Overview

Dataset statistics

Number of variables30
Number of observations7104
Missing cells30863
Missing cells (%)14.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.7 MiB
Average record size in memory255.0 B

Variable types

Text7
Numeric14
Categorical6
Unsupported1
DateTime2

Dataset

Description대구도시개발공사 택지개발 토지 데이터 입니다. 메타데이터기반 공공데이터 개방자료이기 때문에 가공되지 않은 원본 테이블의 데이터가 등록되었습니다.
URLhttps://www.data.go.kr/data/15120628/fileData.do

Alerts

토지구분 has constant value ""Constant
용도구분 is highly imbalanced (58.0%)Imbalance
계약상태 is highly imbalanced (75.4%)Imbalance
등록자번호 is highly imbalanced (54.4%)Imbalance
수정자번호 is highly imbalanced (54.5%)Imbalance
토지 has 80 (1.1%) missing valuesMissing
소재지우편번호 has 5581 (78.6%) missing valuesMissing
소재지상세주소 has 375 (5.3%) missing valuesMissing
소재지_본번 has 765 (10.8%) missing valuesMissing
소재지_부번 has 978 (13.8%) missing valuesMissing
확정면적 has 106 (1.5%) missing valuesMissing
확정단가 has 161 (2.3%) missing valuesMissing
확정금액 has 109 (1.5%) missing valuesMissing
철거이행보증금 has 464 (6.5%) missing valuesMissing
임대보증금 has 464 (6.5%) missing valuesMissing
연간임대료 has 464 (6.5%) missing valuesMissing
첨부파일경로 has 7104 (100.0%) missing valuesMissing
첨부파일 has 7093 (99.8%) missing valuesMissing
파일일련번호 has 7083 (99.7%) missing valuesMissing
당초면적 is highly skewed (γ1 = 26.99082429)Skewed
당초금액 is highly skewed (γ1 = 24.76541808)Skewed
확정금액 is highly skewed (γ1 = 24.62297039)Skewed
철거이행보증금 is highly skewed (γ1 = 64.99623693)Skewed
임대보증금 is highly skewed (γ1 = 65.76623525)Skewed
연간임대료 is highly skewed (γ1 = 45.00202572)Skewed
첨부파일경로 is an unsupported type, check if it needs cleaning or further analysisUnsupported
롯트번호 has 127 (1.8%) zerosZeros
롯트세부번호 has 6858 (96.5%) zerosZeros
당초면적 has 169 (2.4%) zerosZeros
당초단가 has 2260 (31.8%) zerosZeros
당초금액 has 229 (3.2%) zerosZeros
확정면적 has 296 (4.2%) zerosZeros
확정단가 has 2230 (31.4%) zerosZeros
확정금액 has 326 (4.6%) zerosZeros
철거이행보증금 has 6615 (93.1%) zerosZeros
임대보증금 has 6617 (93.1%) zerosZeros
연간임대료 has 6630 (93.3%) zerosZeros
전체면적 has 184 (2.6%) zerosZeros

Reproduction

Analysis started2023-12-12 01:48:30.699242
Analysis finished2023-12-12 01:48:31.679747
Duration0.98 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

토지
Text

MISSING 

Distinct86
Distinct (%)1.2%
Missing80
Missing (%)1.1%
Memory size55.6 KiB
2023-12-12T10:48:31.821536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length4
Mean length5.3109339
Min length3

Characters and Unicode

Total characters37304
Distinct characters165
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

Unique45 ?
Unique (%)0.6%

Sample

1st row성서5차산업단지
2nd row성서5차산업단지
3rd row성서5차산업단지
4th row성서5차산업단지
5th row성서5차산업단지
ValueCountFrequency (%)
시지지구 701
 
10.0%
동서변지구 670
 
9.5%
상인지구 602
 
8.5%
범물지구 595
 
8.4%
지산지구 488
 
6.9%
용산지구 374
 
5.3%
달성2차산업단지 341
 
4.8%
죽곡지구 323
 
4.6%
수성의료지구 320
 
4.5%
장기지구 317
 
4.5%
Other values (78) 2312
32.8%
2023-12-12T10:48:32.180785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 7784
20.9%
구 5605
 
15.0%
산 1986
 
5.3%
단 1333
 
3.6%
성 1305
 
3.5%
업 1034
 
2.8%
차 985
 
2.6%
서 980
 
2.6%
변 863
 
2.3%
2 815
 
2.2%
Other values (155) 14614
39.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 35698
95.7%
Decimal Number 1123
 
3.0%
Open Punctuation 223
 
0.6%
Close Punctuation 223
 
0.6%
Space Separator 23
 
0.1%
Uppercase Letter 12
 
< 0.1%
Other Punctuation 1
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 7784
21.8%
구 5605
15.7%
산 1986
 
5.6%
단 1333
 
3.7%
성 1305
 
3.7%
업 1034
 
2.9%
차 985
 
2.8%
서 980
 
2.7%
변 863
 
2.4%
동 788
 
2.2%
Other values (138) 13035
36.5%
Uppercase Letter
ValueCountFrequency (%)
S 3
25.0%
I 3
25.0%
T 2
16.7%
K 1
 
8.3%
J 1
 
8.3%
B 1
 
8.3%
C 1
 
8.3%
Decimal Number
ValueCountFrequency (%)
2 815
72.6%
5 231
 
20.6%
4 75
 
6.7%
1 1
 
0.1%
3 1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 223
100.0%
Close Punctuation
ValueCountFrequency (%)
) 223
100.0%
Space Separator
ValueCountFrequency (%)
23
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 35698
95.7%
Common 1594
 
4.3%
Latin 12
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 7784
21.8%
구 5605
15.7%
산 1986
 
5.6%
단 1333
 
3.7%
성 1305
 
3.7%
업 1034
 
2.9%
차 985
 
2.8%
서 980
 
2.7%
변 863
 
2.4%
동 788
 
2.2%
Other values (138) 13035
36.5%
Common
ValueCountFrequency (%)
2 815
51.1%
5 231
 
14.5%
( 223
 
14.0%
) 223
 
14.0%
4 75
 
4.7%
23
 
1.4%
, 1
 
0.1%
1 1
 
0.1%
3 1
 
0.1%
- 1
 
0.1%
Latin
ValueCountFrequency (%)
S 3
25.0%
I 3
25.0%
T 2
16.7%
K 1
 
8.3%
J 1
 
8.3%
B 1
 
8.3%
C 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 35698
95.7%
ASCII 1606
 
4.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 7784
21.8%
구 5605
15.7%
산 1986
 
5.6%
단 1333
 
3.7%
성 1305
 
3.7%
업 1034
 
2.9%
차 985
 
2.8%
서 980
 
2.7%
변 863
 
2.4%
동 788
 
2.2%
Other values (138) 13035
36.5%
ASCII
ValueCountFrequency (%)
2 815
50.7%
5 231
 
14.4%
( 223
 
13.9%
) 223
 
13.9%
4 75
 
4.7%
23
 
1.4%
S 3
 
0.2%
I 3
 
0.2%
T 2
 
0.1%
K 1
 
0.1%
Other values (7) 7
 
0.4%

블록번호
Text

Distinct176
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
2023-12-12T10:48:32.498196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length1.8275619
Min length1

Characters and Unicode

Total characters12983
Distinct characters20
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)0.3%

Sample

1st row27
2nd row27
3rd row27
4th row27
5th row27
ValueCountFrequency (%)
0 184
 
2.6%
4 162
 
2.3%
11 160
 
2.3%
10 158
 
2.2%
5 158
 
2.2%
22 151
 
2.1%
8 151
 
2.1%
12 149
 
2.1%
3 147
 
2.1%
23 146
 
2.1%
Other values (166) 5538
78.0%
2023-12-12T10:48:33.039509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2292
17.7%
2 2123
16.4%
3 1788
13.8%
4 1279
9.9%
5 1167
9.0%
6 1079
8.3%
0 815
 
6.3%
7 698
 
5.4%
8 690
 
5.3%
9 683
 
5.3%
Other values (10) 369
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12614
97.2%
Uppercase Letter 369
 
