Overview

Dataset statistics

Number of variables11
Number of observations26
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.5 KiB
Average record size in memory99.1 B

Variable types

Categorical6
Numeric4
DateTime1

Dataset

Description경상북도 김천시 공동주택 분양 현황에 대한 자료로 2020년부터 2021년까지의 공동주택 분양현황, 분양 가격 등의 정보를 제공합니다.
Author경상북도 김천시
URLhttps://www.data.go.kr/data/15107684/fileData.do

Alerts

아파트명 has constant value ""Constant
데이터 기준일자 has constant value ""Constant
층구분 is highly overall correlated with 부가세(단위_원)High correlation
공급세대수 is highly overall correlated with 대지비(단위_원) and 5 other fieldsHigh correlation
동호별 is highly overall correlated with 약식표기 and 2 other fieldsHigh correlation
부가세(단위_원) is highly overall correlated with 해당 세대수 and 7 other fieldsHigh correlation
약식표기 is highly overall correlated with 대지비(단위_원) and 5 other fieldsHigh correlation
해당 세대수 is highly overall correlated with 부가세(단위_원)High correlation
대지비(단위_원) is highly overall correlated with 건축비(단위_원) and 4 other fieldsHigh correlation
건축비(단위_원) is highly overall correlated with 대지비(단위_원) and 4 other fieldsHigh correlation
분양가격(계)(단위_원) is highly overall correlated with 대지비(단위_원) and 4 other fieldsHigh correlation
부가세(단위_원) is highly imbalanced (55.4%)Imbalance
대지비(단위_원) has unique valuesUnique
건축비(단위_원) has unique valuesUnique
분양가격(계)(단위_원) has unique valuesUnique

Reproduction

Analysis started2023-12-12 08:07:43.139984
Analysis finished2023-12-12 08:07:46.050549
Duration2.91 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아파트명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size340.0 B
김천 푸르지오 더 퍼스트
26 

Length

Max length13
Median length13
Mean length13
Min length13

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row김천 푸르지오 더 퍼스트
2nd row김천 푸르지오 더 퍼스트
3rd row김천 푸르지오 더 퍼스트
4th row김천 푸르지오 더 퍼스트
5th row김천 푸르지오 더 퍼스트

Common Values

ValueCountFrequency (%)
김천 푸르지오 더 퍼스트 26
100.0%

Length

2023-12-12T17:07:46.134540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:07:46.246025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
김천 26
25.0%
푸르지오 26
25.0%
더 26
25.0%
퍼스트 26
25.0%

약식표기
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)15.4%
Missing0
Missing (%)0.0%
Memory size340.0 B
74
7 
84A
7 
84B
7 
99
5 

Length

Max length3
Median length3
Mean length2.5384615
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row74
2nd row74
3rd row74
4th row74
5th row74

Common Values

ValueCountFrequency (%)
74 7
26.9%
84A 7
26.9%
84B 7
26.9%
99 5
19.2%

Length

2023-12-12T17:07:46.348250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:07:46.453110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
74 7
26.9%
84a 7
26.9%
84b 7
26.9%
99 5
19.2%

공급세대수
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)15.4%
Missing0
Missing (%)0.0%
Memory size340.0 B
145
7 
310
7 
152
7 
96
5 

Length

Max length3
Median length3
Mean length2.8076923
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row145
2nd row145
3rd row145
4th row145
5th row145

Common Values

ValueCountFrequency (%)
145 7
26.9%
310 7
26.9%
152 7
26.9%
96 5
19.2%

Length

2023-12-12T17:07:46.600430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:07:46.740033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
145 7
26.9%
310 7
26.9%
152 7
26.9%
96 5
19.2%

동호별
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)46.2%
Missing0
Missing (%)0.0%
Memory size340.0 B
101동 1+2호 라인
7 
103동 1+2호 라인
5 
104동 1+3+4호 라인
3 
108동 4호 라인
2 
108동 3호 라인
2 
Other values (7)
7 

Length

Max length14
Median length12
Mean length11.384615
Min length10

Unique

Unique7 ?
Unique (%)26.9%

Sample

1st row101동 1+2호 라인
2nd row101동 1+2호 라인
3rd row101동 1+2호 라인
4th row101동 1+2호 라인
5th row101동 1+2호 라인

Common Values

ValueCountFrequency (%)
101동 1+2호 라인 7
26.9%
103동 1+2호 라인 5
19.2%
104동 1+3+4호 라인 3
11.5%
108동 4호 라인 2
 
7.7%
108동 3호 라인 2
 
7.7%
101동 4호 라인 1
 
3.8%
102동 4호 라인 1
 
3.8%
101동 3호 라인 1
 
3.8%
102동 3호 라인 1
 
3.8%
104동 2호 라인 1
 
3.8%
Other values (2) 2
 
7.7%

Length

2023-12-12T17:07:46.914431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
라인 26
33.3%
1+2호 12
15.4%
101동 9
 
