Overview

Dataset statistics

Number of variables21
Number of observations806
Missing cells23
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory135.5 KiB
Average record size in memory172.2 B

Variable types

Numeric4
Categorical6
Text7
DateTime4

Alerts

sido has constant value ""Constant
reference_date has constant value ""Constant
last_load_dttm has constant value ""Constant
private_public is highly imbalanced (94.6%)Imbalance
lease_sell_inlots is highly imbalanced (92.8%)Imbalance
contract_deadline has 18 (2.2%) missing valuesMissing
skey has unique valuesUnique
unsell_nm_household has 632 (78.4%) zerosZeros

Reproduction

Analysis started2024-04-17 21:29:42.850539
Analysis finished2024-04-17 21:29:43.333278
Duration0.48 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Real number (ℝ)

UNIQUE 

Distinct806
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4062.5
Minimum3660
Maximum4465
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2024-04-18T06:29:43.388822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3660
5-th percentile3700.25
Q13861.25
median4062.5
Q34263.75
95-th percentile4424.75
Maximum4465
Range805
Interquartile range (IQR)402.5

Descriptive statistics

Standard deviation232.81645
Coefficient of variation (CV)0.057308665
Kurtosis-1.2
Mean4062.5
Median Absolute Deviation (MAD)201.5
Skewness0
Sum3274375
Variance54203.5
MonotonicityNot monotonic
2024-04-18T06:29:43.503322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4372 1
 
0.1%
3837 1
 
0.1%
3913 1
 
0.1%
3914 1
 
0.1%
3915 1
 
0.1%
3916 1
 
0.1%
3917 1
 
0.1%
3832 1
 
0.1%
3833 1
 
0.1%
3834 1
 
0.1%
Other values (796) 796
98.8%
ValueCountFrequency (%)
3660 1
0.1%
3661 1
0.1%
3662 1
0.1%
3663 1
0.1%
3664 1
0.1%
3665 1
0.1%
3666 1
0.1%
3667 1
0.1%
3668 1
0.1%
3669 1
0.1%
ValueCountFrequency (%)
4465 1
0.1%
4464 1
0.1%
4463 1
0.1%
4462 1
0.1%
4461 1
0.1%
4460 1
0.1%
4459 1
0.1%
4458 1
0.1%
4457 1
0.1%
4456 1
0.1%

sido
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
부산광역시
806 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부산광역시 806
100.0%

Length

2024-04-18T06:29:43.617030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:29:43.703326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 806
100.0%

sigungu
Categorical

Distinct15
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
동래구
95 
부산진구
83 
수영구
76 
강서구
69 
기장군
55 
Other values (10)
428 

Length

Max length4
Median length3
Mean length2.9789082
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
동래구 95
11.8%
부산진구 83
10.3%
수영구 76
9.4%
강서구 69
 
8.6%
기장군 55
 
6.8%
금정구 55
 
6.8%
사하구 51
 
6.3%
사상구 51
 
6.3%
해운대구 47
 
5.8%
연제구 46
 
5.7%
Other values (5) 178
22.1%

Length

2024-04-18T06:29:43.811689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
동래구 95
11.8%
부산진구 83
10.3%
수영구 76
9.4%
강서구 69
 
8.6%
기장군 55
 
6.8%
금정구 55
 
6.8%
사하구 51
 
6.3%
사상구 51
 
6.3%
해운대구 47
 
5.8%
연제구 46
 
5.7%
Other values (5) 178
22.1%

eupmundong
Text

Distinct68
Distinct (%)8.4%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
2024-04-18T06:29:44.021755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.0558313
Min length2

Characters and Unicode

Total characters2463
Distinct characters80
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row연산동
2nd row연산동
3rd row연산동
4th row연산동
5th row연산동
ValueCountFrequency (%)
온천동 59
 
7.3%
명지동 58
 
7.2%
연산동 43
 
5.3%
민락동 29
 
3.6%
괘법동 27
 
3.3%
문현동 25
 
3.1%
남천동 24
 
3.0%
괴정동 24
 
3.0%
일광면 23
 
2.9%
초량동 21
 
2.6%
Other values (57) 473
58.7%
2024-04-18T06:29:44.345091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 764
31.0%
천 123
 
5.0%
명 84
 
3.4%
지 81
 
3.3%
연 65
 
2.6%
온 59
 
2.4%
정 51
 
2.1%
남 45
 
1.8%
산 43
 
1.7%
광 40
 
1.6%
Other values (70) 1108
45.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2423
98.4%
Decimal Number 29
 
1.2%
Space Separator 11
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 764
31.5%
천 123
 
5.1%
명 84
 
3.5%
지 81
 
3.3%
연 65
 
2.7%
온 59
 
2.4%
정 51
 
2.1%
남 45
 
1.9%
산 43
 
1.8%
광 40
 
1.7%
Other values (67) 1068
44.1%
Decimal Number
ValueCountFrequency (%)
1 19
65.5%
4 10
34.5%
Space Separator
ValueCountFrequency (%)
11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2423
98.4%
Common 40
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 764
31.5%
천 123
 
