Overview

Dataset statistics

Number of variables73
Number of observations10000
Missing cells215163
Missing cells (%)29.5%
Duplicate rows2
Duplicate rows (%)< 0.1%
Total size in memory6.1 MiB
Average record size in memory641.0 B

Variable types

Numeric36
Text8
DateTime3
Categorical19
Unsupported6
Boolean1

Dataset

Description토지매수정보(지순번,접수번호,접수일자,소유자번호,신청자번호,매도신청대장번호,토지고유코드,토지고유코드_코드북 등)
URLhttps://www.data.go.kr/data/15068996/fileData.do

Alerts

농업진흥지역 has constant value ""Constant
Dataset has 2 (< 0.1%) duplicate rowsDuplicates
지목 is highly imbalanced (52.8%)Imbalance
우선매수대상지역 is highly imbalanced (84.0%)Imbalance
매수현황 is highly imbalanced (50.5%)Imbalance
필지정보용도구역 is highly imbalanced (82.1%)Imbalance
현지조사물건개수 is highly imbalanced (62.7%)Imbalance
용도2 is highly imbalanced (59.2%)Imbalance
용도3 is highly imbalanced (59.1%)Imbalance
용도4 is highly imbalanced (67.6%)Imbalance
용도6 is highly imbalanced (74.6%)Imbalance
용도7 is highly imbalanced (71.9%)Imbalance
용도8 is highly imbalanced (59.1%)Imbalance
용도9 is highly imbalanced (59.2%)Imbalance
용도10 is highly imbalanced (67.5%)Imbalance
매수완료_합병년도 is highly imbalanced (96.8%)Imbalance
매수완료_변동유무 is highly imbalanced (82.6%)Imbalance
매수완료_용도 is highly imbalanced (51.2%)Imbalance
용도지역 has 7132 (71.3%) missing valuesMissing
하천거리 has 423 (4.2%) missing valuesMissing
연접 has 2294 (22.9%) missing valuesMissing
매매계약체결일 has 194 (1.9%) missing valuesMissing
하천명 has 434 (4.3%) missing valuesMissing
농업진흥지역 has 9893 (98.9%) missing valuesMissing
필지정보용도지역 has 7047 (70.5%) missing valuesMissing
현지조사순번 has 388 (3.9%) missing valuesMissing
배점거리 has 387 (3.9%) missing valuesMissing
용도1 has 387 (3.9%) missing valuesMissing
용도11 has 8356 (83.6%) missing valuesMissing
용도12 has 8356 (83.6%) missing valuesMissing
용도13 has 8356 (83.6%) missing valuesMissing
용도14 has 8356 (83.6%) missing valuesMissing
용도15 has 8356 (83.6%) missing valuesMissing
규제1 has 387 (3.9%) missing valuesMissing
규제2 has 8356 (83.6%) missing valuesMissing
유하1 has 387 (3.9%) missing valuesMissing
유하2 has 8356 (83.6%) missing valuesMissing
점오염1 has 387 (3.9%) missing valuesMissing
비점오염1 has 8356 (83.6%) missing valuesMissing
연접1 has 592 (5.9%) missing valuesMissing
감정평가대상토지_순번 has 10000 (100.0%) missing valuesMissing
감정평가대상건물_개수 has 10000 (100.0%) missing valuesMissing
전략매수토지_번호 has 8482 (84.8%) missing valuesMissing
감정평가의뢰_번호 has 1249 (12.5%) missing valuesMissing
감정평가의뢰번호 has 1381 (13.8%) missing valuesMissing
감정평가토지 has 1286 (12.9%) missing valuesMissing
감정평가토지외물건_개수 has 7846 (78.5%) missing valuesMissing
매매계약대상번호_특이사항 has 8893 (88.9%) missing valuesMissing
매매계약번호 has 3690 (36.9%) missing valuesMissing
매매계약_계약체결일 has 3690 (36.9%) missing valuesMissing
매수완료번호 has 3688 (36.9%) missing valuesMissing
매수완료_계약일 has 3688 (36.9%) missing valuesMissing
매수완료_거리 has 4074 (40.7%) missing valuesMissing
매수완료_용도점수 has 9030 (90.3%) missing valuesMissing
매수완료_규제점수 has 9030 (90.3%) missing valuesMissing
매수완료_매각년도 has 10000 (100.0%) missing valuesMissing
매수완료_경계표주년도 has 6644 (66.4%) missing valuesMissing
매수완료_안내판년도 has 5896 (59.0%) missing valuesMissing
매수완료_과수벌목년도 has 9211 (92.1%) missing valuesMissing
매수추진대상_면적 has 200 (2.0%) missing valuesMissing
면적 is highly skewed (γ1 = 24.43930114)Skewed
매수추진대상_면적 is highly skewed (γ1 = 24.22402499)Skewed
하천거리 is an unsupported type, check if it needs cleaning or further analysisUnsupported
배점거리 is an unsupported type, check if it needs cleaning or further analysisUnsupported
감정평가대상토지_순번 is an unsupported type, check if it needs cleaning or further analysisUnsupported
감정평가대상건물_개수 is an unsupported type, check if it needs cleaning or further analysisUnsupported
매수완료_거리 is an unsupported type, check if it needs cleaning or further analysisUnsupported
매수완료_매각년도 is an unsupported type, check if it needs cleaning or further analysisUnsupported
연접 has 7489 (74.9%) zerosZeros
용도1 has 8443 (84.4%) zerosZeros
용도11 has 1615 (16.2%) zerosZeros
용도12 has 1547 (15.5%) zerosZeros
용도13 has 691 (6.9%) zerosZeros
용도14 has 1524 (15.2%) zerosZeros
용도15 has 1601 (16.0%) zerosZeros
규제1 has 8572 (85.7%) zerosZeros
규제2 has 933 (9.3%) zerosZeros
유하1 has 9073 (90.7%) zerosZeros
유하2 has 1367 (13.7%) zerosZeros
점오염1 has 8719 (87.2%) zerosZeros
비점오염1 has 1084 (10.8%) zerosZeros
연접1 has 9189 (91.9%) zerosZeros
매수완료_용도점수 has 173 (1.7%) zerosZeros
매수완료_규제점수 has 439 (4.4%) zerosZeros

Reproduction

Analysis started2023-12-12 00:55:39.516372
Analysis finished2023-12-12 00:55:41.433104
Duration1.92 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

Distinct6263
Distinct (%)62.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5091.3709
Minimum1
Maximum15755
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T09:55:41.498635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile417
Q12051
median5014.5
Q37851.25
95-th percentile10370.05
Maximum15755
Range15754
Interquartile range (IQR)5800.25

Descriptive statistics

Standard deviation3250.2124
Coefficient of variation (CV)0.63837667
Kurtosis-1.1566284
Mean5091.3709
Median Absolute Deviation (MAD)2885
Skewness0.13424386
Sum50913709
Variance10563881
MonotonicityNot monotonic
2023-12-12T09:55:41.626841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
992 10
 
0.1%
6308 10
 
0.1%
3358 8
 
0.1%
3347 8
 
0.1%
659 7
 
0.1%
8893 7
 
0.1%
4607 7
 
0.1%
10533 7
 
0.1%
7117 7
 
0.1%
3353 7
 
0.1%
Other values (6253) 9922
99.2%
ValueCountFrequency (%)
1 1
 
< 0.1%
4 3
< 0.1%
7 1
 
< 0.1%
8 2
< 0.1%
9 2
< 0.1%
10 2
< 0.1%
11 2
< 0.1%
14 1
 
< 0.1%
15 3
< 0.1%
19 1
 
< 0.1%
ValueCountFrequency (%)
15755 1
< 0.1%
14793 1
< 0.1%
14259 1
< 0.1%
14258 2
< 0.1%
14244 1
< 0.1%
14042 1
< 0.1%
13725 1
< 0.1%
13448 1
< 0.1%
13323 2
< 0.1%
13322 1
< 0.1%
Distinct6263
Distinct (%)62.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T09:55:41.867686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length13.0424
Min length13

Characters and Unicode

Total characters130424
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

Unique3687 ?
Unique (%)36.9%

Sample

1st row2006-1-0379-1
2nd row2005-1-1059-1
3rd row2005-1-1353-1
4th row2004-1-0007-1
5th row2005-1-0826-2
ValueCountFrequency (%)
2004-2-0302-1 10
 
0.1%
2005-1-1189-11 10
 
0.1%
2005-2-0177-5 8
 
0.1%
2005-2-0179-12 8
 
0.1%
2008-2-0018-1 7
 
0.1%
2005-2-0179-18 7
 
0.1%
2005-1-0580-4 7
 
0.1%
2009-1-0354-1 7
 
0.1%
2004-1-0457-1 7
 
0.1%
2005-1-0426-1 7
 
0.1%
Other values (6253) 9922
99.2%
2023-12-12T09:55:42.205657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 33969
26.0%
- 30000
23.0%
1 18030
13.8%
2 17816
13.7%
4 6567
 
5.0%
5 6473
 
5.0%
3 4150
 
3.2%
6 3957
 
3.0%
7 3265
 
2.5%
8 3215
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 100424
77.0%
Dash Punctuation 30000
 
23.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 33969
33.8%
1 18030
18.0%
2 17816
17.7%
4 6567
 
6.5%
5 6473
 
6.4%
3 4150
 
4.1%
6 3957
 
3.9%
7 3265
 
3.3%
8 3215
 
3.2%
9 2982
 
3.0%
Dash Punctuation
ValueCountFrequency (%)
- 30000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 130424
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 33969
26.0%
- 30000
23.0%
1 18030
13.8%
2 17816
13.7%
4 6567
 
5.0%
5 6473
 
5.0%
3 4150
 
3.2%
6 3957
 
3.0%
7 3265
 
2.5%
8 3215
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 130424
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 33969
26.0%
- 30000
23.0%
1 18030
13.8%
2 17816
13.7%
4 6567
 
5.0%
5 6473
 
5.0%
3 4150
 
3.2%
6 3957
 
3.0%
7 3265
 
2.5%
8 3215
 
2.5%
Distinct994
Distinct (%)9.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2003-03-15 00:00:00
Maximum2010-10-08 00:00:00
2023-12-12T09:55:42.343658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:55:42.490793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

소유자번호
Real number (ℝ)

Distinct6263
Distinct (%)62.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5091.3589
Minimum1
Maximum15753
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T09:55:42.955503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile417
Q12051
median5014.5
Q37851.25
95-th percentile10370.05
Maximum15753
Range15752
Interquartile range (IQR)5800.25

Descriptive statistics

Standard deviation3250.1871
Coefficient of variation (CV)0.63837321
Kurtosis-1.1567165
Mean5091.3589
Median Absolute Deviation (MAD)2885
Skewness0.13420788
Sum50913589
Variance10563716
MonotonicityNot monotonic
2023-12-12T09:55:43.144170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
992 10
 
0.1%
6308 10
 
0.1%
3358 8
 
0.1%
3347 8
 
0.1%
659 7
 
0.1%
8893 7
 
0.1%
4607 7
 
0.1%
10533 7
 
0.1%
7117 7
 
0.1%
3353 7
 
0.1%
Other values (6253) 9922
99.2%
ValueCountFrequency (%)
1 1
 
< 0.1%
4 3
< 0.1%
7 1
 
< 0.1%
8 2
< 0.1%
9 2
< 0.1%
10 2
< 0.1%
11 2
< 0.1%
14 1
 
< 0.1%
15 3
< 0.1%
19 1
 
< 0.1%
ValueCountFrequency (%)
15753 1
< 0.1%
14791 1
< 0.1%
14258 1
< 0.1%
14257 2
< 0.1%
14243 1
< 0.1%
14041 1
< 0.1%
13724 1
< 0.1%
13447 1
< 0.1%
13322 2
< 0.1%
13321 1
< 0.1%

신청자번호
Real number (ℝ)

Distinct6263
Distinct (%)62.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5091.3707
Minimum1
Maximum15754
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T09:55:43.347154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile417
Q12051
median5014.5
Q37851.25
95-th percentile10370.05
Maximum15754
Range15753
Interquartile range (IQR)5800.25

Descriptive statistics

Standard deviation3250.2118
Coefficient of variation (CV)0.63837658
Kurtosis-1.1566346
Mean5091.3707
Median Absolute Deviation (MAD)2885
Skewness0.13424231
Sum50913707
Variance10563877
MonotonicityNot monotonic
2023-12-12T09:55:43.541290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
992 10
 
0.1%
6308 10
 
0.1%
3358 8
 
0.1%
3347 8
 
0.1%
659 7
 
0.1%
8893 7
 
0.1%
4607 7
 
0.1%
10533 7
 
0.1%
7117 7
 
0.1%
3353 7
 
0.1%
Other values (6253) 9922
99.2%
ValueCountFrequency (%)
1 1
 
< 0.1%
4 3
< 0.1%
7 1
 
< 0.1%
8 2
< 0.1%
9 2
< 0.1%
10 2
< 0.1%
11 2
< 0.1%
14 1
 
< 0.1%
15 3
< 0.1%
19 1
 
< 0.1%
ValueCountFrequency (%)
15754 1
< 0.1%
14792 1
< 0.1%
14259 1
< 0.1%
14258 2
< 0.1%
14244 1
< 0.1%
14042 1
< 0.1%
13725 1
< 0.1%
13448 1
< 0.1%
13323 2
< 0.1%
13322 1
< 0.1%

매도신청대장번호
Real number (ℝ)

Distinct6264
Distinct (%)62.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5091.3975
Minimum1
Maximum16163
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T09:55:43.745288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile417
Q12051
median5014.5
Q37851.25
95-th percentile10370.05
Maximum16163
Range16162
Interquartile range (IQR)5800.25

Descriptive statistics

Standard deviation3250.3132
Coefficient of variation (CV)0.63839312
Kurtosis-1.1552681
Mean5091.3975
Median Absolute Deviation (MAD)2885
Skewness0.13454438
Sum50913975
Variance10564536
MonotonicityNot monotonic
2023-12-12T09:55:43.946452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
992 10
 
