Overview

Dataset statistics

Number of variables31
Number of observations3715
Missing cells41914
Missing cells (%)36.4%
Duplicate rows12
Duplicate rows (%)0.3%
Total size in memory943.4 KiB
Average record size in memory260.0 B

Variable types

Numeric9
Text4
Boolean6
Categorical6
DateTime6

Dataset

Description사후관리정보(매수완료번호,토지고유코드,토지고유코드_코드북,순번,매수상황순번,면적,측량,표주,안내판설치 등)
URLhttps://www.data.go.kr/data/15069237/fileData.do

Alerts

종류 has constant value ""Constant
Dataset has 12 (0.3%) duplicate rowsDuplicates
측량 is highly imbalanced (69.0%)Imbalance
표주 is highly imbalanced (78.4%)Imbalance
안내판설치 is highly imbalanced (53.3%)Imbalance
건축물철거 is highly imbalanced (64.0%)Imbalance
폐기물처리 is highly imbalanced (64.6%)Imbalance
공사명 is highly imbalanced (83.1%)Imbalance
가로 is highly imbalanced (87.7%)Imbalance
세로 is highly imbalanced (82.7%)Imbalance
계약명 is highly imbalanced (96.4%)Imbalance
설치업체 is highly imbalanced (93.8%)Imbalance
오염원순번 is highly imbalanced (99.6%)Imbalance
매수상황순번 has 138 (3.7%) missing valuesMissing
안내판순번 has 3306 (89.0%) missing valuesMissing
계약일자 has 3322 (89.4%) missing valuesMissing
착공일 has 3322 (89.4%) missing valuesMissing
준공일 has 3322 (89.4%) missing valuesMissing
측량순번 has 3474 (93.5%) missing valuesMissing
측량날짜 has 3475 (93.5%) missing valuesMissing
비고 has 3506 (94.4%) missing valuesMissing
순번_1 has 3566 (96.0%) missing valuesMissing
계약날짜 has 3594 (96.7%) missing valuesMissing
준공일_1 has 3594 (96.7%) missing valuesMissing
개수 has 3580 (96.4%) missing valuesMissing
종류 has 3714 (> 99.9%) missing valuesMissing
매수완료번호 is highly skewed (γ1 = 45.70745104)Skewed

Reproduction

Analysis started2023-12-12 18:04:58.861571
Analysis finished2023-12-12 18:04:59.751268
Duration0.89 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

매수완료번호
Real number (ℝ)

SKEWED 

Distinct1985
Distinct (%)53.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1687.1661
Minimum1
Maximum1325000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size32.8 KiB
2023-12-13T03:04:59.856353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile75.7
Q1462.5
median968
Q31525.5
95-th percentile1983.3
Maximum1325000
Range1324999
Interquartile range (IQR)1063

Descriptive statistics

Standard deviation24758.365
Coefficient of variation (CV)14.674528
Kurtosis2290.9262
Mean1687.1661
Median Absolute Deviation (MAD)525
Skewness45.707451
Sum6267822
Variance6.1297664 × 108
MonotonicityNot monotonic
2023-12-13T03:05:00.067298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
626 77
 
2.1%
1493 23
 
0.6%
736 22
 
0.6%
360 16
 
0.4%
459 15
 
0.4%
534 12
 
0.3%
53 12
 
0.3%
837 12
 
0.3%
140 11
 
0.3%
352 10
 
0.3%
Other values (1975) 3505
94.3%
ValueCountFrequency (%)
1 1
 
< 0.1%
2 7
0.2%
3 1
 
< 0.1%
4 2
 
0.1%
5 2
 
0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
8 3
0.1%
9 2
 
0.1%
10 1
 
< 0.1%
ValueCountFrequency (%)
1325000 1
< 0.1%
506000 2
0.1%
96500 1
< 0.1%
48000 2
0.1%
10910 1
< 0.1%
9003 1
< 0.1%
9001 2
0.1%
9000 2
0.1%
2090 1
< 0.1%
2089 2
0.1%

토지고유코드
Real number (ℝ)

Distinct3651
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.2502712 × 1018
Minimum3.0110121 × 1018
Maximum4.574036 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size32.8 KiB
2023-12-13T03:05:00.284530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.0110121 × 1018
5-th percentile3.0110127 × 1018
Q14.372037 × 1018
median4.373038 × 1018
Q34.572032 × 1018
95-th percentile4.574025 × 1018
Maximum4.574036 × 1018
Range1.5630239 × 1018
Interquartile range (IQR)1.9999498 × 1017