11.5%
103동 5
 
6.4%
104동 4
 
5.1%
108동 4
 
5.1%
4호 4
 
5.1%
3호 4
 
5.1%
1+3+4호 3
 
3.8%
2호 3
 
3.8%
Other values (3) 4
 
5.1%

층구분
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)26.9%
Missing0
Missing (%)0.0%
Memory size340.0 B
2층(P)
4 
3+5층
4 
6+10층
4 
11+20층
4 
21+28층
4 
Other values (2)
6 

Length

Max length6
Median length5
Mean length4.4615385
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1층
2nd row2층
3rd row2층(P)
4th row3+5층
5th row6+10층

Common Values

ValueCountFrequency (%)
2층(P) 4
15.4%
3+5층 4
15.4%
6+10층 4
15.4%
11+20층 4
15.4%
21+28층 4
15.4%
1층 3
11.5%
2층 3
11.5%

Length

2023-12-12T17:07:47.126911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:07:47.304365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2층(p 4
15.4%
3+5층 4
15.4%
6+10층 4
15.4%
11+20층 4
15.4%
21+28층 4
15.4%
1층 3
11.5%
2층 3
11.5%

해당 세대수
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)69.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27.038462
Minimum1
Maximum120
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-12T17:07:47.485469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q14.25
median19
Q338.25
95-th percentile74.25
Maximum120
Range119
Interquartile range (IQR)34

Descriptive statistics

Standard deviation28.814553
Coefficient of variation (CV)1.0656876
Kurtosis3.1204096
Mean27.038462
Median Absolute Deviation (MAD)15.5
Skewness1.6531512
Sum703
Variance830.27846
MonotonicityNot monotonic
2023-12-12T17:07:47.632999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
5 2
 
7.7%
4 2
 
7.7%
18 2
 
7.7%
30 2
 
7.7%
60 2
 
7.7%
3 2
 
7.7%
20 2
 
7.7%
2 2
 
7.7%
40 1
 
3.8%
12 1
 
3.8%
Other values (8) 8
30.8%
ValueCountFrequency (%)
1 1
3.8%
2 2
7.7%
3 2
7.7%
4 2
7.7%
5 2
7.7%
9 1
3.8%
12 1
3.8%
18 2
7.7%
20 2
7.7%
26 1
3.8%
ValueCountFrequency (%)
120 1
3.8%
79 1
3.8%
60 2
7.7%
57 1
3.8%
40 1
3.8%
39 1
3.8%
36 1
3.8%
30 2
7.7%
26 1
3.8%
20 2
7.7%

대지비(단위_원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean90220423
Minimum73560000
Maximum1.12745 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-12T17:07:47.777845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum73560000
5-th percentile75502500
Q182750000
median88750000
Q394390000
95-th percentile1.1003825 × 108
Maximum1.12745 × 108
Range39185000
Interquartile range (IQR)11640000

Descriptive statistics

Standard deviation11003266
Coefficient of variation (CV)0.12195981
Kurtosis-0.38583983
Mean90220423
Median Absolute Deviation (MAD)6040000
Skewness0.60016545
Sum2.345731 × 109
Variance1.2107186 × 1014
MonotonicityNot monotonic
2023-12-12T17:07:47.962454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
73560000 1
 
3.8%
85890000 1
 
3.8%
112745000 1
 
3.8%
110575000 1
 
3.8%
108428000 1
 
3.8%
106269000 1
 
3.8%
105184000 1
 
3.8%
96620000 1
 
3.8%
94790000 1
 
3.8%
92940000 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
73560000 1
3.8%
74930000 1
3.8%
77220000 1
3.8%
78000000 1
3.8%
79580000 1
3.8%
81160000 1
3.8%
82710000 1
3.8%
82870000 1
3.8%
84400000 1
3.8%
85890000 1
3.8%
ValueCountFrequency (%)
112745000 1
3.8%
110575000 1
3.8%
108428000 1
3.8%
106269000 1
3.8%
105184000 1
3.8%
96620000 1
3.8%
94790000 1
3.8%
93190000 1
3.8%
92940000 1
3.8%
91410000 1
3.8%

건축비(단위_원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0410615 × 108
Minimum2.4794 × 108
Maximum3.8005 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-12T17:07:48.129702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.4794 × 108
5-th percentile2.544975 × 108
Q12.78925 × 108
median2.9915 × 108
Q33.1816 × 108
95-th percentile3.709425 × 108
Maximum3.8005 × 108
Range1.3211 × 108
Interquartile range (IQR)39235000