0.1%
6308 10
 
0.1%
3347 8
 
0.1%
3358 8
 
0.1%
4936 7
 
0.1%
1359 7
 
0.1%
3353 7
 
0.1%
8893 7
 
0.1%
4607 7
 
0.1%
659 7
 
0.1%
Other values (6254) 9922
99.2%
ValueCountFrequency (%)
1 1
 
< 0.1%
4 3
< 0.1%
7 1
 
< 0.1%
8 2
< 0.1%
9 2
< 0.1%
10 2
< 0.1%
11 2
< 0.1%
14 1
 
< 0.1%
15 3
< 0.1%
19 1
 
< 0.1%
ValueCountFrequency (%)
16163 1
< 0.1%
14787 1
< 0.1%
14253 1
< 0.1%
14252 2
< 0.1%
14238 1
< 0.1%
14036 1
< 0.1%
13719 1
< 0.1%
13441 1
< 0.1%
13316 2
< 0.1%
13315 1
< 0.1%

토지고유코드
Real number (ℝ)

Distinct6163
Distinct (%)61.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.7822161 × 1018
Minimum2.7140135 × 1018
Maximum4.889043 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T09:55:44.143114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.7140135 × 1018
5-th percentile4.717038 × 1018
Q14.723036 × 1018
median4.775037 × 1018
Q34.782035 × 1018
95-th percentile4.886037 × 1018
Maximum4.889043 × 1018
Range2.1750295 × 1018
Interquartile range (IQR)5.8999014 × 1016

Descriptive statistics

Standard deviation7.4352159 × 1016
Coefficient of variation (CV)0.015547637
Kurtosis253.19704
Mean4.7822161 × 1018
Median Absolute Deviation (MAD)6.997997 × 1015
Skewness-9.8216048
Sum8.200291 × 1018
Variance5.5282435 × 1033
MonotonicityNot monotonic
2023-12-12T09:55:44.312071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4717040021201040000 13
 
0.1%
4886038031107550001 10
 
0.1%
4776031042102650001 10
 
0.1%
4886025026109140001 10
 
0.1%
4717040024106080006 9
 
0.1%
4886037028104680002 9
 
0.1%
4886038031107550003 8
 
0.1%
4886037028104670001 8
 
0.1%
4717040024106080005 8
 
0.1%
4775037037100570005 7
 
0.1%
Other values (6153) 9908
99.1%
ValueCountFrequency (%)
2714013500106950000 1
 
< 0.1%
2771025327102480001 1
 
< 0.1%
2771031023105910004 1
 
< 0.1%
3171038025200780000 3
< 0.1%
3171038025201170000 1
 
< 0.1%
4711335024104930000 1
 
< 0.1%
4711335024105090000 1
 
< 0.1%
4711335024105110000 3
< 0.1%
4711335024105410000 3
< 0.1%
4711335024105450000 1
 
< 0.1%
ValueCountFrequency (%)
4889043033106540000 1
 
< 0.1%
4889043033106520000 1
 
< 0.1%
4889043033106300000 1
 
< 0.1%
4889039033108650001 1
 
< 0.1%
4889039033108330000 1
 
< 0.1%
4889039032101410004 3
< 0.1%
4889039032101410001 2
< 0.1%
4889038027111050000 1
 
< 0.1%
4889038027111040000 1
 
< 0.1%
4889038027110900004 3
< 0.1%
Distinct6163
Distinct (%)61.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T09:55:44.745791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length26
Mean length21.0642
Min length14

Characters and Unicode

Total characters210642
Distinct characters198
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

Unique3588 ?
Unique (%)35.9%

Sample

1st row경상북도 영양군 영양읍 대천리 919
2nd row경상북도 안동시 임동면 대곡리 537-1
3rd row경상북도 안동시 임동면 대곡리 938
4th row경상북도 경주시 산내면 신원리 1312-1
5th row경상북도 영양군 입암면 병옥리 266
ValueCountFrequency (%)
경상북도 7756
 
15.5%
청송군 2813
 
5.6%
경상남도 2237
 
4.5%
산청군 1769
 
3.5%
영양군 1409
 
2.8%
진보면 1387
 
2.8%
안동시 1311
 
2.6%
단성면 1093
 
2.2%
영천시 948
 
1.9%
자양면 932
 
1.9%
Other values (4349) 28490
56.8%
2023-12-12T09:55:45.394322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
40145
19.1%
10802
 
5.1%
10299
 
4.9%
10196
 
4.8%
9969
 
4.7%
8496
 
4.0%
8020
 
3.8%
7041
 
3.3%
1 6798
 
3.2%
6630
 
3.1%
Other values (188) 92246
43.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 129858
61.6%
Space Separator 40145
 
19.1%
Decimal Number 35409
 
16.8%
Dash Punctuation 5230
 
2.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10802
 
8.3%
10299
 
7.9%
10196
 
7.9%
9969
 
7.7%
8496
 
6.5%
8020
 
6.2%
7041
 
5.4%
6630
 
5.1%
3674
 
2.8%
3272
 
2.5%
Other values (176) 51459
39.6%
Decimal Number
ValueCountFrequency (%)
1 6798
19.2%
2 4430
12.5%
3 3984
11.3%
4 3577
10.1%
5 3291
9.3%
6 2909
8.2%
7 2807
7.9%
9 2666
 
7.5%
8 2664
 
7.5%
0 2283
 
6.4%
Space Separator
ValueCountFrequency (%)
40145
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5230
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 129858
61.6%
Common 80784
38.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10802
 
8.3%
10299
 
7.9%
10196
 
7.9%
9969
 
7.7%
8496
 
6.5%
8020
 
6.2%
7041
 
5.4%
6630
 
5.1%
3674
 
2.8%
3272
 
2.5%
Other values (176) 51459
39.6%
Common
ValueCountFrequency (%)
40145
49.7%
1 6798
 
8.4%
- 5230
 
6.5%
2 4430
 
5.5%
3 3984
 
4.9%
4 3577
 
4.4%
5 3291
 
4.1%
6 2909
 
3.6%
7 2807
 
3.5%
9 2666
 
3.3%
Other values (2) 4947
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 129858
61.6%
ASCII 80784
38.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
40145
49.7%
1 6798
 
8.4%
- 5230
 
6.5%
2 4430
 
5.5%
3 3984
 
4.9%
4 3577
 
4.4%
5 3291
 
4.1%
6 2909
 
3.6%
7 2807
 
3.5%
9 2666
 
3.3%
Other values (2) 4947
 
6.1%
Hangul
ValueCountFrequency (%)
10802
 
8.3%
10299
 
7.9%
10196
 
7.9%
9969
 
7.7%
8496
 
6.5%
8020
 
6.2%
7041
 
5.4%
6630
 
5.1%
3674
 
2.8%
3272
 
2.5%
Other values (176) 51459
39.6%

용도지역
Text

MISSING 

Distinct58
Distinct (%)2.0%
Missing7132
Missing (%)71.3%
Memory size156.2 KiB
2023-12-12T09:55:45.612973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length4
Mean length4.9341004
Min length4

Characters and Unicode

Total characters14151
Distinct characters51
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)0.9%

Sample

1st row관리지역
2nd row생산관리지역
3rd row열람안됨
4th row농림지역
5th row관리지역
ValueCountFrequency (%)
농림지역 1050
36.2%
관리지역 830
28.6%
보전관리지역 356
 
12.3%
계획관리지역 167
 
5.8%
자연환경보전지역 150
 
5.2%
생산관리지역 84
 
2.9%
열람안됨 53
 
1.8%
자연환경보전 45
 
1.6%
자연녹지지역 36
 
1.2%
자연녹지 23
 
0.8%
Other values (42) 105
 
3.6%
2023-12-12T09:55:45.970685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2886
20.4%
2805
19.8%
1495
10.6%
1493
10.6%
1064
 
7.5%
1063
 
7.5%
577
 
4.1%
575
 
4.1%
283
 
2.0%
283
 
2.0%
Other values (41) 1627
11.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14029
99.1%
Other Punctuation 63
 
0.4%
Space Separator 31
 
0.2%
Decimal Number 16
 
0.1%
Open Punctuation 6
 
< 0.1%
Close Punctuation 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2886
20.6%
2805
20.0%
1495
10.7%
1493
10.6%
1064
 
7.6%
1063
 
7.6%
577
 
4.1%
575
 
4.1%
283
 
2.0%
283
 
2.0%
Other values (35) 1505
10.7%
Decimal Number
ValueCountFrequency (%)
1 11
68.8%
2 5
31.2%
Other Punctuation
ValueCountFrequency (%)
, 63
100.0%
Space Separator
ValueCountFrequency (%)
31
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14029
99.1%
Common 122
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2886
20.6%
2805
20.0%
1495
10.7%
1493
10.6%
1064
 
7.6%
1063
 
7.6%
577
 
4.1%
575
 
4.1%
283
 
2.0%
283
 
2.0%
Other values (35) 1505
10.7%
Common
ValueCountFrequency (%)
, 63
51.6%
31
25.4%
1 11
 
9.0%
( 6
 
4.9%
) 6
 
4.9%
2 5
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14029
99.1%
ASCII 122
 
0.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2886
20.6%
2805
20.0%
1495
10.7%
1493
10.6%
1064
 
7.6%
1063
 
7.6%
577
 
4.1%
575
 
4.1%
283
 
2.0%
283
 
2.0%
Other values (35) 1505
10.7%
ASCII
ValueCountFrequency (%)
, 63
51.6%
31
25.4%
1 11
 
9.0%
( 6
 
4.9%
) 6
 
4.9%
2 5
 
4.1%

지목
Categorical

IMBALANCE 

Distinct36
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3643 
3529 
대지
840 
임야
707 
과수원
 
334
Other values (31)
947 

Length

Max length5
Median length1
Mean length1.4122
Min length1

Unique

Unique8 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
3643
36.4%
3529
35.3%
대지 840
 
8.4%
임야 707
 
7.1%
과수원 334
 
3.3%
잡종지 276
 
2.8%
목장용지 141
 
1.4%
공장용지 111
 
1.1%
하천 81
 
0.8%
71
 
0.7%
Other values (26) 267
 
2.7%

Length

2023-12-12T09:55:46.165561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
3652
36.5%
3535
35.4%
대지 840
 
8.4%
임야 707
 
7.1%
과수원 334
 
3.3%
잡종지 276
 
2.8%
목장용지 141
 
1.4%
공장용지 111
 
1.1%
하천 81
 
0.8%
71
 
0.7%
Other values (21) 252
 
2.5%

면적
Real number (ℝ)

SKEWED 

Distinct2710
Distinct (%)27.1%
Missing5
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean3016.1637
Minimum0
Maximum730758
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T09:55:46.348701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile116
Q1442
median1054
Q32047.5
95-th percentile5987
Maximum730758
Range730758
Interquartile range (IQR)1605.5

Descriptive statistics

Standard deviation19307.065
Coefficient of variation (CV)6.4011992
Kurtosis763.52835
Mean3016.1637
Median Absolute Deviation (MAD)707
Skewness24.439301
Sum30146556
Variance3.7276274 × 108
MonotonicityNot monotonic
2023-12-12T09:55:46.568776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
400.0 27
 
0.3%
330.0 25
 
0.2%
162.0 25
 
0.2%
496.0 24
 
0.2%
129.0 24
 
0.2%
271.0 23
 
0.2%
264.0 23
 
0.2%
142.0 22
 
0.2%
40.0 22
 
0.2%
1008.0 21
 
0.2%
Other values (2700) 9759
97.6%
ValueCountFrequency (%)
0.0 1
 
< 0.1%
3.0 9
0.1%
4.0 1
 
< 0.1%
5.0 2
 
< 0.1%
6.0 4
< 0.1%
7.0 7
0.1%
8.0 1
 
< 0.1%
9.0 2
 
< 0.1%
10.0 7
0.1%
11.0 1
 
< 0.1%
ValueCountFrequency (%)
730758.0 3
< 0.1%
514403.0 2
< 0.1%
345917.0 3
< 0.1%
264767.0 3
< 0.1%
251050.0 1
 
< 0.1%
229724.0 2
< 0.1%
223740.0 3
< 0.1%
215901.0 2
< 0.1%
202711.0 3
< 0.1%
172076.0 1
 
< 0.1%

하천거리
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing423
Missing (%)4.2%
Memory size156.2 KiB

우선매수대상지역
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9622 
비대상
 
330
대상
 
48

Length

Max length4
Median length4
Mean length3.9574
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9622
96.2%
비대상 330
 
3.3%
대상 48
 
0.5%

Length

2023-12-12T09:55:46.755792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:55:46.892713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9622
96.2%
비대상 330
 
3.3%
대상 48
 
0.5%

연접
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)0.1%
Missing2294
Missing (%)22.9%
Infinite0
Infinite (%)0.0%
Mean0.19534129
Minimum0
Maximum20
Zeros7489
Zeros (%)74.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T09:55:46.982865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum20
Range20
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.2510202
Coefficient of variation (CV)6.4042795
Kurtosis72.182553
Mean0.19534129
Median Absolute Deviation (MAD)0
Skewness7.6842604
Sum1505.3
Variance1.5650516
MonotonicityNot monotonic
2023-12-12T09:55:47.092037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0.0 7489
74.9%
5.0 120
 
1.2%
10.0 46
 
0.5%
8.0 43
 
0.4%
20.0 5
 
0.1%
0.8 1
 
< 0.1%
0.3 1
 
< 0.1%
0.2 1
 
< 0.1%
(Missing) 2294
 
22.9%
ValueCountFrequency (%)
0.0 7489
74.9%
0.2 1
 
< 0.1%
0.3 1
 
< 0.1%
0.8 1
 
< 0.1%
5.0 120
 
1.2%
8.0 43
 
0.4%
10.0 46
 
0.5%
20.0 5
 
0.1%
ValueCountFrequency (%)
20.0 5
 
0.1%
10.0 46
 
0.5%
8.0 43
 
0.4%
5.0 120
 
1.2%
0.8 1
 
< 0.1%
0.3 1
 
< 0.1%
0.2 1
 
< 0.1%
0.0 7489
74.9%

진행사항
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
매수완료
6310 
감정후포기
2190 
종결
1042 
감정전취하
 
264
추진중
 
194

Length

Max length5
Median length4
Mean length4.0176
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
매수완료 6310
63.1%
감정후포기 2190
 
21.9%
종결 1042
 
10.4%
감정전취하 264
 
2.6%
추진중 194
 
1.9%

Length

2023-12-12T09:55:47.218067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:55:47.320240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
매수완료 6310
63.1%
감정후포기 2190
 
21.9%
종결 1042
 
10.4%
감정전취하 264
 
2.6%
추진중 194
 
1.9%

매매계약체결일
Text

MISSING 

Distinct497
Distinct (%)5.1%
Missing194
Missing (%)1.9%
Memory size156.2 KiB
2023-12-12T09:55:47.557086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length7.8986335
Min length2