Descriptive statistics

Standard deviation5.0020455 × 1017
Coefficient of variation (CV)0.11768768
Kurtosis2.1637468
Mean4.2502712 × 1018
Median Absolute Deviation (MAD)6.1903011 × 1016
Skewness-1.9708272
Sum-6.5534252 × 1017
Variance2.5020459 × 1035
MonotonicityNot monotonic
2023-12-13T03:05:00.507774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4311135026100490000 4
 
0.1%
3011012800100180016 4
 
0.1%
3023012100104970001 4
 
0.1%
3011012800100180001 4
 
0.1%
3011012800100180009 4
 
0.1%
4572032022115310000 3
 
0.1%
4572032022115380000 3
 
0.1%
4374036031106400002 2
 
0.1%
4374040025102690001 2
 
0.1%
4572032021108170000 2
 
0.1%
Other values (3641) 3683
99.1%
ValueCountFrequency (%)
3011012100100180014 1
< 0.1%
3011012100101800001 1
< 0.1%
3011012100101800002 1
< 0.1%
3011012100101850000 1
< 0.1%
3011012100101870000 1
< 0.1%
3011012100101870001 1
< 0.1%
3011012100101960000 1
< 0.1%
3011012100102000007 1
< 0.1%
3011012100102010001 1
< 0.1%
3011012100102040000 1
< 0.1%
ValueCountFrequency (%)
4574036022103370000 1
< 0.1%
4574036022103350005 1
< 0.1%
4574036022103350002 1
< 0.1%
4574036022103350001 1
< 0.1%
4574035021113530005 1
< 0.1%
4574035021113530004 1
< 0.1%
4574035021113520001 1
< 0.1%
4574034030203660000 1
< 0.1%
4574034030201400000 1
< 0.1%
4574034030201320000 1
< 0.1%

토지고유코드_코드북
Text

Distinct3651
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size29.2 KiB
2023-12-13T03:05:00.946260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length26
Mean length20.748587
Min length13

Characters and Unicode

Total characters77081
Distinct characters169
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

Unique3599 ?
Unique (%)96.9%

Sample

1st row전라북도 진안군 상전면 월포리 산66-4
2nd row충청북도 옥천군 군북면 석호리 산22-13
3rd row전라북도 진안군 상전면 구룡리 54
4th row전라북도 진안군 상전면 구룡리 802
5th row대전광역시 대덕구 이현동 140
ValueCountFrequency (%)
충청북도 1862
 
10.2%
전라북도 1140
 
6.2%
옥천군 861
 
4.7%
진안군 799
 
4.4%
대전광역시 507
 
2.8%
영동군 460
 
2.5%
동구 399
 
2.2%
심천면 310
 
1.7%
보은군 301
 
1.6%
상전면 254
 
1.4%
Other values (2889) 11409
62.3%
2023-12-13T03:05:01.893907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
14587
 
18.9%
도 3294
 
4.3%
리 3294
 
4.3%
군 3165
 
4.1%
북 3163
 
4.1%
면 2820
 
3.7%
1 2523
 
3.3%
청 2359
 
3.1%
충 2068
 
2.7%
전 1995
 
2.6%
Other values (159) 37813
49.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 47748
61.9%
Space Separator 14587
 
18.9%
Decimal Number 12788
 
16.6%
Dash Punctuation 1958
 
2.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 3294
 
6.9%
리 3294
 
6.9%
군 3165
 
6.6%
북 3163
 
6.6%
면 2820
 
5.9%
청 2359
 
4.9%
충 2068
 
4.3%
전 1995
 
4.2%
천 1985
 
4.2%
동 1672
 
3.5%
Other values (147) 21933
45.9%
Decimal Number
ValueCountFrequency (%)
1 2523
19.7%
2 1957
15.3%
3 1481
11.6%
4 1237
9.7%
5 1150
9.0%
6 982
 
7.7%
9 904
 
7.1%
7 900
 
7.0%
8 889
 
7.0%
0 765
 
6.0%
Space Separator
ValueCountFrequency (%)
14587
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1958
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 47748
61.9%
Common 29333
38.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 3294
 
6.9%
리 3294
 
6.9%
군 3165
 
6.6%
북 3163
 
6.6%
면 2820
 
5.9%
청 2359
 
4.9%
충 2068
 
4.3%
전 1995
 
4.2%
천 1985
 
4.2%
동 1672
 
3.5%
Other values (147) 21933
45.9%
Common
ValueCountFrequency (%)
14587
49.7%
1 2523
 
8.6%
- 1958
 
6.7%
2 1957
 
6.7%
3 1481
 
5.0%
4 1237
 
4.2%
5 1150
 
3.9%
6 982
 
3.3%
9 904
 
3.1%
7 900
 
3.1%
Other values (2) 1654
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 47748
61.9%
ASCII 29333
38.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
14587
49.7%
1 2523
 