5.1%
명 84
 
3.5%
지 81
 
3.3%
연 65
 
2.7%
온 59
 
2.4%
정 51
 
2.1%
남 45
 
1.9%
산 43
 
1.8%
광 40
 
1.7%
Other values (67) 1068
44.1%
Common
ValueCountFrequency (%)
1 19
47.5%
11
27.5%
4 10
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2423
98.4%
ASCII 40
 
1.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 764
31.5%
천 123
 
5.1%
명 84
 
3.5%
지 81
 
3.3%
연 65
 
2.7%
온 59
 
2.4%
정 51
 
2.1%
남 45
 
1.9%
산 43
 
1.8%
광 40
 
1.7%
Other values (67) 1068
44.1%
ASCII
ValueCountFrequency (%)
1 19
47.5%
11
27.5%
4 10
25.0%

addr
Text

Distinct168
Distinct (%)20.8%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
2024-04-18T06:29:44.560229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length28
Mean length21.769231
Min length12

Characters and Unicode

Total characters17546
Distinct characters267
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)2.6%

Sample

1st row2166번지 일원(센텀리버SK뷰)
2nd row2166번지 일원(센텀리버SK뷰)
3rd row2166번지 일원(센텀리버SK뷰)
4th row1498-9번지 외 6필지(더리체)
5th row1498-9번지 외 6필지(더리체)
ValueCountFrequency (%)
외 65
 
2.7%
온천동 59
 
2.4%
더 49
 
2.0%
민락동 29
 
1.2%
더샵 27
 
1.1%
일원(동래 24
 
1.0%
일광지구 23
 
0.9%
테라스 22
 
0.9%
28-12번지(금상자연드림뷰 21
 
0.9%
범천동 20
 
0.8%
Other values (374) 2097
86.1%
2024-04-18T06:29:44.916603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1645
 
9.4%
지 859
 
4.9%
) 806
 
4.6%
( 806
 
4.6%
1 750
 
4.3%
번 601
 
3.4%
- 551
 
3.1%
2 511
 
2.9%
동 435
 
2.5%
일 416
 
2.4%
Other values (257) 10166
57.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9971
56.8%
Decimal Number 3480
 
19.8%
Space Separator 1645
 
9.4%
Close Punctuation 806
 
4.6%
Open Punctuation 806
 
4.6%
Dash Punctuation 551
 
3.1%
Uppercase Letter 207
 
1.2%
Lowercase Letter 51
 
0.3%
Other Punctuation 29
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 859
 
8.6%
번 601
 
6.0%
동 435
 
4.4%
일 416
 
4.2%
원 386
 
3.9%
스 293
 
2.9%
트 204
 
2.0%
더 175
 
1.8%
이 162
 
1.6%
아 155
 
1.6%
Other values (220) 6285
63.0%
Uppercase Letter
ValueCountFrequency (%)
S 35
16.9%
B 31
15.0%
W 20
9.7%
K 18
8.7%
E 17
8.2%
A 15
7.2%
D 13
 
6.3%
C 12
 
5.8%
V 9
 
4.3%
I 9
 
4.3%
Other values (6) 28
13.5%
Decimal Number
ValueCountFrequency (%)
1 750
21.6%
2 511
14.7%
3 376
10.8%
5 337
9.7%
4 329
9.5%
8 290
 
8.3%
6 234
 
6.7%
0 232
 
6.7%
7 229
 
6.6%
9 192
 
5.5%
Lowercase Letter
ValueCountFrequency (%)
e 42
82.4%
l 5
 
9.8%
t 2
 
3.9%
h 2
 
3.9%
Other Punctuation
ValueCountFrequency (%)
, 17
58.6%
. 6
 
20.7%
: 6
 
20.7%
Space Separator
ValueCountFrequency (%)
1645
100.0%
Close Punctuation
ValueCountFrequency (%)
) 806
100.0%
Open Punctuation
ValueCountFrequency (%)
( 806
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 551
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9964
56.8%
Common 7317
41.7%
Latin 258
 
1.5%
Han 7
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 859
 
8.6%
번 601
 
6.0%
동 435
 
4.4%
일 416
 
4.2%
원 386
 
3.9%
스 293
 
2.9%
트 204
 
2.0%
더 175
 
1.8%
이 162
 
1.6%
아 155
 
1.6%
Other values (219) 6278
63.0%
Latin
ValueCountFrequency (%)
e 42
16.3%
S 35
13.6%
B 31
12.0%
W 20
7.8%
K 18
 
7.0%
E 17
 
6.6%
A 15
 
5.8%
D 13
 
5.0%
C 12
 
4.7%
V 9
 
3.5%
Other values (10) 46
17.8%
Common
ValueCountFrequency (%)
1645
22.5%
) 806
11.0%
( 806
11.0%
1 750
10.3%
- 551
 
7.5%
2 511
 
7.0%
3 376
 
5.1%
5 337
 
4.6%
4 329
 
4.5%
8 290
 
4.0%
Other values (7) 916
12.5%
Han
ValueCountFrequency (%)
休 7
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9964
56.8%
ASCII 7575
43.2%
CJK 7
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1645
21.7%
) 806
10.6%
( 806
10.6%
1 750
9.9%
- 551
 