Characters and Unicode

Total characters77454
Distinct characters21
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

Unique71 ?
Unique (%)0.7%

Sample

1st row2008-10-02
2nd row2009-07-24
3rd row2014-02-24
4th row2004-09-16
5th row2012-05-31
ValueCountFrequency (%)
감정후포기 2190
22.3%
종결 1042
 
10.6%
2004-09-01 267
 
2.7%
감정전취하 264
 
2.7%
2008-09-30 214
 
2.2%
2008-10-01 212
 
2.2%
2009-06-01 205
 
2.1%
2008-10-02 179
 
1.8%
2009-06-02 178
 
1.8%
2009-06-11 111
 
1.1%
Other values (487) 4944
50.4%
2023-12-12T09:55:47.941082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 19700
25.4%
- 12620
16.3%
2 10063
13.0%
1 7105
 
9.2%
5 2642
 
3.4%
9 2584
 
3.3%
2454
 
3.2%
2454
 
3.2%
6 2276
 
2.9%
2190
 
2.8%
Other values (11) 13366
17.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 50480
65.2%
Other Letter 14354
 
18.5%
Dash Punctuation 12620
 
16.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 19700
39.0%
2 10063
19.9%
1 7105
 
14.1%
5 2642
 
5.2%
9 2584
 
5.1%
6 2276
 
4.5%
8 1658
 
3.3%
3 1627
 
3.2%
4 1563
 
3.1%
7 1262
 
2.5%
Other Letter
ValueCountFrequency (%)
2454
17.1%
2454
17.1%
2190
15.3%
2190
15.3%
2190
15.3%
1042
7.3%
1042
7.3%
264
 
1.8%
264
 
1.8%
264
 
1.8%
Dash Punctuation
ValueCountFrequency (%)
- 12620
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 63100
81.5%
Hangul 14354
 
18.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 19700
31.2%
- 12620
20.0%
2 10063
15.9%
1 7105
 
11.3%
5 2642
 
4.2%
9 2584
 
4.1%
6 2276
 
3.6%
8 1658
 
2.6%
3 1627
 
2.6%
4 1563
 
2.5%
Hangul
ValueCountFrequency (%)
2454
17.1%
2454
17.1%
2190
15.3%
2190
15.3%
2190
15.3%
1042
7.3%
1042
7.3%
264
 
1.8%
264
 
1.8%
264
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 63100
81.5%
Hangul 14354
 
18.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 19700
31.2%
- 12620
20.0%
2 10063
15.9%
1 7105
 
11.3%
5 2642
 
4.2%
9 2584
 
4.1%
6 2276
 
3.6%
8 1658
 
2.6%
3 1627
 
2.6%
4 1563
 
2.5%
Hangul
ValueCountFrequency (%)
2454
17.1%
2454
17.1%
2190
15.3%
2190
15.3%
2190
15.3%
1042
7.3%
1042
7.3%
264
 
1.8%
264
 
1.8%
264
 
1.8%

하천명
Text

MISSING 

Distinct120
Distinct (%)1.3%
Missing434
Missing (%)4.3%
Memory size156.2 KiB
2023-12-12T09:55:48.211105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length3
Mean length2.9288104
Min length1

Characters and Unicode

Total characters28017
Distinct characters117
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)0.2%

Sample

1st row하원천
2nd row대곡천
3rd row대곡천
4th row동창천
5th row반변천
ValueCountFrequency (%)
반변천 1757
18.3%
용전천 1106
11.5%
남강 816
 
8.5%
서시천 682
 
7.1%
자호천 524
 
5.5%
용계천 494
 
5.2%
지촌천 455
 
4.7%
남사천 415
 
4.3%
화매천 412
 
4.3%
하거천 407
 
4.2%
Other values (112) 2523
26.3%
2023-12-12T09:55:48.706886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8139
29.1%
1771
 
6.3%
1766
 
6.3%
1603
 
5.7%
1473
 
5.3%
1266
 
4.5%
1125
 
4.0%
787
 
2.8%
693
 
2.5%
686
 
2.4%
Other values (107) 8708
31.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 27965
99.8%
Space Separator 29
 
0.1%
Decimal Number 10
 
< 0.1%
Open Punctuation 5
 
< 0.1%
Close Punctuation 5
 
< 0.1%
Other Punctuation 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
8139
29.1%
1771
 
6.3%
1766
 
6.3%
1603
 
5.7%
1473
 
5.3%
1266
 
4.5%
1125
 
4.0%
787
 
2.8%
693
 
2.5%
686
 
2.5%
Other values (94) 8656
31.0%
Decimal Number
ValueCountFrequency (%)
5 3
30.0%
0 2
20.0%
8 1
 
10.0%
9 1
 
10.0%
3 1
 
10.0%
2 1
 
10.0%
1 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
; 1
33.3%
# 1
33.3%
& 1
33.3%
Space Separator
ValueCountFrequency (%)
29
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 27965
99.8%
Common 52
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
8139
29.1%
1771
 
6.3%
1766
 
6.3%
1603
 
5.7%
1473
 
5.3%
1266
 
4.5%
1125
 
4.0%
787
 
2.8%
693
 
2.5%
686
 
2.5%
Other values (94) 8656
31.0%
Common
ValueCountFrequency (%)
29
55.8%
( 5
 
9.6%
) 5
 
9.6%
5 3
 
5.8%
0 2
 
3.8%
; 1
 
1.9%
8 1
 
1.9%
9 1
 
1.9%
3 1
 
1.9%
2 1
 
1.9%
Other values (3) 3
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 27965
99.8%
ASCII 52
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
8139
29.1%
1771
 
6.3%
1766
 
6.3%
1603
 
5.7%
1473
 
5.3%
1266
 
4.5%
1125
 
4.0%
787
 
2.8%
693
 
2.5%
686
 
2.5%
Other values (94) 8656
31.0%
ASCII
ValueCountFrequency (%)
29
55.8%
( 5
 
9.6%
) 5
 
9.6%
5 3
 
5.8%
0 2
 
3.8%
; 1
 
1.9%
8 1
 
1.9%
9 1
 
1.9%
3 1
 
1.9%
2 1
 
1.9%
Other values (3) 3
 
5.8%

농업진흥지역
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.9%
Missing9893
Missing (%)98.9%
Memory size97.7 KiB
True
 
107
(Missing)
9893 
ValueCountFrequency (%)
True 107
 
1.1%
(Missing) 9893
98.9%
2023-12-12T09:55:48.825893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

매수현황
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
매매계약
6096 
감정평가
3540 
현지조사
 
348
<NA>
 
14
감정의뢰
 
2

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
매매계약 6096
61.0%
감정평가 3540
35.4%
현지조사 348
 
3.5%
<NA> 14
 
0.1%
감정의뢰 2
 
< 0.1%

Length

2023-12-12T09:55:48.941973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:55:49.061299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
매매계약 6096
61.0%
감정평가 3540
35.4%
현지조사 348
 
3.5%
na 14
 
0.1%
감정의뢰 2
 
< 0.1%

필지정보순번
Real number (ℝ)

Distinct6263
Distinct (%)62.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5091.412
Minimum1
Maximum16167
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T09:55:49.209261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile417
Q12051
median5014.5
Q37851.25
95-th percentile10370.05
Maximum16167
Range16166
Interquartile range (IQR)5800.25

Descriptive statistics

Standard deviation3250.3499
Coefficient of variation (CV)0.63839853
Kurtosis-1.1550523
Mean5091.412
Median Absolute Deviation (MAD)2885
Skewness0.1346135
Sum50914120
Variance10564775
MonotonicityNot monotonic
2023-12-12T09:55:49.392330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
992 10
 
0.1%
6308 10
 
0.1%
3358 8
 
0.1%
3347 8
 
0.1%
659 7
 
0.1%
8893 7
 
0.1%
4607 7
 
0.1%
10533 7
 
0.1%
7117 7
 
0.1%
3353 7
 
0.1%
Other values (6253) 9922
99.2%
ValueCountFrequency (%)
1 1
 
< 0.1%
4 3
< 0.1%
7 1
 
< 0.1%
8 2
< 0.1%
9 2
< 0.1%
10 2
< 0.1%
11 2
< 0.1%
14 1
 
< 0.1%
15 3
< 0.1%
19 1
 
< 0.1%
ValueCountFrequency (%)
16167 1
< 0.1%
14792 1
< 0.1%
14259 1
< 0.1%
14258 2
< 0.1%
14244 1
< 0.1%
14042 1
< 0.1%
13725 1
< 0.1%
13448 1
< 0.1%
13323 2
< 0.1%
13322 1
< 0.1%

규제지역
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
수변구역
6543 
기타지역(자연마을외)
1892 
기타지역(자연마을)
886 
상수원보호구역
679 

Length

Max length11
Median length4
Mean length6.0597
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row기타지역(자연마을외)
2nd row수변구역
3rd row수변구역
4th row수변구역
5th row수변구역

Common Values

ValueCountFrequency (%)
수변구역 6543
65.4%
기타지역(자연마을외) 1892
 
18.9%
기타지역(자연마을) 886
 
8.9%
상수원보호구역 679
 
6.8%

Length

2023-12-12T09:55:49.549601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:55:49.692131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수변구역 6543
65.4%
기타지역(자연마을외 1892
 
18.9%
기타지역(자연마을 886
 
8.9%
상수원보호구역 679
 
6.8%
Distinct57
Distinct (%)1.9%
Missing7047
Missing (%)70.5%
Memory size156.2 KiB
2023-12-12T09:55:49.896893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length4
Mean length4.9244836
Min length4

Characters and Unicode

Total characters14542
Distinct characters51
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)0.8%

Sample

1st row관리지역
2nd row생산관리지역
3rd row열람안됨
4th row농림지역
5th row관리지역
ValueCountFrequency (%)
농림지역 1055
35.4%
관리지역 884
29.6%
보전관리지역 367
 
12.3%
계획관리지역 181
 
6.1%
자연환경보전지역 150
 
5.0%
생산관리지역 84
 
2.8%
열람안됨 53
 
1.8%
자연환경보전 45
 
1.5%
자연녹지지역 36
 
1.2%
자연녹지 23
 
0.8%
Other values (40) 106
 
3.6%
2023-12-12T09:55:50.272737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2972
20.4%
2891
19.9%
1574
10.8%
1572
10.8%
1069
 
7.4%
1068
 
7.3%
587
 
4.0%
586
 
4.0%
282
 
1.9%
282
 
1.9%
Other values (41) 1659
11.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14419
99.2%
Other Punctuation 64
 
0.4%
Space Separator 31
 
0.2%
Decimal Number 16
 
0.1%
Open Punctuation 6
 
< 0.1%
Close Punctuation 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2972
20.6%
2891
20.0%
1574
10.9%
1572
10.9%
1069
 
7.4%
1068
 
7.4%
587
 
4.1%
586
 
4.1%
282
 
2.0%
282
 
2.0%
Other values (35) 1536
10.7%
Decimal Number
ValueCountFrequency (%)
1 11
68.8%
2 5
31.2%
Other Punctuation
ValueCountFrequency (%)
, 64
100.0%
Space Separator
ValueCountFrequency (%)
31
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14419
99.2%
Common 123
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2972
20.6%
2891
20.0%
1574
10.9%
1572
10.9%
1069
 
7.4%
1068
 
7.4%
587
 
4.1%
586
 
4.1%
282
 
2.0%
282
 
2.0%
Other values (35) 1536
10.7%
Common
ValueCountFrequency (%)
, 64
52.0%
31
25.2%
1 11
 
8.9%
( 6
 
4.9%
) 6
 
4.9%
2 5
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14419
99.2%
ASCII 123
 
0.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2972
20.6%
2891
20.0%
1574
10.9%
1572
10.9%
1069
 
7.4%
1068
 
7.4%
587
 
4.1%
586
 
4.1%
282
 
2.0%
282
 
2.0%
Other values (35) 1536
10.7%
ASCII
ValueCountFrequency (%)
, 64
52.0%
31
25.2%
1 11
 
8.9%
( 6
 
4.9%
) 6
 
4.9%
2 5
 
4.1%

필지정보용도구역
Categorical

IMBALANCE 

Distinct29
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8281 
농업진흥구역
1361 
농업보호구역
 
206
농업진흥지역
 
71
보전관리지역
 
17
Other values (24)
 
64

Length

Max length29
Median length4
Mean length4.3516
Min length4

Unique

Unique12 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8281
82.8%
농업진흥구역 1361
 
13.6%
농업보호구역 206
 
2.1%
농업진흥지역 71
 
0.7%
보전관리지역 17
 
0.2%
상대정화구역 9
 
0.1%
하수처리예정구역 9
 
0.1%
준보전산지 7
 
0.1%
하천구역 4
 
< 0.1%
공익용산지 4
 
< 0.1%
Other values (19) 31
 
0.3%

Length

2023-12-12T09:55:50.472142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8281
82.7%
농업진흥구역 1365
 
13.6%
농업보호구역 208
 
2.1%
농업진흥지역 71
 
0.7%
보전관리지역 17
 
0.2%
상대정화구역 9
 
0.1%
하수처리예정구역 9
 
0.1%
접도구역 9
 
0.1%
준보전산지 7
 
0.1%
하천구역 5
 
< 0.1%
Other values (18) 28
 
0.3%

현지조사순번
Real number (ℝ)

MISSING 

Distinct5879
Distinct (%)61.2%
Missing388
Missing (%)3.9%
Infinite0
Infinite (%)0.0%
Mean7754.1852
Minimum3
Maximum18382
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T09:55:50.624275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile1805
Q14779.75
median7747.5
Q310824.25
95-th percentile14117.45
Maximum18382
Range18379
Interquartile range (IQR)6044.5

Descriptive statistics

Standard deviation3718.2015
Coefficient of variation (CV)0.47950899
Kurtosis-0.70031681
Mean7754.1852
Median Absolute Deviation (MAD)2996.5
Skewness0.071701559
Sum74533228
Variance13825022
MonotonicityNot monotonic
2023-12-12T09:55:50.824525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12013 10
 
