Overview

Dataset statistics

Number of variables8
Number of observations413
Missing cells137
Missing cells (%)4.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory27.2 KiB
Average record size in memory67.3 B

Variable types

Categorical1
Text3
Numeric3
DateTime1

Dataset

Description충청남도 천안시 공동주택 현황 데이터입니다. 충청남도 천안시 공동주택의 공동주택명, 주소, 세대수, 층수 , 관리실번호 등의 항목들을 제공합니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=59&beforeMenuCd=DOM_000000201001001000&publicdatapk=15111700

Alerts

지역 has constant value ""Constant
세대수 is highly overall correlated with 층수 and 1 other fieldsHigh correlation
층수 is highly overall correlated with 세대수High correlation
동수 is highly overall correlated with 세대수High correlation
관리실번호 has 137 (33.2%) missing valuesMissing
공동주택명 has unique valuesUnique

Reproduction

Analysis started2024-01-09 20:53:21.772245
Analysis finished2024-01-09 20:53:22.948307
Duration1.18 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지역
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
천안시
413 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
천안시 413
100.0%

Length

2024-01-10T05:53:22.997933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:53:23.079537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
천안시 413
100.0%

공동주택명
Text

UNIQUE 

Distinct413
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
2024-01-10T05:53:23.240237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length15
Mean length9.464891
Min length3

Characters and Unicode

Total characters3909
Distinct characters308
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

Unique413 ?
Unique (%)100.0%

Sample

1st row한성스위트빌아파트(1차)
2nd row계룡리슈빌아파트
3rd row두정경남아너스빌
4th row두정e편한세상(1차)
5th row두정푸르지오아파트(3차)
ValueCountFrequency (%)
한성스위트빌아파트(1차 1
 
0.2%
목천동우아파트(1차 1
 
0.2%
한화아파트(한화포레나 1
 
0.2%
성지새말2단지아파트 1
 
0.2%
성지새말1단지아파트 1
 
0.2%
천안병천신한아파트 1
 
0.2%
청수현대아파트 1
 
0.2%
병천중앙아파트 1
 
0.2%
임광아파트 1
 
0.2%
안서동보아파트 1
 
0.2%
Other values (404) 404
97.6%
2024-01-10T05:53:23.557268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 343
 
8.8%
파 328
 
8.4%
트 325
 
8.3%
) 119
 
3.0%
( 119
 
3.0%
차 115
 
2.9%
지 84
 
2.1%
성 67
 
1.7%
1 62
 
1.6%
스 60
 
1.5%
Other values (298) 2287
58.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3441
88.0%
Decimal Number 184
 
4.7%
Close Punctuation 119
 
3.0%
Open Punctuation 119
 
3.0%
Uppercase Letter 32
 
0.8%
Lowercase Letter 11
 
0.3%
Other Punctuation 2
 
0.1%
Space Separator 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 343
 
10.0%
파 328
 
9.5%
트 325
 
9.4%
차 115
 
3.3%
지 84
 
2.4%
성 67
 
1.9%
스 60
 
1.7%
이 52
 
1.5%
단 48
 
1.4%
빌 47
 
1.4%
Other values (269) 1972
57.3%
Uppercase Letter
ValueCountFrequency (%)
L 6
18.8%
H 5
15.6%
S 4
12.5%
F 4
12.5%
M 4
12.5%
J 1
 
3.1%
D 1
 
3.1%
B 1
 
3.1%
K 1
 
3.1%
G 1
 
3.1%
Other values (4) 4
12.5%
Decimal Number
ValueCountFrequency (%)
1 62
33.7%
2 60
32.6%
3 22
 
12.0%
5 10
 
5.4%
6 7
 
3.8%
4 7
 
3.8%
7 6
 
3.3%
8 4
 
2.2%
0 3
 
1.6%
9 3
 
1.6%
Close Punctuation
ValueCountFrequency (%)
) 119
100.0%
Open Punctuation
ValueCountFrequency (%)
( 119
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 11
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3441
88.0%
Common 425
 
