Overview

Dataset statistics

Number of variables10
Number of observations23
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.0 KiB
Average record size in memory88.7 B

Variable types

Numeric3
Text3
Categorical1
DateTime3

Dataset

Description계룡시 관내 공동주택 현황에 관한 데이터로서, 위치, 명칭, 동수, 세대수, 층수, 허가일, 착공일, 준공일에 대한 공공데이터를 제공합니다.
URLhttps://www.data.go.kr/data/15093883/fileData.do

Alerts

분류 has constant value ""Constant
동수 is highly overall correlated with 세대수High correlation
세대수 is highly overall correlated with 동수High correlation
연번 has unique valuesUnique
명칭 has unique valuesUnique
위치 has unique valuesUnique
착공일 has unique valuesUnique

Reproduction

Analysis started2023-12-12 21:19:35.641728
Analysis finished2023-12-12 21:19:37.089831
Duration1.45 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12
Minimum1
Maximum23
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-13T06:19:37.161377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.1
Q16.5
median12
Q317.5
95-th percentile21.9
Maximum23
Range22
Interquartile range (IQR)11

Descriptive statistics

Standard deviation6.78233
Coefficient of variation (CV)0.56519417
Kurtosis-1.2
Mean12
Median Absolute Deviation (MAD)6
Skewness0
Sum276
Variance46
MonotonicityStrictly increasing
2023-12-13T06:19:37.274361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
1 1
 
4.3%
2 1
 
4.3%
23 1
 
4.3%
22 1
 
4.3%
21 1
 
4.3%
20 1
 
4.3%
19 1
 
4.3%
18 1
 
4.3%
17 1
 
4.3%
16 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
1 1
4.3%
2 1
4.3%
3 1
4.3%
4 1
4.3%
5 1
4.3%
6 1
4.3%
7 1
4.3%
8 1
4.3%
9 1
4.3%
10 1
4.3%
ValueCountFrequency (%)
23 1
4.3%
22 1
4.3%
21 1
4.3%
20 1
4.3%
19 1
4.3%
18 1
4.3%
17 1
4.3%
16 1
4.3%
15 1
4.3%
14 1
4.3%

명칭
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-13T06:19:37.486532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length10
Mean length6.3478261
Min length3

Characters and Unicode

Total characters146
Distinct characters79
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)100.0%

Sample

1st row동 아
2nd row두산신성
3rd row비사벌
4th row경남무궁화
5th row성 원
ValueCountFrequency (%)
미소지움 2
 
6.1%
동 1
 
3.0%
계룡더샾 1
 
3.0%
계룡대실한라비발디더센트럴 1
 
3.0%
계룡푸르지오더퍼스트 1
 
3.0%
계룡대실lh리슈빌 1
 
3.0%
4단지 1
 
3.0%
lh 1
 
3.0%
계룡대실 1
 
3.0%
이지 1
 
3.0%
Other values (22) 22
66.7%
2023-12-13T06:19:37.845324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11
 
7.5%
계 8
 
5.5%
룡 8
 
5.5%
지 5
 
3.4%
대 5
 
3.4%
스 5
 
3.4%
성 4
 
2.7%
더 4
 
2.7%
아 4
 
2.7%
미 3
 
2.1%
Other values (69) 89
61.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 127
87.0%
Space Separator 11
 
7.5%
Lowercase Letter 3
 
2.1%
Decimal Number 3
 
2.1%
Uppercase Letter 2
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
계 8
 
6.3%
룡 8
 
6.3%
지 5
 
3.9%
대 5
 
3.9%
스 5
 
3.9%
성 4
 
3.1%
더 4
 
3.1%
아 4
 
3.1%
미 3
 
2.4%
신 3
 
2.4%
Other values (60) 78
61.4%
Lowercase Letter
ValueCountFrequency (%)
h 1
33.3%
l 1
33.3%
e 1
33.3%
Decimal Number
ValueCountFrequency (%)
4 1
33.3%
1 1
33.3%
2 1
33.3%
Uppercase Letter
ValueCountFrequency (%)
H 1
50.0%
L 1
50.0%
Space Separator
ValueCountFrequency (%)
11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 127
87.0%
Common 14
 
9.6%
Latin 5
 
3.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
계 8
 
6.3%
룡 8
 
6.3%
지 5
 
3.9%
대 5
 
3.9%
스 5
 
3.9%
성 4
 
3.1%
더 4
 
3.1%
아 4
 
3.1%
미 3
 
2.4%
신 3
 
2.4%
Other values (60) 78
61.4%
Latin
ValueCountFrequency (%)
h 1
20.0%
l 1
20.0%
H 1
20.0%
L 1
20.0%
e 1
20.0%
Common
ValueCountFrequency (%)
11
78.6%
4 1
 