8.6%
- 1958
 
6.7%
2 1957
 
6.7%
3 1481
 
5.0%
4 1237
 
4.2%
5 1150
 
3.9%
6 982
 
3.3%
9 904
 
3.1%
7 900
 
3.1%
Other values (2) 1654
 
5.6%
Hangul
ValueCountFrequency (%)
도 3294
 
6.9%
리 3294
 
6.9%
군 3165
 
6.6%
북 3163
 
6.6%
면 2820
 
5.9%
청 2359
 
4.9%
충 2068
 
4.3%
전 1995
 
4.2%
천 1985
 
4.2%
동 1672
 
3.5%
Other values (147) 21933
45.9%

순번
Real number (ℝ)

Distinct3666
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3644.3575
Minimum1
Maximum7593
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size32.8 KiB
2023-12-13T03:05:02.080472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile341.7
Q11377.5
median3548
Q35749
95-th percentile7091.3
Maximum7593
Range7592
Interquartile range (IQR)4371.5

Descriptive statistics

Standard deviation2283.3638
Coefficient of variation (CV)0.6265477
Kurtosis-1.3313927
Mean3644.3575
Median Absolute Deviation (MAD)2189
Skewness0.025316161
Sum13538788
Variance5213750.2
MonotonicityNot monotonic
2023-12-13T03:05:02.277641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
757 4
 
0.1%
5628 4
 
0.1%
2398 2
 
0.1%
6146 2
 
0.1%
50 2
 
0.1%
5674 2
 
0.1%
2555 2
 
0.1%
257 2
 
0.1%
2792 2
 
0.1%
2815 2
 
0.1%
Other values (3656) 3691
99.4%
ValueCountFrequency (%)
1 1
< 0.1%
6 1
< 0.1%
11 1
< 0.1%
12 1
< 0.1%
13 1
< 0.1%
14 1
< 0.1%
15 1
< 0.1%
16 1
< 0.1%
17 1
< 0.1%
18 1
< 0.1%
ValueCountFrequency (%)
7593 1
< 0.1%
7592 1
< 0.1%
7591 1
< 0.1%
7590 2
0.1%
7589 2
0.1%
7588 2
0.1%
7583 1
< 0.1%
7582 1
< 0.1%
7581 1
< 0.1%
7580 1
< 0.1%

매수상황순번
Real number (ℝ)

MISSING 

Distinct3514
Distinct (%)98.2%
Missing138
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean3763.927
Minimum1
Maximum7592
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size32.8 KiB
2023-12-13T03:05:02.456556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile333.8
Q12167
median3619
Q35789
95-th percentile7097.2
Maximum7592
Range7591
Interquartile range (IQR)3622

Descriptive statistics

Standard deviation2253.9769
Coefficient of variation (CV)0.59883651
Kurtosis-1.2539835
Mean3763.927
Median Absolute Deviation (MAD)2095
Skewness-0.063577853
Sum13463567
Variance5080411.9
MonotonicityNot monotonic
2023-12-13T03:05:02.653390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2121 6
 
0.2%
2111 4
 
0.1%
5627 4
 
0.1%
775 4
 
0.1%
2259 3
 
0.1%
2313 3
 
0.1%
592 2
 
0.1%
2396 2
 
0.1%
2380 2
 
0.1%
350 2
 
0.1%
Other values (3504) 3545
95.4%
(Missing) 138
 
3.7%
ValueCountFrequency (%)
1 1
< 0.1%
6 1
< 0.1%
11 1
< 0.1%
12 1
< 0.1%
13 1
< 0.1%
14 1
< 0.1%
15 1
< 0.1%
16 1
< 0.1%
17 1
< 0.1%
18 1
< 0.1%
ValueCountFrequency (%)
7592 1
< 0.1%
7591 1
< 0.1%
7590 1
< 0.1%
7589 2
0.1%
7588 2
0.1%
7587 2
0.1%
7582 1
< 0.1%
7581 1
< 0.1%
7580 1
< 0.1%
7579 1
< 0.1%

면적
Real number (ℝ)

Distinct1923
Distinct (%)51.8%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean4180.1243
Minimum0
Maximum266678
Zeros7
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size32.8 KiB
2023-12-13T03:05:02.823450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile129
Q1485.25
median992
Q31982.25
95-th percentile10070.15
Maximum266678
Range266678
Interquartile range (IQR)1497

