아파트도로명주소1.0001.0001.0001.000
세대수1.0001.0001.0001.000
사용승인일1.0001.0001.0001.000

Missing values

2023-12-13T02:14:15.238719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:14:15.341017image/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

아파트명아파트도로명주소세대수사용승인일데이터기준일
0일신건영아파트경기도 포천시 소흘읍 솔모루로 13-14, 161761993-05-102022-06-20
1원일1차아파트경기도 포천시 소흘읍 봉솔로2길 154891993-07-302022-06-20
2한국개나리아파트경기도 포천시 소흘읍 솔모루로81번길 272921994-12-312022-06-20
3원일2차아파트경기도 포천시 소흘읍 봉솔로2길 5-91601995-08-082022-06-20
4신포천아파트경기도 포천시 신북면 호국로 2135-112991995-12-012022-06-20
5산호기지그린빌경기도 포천시 신북면 호국로 1886-274792002-04-302022-06-20
6윤중아파트경기도 포천시 신북면 호국로 2135-145782003-07-112022-06-20
7신아포미재아파트경기도 포천시 신북면 호국로 1886-432262005-01-122022-06-20
8한국아파트경기도 포천시 호병골길 162641993-03-172022-06-20
9현대아파트경기도 포천시 포천로 1642, 16441701996-10-182022-06-20
아파트명아파트도로명주소세대수사용승인일데이터기준일
25태봉마을(주공3)경기도 포천시 소흘읍 태봉로 1531,8032005-03-152022-06-20
26현대아이파크1차경기도 포천시 군내면 호국로1536-104982017-08-302022-06-20
27현대아이파크2차경기도 포천시 군내면 호국로1536-224612017-12-292022-06-20
28포천신읍코아루더스카이1단지경기도 포천시 원앙로 56-8(신읍동)1662020-02-072022-06-20
29포천신읍코아루더스카이2단지경기도 포천시 원앙로 56-7(신읍동)882020-02-072022-06-20
30포천송우서희스타힐스경기도 포천시 소흘읍 송선로608292021-05-212022-06-20
31고은마을(주공4)경기도 포천시 소흘읍 태봉로 12415312004-09-302022-06-20
32추산마을(주공5)경기도 포천시 소흘읍 태봉로 834662005-11-152022-06-20
33포천신읍 휴먼시아경기도 포천시 왕방로 118번길 73602010-11-012022-06-20
34포천 용정 행복주택포천시 군내면 용정경제로1길 143422018-05-142022-06-20