7.1%
1 1
 
7.1%
2 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 127
87.0%
ASCII 19
 
13.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11
57.9%
h 1
 
5.3%
l 1
 
5.3%
4 1
 
5.3%
H 1
 
5.3%
L 1
 
5.3%
e 1
 
5.3%
1 1
 
5.3%
2 1
 
5.3%
Hangul
ValueCountFrequency (%)
계 8
 
6.3%
룡 8
 
6.3%
지 5
 
3.9%
대 5
 
3.9%
스 5
 
3.9%
성 4
 
3.1%
더 4
 
3.1%
아 4
 
3.1%
미 3
 
2.4%
신 3
 
2.4%
Other values (60) 78
61.4%

위치
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-13T06:19:38.054998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length17.391304
Min length15

Characters and Unicode

Total characters400
Distinct characters42
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

Unique23 ?
Unique (%)100.0%

Sample

1st row충청남도 계룡시 엄사중앙로 65-10
2nd row충청남도 계룡시 엄사중앙로 65-9
3rd row충청남도 계룡시 번영3길 43
4th row충청남도 계룡시 번영로 43
5th row충청남도 계룡시 엄사중앙로 66
ValueCountFrequency (%)
충청남도 23
24.0%
계룡시 23
24.0%
농소리 4
 
4.2%
두마면 4
 
4.2%
엄사중앙로 3
 
3.1%
번영3길 3
 
3.1%
9 2
 
2.1%
43 2
 
2.1%
번영로 2
 
2.1%
사계로 2
 
2.1%
Other values (28) 28
29.2%
2023-12-13T06:19:38.394661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
73
18.2%
계 27
 
6.8%
남 24
 
6.0%
룡 24
 
6.0%
충 23
 
5.8%
도 23
 
5.8%
시 23
 
5.8%
청 23
 
5.8%
로 12
 
3.0%
1 12
 
3.0%
Other values (32) 136
34.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 255
63.7%
Space Separator 73
 
18.2%
Decimal Number 67
 
16.8%
Dash Punctuation 5
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
계 27
10.6%
남 24
 
9.4%
룡 24
 
9.4%
충 23
 
9.0%
도 23
 
9.0%
시 23
 
9.0%
청 23
 
9.0%
로 12
 
4.7%
길 7
 
2.7%
번 5
 
2.0%
Other values (20) 64
25.1%
Decimal Number
ValueCountFrequency (%)
1 12
17.9%
3 12
17.9%
9 9
13.4%
5 7
10.4%
7 6
9.0%
6 6
9.0%
0 5
7.5%
2 5
7.5%
4 4
 
6.0%
8 1
 
1.5%
Space Separator
ValueCountFrequency (%)
73
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 255
63.7%
Common 145
36.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
계 27
10.6%
남 24
 
9.4%
룡 24
 
9.4%
충 23
 
9.0%
도 23
 
9.0%
시 23
 
9.0%
청 23
 
9.0%
로 12
 
4.7%
길 7
 
2.7%
번 5
 
2.0%
Other values (20) 64
25.1%
Common
ValueCountFrequency (%)
73
50.3%
1 12
 
8.3%
3 12
 
8.3%
9 9
 
6.2%
5 7
 
4.8%
7 6
 
4.1%
6 6
 
4.1%
- 5
 
3.4%
0 5
 
3.4%
2 5
 
3.4%
Other values (2) 5
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 255
63.7%
ASCII 145
36.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
73
50.3%
1 12
 
8.3%
3 12
 
8.3%
9 9
 
6.2%
5 7
 
4.8%
7 6
 
4.1%
6 6
 
4.1%
- 5
 
3.4%
0 5
 
3.4%
2 5
 
3.4%
Other values (2) 5
 
3.4%
Hangul
ValueCountFrequency (%)
계 27
10.6%
남 24
 
9.4%
룡 24
 
9.4%
충 23
 
9.0%
도 23
 
9.0%
시 23
 
9.0%
청 23
 
9.0%
로 12
 
4.7%
길 7
 
2.7%
번 5
 
2.0%
Other values (20) 64
25.1%

분류
Categorical

CONSTANT 

Distinct1
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
공동주택
23 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공동주택 23
100.0%

Length

2023-12-13T06:19:38.527956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:19:38.653444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동주택 23
100.0%

동수
Real number (ℝ)

