Overview

Dataset statistics

Number of variables66
Number of observations10000
Missing cells275345
Missing cells (%)41.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.4 MiB
Average record size in memory567.0 B

Variable types

Text5
DateTime6
Numeric28
Categorical25
Boolean2

Dataset

Description토지매수정보(접수번호,접수일자,필지수,필지번호,토지소재지,면적,지목,용도,규제지역,하천명,호소명,거리범례 등)
URLhttps://www.data.go.kr/data/15069693/fileData.do

Alerts

특이사항체크 has constant value ""Constant
변동사항 has constant value ""Constant
지목 is highly imbalanced (50.3%)Imbalance
매수제한지역이름 is highly imbalanced (88.5%)Imbalance
우선매수지역 is highly imbalanced (65.0%)Imbalance
철거여부 is highly imbalanced (52.1%)Imbalance
기타사후관리 is highly imbalanced (52.5%)Imbalance
특이사항 is highly imbalanced (98.6%)Imbalance
공사명 is highly imbalanced (64.0%)Imbalance
공사대상 is highly imbalanced (90.7%)Imbalance
공사명_1 is highly imbalanced (79.7%)Imbalance
계약업체_1 is highly imbalanced (87.3%)Imbalance
차수코드 is highly imbalanced (85.3%)Imbalance
차수 is highly imbalanced (85.3%)Imbalance
하천명 has 3908 (39.1%) missing valuesMissing
비고 has 9799 (98.0%) missing valuesMissing
매매계약일련번호 has 4571 (45.7%) missing valuesMissing
계약체결신청일자 has 4571 (45.7%) missing valuesMissing
토지외물건수 has 7132 (71.3%) missing valuesMissing
기타사후관리번호 has 8983 (89.8%) missing valuesMissing
울타리설치 has 9966 (99.7%) missing valuesMissing
경계측량 has 9576 (95.8%) missing valuesMissing
경고표지판 has 9487 (94.9%) missing valuesMissing
벌목 has 9775 (97.8%) missing valuesMissing
특이사항체크 has 9019 (90.2%) missing valuesMissing
변동사항 has 9018 (90.2%) missing valuesMissing
생태복원번호 has 7262 (72.6%) missing valuesMissing
공사기간시작 has 7262 (72.6%) missing valuesMissing
공사기간종료 has 7262 (72.6%) missing valuesMissing
계약업체 has 8795 (87.9%) missing valuesMissing
공사금액 has 7262 (72.6%) missing valuesMissing
철거번호 has 8969 (89.7%) missing valuesMissing
공사기간시작_1 has 9457 (94.6%) missing valuesMissing
공사기간종료_1 has 9457 (94.6%) missing valuesMissing
처리금액총액 has 9457 (94.6%) missing valuesMissing
처리금액지장물 has 9457 (94.6%) missing valuesMissing
처리금액건설폐기물 has 9457 (94.6%) missing valuesMissing
처리금액지정폐기물 has 9457 (94.6%) missing valuesMissing
건폐발생량 has 9457 (94.6%) missing valuesMissing
지폐발생량 has 9457 (94.6%) missing valuesMissing
건설폐기물발생량파쇄 has 9512 (95.1%) missing valuesMissing
건설폐기물발생량소각 has 9512 (95.1%) missing valuesMissing
지정폐기물발생량석면 has 9512 (95.1%) missing valuesMissing
건설폐기물처리비파쇄 has 9512 (95.1%) missing valuesMissing
건설폐기물처리비소각 has 9512 (95.1%) missing valuesMissing
지정폐기물처리비석면 has 9512 (95.1%) missing valuesMissing
하천과거리 has 281 (2.8%) zerosZeros
공사금액 has 1529 (15.3%) zerosZeros
처리금액지정폐기물 has 126 (1.3%) zerosZeros
지폐발생량 has 126 (1.3%) zerosZeros
건설폐기물발생량파쇄 has 243 (2.4%) zerosZeros
건설폐기물발생량소각 has 334 (3.3%) zerosZeros
지정폐기물발생량석면 has 337 (3.4%) zerosZeros
건설폐기물처리비파쇄 has 243 (2.4%) zerosZeros
건설폐기물처리비소각 has 334 (3.3%) zerosZeros
지정폐기물처리비석면 has 337 (3.4%) zerosZeros

Reproduction

Analysis started2023-12-12 04:53:43.121152
Analysis finished2023-12-12 04:53:45.648170
Duration2.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

접수번호
Text

Distinct7189
Distinct (%)71.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T13:53:45.966613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length9
Mean length8.8835
Min length7

Characters and Unicode

Total characters88835
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

Unique5593 ?
Unique (%)55.9%

Sample

1st row2014-8022
2nd row2007-2087-1
3rd row2003-246
4th row2011-5926
5th row2009-4329
ValueCountFrequency (%)
2011-5926 19
 
0.2%
2003-507 19
 
0.2%
2013-7045 16
 
0.2%
2004-844 13
 
0.1%
2004-679 12
 
0.1%
2005-1254 12
 
0.1%
2003-172 12
 
0.1%
2003-435 12
 
0.1%
2006-1836 11
 
0.1%
2005-1323 11
 
0.1%
Other values (7179) 9863
98.6%
2023-12-12T13:53:46.893214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18749
21.1%
2 15005
16.9%
- 10550
11.9%
1 10076
11.3%
3 5829
 
6.6%
6 5005
 
5.6%
4 4953
 
5.6%
9 4770
 
5.4%
5 4719
 
5.3%
8 4631
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 78285
88.1%
Dash Punctuation 10550
 
11.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 18749
23.9%
2 15005
19.2%
1 10076
12.9%
3 5829
 
7.4%
6 5005
 
6.4%
4 4953
 
6.3%
9 4770
 
6.1%
5 4719
 
6.0%
8 4631
 
5.9%
7 4548
 
5.8%
Dash Punctuation
ValueCountFrequency (%)
- 10550
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 88835
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 18749
21.1%
2 15005
16.9%
- 10550
11.9%
1 10076
11.3%
3 5829
 
6.6%
6 5005
 
5.6%
4 4953
 
5.6%
9 4770
 
5.4%
5 4719
 
5.3%
8 4631
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 88835
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18749
21.1%
2 15005
16.9%
- 10550
11.9%
1 10076
11.3%
3 5829
 
6.6%
6 5005
 
5.6%
4 4953
 
5.6%
9 4770
 
5.4%
5 4719
 
5.3%
8 4631
 
5.2%

접수일자
Date

Distinct1684
Distinct (%)16.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2003-01-14 00:00:00
Maximum2020-09-28 00:00:00
2023-12-12T13:53:47.085382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:47.302465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

필지수
Real number (ℝ)

Distinct26
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.2358
Minimum1
Maximum35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T13:53:47.462050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q33
95-th percentile11
Maximum35
Range34
Interquartile range (IQR)2

Descriptive statistics

Standard deviation4.1908895
Coefficient of variation (CV)1.2951633
Kurtosis17.13435
Mean3.2358
Median Absolute Deviation (MAD)1
Skewness3.6573686
Sum32358
Variance17.563555
MonotonicityNot monotonic
2023-12-12T13:53:47.608441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
1 4348
43.5%
2 2153
21.5%
3 1065
 
10.7%
4 596
 
6.0%
5 395
 
4.0%
6 333
 
3.3%
7 236
 
2.4%
9 119
 
1.2%
8 116
 
1.2%
14 78
 
0.8%
Other values (16) 561
 
5.6%
ValueCountFrequency (%)
1 4348
43.5%
2 2153
21.5%
3 1065
 
10.7%
4 596
 
6.0%
5 395
 
4.0%
6 333
 
3.3%
7 236
 
2.4%
8 116
 
1.2%
9 119
 
1.2%
10 69
 
0.7%
ValueCountFrequency (%)
35 19
 
0.2%
33 16
 
0.2%
29 11
 
0.1%
27 19
 
0.2%
26 13
 
0.1%
23 12
 
0.1%
21 55
0.5%
19 21
 
0.2%
18 39
0.4%
17 7
 
0.1%

필지번호
Real number (ℝ)

Distinct33
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.1104
Minimum1
Maximum35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T13:53:47.790358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile6
Maximum35
Range34
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.5358736
Coefficient of variation (CV)1.201608
Kurtosis32.729455
Mean2.1104
Median Absolute Deviation (MAD)0
Skewness4.7773617
Sum21104
Variance6.4306549
MonotonicityNot monotonic
2023-12-12T13:53:47.957514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
1 6156
61.6%
2 1809
 
18.1%
3 763
 
7.6%
4 395
 
4.0%
5 230
 
2.3%
6 185
 
1.8%
7 104
 
1.0%
8 70
 
0.7%
9 59
 
0.6%
10 35
 
0.4%
Other values (23) 194
 
1.9%
ValueCountFrequency (%)
1 6156
61.6%
2 1809
 
18.1%
3 763
 
7.6%
4 395
 
4.0%
5 230
 
2.3%
6 185
 
1.8%
7 104
 
1.0%
8 70
 
0.7%
9 59
 
0.6%
10 35
 
0.4%
ValueCountFrequency (%)
35 1
 
< 0.1%
34 1
 
< 0.1%
33 1
 
< 0.1%
32 1
 
< 0.1%
31 1
 
< 0.1%
30 1
 
< 0.1%
28 1
 
< 0.1%
27 2
< 0.1%
26 2
< 0.1%
25 3
< 0.1%

토지소재지
Text

Distinct9538
Distinct (%)95.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T13:53:48.397334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length24
Mean length20.9284
Min length17

Characters and Unicode

Total characters209284
Distinct characters146
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

Unique9097 ?
Unique (%)91.0%

Sample

1st row전라남도 순천시 송광면 봉산리 165
2nd row전라남도 보성군 겸백면 석호리 258
3rd row전라남도 보성군 겸백면 석호리 633
4th row전라남도 광양시 진상면 비평리 340-2
5th row전라남도 영암군 금정면 청용리 1096
ValueCountFrequency (%)
전라남도 10000
 
20.0%
순천시 2944
 
5.9%
보성군 2841
 
5.7%
화순군 2714
 
5.4%
사평면 1177
 
2.4%
승주읍 1002
 
2.0%
복내면 992
 
2.0%
송광면 906
 
1.8%
겸백면 757
 
1.5%
백아면 732
 
1.5%
Other values (5028) 25935
51.9%
2023-12-12T13:53:49.101171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
40000
19.1%
남 10606
 
5.1%
전 10276
 
4.9%
도 10234
 
4.9%
라 10000
 
4.8%
리 10000
 
4.8%
면 8984
 
4.3%
군 6564
 
3.1%
1 6225
 
3.0%
순 5658
 
2.7%
Other values (136) 90737
43.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 130299
62.3%
Space Separator 40000
 
19.1%
Decimal Number 34373
 
16.4%
Dash Punctuation 4612
 
2.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 10606
 
8.1%
전 10276
 
7.9%
도 10234
 
7.9%
라 10000
 
7.7%
리 10000
 
7.7%
면 8984
 
6.9%
군 6564
 
5.0%
순 5658
 
4.3%
천 3776
 
2.9%
시 3487
 
2.7%
Other values (124) 50714
38.9%
Decimal Number
ValueCountFrequency (%)
1 6225
18.1%
2 4170
12.1%
3 3653
10.6%
5 3469
10.1%
4 3319
9.7%
6 3255
9.5%
7 2937
8.5%
8 2479
 
7.2%
9 2443
 
7.1%
0 2423
 
7.0%
Space Separator
ValueCountFrequency (%)
40000
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4612
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 130299
62.3%
Common 78985
37.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 10606
 
8.1%
전 10276
 
7.9%
도 10234
 
7.9%
라 10000
 
7.7%
리 10000
 
7.7%
면 8984
 
6.9%
군 6564
 
5.0%
순 5658
 
4.3%
천 3776
 
2.9%
시 3487
 
2.7%
Other values (124) 50714
38.9%
Common
ValueCountFrequency (%)
40000
50.6%
1 6225
 
7.9%
- 4612
 
5.8%
2 4170
 
5.3%
3 3653
 
4.6%
5 3469
 
4.4%
4 3319
 
4.2%
6 3255
 
4.1%
7 2937
 
3.7%
8 2479
 
3.1%
Other values (2) 4866
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 130299
62.3%
ASCII 78985
37.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
40000
50.6%
1 6225
 