0.1%
7407 10
 
0.1%
4642 8
 
0.1%
4568 8
 
0.1%
11413 7
 
0.1%
5917 7
 
0.1%
103 7
 
0.1%
8170 7
 
0.1%
6941 7
 
0.1%
6261 7
 
0.1%
Other values (5869) 9534
95.3%
(Missing) 388
 
3.9%
ValueCountFrequency (%)
3 4
< 0.1%
36 1
 
< 0.1%
91 4
< 0.1%
92 2
< 0.1%
94 4
< 0.1%
95 4
< 0.1%
96 1
 
< 0.1%
97 3
< 0.1%
99 4
< 0.1%
100 2
< 0.1%
ValueCountFrequency (%)
18382 1
< 0.1%
18381 1
< 0.1%
17432 1
< 0.1%
17428 2
< 0.1%
17427 1
< 0.1%
17425 2
< 0.1%
17424 1
< 0.1%
17417 2
< 0.1%
17416 2
< 0.1%
16769 1
< 0.1%

현지조사물건개수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
7591 
1
2309 
2
 
74
3
 
23
4
 
3

Length

Max length4
Median length4
Mean length3.2773
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row<NA>
3rd row1
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 7591
75.9%
1 2309
 
23.1%
2 74
 
0.7%
3 23
 
0.2%
4 3
 
< 0.1%

Length

2023-12-12T09:55:50.996133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:55:51.115144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7591
75.9%
1 2309
 
23.1%
2 74
 
0.7%
3 23
 
0.2%
4 3
 
< 0.1%

배점거리
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing387
Missing (%)3.9%
Memory size156.2 KiB

용도1
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)0.1%
Missing387
Missing (%)3.9%
Infinite0
Infinite (%)0.0%
Mean1.995787
Minimum0
Maximum60
Zeros8443
Zeros (%)84.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T09:55:51.229641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile20
Maximum60
Range60
Interquartile range (IQR)0

Descriptive statistics

Standard deviation6.2900823
Coefficient of variation (CV)3.1516802
Kurtosis11.565886
Mean1.995787
Median Absolute Deviation (MAD)0
Skewness3.4477497
Sum19185.5
Variance39.565135
MonotonicityNot monotonic
2023-12-12T09:55:51.361946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0.0 8443
84.4%
5.0 276
 
2.8%
20.0 250
 
2.5%
30.0 246
 
2.5%
15.0 190
 
1.9%
10.0 146
 
1.5%
3.0 26
 
0.3%
25.0 26
 
0.3%
40.0 8
 
0.1%
7.5 1
 
< 0.1%
(Missing) 387
 
3.9%
ValueCountFrequency (%)
0.0 8443
84.4%
3.0 26
 
0.3%
5.0 276
 
2.8%
7.5 1
 
< 0.1%
10.0 146
 
1.5%
15.0 190
 
1.9%
20.0 250
 
2.5%
25.0 26
 
0.3%
30.0 246
 
2.5%
40.0 8
 
0.1%
ValueCountFrequency (%)
60.0 1
 
< 0.1%
40.0 8
 
0.1%
30.0 246
2.5%
25.0 26
 
0.3%
20.0 250
2.5%
15.0 190
1.9%
10.0 146
1.5%
7.5 1
 
< 0.1%
5.0 276
2.8%
3.0 26
 
0.3%

용도2
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8356 
0
1643 
30
 
1

Length

Max length4
Median length4
Mean length3.5069
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row0
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
<NA> 8356
83.6%
0 1643
 
16.4%
30 1
 
< 0.1%

Length

2023-12-12T09:55:51.530218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:55:51.670056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8356
83.6%
0 1643
 
16.4%
30 1
 
< 0.1%

용도3
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8356 
0
1641 
30
 
3

Length

Max length4
Median length4
Mean length3.5071
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row0
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
<NA> 8356
83.6%
0 1641
 
16.4%
30 3
 
< 0.1%

Length

2023-12-12T09:55:51.785918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:55:52.245770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8356
83.6%
0 1641
 
16.4%
30 3
 
< 0.1%

용도4
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8356 
0
1642 
15
 
1
20
 
1

Length

Max length4
Median length4
Mean length3.507
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row0
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
<NA> 8356
83.6%
0 1642
 
16.4%
15 1
 
< 0.1%
20 1
 
< 0.1%

Length

2023-12-12T09:55:52.409393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:55:52.555105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8356
83.6%
0 1642
 
16.4%
15 1
 
< 0.1%
20 1
 
< 0.1%

용도5
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8356 
0
1644 

Length

Max length4
Median length4
Mean length3.5068
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row0
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
<NA> 8356
83.6%
0 1644
 
16.4%

Length

2023-12-12T09:55:52.705621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:55:52.842688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8356
83.6%
0 1644
 
16.4%

용도6
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8356 
0
1633 
30
 
4
20
 
3
45
 
2

Length

Max length4
Median length4
Mean length3.5079
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row0
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
<NA> 8356
83.6%
0 1633
 
16.3%
30 4
 
< 0.1%
20 3
 
< 0.1%
45 2
 
< 0.1%
50 2
 
< 0.1%

Length

2023-12-12T09:55:52.970345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:55:53.094592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8356
83.6%
0 1633
 
16.3%
30 4
 
< 0.1%
20 3
 
< 0.1%
45 2
 
< 0.1%
50 2
 
< 0.1%

용도7
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8356 
0
1638 
15
 
3
40
 
2
20
 
1

Length

Max length4
Median length4
Mean length3.5074
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row0
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
<NA> 8356
83.6%
0 1638
 
16.4%
15 3
 
< 0.1%
40 2
 
< 0.1%
20 1
 
< 0.1%

Length

2023-12-12T09:55:53.276515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:55:53.430752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8356
83.6%
0 1638
 
16.4%
15 3
 
< 0.1%
40 2
 
< 0.1%
20 1
 
< 0.1%

용도8
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8356 
0
1641 
15
 
3

Length

Max length4
Median length4
Mean length3.5071
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row0
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
<NA> 8356
83.6%
0 1641
 
16.4%
15 3
 
< 0.1%

Length

2023-12-12T09:55:53.566980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:55:53.687630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8356
83.6%
0 1641
 
16.4%
15 3
 
< 0.1%

용도9
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8356 
0
1643 
25
 
1

Length

Max length4
Median length4
Mean length3.5069
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row0
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
<NA> 8356
83.6%
0 1643
 
16.4%
25 1
 
< 0.1%

Length

2023-12-12T09:55:53.805089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:55:53.925505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8356
83.6%
0 1643
 
16.4%
25 1
 
< 0.1%

용도10
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8356 
0
1640 
5
 
2
27
 
2

Length

Max length4
Median length4
Mean length3.507
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row0
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
<NA> 8356
83.6%
0 1640
 
16.4%
5 2
 
< 0.1%
27 2
 
< 0.1%

Length

2023-12-12T09:55:54.053700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:55:54.181122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8356
83.6%
0 1640
 
16.4%
5 2
 
< 0.1%
27 2
 
< 0.1%

용도11
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)0.4%
Missing8356
Missing (%)83.6%
Infinite0
Infinite (%)0.0%
Mean0.51034063
Minimum0
Maximum40
Zeros1615
Zeros (%)16.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T09:55:54.342812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum40
Range40
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4.0471073
Coefficient of variation (CV)7.9302079
Kurtosis71.753546
Mean0.51034063
Median Absolute Deviation (MAD)0
Skewness8.3965071
Sum839
Variance16.379077
MonotonicityNot monotonic
2023-12-12T09:55:54.504678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 1615
 
16.2%
20 10
 
0.1%
36 9
 
0.1%
40 7
 
0.1%
15 2
 
< 0.1%
5 1
 
< 0.1%
(Missing) 8356
83.6%
ValueCountFrequency (%)
0 1615
16.2%
5 1
 
< 0.1%
15 2
 
< 0.1%
20 10
 
0.1%
36 9
 
0.1%
40 7
 
0.1%
ValueCountFrequency (%)
40 7
 
0.1%
36 9
 
0.1%
20 10
 
0.1%
15 2
 
< 0.1%
5 1
 
< 0.1%
0 1615
16.2%

용도12
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)0.5%
Missing8356
Missing (%)83.6%
Infinite0
Infinite (%)0.0%
Mean1.426399
Minimum0
Maximum45
Zeros1547
Zeros (%)15.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T09:55:54.665391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile10
Maximum45
Range45
Interquartile range (IQR)0

Descriptive statistics

Standard deviation6.285004
Coefficient of variation (CV)4.4062032
Kurtosis21.391306
Mean1.426399
Median Absolute Deviation (MAD)0
Skewness4.6516331
Sum2345
Variance39.501275
MonotonicityNot monotonic
2023-12-12T09:55:54.787226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0.0 1547
 
15.5%
30.0 28
 
0.3%
27.0 26
 
0.3%
15.0 14
 
0.1%
5.0 11
 
0.1%
10.0 7
 
0.1%
40.5 6
 
0.1%
45.0 5
 
0.1%
(Missing) 8356
83.6%
ValueCountFrequency (%)
0.0 1547
15.5%
5.0 11
 
0.1%
10.0 7
 
0.1%
15.0 14
 
0.1%
27.0 26
 
0.3%
30.0 28
 
0.3%
40.5 6
 
0.1%
45.0 5
 
0.1%
ValueCountFrequency (%)
45.0 5
 
0.1%
40.5 6
 
0.1%
30.0 28
 
0.3%
27.0 26
 
0.3%
15.0 14
 
0.1%
10.0 7
 
0.1%
5.0 11
 
0.1%
0.0 1547
15.5%

용도13
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)0.5%
Missing8356
Missing (%)83.6%
Infinite0
Infinite (%)0.0%
Mean10.758516
Minimum0
Maximum45
Zeros691
Zeros (%)6.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T09:55:54.948052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q320
95-th percentile30
Maximum45
Range45
Interquartile range (IQR)20

Descriptive statistics

Standard deviation12.322375
Coefficient of variation (CV)1.1453601
Kurtosis-0.62034601
Mean10.758516
Median Absolute Deviation (MAD)5
Skewness0.79752315
Sum17687
Variance151.84092
MonotonicityNot monotonic
2023-12-12T09:55:55.090960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0.0 691
 
6.9%
5.0 279
 
2.8%
30.0 186
 
1.9%
15.0 173
 
1.7%
27.0 149
 
1.5%
20.0 130
 
1.3%
45.0 30
 
0.3%
7.5 3
 
< 0.1%
40.5 3
 
< 0.1%
(Missing) 8356
83.6%
ValueCountFrequency (%)
0.0 691
6.9%
5.0 279
2.8%
7.5 3
 
< 0.1%
15.0 173
 
1.7%
20.0 130
 
1.3%
27.0 149
 
1.5%
30.0 186
 
1.9%
40.5 3
 
< 0.1%
45.0 30
 
0.3%
ValueCountFrequency (%)
45.0 30
 
0.3%
40.5 3
 
< 0.1%
30.0 186
 
1.9%
27.0 149
 
1.5%
20.0 130
 
1.3%
15.0 173
 
1.7%
7.5 3
 
< 0.1%
5.0 279
2.8%
0.0 691
6.9%

용도14
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)0.4%
Missing8356
Missing (%)83.6%
Infinite0
Infinite (%)0.0%
Mean0.48296837
Minimum0
Maximum15
Zeros1524
Zeros (%)15.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T09:55:55.204735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum15
Range15
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.1666036
Coefficient of variation (CV)4.4860155
Kurtosis29.628164
Mean0.48296837
Median Absolute Deviation (MAD)0
Skewness5.3390017
Sum794
Variance4.6941711
MonotonicityNot monotonic
2023-12-12T09:55:55.357474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 1524
 
15.2%
2 48
 
0.5%
7 40
 
0.4%
15 21
 
0.2%
13 7
 
0.1%
3 4
 
< 0.1%
(Missing) 8356
83.6%
ValueCountFrequency (%)
0 1524
15.2%
2 48
 
0.5%
3 4
 
< 0.1%
7 40
 
0.4%
13 7
 
0.1%
15 21
 
0.2%
ValueCountFrequency (%)
15 21
 
0.2%
13 7
 
0.1%
7 40
 
0.4%
3 4
 
< 0.1%
2 48
 
0.5%
0 1524
15.2%

용도15
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)0.5%
Missing8356
Missing (%)83.6%
Infinite0
Infinite (%)0.0%
Mean0.41909976
Minimum0
Maximum30
Zeros1601
Zeros (%)16.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T09:55:55.507550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum30
Range30
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.9226423
Coefficient of variation (CV)6.9736198
Kurtosis58.666307
Mean0.41909976
Median Absolute Deviation (MAD)0
Skewness7.517697
Sum689
Variance8.5418383
MonotonicityNot monotonic
2023-12-12T09:55:55.633420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 1601
 
16.0%
20 10
 
0.1%
18 9
 
0.1%
10 8
 
0.1%
1 7
 
0.1%
30 5
 
0.1%
25 3
 
< 0.1%
15 1
 
< 0.1%
(Missing) 8356
83.6%
ValueCountFrequency (%)
0 1601
16.0%
1 7
 
0.1%
10 8
 
0.1%
15 1
 
< 0.1%
18 9
 
0.1%
20 10
 
0.1%
25 3
 
< 0.1%
30 5
 
0.1%
ValueCountFrequency (%)
30 5
 
0.1%
25 3
 
< 0.1%
20 10
 
0.1%
18 9
 
0.1%
15 1
 
< 0.1%
10 8
 
0.1%
1 7
 
0.1%
0 1601
16.0%

규제1
Real number (ℝ)

MISSING  ZEROS 

Distinct15
Distinct (%)0.2%
Missing387
Missing (%)3.9%
Infinite0
Infinite (%)0.0%
Mean2.697597
Minimum0
Maximum40
Zeros8572
Zeros (%)85.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T09:55:55.754704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile20
Maximum40
Range40
Interquartile range (IQR)0

Descriptive statistics

Standard deviation8.1808834
Coefficient of variation (CV)3.0326559
Kurtosis8.0736143
Mean2.697597
Median Absolute Deviation (MAD)0
Skewness3.019906
Sum25932
Variance66.926853
MonotonicityNot monotonic
2023-12-12T09:55:55.899701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0.0 8572
85.7%
20.0 573
 