2.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2292
18.2%
2 2123
16.8%
3 1788
14.2%
4 1279
10.1%
5 1167
9.3%
6 1079
8.6%
0 815
 
6.5%
7 698
 
5.5%
8 690
 
5.5%
9 683
 
5.4%
Uppercase Letter
ValueCountFrequency (%)
A 120
32.5%
C 91
24.7%
D 52
14.1%
E 50
13.6%
H 26
 
7.0%
G 13
 
3.5%
B 9
 
2.4%
I 4
 
1.1%
F 3
 
0.8%
M 1
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common 12614
97.2%
Latin 369
 
2.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2292
18.2%
2 2123
16.8%
3 1788
14.2%
4 1279
10.1%
5 1167
9.3%
6 1079
8.6%
0 815
 
6.5%
7 698
 
5.5%
8 690
 
5.5%
9 683
 
5.4%
Latin
ValueCountFrequency (%)
A 120
32.5%
C 91
24.7%
D 52
14.1%
E 50
13.6%
H 26
 
7.0%
G 13
 
3.5%
B 9
 
2.4%
I 4
 
1.1%
F 3
 
0.8%
M 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12983
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2292
17.7%
2 2123
16.4%
3 1788
13.8%
4 1279
9.9%
5 1167
9.0%
6 1079
8.3%
0 815
 
6.3%
7 698
 
5.4%
8 690
 
5.3%
9 683
 
5.3%
Other values (10) 369
 
2.8%

롯트번호
Real number (ℝ)

ZEROS 

Distinct82
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.0149212
Minimum0
Maximum82
Zeros127
Zeros (%)1.8%
Negative0
Negative (%)0.0%
Memory size62.6 KiB
2023-12-12T10:48:33.191768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q13
median6
Q310
95-th percentile17
Maximum82
Range82
Interquartile range (IQR)7

Descriptive statistics

Standard deviation6.642904
Coefficient of variation (CV)0.94696774
Kurtosis35.192871
Mean7.0149212
Median Absolute Deviation (MAD)3
Skewness4.2828092
Sum49834
Variance44.128174
MonotonicityNot monotonic
2023-12-12T10:48:33.335283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 845
11.9%
2 699
9.8%
3 654
 
9.2%
4 618
 
8.7%
5 543
 
7.6%
6 503
 
7.1%
7 467
 
6.6%
8 410
 
5.8%
9 360
 
5.1%
10 331
 
4.7%
Other values (72) 1674
23.6%
ValueCountFrequency (%)
0 127
 
1.8%
1 845
11.9%
2 699
9.8%
3 654
9.2%
4 618
8.7%
5 543
7.6%
6 503
7.1%
7 467
6.6%
8 410
5.8%
9 360
5.1%
ValueCountFrequency (%)
82 2
< 0.1%
81 1
< 0.1%
80 1
< 0.1%
79 1
< 0.1%
78 1
< 0.1%
77 1
< 0.1%
76 1
< 0.1%
75 1
< 0.1%
74 1
< 0.1%
73 1
< 0.1%

롯트세부번호
Real number (ℝ)

ZEROS 

Distinct19
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.090512387
Minimum0
Maximum18
Zeros6858
Zeros (%)96.5%
Negative0
Negative (%)0.0%
Memory size62.6 KiB
2023-12-12T10:48:33.497725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum18
Range18
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.74068437
Coefficient of variation (CV)8.1832376
Kurtosis238.84493
Mean0.090512387
Median Absolute Deviation (MAD)0
Skewness13.902544
Sum643
Variance0.54861334
MonotonicityNot monotonic
2023-12-12T10:48:33.647413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 6858
96.5%
1 133
 
1.9%
2 48
 
0.7%
3 20
 
0.3%
4 11
 
0.2%
5 5
 
0.1%
6 5
 
0.1%
7 5
 
0.1%
9 3
 
< 0.1%
10 3
 
< 0.1%
Other values (9) 13
 
0.2%
ValueCountFrequency (%)
0 6858
96.5%
1 133
 
1.9%
2 48
 
0.7%
3 20
 
0.3%
4 11
 
0.2%
5 5
 
0.1%
6 5
 
0.1%
7 5
 
0.1%
8 3
 
< 0.1%
9 3
 
< 0.1%
ValueCountFrequency (%)
18 1
 
< 0.1%
17 1
 
< 0.1%
16 1
 
< 0.1%
15 1
 
< 0.1%
14 1
 
< 0.1%
13 1
 
< 0.1%
12 2
< 0.1%
11 2
< 0.1%
10 3
< 0.1%
9 3
< 0.1%

토지구분
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
전
7104 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전 7104
100.0%

Length

2023-12-12T10:48:33.804403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:48:33.927923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전 7104
100.0%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct31
Distinct (%)2.0%
Missing5581
Missing (%)78.6%
Infinite0
Infinite (%)0.0%
Mean593386.01
Minimum41065
Maximum711892
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size62.6 KiB
2023-12-12T10:48:34.034893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41065
5-th percentile41065
Q1704180
median711814
Q3711891
95-th percentile711891
Maximum711892
Range670827
Interquartile range (IQR)7711

Descriptive statistics

Standard deviation253468.84
Coefficient of variation (CV)0.42715675
Kurtosis0.96376035
Mean593386.01
Median Absolute Deviation (MAD)77
Skewness-1.7208428
Sum9.037269 × 108
Variance6.4246453 × 1010
MonotonicityNot monotonic
2023-12-12T10:48:34.156156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
711891 452
 
6.4%
711814 231
 
3.3%
41507 175
 
2.5%
711815 168
 
2.4%
704400 98
 
1.4%
41065 89
 
1.3%
706220 49
 
0.7%
711892 45
 
0.6%
701857 41
 
0.6%
704180 37
 
0.5%
Other values (21) 138
 
1.9%
(Missing) 5581
78.6%
ValueCountFrequency (%)
41065 89
1.3%
41213 1
 
< 0.1%
41507 175
2.5%
701010 2
 
< 0.1%
701020 1
 
< 0.1%
701040 6
 
0.1%
701808 5
 
0.1%
701836 2
 
< 0.1%
701848 11
 
0.2%
701856 28
 
0.4%
ValueCountFrequency (%)
711892 45
 
0.6%
711891 452
6.4%
711890 18
 
0.3%
711873 1
 
< 0.1%
711815 168
 
2.4%
711814 231
3.3%
711812 2
 
< 0.1%
706220 49
 
0.7%
706170 1
 
< 0.1%
706130 5
 
0.1%

소재지기본주소
Text

Distinct93
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
2023-12-12T10:48:34.384933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length12
Mean length12.532095
Min length1

Characters and Unicode

Total characters89028
Distinct characters88
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

Unique28 ?
Unique (%)0.4%

Sample

1st row대구광역시 달성군 다사읍세천리
2nd row대구광역시 달성군 다사읍세천리
3rd row대구광역시 달성군 다사읍세천리
4th row대구광역시 달성군 다사읍세천리
5th row대구광역시 달성군 다사읍세천리
ValueCountFrequency (%)
대구광역시 6605
39.8%
달성군 812
 
4.9%
달서구상인동 601
 
3.6%
수성구범물동 593
 
3.6%
수성구지산동 488
 
2.9%
수성구신매동 447
 
2.7%
달성군다사읍 420
 
2.5%
북구서변동 405
 
2.4%
달서구용산동 374
 
2.3%
달성군구지면 350
 
2.1%
Other values (81) 5497
33.1%
2023-12-12T10:48:34.785770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
구 13174
14.8%
9984
11.2%
대 7155
 
8.0%
시 6894
 
7.7%
광 6605
 
7.4%
역 6605
 
7.4%
동 6014
 
6.8%
성 3986
 
4.5%
달 3152
 
3.5%
수 2303
 
2.6%
Other values (78) 23156
26.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 78666
88.4%
Space Separator 9984
 
11.2%
Decimal Number 369
 
0.4%
Dash Punctuation 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 13174
16.7%
대 7155
 