7.3%
2 511
 
6.7%
3 376
 
5.0%
5 337
 
4.4%
4 329
 
4.3%
8 290
 
3.8%
Other values (27) 1174
15.5%
Hangul
ValueCountFrequency (%)
지 859
 
8.6%
번 601
 
6.0%
동 435
 
4.4%
일 416
 
4.2%
원 386
 
3.9%
스 293
 
2.9%
트 204
 
2.0%
더 175
 
1.8%
이 162
 
1.6%
아 155
 
1.6%
Other values (219) 6278
63.0%
CJK
ValueCountFrequency (%)
休 7
100.0%

contractor
Text

Distinct137
Distinct (%)17.0%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
2024-04-18T06:29:45.099603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length19
Mean length6.5421836
Min length3

Characters and Unicode

Total characters5273
Distinct characters140
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)4.2%

Sample

1st rowSK건설
2nd rowSK건설
3rd rowSK건설
4th row㈜두잉건설
5th row㈜두잉건설
ValueCountFrequency (%)
대림산업㈜ 25
 
2.9%
경동건설㈜ 22
 
2.6%
수근종합건설㈜ 21
 
2.5%
금상건설주식회사 21
 
2.5%
㈜동부토건 20
 
2.4%
아이에스동서㈜ 20
 
2.4%
가화건설대표김병균 18
 
2.1%
㈜동원개발 17
 
2.0%
한신공영 17
 
2.0%
롯데건설㈜ 16
 
1.9%
Other values (133) 651
76.8%
2024-04-18T06:29:45.400957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
건 559
 
10.6%
설 507
 
9.6%
㈜ 502
 
9.5%
주 150
 
2.8%
동 148
 
2.8%
합 143
 
2.7%
종 141
 
2.7%
대 120
 
2.3%
산 96
 
1.8%
삼 76
 
1.4%
Other values (130) 2831
53.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4180
79.3%
Other Symbol 502
 
9.5%
Decimal Number 284
 
5.4%
Open Punctuation 69
 
1.3%
Close Punctuation 69
 
1.3%
Space Separator 63
 
1.2%
Dash Punctuation 54
 
1.0%
Uppercase Letter 46
 
0.9%
Other Punctuation 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
건 559
 
13.4%
설 507
 
12.1%
주 150
 
3.6%
동 148
 
3.5%
합 143
 
3.4%
종 141
 
3.4%
대 120
 
2.9%
산 96
 
2.3%
삼 76
 
1.8%
성 73
 
1.7%
Other values (111) 2167
51.8%
Decimal Number
ValueCountFrequency (%)
1 62
21.8%
0 52
18.3%
5 36
12.7%
8 35
12.3%
7 27
9.5%
2 22
 
7.7%
6 20
 
7.0%
9 13
 
4.6%
3 10
 
3.5%
4 7
 
2.5%
Uppercase Letter
ValueCountFrequency (%)
S 23
50.0%
K 18
39.1%
I 5
 
10.9%
Other Symbol
ValueCountFrequency (%)
㈜ 502
100.0%
Open Punctuation
ValueCountFrequency (%)
( 69
100.0%
Close Punctuation
ValueCountFrequency (%)
) 69
100.0%
Space Separator
ValueCountFrequency (%)
63
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 54
100.0%
Other Punctuation
ValueCountFrequency (%)
. 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4682
88.8%
Common 545
 
10.3%
Latin 46
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
건 559
 
11.9%
설 507
 
10.8%
㈜ 502
 
10.7%
주 150
 
3.2%
동 148
 
3.2%
합 143
 
3.1%
종 141
 
3.0%
대 120
 
2.6%
산 96
 
2.1%
삼 76
 
1.6%
Other values (112) 2240
47.8%
Common
ValueCountFrequency (%)
( 69
12.7%
) 69
12.7%
63
11.6%
1 62
11.4%
- 54
9.9%
0 52
9.5%
5 36
6.6%
8 35
6.4%
7 27
 
5.0%
2 22
 
4.0%
Other values (5) 56
10.3%
Latin
ValueCountFrequency (%)
S 23
50.0%
K 18
39.1%
I 5
 
10.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4180
79.3%
ASCII 591
 
11.2%
None 502
 
9.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
건 559
 
13.4%
설 507
 
12.1%
주 150
 
3.6%
동 148
 
3.5%
합 143
 
3.4%
종 141
 
3.4%
대 120
 
2.9%
산 96
 
2.3%
삼 76
 
1.8%
성 73
 
1.7%
Other values (111) 2167
51.8%
None
ValueCountFrequency (%)
㈜ 502
100.0%
ASCII
ValueCountFrequency (%)
( 69
11.7%
) 69
11.7%
63
10.7%
1 62
10.5%
- 54
9.1%
0 52
8.8%
5 36
 
6.1%
8 35
 
5.9%
7 27
 
4.6%
S 23
 
3.9%
Other values (8) 101
17.1%

developer
Text

Distinct136
Distinct (%)16.9%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
2024-04-18T06:29:45.636758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length17
Mean length8.7630273
Min length2