7.9%
- 4612
 
5.8%
2 4170
 
5.3%
3 3653
 
4.6%
5 3469
 
4.4%
4 3319
 
4.2%
6 3255
 
4.1%
7 2937
 
3.7%
8 2479
 
3.1%
Other values (2) 4866
 
6.2%
Hangul
ValueCountFrequency (%)
남 10606
 
8.1%
전 10276
 
7.9%
도 10234
 
7.9%
라 10000
 
7.7%
리 10000
 
7.7%
면 8984
 
6.9%
군 6564
 
5.0%
순 5658
 
4.3%
천 3776
 
2.9%
시 3487
 
2.7%
Other values (124) 50714
38.9%

면적
Real number (ℝ)

Distinct3071
Distinct (%)30.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2124.6825
Minimum2
Maximum266876
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T13:53:49.312484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile105
Q1379
median835
Q31660
95-th percentile5141.8
Maximum266876
Range266874
Interquartile range (IQR)1281

Descriptive statistics

Standard deviation7658.504
Coefficient of variation (CV)3.6045404
Kurtosis315.87984
Mean2124.6825
Median Absolute Deviation (MAD)544
Skewness14.30962
Sum21246825
Variance58652683
MonotonicityNot monotonic
2023-12-12T13:53:49.545824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
496.0 40
 
0.4%
660.0 38
 
0.4%
397.0 31
 
0.3%
436.0 30
 
0.3%
446.0 29
 
0.3%
486.0 29
 
0.3%
793.0 28
 
0.3%
198.0 27
 
0.3%
251.0 26
 
0.3%
347.0 25
 
0.2%
Other values (3061) 9697
97.0%
ValueCountFrequency (%)
2.0 2
 
< 0.1%
3.0 1
 
< 0.1%
4.0 3
< 0.1%
6.0 3
< 0.1%
7.0 5
0.1%
8.0 2
 
< 0.1%
9.0 2
 
< 0.1%
10.0 1
 
< 0.1%
12.0 2
 
< 0.1%
13.0 5
0.1%
ValueCountFrequency (%)
266876.0 1
< 0.1%
232036.0 1
< 0.1%
166215.0 1
< 0.1%
129421.0 1
< 0.1%
124982.0 1
< 0.1%
122396.0 1
< 0.1%
114645.0 1
< 0.1%
113950.0 1
< 0.1%
108469.0 1
< 0.1%
107481.0 1
< 0.1%

지목
Categorical

IMBALANCE 

Distinct22
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
답
4197 
전
2528 
대
1640 
임야
949 
잡종지
 
207
Other values (17)
479 

Length

Max length5
Median length1
Mean length1.2564
Min length1

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
답 4197
42.0%
전 2528
25.3%
대 1640
 
16.4%
임야 949
 
9.5%
잡종지 207
 
2.1%
목장용지 203
 
2.0%
과수원 141
 
1.4%
창고용지 46
 
0.5%
도로 27
 
0.3%
공장용지 13
 
0.1%
Other values (12) 49
 
0.5%

Length

2023-12-12T13:53:49.774817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
답 4197
42.0%
전 2528
25.3%
대 1640
 
16.4%
임야 949
 
9.5%
잡종지 207
 
2.1%
목장용지 203
 
2.0%
과수원 141
 
1.4%
창고용지 46
 
0.5%
도로 27
 
0.3%
공장용지 13
 
0.1%
Other values (12) 49
 
0.5%

용도
Categorical

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
전ㆍ답
6834 
임야
915 
주택등
819 
대지(잡종지)
 
613
축사
 
326
Other values (4)
 
493

Length

Max length7
Median length3
Mean length3.2067
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row전ㆍ답
2nd row전ㆍ답
3rd row축사
4th row전ㆍ답
5th row전ㆍ답

Common Values

ValueCountFrequency (%)
전ㆍ답 6834
68.3%
임야 915
 
9.2%
주택등 819
 
8.2%
대지(잡종지) 613
 
6.1%
축사 326
 
3.3%
기타건물 241
 
2.4%
숙박·음식점 211
 
2.1%
과수원 23
 
0.2%
공장 18
 
0.2%

Length

2023-12-12T13:53:49.969762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:50.123923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전ㆍ답 6834
68.3%
임야 915
 
9.2%
주택등 819
 
8.2%
대지(잡종지 613
 
6.1%
축사 326
 
3.3%
기타건물 241
 
2.4%
숙박·음식점 211
 
2.1%
과수원 23
 
0.2%
공장 18
 
0.2%

규제지역
Categorical

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
수변구역
5440 
기타지역
2120 
자연마을
1269 
상수원보호구역
 
518
도시지역
 
382
Other values (4)
 
271

Length

Max length8
Median length4
Mean length4.2112
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row기타지역
2nd row기타지역
3rd row수변구역
4th row수변구역
5th row기타지역

Common Values

ValueCountFrequency (%)
수변구역 5440
54.4%
기타지역 2120
 
21.2%
자연마을 1269
 
12.7%
상수원보호구역 518
 
5.2%
도시지역 382
 
3.8%
하수처리구역 220
 
2.2%
하수처리예정구역 28
 
0.3%
취락지구 20
 
0.2%
개발제한구역 3
 
< 0.1%

Length

2023-12-12T13:53:50.298401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:50.463646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수변구역 5440
54.4%
기타지역 2120
 
21.2%
자연마을 1269
 
12.7%
상수원보호구역 518
 
5.2%
도시지역 382
 
3.8%
하수처리구역 220
 
2.2%
하수처리예정구역 28
 
0.3%
취락지구 20
 
0.2%
개발제한구역 3
 
< 0.1%

하천명
Text

MISSING 

Distinct54
Distinct (%)0.9%
Missing3908
Missing (%)39.1%
Memory size156.2 KiB
2023-12-12T13:53:50.734259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.0078792
Min length2

Characters and Unicode

Total characters18324
Distinct characters65
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

Unique3 ?
Unique (%)< 0.1%

Sample

1st row송광천
2nd row보성강
3rd row수어천
4th row내남천
5th row용문천
ValueCountFrequency (%)
송광천 524
 
8.6%
외남천 501
 
8.2%
보성강 454
 
7.5%
이사천 379
 
6.2%
율어천 316
 
5.2%
유정천 302
 
5.0%
문덕천 281
 
4.6%
동복천 275
 
4.5%
남정천 232
 
3.8%
석흥천 228
 
3.7%
Other values (44) 2600
42.7%
2023-12-12T13:53:51.188362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
천 5764
31.5%
남 853
 
4.7%
성 681
 
3.7%
강 656
 
3.6%
송 595
 
3.2%
외 566
 
3.1%
정 534
 
2.9%
이 532
 
2.9%
광 527
 
2.9%
사 519
 
2.8%
Other values (55) 7097
38.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 18324
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 5764
31.5%
남 853
 
4.7%
성 681
 
3.7%
강 656
 
3.6%
송 595
 
3.2%
외 566
 
3.1%
정 534
 
2.9%
이 532
 
2.9%
광 527
 
2.9%
사 519
 
2.8%
Other values (55) 7097
38.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 18324
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 5764
31.5%
남 853
 
4.7%
성 681
 
3.7%
강 656
 
3.6%
송 595
 
3.2%
외 566
 
3.1%
정 534
 
2.9%
이 532
 
2.9%
광 527
 
2.9%
사 519
 
2.8%
Other values (55) 7097
38.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 18324
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
천 5764
31.5%
남 853
 
4.7%
성 681
 
3.7%
강 656
 
3.6%
송 595
 
3.2%
외 566
 
3.1%
정 534
 
2.9%
이 532
 
2.9%
광 527
 
2.9%
사 519
 
2.8%
Other values (55) 7097
38.7%

호소명
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
주암호
5854 
상사호
1627 
동복호
1204 
탐진호
824 
수어호
 
491

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row주암호
2nd row주암호
3rd row주암호
4th row수어호
5th row탐진호

Common Values

ValueCountFrequency (%)
주암호 5854
58.5%
상사호 1627
 
16.3%
동복호 1204
 
12.0%
탐진호 824
 
8.2%
수어호 491
 
4.9%

Length

2023-12-12T13:53:51.358504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:51.501068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주암호 5854
58.5%
상사호 1627
 
16.3%
동복호 1204
 
12.0%
탐진호 824
 
8.2%
수어호 491
 
4.9%

거리범례
Real number (ℝ)

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean368.8607
Minimum50
Maximum5000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T13:53:51.625379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum50
5-th percentile50
Q150
median300
Q3500
95-th percentile1000
Maximum5000
Range4950
Interquartile range (IQR)450

Descriptive statistics

Standard deviation331.88658
Coefficient of variation (CV)0.89976128
Kurtosis3.7451345
Mean368.8607
Median Absolute Deviation (MAD)200
Skewness1.2529052
Sum3688607
Variance110148.7
MonotonicityNot monotonic
2023-12-12T13:53:51.776109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
300 2862
28.6%
50 2534
25.3%
500 1750
17.5%
1000 1685
16.9%
100 1153
11.5%
2000 8
 
0.1%
1001 7
 
0.1%
5000 1
 
< 0.1%
ValueCountFrequency (%)
50 2534
25.3%
100 1153
11.5%
300 2862
28.6%
500 1750
17.5%
1000 1685
16.9%
1001 7
 
0.1%
2000 8
 
0.1%
5000 1
 
< 0.1%
ValueCountFrequency (%)
5000 1
 
< 0.1%
2000 8
 
0.1%
1001 7
 
0.1%
1000 1685
16.9%
500 1750
17.5%
300 2862
28.6%
100 1153
11.5%
50 2534
25.3%

하천과거리
Real number (ℝ)

ZEROS 

Distinct976
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean259.3756
Minimum0
Maximum2011
Zeros281
Zeros (%)2.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T13:53:51.967249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5
Q150
median180
Q3396
95-th percentile801
Maximum2011
Range2011
Interquartile range (IQR)346

Descriptive statistics

Standard deviation252.57453
Coefficient of variation (CV)0.97377907
Kurtosis0.63966524
Mean259.3756
Median Absolute Deviation (MAD)147
Skewness1.1337995
Sum2593756
Variance63793.893
MonotonicityNot monotonic
2023-12-12T13:53:52.163786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 281
 
2.8%
5 265
 
2.6%
50 216
 
2.2%
200 100
 
1.0%
1 79
 
0.8%
1000 68
 
0.7%
10 60
 
0.6%
3 60
 
0.6%
20 54
 
0.5%
500 53
 
0.5%
Other values (966) 8764
87.6%
ValueCountFrequency (%)
0 281
2.8%
1 79
 
0.8%
2 30
 
0.3%
3 60
 
0.6%
4 23
 
0.2%
5 265
2.6%
6 49
 
0.5%
7 42
 
0.4%
8 51
 
0.5%
9 33
 
0.3%
ValueCountFrequency (%)
2011 1
 
< 0.1%
1090 2
 
< 0.1%
1079 1
 
< 0.1%
1030 1
 
< 0.1%
1028 1
 
< 0.1%
1023 2
 
< 0.1%
1010 1
 
< 0.1%
1000 68
0.7%
999 2
 
< 0.1%
998 1
 
< 0.1%

용도지역
Categorical

Distinct13
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
2245 
보전관리지역
2005 
농림지역
1599 
생산관리지역
1485 
관리지역
1161 
Other values (8)
1505 

Length

Max length8
Median length4
Mean length5.0135
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2245
22.4%
보전관리지역 2005
20.1%
농림지역 1599
16.0%
생산관리지역 1485
14.8%
관리지역 1161
11.6%
계획관리지역 745
 
7.4%
자연환경보전지역 415
 
4.2%
도시지역 279
 
2.8%
녹지지역 56
 
0.6%
상업지역 4
 
< 0.1%
Other values (3) 6
 
0.1%

Length

2023-12-12T13:53:52.363539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2245
22.4%
보전관리지역 2005
20.1%
농림지역 1599
16.0%
생산관리지역 1485
14.8%
관리지역 1161
11.6%
계획관리지역 745
 