9.1%
시 6894
 
8.8%
광 6605
 
8.4%
역 6605
 
8.4%
동 6014
 
7.6%
성 3986
 
5.1%
달 3152
 
4.0%
수 2303
 
2.9%
서 1982
 
2.5%
Other values (66) 20796
26.4%
Decimal Number
ValueCountFrequency (%)
3 114
30.9%
1 111
30.1%
0 107
29.0%
2 11
 
3.0%
9 10
 
2.7%
7 5
 
1.4%
6 4
 
1.1%
5 3
 
0.8%
8 2
 
0.5%
4 2
 
0.5%
Space Separator
ValueCountFrequency (%)
9984
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 78666
88.4%
Common 10362
 
11.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 13174
16.7%
대 7155
 
9.1%
시 6894
 
8.8%
광 6605
 
8.4%
역 6605
 
8.4%
동 6014
 
7.6%
성 3986
 
5.1%
달 3152
 
4.0%
수 2303
 
2.9%
서 1982
 
2.5%
Other values (66) 20796
26.4%
Common
ValueCountFrequency (%)
9984
96.4%
3 114
 
1.1%
1 111
 
1.1%
0 107
 
1.0%
2 11
 
0.1%
9 10
 
0.1%
- 9
 
0.1%
7 5
 
< 0.1%
6 4
 
< 0.1%
5 3
 
< 0.1%
Other values (2) 4
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 78666
88.4%
ASCII 10362
 
11.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
구 13174
16.7%
대 7155
 
9.1%
시 6894
 
8.8%
광 6605
 
8.4%
역 6605
 
8.4%
동 6014
 
7.6%
성 3986
 
5.1%
달 3152
 
4.0%
수 2303
 
2.9%
서 1982
 
2.5%
Other values (66) 20796
26.4%
ASCII
ValueCountFrequency (%)
9984
96.4%
3 114
 
1.1%
1 111
 
1.1%
0 107
 
1.0%
2 11
 
0.1%
9 10
 
0.1%
- 9
 
0.1%
7 5
 
< 0.1%
6 4
 
< 0.1%
5 3
 
< 0.1%
Other values (2) 4
 
< 0.1%

소재지상세주소
Text

MISSING 

Distinct5854
Distinct (%)87.0%
Missing375
Missing (%)5.3%
Memory size55.6 KiB
2023-12-12T10:48:35.239780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length6
Mean length5.7247734
Min length1

Characters and Unicode

Total characters38522
Distinct characters34
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

Unique5127 ?
Unique (%)76.2%

Sample

1st row1686-1
2nd row1686-2
3rd row1686-3
4th row1686-4
5th row1686-5
ValueCountFrequency (%)
외 34
 
0.5%
1필지 29
 
0.4%
1548-3 20
 
0.3%
1275-0 8
 
0.1%
1526-1 6
 
0.1%
814-1 6
 
0.1%
1277-4 6
 
0.1%
1547-8 5
 
0.1%
921-8 5
 
0.1%
567-24 4
 
0.1%
Other values (5848) 6644
98.2%
2023-12-12T10:48:35.837657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 7487
19.4%
- 6270
16.3%
5 3439
8.9%
2 3399
8.8%
3 3030
7.9%
8 2753
 
7.1%
7 2668
 
6.9%
4 2509
 
6.5%
6 2499
 
6.5%
9 2295
 
6.0%
Other values (24) 2173
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 32073
83.3%
Dash Punctuation 6270
 
16.3%
Other Letter 129
 
0.3%
Space Separator 40
 
0.1%
Other Punctuation 4
 
< 0.1%
Open Punctuation 3
 
< 0.1%
Close Punctuation 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
외 40
31.0%
필 34
26.4%
지 34
26.4%
동 4
 
3.1%
사 3
 
2.3%
산 1
 
0.8%
시 1
 
0.8%
신 1
 
0.8%
옥 1
 
0.8%
공 1
 
0.8%
Other values (9) 9
 
7.0%
Decimal Number
ValueCountFrequency (%)
1 7487
23.3%
5 3439
10.7%
2 3399
10.6%
3 3030
9.4%
8 2753
 
8.6%
7 2668
 
8.3%
4 2509
 
7.8%
6 2499
 
7.8%
9 2295
 
7.2%
0 1994
 
6.2%
Dash Punctuation
ValueCountFrequency (%)
- 6270
100.0%
Space Separator
ValueCountFrequency (%)
40
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 38393
99.7%
Hangul 129
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
외 40
31.0%
필 34
26.4%
지 34
26.4%
동 4
 
3.1%
사 3
 
2.3%
산 1
 
0.8%
시 1
 
0.8%
신 1
 
0.8%
옥 1
 
0.8%
공 1
 
0.8%
Other values (9) 9
 
7.0%
Common
ValueCountFrequency (%)
1 7487
19.5%
- 6270
16.3%
5 3439
9.0%
2 3399
8.9%
3 3030
7.9%
8 2753
 
7.2%
7 2668
 
6.9%
4 2509
 
6.5%
6 2499
 
6.5%
9 2295
 
6.0%
Other values (5) 2044
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 38393
99.7%
Hangul 129
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 7487
19.5%
- 6270
16.3%
5 3439
9.0%
2 3399
8.9%
3 3030
7.9%
8 2753
 
7.2%
7 2668
 
6.9%
4 2509
 
6.5%
6 2499
 
6.5%
9 2295
 
6.0%
Other values (5) 2044
 
5.3%
Hangul
ValueCountFrequency (%)
외 40
31.0%
필 34
26.4%
지 34
26.4%
동 4
 
3.1%
사 3
 
2.3%
산 1
 
0.8%
시 1
 
0.8%
신 1
 
0.8%
옥 1
 
0.8%
공 1
 
0.8%
Other values (9) 9
 
7.0%

소재지_본번
Text

MISSING 

Distinct647
Distinct (%)10.2%
Missing765
Missing (%)10.8%
Memory size55.6 KiB
2023-12-12T10:48:36.310838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length3.5565547
Min length1

Characters and Unicode

Total characters22545
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique149 ?
Unique (%)2.4%

Sample

1st row1686
2nd row1686
3rd row1686
4th row1686
5th row1686
ValueCountFrequency (%)
756 68
 
1.1%
842 49
 
0.8%
1547 42
 
0.7%
947 40
 
0.6%
1533 38
 
0.6%
1262 38
 
0.6%
1343 38
 
0.6%
1277 37
 
0.6%
1338 34
 
0.5%
945 33
 
0.5%
Other values (637) 5922
93.4%
2023-12-12T10:48:37.275160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 4676
20.7%
5 2739
12.1%
2 2260
10.0%
8 2242
9.9%
3 2122
9.4%
7 2098
9.3%
6 1908
8.5%
9 1829
 
8.1%
4 1532
 
6.8%
0 1138
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 22544
> 99.9%
Other Letter 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 4676
20.7%
5 2739
12.1%
2 2260
10.0%
8 2242
9.9%
3 2122
9.4%
7 2098
9.3%
6 1908
8.5%
9 1829
 
8.1%
4 1532
 
6.8%
0 1138
 
5.0%
Other Letter
ValueCountFrequency (%)
층 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 22544
> 99.9%
Hangul 1
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 4676
20.7%
5 2739
12.1%
2 2260
10.0%
8 2242
9.9%
3 2122
9.4%
7 2098
9.3%
6 1908
8.5%
9 1829
 
8.1%
4 1532
 
6.8%
0 1138
 
5.0%
Hangul
ValueCountFrequency (%)
층 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22544
> 99.9%
Hangul 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 4676
20.7%
5 2739
12.1%
2 2260
10.0%
8 2242
9.9%
3 2122
9.4%
7 2098
9.3%
6 1908
8.5%
9 1829
 
8.1%
4 1532
 
6.8%
0 1138
 
5.0%
Hangul
ValueCountFrequency (%)
층 1
100.0%

소재지_부번
Text

MISSING 

Distinct159
Distinct (%)2.6%
Missing978
Missing (%)13.8%
Memory size55.6 KiB
2023-12-12T10:48:37.662773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.291381
Min length1

Characters and Unicode

Total characters7911
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique112 ?
Unique (%)1.8%