10.9%
Latin 43
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 343
 
10.0%
파 328
 
9.5%
트 325
 
9.4%
차 115
 
3.3%
지 84
 
2.4%
성 67
 
1.9%
스 60
 
1.7%
이 52
 
1.5%
단 48
 
1.4%
빌 47
 
1.4%
Other values (269) 1972
57.3%
Latin
ValueCountFrequency (%)
e 11
25.6%
L 6
14.0%
H 5
11.6%
S 4
 
9.3%
F 4
 
9.3%
M 4
 
9.3%
J 1
 
2.3%
D 1
 
2.3%
B 1
 
2.3%
K 1
 
2.3%
Other values (5) 5
11.6%
Common
ValueCountFrequency (%)
) 119
28.0%
( 119
28.0%
1 62
14.6%
2 60
14.1%
3 22
 
5.2%
5 10
 
2.4%
6 7
 
1.6%
4 7
 
1.6%
7 6
 
1.4%
8 4
 
0.9%
Other values (4) 9
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3441
88.0%
ASCII 468
 
12.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 343
 
10.0%
파 328
 
9.5%
트 325
 
9.4%
차 115
 
3.3%
지 84
 
2.4%
성 67
 
1.9%
스 60
 
1.7%
이 52
 
1.5%
단 48
 
1.4%
빌 47
 
1.4%
Other values (269) 1972
57.3%
ASCII
ValueCountFrequency (%)
) 119
25.4%
( 119
25.4%
1 62
13.2%
2 60
12.8%
3 22
 
4.7%
e 11
 
2.4%
5 10
 
2.1%
6 7
 
1.5%
4 7
 
1.5%
L 6
 
1.3%
Other values (19) 45
 
9.6%

주소
Text

Distinct408
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
2024-01-10T05:53:23.811248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length30
Mean length25.973366
Min length23

Characters and Unicode

Total characters10727
Distinct characters147
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

Unique403 ?
Unique (%)97.6%

Sample

1st row충청남도 천안시 서북구 부성6길 11(두정동)
2nd row충청남도 천안시 서북구 부성8길 29(두정동)
3rd row충청남도 천안시 서북구 두정중11길 17(두정동)
4th row충청남도 천안시 서북구 두정중2길 12(두정동)
5th row충청남도 천안시 서북구 성정두정로 142(두정동)
ValueCountFrequency (%)
충청남도 413
20.0%
천안시 413
20.0%
서북구 259
 
12.5%
동남구 154
 
7.5%
충절로 13
 
0.6%
충무로 10
 
0.5%
천안대로 9
 
0.4%
성정두정로 8
 
0.4%
일봉로 7
 
0.3%
성거길 7
 
0.3%
Other values (588) 774
37.4%
2024-01-10T05:53:24.242147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1654
 
15.4%
남 569
 
5.3%
동 475
 
4.4%
천 471
 
4.4%
청 452
 
4.2%
안 447
 
4.2%
충 436
 
4.1%
시 422
 
3.9%
구 419
 
3.9%
도 415
 
3.9%
Other values (137) 4967
46.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6810
63.5%
Space Separator 1654
 
15.4%
Decimal Number 1354
 
12.6%
Close Punctuation 413
 
3.9%
Open Punctuation 413
 
3.9%
Dash Punctuation 82
 
0.8%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 569
 
8.4%
동 475
 
7.0%
천 471
 
6.9%
청 452
 
6.6%
안 447
 
6.6%
충 436
 
6.4%
시 422
 
6.2%
구 419
 
6.2%
도 415
 
6.1%
서 296
 
4.3%
Other values (122) 2408
35.4%
Decimal Number
ValueCountFrequency (%)
1 341
25.2%
2 197
14.5%
3 129
 