HIGH CORRELATION 

Distinct14
Distinct (%)60.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.1304348
Minimum1
Maximum18
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-13T06:19:38.751507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.3
Q15.5
median10
Q312.5
95-th percentile16.8
Maximum18
Range17
Interquartile range (IQR)7

Descriptive statistics

Standard deviation4.8364558
Coefficient of variation (CV)0.52970706
Kurtosis-0.83298286
Mean9.1304348
Median Absolute Deviation (MAD)4
Skewness0.047340966
Sum210
Variance23.391304
MonotonicityNot monotonic
2023-12-13T06:19:38.863252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
4 3
13.0%
10 3
13.0%
6 2
8.7%
14 2
8.7%
1 2
8.7%
8 2
8.7%
12 2
8.7%
5 1
 
4.3%
17 1
 
4.3%
13 1
 
4.3%
Other values (4) 4
17.4%
ValueCountFrequency (%)
1 2
8.7%
4 3
13.0%
5 1
 
4.3%
6 2
8.7%
7 1
 
4.3%
8 2
8.7%
10 3
13.0%
11 1
 
4.3%
12 2
8.7%
13 1
 
4.3%
ValueCountFrequency (%)
18 1
 
4.3%
17 1
 
4.3%
15 1
 
4.3%
14 2
8.7%
13 1
 
4.3%
12 2
8.7%
11 1
 
4.3%
10 3
13.0%
8 2
8.7%
7 1
 
4.3%

세대수
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean658.95652
Minimum60
Maximum1850
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-13T06:19:38.974592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum60
5-th percentile150.5
Q1349
median608
Q3894
95-th percentile993.3
Maximum1850
Range1790
Interquartile range (IQR)545

Descriptive statistics

Standard deviation391.40742
Coefficient of variation (CV)0.59398065
Kurtosis2.5581314
Mean658.95652
Median Absolute Deviation (MAD)297
Skewness1.0140885
Sum15156
Variance153199.77
MonotonicityNot monotonic
2023-12-13T06:19:39.381040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
600 2
 
8.7%
394 1
 
4.3%
987 1
 
4.3%
905 1
 
4.3%
883 1
 
4.3%
842 1
 
4.3%
144 1
 
4.3%
938 1
 
4.3%
209 1
 
4.3%
304 1
 
4.3%
Other values (12) 12
52.2%
ValueCountFrequency (%)
60 1
4.3%
144 1
4.3%
209 1
4.3%
272 1
4.3%
274 1
4.3%
304 1
4.3%
394 1
4.3%
510 1
4.3%
532 1
4.3%
600 2
8.7%
ValueCountFrequency (%)
1850 1
4.3%
994 1
4.3%
987 1
4.3%
938 1
4.3%
918 1
4.3%
905 1
4.3%
883 1
4.3%
868 1
4.3%
842 1
4.3%
832 1
4.3%

층수
Text

Distinct17
Distinct (%)73.9%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-13T06:19:39.551589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.2173913
Min length1

Characters and Unicode

Total characters97
Distinct characters11
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

Unique12 ?
Unique (%)52.2%

Sample

1st row13~15
2nd row15
3rd row15
4th row13~14
5th row13~15
ValueCountFrequency (%)
13~15 3
13.0%
12~15 2
 
8.7%
15 2
 
8.7%
2~25 2
 
8.7%
15~20 2
 
8.7%
10~18 1
 
4.3%
7 1
 
4.3%
12~25 1
 
4.3%
16~20 1
 
4.3%
18~23 1
 
4.3%
Other values (7) 7
30.4%
2023-12-13T06:19:39.841635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 27
27.8%
~ 18
18.6%
5 14
14.4%
2 14
14.4%
3 6
 
6.2%
0 6
 
6.2%
- 3
 
3.1%
4 3
 
3.1%
8 3
 
3.1%
6 2
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 76
78.4%
Math Symbol 18
 
18.6%
Dash Punctuation 3
 
3.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 27
35.5%
5 14
18.4%
2 14
18.4%
3 6
 
7.9%
0 6
 
7.9%
4 3
 
3.9%
8 3
 
3.9%
6 2
 
2.6%
7 1
 
1.3%
Math Symbol
ValueCountFrequency (%)
~ 18
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 97
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 27
27.8%
~ 18
18.6%
5 14
14.4%
2 14
14.4%
3 6
 
6.2%
0 6
 
6.2%
- 3
 
3.1%
4 3
 
3.1%
8 3
 
3.1%
6 2
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 97
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 27
27.8%
~ 18
18.6%
5 14
14.4%
2 14
14.4%
3 6
 