Descriptive statistics

Standard deviation17864.808
Coefficient of variation (CV)4.2737504
Kurtosis98.288323
Mean4180.1243
Median Absolute Deviation (MAD)622
Skewness9.1050962
Sum15524982
Variance3.1915135 × 108
MonotonicityNot monotonic
2023-12-13T03:05:02.999843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
962.0 12
 
0.3%
774.0 11
 
0.3%
60.0 10
 
0.3%
674.0 10
 
0.3%
347.0 10
 
0.3%
248.0 10
 
0.3%
1223.0 10
 
0.3%
397.0 10
 
0.3%
238.0 10
 
0.3%
638.0 10
 
0.3%
Other values (1913) 3611
97.2%
ValueCountFrequency (%)
0.0 7
0.2%
1.0 2
 
0.1%
2.0 2
 
0.1%
3.0 1
 
< 0.1%
4.0 1
 
< 0.1%
5.0 1
 
< 0.1%
6.0 2
 
0.1%
9.0 1
 
< 0.1%
10.0 1
 
< 0.1%
11.0 2
 
0.1%
ValueCountFrequency (%)
266678.0 1
< 0.1%
260430.0 1
< 0.1%
251008.0 1
< 0.1%
239628.0 1
< 0.1%
237604.0 1
< 0.1%
233058.0 1
< 0.1%
224769.0 1
< 0.1%
224709.0 1
< 0.1%
202314.0 1
< 0.1%
187934.0 1
< 0.1%

측량
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
False
3508 
True
 
207
ValueCountFrequency (%)
False 3508
94.4%
True 207
 
5.6%
2023-12-13T03:05:03.181965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

표주
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
False
3587 
True
 
128
ValueCountFrequency (%)
False 3587
96.6%
True 128
 
3.4%
2023-12-13T03:05:03.303997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

안내판설치
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
False
3346 
True
369 
ValueCountFrequency (%)
False 3346
90.1%
True 369
 
9.9%
2023-12-13T03:05:03.469630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

건축물철거
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
False
3461 
True
 
254
ValueCountFrequency (%)
False 3461
93.2%
True 254
 
6.8%
2023-12-13T03:05:03.613132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

폐기물처리
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
False
3467 
True
 
248
ValueCountFrequency (%)
False 3467
93.3%
True 248
 
6.7%
2023-12-13T03:05:03.734185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

생태복원
Boolean

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
True
1865 
False
1850 
ValueCountFrequency (%)
True 1865
50.2%
False 1850
49.8%
2023-12-13T03:05:03.858393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

접수번호
Text

Distinct1989
Distinct (%)53.5%
Missing0
Missing (%)0.0%
Memory size29.2 KiB
2023-12-13T03:05:04.332719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length3.6629879
Min length1

Characters and Unicode

Total characters13608
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

Unique1207 ?
Unique (%)32.5%

Sample

1st row2
2nd row14
3rd row2423
4th row2423
5th row2296-1
ValueCountFrequency (%)
72 77
 
2.1%
3445 23
 
0.6%
1895 22
 
0.6%
616 16
 
0.4%
1462 15
 
0.4%
71 12
 
0.3%
2210 12
 
0.3%
1686 12
 
0.3%
221 11
 
0.3%
464 10
 
0.3%
Other values (1979) 3505
94.3%
2023-12-13T03:05:04.937478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 2147
15.8%
3 1937
14.2%
1 1848
13.6%
4 1489
10.9%
7 1097
8.1%
5 1069
7.9%
6 1066
7.8%
9 975
7.2%
0 972
7.1%
8 946
7.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13546
99.5%
Dash Punctuation 62
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 2147
15.8%
3 1937
14.3%
1 1848
13.6%
4 1489
11.0%
7 1097
8.1%
5 1069
7.9%
6 1066
7.9%
9 975
7.2%
0 972
7.2%
8 946
7.0%
Dash Punctuation
ValueCountFrequency (%)
- 62
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13608
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 2147
15.8%
3 1937
14.2%
1 1848
13.6%
4 1489
10.9%
7 1097
8.1%
5 1069
7.9%
6 1066
7.8%
9 975
7.2%
0 972
7.1%
8 946
7.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13608
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 2147
15.8%
3 1937
14.2%
1 1848
13.6%
4 1489
10.9%
7 1097
8.1%
5 1069
7.9%
6 1066
7.8%
9 975
7.2%
0 972
7.1%
8 946
7.0%

안내판순번
Real number (ℝ)

MISSING 

Distinct401
Distinct (%)98.0%
Missing3306
Missing (%)89.0%
Infinite0
Infinite (%)0.0%
Mean220.46455
Minimum2
Maximum456
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size32.8 KiB
2023-12-13T03:05:05.127222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile24.4
Q1109
median216
Q3318
95-th percentile435.6
Maximum456
Range454
Interquartile range (IQR)209