Descriptive statistics

Standard deviation37099575
Coefficient of variation (CV)0.12199547
Kurtosis-0.38534504
Mean3.0410615 × 108
Median Absolute Deviation (MAD)20360000
Skewness0.60065879
Sum7.90676 × 109
Variance1.3763784 × 1015
MonotonicityNot monotonic
2023-12-12T17:07:48.283931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
247940000 1
 
3.8%
289510000 1
 
3.8%
380050000 1
 
3.8%
372750000 1
 
3.8%
365520000 1
 
3.8%
358210000 1
 
3.8%
354560000 1
 
3.8%
325680000 1
 
3.8%
319510000 1
 
3.8%
313260000 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
247940000 1
3.8%
252570000 1
3.8%
260280000 1
3.8%
262900000 1
3.8%
268220000 1
3.8%
273540000 1
3.8%
278790000 1
3.8%
279330000 1
3.8%
284500000 1
3.8%
289510000 1
3.8%
ValueCountFrequency (%)
380050000 1
3.8%
372750000 1
3.8%
365520000 1
3.8%
358210000 1
3.8%
354560000 1
3.8%
325680000 1
3.8%
319510000 1
3.8%
314110000 1
3.8%
313260000 1
3.8%
308090000 1
3.8%

부가세(단위_원)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)23.1%
Missing0
Missing (%)0.0%
Memory size340.0 B
<NA>
21 
35456000
 
1
35821000
 
1
36552000
 
1
37275000
 
1

Length

Max length8
Median length4
Mean length4.7692308
Min length4

Unique

Unique5 ?
Unique (%)19.2%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 21
80.8%
35456000 1
 
3.8%
35821000 1
 
3.8%
36552000 1
 
3.8%
37275000 1
 
3.8%
38005000 1
 
3.8%

Length

2023-12-12T17:07:48.430611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:07:48.584656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 21
80.8%
35456000 1
 
3.8%
35821000 1
 
3.8%
36552000 1
 
3.8%
37275000 1
 
3.8%
38005000 1
 
3.8%

분양가격(계)(단위_원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.0136923 × 108
Minimum3.215 × 108
Maximum5.308 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-12T17:07:48.725352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.215 × 108
5-th percentile3.3 × 108
Q13.61675 × 108
median3.879 × 108
Q34.1255 × 108
95-th percentile5.18075 × 108
Maximum5.308 × 108
Range2.093 × 108
Interquartile range (IQR)50875000

Descriptive statistics

Standard deviation60949958
Coefficient of variation (CV)0.15185508
Kurtosis-0.011317176
Mean4.0136923 × 108
Median Absolute Deviation (MAD)26400000
Skewness0.98012836
Sum1.04356 × 1010
Variance3.7148974 × 1015
MonotonicityNot monotonic
2023-12-12T17:07:48.868698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
321500000 1
 
3.8%
375400000 1
 
3.8%
530800000 1
 
3.8%
520600000 1
 
3.8%
510500000 1
 
3.8%
500300000 1
 
3.8%
495200000 1
 
3.8%
422300000 1
 
3.8%
414300000 1
 
3.8%
406200000 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
321500000 1
3.8%
327500000 1
3.8%
337500000 1
3.8%
340900000 1
3.8%
347800000 1
3.8%
354700000 1
3.8%
361500000 1
3.8%
362200000 1
3.8%
368900000 1
3.8%
375400000 1
3.8%
ValueCountFrequency (%)
530800000 1
3.8%
520600000 1
3.8%
510500000 1
3.8%
500300000 1
3.8%
495200000 1
3.8%
422300000 1
3.8%
414300000 1
3.8%
407300000 1
3.8%
406200000 1
3.8%
399500000 1
3.8%