7.4%
자연환경보전지역 415
 
4.2%
도시지역 279
 
2.8%
녹지지역 56
 
0.6%
상업지역 4
 
< 0.1%
Other values (3) 6
 
0.1%

비고
Text

MISSING 

Distinct79
Distinct (%)39.3%
Missing9799
Missing (%)98.0%
Memory size156.2 KiB
2023-12-12T13:53:52.722662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length36
Mean length11.004975
Min length1

Characters and Unicode

Total characters2212
Distinct characters155
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique62 ?
Unique (%)30.8%

Sample

1st row실제이용상황 임야 아님
2nd row주거개발진흥지구
3rd row실제 이용상황 임야 아님
4th row소유권이전청구권가등기 설정됨
5th row공(폐)가
ValueCountFrequency (%)
공(폐)가 48
 
11.6%
5년 23
 
5.5%
취득 21
 
5.1%
소유권 20
 
4.8%
불응 20
 
4.8%
이후 20
 
4.8%
대상 20
 
4.8%
임야 18
 
4.3%
주거개발진흥지구 15
 
3.6%
실제이용상황 8
 
1.9%
Other values (117) 202
48.7%
2023-12-12T13:53:53.320366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
219
 
9.9%
지 93
 
4.2%
( 77
 
3.5%
) 75
 
3.4%
1 66
 
3.0%
0 65
 
2.9%
구 64
 
2.9%
가 60
 
2.7%
폐 55
 
2.5%
공 51
 
2.3%
Other values (145) 1387
62.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1454
65.7%
Decimal Number 267
 
12.1%
Space Separator 219
 
9.9%
Other Punctuation 115
 
5.2%
Open Punctuation 77
 
3.5%
Close Punctuation 75
 
3.4%
Dash Punctuation 5
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 93
 
6.4%
구 64
 
4.4%
가 60
 
4.1%
폐 55
 
3.8%
공 51
 
3.5%
이 43
 
3.0%
권 37
 
2.5%
진 31
 
2.1%
소 31
 
2.1%
유 31
 
2.1%
Other values (125) 958
65.9%
Decimal Number
ValueCountFrequency (%)
1 66
24.7%
0 65
24.3%
2 36
13.5%
5 28
10.5%
3 27
10.1%
9 18
 
6.7%
8 9
 
3.4%
7 7
 
2.6%
6 6
 
2.2%
4 5
 
1.9%
Other Punctuation
ValueCountFrequency (%)
. 48
41.7%
, 19
 
16.5%
# 14
 
12.2%
; 14
 
12.2%
& 14
 
12.2%
: 6
 
5.2%
Space Separator
ValueCountFrequency (%)
219
100.0%
Open Punctuation
ValueCountFrequency (%)
( 77
100.0%
Close Punctuation
ValueCountFrequency (%)
) 75
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1454
65.7%
Common 758
34.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 93
 
6.4%
구 64
 
4.4%
가 60
 
4.1%
폐 55
 
3.8%
공 51
 
3.5%
이 43
 
3.0%
권 37
 
2.5%
진 31
 
2.1%
소 31
 
2.1%
유 31
 
2.1%
Other values (125) 958
65.9%
Common
ValueCountFrequency (%)
219
28.9%
( 77
 
10.2%
) 75
 
9.9%
1 66
 
8.7%
0 65
 
8.6%
. 48
 
6.3%
2 36
 
4.7%
5 28
 
3.7%
3 27
 
3.6%
, 19
 
2.5%
Other values (10) 98
12.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1454
65.7%
ASCII 758
34.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
219
28.9%
( 77
 
10.2%
) 75
 
9.9%
1 66
 
8.7%
0 65
 
8.6%
. 48
 
6.3%
2 36
 
4.7%
5 28
 
3.7%
3 27
 
3.6%
, 19
 
2.5%
Other values (10) 98
12.9%
Hangul
ValueCountFrequency (%)
지 93
 
6.4%
구 64
 
4.4%
가 60
 
4.1%
폐 55
 
3.8%
공 51
 
3.5%
이 43
 
3.0%
권 37
 
2.5%
진 31
 
2.1%
소 31
 
2.1%
유 31
 
2.1%
Other values (125) 958
65.9%

매수제한지역이름
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9564 
지목(하천,도로,철도용지,구거,유지,임야)
 
214
하수처리구역 내 건축물
 
117
행정계획수립단지(개발촉진지구 등)
 
46
소유권이전 5년미만
 
26
Other values (3)
 
33

Length

Max length23
Median length4
Mean length4.6047
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> 9564
95.6%
지목(하천,도로,철도용지,구거,유지,임야) 214
 
2.1%
하수처리구역 내 건축물 117
 
1.2%
행정계획수립단지(개발촉진지구 등) 46
 
0.5%
소유권이전 5년미만 26
 
0.3%
경매취득 5년미만 19
 
0.2%
이주목적매도자 10년 미경과 12
 
0.1%
건축물 준공 3년 미경과 2
 
< 0.1%

Length

2023-12-12T13:53:53.531517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:53.679800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9564
92.4%
지목(하천,도로,철도용지,구거,유지,임야 214
 
2.1%
건축물 119
 
1.1%
하수처리구역 117
 
1.1%
내 117
 
1.1%
행정계획수립단지(개발촉진지구 46
 
0.4%
등 46
 
0.4%
5년미만 45
 
0.4%
소유권이전 26
 
0.3%
경매취득 19
 
0.2%
Other values (5) 42
 
0.4%

우선매수지역
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
X
9342 
O
 
658

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
X 9342
93.4%
O 658
 
6.6%

Length

2023-12-12T13:53:53.842718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:53.933885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
x 9342
93.4%
o 658
 
6.6%

배점표처리지침
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2009년기준
6907 
2003년기준
1736 
2019년기준
970 
2008년기준
 
387

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2009년기준
2nd row2003년기준
3rd row2003년기준
4th row2009년기준
5th row2009년기준

Common Values

ValueCountFrequency (%)
2009년기준 6907
69.1%
2003년기준 1736
 
17.4%
2019년기준 970
 
9.7%
2008년기준 387
 
3.9%

Length

2023-12-12T13:53:54.054365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:54.155266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2009년기준 6907
69.1%
2003년기준 1736
 
17.4%
2019년기준 970
 
9.7%
2008년기준 387
 
3.9%

배점선택경계거리
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
2700 
1
2174 
3
1931 
<NA>
1721 
4
1465 

Length

Max length4
Median length1
Mean length1.5163
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row1
3rd row<NA>
4th row2
5th row4

Common Values

ValueCountFrequency (%)
2 2700
27.0%
1 2174
21.7%
3 1931
19.3%
<NA> 1721
17.2%
4 1465
14.6%
5 9
 
0.1%

Length

2023-12-12T13:53:54.279802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:54.404629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 2700
27.0%
1 2174
21.7%
3 1931
19.3%
na 1721
17.2%
4 1465
14.6%
5 9
 
0.1%

매수현황번호
Real number (ℝ)

Distinct33
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.1104
Minimum1
Maximum35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T13:53:54.581260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile6
Maximum35
Range34
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.5358736
Coefficient of variation (CV)1.201608
Kurtosis32.729455
Mean2.1104
Median Absolute Deviation (MAD)0
Skewness4.7773617
Sum21104
Variance6.4306549
MonotonicityNot monotonic
2023-12-12T13:53:54.714599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
1 6156
61.6%
2 1809
 
18.1%
3 763
 
7.6%
4 395
 
4.0%
5 230
 
2.3%
6 185
 
1.8%
7 104
 
1.0%
8 70
 
0.7%
9 59
 
0.6%
10 35
 
0.4%
Other values (23) 194
 
1.9%
ValueCountFrequency (%)
1 6156
61.6%
2 1809
 
18.1%
3 763
 
7.6%
4 395
 
4.0%
5 230
 
2.3%
6 185
 
1.8%
7 104
 
1.0%
8 70
 
0.7%
9 59
 
0.6%
10 35
 
0.4%
ValueCountFrequency (%)
35 1
 
< 0.1%
34 1
 
< 0.1%
33 1
 
< 0.1%
32 1
 
< 0.1%
31 1
 
< 0.1%
30 1
 
< 0.1%
28 1
 
< 0.1%
27 2
< 0.1%
26 2
< 0.1%
25 3
< 0.1%

현지조사
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
완료
6279 
대기
3721 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row완료
2nd row완료
3rd row완료
4th row대기
5th row완료

Common Values

ValueCountFrequency (%)
완료 6279
62.8%
대기 3721
37.2%

Length

2023-12-12T13:53:54.897014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:55.014105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
완료 6279
62.8%
대기 3721
37.2%

감정의뢰
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
완료
6106 
대기
3894 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row완료
2nd row완료
3rd row완료
4th row대기
5th row완료

Common Values

ValueCountFrequency (%)
완료 6106
61.1%
대기 3894
38.9%

Length

2023-12-12T13:53:55.151058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:55.261244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
완료 6106
61.1%
대기 3894
38.9%

매매계약
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
완료
5422 
대기
4578 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row완료
2nd row완료
3rd row완료
4th row대기
5th row완료

Common Values

ValueCountFrequency (%)
완료 5422
54.2%
대기 4578
45.8%

Length

2023-12-12T13:53:55.366552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:55.471900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
완료 5422
54.2%
대기 4578
45.8%

매매완료
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
완료
5421 
대기
4579 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row완료
2nd row완료
3rd row완료
4th row대기
5th row완료

Common Values

ValueCountFrequency (%)
완료 5421
54.2%
대기 4579
45.8%

Length

2023-12-12T13:53:55.590643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:55.687122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
완료 5421
54.2%
대기 4579
45.8%

매수상황
Categorical

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
완료
5423 
대기
2659 
철회
990 
불응
 
390
제한
 
340
Other values (2)
 
198

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row완료
2nd row완료
3rd row완료
4th row연기
5th row완료

Common Values

ValueCountFrequency (%)
완료 5423
54.2%
대기 2659
26.6%
철회 990
 
9.9%
불응 390
 
3.9%
제한 340
 
3.4%
연기 163
 
1.6%
반려 35
 
0.4%

Length

2023-12-12T13:53:55.824368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:56.325163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
완료 5423
54.2%
대기 2659
26.6%
철회 990
 
9.9%
불응 390
 
3.9%
제한 340
 
3.4%
연기 163
 
1.6%
반려 35
 
0.4%

철거여부
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
대기
8969 
완료
1031 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대기
2nd row대기
3rd row완료
4th row대기
5th row대기

Common Values

ValueCountFrequency (%)
대기 8969
89.7%
완료 1031
 
10.3%

Length

2023-12-12T13:53:56.493306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:56.613580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대기 8969
89.7%
완료 1031
 
10.3%

생태복원
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
대기
7262 
완료
2738 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대기
2nd row완료
3rd row완료
4th row대기
5th row대기

Common Values

ValueCountFrequency (%)
대기 7262
72.6%
완료 2738
 
27.4%

Length

2023-12-12T13:53:56.847993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:57.007281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대기 7262
72.6%
완료 2738
 
27.4%

기타사후관리
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
대기
8981 
완료
1019 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대기 8981
89.8%
완료 1019
 
10.2%

Length

2023-12-12T13:53:57.173387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:57.299156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대기 8981
89.8%
완료 1019
 
10.2%

매매계약일련번호
Real number (ℝ)

MISSING 

Distinct3623
Distinct (%)66.7%
Missing4571
Missing (%)45.7%
Infinite0
Infinite (%)0.0%
Mean2891.8943
Minimum15
Maximum6634
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T13:53:57.443514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum15
5-th percentile262.4
Q11332
median2673
Q34121
95-th percentile6102.4
Maximum6634
Range6619
Interquartile range (IQR)2789

Descriptive statistics

Standard deviation1805.8421
Coefficient of variation (CV)0.62444954
Kurtosis-0.88240971
Mean2891.8943
Median Absolute Deviation (MAD)1387
Skewness0.36463515
Sum15700094
Variance3261065.5
MonotonicityNot monotonic
2023-12-12T13:53:57.598521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1162 19
 