Descriptive statistics

Standard deviation130.57337
Coefficient of variation (CV)0.59226473
Kurtosis-1.0830846
Mean220.46455
Median Absolute Deviation (MAD)105
Skewness0.13661094
Sum90170
Variance17049.406
MonotonicityNot monotonic
2023-12-13T03:05:05.286420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
57 4
 
0.1%
220 2
 
0.1%
91 2
 
0.1%
46 2
 
0.1%
102 2
 
0.1%
79 2
 
0.1%
27 1
 
< 0.1%
280 1
 
< 0.1%
115 1
 
< 0.1%
164 1
 
< 0.1%
Other values (391) 391
 
10.5%
(Missing) 3306
89.0%
ValueCountFrequency (%)
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
11 1
< 0.1%
12 1
< 0.1%
ValueCountFrequency (%)
456 1
< 0.1%
455 1
< 0.1%
454 1
< 0.1%
453 1
< 0.1%
452 1
< 0.1%
451 1
< 0.1%
450 1
< 0.1%
449 1
< 0.1%
448 1
< 0.1%
447 1
< 0.1%

공사명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.2 KiB
<NA>
3544 
2017년 금강수계 매수토지 안내판 신규설치 및 보수·이전 공사
 
75
금강수계 매수토지내 안내표지판 제작설치공사
 
68
수변구역 안내표지만 제작 및 설치공사
 
28

Length

Max length35
Median length4
Mean length5.1017497
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row수변구역 안내표지만 제작 및 설치공사
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 3544
95.4%
2017년 금강수계 매수토지 안내판 신규설치 및 보수·이전 공사 75
 
2.0%
금강수계 매수토지내 안내표지판 제작설치공사 68
 
1.8%
수변구역 안내표지만 제작 및 설치공사 28
 
0.8%

Length

2023-12-13T03:05:05.462802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:05:05.613456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3544
77.8%
금강수계 143
 
3.1%
및 103
 
2.3%
2017년 75
 
1.6%
매수토지 75
 
1.6%
안내판 75
 
1.6%
신규설치 75
 
1.6%
보수·이전 75
 
1.6%
공사 75
 
1.6%
매수토지내 68
 
1.5%
Other values (6) 248
 
5.4%

계약일자
Date

MISSING 

Distinct9
Distinct (%)2.3%
Missing3322
Missing (%)89.4%
Memory size29.2 KiB
Minimum2004-12-24 00:00:00
Maximum2017-10-31 00:00:00
2023-12-13T03:05:05.741159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:05:05.883894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)

착공일
Date

MISSING 

Distinct10
Distinct (%)2.5%
Missing3322
Missing (%)89.4%
Memory size29.2 KiB
Minimum2004-12-24 00:00:00
Maximum2017-10-31 00:00:00
2023-12-13T03:05:06.025881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:05:06.157201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)

준공일
Date

MISSING 

Distinct11
Distinct (%)2.8%
Missing3322
Missing (%)89.4%
Memory size29.2 KiB
Minimum2005-03-28 00:00:00
Maximum2017-12-31 00:00:00
2023-12-13T03:05:06.297500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:05:06.463925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)

가로
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.2 KiB
<NA>
3619 
1.5
 
68
1.2
 
28

Length

Max length4
Median length4
Mean length3.9741588
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3619
97.4%
1.5 68
 
1.8%
1.2 28
 
0.8%

Length

2023-12-13T03:05:06.653795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:05:06.802414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3619
97.4%
1.5 68
 
1.8%
1.2 28
 
0.8%

세로
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.2 KiB
<NA>
3619 
1
 
96

Length

Max length4
Median length4
Mean length3.9224764
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3619
97.4%
1 96
 
2.6%

Length

2023-12-13T03:05:06.958038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:05:07.099580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3619
97.4%
1 96
 
2.6%

측량순번
Real number (ℝ)

MISSING 

Distinct221
Distinct (%)91.7%
Missing3474
Missing (%)93.5%
Infinite0
Infinite (%)0.0%
Mean115.61826
Minimum1
Maximum229
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size32.8 KiB
2023-12-13T03:05:07.244217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile16
Q161
median113
Q3171
95-th percentile219
Maximum229
Range228
Interquartile range (IQR)110

Descriptive statistics

Standard deviation64.929477
Coefficient of variation (CV)0.56158498
Kurtosis-1.1432398
Mean115.61826
Median Absolute Deviation (MAD)55
Skewness0.037042939
Sum27864
Variance4215.837
MonotonicityNot monotonic
2023-12-13T03:05:07.402229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
83 4
 