Characters and Unicode

Total characters7063
Distinct characters184
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)0.2%

Sample

1st row주식회사 하나신탁
2nd row주식회사 하나신탁
3rd row주식회사 하나신탁
4th row㈜두잉건설
5th row㈜두잉건설
ValueCountFrequency (%)
주택재개발정비사업조합 33
 
3.5%
대한토지신탁㈜ 22
 
2.3%
금상건설주식회사 21
 
2.2%
주식회사 20
 
2.1%
대한리츠 15
 
1.6%
코리아신탁㈜ 13
 
1.4%
온천2구역 13
 
1.4%
㈜무궁화신탁 13
 
1.4%
국제자산신탁㈜ 13
 
1.4%
kb부동산신탁㈜ 13
 
1.4%
Other values (142) 774
81.5%
2024-04-18T06:29:46.023597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 420
 
5.9%
주 360
 
5.1%
합 234
 
3.3%
건 224
 
3.2%
사 222
 
3.1%
택 216
 
3.1%
조 197
 
2.8%
신 191
 
2.7%
역 190
 
2.7%
설 190
 
2.7%
Other values (174) 4619
65.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6153
87.1%
Other Symbol 420
 
5.9%
Space Separator 151
 
2.1%
Decimal Number 144
 
2.0%
Uppercase Letter 78
 
1.1%
Close Punctuation 47
 
0.7%
Open Punctuation 47
 
0.7%
Other Punctuation 18
 
0.3%
Dash Punctuation 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 360
 
5.9%
합 234
 
3.8%
건 224
 
3.6%
사 222
 
3.6%
택 216
 
3.5%
조 197
 
3.2%
신 191
 
3.1%
역 190
 
3.1%
설 190
 
3.1%
정 177
 
2.9%
Other values (158) 3952
64.2%
Uppercase Letter
ValueCountFrequency (%)
K 34
43.6%
S 17
21.8%
B 13
 
16.7%
M 9
 
11.5%
D 5
 
6.4%
Decimal Number
ValueCountFrequency (%)
2 70
48.6%
1 53
36.8%
3 16
 
11.1%
6 5
 
3.5%
Other Punctuation
ValueCountFrequency (%)
, 12
66.7%
. 6
33.3%
Other Symbol
ValueCountFrequency (%)
㈜ 420
100.0%
Space Separator
ValueCountFrequency (%)
151
100.0%
Close Punctuation
ValueCountFrequency (%)
) 47
100.0%
Open Punctuation
ValueCountFrequency (%)
( 47
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6573
93.1%
Common 412
 
5.8%
Latin 78
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 420
 
6.4%
주 360
 
5.5%
합 234
 
3.6%
건 224
 
3.4%
사 222
 
3.4%
택 216
 
3.3%
조 197
 
3.0%
신 191
 
2.9%
역 190
 
2.9%
설 190
 
2.9%
Other values (159) 4129
62.8%
Common
ValueCountFrequency (%)
151
36.7%
2 70
17.0%
1 53
 
12.9%
) 47
 
11.4%
( 47
 
11.4%
3 16
 
3.9%
, 12
 
2.9%
. 6
 
1.5%
- 5
 
1.2%
6 5
 
1.2%
Latin
ValueCountFrequency (%)
K 34
43.6%
S 17
21.8%
B 13
 
16.7%
M 9
 
11.5%
D 5
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6153
87.1%
ASCII 490
 
6.9%
None 420
 
5.9%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 420
100.0%
Hangul
ValueCountFrequency (%)
주 360
 
5.9%
합 234
 
3.8%
건 224
 
3.6%
사 222
 
3.6%
택 216
 
3.5%
조 197
 
3.2%
신 191
 
3.1%
역 190
 
3.1%
설 190
 
3.1%
정 177
 
2.9%
Other values (158) 3952
64.2%
ASCII
ValueCountFrequency (%)
151
30.8%
2 70
14.3%
1 53
 
10.8%
) 47
 
9.6%
( 47
 
9.6%
K 34
 
6.9%
S 17
 
3.5%
3 16
 
3.3%
B 13
 
2.7%
, 12
 
2.4%
Other values (5) 30
 
6.1%

private_public
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
민간
801 
민간
 
5

Length

Max length3
Median length2
Mean length2.0062035
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
민간 801
99.4%
민간 5
 
0.6%

Length

2024-04-18T06:29:46.144709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:29:46.229492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
민간 806
100.0%

lease_sell_inlots
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
분양
799 
분양(완료)
 
7

Length

Max length6
Median length2
Mean length2.0347395
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
분양 799
99.1%
분양(완료) 7
 
0.9%

Length

2024-04-18T06:29:46.327478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:29:46.419680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
분양 799
99.1%
분양(완료 7
 
0.9%

scale
Text

Distinct620
Distinct (%)76.9%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
2024-04-18T06:29:46.660789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length5.6823821
Min length2

Characters and Unicode

Total characters4580
Distinct characters34
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique541 ?
Unique (%)67.1%

Sample

1st row64.0118
2nd row84.9554
3rd row84.9972
4th row64.76
5th row71.29
ValueCountFrequency (%)
84b 15
 