0.2%
4239 16
 
0.2%
1234 13
 
0.1%
93 12
 
0.1%
522 12
 
0.1%
482 11
 
0.1%
1996 11
 
0.1%
420 11
 
0.1%
2091 11
 
0.1%
1997 10
 
0.1%
Other values (3613) 5303
53.0%
(Missing) 4571
45.7%
ValueCountFrequency (%)
15 3
< 0.1%
20 1
 
< 0.1%
21 1
 
< 0.1%
24 2
< 0.1%
28 1
 
< 0.1%
29 1
 
< 0.1%
30 1
 
< 0.1%
32 4
< 0.1%
33 1
 
< 0.1%
34 1
 
< 0.1%
ValueCountFrequency (%)
6634 1
 
< 0.1%
6632 1
 
< 0.1%
6630 1
 
< 0.1%
6628 1
 
< 0.1%
6625 2
< 0.1%
6624 2
< 0.1%
6623 4
< 0.1%
6622 1
 
< 0.1%
6620 1
 
< 0.1%
6619 1
 
< 0.1%

계약체결신청일자
Date

MISSING 

Distinct836
Distinct (%)15.4%
Missing4571
Missing (%)45.7%
Memory size156.2 KiB
Minimum2003-09-06 00:00:00
Maximum2017-12-20 00:00:00
2023-12-12T13:53:57.801877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:58.010596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

매매계약율
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5773 
100
2273 
75
1954 

Length

Max length4
Median length4
Mean length3.3819
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row75
3rd row75
4th row<NA>
5th row100

Common Values

ValueCountFrequency (%)
<NA> 5773
57.7%
100 2273
 
22.7%
75 1954
 
19.5%

Length

2023-12-12T13:53:58.189308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:58.338188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5773
57.7%
100 2273
 
22.7%
75 1954
 
19.5%

토지외물건수
Real number (ℝ)

MISSING 

Distinct72
Distinct (%)2.5%
Missing7132
Missing (%)71.3%
Infinite0
Infinite (%)0.0%
Mean8.9672245
Minimum1
Maximum131
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T13:53:58.535000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q311
95-th percentile33.65
Maximum131
Range130
Interquartile range (IQR)9

Descriptive statistics

Standard deviation11.925284
Coefficient of variation (CV)1.3298745
Kurtosis12.136063
Mean8.9672245
Median Absolute Deviation (MAD)3
Skewness2.8467895
Sum25718
Variance142.21239
MonotonicityNot monotonic
2023-12-12T13:53:58.747794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 665
 
6.7%
2 374
 
3.7%
3 271
 
2.7%
4 194
 
1.9%
5 145
 
1.5%
6 135
 
1.4%
7 94
 
0.9%
8 85
 
0.9%
9 74
 
0.7%
10 62
 
0.6%
Other values (62) 769
 
7.7%
(Missing) 7132
71.3%
ValueCountFrequency (%)
1 665
6.7%
2 374
3.7%
3 271
2.7%
4 194
 
1.9%
5 145
 
1.5%
6 135
 
1.4%
7 94
 
0.9%
8 85
 
0.9%
9 74
 
0.7%
10 62
 
0.6%
ValueCountFrequency (%)
131 1
< 0.1%
102 1
< 0.1%
93 1
< 0.1%
90 2
< 0.1%
87 1
< 0.1%
78 1
< 0.1%
74 1
< 0.1%
72 2
< 0.1%
70 2
< 0.1%
68 1
< 0.1%

기타사후관리번호
Real number (ℝ)

MISSING 

Distinct1017
Distinct (%)100.0%
Missing8983
Missing (%)89.8%
Infinite0
Infinite (%)0.0%
Mean1021.5713
Minimum2
Maximum1954
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T13:53:58.964417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile145.8
Q1564
median1033
Q31477
95-th percentile1867.2
Maximum1954
Range1952
Interquartile range (IQR)913

Descriptive statistics

Standard deviation547.7201
Coefficient of variation (CV)0.53615455
Kurtosis-1.1510604
Mean1021.5713
Median Absolute Deviation (MAD)457
Skewness-0.046737673
Sum1038938
Variance299997.3
MonotonicityNot monotonic
2023-12-12T13:53:59.145295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
327 1
 
< 0.1%
921 1
 
< 0.1%
230 1
 
< 0.1%
125 1
 
< 0.1%
1847 1
 
< 0.1%
1520 1
 
< 0.1%
1872 1
 
< 0.1%
59 1
 
< 0.1%
860 1
 
< 0.1%
1369 1
 
< 0.1%
Other values (1007) 1007
 
10.1%
(Missing) 8983
89.8%
ValueCountFrequency (%)
2 1
< 0.1%
4 1
< 0.1%
13 1
< 0.1%
19 1
< 0.1%
21 1
< 0.1%
23 1
< 0.1%
26 1
< 0.1%
27 1
< 0.1%
29 1
< 0.1%
34 1
< 0.1%
ValueCountFrequency (%)
1954 1
< 0.1%
1953 1
< 0.1%
1952 1
< 0.1%
1951 1
< 0.1%
1950 1
< 0.1%
1949 1
< 0.1%
1946 1
< 0.1%
1944 1
< 0.1%
1943 1
< 0.1%
1941 1
< 0.1%

울타리설치
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)20.6%
Missing9966
Missing (%)99.7%
Infinite0
Infinite (%)0.0%
Mean2008.9118
Minimum2005
Maximum2016
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T13:53:59.323114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2005
5-th percentile2006
Q12008
median2008
Q32009
95-th percentile2016
Maximum2016
Range11
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.8108841
Coefficient of variation (CV)0.0013992074
Kurtosis2.8638015
Mean2008.9118
Median Absolute Deviation (MAD)0.5
Skewness1.8441127
Sum68303
Variance7.9010695
MonotonicityNot monotonic
2023-12-12T13:53:59.439255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
2008 17
 
0.2%
2009 7
 
0.1%
2016 4
 
< 0.1%
2006 3
 
< 0.1%
2010 1
 
< 0.1%
2005 1
 
< 0.1%
2007 1
 
< 0.1%
(Missing) 9966
99.7%
ValueCountFrequency (%)
2005 1
 
< 0.1%
2006 3
 
< 0.1%
2007 1
 
< 0.1%
2008 17
0.2%
2009 7
0.1%
2010 1
 
< 0.1%
2016 4
 
< 0.1%
ValueCountFrequency (%)
2016 4
 
< 0.1%
2010 1
 
< 0.1%
2009 7
0.1%
2008 17
0.2%
2007 1
 
< 0.1%
2006 3
 
< 0.1%
2005 1
 
< 0.1%

경계측량
Real number (ℝ)

MISSING 

Distinct13
Distinct (%)3.1%
Missing9576
Missing (%)95.8%
Infinite0
Infinite (%)0.0%
Mean2011.9269
Minimum2005
Maximum2017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T13:53:59.596785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2005
5-th percentile2008
Q12009
median2011
Q32015
95-th percentile2017
Maximum2017
Range12
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.0359289
Coefficient of variation (CV)0.0015089658
Kurtosis-1.4003109
Mean2011.9269
Median Absolute Deviation (MAD)2
Skewness0.2553649
Sum853057
Variance9.216864
MonotonicityNot monotonic
2023-12-12T13:53:59.737996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
2009 119
 
1.2%
2010 62
 
0.6%
2016 50
 
0.5%
2015 49
 
0.5%
2014 37
 
0.4%
2017 27
 
0.3%
2012 24
 
0.2%
2008 19
 
0.2%
2013 16
 
0.2%
2011 16
 
0.2%
Other values (3) 5
 
0.1%
(Missing) 9576
95.8%
ValueCountFrequency (%)
2005 1
 
< 0.1%
2006 3
 
< 0.1%
2007 1
 
< 0.1%
2008 19
 
0.2%
2009 119
1.2%
2010 62
0.6%
2011 16
 
0.2%
2012 24
 
0.2%
2013 16
 
0.2%
2014 37
 
0.4%
ValueCountFrequency (%)
2017 27
 
0.3%
2016 50
0.5%
2015 49
0.5%
2014 37
 
0.4%
2013 16
 
0.2%
2012 24
 
0.2%
2011 16
 
0.2%
2010 62
0.6%
2009 119
1.2%
2008 19
 
0.2%

경고표지판
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)1.4%
Missing9487
Missing (%)94.9%
Infinite0
Infinite (%)0.0%
Mean2014.7895
Minimum2008
Maximum2017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T13:53:59.851326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2008
5-th percentile2008
Q12014
median2016
Q32016
95-th percentile2017
Maximum2017
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.4211241
Coefficient of variation (CV)0.001201676
Kurtosis2.7541908
Mean2014.7895
Median Absolute Deviation (MAD)1
Skewness-1.8860855
Sum1033587
Variance5.8618421
MonotonicityNot monotonic
2023-12-12T13:53:59.969339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
2016 255
 
2.5%
2017 60
 
0.6%
2013 54
 
0.5%
2014 50
 
0.5%
2015 47
 
0.5%
2008 46
 
0.5%
2012 1
 
< 0.1%
(Missing) 9487
94.9%
ValueCountFrequency (%)
2008 46
 
0.5%
2012 1
 
< 0.1%
2013 54
 
0.5%
2014 50
 
0.5%
2015 47
 
0.5%
2016 255
2.5%
2017 60
 
0.6%
ValueCountFrequency (%)
2017 60
 
0.6%
2016 255
2.5%
2015 47
 
0.5%
2014 50
 
0.5%
2013 54
 
0.5%
2012 1
 
< 0.1%
2008 46
 
0.5%

특이사항
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9973 
제초작업 2009
 
25
잡목제거 2009
 
1
2009 제초작업
 
1

Length

Max length9
Median length4
Mean length4.0135
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> 9973
99.7%
제초작업 2009 25
 
0.2%
잡목제거 2009 1
 
< 0.1%
2009 제초작업 1
 
< 0.1%

Length

2023-12-12T13:54:00.098735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:54:00.205815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9973
99.5%
2009 27
 
0.3%
제초작업 26
 
0.3%
잡목제거 1
 
< 0.1%

벌목
Real number (ℝ)

MISSING 

Distinct9
Distinct (%)4.0%
Missing9775
Missing (%)97.8%
Infinite0
Infinite (%)0.0%
Mean2014.5556
Minimum2009
Maximum2017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T13:54:00.286816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2009
5-th percentile2010
Q12013
median2016
Q32016
95-th percentile2017
Maximum2017
Range8
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.2216021
Coefficient of variation (CV)0.0011027753
Kurtosis0.017385901
Mean2014.5556
Median Absolute Deviation (MAD)1
Skewness-1.0098183
Sum453275
Variance4.9355159
MonotonicityNot monotonic
2023-12-12T13:54:00.391767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
2016 87
 
0.9%
2015 31
 
0.3%
2017 29
 
0.3%
2012 26
 
0.3%
2013 22
 
0.2%
2009 11
 
0.1%
2014 8
 
0.1%
2011 6
 
0.1%
2010 5
 
0.1%
(Missing) 9775
97.8%
ValueCountFrequency (%)
2009 11
 
0.1%
2010 5
 
0.1%
2011 6
 
0.1%
2012 26
 
0.3%
2013 22
 
0.2%
2014 8
 
0.1%
2015 31
 
0.3%
2016 87
0.9%
2017 29
 
0.3%
ValueCountFrequency (%)
2017 29
 
0.3%
2016 87
0.9%
2015 31
 
0.3%
2014 8
 
0.1%
2013 22
 
0.2%
2012 26
 
0.3%
2011 6
 
0.1%
2010 5
 
0.1%
2009 11
 
0.1%

특이사항체크
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.1%
Missing9019
Missing (%)90.2%
Memory size97.7 KiB
False
981 
(Missing)
9019 
ValueCountFrequency (%)
False 981
 
9.8%
(Missing) 9019
90.2%
2023-12-12T13:54:00.493349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

변동사항
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.1%
Missing9018
Missing (%)90.2%
Memory size97.7 KiB
True
982 
(Missing)
9018 
ValueCountFrequency (%)
True 982
 
9.8%
(Missing) 9018
90.2%
2023-12-12T13:54:00.559750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

생태복원번호
Real number (ℝ)

MISSING 

Distinct272
Distinct (%)9.9%
Missing7262
Missing (%)72.6%
Infinite0
Infinite (%)0.0%
Mean75.289262
Minimum1
Maximum354
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T13:54:00.683932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile16
Q145
median73
Q380
95-th percentile218
Maximum354
Range353
Interquartile range (IQR)35