0.1%
96 4
 
0.1%
61 2
 
0.1%
109 2
 
0.1%
173 2
 
0.1%
82 2
 
0.1%
102 2
 
0.1%
28 2
 
0.1%
222 2
 
0.1%
87 2
 
0.1%
Other values (211) 217
 
5.8%
(Missing) 3474
93.5%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
12 1
< 0.1%
ValueCountFrequency (%)
229 1
< 0.1%
228 1
< 0.1%
227 2
0.1%
226 1
< 0.1%
225 1
< 0.1%
224 1
< 0.1%
223 1
< 0.1%
222 2
0.1%
221 1
< 0.1%
220 1
< 0.1%

측량날짜
Date

MISSING 

Distinct48
Distinct (%)20.0%
Missing3475
Missing (%)93.5%
Memory size29.2 KiB
Minimum2005-01-01 00:00:00
Maximum2018-01-26 00:00:00
2023-12-13T03:05:07.542635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:05:07.685251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)

비고
Text

MISSING 

Distinct179
Distinct (%)85.6%
Missing3506
Missing (%)94.4%
Memory size29.2 KiB
2023-12-13T03:05:08.084407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length7
Mean length4.2440191
Min length1

Characters and Unicode

Total characters887
Distinct characters13
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

Unique155 ?
Unique (%)74.2%

Sample

1st row525-1
2nd row46-1
3rd row383-1
4th row138-1
5th row461-1
ValueCountFrequency (%)
18-9 4
 
1.9%
49 4
 
1.9%
497-1 4
 
1.9%
430-2 2
 
1.0%
545-5 2
 
1.0%
1084-1 2
 
1.0%
664 2
 
1.0%
11-2 2
 
1.0%
1012 2
 
1.0%
535-8 2
 
1.0%
Other values (169) 183
87.6%
2023-12-13T03:05:08.662890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 159
17.9%
- 134
15.1%
2 118
13.3%
3 87
9.8%
4 78
8.8%
5 69
7.8%
9 58
 
6.5%
6 54
 
6.1%
7 44
 
5.0%
8 43
 
4.8%
Other values (3) 43
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 745
84.0%
Dash Punctuation 134
 
15.1%
Other Letter 6
 
0.7%
Other Punctuation 2
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 159
21.3%
2 118
15.8%
3 87
11.7%
4 78
10.5%
5 69
9.3%
9 58
 
7.8%
6 54
 
7.2%
7 44
 
5.9%
8 43
 
5.8%
0 35
 
4.7%
Dash Punctuation
ValueCountFrequency (%)
- 134
100.0%
Other Letter
ValueCountFrequency (%)
산 6
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 881
99.3%
Hangul 6
 
0.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 159
18.0%
- 134
15.2%
2 118
13.4%
3 87
9.9%
4 78
8.9%
5 69
7.8%
9 58
 
6.6%
6 54
 
6.1%
7 44
 
5.0%
8 43
 
4.9%
Other values (2) 37
 
4.2%
Hangul
ValueCountFrequency (%)
산 6
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 881
99.3%
Hangul 6
 
0.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 159
18.0%
- 134
15.2%
2 118
13.4%
3 87
9.9%
4 78
8.9%
5 69
7.8%
9 58
 
6.6%
6 54
 
6.1%
7 44
 
5.0%
8 43
 
4.9%
Other values (2) 37
 
4.2%
Hangul
ValueCountFrequency (%)
산 6
100.0%

순번_1
Real number (ℝ)

MISSING 

Distinct137
Distinct (%)91.9%
Missing3566
Missing (%)96.0%
Infinite0
Infinite (%)0.0%
Mean74.530201
Minimum1
Maximum146
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size32.8 KiB
2023-12-13T03:05:08.833163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.4
Q141
median74
Q3110
95-th percentile138.6
Maximum146
Range145
Interquartile range (IQR)69

Descriptive statistics

Standard deviation41.793824
Coefficient of variation (CV)0.5607636
Kurtosis-1.1183251
Mean74.530201
Median Absolute Deviation (MAD)35
Skewness-0.069050656
Sum11105
Variance1746.7237
MonotonicityNot monotonic
2023-12-13T03:05:08.978356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
66 4
 