Sample

1st row1
2nd row2
3rd row3
4th row4
5th row5
ValueCountFrequency (%)
1 561
 
9.2%
2 537
 
8.8%
3 521
 
8.5%
4 479
 
7.8%
0 476
 
7.8%
5 430
 
7.0%
6 413
 
6.7%
7 368
 
6.0%
8 332
 
5.4%
9 299
 
4.9%
Other values (149) 1710
27.9%
2023-12-12T10:48:38.223563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2289
28.9%
2 904
 
11.4%
0 801
 
10.1%
3 774
 
9.8%
4 737
 
9.3%
5 605
 
7.6%
6 529
 
6.7%
7 479
 
6.1%
8 412
 
5.2%
9 374
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7904
99.9%
Other Letter 7
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2289
29.0%
2 904
 
11.4%
0 801
 
10.1%
3 774
 
9.8%
4 737
 
9.3%
5 605
 
7.7%
6 529
 
6.7%
7 479
 
6.1%
8 412
 
5.2%
9 374
 
4.7%
Other Letter
ValueCountFrequency (%)
외 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7904
99.9%
Hangul 7
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2289
29.0%
2 904
 
11.4%
0 801
 
10.1%
3 774
 
9.8%
4 737
 
9.3%
5 605
 
7.7%
6 529
 
6.7%
7 479
 
6.1%
8 412
 
5.2%
9 374
 
4.7%
Hangul
ValueCountFrequency (%)
외 7
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7904
99.9%
Hangul 7
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2289
29.0%
2 904
 
11.4%
0 801
 
10.1%
3 774
 
9.8%
4 737
 
9.3%
5 605
 
7.7%
6 529
 
6.7%
7 479
 
6.1%
8 412
 
5.2%
9 374
 
4.7%
Hangul
ValueCountFrequency (%)
외 7
100.0%

용도구분
Categorical

IMBALANCE 

Distinct42
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
단독주택지
4382 
산업시설용지
646 
상업용지
587 
근린생활시설
 
430
공동주택지
 
163
Other values (37)
896 

Length

Max length16
Median length5
Mean length5.1014921
Min length2

Unique

Unique9 ?
Unique (%)0.1%

Sample

1st row공공.후생복지시설
2nd row공공.후생복지시설
3rd row공공.후생복지시설
4th row공공.후생복지시설
5th row공공.후생복지시설

Common Values

ValueCountFrequency (%)
단독주택지 4382
61.7%
산업시설용지 646
 
9.1%
상업용지 587
 
8.3%
근린생활시설 430
 
6.1%
공동주택지 163
 
2.3%
준주거지역 150
 
2.1%
공공.후생복지시설 118
 
1.7%
공공용지 105
 
1.5%
지원시설용지 104
 
1.5%
<NA> 81
 
1.1%
Other values (32) 338
 
4.8%

Length

2023-12-12T10:48:38.471155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
단독주택지 4382
61.7%
산업시설용지 646
 
9.1%
상업용지 587
 
8.3%
근린생활시설 430
 
6.1%
공동주택지 163
 
2.3%
준주거지역 150
 
2.1%
공공.후생복지시설 118
 
1.7%
공공용지 105
 
1.5%
지원시설용지 104
 
1.5%
na 81
 
1.1%
Other values (32) 338
 
4.8%

당초면적
Real number (ℝ)

SKEWED  ZEROS 

Distinct2310
Distinct (%)32.6%
Missing11
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean1533.5061
Minimum0
Maximum376800
Zeros169
Zeros (%)2.4%
Negative0
Negative (%)0.0%
Memory size62.6 KiB
2023-12-12T10:48:38.656541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile165
Q1196.12
median226
Q3439
95-th percentile7823.16
Maximum376800
Range376800
Interquartile range (IQR)242.88

Descriptive statistics

Standard deviation8106.5088
Coefficient of variation (CV)5.2862579
Kurtosis1076.7675
Mean1533.5061
Median Absolute Deviation (MAD)44
Skewness26.990824
Sum10877159
Variance65715484
MonotonicityNot monotonic
2023-12-12T10:48:38.834469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
200.0 180
 
2.5%
0.0 169
 
2.4%
196.0 83
 
1.2%
210.0 72
 
1.0%
198.0 70
 
1.0%
197.0 68
 
1.0%
203.0 65
 
0.9%
220.0 64
 
0.9%
215.0 63
 
0.9%
187.0 61
 
0.9%
Other values (2300) 6198
87.2%
ValueCountFrequency (%)
0.0 169
2.4%
0.7 1
 
< 0.1%
0.8 1
 
< 0.1%
1.5 1
 
< 0.1%
1.68 1
 
< 0.1%
2.0 1
 
< 0.1%
3.0 2
 
< 0.1%
4.0 3
 
< 0.1%
5.0 1
 
< 0.1%
6.0 1
 
< 0.1%
ValueCountFrequency (%)
376800.0 1
< 0.1%
332983.0 1
< 0.1%
145209.0 1
< 0.1%
110719.0 1
< 0.1%
104187.5 1
< 0.1%
102316.0 1
< 0.1%
94720.2 1
< 0.1%
81175.0 1
< 0.1%
78800.7 1
< 0.1%
77049.0 1
< 0.1%

당초단가
Real number (ℝ)

ZEROS 

Distinct1580
Distinct (%)22.3%
Missing16
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean535633.19
Minimum0
Maximum14364000
Zeros2260
Zeros (%)31.8%
Negative0
Negative (%)0.0%
Memory size62.6 KiB
2023-12-12T10:48:39.041456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median401670
Q3587125
95-th percentile2135819.4
Maximum14364000
Range14364000
Interquartile range (IQR)587125

Descriptive statistics

Standard deviation790272.05
Coefficient of variation (CV)1.4753978
Kurtosis28.031271
Mean535633.19
Median Absolute Deviation (MAD)336170
Skewness3.9256476
Sum3.7965681 × 109
Variance6.2452991 × 1011
MonotonicityNot monotonic
2023-12-12T10:48:39.243820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 2260
31.8%
292500.0 97
 
1.4%
98000.0 85
 
1.2%
401670.0 80
 
1.1%
371920.0 66
 
0.9%
450000.0 61
 
0.9%
602500.0 60
 
0.8%
526400.0 58
 
0.8%
392000.0 53
 
0.7%
511500.0 49
 
0.7%
Other values (1570) 4219
59.4%
ValueCountFrequency (%)
0.0 2260
31.8%
59371.8 2
 
< 0.1%
64000.0 1
 
< 0.1%
64500.0 2
 
< 0.1%
65000.0 3
 
< 0.1%
65500.0 8
 
0.1%
66000.0 6
 
0.1%
66500.0 2
 
< 0.1%
94000.0 4
 
0.1%
95000.0 2
 
< 0.1%
ValueCountFrequency (%)
14364000.0 1
< 0.1%
9331109.0 1
< 0.1%
8359456.63 1
< 0.1%
7869960.0 1
< 0.1%
6912212.16 1
< 0.1%
6817187.5 1
< 0.1%
6655077.79 1
< 0.1%
6405420.0 1
< 0.1%
6298500.0 1
< 0.1%
6153387.097 1
< 0.1%

당초금액
Real number (ℝ)

SKEWED  ZEROS 

Distinct4596
Distinct (%)64.8%
Missing8
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean7.8875962 × 108
Minimum0
Maximum1.8252064 × 1011
Zeros229
Zeros (%)3.2%
Negative0
Negative (%)0.0%
Memory size62.6 KiB
2023-12-12T10:48:39.448400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile30175130
Q173926600
median1.1326625 × 108
Q34.00208 × 108
95-th percentile2.872015 × 109
Maximum1.8252064 × 1011
Range1.8252064 × 1011
Interquartile range (IQR)3.262814 × 108

Descriptive statistics

Standard deviation4.9098209 × 109
Coefficient of variation (CV)6.2247366
Kurtosis723.78406
Mean7.8875962 × 108
Median Absolute Deviation (MAD)70016200
Skewness24.765418
Sum5.5970383 × 1012
Variance2.4106341 × 1019
MonotonicityNot monotonic
2023-12-12T10:48:39.663297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 229
 