5.7%
35.0 317
 
3.2%
40.0 33
 
0.3%
25.0 30
 
0.3%
10.0 25
 
0.2%
15.0 24
 
0.2%
18.0 9
 
0.1%
30.0 9
 
0.1%
27.0 6
 
0.1%
Other values (5) 15
 
0.1%
(Missing) 387
 
3.9%
ValueCountFrequency (%)
0.0 8572
85.7%
1.5 1
 
< 0.1%
3.0 2
 
< 0.1%
5.0 5
 
0.1%
7.5 3
 
< 0.1%
10.0 25
 
0.2%
12.0 4
 
< 0.1%
15.0 24
 
0.2%
18.0 9
 
0.1%
20.0 573
 
5.7%
ValueCountFrequency (%)
40.0 33
 
0.3%
35.0 317
3.2%
30.0 9
 
0.1%
27.0 6
 
0.1%
25.0 30
 
0.3%
20.0 573
5.7%
18.0 9
 
0.1%
15.0 24
 
0.2%
12.0 4
 
< 0.1%
10.0 25
 
0.2%

규제2
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)0.5%
Missing8356
Missing (%)83.6%
Infinite0
Infinite (%)0.0%
Mean7.6952555
Minimum0
Maximum35
Zeros933
Zeros (%)9.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T09:55:56.044183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q318
95-th percentile25
Maximum35
Range35
Interquartile range (IQR)18

Descriptive statistics

Standard deviation9.9764276
Coefficient of variation (CV)1.2964388
Kurtosis-0.73026417
Mean7.6952555
Median Absolute Deviation (MAD)0
Skewness0.83613284
Sum12651
Variance99.529107
MonotonicityNot monotonic
2023-12-12T09:55:56.176395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 933
 
9.3%
18 274
 
2.7%
20 104
 
1.0%
5 101
 
1.0%
25 94
 
0.9%
12 80
 
0.8%
30 38
 
0.4%
35 18
 
0.2%
27 2
 
< 0.1%
(Missing) 8356
83.6%
ValueCountFrequency (%)
0 933
9.3%
5 101
 
1.0%
12 80
 
0.8%
18 274
 
2.7%
20 104
 
1.0%
25 94
 
0.9%
27 2
 
< 0.1%
30 38
 
0.4%
35 18
 
0.2%
ValueCountFrequency (%)
35 18
 
0.2%
30 38
 
0.4%
27 2
 
< 0.1%
25 94
 
0.9%
20 104
 
1.0%
18 274
 
2.7%
12 80
 
0.8%
5 101
 
1.0%
0 933
9.3%

유하1
Real number (ℝ)

MISSING  ZEROS 

Distinct14
Distinct (%)0.1%
Missing387
Missing (%)3.9%
Infinite0
Infinite (%)0.0%
Mean0.92838864
Minimum0
Maximum30
Zeros9073
Zeros (%)90.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T09:55:56.331231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile10
Maximum30
Range30
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4.2156314
Coefficient of variation (CV)4.5408046
Kurtosis26.89285
Mean0.92838864
Median Absolute Deviation (MAD)0
Skewness5.0762703
Sum8924.6
Variance17.771548
MonotonicityNot monotonic
2023-12-12T09:55:56.479653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0.0 9073
90.7%
10.0 149
 
1.5%
15.0 113
 
1.1%
20.0 98
 
1.0%
30.0 96
 
1.0%
7.0 22
 
0.2%
5.0 18
 
0.2%
14.0 17
 
0.2%
22.5 10
 
0.1%
21.0 6
 
0.1%
Other values (4) 11
 
0.1%
(Missing) 387
 
3.9%
ValueCountFrequency (%)
0.0 9073
90.7%
0.2 3
 
< 0.1%
1.5 1
 
< 0.1%
5.0 18
 
0.2%
7.0 22
 
0.2%
7.5 3
 
< 0.1%
10.0 149
 
1.5%
10.5 4
 
< 0.1%
14.0 17
 
0.2%
15.0 113
 
1.1%
ValueCountFrequency (%)
30.0 96
1.0%
22.5 10
 
0.1%
21.0 6
 
0.1%
20.0 98
1.0%
15.0 113
1.1%
14.0 17
 
0.2%
10.5 4
 
< 0.1%
10.0 149
1.5%
7.5 3
 
< 0.1%
7.0 22
 
0.2%

유하2
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)0.5%
Missing8356
Missing (%)83.6%
Infinite0
Infinite (%)0.0%
Mean1.2691606
Minimum0
Maximum20
Zeros1367
Zeros (%)13.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T09:55:56.630631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile10
Maximum20
Range20
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.1930336
Coefficient of variation (CV)2.5158625
Kurtosis8.7199227
Mean1.2691606
Median Absolute Deviation (MAD)0
Skewness2.8498109
Sum2086.5
Variance10.195463
MonotonicityNot monotonic
2023-12-12T09:55:56.794359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0.0 1367
 
13.7%
5.0 106
 
1.1%
10.0 67
 
0.7%
8.0 52
 
0.5%
3.0 28
 
0.3%
15.0 13
 
0.1%
20.0 8
 
0.1%
12.0 2
 
< 0.1%
7.5 1
 
< 0.1%
(Missing) 8356
83.6%
ValueCountFrequency (%)
0.0 1367
13.7%
3.0 28
 
0.3%
5.0 106
 
1.1%
7.5 1
 
< 0.1%
8.0 52
 
0.5%
10.0 67
 
0.7%
12.0 2
 
< 0.1%
15.0 13
 
0.1%
20.0 8
 
0.1%
ValueCountFrequency (%)
20.0 8
 
0.1%
15.0 13
 
0.1%
12.0 2
 
< 0.1%
10.0 67
 
0.7%
8.0 52
 
0.5%
7.5 1
 
< 0.1%
5.0 106
 
1.1%
3.0 28
 
0.3%
0.0 1367
13.7%

점오염1
Real number (ℝ)

MISSING  ZEROS 

Distinct43
Distinct (%)0.4%
Missing387
Missing (%)3.9%
Infinite0
Infinite (%)0.0%
Mean0.089035681
Minimum0
Maximum11
Zeros8719
Zeros (%)87.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T09:55:56.998363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0.4
Maximum11
Range11
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.61349476
Coefficient of variation (CV)6.8904371
Kurtosis200.84564
Mean0.089035681
Median Absolute Deviation (MAD)0
Skewness13.319699
Sum855.9
Variance0.37637582
MonotonicityNot monotonic
2023-12-12T09:55:57.164594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
0.0 8719
87.2%
0.1 127
 
1.3%
0.3 116
 
1.2%
0.2 101
 
1.0%
0.4 85
 
0.9%
0.5 81
 
0.8%
0.7 57
 
0.6%
0.6 55
 
0.5%
0.9 50
 
0.5%
0.8 40
 
0.4%
Other values (33) 182
 
1.8%
(Missing) 387
 
3.9%
ValueCountFrequency (%)
0.0 8719
87.2%
0.1 127
 
1.3%
0.2 101
 
1.0%
0.3 116
 
1.2%
0.4 85
 
0.9%
0.5 81
 
0.8%
0.6 55
 
0.5%
0.7 57
 
0.6%
0.8 40
 
0.4%
0.9 50
 
0.5%
ValueCountFrequency (%)
11.0 2
 
< 0.1%
10.0 23
0.2%
8.5 1
 
< 0.1%
7.7 1
 
< 0.1%
7.0 2
 
< 0.1%
6.9 2
 
< 0.1%
6.5 1
 
< 0.1%
6.4 2
 
< 0.1%
6.0 1
 
< 0.1%
4.6 1
 
< 0.1%

비점오염1
Real number (ℝ)

MISSING  ZEROS 

Distinct38
Distinct (%)2.3%
Missing8356
Missing (%)83.6%
Infinite0
Infinite (%)0.0%
Mean0.24045012
Minimum0
Maximum10
Zeros1084
Zeros (%)10.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T09:55:57.306909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.2
95-th percentile1.1
Maximum10
Range10
Interquartile range (IQR)0.2

Descriptive statistics

Standard deviation0.65030545
Coefficient of variation (CV)2.7045337
Kurtosis80.794595
Mean0.24045012
Median Absolute Deviation (MAD)0
Skewness7.2378406
Sum395.3
Variance0.42289718
MonotonicityNot monotonic
2023-12-12T09:55:57.471723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
0.0 1084
 
10.8%
0.1 89
 
0.9%
0.2 71
 
0.7%
0.3 58
 
0.6%
0.4 55
 
0.5%
0.6 50
 
0.5%
0.5 44
 
0.4%
0.7 36
 
0.4%
0.8 31
 
0.3%
1.1 23
 
0.2%
Other values (28) 103
 
1.0%
(Missing) 8356
83.6%
ValueCountFrequency (%)
0.0 1084
10.8%
0.1 89
 
0.9%
0.2 71
 
0.7%
0.3 58
 
0.6%
0.4 55
 
0.5%
0.5 44
 
0.4%
0.6 50
 
0.5%
0.7 36
 
0.4%
0.8 31
 
0.3%
0.9 21
 
0.2%
ValueCountFrequency (%)
10.0 2
< 0.1%
7.5 1
 
< 0.1%
5.5 1
 
< 0.1%
4.6 1
 
< 0.1%
4.5 3
< 0.1%
3.9 2
< 0.1%
3.5 4
< 0.1%
3.3 1
 
< 0.1%
3.0 1
 
< 0.1%
2.9 2
< 0.1%

연접1
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)0.1%
Missing592
Missing (%)5.9%
Infinite0
Infinite (%)0.0%
Mean0.16011905
Minimum0
Maximum20
Zeros9189
Zeros (%)91.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T09:55:57.611951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum20
Range20
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.1347107
Coefficient of variation (CV)7.0866693
Kurtosis89.023073
Mean0.16011905
Median Absolute Deviation (MAD)0
Skewness8.5263918
Sum1506.4
Variance1.2875685
MonotonicityNot monotonic
2023-12-12T09:55:57.746200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0.0 9189
91.9%
5.0 120
 
1.2%
10.0 46
 
0.5%
8.0 43
 
0.4%
20.0 5
 
0.1%
0.7 2
 
< 0.1%
0.5 1
 
< 0.1%
0.3 1
 
< 0.1%
0.2 1
 
< 0.1%
(Missing) 592
 
5.9%
ValueCountFrequency (%)
0.0 9189
91.9%
0.2 1
 
< 0.1%
0.3 1
 
< 0.1%
0.5 1
 
< 0.1%
0.7 2
 
< 0.1%
5.0 120
 
1.2%
8.0 43
 
0.4%
10.0 46
 
0.5%
20.0 5
 
0.1%
ValueCountFrequency (%)
20.0 5
 
0.1%
10.0 46
 
0.5%
8.0 43
 
0.4%
5.0 120
 
1.2%
0.7 2
 
< 0.1%
0.5 1
 
< 0.1%
0.3 1
 
< 0.1%
0.2 1
 
< 0.1%
0.0 9189
91.9%

감정평가대상토지_순번
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

감정평가대상건물_개수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

전략매수토지_번호
Real number (ℝ)

MISSING 

Distinct851
Distinct (%)56.1%
Missing8482
Missing (%)84.8%
Infinite0
Infinite (%)0.0%
Mean20286.07
Minimum51
Maximum46069
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T09:55:57.886611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum51
5-th percentile1396.4
Q15006.75
median11470
Q339345
95-th percentile44025
Maximum46069
Range46018
Interquartile range (IQR)34338.25

Descriptive statistics

Standard deviation16584.999
Coefficient of variation (CV)0.81755603
Kurtosis-1.6705539
Mean20286.07
Median Absolute Deviation (MAD)9451
Skewness0.30825666
Sum30794255
Variance2.750622 × 108
MonotonicityNot monotonic
2023-12-12T09:55:58.022663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
44003 8
 
0.1%
1574 8
 
0.1%
39484 7
 
0.1%
154 7
 
0.1%
32913 6
 
0.1%
44011 6
 
0.1%
39490 6
 
0.1%
44009 6
 
0.1%
44014 6
 
0.1%
39471 6
 
0.1%
Other values (841) 1452
 
14.5%
(Missing) 8482
84.8%
ValueCountFrequency (%)
51 1
< 0.1%
54 1
< 0.1%
57 2
< 0.1%
59 1
< 0.1%
62 1
< 0.1%
77 1
< 0.1%
80 2
< 0.1%
86 2
< 0.1%
88 1
< 0.1%
89 1
< 0.1%
ValueCountFrequency (%)
46069 1
 
< 0.1%
46066 2
< 0.1%
46001 1
 
< 0.1%
45955 3
< 0.1%
45692 2
< 0.1%
45542 2
< 0.1%
45424 3
< 0.1%
45134 1
 
< 0.1%
45132 2
< 0.1%
45129 1
 
< 0.1%

감정평가의뢰_번호
Real number (ℝ)

MISSING 

Distinct7139
Distinct (%)81.6%
Missing1249
Missing (%)12.5%
Infinite0
Infinite (%)0.0%
Mean7193.5217
Minimum4
Maximum16842
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T09:55:58.151934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile831.5
Q13669.5
median7033
Q310554
95-th percentile14147
Maximum16842
Range16838
Interquartile range (IQR)6884.5

Descriptive statistics

Standard deviation4144.8972
Coefficient of variation (CV)0.57619861
Kurtosis-0.94164806
Mean7193.5217
Median Absolute Deviation (MAD)3434
Skewness0.14774482
Sum62950508
Variance17180173
MonotonicityNot monotonic
2023-12-12T09:55:58.318460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12390 4
 
< 0.1%
6477 4
 
< 0.1%
12138 4
 
< 0.1%
6000 4
 
< 0.1%
10018 4
 
< 0.1%
3342 4
 
< 0.1%
6651 4
 
< 0.1%
156 4
 
< 0.1%
12137 4
 
< 0.1%
6475 3
 
< 0.1%
Other values (7129) 8712
87.1%
(Missing) 1249
 
12.5%
ValueCountFrequency (%)
4 2
< 0.1%
5 2
< 0.1%
6 2
< 0.1%
13 2
< 0.1%
15 1
< 0.1%
18 1
< 0.1%
19 1
< 0.1%
22 1
< 0.1%
23 2
< 0.1%
24 2
< 0.1%
ValueCountFrequency (%)
16842 1
< 0.1%
16838 1
< 0.1%
16836 1
< 0.1%
16819 1
< 0.1%
16818 1
< 0.1%
16816 1
< 0.1%
16813 1
< 0.1%
16812 1
< 0.1%
16811 1
< 0.1%
16809 1
< 0.1%
Distinct2514
Distinct (%)29.2%
Missing1381
Missing (%)13.8%
Memory size156.2 KiB
2023-12-12T09:55:58.696061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length7.5873071
Min length4

Characters and Unicode

Total characters65395
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique761 ?
Unique (%)8.8%