9.5%
5 121
 
8.9%
4 116
 
8.6%
6 102
 
7.5%
8 98
 
7.2%
0 85
 
6.3%
9 85
 
6.3%
7 80
 
5.9%
Space Separator
ValueCountFrequency (%)
1654
100.0%
Close Punctuation
ValueCountFrequency (%)
) 413
100.0%
Open Punctuation
ValueCountFrequency (%)
( 413
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 82
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6810
63.5%
Common 3917
36.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 569
 
8.4%
동 475
 
7.0%
천 471
 
6.9%
청 452
 
6.6%
안 447
 
6.6%
충 436
 
6.4%
시 422
 
6.2%
구 419
 
6.2%
도 415
 
6.1%
서 296
 
4.3%
Other values (122) 2408
35.4%
Common
ValueCountFrequency (%)
1654
42.2%
) 413
 
10.5%
( 413
 
10.5%
1 341
 
8.7%
2 197
 
5.0%
3 129
 
3.3%
5 121
 
3.1%
4 116
 
3.0%
6 102
 
2.6%
8 98
 
2.5%
Other values (5) 333
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6810
63.5%
ASCII 3917
36.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1654
42.2%
) 413
 
10.5%
( 413
 
10.5%
1 341
 
8.7%
2 197
 
5.0%
3 129
 
3.3%
5 121
 
3.1%
4 116
 
3.0%
6 102
 
2.6%
8 98
 
2.5%
Other values (5) 333
 
8.5%
Hangul
ValueCountFrequency (%)
남 569
 
8.4%
동 475
 
7.0%
천 471
 
6.9%
청 452
 
6.6%
안 447
 
6.6%
충 436
 
6.4%
시 422
 
6.2%
구 419
 
6.2%
도 415
 
6.1%
서 296
 
4.3%
Other values (122) 2408
35.4%

세대수
Real number (ℝ)

HIGH CORRELATION 

Distinct312
Distinct (%)75.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean460.47215
Minimum16
Maximum4168
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.8 KiB
2024-01-10T05:53:24.369139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum16
5-th percentile49
Q1164
median318
Q3612
95-th percentile1154
Maximum4168
Range4152
Interquartile range (IQR)448

Descriptive statistics

Standard deviation432.88784
Coefficient of variation (CV)0.94009559
Kurtosis14.43297
Mean460.47215
Median Absolute Deviation (MAD)203
Skewness2.6566478
Sum190175
Variance187391.89
MonotonicityNot monotonic
2024-01-10T05:53:24.482807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
299 7
 
1.7%
40 5
 
1.2%
297 5
 
1.2%
200 4
 
1.0%
99 4
 
1.0%
49 4
 
1.0%
60 4
 
1.0%
168 4
 
1.0%
76 3
 
0.7%
96 3
 
0.7%
Other values (302) 370
89.6%
ValueCountFrequency (%)
16 1
 
0.2%
18 1
 
0.2%
25 2
 
0.5%
26 1
 
0.2%
28 1
 
0.2%
30 1
 
0.2%
39 1
 
0.2%
40 5
1.2%
42 2
 
0.5%
44 1
 
0.2%
ValueCountFrequency (%)
4168 1
0.2%
2586 1
0.2%
2144 1
0.2%
1922 1
0.2%
1833 1
0.2%
1730 1
0.2%
1647 1
0.2%
1646 1
0.2%
1562 1
0.2%
1534 1
0.2%

층수
Real number (ℝ)

HIGH CORRELATION 

Distinct37
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.271186
Minimum2
Maximum66
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.8 KiB
2024-01-10T05:53:24.592908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile5
Q111
median15
Q318
95-th percentile28.4
Maximum66
Range64
Interquartile range (IQR)7

Descriptive statistics

Standard deviation7.8049068
Coefficient of variation (CV)0.51108713
Kurtosis5.2832748
Mean15.271186
Median Absolute Deviation (MAD)4
Skewness1.432723
Sum6307
Variance60.916571
MonotonicityNot monotonic
2024-01-10T05:53:24.704298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
15 120
29.1%
5 41
 