Descriptive statistics

Standard deviation59.589268
Coefficient of variation (CV)0.791471
Kurtosis7.7152449
Mean75.289262
Median Absolute Deviation (MAD)18
Skewness2.6102766
Sum206142
Variance3550.8809
MonotonicityNot monotonic
2023-12-12T13:54:00.850372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
77 190
 
1.9%
74 176
 
1.8%
78 159
 
1.6%
48 128
 
1.3%
73 116
 
1.2%
91 42
 
0.4%
85 38
 
0.4%
35 37
 
0.4%
56 36
 
0.4%
21 35
 
0.4%
Other values (262) 1781
 
17.8%
(Missing) 7262
72.6%
ValueCountFrequency (%)
1 1
 
< 0.1%
2 24
0.2%
3 3
 
< 0.1%
4 15
0.1%
6 3
 
< 0.1%
7 28
0.3%
8 2
 
< 0.1%
9 3
 
< 0.1%
10 3
 
< 0.1%
12 9
 
0.1%
ValueCountFrequency (%)
354 1
 
< 0.1%
352 1
 
< 0.1%
351 1
 
< 0.1%
350 4
< 0.1%
345 6
0.1%
344 1
 
< 0.1%
342 1
 
< 0.1%
341 1
 
< 0.1%
340 1
 
< 0.1%
339 1
 
< 0.1%

공사명
Categorical

IMBALANCE 

Distinct44
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
7390 
2016년 영산강섬진강수계 1차 생태벨트조성공사
 
409
수변생태벨트 조성공사
 
239
2015년도영산강.섬진강수계1차생태복원공사
 
190
2014년도영산강.섬진강수계2차생태복원공사
 
176
Other values (39)
1596 

Length

Max length30
Median length4
Mean length7.9631
Min length4

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row2017년 영산강섬진강수계1차 생태복원공사
3rd row2015년도영산강.섬진강수계1차생태복원공사
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 7390
73.9%
2016년 영산강섬진강수계 1차 생태벨트조성공사 409
 
4.1%
수변생태벨트 조성공사 239
 
2.4%
2015년도영산강.섬진강수계1차생태복원공사 190
 
1.9%
2014년도영산강.섬진강수계2차생태복원공사 176
 
1.8%
2017년 영산강섬진강수계2차 생태복원공사 163
 
1.6%
16년도 식목행사 159
 
1.6%
수변생태벨트 조성공사상반기 128
 
1.3%
10년 상반기 수변생태벨트조성공사 121
 
1.2%
수변생태벨트 조성공사하반기 116
 
1.2%
Other values (34) 909
 
9.1%

Length

2023-12-12T13:54:00.997640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 7390
53.3%
생태벨트조성공사 567
 
4.1%
수변생태벨트 542
 
3.9%
2016년 453
 
3.3%
영산강섬진강수계 453
 
3.3%
1차 409
 
2.9%
수변생태벨트조성공사 394
 
2.8%
조성공사 300
 
2.2%
2017년 268
 
1.9%
생태복원공사 268
 
1.9%
Other values (63) 2832
 
20.4%

공사대상
Categorical

IMBALANCE 

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9610 
자연천이
 
128
화순3구역
 
37
화순4구역
 
33
화순2구역
 
31
Other values (10)
 
161

Length

Max length8
Median length4
Mean length4.0287
Min length3

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> 9610
96.1%
자연천이 128
 
1.3%
화순3구역 37
 
0.4%
화순4구역 33
 
0.3%
화순2구역 31
 
0.3%
화순1구역 27
 
0.3%
보성2구역 25
 
0.2%
순천4구역 25
 
0.2%
보성1구역 22
 
0.2%
순천5구역 22
 
0.2%
Other values (5) 40
 
0.4%

Length

2023-12-12T13:54:01.130744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 9610
96.1%
자연천이 128
 
1.3%
화순3구역 37
 
0.4%
화순4구역 33
 
0.3%
화순2구역 31
 
0.3%
화순1구역 27
 
0.3%
보성2구역 25
 
0.2%
순천4구역 25
 
0.2%
보성1구역 22
 
0.2%
순천5구역 22
 
0.2%
Other values (5) 40
 
0.4%

공사기간시작
Date

MISSING 

Distinct37
Distinct (%)1.4%
Missing7262
Missing (%)72.6%
Memory size156.2 KiB
Minimum2005-01-05 00:00:00
Maximum2017-02-01 00:00:00
2023-12-12T13:54:01.236288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:54:01.368015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)

공사기간종료
Date

MISSING 

Distinct38
Distinct (%)1.4%
Missing7262
Missing (%)72.6%
Memory size156.2 KiB
Minimum2005-02-17 00:00:00
Maximum2017-12-31 00:00:00
2023-12-12T13:54:01.544768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:54:01.687364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)

계약업체
Text

MISSING 

Distinct57
Distinct (%)4.7%
Missing8795
Missing (%)87.9%
Memory size156.2 KiB
2023-12-12T13:54:02.041792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length7
Mean length7.4290456
Min length4

Characters and Unicode

Total characters8952
Distinct characters113
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row(주)대원종합조경
2nd row(주)한성종합조경
3rd row(주)금호조경
4th row(주)한성종합조경
5th row(주)늘푸른조경산업
ValueCountFrequency (%)
주식회사 82
 
6.2%
주)금호조경 53
 
4.0%
주)유로조경 42
 
3.2%
주)가람조경 37
 
2.8%
할림조경(주 36
 
2.7%
주)한려종합개발 35
 
2.6%
주)그린월드 33
 
2.5%
해천산업개발(주 33
 
2.5%
도시조경(주 33
 
2.5%
유)명신건설 32
 
2.4%
Other values (53) 912
68.7%
2023-12-12T13:54:02.600867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 1008
 
11.3%
( 971
 
10.8%
) 971
 
10.8%
경 810
 
9.0%
조 752
 
8.4%
사 177
 
2.0%
설 156
 
1.7%
건 156
 
1.7%
합 145
 
1.6%
종 140
 
1.6%
Other values (103) 3666
41.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6766
75.6%
Open Punctuation 971
 
10.8%
Close Punctuation 971
 
10.8%
Space Separator 123
 
1.4%
Other Symbol 121
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 1008
 
14.9%
경 810
 
12.0%
조 752
 
11.1%
사 177
 
2.6%
설 156
 
2.3%
건 156
 
2.3%
합 145
 
2.1%
종 140
 
2.1%
산 136
 
2.0%
유 109
 
1.6%
Other values (99) 3177
47.0%
Open Punctuation
ValueCountFrequency (%)
( 971
100.0%
Close Punctuation
ValueCountFrequency (%)
) 971
100.0%
Space Separator
ValueCountFrequency (%)
123
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 121
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6887
76.9%
Common 2065
 
23.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 1008
 
14.6%
경 810
 
11.8%
조 752
 
10.9%
사 177
 
2.6%
설 156
 
2.3%
건 156
 
2.3%
합 145
 
2.1%
종 140
 
2.0%
산 136
 
2.0%
㈜ 121
 
1.8%
Other values (100) 3286
47.7%
Common
ValueCountFrequency (%)
( 971
47.0%
) 971
47.0%
123
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6766
75.6%
ASCII 2065
 
23.1%
None 121
 
1.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 1008
 
14.9%
경 810
 
12.0%
조 752
 
11.1%
사 177
 
2.6%
설 156
 
2.3%
건 156
 
2.3%
합 145
 
2.1%
종 140
 
2.1%
산 136
 
2.0%
유 109
 
1.6%
Other values (99) 3177
47.0%
ASCII
ValueCountFrequency (%)
( 971
47.0%
) 971
47.0%
123
 
6.0%
None
ValueCountFrequency (%)
㈜ 121
100.0%

공사금액
Real number (ℝ)

MISSING  ZEROS 

Distinct68
Distinct (%)2.5%
Missing7262
Missing (%)72.6%
Infinite0
Infinite (%)0.0%
Mean1.7347362 × 108
Minimum0
Maximum5.91542 × 108
Zeros1529
Zeros (%)15.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T13:54:02.841148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33.8558598 × 108
95-th percentile5.43588 × 108
Maximum5.91542 × 108
Range5.91542 × 108
Interquartile range (IQR)3.8558598 × 108

Descriptive statistics

Standard deviation2.1254307 × 108
Coefficient of variation (CV)1.2252183
Kurtosis-1.4050545
Mean1.7347362 × 108
Median Absolute Deviation (MAD)0
Skewness0.56645508
Sum4.7497078 × 1011
Variance4.5174555 × 1016
MonotonicityNot monotonic
2023-12-12T13:54:03.401866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1529
 
15.3%
543588000 37
 
0.4%
591542000 36
 
0.4%
364672000 35
 
0.4%
10510780 33
 
0.3%
385265000 33
 
0.3%
315678000 33
 
0.3%
452143000 32
 
0.3%
515000000 32
 
0.3%
532050650 31
 
0.3%
Other values (58) 907
 
9.1%
(Missing) 7262
72.6%
ValueCountFrequency (%)
0 1529
15.3%
300000 1
 
< 0.1%
5300000 3
 
< 0.1%
6093000 3
 
< 0.1%
6300000 4
 
< 0.1%
10510780 33
 
0.3%
11603000 3
 
< 0.1%
14000000 1
 
< 0.1%
29443000 3
 
< 0.1%
33815000 2
 
< 0.1%
ValueCountFrequency (%)
591542000 36
0.4%
571813000 29
0.3%
570090800 20
0.2%
545800000 22
0.2%
543588000 37
0.4%
535021210 11
 
0.1%
532050650 31
0.3%
521906100 22
0.2%
515000000 32
0.3%
490460000 14
 
0.1%

철거번호
Real number (ℝ)

MISSING 

Distinct52
Distinct (%)5.0%
Missing8969
Missing (%)89.7%
Infinite0
Infinite (%)0.0%
Mean20.42386
Minimum1
Maximum56
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T13:54:03.552392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q19
median15
Q330
95-th percentile50
Maximum56
Range55
Interquartile range (IQR)21

Descriptive statistics

Standard deviation15.172336
Coefficient of variation (CV)0.74287308
Kurtosis-0.48440359
Mean20.42386
Median Absolute Deviation (MAD)8
Skewness0.83323726
Sum21057
Variance230.19978
MonotonicityNot monotonic
2023-12-12T13:54:03.703926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10 83
 
0.8%
5 83
 
0.8%
14 82
 
0.8%
7 66
 
0.7%
15 49
 
0.5%
9 49
 
0.5%
3 41
 
0.4%
1 34
 
0.3%
18 28
 
0.3%
20 27
 
0.3%
Other values (42) 489
 
4.9%
(Missing) 8969
89.7%
ValueCountFrequency (%)
1 34
0.3%
3 41
0.4%
4 1
 
< 0.1%
5 83
0.8%
6 1
 
< 0.1%
7 66
0.7%
9 49
0.5%
10 83
0.8%
11 27
 
0.3%
12 8
 
0.1%
ValueCountFrequency (%)
56 2
 
< 0.1%
55 16
0.2%
54 9
0.1%
53 16
0.2%
51 5
 
0.1%
50 10
0.1%
49 13
0.1%
48 17
0.2%
47 21
0.2%
46 6
 
0.1%

공사명_1
Categorical

IMBALANCE 

Distinct21
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8969 
2011
 
115
08년 1차 지장물철거 및 폐기물처리용역
 
83
3차 지장물철거 및 폐기물처리용역(2005년)
 
83
2012
 
82
Other values (16)
 
668

Length

Max length29
Median length4
Mean length5.0434
Min length4

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row3차 지장물철거 및 폐기물처리용역(2005년)
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 8969
89.7%
2011 115
 
1.1%
08년 1차 지장물철거 및 폐기물처리용역 83
 
0.8%
3차 지장물철거 및 폐기물처리용역(2005년) 83
 
0.8%
2012 82
 
0.8%
2010년 1차 지장물철거 및 폐기물처리용역 82
 
0.8%
2016 66
 
0.7%
2013 66
 
0.7%
5차 지장물철거 및 폐기물처리용역 66
 
0.7%
2014 61
 
0.6%
Other values (11) 327
 
3.3%

Length

2023-12-12T13:54:03.848625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8969
74.7%
및 542
 