0.1%
87 2
 
0.1%
47 2
 
0.1%
74 2
 
0.1%
48 2
 
0.1%
59 2
 
0.1%
2 2
 
0.1%
12 2
 
0.1%
116 2
 
0.1%
69 2
 
0.1%
Other values (127) 127
 
3.4%
(Missing) 3566
96.0%
ValueCountFrequency (%)
1 1
< 0.1%
2 2
0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
11 1
< 0.1%
ValueCountFrequency (%)
146 1
< 0.1%
145 1
< 0.1%
144 1
< 0.1%
143 1
< 0.1%
142 1
< 0.1%
141 1
< 0.1%
140 1
< 0.1%
139 1
< 0.1%
138 1
< 0.1%
137 1
< 0.1%

계약명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.2 KiB
<NA>
3693 
2017년 금강수계 매수토지 경계복원
 
17
16년 경계관목 식재공사 시 표주설치
 
5

Length

Max length20
Median length4
Mean length4.094751
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> 3693
99.4%
2017년 금강수계 매수토지 경계복원 17
 
0.5%
16년 경계관목 식재공사 시 표주설치 5
 
0.1%

Length

2023-12-13T03:05:09.144777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:05:09.290773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3693
97.5%
2017년 17
 
0.4%
금강수계 17
 
0.4%
매수토지 17
 
0.4%
경계복원 17
 
0.4%
16년 5
 
0.1%
경계관목 5
 
0.1%
식재공사 5
 
0.1%
시 5
 
0.1%
표주설치 5
 
0.1%

설치업체
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.2 KiB
<NA>
3674 
자력
 
24
청심조경㈜
 
17

Length

Max length5
Median length4
Mean length3.9916555
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> 3674
98.9%
자력 24
 
0.6%
청심조경㈜ 17
 
0.5%

Length

2023-12-13T03:05:09.440266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:05:09.586140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3674
98.9%
자력 24
 
0.6%
청심조경㈜ 17
 
0.5%

계약날짜
Date

MISSING 

Distinct9
Distinct (%)7.4%
Missing3594
Missing (%)96.7%
Memory size29.2 KiB
Minimum2006-11-16 00:00:00
Maximum2018-01-01 00:00:00
2023-12-13T03:05:10.041385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:05:10.140419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)

준공일_1
Date

MISSING 

Distinct11
Distinct (%)9.1%
Missing3594
Missing (%)96.7%
Memory size29.2 KiB
Minimum2006-12-20 00:00:00
Maximum2019-01-01 00:00:00
2023-12-13T03:05:10.251310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:05:10.353995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)

개수
Real number (ℝ)

MISSING 

Distinct20
Distinct (%)14.8%
Missing3580
Missing (%)96.4%
Infinite0
Infinite (%)0.0%
Mean7.6074074
Minimum2
Maximum50
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size32.8 KiB
2023-12-13T03:05:10.478551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q14
median6
Q310
95-th percentile17.3
Maximum50
Range48
Interquartile range (IQR)6

Descriptive statistics

Standard deviation6.3798848
Coefficient of variation (CV)0.83864113
Kurtosis16.933018
Mean7.6074074
Median Absolute Deviation (MAD)3
Skewness3.2627699
Sum1027
Variance40.70293
MonotonicityNot monotonic
2023-12-13T03:05:10.581008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
2 18
 
0.5%
4 18
 
0.5%
3 14
 
0.4%
6 14
 
0.4%
5 13
 
0.3%
10 10
 
0.3%
7 9
 
0.2%
12 8
 
0.2%
11 7
 
0.2%
9 5
 
0.1%
Other values (10) 19
 
0.5%
(Missing) 3580
96.4%
ValueCountFrequency (%)
2 18
0.5%
3 14
0.4%
4 18
0.5%
5 13
0.3%
6 14
0.4%
7 9
0.2%
8 2
 
0.1%
9 5
 
0.1%
10 10
0.3%
11 7
 
0.2%
ValueCountFrequency (%)
50 1
 
< 0.1%
38 1
 
< 0.1%
21 2
 
0.1%
18 3
 
0.1%
17 1
 
< 0.1%
16 3
 
0.1%
15 1
 
< 0.1%
14 2
 
0.1%
13 3
 
0.1%
12 8
0.2%

오염원순번
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.2 KiB
<NA>
3714 
5
 
1

Length

Max length4
Median length4
Mean length3.9991925
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3714
> 99.9%
5 1
 
< 0.1%

Length

2023-12-13T03:05:10.696232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:05:10.800335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3714
> 99.9%
5 1
 
< 0.1%

종류
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing3714
Missing (%)> 99.9%
Memory size29.2 KiB
2023-12-13T03:05:10.864443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row주택
ValueCountFrequency (%)
주택 1
100.0%
2023-12-13T03:05:11.044499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 1
50.0%
택 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 1
50.0%
택 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 1
50.0%
택 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 1
50.0%
택 1
50.0%