9.9%
12 32
 
7.7%
20 21
 
5.1%
6 20
 
4.8%
10 17
 
4.1%
14 17
 
4.1%
18 17
 
4.1%
25 15
 
3.6%
23 10
 
2.4%
Other values (27) 103
24.9%
ValueCountFrequency (%)
2 1
 
0.2%
3 2
 
0.5%
4 6
 
1.5%
5 41
9.9%
6 20
4.8%
7 3
 
0.7%
8 7
 
1.7%
9 3
 
0.7%
10 17
4.1%
11 8
 
1.9%
ValueCountFrequency (%)
66 1
 
0.2%
48 1
 
0.2%
46 1
 
0.2%
44 1
 
0.2%
39 3
 
0.7%
37 1
 
0.2%
33 1
 
0.2%
32 1
 
0.2%
31 2
 
0.5%
29 9
2.2%

동수
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.5181598
Minimum1
Maximum25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.8 KiB
2024-01-10T05:53:24.812167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median4
Q38
95-th percentile15
Maximum25
Range24
Interquartile range (IQR)7

Descriptive statistics

Standard deviation4.77176
Coefficient of variation (CV)0.86473756
Kurtosis1.3410017
Mean5.5181598
Median Absolute Deviation (MAD)3
Skewness1.2520032
Sum2279
Variance22.769694
MonotonicityNot monotonic
2024-01-10T05:53:24.914346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
1 108
26.2%
4 44
10.7%
2 43
 
10.4%
6 32
 
7.7%
8 31
 
7.5%
3 27
 
6.5%
5 21
 
5.1%
9 19
 
4.6%
7 17
 
4.1%
11 14
 
3.4%
Other values (12) 57
13.8%
ValueCountFrequency (%)
1 108
26.2%
2 43
 
10.4%
3 27
 
6.5%
4 44
10.7%
5 21
 
5.1%
6 32
 
7.7%
7 17
 
4.1%
8 31
 
7.5%
9 19
 
4.6%
10 7
 
1.7%
ValueCountFrequency (%)
25 2
 
0.5%
21 1
 
0.2%
20 2
 
0.5%
19 2
 
0.5%
18 3
 
0.7%
17 5
1.2%
16 5
1.2%
15 6
1.5%
14 6
1.5%
13 11
2.7%

준공연도
Date

Distinct368
Distinct (%)89.1%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
Minimum1979-01-12 00:00:00
Maximum2022-04-19 00:00:00
2024-01-10T05:53:25.016076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:53:25.136705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

관리실번호
Text

MISSING 

Distinct272
Distinct (%)98.6%
Missing137
Missing (%)33.2%
Memory size3.4 KiB
2024-01-10T05:53:25.343492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters3312
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

Unique268 ?
Unique (%)97.1%

Sample

1st row041-554-1133
2nd row041-557-1472
3rd row041-556-3307
4th row041-561-8040
5th row041-554-9116
ValueCountFrequency (%)
041-553-3844 2
 
0.7%
041-522-0026 2
 
0.7%
041-567-8824 2
 
0.7%
041-563-7111 2
 
0.7%
041-561-2416 1
 
0.4%
041-576-9911 1
 
0.4%
041-554-1133 1
 
0.4%
041-575-2721 1
 
0.4%
041-571-6988 1
 
0.4%
041-555-2690 1
 
0.4%
Other values (262) 262
94.9%
2024-01-10T05:53:25.653359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 552
16.7%
5 439
13.3%
1 429
13.0%
4 423
12.8%
0 410
12.4%
7 233
7.0%
2 226
6.8%
6 188
 
5.7%
3 152
 
4.6%
8 150
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2760
83.3%
Dash Punctuation 552
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 439
15.9%
1 429
15.5%
4 423
15.3%
0 410
14.9%
7 233
8.4%
2 226
8.2%
6 188
6.8%
3 152
 