6.2%
0 6
 
6.2%
- 3
 
3.1%
4 3
 
3.1%
8 3
 
3.1%
6 2
 
2.1%

허가일
Date

Distinct22
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
Minimum1992-06-19 00:00:00
Maximum2019-02-28 00:00:00
2023-12-13T06:19:39.952277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:19:40.046570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)

착공일
Date

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
Minimum1992-08-28 00:00:00
Maximum2021-02-15 00:00:00
2023-12-13T06:19:40.144094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:19:40.252740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)

준공일
Date

Distinct22
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
Minimum1994-09-16 00:00:00
Maximum2023-07-24 00:00:00
2023-12-13T06:19:40.369080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:19:40.476092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)

Interactions

2023-12-13T06:19:36.534721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:19:36.014464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:19:36.263726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:19:36.607464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:19:36.099503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:19:36.350404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:19:36.702168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:19:36.183727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:19:36.436070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:19:40.567064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번명칭위치동수세대수층수허가일착공일준공일
연번1.0001.0001.0000.0000.3440.8571.0001.0000.891
명칭1.0001.0001.0001.0001.0001.0001.0001.0001.000
위치1.0001.0001.0001.0001.0001.0001.0001.0001.000
동수0.0001.0001.0001.0000.5550.7800.7981.0001.000
세대수0.3441.0001.0000.5551.0000.7710.9481.0001.000
층수0.8571.0001.0000.7800.7711.0000.9501.0000.975
허가일1.0001.0001.0000.7980.9480.9501.0001.0000.985
착공일1.0001.0001.0001.0001.0001.0001.0001.0001.000
준공일0.8911.0001.0001.0001.0000.9750.9851.0001.000
2023-12-13T06:19:40.668268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번동수세대수
연번1.0000.1730.067
동수0.1731.0000.687
세대수0.0670.6871.000

Missing values

2023-12-13T06:19:36.833277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:19:37.015677image/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

연번명칭위치분류동수세대수층수허가일착공일준공일
01동 아충청남도 계룡시 엄사중앙로 65-10공동주택439413~151992-06-191992-08-281994-09-23
12두산신성충청남도 계룡시 엄사중앙로 65-9공동주택6532151992-06-241992-09-011994-09-16
23비사벌충청남도 계룡시 번영3길 43공동주택4510151993-12-301994-02-011995-12-01
34경남무궁화충청남도 계룡시 번영로 43공동주택427213~141994-07-021994-07-011996-10-30
45성 원충청남도 계룡시 엄사중앙로 66공동주택14185013~151995-02-141995-03-241997-11-21
56삼 진충청남도 계룡시 번영3길 73-12공동주택599410~151996-01-261996-02-261997-10-16
67대동황토방충청남도 계룡시 번영3길 91공동주택1763213~151997-11-291997-12-192001-04-19
78금암주공충청남도 계룡시 서금암4길 6-9공동주택627410~141999-10-292000-05-312002-07-13
89신성1차 미소지움충청남도 계룡시 장안1길 9공동주택1383215~202002-11-272002-12-092005-06-16
910우림루미아트충청남도 계룡시 장안로 75공동주택1486812~152003-06-052003-06-242005-06-16
연번명칭위치분류동수세대수층수허가일착공일준공일
1314더 플러스충청남도 계룡시 계룡대로 363공동주택16052011-02-152011-03-092011-11-18
1415블루힐스충청남도 계룡시 계백로 3051공동주택830412~152011-06-242011-07-292012-08-29
1516한양아이클래스충청남도 계룡시 서금암로 10공동주택120972011-03-282011-04-072015-12-30
1617계룡파라디아충청남도 계룡시 번영로 113-32공동주택1293818~232007-05-312013-12-172016-12-14
1718타운하우스 이지충청남도 계룡시 서금암 5길 24공동주택1014442015-02-152015-08-202017-10-13
1819계룡대실 LH 4단지충청남도 계룡시 대실남북로82공동주택884216~202013-12-262018-03-272020-10-20
1920계룡대실lh리슈빌충청남도 계룡시 두마면 농소리 972공동주택1060012~252018-12-312019-05-072021-11-17
2021계룡푸르지오더퍼스트충청남도 계룡시 두마면 농소리 973공동주택10883-2~252019-02-282020-03-122022-08-12
2122계룡대실한라비발디더센트럴충청남도 계룡시 두마면 농소리 971공동주택12905-2~252018-07-032020-06-222023-02-16
2223계룡자이충청남도 계룡시 두마면 농소리 970공동주택7600-3~262019-02-282021-02-152023-07-24