3.2%
36069490 28
 
0.4%
32851500 27
 
0.4%
52065000 22
 
0.3%
73268240 21
 
0.3%
45302470 19
 
0.3%
37943480 18
 
0.3%
87500000 18
 
0.3%
27102480 18
 
0.3%
136143980 16
 
0.2%
Other values (4586) 6680
94.0%
ValueCountFrequency (%)
0 229
3.2%
64500 1
 
< 0.1%
380400 1
 
< 0.1%
434000 1
 
< 0.1%
713250 1
 
< 0.1%
1559250 1
 
< 0.1%
1762000 1
 
< 0.1%
2614500 1
 
< 0.1%
2682500 1
 
< 0.1%
2756250 1
 
< 0.1%
ValueCountFrequency (%)
182520639000 1
< 0.1%
151225712000 1
< 0.1%
146015500000 1
< 0.1%
128150000000 1
< 0.1%
125591000000 1
< 0.1%
124288560000 1
< 0.1%
115200000000 1
< 0.1%
54010000000 1
< 0.1%
51264000000 1
< 0.1%
44592391000 1
< 0.1%

확정면적
Real number (ℝ)

MISSING  ZEROS 

Distinct2952
Distinct (%)42.2%
Missing106
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean1388.8104
Minimum0
Maximum145168
Zeros296
Zeros (%)4.2%
Negative0
Negative (%)0.0%
Memory size62.6 KiB
2023-12-12T10:48:39.870407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile49.6
Q1194
median220.85
Q3399.95
95-th percentile7843.335
Maximum145168
Range145168
Interquartile range (IQR)205.95

Descriptive statistics

Standard deviation5321.1677
Coefficient of variation (CV)3.8314572
Kurtosis183.47707
Mean1388.8104
Median Absolute Deviation (MAD)41.25
Skewness10.899982
Sum9718895.5
Variance28314826
MonotonicityNot monotonic
2023-12-12T10:48:40.081805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 296
 
4.2%
200.1 29
 
0.4%
178.9 27
 
0.4%
178.3 17
 
0.2%
200.0 17
 
0.2%
188.9 16
 
0.2%
202.9 16
 
0.2%
229.3 15
 
0.2%
199.6 15
 
0.2%
187.8 15
 
0.2%
Other values (2942) 6535
92.0%
(Missing) 106
 
1.5%
ValueCountFrequency (%)
0.0 296
4.2%
1.68 1
 
< 0.1%
2.0 1
 
< 0.1%
3.0 2
 
< 0.1%
4.0 2
 
< 0.1%
6.0 1
 
< 0.1%
11.0 1
 
< 0.1%
11.2 1
 
< 0.1%
12.0 2
 
< 0.1%
13.0 3
 
< 0.1%
ValueCountFrequency (%)
145168.0 1
< 0.1%
110401.2 1
< 0.1%
104187.5 1
< 0.1%
102511.3 1
< 0.1%
81175.0 1
< 0.1%
78800.7 1
< 0.1%
77049.1 1
< 0.1%
65243.4 1
< 0.1%
62727.4 1
< 0.1%
60847.0 1
< 0.1%

확정단가
Real number (ℝ)

MISSING  ZEROS 

Distinct1480
Distinct (%)21.3%
Missing161
Missing (%)2.3%
Infinite0
Infinite (%)0.0%
Mean520633.51
Minimum0
Maximum14364000
Zeros2230
Zeros (%)31.4%
Negative0
Negative (%)0.0%
Memory size62.6 KiB
2023-12-12T10:48:40.249058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median421000
Q3602500
95-th percentile1859200.6
Maximum14364000
Range14364000
Interquartile range (IQR)602500

Descriptive statistics

Standard deviation756902.98
Coefficient of variation (CV)1.4538115
Kurtosis33.956778
Mean520633.51
Median Absolute Deviation (MAD)326000
Skewness4.285678
Sum3.6147584 × 109
Variance5.7290213 × 1011
MonotonicityNot monotonic
2023-12-12T10:48:40.413229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 2230
31.4%
292500.0 97
 
1.4%
98000.0 85
 
1.2%
401670.0 80
 
1.1%
371920.0 66
 
0.9%
450000.0 61
 
0.9%
602500.0 60
 
0.8%
526400.0 58
 
0.8%
392000.0 53
 
0.7%
511500.0 49
 
0.7%
Other values (1470) 4104
57.8%
(Missing) 161
 
2.3%
ValueCountFrequency (%)
0.0 2230
31.4%
64000.0 1
 
< 0.1%
64500.0 2
 
< 0.1%
65000.0 3
 
< 0.1%
65500.0 8
 
0.1%
66000.0 6
 
0.1%
66500.0 2
 
< 0.1%
94000.0 4
 
0.1%
95000.0 2
 
< 0.1%
96000.0 10
 
0.1%
ValueCountFrequency (%)
14364000.0 1
< 0.1%
9331109.0 1
< 0.1%
8359456.635 1
< 0.1%
7869960.0 1
< 0.1%
7489663.462 1
< 0.1%
6912212.168 1
< 0.1%
6817187.5 1
< 0.1%
6655077.793 1
< 0.1%
6405420.0 1
< 0.1%
6298500.0 1
< 0.1%

확정금액
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct5643
Distinct (%)80.7%
Missing109
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean6.6191048 × 108
Minimum0
Maximum1.2811457 × 1011
Zeros326
Zeros (%)4.6%
Negative0
Negative (%)0.0%
Memory size62.6 KiB
2023-12-12T10:48:40.615368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile16386920
Q171189245
median1.0939735 × 108
Q33.51241 × 108
95-th percentile2.7000222 × 109
Maximum1.2811457 × 1011
Range1.2811457 × 1011
Interquartile range (IQR)2.8005176 × 108

Descriptive statistics

Standard deviation3.3535182 × 109
Coefficient of variation (CV)5.0664227
Kurtosis809.85162
Mean6.6191048 × 108
Median Absolute Deviation (MAD)65733650
Skewness24.62297
Sum4.6300638 × 1012
Variance1.1246085 × 1019
MonotonicityNot monotonic
2023-12-12T10:48:40.825063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 326
 
4.6%
45077210 11
 
0.2%
91239000 9
 
0.1%
45063130 8
 
0.1%
52152750 7
 
0.1%
63254070 7
 
0.1%
27135330 6
 
0.1%
64596270 6
 
0.1%
52035750 6
 
0.1%
34958100 6
 
0.1%
Other values (5633) 6603
92.9%
(Missing) 109
 
1.5%
ValueCountFrequency (%)
0 326
4.6%
1559250 1
 
< 0.1%
1906600 1
 
< 0.1%
2614500 1
 
< 0.1%
2756250 1
 
< 0.1%
2981390 1
 
< 0.1%
3117860 1
 
< 0.1%
4220000 1
 
< 0.1%
5038000 1
 
< 0.1%
6737500 1
 
< 0.1%
ValueCountFrequency (%)
128114569900 1
< 0.1%
125591163000 1
< 0.1%
115200000000 1
< 0.1%
54091895040 1
< 0.1%
51265212280 1
< 0.1%
44464304100 1
< 0.1%
43770995000 1
< 0.1%
42394738000 1
< 0.1%
42015973650 1
< 0.1%
41462811000 1
< 0.1%

철거이행보증금
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct21
Distinct (%)0.3%
Missing464
Missing (%)6.5%
Infinite0
Infinite (%)0.0%
Mean241830.16
Minimum0
Maximum6.18 × 108
Zeros6615
Zeros (%)93.1%
Negative0
Negative (%)0.0%
Memory size62.6 KiB
2023-12-12T10:48:40.984355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum6.18 × 108
Range6.18 × 108
Interquartile range (IQR)0

Descriptive statistics

Standard deviation8260142.5
Coefficient of variation (CV)34.156792
Kurtosis4742.1757
Mean241830.16
Median Absolute Deviation (MAD)0
Skewness64.996237
Sum1.6057523 × 109
Variance6.8229954 × 1013
MonotonicityNot monotonic
2023-12-12T10:48:41.132402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 6615
93.1%
27459540 2
 