데이터 기준일자
Date

CONSTANT 

Distinct1
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size340.0 B
Minimum2022-10-26 00:00:00
Maximum2022-10-26 00:00:00
2023-12-12T17:07:49.328027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:49.438309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T17:07:45.142939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:43.684335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:44.142488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:44.652702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:45.278388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:43.790080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:44.262801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:44.752803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:45.427854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:43.915190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:44.393773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:44.889714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:45.547363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:44.041479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:44.560343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:45.024625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:07:49.531343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
약식표기공급세대수동호별층구분해당 세대수대지비(단위_원)건축비(단위_원)부가세(단위_원)분양가격(계)(단위_원)
약식표기1.0001.0001.0000.0000.0000.9570.957NaN0.820
공급세대수1.0001.0001.0000.0000.0000.9570.957NaN0.820
동호별1.0001.0001.0000.0000.0000.7900.790NaN0.778
층구분0.0000.0000.0001.0000.7100.0000.0001.0000.000
해당 세대수0.0000.0000.0000.7101.0000.0000.0001.0000.469
대지비(단위_원)0.9570.9570.7900.0000.0001.0001.0001.0000.913
건축비(단위_원)0.9570.9570.7900.0000.0001.0001.0001.0000.913
부가세(단위_원)NaNNaNNaN1.0001.0001.0001.0001.0001.000
분양가격(계)(단위_원)0.8200.8200.7780.0000.4690.9130.9131.0001.000
2023-12-12T17:07:49.702955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
층구분공급세대수동호별부가세(단위_원)약식표기
층구분1.0000.0000.0001.0000.000
공급세대수0.0001.0000.7981.0001.000
동호별0.0000.7981.0001.0000.798
부가세(단위_원)1.0001.0001.0001.0001.000
약식표기0.0001.0000.7981.0001.000
2023-12-12T17:07:49.852626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
해당 세대수대지비(단위_원)건축비(단위_원)분양가격(계)(단위_원)약식표기공급세대수동호별층구분부가세(단위_원)
해당 세대수1.0000.3650.3650.3650.0000.0000.0000.2991.000
대지비(단위_원)0.3651.0001.0001.0000.6600.6600.4280.0001.000
건축비(단위_원)0.3651.0001.0001.0000.6600.6600.4280.0001.000
분양가격(계)(단위_원)0.3651.0001.0001.0000.6810.6810.4570.0001.000
약식표기0.0000.6600.6600.6811.0001.0000.7980.0001.000
공급세대수0.0000.6600.6600.6811.0001.0000.7980.0001.000
동호별0.0000.4280.4280.4570.7980.7981.0000.0001.000
층구분0.2990.0000.0000.0000.0000.0000.0001.0001.000
부가세(단위_원)1.0001.0001.0001.0001.0001.0001.0001.0001.000

Missing values

2023-12-12T17:07:45.712596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:07:45.958929image/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

아파트명약식표기공급세대수동호별층구분해당 세대수대지비(단위_원)건축비(단위_원)부가세(단위_원)분양가격(계)(단위_원)데이터 기준일자
0김천 푸르지오 더 퍼스트74145101동 1+2호 라인1층573560000247940000<NA>3215000002022-10-26
1김천 푸르지오 더 퍼스트74145101동 1+2호 라인2층574930000252570000<NA>3275000002022-10-26
2김천 푸르지오 더 퍼스트74145101동 1+2호 라인2층(P)177220000260280000<NA>3375000002022-10-26
3김천 푸르지오 더 퍼스트74145101동 1+2호 라인3+5층1878000000262900000<NA>3409000002022-10-26
4김천 푸르지오 더 퍼스트74145101동 1+2호 라인6+10층3079580000268220000<NA>3478000002022-10-26
5김천 푸르지오 더 퍼스트74145101동 1+2호 라인11+20층6081160000273540000<NA>3547000002022-10-26
6김천 푸르지오 더 퍼스트74145101동 1+2호 라인21+28층2682710000278790000<NA>3615000002022-10-26
7김천 푸르지오 더 퍼스트84A310101동 4호 라인1층382870000279330000<NA>3622000002022-10-26
8김천 푸르지오 더 퍼스트84A310102동 4호 라인2층384400000284500000<NA>3689000002022-10-26
9김천 푸르지오 더 퍼스트84A310104동 1+3+4호 라인2층(P)986990000293210000<NA>3802000002022-10-26
아파트명약식표기공급세대수동호별층구분해당 세대수대지비(단위_원)건축비(단위_원)부가세(단위_원)분양가격(계)(단위_원)데이터 기준일자
16김천 푸르지오 더 퍼스트84B152104동 2호 라인2층(P)490170000303930000<NA>3941000002022-10-26
17김천 푸르지오 더 퍼스트84B152105동 2호 라인3+5층1891110000307090000<NA>3982000002022-10-26
18김천 푸르지오 더 퍼스트84B152106동 2호 라인6+10층3092940000313260000<NA>4062000002022-10-26
19김천 푸르지오 더 퍼스트84B152108동 3호 라인11+20층5794790000319510000<NA>4143000002022-10-26
20김천 푸르지오 더 퍼스트84B152108동 3호 라인21+28층3996620000325680000<NA>4223000002022-10-26
21김천 푸르지오 더 퍼스트9996103동 1+2호 라인2층(P)4105184000354560000354560004952000002022-10-26
22김천 푸르지오 더 퍼스트9996103동 1+2호 라인3+5층12106269000358210000358210005003000002022-10-26
23김천 푸르지오 더 퍼스트9996103동 1+2호 라인6+10층20108428000365520000365520005105000002022-10-26
24김천 푸르지오 더 퍼스트9996103동 1+2호 라인11+20층40110575000372750000372750005206000002022-10-26
25김천 푸르지오 더 퍼스트9996103동 1+2호 라인21+28층20112745000380050000380050005308000002022-10-26