1.8%
59 15
 
1.8%
84 14
 
1.7%
84a 13
 
1.6%
84c 11
 
1.3%
84.99 9
 
1.1%
73 6
 
0.7%
84.96 6
 
0.7%
60 5
 
0.6%
74 5
 
0.6%
Other values (615) 717
87.9%
2024-04-18T06:29:47.097138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 555
12.1%
9 515
11.2%
4 505
11.0%
8 491
10.7%
7 380
8.3%
1 351
7.7%
6 330
7.2%
5 315
6.9%
2 216
 
4.7%
3 206
 
4.5%
Other values (24) 716
15.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3497
76.4%
Other Punctuation 555
 
12.1%
Uppercase Letter 254
 
5.5%
Open Punctuation 86
 
1.9%
Close Punctuation 86
 
1.9%
Other Symbol 41
 
0.9%
Other Letter 36
 
0.8%
Space Separator 10
 
0.2%
Dash Punctuation 9
 
0.2%
Math Symbol 5
 
0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 95
37.4%
B 91
35.8%
C 39
15.4%
D 17
 
6.7%
E 4
 
1.6%
P 2
 
0.8%
F 2
 
0.8%
G 1
 
0.4%
I 1
 
0.4%
H 1
 
0.4%
Decimal Number
ValueCountFrequency (%)
9 515
14.7%
4 505
14.4%
8 491
14.0%
7 380
10.9%
1 351
10.0%
6 330
9.4%
5 315
9.0%
2 216
6.2%
3 206
 
5.9%
0 188
 
5.4%
Other Letter
ValueCountFrequency (%)
층 26
72.2%
가 3
 
8.3%
다 3
 
8.3%
라 2
 
5.6%
나 2
 
5.6%
Other Punctuation
ValueCountFrequency (%)
. 555
100.0%
Open Punctuation
ValueCountFrequency (%)
( 86
100.0%
Close Punctuation
ValueCountFrequency (%)
) 86
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 41
100.0%
Space Separator
ValueCountFrequency (%)
10
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%
Lowercase Letter
ValueCountFrequency (%)
z 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4289
93.6%
Latin 255
 
5.6%
Hangul 36
 
0.8%

Most frequent character per script

Common
ValueCountFrequency (%)
. 555
12.9%
9 515
12.0%
4 505
11.8%
8 491
11.4%
7 380
8.9%
1 351
8.2%
6 330
7.7%
5 315
7.3%
2 216
 
5.0%
3 206
 
4.8%
Other values (7) 425
9.9%
Latin
ValueCountFrequency (%)
A 95
37.3%
B 91
35.7%
C 39
15.3%
D 17
 
6.7%
E 4
 
1.6%
P 2
 
0.8%
F 2
 
0.8%
G 1
 
0.4%
I 1
 
0.4%
H 1
 
0.4%
Other values (2) 2
 
0.8%
Hangul
ValueCountFrequency (%)
층 26
72.2%
가 3
 
8.3%
다 3
 
8.3%
라 2
 
5.6%
나 2
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4503
98.3%
CJK Compat 41
 
0.9%
Hangul 36
 
0.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 555
12.3%
9 515
11.4%
4 505
11.2%
8 491
10.9%
7 380
8.4%
1 351
7.8%
6 330
7.3%
5 315
7.0%
2 216
 
4.8%
3 206
 
4.6%
Other values (18) 639
14.2%
CJK Compat
ValueCountFrequency (%)
㎡ 41
100.0%
Hangul
ValueCountFrequency (%)
층 26
72.2%
가 3
 
8.3%
다 3
 
8.3%
라 2
 
5.6%
나 2
 
5.6%

tot_sell_nm_household
Text

Distinct236
Distinct (%)29.4%
Missing4
Missing (%)0.5%
Memory size6.4 KiB
2024-04-18T06:29:47.425206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.0947631
Min length1

Characters and Unicode

Total characters1680
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

Unique106 ?
Unique (%)13.2%

Sample

1st row239
2nd row50
3rd row240
4th row16
5th row17
ValueCountFrequency (%)
1 56
 
7.0%
19 27
 
3.4%
17 27
 
3.4%
2 24
 
3.0%
4 17
 
2.1%
38 17
 
2.1%
25 17
 
2.1%
14 16
 
2.0%
16 15
 
1.9%
13 15
 
1.9%
Other values (226) 571
71.2%
2024-04-18T06:29:47.858714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 366
21.8%
2 268
16.0%
3 171
10.2%
4 153
9.1%
5 134
 
8.0%
6 134
 
8.0%
0 127
 
7.6%
7 111
 
6.6%
8 111
 
6.6%
9 102
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1677
99.8%
Other Punctuation 3
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 366
21.8%
2 268
16.0%
3 171
10.2%
4 153
9.1%
5 134
 
8.0%
6 134
 
8.0%
0 127
 
7.6%
7 111
 
6.6%
8 111
 
6.6%
9 102
 
6.1%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1680
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 366
21.8%
2 268
16.0%
3 171
10.2%
4 153
9.1%
5 134
 