4.5%
지장물철거 501
 
4.2%
폐기물처리용역 277
 
2.3%
1차 240
 
2.0%
2010년 131
 
1.1%
2011 115
 
1.0%
08년 110
 
0.9%
2차 84
 
0.7%
3차 83
 
0.7%
Other values (25) 955
 
8.0%

계약업체_1
Categorical

IMBALANCE 

Distinct14
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9457 
철거:(주)청웅건설(화순),(주)해광개발(보성),(주)지오콘(순천,광양)건서례기물:(주)대길산업(화순),(유)남해환경(보성), (주)전일환경(순천,광양)
 
83
철거:(주)구미녹색환경(순천), (주)도솔환경산업(보성), (주)은성건선(화순), (주)남경이엔지개발(광양), (주)다일건설(장흥,영암,강진)건설폐기물:(주)세계호나경(순천), (유)전일환경(보성), (주)금성환경산업, (유)삼려환경(광양), (주)대길산업(장흥, 영암,강진)지정폐기물:(주)인선이엔티
 
83
지장물철거:화순(신명건설),보성(세일건설),순천(자연토건)건설폐기물처리용역-파쇄(화순:두제산업, 보성:그린환경, 순천:남부환경)건설폐기물처리용역-소각(화순,보성,순천:동양환경)지정폐기물처리용역(화순,보성,순천:이에스티,빛고을환경)
 
82
철거:(주)신태전건설산업(화순), (주)도건개발(순천,광양)건설폐기물:(주)대길산업(화순),(유)남해환경(보성), (주)전일환경(순천,광양)
 
66
Other values (9)
 
229

Length

Max length176
Median length4
Mean length9.6946
Min length4

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row철거:(주)청웅건설(화순),(주)해광개발(보성),(주)지오콘(순천,광양)건서례기물:(주)대길산업(화순),(유)남해환경(보성), (주)전일환경(순천,광양)
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 9457
94.6%
철거:(주)청웅건설(화순),(주)해광개발(보성),(주)지오콘(순천,광양)건서례기물:(주)대길산업(화순),(유)남해환경(보성), (주)전일환경(순천,광양) 83
 
0.8%
철거:(주)구미녹색환경(순천), (주)도솔환경산업(보성), (주)은성건선(화순), (주)남경이엔지개발(광양), (주)다일건설(장흥,영암,강진)건설폐기물:(주)세계호나경(순천), (유)전일환경(보성), (주)금성환경산업, (유)삼려환경(광양), (주)대길산업(장흥, 영암,강진)지정폐기물:(주)인선이엔티 83
 
0.8%
지장물철거:화순(신명건설),보성(세일건설),순천(자연토건)건설폐기물처리용역-파쇄(화순:두제산업, 보성:그린환경, 순천:남부환경)건설폐기물처리용역-소각(화순,보성,순천:동양환경)지정폐기물처리용역(화순,보성,순천:이에스티,빛고을환경) 82
 
0.8%
철거:(주)신태전건설산업(화순), (주)도건개발(순천,광양)건설폐기물:(주)대길산업(화순),(유)남해환경(보성), (주)전일환경(순천,광양) 66
 
0.7%
지장물철거:화순,담양,광양(창명건업),보성,장흥,강진,영암(남해환경)건설폐기물처리용역-파쇄(화순,담양,광양:삼려환경, 보성,장흥,강진,영암:유승건기산업)건설폐기물처리용역-소각(화순,담양,광양,보성,장흥,강진,영암:초당환경)지정폐기물처리용역-폐석면(화순,담양,광양,보성,장흥,강진,영암 처리:유성, 수집운반:동남환경) 49
 
0.5%
철거:(주)도양기업(순천), (주)대성건업(보성),(주)지오콘(화순),(주)인경건설(장흥,영암,강진) 49
 
0.5%
철거:(주)순천건설(순천,광양,화순,보성)건설폐기물:(주)미래환경개발산업(순천,보성), (주)광주환경산업(화순,보성), (주)초당산업(광양) 41
 
0.4%
지장물철거 : (주)삼협기공(승주, 상사, 낙안), (주)활성건설(송광), (주)에스엠건설(송광,외서) 건설폐기물 처리용역 : (주)두제산업(승주, 상사, 낙안), (주)초당산업(송광, 외서)지정폐기물 처리용역: (주)인선이엔티 34
 
0.3%
철거:(주)해강건설(화순,담양),(주)세강건설(보성)건설폐기물:(주)대길환경산업(화순,담양), (주)초당산업(보성) 27
 
0.3%
Other values (4) 29
 
0.3%

Length

2023-12-12T13:54:04.006700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 9457
79.0%
주)전일환경(순천,광양 149
 
1.2%
유)전일환경(보성 83
 
0.7%
영암,강진)지정폐기물:(주)인선이엔티 83
 
0.7%
철거:(주)청웅건설(화순),(주)해광개발(보성),(주)지오콘(순천,광양)건서례기물:(주)대길산업(화순),(유)남해환경(보성 83
 
0.7%
유)삼려환경(광양 83
 
0.7%
주)금성환경산업 83
 
0.7%
주)대길산업(장흥 83
 
0.7%
주)다일건설(장흥,영암,강진)건설폐기물:(주)세계호나경(순천 83
 
0.7%
주)남경이엔지개발(광양 83
 
0.7%
Other values (36) 1705
 
14.2%

공사기간시작_1
Date

MISSING 

Distinct13
Distinct (%)2.4%
Missing9457
Missing (%)94.6%
Memory size156.2 KiB
Minimum2004-04-19 00:00:00
Maximum2010-09-06 00:00:00
2023-12-12T13:54:04.170467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:54:04.307546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)

공사기간종료_1
Date

MISSING 

Distinct13
Distinct (%)2.4%
Missing9457
Missing (%)94.6%
Memory size156.2 KiB
Minimum2004-05-18 00:00:00
Maximum2010-12-14 00:00:00
2023-12-12T13:54:04.460912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:54:04.575365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)

처리금액총액
Real number (ℝ)

MISSING 

Distinct13
Distinct (%)2.4%
Missing9457
Missing (%)94.6%
Infinite0
Infinite (%)0.0%
Mean2.5989664 × 109
Minimum7855645
Maximum4.4309021 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T13:54:04.677672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7855645
5-th percentile3.85755 × 108
Q11.8725984 × 109
median2.7133236 × 109
Q33.621404 × 109
95-th percentile4.4309021 × 109
Maximum4.4309021 × 109
Range4.4230464 × 109
Interquartile range (IQR)1.7488056 × 109

Descriptive statistics

Standard deviation1.1752353 × 109
Coefficient of variation (CV)0.45219332
Kurtosis-0.57490038
Mean2.5989664 × 109
Median Absolute Deviation (MAD)8.4072515 × 108
Skewness-0.1696034
Sum1.4112388 × 1012
Variance1.3811779 × 1018
MonotonicityNot monotonic
2023-12-12T13:54:04.800436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
2941396497 83
 
0.8%
4430902070 83
 
0.8%
2362894830 82
 
0.8%
3621404020 66
 
0.7%
1563963200 49
 
0.5%
2713323580 49
 
0.5%
385755000 41
 
0.4%
2099800000 34
 
0.3%
1872598430 27
 
0.3%
593860000 19
 
0.2%
Other values (3) 10
 
0.1%
(Missing) 9457
94.6%
ValueCountFrequency (%)
7855645 1
 
< 0.1%
298384700 1
 
< 0.1%
385755000 41
0.4%
593860000 19
 
0.2%
952751000 8
 
0.1%
1563963200 49
0.5%
1872598430 27
 
0.3%
2099800000 34
0.3%
2362894830 82
0.8%
2713323580 49
0.5%
ValueCountFrequency (%)
4430902070 83
0.8%
3621404020 66
0.7%
2941396497 83
0.8%
2713323580 49
0.5%
2362894830 82
0.8%
2099800000 34
0.3%
1872598430 27
 
0.3%
1563963200 49
0.5%
952751000 8
 
0.1%
593860000 19
 
0.2%

처리금액지장물
Real number (ℝ)

MISSING 

Distinct13
Distinct (%)2.4%
Missing9457
Missing (%)94.6%
Infinite0
Infinite (%)0.0%
Mean1.1716569 × 109
Minimum3300070
Maximum1.9136813 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T13:54:04.920090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3300070
5-th percentile1.34849 × 108
Q19.603631 × 108
median1.2095675 × 109
Q31.5580537 × 109
95-th percentile1.9136813 × 109
Maximum1.9136813 × 109
Range1.9103812 × 109
Interquartile range (IQR)5.9769061 × 108

Descriptive statistics

Standard deviation4.8684697 × 108
Coefficient of variation (CV)0.4155201
Kurtosis-0.065902124
Mean1.1716569 × 109
Median Absolute Deviation (MAD)2.492044 × 108
Skewness-0.43445999
Sum6.3620967 × 1011
Variance2.3701997 × 1017
MonotonicityNot monotonic
2023-12-12T13:54:05.059737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
1209567497 83
 
0.8%
1913681280 83
 
0.8%
1254835710 82
 
0.8%
1558053710 66
 
0.7%
794215000 49
 
0.5%
1095096730 49
 
0.5%
134849000 41
 
0.4%
1083180000 34
 
0.3%
960363102 27
 
0.3%
400020000 19
 
0.2%
Other values (3) 10
 
0.1%
(Missing) 9457
94.6%
ValueCountFrequency (%)
3300070 1
 
< 0.1%
114321240 1
 
< 0.1%
134849000 41
0.4%
333868000 8
 
0.1%
400020000 19
 
0.2%
794215000 49
0.5%
960363102 27
 
0.3%
1083180000 34
0.3%
1095096730 49
0.5%
1209567497 83
0.8%
ValueCountFrequency (%)
1913681280 83
0.8%
1558053710 66
0.7%
1254835710 82
0.8%
1209567497 83
0.8%
1095096730 49
0.5%
1083180000 34
0.3%
960363102 27
 
0.3%
794215000 49
0.5%
400020000 19
 
0.2%
333868000 8
 
0.1%

처리금액건설폐기물
Real number (ℝ)

MISSING 

Distinct13
Distinct (%)2.4%
Missing9457
Missing (%)94.6%
Infinite0
Infinite (%)0.0%
Mean1.3970686 × 109
Minimum4555575
Maximum2.4364843 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T13:54:05.187917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4555575
5-th percentile2.50906 × 108
Q18.9078533 × 108
median1.5959399 × 109
Q32.0412027 × 109
95-th percentile2.4364843 × 109
Maximum2.4364843 × 109
Range2.4319288 × 109
Interquartile range (IQR)1.1504174 × 109

Descriptive statistics

Standard deviation6.9483803 × 108
Coefficient of variation (CV)0.49735427
Kurtosis-1.0688454
Mean1.3970686 × 109
Median Absolute Deviation (MAD)5.3089228 × 108
Skewness-0.070391552
Sum7.5860825 × 1011
Variance4.8279989 × 1017
MonotonicityNot monotonic
2023-12-12T13:54:05.309905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
1731829000 83
 
0.8%
2436484340 83
 
0.8%
1065047580 82
 
0.8%
2041202690 66
 
0.7%
735161000 49
 
0.5%
1595939860 49
 
0.5%
250906000 41
 
0.4%
982514000 34
 
0.3%
890785328 27
 
0.3%
183590000 19
 
0.2%
Other values (3) 10
 
0.1%
(Missing) 9457
94.6%
ValueCountFrequency (%)
4555575 1
 
< 0.1%
183590000 19
 
0.2%
184063460 1
 
< 0.1%
250906000 41
0.4%
617546000 8
 
0.1%
735161000 49
0.5%
890785328 27
 
0.3%
982514000 34
0.3%
1065047580 82
0.8%
1595939860 49
0.5%
ValueCountFrequency (%)
2436484340 83
0.8%
2041202690 66
0.7%
1731829000 83
0.8%
1595939860 49
0.5%
1065047580 82
0.8%
982514000 34
0.3%
890785328 27
 