Sample

1st row2008-125
2nd row2009-454
3rd row13-66
4th row2004-31
5th row2012-18
ValueCountFrequency (%)
2005-429 70
 
0.8%
2004-179 61
 
0.7%
2012-18 56
 
0.6%
2006-272 50
 
0.6%
13-68 43
 
0.5%
2009-131 38
 
0.4%
2015-36 37
 
0.4%
2004 35
 
0.4%
2007-142 33
 
0.4%
2004-234 33
 
0.4%
Other values (2503) 8163
94.7%
2023-12-12T09:55:59.292171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 17526
26.8%
2 11762
18.0%
- 8574
13.1%
1 4751
 
7.3%
4 3703
 
5.7%
9 3623
 
5.5%
5 3588
 
5.5%
8 3340
 
5.1%
6 3114
 
4.8%
3 3054
 
4.7%
Other values (3) 2360
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 56798
86.9%
Dash Punctuation 8574
 
13.1%
Uppercase Letter 22
 
< 0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 17526
30.9%
2 11762
20.7%
1 4751
 
8.4%
4 3703
 
6.5%
9 3623
 
6.4%
5 3588
 
6.3%
8 3340
 
5.9%
6 3114
 
5.5%
3 3054
 
5.4%
7 2337
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 8574
100.0%
Uppercase Letter
ValueCountFrequency (%)
N 22
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 65373
> 99.9%
Latin 22
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 17526
26.8%
2 11762
18.0%
- 8574
13.1%
1 4751
 
7.3%
4 3703
 
5.7%
9 3623
 
5.5%
5 3588
 
5.5%
8 3340
 
5.1%
6 3114
 
4.8%
3 3054
 
4.7%
Other values (2) 2338
 
3.6%
Latin
ValueCountFrequency (%)
N 22
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 65395
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 17526
26.8%
2 11762
18.0%
- 8574
13.1%
1 4751
 
7.3%
4 3703
 
5.7%
9 3623
 
5.5%
5 3588
 
5.5%
8 3340
 
5.1%
6 3114
 
4.8%
3 3054
 
4.7%
Other values (3) 2360
 
3.6%

감정평가토지
Real number (ℝ)

MISSING 

Distinct7110
Distinct (%)81.6%
Missing1286
Missing (%)12.9%
Infinite0
Infinite (%)0.0%
Mean7240.9114
Minimum3
Maximum17207
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T09:55:59.495425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile788.65
Q13717
median7043.5
Q310574
95-th percentile14544.7
Maximum17207
Range17204
Interquartile range (IQR)6857

Descriptive statistics

Standard deviation4223.9015
Coefficient of variation (CV)0.58333838
Kurtosis-0.85829056
Mean7240.9114
Median Absolute Deviation (MAD)3421
Skewness0.19232269
Sum63097302
Variance17841344
MonotonicityNot monotonic
2023-12-12T09:55:59.650465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3364 5
 
0.1%
3530 4
 
< 0.1%
140 4
 
< 0.1%
3797 4
 
< 0.1%
1578 4
 
< 0.1%
12086 4
 
< 0.1%
2876 4
 
< 0.1%
3549 4
 
< 0.1%
12340 4
 
< 0.1%
5668 3
 
< 0.1%
Other values (7100) 8674
86.7%
(Missing) 1286
 
12.9%
ValueCountFrequency (%)
3 1
< 0.1%
4 1
< 0.1%
5 2
< 0.1%
6 2
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
12 1
< 0.1%
14 1
< 0.1%
16 1
< 0.1%
18 1
< 0.1%
ValueCountFrequency (%)
17207 1
< 0.1%
17202 1
< 0.1%
17200 1
< 0.1%
17183 1
< 0.1%
17182 1
< 0.1%
17181 1
< 0.1%
17177 1
< 0.1%
17176 1
< 0.1%
17174 1
< 0.1%
17173 2
< 0.1%

감정평가토지외물건_개수
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)0.3%
Missing7846
Missing (%)78.5%
Infinite0
Infinite (%)0.0%
Mean2.2948004
Minimum2
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T09:55:59.806530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q12
median2
Q32
95-th percentile3
Maximum9
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.77339702
Coefficient of variation (CV)0.33702148
Kurtosis21.676045
Mean2.2948004
Median Absolute Deviation (MAD)0
Skewness4.1292905
Sum4943
Variance0.59814295
MonotonicityNot monotonic
2023-12-12T09:55:59.953141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2 1728
 
17.3%
3 329
 
3.3%
4 51
 
0.5%
6 37
 
0.4%
8 7
 
0.1%
9 2
 
< 0.1%
(Missing) 7846
78.5%
ValueCountFrequency (%)
2 1728
17.3%
3 329
 
3.3%
4 51
 
0.5%
6 37
 
0.4%
8 7
 
0.1%
9 2
 
< 0.1%
ValueCountFrequency (%)
9 2
 
< 0.1%
8 7
 
0.1%
6 37
 
0.4%
4 51
 
0.5%
3 329
 
3.3%
2 1728
17.3%

매매계약대상번호
Real number (ℝ)

Distinct6263
Distinct (%)62.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5091.4077
Minimum1
Maximum16166
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T09:56:00.150032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile417
Q12051
median5014.5
Q37851.25
95-th percentile10370.05
Maximum16166
Range16165
Interquartile range (IQR)5800.25

Descriptive statistics

Standard deviation3250.3393
Coefficient of variation (CV)0.63839698
Kurtosis-1.1551108
Mean5091.4077
Median Absolute Deviation (MAD)2885
Skewness0.13459428
Sum50914077
Variance10564706
MonotonicityNot monotonic
2023-12-12T09:56:00.693116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
992 10
 
0.1%
6308 10
 
0.1%
3358 8
 
0.1%
3347 8
 
0.1%
659 7
 
0.1%
8893 7
 
0.1%
4607 7
 
0.1%
10533 7
 
0.1%
7117 7
 
0.1%
3353 7
 
0.1%
Other values (6253) 9922
99.2%
ValueCountFrequency (%)
1 1
 
< 0.1%
4 3
< 0.1%
7 1
 
< 0.1%
8 2
< 0.1%
9 2
< 0.1%
10 2
< 0.1%
11 2
< 0.1%
14 1
 
< 0.1%
15 3
< 0.1%
19 1
 
< 0.1%
ValueCountFrequency (%)
16166 1
< 0.1%
14791 1
< 0.1%
14257 1
< 0.1%
14256 2
< 0.1%
14242 1
< 0.1%
14040 1
< 0.1%
13723 1
< 0.1%
13446 1
< 0.1%
13322 2
< 0.1%
13321 1
< 0.1%
Distinct367
Distinct (%)33.2%
Missing8893
Missing (%)88.9%
Memory size156.2 KiB
2023-12-12T09:56:00.956914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length223
Median length62
Mean length16.709124
Min length2

Characters and Unicode

Total characters18497
Distinct characters275
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique259 ?
Unique (%)23.4%

Sample

1st row개인매매(소유권이전)
2nd row계약체결신청서 미제출
3rd row소방도로로 계획중으로 생태복원 불가지역으로 매수종결
4th row계약체결신청서 미제출
5th row하천미정비
ValueCountFrequency (%)
미제출 240
 
6.9%
계약체결신청서 198
 
5.7%
제출 150
 
4.3%
매수종결 124
 
3.5%
요청서 123
 
3.5%
취하 123
 
3.5%
매도신청 123
 
3.5%
감정평가후 94
 
2.7%
개인매매(소유권이전 64
 
1.8%
매수종결함 61
 
1.7%
Other values (622) 2200
62.9%
2023-12-12T09:56:01.426975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2451
 
13.3%
927
 
5.0%
645
 
3.5%
624
 
3.4%
581
 
3.1%
574
 
3.1%
509
 
2.8%
473
 
2.6%
469
 
2.5%
391
 
2.1%
Other values (265) 10853
58.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13939
75.4%
Space Separator 2451
 
13.3%
Decimal Number 1097
 
5.9%
Other Punctuation 498
 
2.7%
Open Punctuation 234
 
1.3%
Close Punctuation 234
 
1.3%
Dash Punctuation 40
 
0.2%
Lowercase Letter 2
 
< 0.1%
Math Symbol 1
 
< 0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
927
 
6.7%
645
 
4.6%
624
 
4.5%
581
 
4.2%
574
 
4.1%
509
 
3.7%
473
 
3.4%
469
 
3.4%
391
 
2.8%
368
 
2.6%
Other values (240) 8378
60.1%
Decimal Number
ValueCountFrequency (%)
1 265
24.2%
0 248
22.6%
2 136
12.4%
9 101
 
9.2%
3 72
 
6.6%
6 68
 
6.2%
8 59
 
5.4%
5 51
 
4.6%
4 49
 
4.5%
7 48
 
4.4%
Other Punctuation
ValueCountFrequency (%)
. 291
58.4%
, 143
28.7%
: 41
 
8.2%
/ 12
 
2.4%
" 6
 
1.2%
; 2
 
0.4%
2
 
0.4%
' 1
 
0.2%
Space Separator
ValueCountFrequency (%)
2451
100.0%
Open Punctuation
ValueCountFrequency (%)
( 234
100.0%
Close Punctuation
ValueCountFrequency (%)
) 234
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 40
100.0%
Lowercase Letter
ValueCountFrequency (%)
m 2
100.0%
Math Symbol
ValueCountFrequency (%)
> 1
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13939
75.4%
Common 4556
 
24.6%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
927
 
6.7%
645
 
4.6%
624
 
4.5%
581
 
4.2%
574
 
4.1%
509
 
3.7%
473
 
3.4%
469
 
3.4%
391
 
2.8%
368
 
2.6%
Other values (240) 8378
60.1%
Common
ValueCountFrequency (%)
2451
53.8%
. 291
 
6.4%
1 265
 
5.8%
0 248
 
5.4%
( 234
 
5.1%
) 234
 
5.1%
, 143
 
3.1%
2 136
 
3.0%
9 101
 
2.2%
3 72
 
1.6%
Other values (14) 381
 
8.4%
Latin
ValueCountFrequency (%)
m 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13939
75.4%
ASCII 4555
 
24.6%
Punctuation 2
 
< 0.1%
CJK Compat 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2451
53.8%
. 291
 
6.4%
1 265
 
5.8%
0 248
 
5.4%
( 234
 
5.1%
) 234
 
5.1%
, 143
 
3.1%
2 136
 
3.0%
9 101
 
2.2%
3 72
 
1.6%
Other values (13) 380
 
8.3%
Hangul
ValueCountFrequency (%)
927
 
6.7%
645
 
4.6%
624
 
4.5%
581
 
4.2%
574
 
4.1%
509
 
3.7%
473
 
3.4%
469
 
3.4%
391
 
2.8%
368
 
2.6%
Other values (240) 8378
60.1%
Punctuation
ValueCountFrequency (%)
2
100.0%
CJK Compat
ValueCountFrequency (%)
1
100.0%

매매계약번호
Real number (ℝ)

MISSING 

Distinct3634
Distinct (%)57.6%
Missing3690
Missing (%)36.9%
Infinite0
Infinite (%)0.0%
Mean2513.8824
Minimum2
Maximum6973
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T09:56:01.601421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile275
Q11273.25
median2443.5
Q33608
95-th percentile5197
Maximum6973
Range6971
Interquartile range (IQR)2334.75

Descriptive statistics

Standard deviation1501.7215
Coefficient of variation (CV)0.59737143
Kurtosis-0.69426652
Mean2513.8824
Median Absolute Deviation (MAD)1167
Skewness0.30151078
Sum15862598
Variance2255167.6
MonotonicityNot monotonic
2023-12-12T09:56:01.792612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2004 10
 
0.1%
4038 10
 
0.1%
23 7
 
0.1%
873 7
 
0.1%
1505 7
 
0.1%
2290 7
 
0.1%
4125 7
 
0.1%
4753 6
 
0.1%
1067 6
 
0.1%
3621 6
 
0.1%
Other values (3624) 6237
62.4%
(Missing) 3690
36.9%
ValueCountFrequency (%)
2 4
< 0.1%
3 2
< 0.1%
5 2
< 0.1%
7 1
 
< 0.1%
8 2
< 0.1%
9 3
< 0.1%
11 4
< 0.1%
12 2
< 0.1%
13 4
< 0.1%
14 4
< 0.1%
ValueCountFrequency (%)
6973 2
< 0.1%
6278 1
 
< 0.1%
6276 1
 
< 0.1%
6275 1
 
< 0.1%
6266 2
< 0.1%
6265 1
 
< 0.1%
6263 2
< 0.1%
6262 1
 
< 0.1%
6261 3
< 0.1%
6257 1
 
< 0.1%
Distinct494
Distinct (%)7.8%
Missing3690
Missing (%)36.9%
Memory size156.2 KiB
Minimum2003-11-04 00:00:00
Maximum2016-04-28 00:00:00
2023-12-12T09:56:01.960214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:56:02.143984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

매수완료번호
Real number (ℝ)

MISSING 

Distinct3686
Distinct (%)58.4%
Missing3688
Missing (%)36.9%
Infinite0
Infinite (%)0.0%
Mean2685.9965
Minimum3
Maximum7171
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T09:56:02.336107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile378.55
Q11439.75
median2627
Q33802
95-th percentile5397
Maximum7171
Range7168
Interquartile range (IQR)2362.25

Descriptive statistics

Standard deviation1528.279
Coefficient of variation (CV)0.56898026
Kurtosis-0.71013736
Mean2685.9965
Median Absolute Deviation (MAD)1182
Skewness0.27260767
Sum16954010
Variance2335636.7
MonotonicityNot monotonic
2023-12-12T09:56:02.502558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4217 10
 
0.1%
2111 10
 
0.1%
2397 7
 
0.1%
1612 7
 
0.1%
4304 7
 
0.1%
1173 6
 
0.1%
3800 6
 
0.1%
4185 6
 
0.1%
4953 6
 
0.1%
2740 6
 
0.1%
Other values (3676) 6241
62.4%
(Missing) 3688
36.9%
ValueCountFrequency (%)
3 4
< 0.1%
4 2
< 0.1%
8 1
 