< 0.1%
29463690 2
 
< 0.1%
21733380 2
 
< 0.1%
22384080 2
 
< 0.1%
27368440 2
 
< 0.1%
26991030 1
 
< 0.1%
22045710 1
 
< 0.1%
97631020 1
 
< 0.1%
148697960 1
 
< 0.1%
Other values (11) 11
 
0.2%
(Missing) 464
 
6.5%
ValueCountFrequency (%)
0 6615
93.1%
1800000 1
 
< 0.1%
21733380 2
 
< 0.1%
22045710 1
 
< 0.1%
22057420 1
 
< 0.1%
22058730 1
 
< 0.1%
22384080 2
 
< 0.1%
26665680 1
 
< 0.1%
26965000 1
 
< 0.1%
26991030 1
 
< 0.1%
ValueCountFrequency (%)
618000000 1
< 0.1%
148697960 1
< 0.1%
110111450 1
< 0.1%
109760070 1
< 0.1%
97631020 1
< 0.1%
62000000 1
< 0.1%
29463690 2
< 0.1%
27459540 2
< 0.1%
27368440 2
< 0.1%
27125080 1
< 0.1%

임대보증금
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct19
Distinct (%)0.3%
Missing464
Missing (%)6.5%
Infinite0
Infinite (%)0.0%
Mean116110.86
Minimum0
Maximum3.09 × 108
Zeros6617
Zeros (%)93.1%
Negative0
Negative (%)0.0%
Memory size62.6 KiB
2023-12-12T10:48:41.338178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum3.09 × 108
Range3.09 × 108
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4112633.5
Coefficient of variation (CV)35.419887
Kurtosis4822.9963
Mean116110.86
Median Absolute Deviation (MAD)0
Skewness65.766235
Sum7.709761 × 108
Variance1.6913754 × 1013
MonotonicityNot monotonic
2023-12-12T10:48:41.478385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 6617
93.1%
14731840 2
 
< 0.1%
13684220 2
 
< 0.1%
11192040 2
 
< 0.1%
10866690 2
 
< 0.1%
13729770 2
 
< 0.1%
13512430 1
 
< 0.1%
54880030 1
 
< 0.1%
55055720 1
 
< 0.1%
309000000 1
 
< 0.1%
Other values (9) 9
 
0.1%
(Missing) 464
 
6.5%
ValueCountFrequency (%)
0 6617
93.1%
10866690 2
 
< 0.1%
11022850 1
 
< 0.1%
11028710 1
 
< 0.1%
11029360 1
 
< 0.1%
11192040 2
 
< 0.1%
13332840 1
 
< 0.1%
13482500 1
 
< 0.1%
13495510 1
 
< 0.1%
13512430 1
 
< 0.1%
ValueCountFrequency (%)
309000000 1
< 0.1%
74348980 1
< 0.1%
55055720 1
< 0.1%
54880030 1
< 0.1%
48815510 1
< 0.1%
14731840 2
< 0.1%
13729770 2
< 0.1%
13684220 2
< 0.1%
13562540 1
< 0.1%
13512430 1
< 0.1%

연간임대료
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct10
Distinct (%)0.2%
Missing464
Missing (%)6.5%
Infinite0
Infinite (%)0.0%
Mean21501.312
Minimum0
Maximum42487500
Zeros6630
Zeros (%)93.3%
Negative0
Negative (%)0.0%
Memory size62.6 KiB
2023-12-12T10:48:41.645000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum42487500
Range42487500
Interquartile range (IQR)0

Descriptive statistics

Standard deviation737545.85
Coefficient of variation (CV)34.302365
Kurtosis2257.177
Mean21501.312
Median Absolute Deviation (MAD)0
Skewness45.002026
Sum1.4276871 × 108
Variance5.4397389 × 1011
MonotonicityNot monotonic
2023-12-12T10:48:41.779624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 6630
93.3%
6856060 2
 
< 0.1%
16825810 1
 
< 0.1%
2456850 1
 
< 0.1%
31583750 1
 
< 0.1%
17969600 1
 
< 0.1%
42487500 1
 
< 0.1%
5132650 1
 
< 0.1%
6288550 1
 
< 0.1%
6311880 1
 
< 0.1%
(Missing) 464
 
6.5%
ValueCountFrequency (%)
0 6630
93.3%
2456850 1
 
< 0.1%
5132650 1
 
< 0.1%
6288550 1
 
< 0.1%
6311880 1
 
< 0.1%
6856060 2
 
< 0.1%
16825810 1
 
< 0.1%
17969600 1
 
< 0.1%
31583750 1
 
< 0.1%
42487500 1
 
< 0.1%
ValueCountFrequency (%)
42487500 1
 
< 0.1%
31583750 1
 
< 0.1%
17969600 1
 
< 0.1%
16825810 1
 
< 0.1%
6856060 2
 
< 0.1%
6311880 1
 
< 0.1%
6288550 1
 
< 0.1%
5132650 1
 
< 0.1%
2456850 1
 
< 0.1%
0 6630
93.3%

첨부파일경로
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7104
Missing (%)100.0%
Memory size62.6 KiB

첨부파일
Text

MISSING 

Distinct11
Distinct (%)100.0%
Missing7093
Missing (%)99.8%
Memory size55.6 KiB
2023-12-12T10:48:42.005269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length19
Mean length19.090909
Min length18

Characters and Unicode

Total characters210
Distinct characters31
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)100.0%

Sample

1st row00407_신매동 276-1.hwp
2nd row00408_신매동 276-8.hwp
3rd row00303_상인동214-6.hwp
4th row003023_상인동214-6.hwp
5th row003030_도원동 1367.hwp
ValueCountFrequency (%)
00407_신매동 1
 
5.6%
276-1.hwp 1
 
5.6%
00701_감삼동 1
 
5.6%
1196-80.hwp 1
 
5.6%
09212_신암동 1
 
5.6%
187-10.hwp 1
 
5.6%
13410_신천동 1
 
5.6%
00108_지산동1238-3.hwp 1
 
5.6%
00101_지산동480-3.hwp 1
 
5.6%
320-1.hwp 1
 
5.6%
Other values (8) 8
44.4%
2023-12-12T10:48:42.452814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 34
16.2%
1 17
 
8.1%
3 12
 
5.7%
w 11
 
5.2%
h 11
 
5.2%
. 11
 
5.2%
p 11
 
5.2%
동 11
 
5.2%
_ 11
 
5.2%
- 10
 
4.8%
Other values (21) 71
33.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 105
50.0%
Lowercase Letter 33
 
15.7%
Other Letter 33
 
15.7%
Other Punctuation 11
 
5.2%
Connector Punctuation 11
 
5.2%
Dash Punctuation 10
 
4.8%
Space Separator 7
 
3.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 11
33.3%
신 4
 
12.1%
지 3
 
9.1%
산 2
 
6.1%
인 2
 
6.1%
상 2
 
6.1%
매 2
 
6.1%
원 1
 
3.0%
시 1
 
3.0%
도 1
 
3.0%
Other values (4) 4
 
12.1%
Decimal Number
ValueCountFrequency (%)
0 34
32.4%
1 17
16.2%
3 12
 
11.4%
2 10
 
9.5%
8 9
 
8.6%
4 7
 
6.7%
6 6
 
5.7%
7 6
 
5.7%
5 2
 
1.9%
9 2
 
1.9%
Lowercase Letter
ValueCountFrequency (%)
w 11
33.3%
h 11
33.3%
p 11
33.3%
Other Punctuation
ValueCountFrequency (%)
. 11
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 11
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 144
68.6%
Latin 33
 
15.7%
Hangul 33
 
15.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 34
23.6%
1 17
11.8%
3 12
 
8.3%
. 11
 
7.6%
_ 11
 
7.6%
- 10
 
6.9%
2 10
 
6.9%
8 9
 
6.2%
7
 
4.9%
4 7
 
4.9%
Other values (4) 16
11.1%
Hangul
ValueCountFrequency (%)
동 11
33.3%
신 4
 
12.1%
지 3
 
9.1%
산 2
 
6.1%
인 2
 
6.1%
상 2
 
6.1%
매 2
 
6.1%
원 1
 
3.0%
시 1
 
3.0%
도 1
 
3.0%
Other values (4) 4
 
12.1%
Latin
ValueCountFrequency (%)
w 11
33.3%
h 11
33.3%
p 11
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 177
84.3%
Hangul 33
 