0.3%
735161000 49
0.5%
617546000 8
 
0.1%
250906000 41
0.4%

처리금액지정폐기물
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)1.8%
Missing9457
Missing (%)94.6%
Infinite0
Infinite (%)0.0%
Mean30240976
Minimum0
Maximum80736450
Zeros126
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T13:54:05.459828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q110250000
median22286990
Q343011540
95-th percentile80736450
Maximum80736450
Range80736450
Interquartile range (IQR)32761540

Descriptive statistics

Standard deviation25966733
Coefficient of variation (CV)0.85866056
Kurtosis-0.32297341
Mean30240976
Median Absolute Deviation (MAD)20724550
Skewness0.73568159
Sum1.642085 × 1010
Variance6.7427123 × 1014
MonotonicityNot monotonic
2023-12-12T13:54:05.579584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 126
 
1.3%
80736450 83
 
0.8%
43011540 82
 
0.8%
22147620 66
 
0.7%
34587200 49
 
0.5%
22286990 49
 
0.5%
34106000 34
 
0.3%
21450000 27
 
0.3%
10250000 19
 
0.2%
1337000 8
 
0.1%
(Missing) 9457
94.6%
ValueCountFrequency (%)
0 126
1.3%
1337000 8
 
0.1%
10250000 19
 
0.2%
21450000 27
 
0.3%
22147620 66
0.7%
22286990 49
 
0.5%
34106000 34
 
0.3%
34587200 49
 
0.5%
43011540 82
0.8%
80736450 83
0.8%
ValueCountFrequency (%)
80736450 83
0.8%
43011540 82
0.8%
34587200 49
 
0.5%
34106000 34
 
0.3%
22286990 49
 
0.5%
22147620 66
0.7%
21450000 27
 
0.3%
10250000 19
 
0.2%
1337000 8
 
0.1%
0 126
1.3%

건폐발생량
Real number (ℝ)

MISSING 

Distinct13
Distinct (%)2.4%
Missing9457
Missing (%)94.6%
Infinite0
Infinite (%)0.0%
Mean43240.813
Minimum320
Maximum72753
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T13:54:05.719181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum320
5-th percentile10382
Q124215.82
median47962
Q364586
95-th percentile72753
Maximum72753
Range72433
Interquartile range (IQR)40370.18

Descriptive statistics

Standard deviation20865.844
Coefficient of variation (CV)0.48254976
Kurtosis-1.1389279
Mean43240.813
Median Absolute Deviation (MAD)16624
Skewness-0.1639801
Sum23479761
Variance4.3538343 × 108
MonotonicityNot monotonic
2023-12-12T13:54:05.846576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
52457.0 83
 
0.8%
72753.0 83
 
0.8%
39622.61 82
 
0.8%
64586.0 66
 
0.7%
24215.82 49
 
0.5%
47962.0 49
 
0.5%
10382.0 41
 
0.4%
23335.0 34
 
0.3%
21592.0 27
 
0.3%
5690.0 19
 
0.2%
Other values (3) 10
 
0.1%
(Missing) 9457
94.6%
ValueCountFrequency (%)
320.0 1
 
< 0.1%
5638.0 1
 
< 0.1%
5690.0 19
 
0.2%
10382.0 41
0.4%
15348.0 8
 
0.1%
21592.0 27
 
0.3%
23335.0 34
0.3%
24215.82 49
0.5%
39622.61 82
0.8%
47962.0 49
0.5%
ValueCountFrequency (%)
72753.0 83
0.8%
64586.0 66
0.7%
52457.0 83
0.8%
47962.0 49
0.5%
39622.61 82
0.8%
24215.82 49
0.5%
23335.0 34
0.3%
21592.0 27
 
0.3%
15348.0 8
 
0.1%
10382.0 41
0.4%

지폐발생량
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)1.8%
Missing9457
Missing (%)94.6%
Infinite0
Infinite (%)0.0%
Mean125.37628
Minimum0
Maximum256
Zeros126
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T13:54:05.989918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q137
median161.59
Q3175
95-th percentile256
Maximum256
Range256
Interquartile range (IQR)138

Descriptive statistics

Standard deviation87.56104
Coefficient of variation (CV)0.69838601
Kurtosis-1.1291984
Mean125.37628
Median Absolute Deviation (MAD)60.92
Skewness-0.19603525
Sum68079.32
Variance7666.9357
MonotonicityNot monotonic
2023-12-12T13:54:06.145372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0.0 126
 
1.3%
256.0 83
 
0.8%
161.59 82
 
0.8%
175.0 66
 
0.7%
129.84 49
 
0.5%
184.0 49
 
0.5%
100.67 34
 
0.3%
93.0 27
 
0.3%
37.0 19
 
0.2%
2.0 8
 
0.1%
(Missing) 9457
94.6%
ValueCountFrequency (%)
0.0 126
1.3%
2.0 8
 
0.1%
37.0 19
 
0.2%
93.0 27
 
0.3%
100.67 34
 
0.3%
129.84 49
 
0.5%
161.59 82
0.8%
175.0 66
0.7%
184.0 49
 
0.5%
256.0 83
0.8%
ValueCountFrequency (%)
256.0 83
0.8%
184.0 49
 
0.5%
175.0 66
0.7%
161.59 82
0.8%
129.84 49
 
0.5%
100.67 34
 
0.3%
93.0 27
 
0.3%
37.0 19
 
0.2%
2.0 8
 
0.1%
0.0 126
1.3%

건설폐기물발생량파쇄
Real number (ℝ)

MISSING  ZEROS 

Distinct19
Distinct (%)3.9%
Missing9512
Missing (%)95.1%
Infinite0
Infinite (%)0.0%
Mean3778.8151
Minimum0
Maximum14047.47
Zeros243
Zeros (%)2.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T13:54:06.268535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2919.32
Q36378
95-th percentile11124
Maximum14047.47
Range14047.47
Interquartile range (IQR)6378

Descriptive statistics

Standard deviation4346.9718
Coefficient of variation (CV)1.1503531
Kurtosis-0.595331
Mean3778.8151
Median Absolute Deviation (MAD)2919.32
Skewness0.77180342
Sum1844061.8
Variance18896164
MonotonicityNot monotonic
2023-12-12T13:54:06.386982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0.0 243
 
2.4%
11124.0 28
 
0.3%
5225.0 27
 
0.3%
11018.0 24
 
0.2%
14047.47 18
 
0.2%
4608.0 16
 
0.2%
7226.0 16
 
0.2%
9313.96 16
 
0.2%
5088.0 15
 
0.1%
6521.0 13
 
0.1%
Other values (9) 72
 
0.7%
(Missing) 9512
95.1%
ValueCountFrequency (%)
0.0 243
2.4%
2919.32 2
 
< 0.1%
4244.48 12
 
0.1%
4608.0 16
 
0.2%
4680.96 3
 
< 0.1%
4800.51 3
 
< 0.1%
4923.0 10
 
0.1%
5021.69 11
 
0.1%
5088.0 15
 
0.1%
5225.0 27
 
0.3%
ValueCountFrequency (%)
14047.47 18
0.2%
11124.0 28
0.3%
11018.0 24
0.2%
9313.96 16
0.2%
7226.0 16
0.2%
6521.0 13
0.1%
6378.0 11
 
0.1%
6250.57 8
 
0.1%
5410.0 12
0.1%
5225.0 27
0.3%

건설폐기물발생량소각
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)1.6%
Missing9512
Missing (%)95.1%
Infinite0
Infinite (%)0.0%
Mean46.098361
Minimum0
Maximum290
Zeros334
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T13:54:06.496639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q394
95-th percentile197
Maximum290
Range290
Interquartile range (IQR)94

Descriptive statistics

Standard deviation74.726651
Coefficient of variation (CV)1.6210262
Kurtosis0.99563392
Mean46.098361
Median Absolute Deviation (MAD)0
Skewness1.4110479
Sum22496
Variance5584.0724
MonotonicityNot monotonic
2023-12-12T13:54:06.594932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 334
 
3.3%
149 43
 
0.4%
94 39
 
0.4%
168 24
 
0.2%
197 18
 
0.2%
98 16
 
0.2%
290 11
 
0.1%
29 3
 
< 0.1%
(Missing) 9512
95.1%
ValueCountFrequency (%)
0 334
3.3%
29 3
 
< 0.1%
94 39
 
0.4%
98 16
 
0.2%
149 43
 
0.4%
168 24
 
0.2%
197 18
 
0.2%
290 11
 
0.1%
ValueCountFrequency (%)
290 11
 
0.1%
197 18
 
0.2%
168 24
 
0.2%
149 43
 
0.4%
98 16
 
0.2%
94 39
 
0.4%
29 3
 
< 0.1%
0 334
3.3%

지정폐기물발생량석면
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)1.4%
Missing9512
Missing (%)95.1%
Infinite0
Infinite (%)0.0%
Mean35.387213
Minimum0
Maximum257
Zeros337
Zeros (%)3.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T13:54:06.702284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q383.1
95-th percentile154
Maximum257
Range257
Interquartile range (IQR)83.1

Descriptive statistics

Standard deviation60.753364
Coefficient of variation (CV)1.7168169
Kurtosis2.5110103
Mean35.387213
Median Absolute Deviation (MAD)0
Skewness1.7367565
Sum17268.96
Variance3690.9713
MonotonicityNot monotonic
2023-12-12T13:54:06.826564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0.0 337
 
3.4%
154.0 43
 
0.4%
90.0 39
 
0.4%
83.1 25
 
0.2%
93.1 17
 
0.2%
40.61 16
 
0.2%
257.0 11
 
0.1%
(Missing) 9512
95.1%
ValueCountFrequency (%)
0.0 337
3.4%
40.61 16
 
0.2%
83.1 25
 
0.2%
90.0 39
 
0.4%
93.1 17
 
0.2%
154.0 43
 
0.4%
257.0 11
 
0.1%
ValueCountFrequency (%)
257.0 11
 
0.1%
154.0 43
 
0.4%
93.1 17
 
0.2%
90.0 39
 
0.4%
83.1 25
 
0.2%
40.61 16
 
0.2%
0.0 337
3.4%

건설폐기물처리비파쇄
Real number (ℝ)

MISSING  ZEROS 

Distinct19
Distinct (%)3.9%
Missing9512
Missing (%)95.1%
Infinite0
Infinite (%)0.0%
Mean1.2689628 × 108
Minimum0
Maximum4.733756 × 108
Zeros243
Zeros (%)2.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T13:54:06.936413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1.06177 × 108
Q31.933493 × 108
95-th percentile3.977697 × 108
Maximum4.733756 × 108
Range4.733756 × 108
Interquartile range (IQR)1.933493 × 108

Descriptive statistics

Standard deviation1.493359 × 108
Coefficient of variation (CV)1.1768344
Kurtosis-0.46070361
Mean1.2689628 × 108
Median Absolute Deviation (MAD)1.06177 × 108
Skewness0.86242345
Sum6.1925384 × 1010
Variance2.2301212 × 1016
MonotonicityNot monotonic
2023-12-12T13:54:07.045309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 243
 
2.4%
389567600 28
 
0.3%
187422000 27
 
0.3%
397769700 24
 
0.2%
473375600 18
 
0.2%
141116950 16
 
0.2%
193349300 16
 
0.2%
324914000 16
 
0.2%
158958500 15
 
0.1%
199587000 13
 
0.1%
Other values (9) 72
 
0.7%
(Missing) 9512
95.1%
ValueCountFrequency (%)
0 243
2.4%
106177000 2
 
< 0.1%
134338000 12
 
0.1%
141116950 16
 
0.2%
154435000 3
 
< 0.1%
157994910 10
 
0.1%
158958500 15
 
0.1%
166227000 3
 
< 0.1%
167832800 11
 
0.1%
175980000 12
 
0.1%
ValueCountFrequency (%)
473375600 18
0.2%
397769700 24
0.2%
389567600 28
0.3%
324914000 16
0.2%
231924000 8
 
0.1%
199587000 13
0.1%
198283000 11
 
0.1%
193349300 16
0.2%
187422000 27
0.3%
175980000 12
0.1%

건설폐기물처리비소각
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)1.6%
Missing9512
Missing (%)95.1%
Infinite0
Infinite (%)0.0%
Mean11711427
Minimum0
Maximum68432100
Zeros334
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T13:54:07.143073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q323689000
95-th percentile54154820
Maximum68432100
Range68432100
Interquartile range (IQR)23689000