< 0.1%
9 2
< 0.1%
10 1
 
< 0.1%
12 4
< 0.1%
13 2
< 0.1%
14 4
< 0.1%
15 4
< 0.1%
17 1
 
< 0.1%
ValueCountFrequency (%)
7171 2
< 0.1%
6475 1
 
< 0.1%
6473 1
 
< 0.1%
6472 1
 
< 0.1%
6463 2
< 0.1%
6462 1
 
< 0.1%
6460 2
< 0.1%
6459 1
 
< 0.1%
6458 3
< 0.1%
6454 1
 
< 0.1%
Distinct494
Distinct (%)7.8%
Missing3688
Missing (%)36.9%
Memory size156.2 KiB
Minimum2003-11-04 00:00:00
Maximum2016-04-28 00:00:00
2023-12-12T09:56:02.669962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:56:02.873699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

매수완료_거리
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4074
Missing (%)40.7%
Memory size156.2 KiB

매수완료_용도점수
Real number (ℝ)

MISSING  ZEROS 

Distinct18
Distinct (%)1.9%
Missing9030
Missing (%)90.3%
Infinite0
Infinite (%)0.0%
Mean14.831443
Minimum0
Maximum50
Zeros173
Zeros (%)1.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T09:56:03.036223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15
median15
Q327
95-th percentile30
Maximum50
Range50
Interquartile range (IQR)22

Descriptive statistics

Standard deviation12.244992
Coefficient of variation (CV)0.82561027
Kurtosis-0.79679698
Mean14.831443
Median Absolute Deviation (MAD)12
Skewness0.44338463
Sum14386.5
Variance149.93983
MonotonicityNot monotonic
2023-12-12T09:56:03.143584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
5.0 192
 
1.9%
0.0 173
 
1.7%
15.0 156
 
1.6%
30.0 130
 
1.3%
27.0 115
 
1.1%
20.0 92
 
0.9%
2.0 23
 
0.2%
45.0 21
 
0.2%
7.0 19
 
0.2%
18.0 9
 
0.1%
Other values (8) 40
 
0.4%
(Missing) 9030
90.3%
ValueCountFrequency (%)
0.0 173
1.7%
1.0 7
 
0.1%
2.0 23
 
0.2%
5.0 192
1.9%
7.0 19
 
0.2%
7.5 2
 
< 0.1%
10.0 7
 
0.1%
13.0 4
 
< 0.1%
15.0 156
1.6%
18.0 9
 
0.1%
ValueCountFrequency (%)
50.0 2
 
< 0.1%
45.0 21
 
0.2%
40.5 7
 
0.1%
40.0 8
 
0.1%
36.0 3
 
< 0.1%
30.0 130
1.3%
27.0 115
1.1%
20.0 92
0.9%
18.0 9
 
0.1%
15.0 156
1.6%

매수완료_규제점수
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)1.2%
Missing9030
Missing (%)90.3%
Infinite0
Infinite (%)0.0%
Mean10.068041
Minimum0
Maximum40
Zeros439
Zeros (%)4.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T09:56:03.244917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median10
Q318
95-th percentile25
Maximum40
Range40
Interquartile range (IQR)18

Descriptive statistics

Standard deviation10.313607
Coefficient of variation (CV)1.0243906
Kurtosis-1.2043744
Mean10.068041
Median Absolute Deviation (MAD)10
Skewness0.38350657
Sum9766
Variance106.37049
MonotonicityNot monotonic
2023-12-12T09:56:03.365640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0.0 439
 
4.4%
18.0 226
 
2.3%
25.0 75
 
0.8%
20.0 69
 
0.7%
12.0 66
 
0.7%
5.0 42
 
0.4%
30.0 28
 
0.3%
27.0 8
 
0.1%
10.0 7
 
0.1%
40.0 4
 
< 0.1%
Other values (2) 6
 
0.1%
(Missing) 9030
90.3%
ValueCountFrequency (%)
0.0 439
4.4%
5.0 42
 
0.4%
7.5 2
 
< 0.1%
10.0 7
 
0.1%
12.0 66
 
0.7%
18.0 226
2.3%
20.0 69
 
0.7%
25.0 75
 
0.8%
27.0 8
 
0.1%
30.0 28
 
0.3%
ValueCountFrequency (%)
40.0 4
 
< 0.1%
35.0 4
 
< 0.1%
30.0 28
 
0.3%
27.0 8
 
0.1%
25.0 75
 
0.8%
20.0 69
 
0.7%
18.0 226
2.3%
12.0 66
 
0.7%
10.0 7
 
0.1%
7.5 2
 
< 0.1%

매수완료_합병년도
Categorical

IMBALANCE 

Distinct13
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9892 
2009-03-10
 
26
2010-04-02
 
21
2009-03-03
 
15
2009-02-26
 
14
Other values (8)
 
32

Length

Max length10
Median length4
Mean length4.0648
Min length4

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9892
98.9%
2009-03-10 26
 
0.3%
2010-04-02 21
 
0.2%
2009-03-03 15
 
0.1%
2009-02-26 14
 
0.1%
2009-03-04 9
 
0.1%
2009-03-09 8
 
0.1%
2009-03-06 7
 
0.1%
2011-02-18 2
 
< 0.1%
2010-04-01 2
 
< 0.1%
Other values (3) 4
 
< 0.1%

Length

2023-12-12T09:56:03.494528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 9892
98.9%
2009-03-10 26
 
0.3%
2010-04-02 21
 
0.2%
2009-03-03 15
 
0.1%
2009-02-26 14
 
0.1%
2009-03-04 9
 
0.1%
2009-03-09 8
 
0.1%
2009-03-06 7
 
0.1%
2011-02-18 2
 
< 0.1%
2010-04-01 2
 
< 0.1%
Other values (3) 4
 
< 0.1%

매수완료_매각년도
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

매수완료_경계표주년도
Real number (ℝ)

MISSING 

Distinct13
Distinct (%)0.4%
Missing6644
Missing (%)66.4%
Infinite0
Infinite (%)0.0%
Mean2008.5378
Minimum2005
Maximum2017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T09:56:03.600260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2005
5-th percentile2005
Q12005
median2009
Q32010
95-th percentile2015
Maximum2017
Range12
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.3837604
Coefficient of variation (CV)0.0016846884
Kurtosis-0.33623776
Mean2008.5378
Median Absolute Deviation (MAD)3
Skewness0.7704166
Sum6740653
Variance11.449834
MonotonicityNot monotonic
2023-12-12T09:56:03.697661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
2005 977
 
9.8%
2010 593
 
5.9%
2009 490
 
4.9%
2007 281
 
2.8%
2006 274
 
2.7%
2015 168
 
1.7%
2008 135
 
1.4%
2014 130
 
1.3%
2016 119
 
1.2%
2012 76
 
0.8%
Other values (3) 113
 
1.1%
(Missing) 6644
66.4%
ValueCountFrequency (%)
2005 977
9.8%
2006 274
 
2.7%
2007 281
 
2.8%
2008 135
 
1.4%
2009 490
4.9%
2010 593
5.9%
2011 18
 
0.2%
2012 76
 
0.8%
2013 58
 
0.6%
2014 130
 
1.3%
ValueCountFrequency (%)
2017 37
 
0.4%
2016 119
 
1.2%
2015 168
 
1.7%
2014 130
 
1.3%
2013 58
 
0.6%
2012 76
 
0.8%
2011 18
 
0.2%
2010 593
5.9%
2009 490
4.9%
2008 135
 
1.4%

매수완료_안내판년도
Real number (ℝ)

MISSING 

Distinct13
Distinct (%)0.3%
Missing5896
Missing (%)59.0%
Infinite0
Infinite (%)0.0%
Mean2008.5962
Minimum2005
Maximum2017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T09:56:03.796716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2005
5-th percentile2005
Q12005
median2009
Q32010
95-th percentile2016
Maximum2017
Range12
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.2077313
Coefficient of variation (CV)0.0015970015
Kurtosis-0.21700639
Mean2008.5962
Median Absolute Deviation (MAD)3
Skewness0.71156486
Sum8243279
Variance10.28954
MonotonicityNot monotonic
2023-12-12T09:56:03.890228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
2005 1074
 
10.7%
2009 720
 
7.2%
2010 689
 
6.9%
2007 374
 
3.7%
2006 292
 
2.9%
2014 195
 
1.9%
2008 187
 
1.9%
2016 181
 
1.8%
2012 131
 
1.3%
2013 129
 
1.3%
Other values (3) 132
 
1.3%
(Missing) 5896
59.0%
ValueCountFrequency (%)
2005 1074
10.7%
2006 292
 
2.9%
2007 374
 
3.7%
2008 187
 
1.9%
2009 720
7.2%
2010 689
6.9%
2011 63
 
0.6%
2012 131
 
1.3%
2013 129
 
1.3%
2014 195
 
1.9%
ValueCountFrequency (%)
2017 35
 
0.4%
2016 181
 
1.8%
2015 34
 
0.3%
2014 195
 
1.9%
2013 129
 
1.3%
2012 131
 
1.3%
2011 63
 
0.6%
2010 689
6.9%
2009 720
7.2%
2008 187
 
1.9%

매수완료_과수벌목년도
Real number (ℝ)

MISSING 

Distinct10
Distinct (%)1.3%
Missing9211
Missing (%)92.1%
Infinite0
Infinite (%)0.0%
Mean2010.7326
Minimum2008
Maximum2017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T09:56:03.978859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2008
5-th percentile2008
Q12009
median2010
Q32012
95-th percentile2014
Maximum2017
Range9
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.1131006
Coefficient of variation (CV)0.0010509108
Kurtosis-0.084856876
Mean2010.7326
Median Absolute Deviation (MAD)1
Skewness0.96180337
Sum1586468
Variance4.465194
MonotonicityNot monotonic
2023-12-12T09:56:04.068227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
2010 266
 
2.7%
2009 213
 
2.1%
2014 94
 
0.9%
2012 72
 
0.7%
2008 49
 
0.5%
2013 44
 
0.4%
2016 26
 
0.3%
2011 13
 
0.1%
2015 8
 
0.1%
2017 4
 
< 0.1%
(Missing) 9211
92.1%
ValueCountFrequency (%)
2008 49
 
0.5%
2009 213
2.1%
2010 266
2.7%
2011 13
 
0.1%
2012 72
 
0.7%
2013 44
 
0.4%
2014 94
 
0.9%
2015 8
 
0.1%
2016 26
 
0.3%
2017 4
 
< 0.1%
ValueCountFrequency (%)
2017 4
 
< 0.1%
2016 26
 
0.3%
2015 8
 
0.1%
2014 94
 
0.9%
2013 44
 
0.4%
2012 72
 
0.7%
2011 13
 
0.1%
2010 266
2.7%
2009 213
2.1%
2008 49
 
0.5%

매수완료_변동유무
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9601 
origin
 
291
union
 
108

Length

Max length6
Median length4
Mean length4.069
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9601
96.0%
origin 291
 
2.9%
union 108
 
1.1%

Length

2023-12-12T09:56:04.172462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:56:04.266738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9601
96.0%
origin 291
 
2.9%
union 108
 
1.1%

매수완료_용도
Categorical

IMBALANCE 

Distinct13
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
전,답
4794 
<NA>
3926 
공장,양어장
 
241
숙박,음식점
 
207
임야
 
202
Other values (8)
630 

Length

Max length7
Median length6
Mean length3.535
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전,답 4794
47.9%
<NA> 3926
39.3%
공장,양어장 241
 
2.4%
숙박,음식점 207
 
2.1%
임야 202
 
2.0%
축사 159
 
1.6%
주택 151
 
1.5%
대지(잡종지) 135
 
1.4%
기타건물 107
 
1.1%
과수원 35
 
0.4%
Other values (3) 43
 
0.4%

Length

2023-12-12T09:56:04.364139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전,답 4794
47.9%
na 3926
39.3%
공장,양어장 241
 
2.4%
숙박,음식점 207
 
2.1%
임야 202
 
2.0%
축사 159
 
1.6%
주택 151
 
1.5%
대지(잡종지 135
 
1.4%
기타건물 107
 
1.1%
과수원 35
 
0.4%
Other values (3) 43
 
0.4%

매수추진대상_번호
Real number (ℝ)

Distinct6263
Distinct (%)62.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5091.4122
Minimum1
Maximum16168
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T09:56:04.525124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile417
Q12051
median5014.5
Q37851.25
95-th percentile10370.05
Maximum16168
Range16167
Interquartile range (IQR)5800.25

Descriptive statistics

Standard deviation3250.3506
Coefficient of variation (CV)0.63839863
Kurtosis-1.1550457
Mean5091.4122
Median Absolute Deviation (MAD)2885
Skewness0.13461514
Sum50914122
Variance10564779
MonotonicityNot monotonic
2023-12-12T09:56:04.671319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
992 10
 
0.1%
6308 10
 
0.1%
3358 8
 
0.1%
3347 8
 
0.1%
659 7
 
0.1%
8893 7
 
0.1%
4607 7
 
0.1%
10533 7
 
0.1%
7117 7
 
0.1%
3353 7
 
0.1%
Other values (6253) 9922
99.2%
ValueCountFrequency (%)
1 1
 
< 0.1%
4 3
< 0.1%
7 1
 
< 0.1%
8 2
< 0.1%
9 2
< 0.1%
10 2
< 0.1%
11 2
< 0.1%
14 1
 
< 0.1%
15 3
< 0.1%
19 1
 
< 0.1%
ValueCountFrequency (%)
16168 1
< 0.1%
14793 1
< 0.1%
14259 1
< 0.1%
14258 2
< 0.1%
14244 1
< 0.1%
14042 1
< 0.1%
13725 1
< 0.1%
13448 1
< 0.1%
13323 2
< 0.1%
13322 1
< 0.1%

매수추진대상_면적
Real number (ℝ)

MISSING  SKEWED 

Distinct2671
Distinct (%)27.3%
Missing200
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean3028.2943
Minimum0
Maximum730758
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T09:56:04.851206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile115.95
Q1436
median1048
Q32033
95-th percentile5920.45
Maximum730758
Range730758
Interquartile range (IQR)1597

Descriptive statistics

Standard deviation19491.091
Coefficient of variation (CV)6.4363266
Kurtosis749.62088
Mean3028.2943
Median Absolute Deviation (MAD)704
Skewness24.224025
Sum29677284
Variance3.7990263 × 108
MonotonicityNot monotonic
2023-12-12T09:56:05.018114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
400.0 26
 