8.0%
6 134
 
8.0%
0 127
 
7.6%
7 111
 
6.6%
8 111
 
6.6%
9 102
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1680
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 366
21.8%
2 268
16.0%
3 171
10.2%
4 153
9.1%
5 134
 
8.0%
6 134
 
8.0%
0 127
 
7.6%
7 111
 
6.6%
8 111
 
6.6%
9 102
 
6.1%

unsell_nm_household
Real number (ℝ)

ZEROS 

Distinct23
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3511166
Minimum0
Maximum62
Zeros632
Zeros (%)78.4%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2024-04-18T06:29:47.968706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile8
Maximum62
Range62
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4.785282
Coefficient of variation (CV)3.5417239
Kurtosis74.447577
Mean1.3511166
Median Absolute Deviation (MAD)0
Skewness7.3507424
Sum1089
Variance22.898924
MonotonicityNot monotonic
2024-04-18T06:29:48.070766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 632
78.4%
1 50
 
6.2%
2 26
 
3.2%
3 17
 
2.1%
6 11
 
1.4%
4 9
 
1.1%
5 8
 
1.0%
11 7
 
0.9%
7 7
 
0.9%
8 6
 
0.7%
Other values (13) 33
 
4.1%
ValueCountFrequency (%)
0 632
78.4%
1 50
 
6.2%
2 26
 
3.2%
3 17
 
2.1%
4 9
 
1.1%
5 8
 
1.0%
6 11
 
1.4%
7 7
 
0.9%
8 6
 
0.7%
9 5
 
0.6%
ValueCountFrequency (%)
62 2
0.2%
40 1
 
0.1%
36 1
 
0.1%
27 1
 
0.1%
20 4
0.5%
19 3
0.4%
18 2
0.2%
16 2
0.2%
14 1
 
0.1%
13 3
0.4%

sell_subscription_dt
Date

Distinct145
Distinct (%)18.0%
Missing1
Missing (%)0.1%
Memory size6.4 KiB
Minimum2003-12-10 00:00:00
Maximum2020-09-10 00:00:00
2024-04-18T06:29:48.189269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T06:29:48.311390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

contract_deadline
Text

MISSING 

Distinct137
Distinct (%)17.4%
Missing18
Missing (%)2.2%
Memory size6.4 KiB
2024-04-18T06:29:48.556728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.9733503
Min length3

Characters and Unicode

Total characters7859
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)0.5%

Sample

1st row2017-01-01
2nd row2017-01-01
3rd row2017-01-01
4th row2018-11-01
5th row2018-11-01
ValueCountFrequency (%)
2014-07-23 21
 
2.7%
2017-11-27 16
 
2.0%
2018-04-25 14
 
1.8%
2019-07-31 13
 
1.6%
2018-10-26 13
 
1.6%
2017-09-14 13
 
1.6%
2018-06-21 12
 
1.5%
2017-11-17 12
 
1.5%
2019-07-19 12
 
1.5%
2017-09-28 10
 
1.3%
Other values (127) 652
82.7%
2024-04-18T06:29:48.966662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1744
22.2%
- 1570
20.0%
1 1512
19.2%
2 1298
16.5%
7 377
 
4.8%
8 319
 
4.1%
9 246
 
3.1%
3 208
 
2.6%
6 207
 
2.6%
5 197
 
2.5%
Other values (4) 181
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6280
79.9%
Dash Punctuation 1570
 
20.0%
Other Letter 9
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1744
27.8%
1 1512
24.1%
2 1298
20.7%
7 377
 
6.0%
8 319
 
5.1%
9 246
 
3.9%
3 208
 
3.3%
6 207
 
3.3%
5 197
 
3.1%
4 172
 
2.7%
Other Letter
ValueCountFrequency (%)
후 3
33.3%
분 3
33.3%
양 3
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 1570
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7850
99.9%
Hangul 9
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1744
22.2%
- 1570
20.0%
1 1512
19.3%
2 1298
16.5%
7 377
 
4.8%
8 319
 
4.1%
9 246
 
3.1%
3 208
 
2.6%
6 207
 
2.6%
5 197
 
2.5%
Hangul
ValueCountFrequency (%)
후 3
33.3%
분 3
33.3%
양 3
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7850
99.9%
Hangul 9
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1744
22.2%
- 1570
20.0%
1 1512
19.3%
2 1298
16.5%
7 377
 
4.8%
8 319
 
4.1%
9 246
 
3.1%
3 208
 
2.6%
6 207
 
2.6%
5 197
 
2.5%
Hangul
ValueCountFrequency (%)
후 3
33.3%
분 3
33.3%
양 3
33.3%

move_in_month
Date

Distinct104
Distinct (%)12.9%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
Minimum2005-11-01 00:00:00
Maximum2023-09-01 00:00:00
2024-04-18T06:29:49.097440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T06:29:49.215616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

completion_at
Categorical

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
준공
483 
미준공
320 
준공
 
3

Length

Max length3
Median length2
Mean length2.4007444
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
준공 483
59.9%
미준공 320
39.7%
준공 3
 