Descriptive statistics

Standard deviation18926152
Coefficient of variation (CV)1.6160414
Kurtosis0.64361987
Mean11711427
Median Absolute Deviation (MAD)0
Skewness1.3622104
Sum5.7151765 × 109
Variance3.5819921 × 1014
MonotonicityNot monotonic
2023-12-12T13:54:07.244420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 334
 
3.3%
34819500 43
 
0.4%
23689000 39
 
0.4%
46077120 24
 
0.2%
54154820 18
 
0.2%
27277700 16
 
0.2%
68432100 11
 
0.1%
8077700 3
 
< 0.1%
(Missing) 9512
95.1%
ValueCountFrequency (%)
0 334
3.3%
8077700 3
 
< 0.1%
23689000 39
 
0.4%
27277700 16
 
0.2%
34819500 43
 
0.4%
46077120 24
 
0.2%
54154820 18
 
0.2%
68432100 11
 
0.1%
ValueCountFrequency (%)
68432100 11
 
0.1%
54154820 18
 
0.2%
46077120 24
 
0.2%
34819500 43
 
0.4%
27277700 16
 
0.2%
23689000 39
 
0.4%
8077700 3
 
< 0.1%
0 334
3.3%

지정폐기물처리비석면
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)1.2%
Missing9512
Missing (%)95.1%
Infinite0
Infinite (%)0.0%
Mean12786420
Minimum0
Maximum82156000
Zeros337
Zeros (%)3.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T13:54:07.357617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q332461740
95-th percentile56864540
Maximum82156000
Range82156000
Interquartile range (IQR)32461740

Descriptive statistics

Standard deviation21425202
Coefficient of variation (CV)1.6756216
Kurtosis1.3082565
Mean12786420
Median Absolute Deviation (MAD)0
Skewness1.5266291
Sum6.2397731 × 109
Variance4.5903928 × 1014
MonotonicityNot monotonic
2023-12-12T13:54:07.455286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 337
 
3.4%
56864540 43
 
0.4%
32761000 42
 
0.4%
32461740 39
 
0.4%
15557000 16
 
0.2%
82156000 11
 
0.1%
(Missing) 9512
95.1%
ValueCountFrequency (%)
0 337
3.4%
15557000 16
 
0.2%
32461740 39
 
0.4%
32761000 42
 
0.4%
56864540 43
 
0.4%
82156000 11
 
0.1%
ValueCountFrequency (%)
82156000 11
 
0.1%
56864540 43
 
0.4%
32761000 42
 
0.4%
32461740 39
 
0.4%
15557000 16
 
0.2%
0 337
3.4%

차수코드
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9512 
1
 
188
2
 
159
3
 
75
4
 
37

Length

Max length4
Median length4
Mean length3.8536
Min length1

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> 9512
95.1%
1 188
 
1.9%
2 159
 
1.6%
3 75
 
0.8%
4 37
 
0.4%
5 29
 
0.3%

Length

2023-12-12T13:54:07.582591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:54:07.693901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9512
95.1%
1 188
 
1.9%
2 159
 
1.6%
3 75
 
0.8%
4 37
 
0.4%
5 29
 
0.3%

차수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9512 
1차
 
188
2차
 
159
3차
 
75
4차
 
37

Length

Max length4
Median length4
Mean length3.9024
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> 9512
95.1%
1차 188
 
1.9%
2차 159
 
1.6%
3차 75
 
0.8%
4차 37
 
0.4%
5차 29
 
0.3%

Length

2023-12-12T13:54:07.835650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:54:07.973383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9512
95.1%
1차 188
 
1.9%
2차 159
 
1.6%
3차 75
 
0.8%
4차 37
 
0.4%
5차 29
 
0.3%

Sample

접수번호접수일자필지수필지번호토지소재지면적지목용도규제지역하천명호소명거리범례하천과거리용도지역비고매수제한지역이름우선매수지역배점표처리지침배점선택경계거리매수현황번호현지조사감정의뢰매매계약매매완료매수상황철거여부생태복원기타사후관리매매계약일련번호계약체결신청일자매매계약율토지외물건수기타사후관리번호울타리설치경계측량경고표지판특이사항벌목특이사항체크변동사항생태복원번호공사명공사대상공사기간시작공사기간종료계약업체공사금액철거번호공사명_1계약업체_1공사기간시작_1공사기간종료_1처리금액총액처리금액지장물처리금액건설폐기물처리금액지정폐기물건폐발생량지폐발생량건설폐기물발생량파쇄건설폐기물발생량소각지정폐기물발생량석면건설폐기물처리비파쇄건설폐기물처리비소각지정폐기물처리비석면차수코드차수
140872014-80222014-12-3122전라남도 순천시 송광면 봉산리 165734.0답전ㆍ답기타지역송광천주암호1000977보전관리지역<NA><NA>X2009년기준42완료완료완료완료완료대기대기대기54772015-05-26<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
53782007-2087-12007-01-0922전라남도 보성군 겸백면 석호리 258175.0답전ㆍ답기타지역보성강주암호500494관리지역<NA><NA>X2003년기준12완료완료완료완료완료대기완료대기7852008-08-26753<NA><NA><NA><NA><NA><NA><NA><NA>1122017년 영산강섬진강수계1차 생태복원공사<NA>2017-02-012017-12-31<NA>0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
9112003-2462003-03-3131전라남도 보성군 겸백면 석호리 6332500.0답축사수변구역<NA>주암호300200<NA><NA><NA>X2003년기준<NA>1완료완료완료완료완료완료완료대기11612004-12-047523<NA><NA><NA><NA><NA><NA><NA><NA>772015년도영산강.섬진강수계1차생태복원공사<NA>2015-02-012015-12-31<NA>053차 지장물철거 및 폐기물처리용역(2005년)철거:(주)청웅건설(화순),(주)해광개발(보성),(주)지오콘(순천,광양)건서례기물:(주)대길산업(화순),(유)남해환경(보성), (주)전일환경(순천,광양)2006-01-062006-04-05294139649712095674971731829000052457.00.0<NA><NA><NA><NA><NA><NA><NA><NA>
108942011-59262011-12-302710전라남도 광양시 진상면 비평리 340-21156.0전전ㆍ답수변구역수어천수어호300225보전관리지역<NA><NA>X2009년기준210대기대기대기대기연기대기대기대기<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
85312009-43292009-12-1687전라남도 영암군 금정면 청용리 1096664.0답전ㆍ답기타지역<NA>탐진호1000598보전관리지역<NA><NA>X2009년기준47완료완료완료완료완료대기대기대기24162010-06-23100<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
41522006-13462006-01-1111전라남도 화순군 사평면 남계리 21625.0과수원전ㆍ답수변구역내남천주암호300175농림지역<NA>소유권이전 5년미만X2009년기준21대기대기대기대기제한대기대기대기<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
82552009-41342009-10-06107전라남도 순천시 송광면 신평리 11319009.0전전ㆍ답수변구역<NA>주암호300125보전관리지역<NA><NA>X2009년기준27대기대기대기대기철회대기대기대기<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
46972006-16382006-06-29125전라남도 장흥군 유치면 용문리 88-16236.0대대지(잡종지)수변구역용문천탐진호5039<NA><NA><NA>X2009년기준15완료완료완료완료완료대기완료대기1012006-10-1075<NA><NA><NA><NA><NA><NA><NA><NA><NA>742014년도영산강.섬진강수계2차생태복원공사<NA>2014-02-012014-12-31<NA>0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
55062007-21782007-02-2111전라남도 화순군 이서면 장학리 산1828069.0임야임야수변구역<NA>동복호500<NA><NA><NA>X2003년기준<NA>1대기대기대기대기철회대기대기대기<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
142732015-81402015-04-0731전라남도 순천시 송광면 봉산리 187-2605.0답전ㆍ답기타지역송광천주암호1000896보전관리지역<NA><NA>X2009년기준41완료완료완료완료완료대기대기대기61682015-12-27<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
접수번호접수일자필지수필지번호토지소재지면적지목용도규제지역하천명호소명거리범례하천과거리용도지역비고매수제한지역이름우선매수지역배점표처리지침배점선택경계거리매수현황번호현지조사감정의뢰매매계약매매완료매수상황철거여부생태복원기타사후관리매매계약일련번호계약체결신청일자매매계약율토지외물건수기타사후관리번호울타리설치경계측량경고표지판특이사항벌목특이사항체크변동사항생태복원번호공사명공사대상공사기간시작공사기간종료계약업체공사금액철거번호공사명_1계약업체_1공사기간시작_1공사기간종료_1처리금액총액처리금액지장물처리금액건설폐기물처리금액지정폐기물건폐발생량지폐발생량건설폐기물발생량파쇄건설폐기물발생량소각지정폐기물발생량석면건설폐기물처리비파쇄건설폐기물처리비소각지정폐기물처리비석면차수코드차수
147702015-84392015-11-0511전라남도 순천시 송광면 신평리 461-7336.0대주택등자연마을<NA>주암호300159계획관리지역<NA><NA>X2009년기준21완료완료완료완료완료대기대기대기60682016-06-27<NA>19<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
44112006-14722006-04-0721전라남도 순천시 승주읍 평중리 51-4184.0대숙박·음식점도시지역이사천상사호300184<NA><NA><NA>X2009년기준21완료완료완료완료완료완료대기대기1192006-11-16758<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1008년 1차 지장물철거 및 폐기물처리용역철거:(주)구미녹색환경(순천), (주)도솔환경산업(보성), (주)은성건선(화순), (주)남경이엔지개발(광양), (주)다일건설(장흥,영암,강진)건설폐기물:(주)세계호나경(순천), (유)전일환경(보성), (주)금성환경산업, (유)삼려환경(광양), (주)대길산업(장흥, 영암,강진)지정폐기물:(주)인선이엔티2008-06-262008-11-304430902070191368128024364843408073645072753.0256.0<NA><NA><NA><NA><NA><NA><NA><NA>
102902011-55222011-06-2873전라남도 화순군 사평면 다산리 407-2446.0임야임야수변구역송암천주암호500399보전관리지역<NA><NA>X2009년기준33완료완료완료완료완료대기대기대기29652011-11-11100<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
126042013-70452013-06-133320전라남도 강진군 옴천면 봉림리 382165.0답전ㆍ답상수원보호구역옴천천탐진호1000863자연환경보전지역<NA><NA>X2009년기준420완료완료완료완료완료대기대기대기42392013-11-11100<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
169392018-98302018-06-2522전라남도 순천시 송광면 신평리 360-1956.0전전ㆍ답기타지역<NA>주암호1000537생산관리지역<NA><NA>X2019년기준42대기대기대기대기대기대기대기대기<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
40302005-9452005-01-2432전라남도 화순군 사평면 사평리 62-54148.0답전ㆍ답도시지역<NA>주암호10071도시지역<NA>하수처리구역 내 건축물X2009년기준22완료완료대기대기불응대기대기대기<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
92222010-47992010-07-2922전라남도 보성군 복내면 계산리 302347.0답전ㆍ답기타지역유정천주암호1000526생산관리지역<NA><NA>X2009년기준42완료완료완료완료완료대기대기대기31212011-12-05100<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
84322009-42582009-11-2521전라남도 영암군 금정면 세류리 1543180.0답전ㆍ답수변구역탐진강탐진호5013농림지역<NA><NA>X2009년기준11완료완료완료완료완료대기완료대기23872010-06-28100<NA><NA><NA><NA><NA><NA><NA><NA><NA>57수변생태벨트 조성공사<NA>2011-05-172011-07-04(주)신신조경392120000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
159622017-92442017-03-0911전라남도 화순군 사평면 장전리 337614.0답전ㆍ답수변구역오룡천주암호300159보전관리지역<NA><NA>X2009년기준21완료완료대기대기대기대기대기대기<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
146772015-83832015-08-2411전라남도 강진군 옴천면 황막리 399655.0전전ㆍ답상수원보호구역신덕천탐진호500430자연환경보전지역<NA><NA>X2009년기준31완료완료완료완료완료대기대기대기61002016-06-10<NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>