Sample

매수완료번호토지고유코드토지고유코드_코드북순번매수상황순번면적측량표주안내판설치건축물철거폐기물처리생태복원접수번호안내판순번공사명계약일자착공일준공일가로세로측량순번측량날짜비고순번_1계약명설치업체계약날짜준공일_1개수오염원순번종류
014572034024200660004전라북도 진안군 상전면 월포리 산66-411237604.0NNNNNN2<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1104373038032200220013충청북도 옥천군 군북면 석호리 산22-13181827462.0NNYNNN1434수변구역 안내표지만 제작 및 설치공사2004-12-242004-12-242005-03-281.21<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
210004572034025100540000전라북도 진안군 상전면 구룡리 5430503049648.0NNNNNN2423<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
310004572034025108020000전라북도 진안군 상전면 구룡리 80230513050532.0NNNNNN2423<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
410013023012000101400000대전광역시 대덕구 이현동 140301830172469.0NNNNNN2296-1<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
510024372037030102000000충청북도 보은군 회남면 판장리 200286928681864.0NNNNNY1517<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
610024372037030102170000충청북도 보은군 회남면 판장리 21728702869605.0NNNNNY1517<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
710024372037030102180000충청북도 보은군 회남면 판장리 218287128703041.0NNNNNY1517<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
810024372037030102190000충청북도 보은군 회남면 판장리 21928722871840.0NNNNNY1517<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
910033023012100105250000대전광역시 대덕구 갈전동 52528622861864.0NNNNNY2396<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
매수완료번호토지고유코드토지고유코드_코드북순번매수상황순번면적측량표주안내판설치건축물철거폐기물처리생태복원접수번호안내판순번공사명계약일자착공일준공일가로세로측량순번측량날짜비고순번_1계약명설치업체계약날짜준공일_1개수오염원순번종류
37059973011012100103870000대전광역시 동구 추동 387280628053376.0NNYNNN2477177<NA>2012-01-012012-01-012012-12-31<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
37069984372037031101390000충청북도 보은군 회남면 분저리 13928932892407.0NNNNNN2345<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
37079994372037022100560000충청북도 보은군 회남면 금곡리 5653545353278.0NNNNNY1077<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
37089994372037022100570000충청북도 보은군 회남면 금곡리 5753555354245.0NNNNNY1077<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
37099994372037034100940000충청북도 보은군 회남면 매산리 9414792094370.0NNNNNN214<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
37109994372037034101230001충청북도 보은군 회남면 매산리 123-114782093674.0NNNNNN214<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
37119994372037034200250001충청북도 보은군 회남면 매산리 산25-11480209518050.0NNNNNN214<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
37129994373038035200250004충청북도 옥천군 군북면 국원리 산25-41501212180843.0NNNNNN526<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
37139994373038035200250014충청북도 옥천군 군북면 국원리 산25-141502212138184.0NNNNNN526<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
37149994373038035200260000충청북도 옥천군 군북면 국원리 산261503212154141.0NNNNNN526<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

매수완료번호토지고유코드토지고유코드_코드북순번매수상황순번면적측량표주안내판설치건축물철거폐기물처리생태복원접수번호안내판순번공사명계약일자착공일준공일가로세로측량순번측량날짜비고순번_1계약명설치업체계약날짜준공일_1개수오염원순번종류# duplicates
07184373036035100450000충청북도 옥천군 이원면 용방리 4523882387456.0NNNNNY1977<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2
17184373036035100500000충청북도 옥천군 이원면 용방리 50238923881818.0NNNNNY1977<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2
27644572032021108130001전라북도 진안군 안천면 노성리 813-1237923781273.0NNNNNY2242<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2
37644572032021108170000전라북도 진안군 안천면 노성리 817238123802179.0NNNNNY2242<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2
47664572032021108160000전라북도 진안군 안천면 노성리 8162382238160.0NNNNNY2244<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2
57664572032021108160001전라북도 진안군 안천면 노성리 816-1238323821646.0NNNNNY2244<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2
68373011012800100180001대전광역시 동구 세천동 18-123902389625.0NNNNNY2210<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2
78373011012800100180001대전광역시 동구 세천동 18-123962395625.0NNNNNY2210<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2
88373011012800100180009대전광역시 동구 세천동 18-9239123901812.0YYNNNY2210<NA><NA><NA><NA><NA><NA><NA>962012-01-0118-966<NA><NA>2012-01-012012-12-312<NA><NA>2
98373011012800100180009대전광역시 동구 세천동 18-9239723961812.0YYNNNY2210<NA><NA><NA><NA><NA><NA><NA>962012-01-0118-966<NA><NA>2012-01-012012-12-312<NA><NA>2