0.3%
162.0 25
 
0.2%
496.0 24
 
0.2%
330.0 24
 
0.2%
129.0 24
 
0.2%
271.0 23
 
0.2%
264.0 23
 
0.2%
142.0 22
 
0.2%
40.0 21
 
0.2%
1008.0 21
 
0.2%
Other values (2661) 9567
95.7%
(Missing) 200
 
2.0%
ValueCountFrequency (%)
0.0 1
 
< 0.1%
3.0 9
0.1%
4.0 1
 
< 0.1%
5.0 2
 
< 0.1%
6.0 4
< 0.1%
7.0 7
0.1%
8.0 1
 
< 0.1%
9.0 2
 
< 0.1%
10.0 7
0.1%
12.0 1
 
< 0.1%
ValueCountFrequency (%)
730758.0 3
< 0.1%
514403.0 2
< 0.1%
345917.0 3
< 0.1%
264767.0 3
< 0.1%
251050.0 1
 
< 0.1%
229724.0 2
< 0.1%
223740.0 3
< 0.1%
215901.0 2
< 0.1%
202711.0 3
< 0.1%
172076.0 1
 
< 0.1%

Sample

순번접수번호접수일자소유자번호신청자번호매도신청대장번호토지고유코드토지고유코드_코드북용도지역지목면적하천거리우선매수대상지역연접진행사항매매계약체결일하천명농업진흥지역매수현황필지정보순번규제지역필지정보용도지역필지정보용도구역현지조사순번현지조사물건개수배점거리용도1용도2용도3용도4용도5용도6용도7용도8용도9용도10용도11용도12용도13용도14용도15규제1규제2유하1유하2점오염1비점오염1연접1감정평가대상토지_순번감정평가대상건물_개수전략매수토지_번호감정평가의뢰_번호감정평가의뢰번호감정평가토지감정평가토지외물건_개수매매계약대상번호매매계약대상번호_특이사항매매계약번호매매계약_계약체결일매수완료번호매수완료_계약일매수완료_거리매수완료_용도점수매수완료_규제점수매수완료_합병년도매수완료_매각년도매수완료_경계표주년도매수완료_안내판년도매수완료_과수벌목년도매수완료_변동유무매수완료_용도매수추진대상_번호매수추진대상_면적
2425878582006-1-0379-12006-07-127858785878584776025032109190000경상북도 영양군 영양읍 대천리 919관리지역5035.050<NA>0.0매수완료2008-10-02하원천<NA>매매계약7858기타지역(자연마을외)관리지역<NA>104161500.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0.0<NA>0.0<NA>0.0<NA>0.0<NA><NA><NA>100072008-125993327858<NA>32072008-10-0233292008-10-0250<NA><NA><NA><NA>200920092009<NA>전,답78585035.0
1698559622005-1-1059-12005-08-025962596259624717040027105370001경상북도 안동시 임동면 대곡리 537-1<NA>992.0100<NA>0.0매수완료2009-07-24대곡천<NA>매매계약5962수변구역<NA><NA>5929<NA>1000.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0.0<NA>0.0<NA>0.0<NA>0.0<NA><NA><NA>50172009-4544973<NA>5962<NA>15122009-07-2416192009-07-24100<NA><NA><NA><NA><NA><NA><NA><NA>전,답5962992.0
1910966352005-1-1353-12005-12-226635663566354717040027109380000경상북도 안동시 임동면 대곡리 938생산관리지역5639.0500<NA>0.0매수완료2014-02-24대곡천<NA>매매계약6635수변구역생산관리지역<NA>1605715000.000000000000.05.0000.050.00.00.01.90.0<NA><NA><NA>1497913-661521426635<NA>53382014-02-2455382014-02-245005.05.0<NA><NA>20142014<NA><NA>전,답66355639.0
6951942004-1-0007-12004-01-191941941944713034025113120001경상북도 경주시 산내면 신원리 1312-1<NA>1035.050.0<NA>5.0매수완료2004-09-16동창천<NA>매매계약194수변구역<NA><NA>8678<NA>50.05.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>20.0<NA>0.0<NA>0.0<NA>5.0<NA><NA><NA>81512004-318055<NA>194<NA>25612004-09-1626682004-09-1650.0<NA><NA><NA><NA><NA><NA><NA><NA>전,답1941035.0
1549454522005-1-0826-22005-05-125452545254524776031045102660000경상북도 영양군 입암면 병옥리 266열람안됨950.0300.0<NA>0.0매수완료2012-05-31반변천<NA>매매계약5452수변구역열람안됨농업진흥구역14185<NA>300.00.000000000000.015.0000.0250.05.00.30.00.0<NA><NA><NA>137272012-1813850<NA>5452<NA>47892012-05-3149882012-05-31300.015.025.0<NA><NA><NA>2012<NA><NA>전,답5452950.0
2327075522006-1-0243-22006-04-067552755275524776025023106950006경상북도 영양군 영양읍 감천리 695-6농림지역2191.050<NA>0.0감정후포기감정후포기반변천<NA>감정평가7552수변구역농림지역농업진흥구역7820<NA>500.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0.0<NA>0.0<NA>0.0<NA>0.0<NA><NA>15769512008-1566877<NA>7552<NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA>75522191.0
2508681272006-1-0496-32006-12-078127812781274776035034200260002경상북도 영양군 석보면 원리리 산26-2관리지역임야5728.0500.0<NA><NA>종결종결화매천<NA>감정평가8127수변구역관리지역<NA>3480<NA>500.00.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>5.0<NA>10.0<NA>1.9<NA>0.0<NA><NA><NA><NA><NA><NA><NA>8127개인매매(소유권이전)<NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA>81275728.0
430913852004-1-0472-22004-09-061385138513854775025024101000076경상북도 청송군 청송읍 청운리 100-76<NA>70.0300.0<NA>0.0매수완료2005-07-11용전천<NA>매매계약1385수변구역<NA><NA>8277<NA>300.00.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0.0<NA>0.0<NA>0.0<NA>0.0<NA><NA><NA>75162005-1617415<NA>1385<NA>23452005-07-1124522005-07-11300.0<NA><NA><NA><NA><NA><NA><NA><NA>전,답138570.0
95029602004-2-0289-52004-07-199609609604886037028104690003경상남도 산청군 단성면 남사리 469-3<NA>대지18.050.0<NA>0.0감정후포기감정후포기남사천<NA>감정평가960수변구역<NA><NA>11829<NA>50.00.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0.0<NA>0.0<NA>0.0<NA>0.0<NA><NA><NA>118802004-23711835<NA>960<NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA>96018.0
2842291122008-1-0022-22008-02-139112911291124717031036107030000경상북도 안동시 와룡면 도곡리 703자연환경보전지역879.0300.0<NA>0.0매수완료2015-10-12낙동강<NA>매매계약9112기타지역(자연마을외)자연환경보전지역<NA>15688<NA>300.00.000000000000.015.0000.000.00.00.00.00.0<NA><NA><NA>160422015-3616400<NA>9112<NA>58942015-10-1260922015-10-12300.015.00.0<NA><NA><NA><NA><NA><NA>전,답9112<NA>
순번접수번호접수일자소유자번호신청자번호매도신청대장번호토지고유코드토지고유코드_코드북용도지역지목면적하천거리우선매수대상지역연접진행사항매매계약체결일하천명농업진흥지역매수현황필지정보순번규제지역필지정보용도지역필지정보용도구역현지조사순번현지조사물건개수배점거리용도1용도2용도3용도4용도5용도6용도7용도8용도9용도10용도11용도12용도13용도14용도15규제1규제2유하1유하2점오염1비점오염1연접1감정평가대상토지_순번감정평가대상건물_개수전략매수토지_번호감정평가의뢰_번호감정평가의뢰번호감정평가토지감정평가토지외물건_개수매매계약대상번호매매계약대상번호_특이사항매매계약번호매매계약_계약체결일매수완료번호매수완료_계약일매수완료_거리매수완료_용도점수매수완료_규제점수매수완료_합병년도매수완료_매각년도매수완료_경계표주년도매수완료_안내판년도매수완료_과수벌목년도매수완료_변동유무매수완료_용도매수추진대상_번호매수추진대상_면적
31415102722009-1-0231-52009-09-071027210272102724776025023106010012경상북도 영양군 영양읍 감천리 601-12보전관리지역과수원88.0300.0<NA>0.0종결종결반변천<NA>감정평가10272기타지역(자연마을)보전관리지역<NA>13177<NA>300.00.000000000000.020.0000.007.00.00.00.00.0<NA><NA><NA><NA><NA><NA><NA>10272자진취하요청으로 매수종결함<NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA>1027288.0
9402512004-1-0025-22004-02-022512512514775037044102990003경상북도 청송군 진보면 광덕리 299-3<NA>1132.0500.0<NA>0.0감정후포기감정후포기반변천<NA>감정평가251수변구역<NA><NA>9171<NA>500.05.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>20.0<NA>0.0<NA>0.0<NA>0.0<NA><NA><NA>88932004-518811<NA>251<NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA>2511132.0
2054834032005-2-0190-52005-05-303403340334034886037027106380000경상남도 산청군 단성면 길리 638<NA>3034.0300<NA><NA>종결종결남사천<NA>감정평가3403수변구역<NA>농업진흥지역4860<NA>3000.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0.0<NA>0.0<NA>0.0<NA>0.0<NA><NA><NA><NA><NA><NA><NA>3403<NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA>34033034.0
2553668132006-2-0056-22006-03-256813681368134886037032102660004경상남도 산청군 단성면 관정리 266-4<NA>602.0500.0<NA>0.0종결종결자매천<NA>감정평가6813기타지역(자연마을)<NA><NA>3872<NA>500.00.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0.0<NA>0.0<NA>0.0<NA>0.0<NA><NA><NA><NA><NA><NA><NA>6813※ 266-3,-4번지는 2009년02월06일 합병(대표번지:270번지)<NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA>6813602.0
1671858642005-1-1015-22005-07-145864586458644775031032100320002경상북도 청송군 부동면 지리 32-2<NA>1497.0300<NA>0.0감정후포기감정후포기용전천<NA>감정평가5864수변구역<NA><NA>557013000.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0.0<NA>0.0<NA>0.0<NA>0.0<NA><NA><NA>45342009-443453125864매도신청 취하 요청서 제출<NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA>58641497.0
1983732392005-2-0147-82005-03-243239323932394886037028104680002경상남도 산청군 단성면 남사리 468-2<NA>잡종지56.050<NA>0.0매수완료2005-12-22남사천<NA>감정평가3239수변구역<NA><NA>9700<NA>500.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0.0<NA>0.0<NA>0.0<NA>0.0<NA><NA><NA>94352005-4649326<NA>3239<NA>30412005-12-2231482005-12-2250<NA><NA><NA><NA><NA><NA><NA><NA>숙박,음식점323956.0
1862964722005-1-1270-32005-11-186472647264724717039029101900003경상북도 안동시 길안면 구수리 190-3<NA>2112.0300<NA>0.0감정후포기감정후포기용계천<NA>감정평가6472수변구역<NA>농업진흥구역8049<NA>3000.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0.0<NA>0.0<NA>0.0<NA>0.0<NA><NA><NA>72362009-4897126<NA>6472매도신청 취하 요청서 제출<NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA>64722112.0
2314875112006-1-0222-32006-03-237511751175114775036039200580000경상북도 청송군 파천면 어천리 산58농림지역임야8043.050<NA>0.0매수완료2008-10-20용전천<NA>매매계약7511수변구역농림지역<NA>7620<NA>500.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0.0<NA>0.0<NA>0.0<NA>0.0<NA><NA><NA>67032008-4146651<NA>7511<NA>20792008-10-2021862008-10-2050<NA><NA><NA><NA><NA><NA><NA><NA>임야75118043.0
1113938262005-1-0052-62005-01-133826382638264717039032109030000경상북도 안동시 길안면 대곡리 903<NA>1835.050.0<NA><NA>매수완료2007-12-07일락천<NA>매매계약3826수변구역<NA><NA>4360<NA>50.00.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0.0<NA>0.0<NA>0.0<NA>0.0<NA><NA><NA>31372007-593151<NA>3826<NA>9382007-12-0710442007-12-0750.0<NA><NA><NA><NA>20082008<NA><NA>전,답38261835.0
1979732342005-2-0147-32005-03-243234323432344886037028104690003경상남도 산청군 단성면 남사리 469-3<NA>대지18.050<NA>0.0매수완료2005-12-22남사천<NA>감정평가3234수변구역<NA><NA>9701<NA>500.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0.0<NA>0.0<NA>0.0<NA>0.0<NA><NA><NA>94492005-4649342<NA>3234<NA>30432005-12-2231502005-12-2250<NA><NA><NA><NA><NA><NA><NA><NA>숙박,음식점323418.0

Duplicate rows

Most frequently occurring

순번접수번호접수일자소유자번호신청자번호매도신청대장번호토지고유코드토지고유코드_코드북용도지역지목면적우선매수대상지역연접진행사항매매계약체결일하천명농업진흥지역매수현황필지정보순번규제지역필지정보용도지역필지정보용도구역현지조사순번현지조사물건개수용도1용도2용도3용도4용도5용도6용도7용도8용도9용도10용도11용도12용도13용도14용도15규제1규제2유하1유하2점오염1비점오염1연접1전략매수토지_번호감정평가의뢰_번호감정평가의뢰번호감정평가토지감정평가토지외물건_개수매매계약대상번호매매계약대상번호_특이사항매매계약번호매매계약_계약체결일매수완료번호매수완료_계약일매수완료_용도점수매수완료_규제점수매수완료_합병년도매수완료_경계표주년도매수완료_안내판년도매수완료_과수벌목년도매수완료_변동유무매수완료_용도매수추진대상_번호매수추진대상_면적# duplicates
090912008-1-0013-12008-01-239091909190914776035038103790001경상북도 영양군 석보면 택전리 379-1농림지역364.0<NA>0.0매수완료2012-06-19화매천<NA>매매계약9091기타지역(자연마을)농림지역<NA>14143<NA>0.000000000000.027.0000.0020.00.00.10.00.0<NA>136712012-1815966<NA>9091<NA>47532012-06-1949532012-06-1927.00.0<NA><NA><NA><NA><NA>전,답9091364.02
190912008-1-0013-12008-01-239091909190914776035038103790001경상북도 영양군 석보면 택전리 379-1농림지역364.0<NA>0.0매수완료2012-06-19화매천<NA>매매계약9091기타지역(자연마을)농림지역<NA>14143<NA>0.000000000000.027.0000.0020.00.00.10.00.0<NA>136722012-1815967<NA>9091<NA>47532012-06-1949532012-06-1927.00.0<NA><NA><NA><NA><NA>전,답9091364.02