0.4%

Length

2024-04-18T06:29:49.325106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:29:49.412565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
준공 486
60.3%
미준공 320
39.7%

housing_site_kind
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
민간
687 
공공
119 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
민간 687
85.2%
공공 119
 
14.8%

Length

2024-04-18T06:29:49.501449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:29:49.579607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
민간 687
85.2%
공공 119
 
14.8%

reference_date
Date

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
Minimum2020-12-31 00:00:00
Maximum2020-12-31 00:00:00
2024-04-18T06:29:49.648158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T06:29:49.718838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

lat
Real number (ℝ)

Distinct134
Distinct (%)16.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.162931
Minimum35.069128
Maximum35.329677
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2024-04-18T06:29:49.831374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.069128
5-th percentile35.080206
Q135.113744
median35.160886
Q335.196395
95-th percentile35.27425
Maximum35.329677
Range0.26054951
Interquartile range (IQR)0.08265103

Descriptive statistics

Standard deviation0.058676321
Coefficient of variation (CV)0.0016686982
Kurtosis-0.123535
Mean35.162931
Median Absolute Deviation (MAD)0.043182035
Skewness0.49503376
Sum28341.322
Variance0.0034429107
MonotonicityNot monotonic
2024-04-18T06:29:50.386306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.19409095 50
 
6.2%
35.07929348 29
 
3.6%
35.28509964 23
 
2.9%
35.11144649 19
 
2.4%
35.27424957 16
 
2.0%
35.23059965 14
 
1.7%
35.14414797 13
 
1.6%
35.21113915 13
 
1.6%
35.15568 13
 
1.6%
35.24768018 11
 
1.4%
Other values (124) 605
75.1%
ValueCountFrequency (%)
35.06912765 9
 
1.1%
35.07929348 29
3.6%
35.08020566 7
 
0.9%
35.08055239 5
 
0.6%
35.0817247 6
 
0.7%
35.08174187 4
 
0.5%
35.08266386 8
 
1.0%
35.08392102 7
 
0.9%
35.08394289 5
 
0.6%
35.08398608 5
 
0.6%
ValueCountFrequency (%)
35.32967716 3
 
0.4%
35.32335913 1
 
0.1%
35.32182119 11
1.4%
35.32162783 1
 
0.1%
35.28509964 23
2.9%
35.27424957 16
2.0%
35.25465638 6
 
0.7%
35.253 7
 
0.9%
35.24768018 11
1.4%
35.23900076 6
 
0.7%

lng
Real number (ℝ)

Distinct134
Distinct (%)16.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.06273
Minimum128.8762
Maximum129.98382
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2024-04-18T06:29:50.508485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.8762
5-th percentile128.90496
Q1129.02243
median129.06356
Q3129.09006
95-th percentile129.19398
Maximum129.98382
Range1.1076201
Interquartile range (IQR)0.0676301

Descriptive statistics

Standard deviation0.097639099
Coefficient of variation (CV)0.00075652437
Kurtosis37.824516
Mean129.06273
Median Absolute Deviation (MAD)0.0398318
Skewness4.063853
Sum104024.56
Variance0.0095333936
MonotonicityNot monotonic
2024-04-18T06:29:50.650718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
129.0224282 29
 
3.6%
129.0635613 28
 
3.5%
129.0900583 26
 
3.2%
129.2355707 23
 
2.9%
129.0235103 19
 
2.4%
129.0921658 16
 
2.0%
129.0897561 14
 
1.7%
129.0582469 13
 
1.6%
129.07055 13
 
1.6%
129.119064 13
 
1.6%
Other values (124) 612
75.9%
ValueCountFrequency (%)
128.8762039 8
1.0%
128.8780033 5
0.6%
128.8965939 4
0.5%
128.8967876 1
 
0.1%
128.8969029 7
0.9%
128.8998465 7
0.9%
128.9000285 4
0.5%
128.9049606 6
0.7%
128.9051172 5
0.6%
128.906 8
1.0%
ValueCountFrequency (%)
129.983824 4
 
0.5%
129.2355707 23
2.9%
129.219 7
 
0.9%
129.2155591 6
 
0.7%
129.1950827 1
 
0.1%
129.190665 11
1.4%
129.1900937 1
 
0.1%
129.1874178 1
 
0.1%
129.1818823 3
 
0.4%
129.1729215 5
 
0.6%

last_load_dttm
Date

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
Minimum2021-04-01 06:20:03
Maximum2021-04-01 06:20:03
2024-04-18T06:29:50.753911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T06:29:50.837589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Sample