5.5%
8 150
 
5.4%
9 110
 
4.0%
Dash Punctuation
ValueCountFrequency (%)
- 552
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3312
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 552
16.7%
5 439
13.3%
1 429
13.0%
4 423
12.8%
0 410
12.4%
7 233
7.0%
2 226
6.8%
6 188
 
5.7%
3 152
 
4.6%
8 150
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3312
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 552
16.7%
5 439
13.3%
1 429
13.0%
4 423
12.8%
0 410
12.4%
7 233
7.0%
2 226
6.8%
6 188
 
5.7%
3 152
 
4.6%
8 150
 
4.5%

Interactions

2024-01-10T05:53:22.497709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:53:22.093471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:53:22.292581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:53:22.578814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:53:22.155294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:53:22.359508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:53:22.682216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:53:22.225790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:53:22.430500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T05:53:25.737900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세대수층수동수
세대수1.0000.4620.706
층수0.4621.0000.368
동수0.7060.3681.000
2024-01-10T05:53:25.810885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세대수층수동수
세대수1.0000.5960.848
층수0.5961.0000.408
동수0.8480.4081.000

Missing values

2024-01-10T05:53:22.794799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T05:53:22.904766image/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

지역공동주택명주소세대수층수동수준공연도관리실번호
0천안시한성스위트빌아파트(1차)충청남도 천안시 서북구 부성6길 11(두정동)6001562002-08-26041-554-1133
1천안시계룡리슈빌아파트충청남도 천안시 서북구 부성8길 29(두정동)3861542004-03-18041-557-1472
2천안시두정경남아너스빌충청남도 천안시 서북구 두정중11길 17(두정동)4581562004-06-10041-556-3307
3천안시두정e편한세상(1차)충청남도 천안시 서북구 두정중2길 12(두정동)4661592004-06-25041-561-8040
4천안시두정푸르지오아파트(3차)충청남도 천안시 서북구 성정두정로 142(두정동)3261542003-09-09041-554-9116
5천안시우남두정마을아파트(1차)충청남도 천안시 서북구 두정역서5길 11(두정동)3251542003-08-21041-567-8824
6천안시우남두정마을아파트(2차)충청남도 천안시 서북구 두정역서1길 22(두정동)1941522003-08-21041-567-8824
7천안시한성필하우스아파트(2차)충청남도 천안시 서북구 두정고8길 24(두정동)991512004-06-19<NA>
8천안시대주파크빌(1단지)충청남도 천안시 서북구 두정고7길 9(두정동)1401512005-10-28<NA>
9천안시대주파크빌(2단지)충청남도 천안시 서북구 두정고7길 10(두정동)491312005-11-02<NA>
지역공동주택명주소세대수층수동수준공연도관리실번호
403천안시천안신방LH1단지충청남도 천안시 동남구 통정11로 80(신방동)4501542018-10-25041-592-6677
404천안시천안불당LH1단지아파트충청남도 천안시 서북구 불당24로 9(불당동)11482582019-06-30041-622-9771
405천안시목천고운라피네아파트충청남도 천안시 동남구 성남로 35(목천읍)2522042020-12-28041-552-5220
406천안시직산월드메르디앙레이크파크아파트충청남도 천안시 서북구 직산로 59(직산읍)3742072020-10-07041-585-3740
407천안시힐스테이트천안아파트충청남도 천안시 동남구 옛시청길 29(문화동)4514432021-03-16041-523-0451
408천안시천안역사동아라이크텐아파트충청남도 천안시 서북구 천안천4길 20(와촌동)9924842021-04-30041-579-9801
409천안시브리엔츠아파트충청남도 천안시 서북구 삼은2길 26(직산읍)991612019-09-04<NA>
410천안시두정한화포레나충청남도 천안시 서북구 천안대로 980-17(두정동)106729132022-03-30041-552-9300
411천안시천안필하우스에듀시티1단지충청남도 천안시 동남구 성황로 40(문화동)153228132022-04-19041-622-8574
412천안시천안필하우스에듀시티2단지충청남도 천안시 동남구 성황로 66(문화동)2521732022-04-19041-552-6661