15.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 34
19.2%
1 17
9.6%
3 12
 
6.8%
w 11
 
6.2%
h 11
 
6.2%
. 11
 
6.2%
p 11
 
6.2%
_ 11
 
6.2%
- 10
 
5.6%
2 10
 
5.6%
Other values (7) 39
22.0%
Hangul
ValueCountFrequency (%)
동 11
33.3%
신 4
 
12.1%
지 3
 
9.1%
산 2
 
6.1%
인 2
 
6.1%
상 2
 
6.1%
매 2
 
6.1%
원 1
 
3.0%
시 1
 
3.0%
도 1
 
3.0%
Other values (4) 4
 
12.1%

공급코드
Categorical

Distinct20
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
특별공급
2719 
수의계약
1289 
일반공급
803 
입찰공급
763 
추첨공급
484 
Other values (15)
1046 

Length

Max length11
Median length4
Mean length4.3620495
Min length4

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row수의계약(토지리턴제)
2nd row입찰공급
3rd row수의계약
4th row수의계약(토지리턴제)
5th row수의계약(토지리턴제)

Common Values

ValueCountFrequency (%)
특별공급 2719
38.3%
수의계약 1289
18.1%
일반공급 803
 
11.3%
입찰공급 763
 
10.7%
추첨공급 484
 
6.8%
공급준비 245
 
3.4%
이주자택지공급 205
 
2.9%
수의계약(토지리턴제) 202
 
2.8%
협동화단지 118
 
1.7%
우선공급 97
 
1.4%
Other values (10) 179
 
2.5%

Length

2023-12-12T10:48:42.648214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
특별공급 2719
38.3%
수의계약 1289
18.1%
일반공급 803
 
11.3%
입찰공급 763
 
10.7%
추첨공급 484
 
6.8%
공급준비 245
 
3.4%
이주자택지공급 205
 
2.9%
수의계약(토지리턴제 202
 
2.8%
협동화단지 118
 
1.7%
우선공급 97
 
1.4%
Other values (10) 179
 
2.5%

계약상태
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
분양계약
6616 
<NA>
 
448
임대계약
 
40

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
분양계약 6616
93.1%
<NA> 448
 
6.3%
임대계약 40
 
0.6%

Length

2023-12-12T10:48:42.778301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:48:42.907706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
분양계약 6616
93.1%
na 448
 
6.3%
임대계약 40
 
0.6%

전체면적
Real number (ℝ)

ZEROS 

Distinct2973
Distinct (%)41.9%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean1446.7031
Minimum0
Maximum145209
Zeros184
Zeros (%)2.6%
Negative0
Negative (%)0.0%
Memory size62.6 KiB
2023-12-12T10:48:43.078606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile164.95
Q1195.65
median225.2
Q3445
95-th percentile7608.91
Maximum145209
Range145209
Interquartile range (IQR)249.35

Descriptive statistics

Standard deviation5504.7742
Coefficient of variation (CV)3.8050475
Kurtosis172.68281
Mean1446.7031
Median Absolute Deviation (MAD)44
Skewness10.743802
Sum10275932
Variance30302539
MonotonicityNot monotonic
2023-12-12T10:48:43.308564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 184
 
2.6%
200.1 29
 
0.4%
178.9 27
 
0.4%
249.0 24
 
0.3%
248.0 21
 
0.3%
570.0 19
 
0.3%
263.0 19
 
0.3%
264.0 18
 
0.3%
200.0 17
 
0.2%
236.0 17
 
0.2%
Other values (2963) 6728
94.7%
ValueCountFrequency (%)
0.0 184
2.6%
0.7 1
 
< 0.1%
0.8 1
 
< 0.1%
1.5 1
 
< 0.1%
1.68 1
 
< 0.1%
3.0 2
 
< 0.1%
4.0 3
 
< 0.1%
5.0 1
 
< 0.1%
6.0 1
 
< 0.1%
9.1 1
 
< 0.1%
ValueCountFrequency (%)
145209.0 1
< 0.1%
110401.2 1
< 0.1%
104187.5 1
< 0.1%
102511.3 1
< 0.1%
94720.2 1
< 0.1%
81175.0 1
< 0.1%
78800.7 1
< 0.1%
77049.0 1
< 0.1%
65243.4 1
< 0.1%
63485.0 1
< 0.1%

등록자번호
Categorical

IMBALANCE 

Distinct30
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
admin
4590 
19880040
757 
20070203
 
231
19940148
 
223
20050190
 
164
Other values (25)
1139 

Length

Max length8
Median length5
Mean length6.0188626
Min length4

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row19880040
2nd row19880040
3rd row19880040
4th row19880040
5th row19880040

Common Values

ValueCountFrequency (%)
admin 4590
64.6%
19880040 757
 
10.7%
20070203 231
 
3.3%
19940148 223
 
3.1%
20050190 164
 
2.3%
20070207 137
 
1.9%
19990165 121
 
1.7%
20150234 118
 
1.7%
20040172 105
 
1.5%
20160240 99
 
1.4%
Other values (20) 559
 
7.9%

Length

2023-12-12T10:48:43.488705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
admin 4590
64.6%
19880040 757
 
10.7%
20070203 231
 
3.3%
19940148 223
 
3.1%
20050190 164
 
2.3%
20070207 137
 
1.9%
19990165 121
 
1.7%
20150234 118
 
1.7%
20040172 105
 
1.5%
20160240 99
 
1.4%
Other values (20) 559
 
7.9%

등록일시
Date

Distinct1891
Distinct (%)26.6%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
Minimum2008-01-07 19:21:40
Maximum2021-05-21 15:44:33
2023-12-12T10:48:43.663706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:48:43.836253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

수정자번호
Categorical

IMBALANCE 

Distinct28
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
admin
4583 
19880040
756 
20189100
 
254
20070203
 
231
19940148
 
224
Other values (23)
1056 

Length

Max length8
Median length5
Mean length6.0218187
Min length4

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row19880040
2nd row19880040
3rd row19880040
4th row19880040
5th row19880040

Common Values

ValueCountFrequency (%)
admin 4583
64.5%
19880040 756
 
10.6%
20189100 254
 
3.6%
20070203 231
 
3.3%
19940148 224
 
3.2%
20200306 205
 
2.9%
20189121 161
 
2.3%
19990165 121
 
1.7%
20160248 119
 
1.7%
자료이관 76
 
1.1%
Other values (18) 374
 
5.3%

Length

2023-12-12T10:48:44.015083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
admin 4583
64.5%
19880040 756
 
10.6%
20189100 254
 
3.6%
20070203 231
 
3.3%
19940148 224
 
3.2%
20200306 205
 
2.9%
20189121 161
 
2.3%
19990165 121
 
1.7%
20160248 119
 
1.7%
자료이관 76
 
1.1%
Other values (18) 374
 
5.3%

수정일시
Date

Distinct1944
Distinct (%)27.4%
Missing0
Missing (%)0.0%
Memory size55.6 KiB
Minimum2008-01-07 19:21:40
Maximum2023-08-23 10:17:43
2023-12-12T10:48:44.179924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:48:44.373314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

파일일련번호
Real number (ℝ)

MISSING 

Distinct21
Distinct (%)100.0%
Missing7083
Missing (%)99.7%
Infinite0
Infinite (%)0.0%
Mean2.0175175 × 1013
Minimum2.0160902 × 1013
Maximum2.0190917 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size62.6 KiB
2023-12-12T10:48:44.543404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0160902 × 1013
5-th percentile2.0160902 × 1013
Q12.0160902 × 1013
median2.0160902 × 1013
Q32.0190917 × 1013
95-th percentile2.0190917 × 1013
Maximum2.0190917 × 1013
Range3.0014323 × 1010
Interquartile range (IQR)3.0014323 × 1010