skeysidosigungueupmundongaddrcontractordeveloperprivate_publiclease_sell_inlotsscaletot_sell_nm_householdunsell_nm_householdsell_subscription_dtcontract_deadlinemove_in_monthcompletion_athousing_site_kindreference_datelatlnglast_load_dttm
04372부산광역시연제구연산동2166번지 일원(센텀리버SK뷰)SK건설주식회사 하나신탁민간분양64.011823902014-07-012017-01-012017-01-01준공민간2020-12-3135.161852128.9822782021-04-01 06:20:03
14373부산광역시연제구연산동2166번지 일원(센텀리버SK뷰)SK건설주식회사 하나신탁민간분양84.95545002014-07-012017-01-012017-01-01준공민간2020-12-3135.161852128.9822782021-04-01 06:20:03
24374부산광역시연제구연산동2166번지 일원(센텀리버SK뷰)SK건설주식회사 하나신탁민간분양84.997224002014-07-012017-01-012017-01-01준공민간2020-12-3135.161852128.9822782021-04-01 06:20:03
34375부산광역시연제구연산동1498-9번지 외 6필지(더리체)㈜두잉건설㈜두잉건설민간분양64.761602017-04-012018-11-012018-11-01준공민간2020-12-3135.161852128.9822782021-04-01 06:20:03
44376부산광역시연제구연산동1498-9번지 외 6필지(더리체)㈜두잉건설㈜두잉건설민간분양71.291702017-04-012018-11-012018-11-01준공민간2020-12-3135.161852128.9822782021-04-01 06:20:03
54377부산광역시연제구연산동1498-9번지 외 6필지(더리체)㈜두잉건설㈜두잉건설민간분양82.271602017-04-012018-11-012018-11-01준공민간2020-12-3135.161852128.9822782021-04-01 06:20:03
64378부산광역시연제구연산동1498-9번지 외 6필지(더리체)㈜두잉건설㈜두잉건설민간분양84.091602017-04-012018-11-012018-11-01준공민간2020-12-3135.107858129.0182662021-04-01 06:20:03
74379부산광역시연제구연산동1498-9번지 외 6필지(더리체)㈜두잉건설㈜두잉건설민간분양91.11102017-04-012018-11-012018-11-01준공민간2020-12-3135.161852128.9822782021-04-01 06:20:03
84380부산광역시연제구연산동834-4번지 일원(연산 롯데캐슬 골드포레)롯데건설연산6구역주택재개발정비사업조합민간분양59.849302017-11-032017-11-292020-07-01미준공민간2020-12-3135.161852128.9822782021-04-01 06:20:03
94381부산광역시연제구연산동834-4번지 일원(연산 롯데캐슬 골드포레)롯데건설연산6구역주택재개발정비사업조합민간분양72.83519002017-11-032017-11-292020-07-01미준공민간2020-12-3135.161852128.9822782021-04-01 06:20:03
skeysidosigungueupmundongaddrcontractordeveloperprivate_publiclease_sell_inlotsscaletot_sell_nm_householdunsell_nm_householdsell_subscription_dtcontract_deadlinemove_in_monthcompletion_athousing_site_kindreference_datelatlnglast_load_dttm
7963695부산광역시강서구명지동3232번지 A4블록(퀸덤1차아파트)영조주택대한리츠민간분양84.848002006-04-052006-04-202009-02-01준공공공2020-12-3135.165126128.9820212021-04-01 06:20:03
7973696부산광역시강서구명지동3232번지 A4블록(퀸덤1차아파트)영조주택대한리츠민간분양101.828202006-04-052006-04-202009-02-01준공공공2020-12-3135.165126128.9820212021-04-01 06:20:03
7983697부산광역시강서구명지동3232번지 A4블록(퀸덤1차아파트)영조주택대한리츠민간분양117.228202006-04-052006-04-202009-02-01준공공공2020-12-3135.165126128.9820212021-04-01 06:20:03
7993698부산광역시강서구명지동3232번지 A4블록(퀸덤1차아파트)영조주택대한리츠민간분양144.56802006-04-052006-04-202009-02-01준공공공2020-12-3135.165126128.9820212021-04-01 06:20:03
8003699부산광역시강서구명지동3231번지외 1필지 A1,3블록(퀸덤1차아파트)영조주택대한리츠민간분양84.867902006-04-052006-04-202009-02-01준공공공2020-12-3135.111446129.023512021-04-01 06:20:03
8013700부산광역시강서구명지동3231번지외 1필지 A1,3블록(퀸덤1차아파트)영조주택대한리츠민간분양101.851602006-04-052006-04-202009-02-01준공공공2020-12-3135.111446129.023512021-04-01 06:20:03
8023701부산광역시강서구명지동3231번지외 1필지 A1,3블록(퀸덤1차아파트)영조주택대한리츠민간분양117.244702006-04-052006-04-202009-02-01준공공공2020-12-3135.111446129.023512021-04-01 06:20:03
8033702부산광역시강서구명지동3231번지외 1필지 A1,3블록(퀸덤1차아파트)영조주택대한리츠민간분양144.510302006-04-052006-04-202009-02-01준공공공2020-12-3135.111446129.023512021-04-01 06:20:03
8043703부산광역시강서구명지동3231번지외 1필지 A1,3블록(퀸덤1차아파트)영조주택대한리츠민간분양232902006-04-052006-04-202009-02-01준공공공2020-12-3135.111446129.023512021-04-01 06:20:03
8053704부산광역시강서구명지동3241번지외 3필지 C2,3,4블록엘크루 블루오션(변경전 : 퀸덤2차아파트)영조주택대한리츠민간분양124.7127602006-12-192006-12-282012-06-01준공공공2020-12-3135.111446129.023512021-04-01 06:20:03