Descriptive statistics

Standard deviation1.5339733 × 1010
Coefficient of variation (CV)0.00076032712
Kurtosis-2.2103433
Mean2.0175175 × 1013
Median Absolute Deviation (MAD)133
Skewness0.10294487
Sum4.2367868 × 1014
Variance2.3530741 × 1020
MonotonicityNot monotonic
2023-12-12T10:48:45.050689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
20190916556639 1
 
< 0.1%
20160902234097 1
 
< 0.1%
20190916556635 1
 
< 0.1%
20190509551132 1
 
< 0.1%
20160902234112 1
 
< 0.1%
20190916556631 1
 
< 0.1%
20190916556643 1
 
< 0.1%
20190916556642 1
 
< 0.1%
20190916556641 1
 
< 0.1%
20160902234137 1
 
< 0.1%
Other values (11) 11
 
0.2%
(Missing) 7083
99.7%
ValueCountFrequency (%)
20160902234004 1
< 0.1%
20160902234011 1
< 0.1%
20160902234034 1
< 0.1%
20160902234053 1
< 0.1%
20160902234059 1
< 0.1%
20160902234071 1
< 0.1%
20160902234072 1
< 0.1%
20160902234081 1
< 0.1%
20160902234097 1
< 0.1%
20160902234112 1
< 0.1%
ValueCountFrequency (%)
20190916556643 1
< 0.1%
20190916556642 1
< 0.1%
20190916556641 1
< 0.1%
20190916556640 1
< 0.1%
20190916556639 1
< 0.1%
20190916556638 1
< 0.1%
20190916556636 1
< 0.1%
20190916556635 1
< 0.1%
20190916556631 1
< 0.1%
20190509551132 1
< 0.1%

Sample

토지블록번호롯트번호롯트세부번호토지구분소재지우편번호소재지기본주소소재지상세주소소재지_본번소재지_부번용도구분당초면적당초단가당초금액확정면적확정단가확정금액철거이행보증금임대보증금연간임대료첨부파일경로첨부파일공급코드계약상태전체면적등록자번호등록일시수정자번호수정일시파일일련번호
0성서5차산업단지2710전711814대구광역시 달성군 다사읍세천리1686-116861공공.후생복지시설826.01072619.0885984000826.11072619.0886090550000<NA><NA>수의계약(토지리턴제)분양계약826.1198800402012-06-25 14:52:08198800402012-06-25 14:52:08<NA>
1성서5차산업단지2720전711814대구광역시 달성군 다사읍세천리1686-216862공공.후생복지시설826.0680750.0562300000826.1680750.0562367570000<NA><NA>입찰공급분양계약826.1198800402012-06-25 14:52:08198800402012-06-25 14:52:08<NA>
2성서5차산업단지2730전711814대구광역시 달성군 다사읍세천리1686-316863공공.후생복지시설826.0680739.0562291000825.9680739.0562222340000<NA><NA>수의계약분양계약825.9198800402012-06-25 14:52:08198800402012-06-25 14:52:08<NA>
3성서5차산업단지2740전711814대구광역시 달성군 다사읍세천리1686-416864공공.후생복지시설825.0680739.0561610000825.1680739.0561677740000<NA><NA>수의계약(토지리턴제)분양계약825.1198800402012-06-25 14:52:08198800402012-06-25 14:52:08<NA>
4성서5차산업단지2750전711814대구광역시 달성군 다사읍세천리1686-516865공공.후생복지시설825.0680739.0561610000824.9680739.0561541600000<NA><NA>수의계약(토지리턴제)분양계약824.9198800402012-06-25 14:52:08198800402012-06-25 14:52:08<NA>
5성서5차산업단지2760전711814대구광역시 달성군 다사읍세천리1686-616866공공.후생복지시설826.0705989.0583147000826.0705989.0583147000000<NA><NA>수의계약분양계약826.0198800402012-06-25 14:52:08198800402012-06-25 14:52:08<NA>
6성서5차산업단지2770전711814대구광역시 달성군 다사읍세천리1686-716867산업시설용지3952.4448000.017706752008034.1452000.03631413200000<NA><NA>대기업유치분양계약8034.1200501902013-05-02 16:56:50200501902013-05-02 16:56:50<NA>
7성서5차산업단지2790전711814대구광역시 달성군 다사읍세천리1686-916869산업시설용지7842.0451000.035367420007842.0451000.03536742000000<NA><NA>대기업유치분양계약7842.0198800402012-06-25 14:52:08198800402012-06-25 14:52:08<NA>
8성서5차산업단지2810전711814대구광역시 달성군 다사읍세천리1685-116851공공.후생복지시설655.01420900.0930690000655.21420900.0930973680000<NA><NA>입찰공급분양계약655.2198800402012-06-25 14:52:08198800402012-06-25 14:52:08<NA>
9성서5차산업단지2820전711814대구광역시 달성군 다사읍세천리1685-316853공공.후생복지시설1309.01070094.014007540001309.91070094.01401716130000<NA><NA>수의계약(토지리턴제)분양계약1309.9198800402012-06-25 14:52:08198800402012-06-25 14:52:08<NA>
토지블록번호롯트번호롯트세부번호토지구분소재지우편번호소재지기본주소소재지상세주소소재지_본번소재지_부번용도구분당초면적당초단가당초금액확정면적확정단가확정금액철거이행보증금임대보증금연간임대료첨부파일경로첨부파일공급코드계약상태전체면적등록자번호등록일시수정자번호수정일시파일일련번호
7094죽곡2지구920전711815대구광역시 달성군 다사읍죽곡리826-28262단독주택지275.0741084.0203798000275.1741084.0203872200000<NA><NA>특별공급분양계약275.1199401482011-10-10 11:15:05199401482011-10-10 11:15:05<NA>
7095죽곡2지구930전711815대구광역시 달성군 다사읍죽곡리826-38263단독주택지275.0741084.0203798000275.0741084.0203798000000<NA><NA>특별공급분양계약275.0199401482011-10-10 11:19:34199401482011-10-10 11:19:34<NA>
7096죽곡2지구940전711815대구광역시 달성군 다사읍죽곡리826-48264단독주택지275.0741084.0203798000275.5741084.0204168640000<NA><NA>특별공급분양계약275.5199401482011-10-10 11:27:58199401482011-10-10 11:27:58<NA>
7097죽곡2지구950전711815대구광역시 달성군 다사읍죽곡리826-58265단독주택지275.0741084.0203798000275.0741084.0203798000000<NA><NA>특별공급분양계약275.0199401482011-10-10 11:28:27199401482011-10-10 11:28:27<NA>
7098죽곡2지구960전711815대구광역시 달성군 다사읍죽곡리826-68266단독주택지275.0741084.0203798000275.4741084.0204094530000<NA><NA>특별공급분양계약275.4199401482011-10-10 11:28:55199401482011-10-10 11:28:55<NA>
7099죽곡2지구970전711815대구광역시 달성군 다사읍죽곡리826-78267단독주택지284.0815243.0231529000284.0815243.0231529000000<NA><NA>특별공급분양계약284.0199401482011-10-10 11:47:36199401482011-10-10 11:47:36<NA>
7100죽곡2지구980전711815대구광역시 달성군 다사읍죽곡리826-88268단독주택지255.0800310.0204079000255.4800310.0204399170000<NA><NA>특별공급분양계약255.4199401482011-10-10 11:47:59199401482011-10-10 11:47:59<NA>
7101죽곡2지구990전711815대구광역시 달성군 다사읍죽곡리826-98269단독주택지275.0725633.0199549000275.1725633.0199621630000<NA><NA>특별공급분양계약275.1199401482011-10-10 11:48:21199401482011-10-10 11:48:21<NA>
7102죽곡2지구9100전711815대구광역시 달성군 다사읍죽곡리826-1082610단독주택지275.0725633.0199549000275.0725633.0199549000000<NA><NA>특별공급분양계약275.0199401482011-10-10 11:59:00199401482011-10-10 11:59:00<NA>
7103죽곡2지구9110전711815대구광역시 달성군 다사읍죽곡리826-1182611단독주택지275.0725633.0199549000275.3725633.0199766760000<NA><NA>특별공급분양계약275.3199401482011-10-10 11:59:46199401482011-10-10 11:59:46<NA>