Overview

Dataset statistics

Number of variables70
Number of observations10000
Missing cells189794
Missing cells (%)27.1%
Duplicate rows12
Duplicate rows (%)0.1%
Total size in memory5.8 MiB
Average record size in memory613.0 B

Variable types

Numeric27
Text9
DateTime8
Categorical23
Unsupported1
Boolean2

Dataset

Description토지매수정보(지역구분,지목,면적,하천경계로부터의거리,계약체결일,이행완료일,매수상황진행상태 등)
URLhttps://www.data.go.kr/data/15069247/fileData.do

Alerts

농업진흥구역 has constant value ""Constant
우선매수 has constant value ""Constant
Dataset has 12 (0.1%) duplicate rowsDuplicates
지역구분 is highly imbalanced (59.1%)Imbalance
지목 is highly imbalanced (51.8%)Imbalance
폐수배출시설공장 is highly imbalanced (99.3%)Imbalance
특정토양오염관리대상시설 is highly imbalanced (99.6%)Imbalance
돈사허가규모이상 is highly imbalanced (99.9%)Imbalance
돈사신고규모이상 is highly imbalanced (99.9%)Imbalance
우사허가규모이상 is highly imbalanced (99.4%)Imbalance
우사신고규모이상 is highly imbalanced (99.5%)Imbalance
우사신고규모미만 is highly imbalanced (99.9%)Imbalance
기타신고규모이상 is highly imbalanced (99.4%)Imbalance
기타신고규모미만 is highly imbalanced (99.9%)Imbalance
목욕장숙박식품접객업소공동주택 is highly imbalanced (97.9%)Imbalance
임야 is highly imbalanced (99.9%)Imbalance
상수원보호구역 is highly imbalanced (96.9%)Imbalance
수변구역 is highly imbalanced (92.5%)Imbalance
특별대책지역1권역 is highly imbalanced (99.0%)Imbalance
특별대책지역2권역 is highly imbalanced (97.8%)Imbalance
연접토지 is highly imbalanced (97.8%)Imbalance
경사도 is highly imbalanced (99.3%)Imbalance
하천경계로부터의거리 is highly imbalanced (76.7%)Imbalance
지목_1 is highly imbalanced (51.9%)Imbalance
공시지가 has 155 (1.6%) missing valuesMissing
매수시작순번 has 125 (1.2%) missing valuesMissing
매수시작접수일 has 125 (1.2%) missing valuesMissing
거리 has 1401 (14.0%) missing valuesMissing
거리순번 has 544 (5.4%) missing valuesMissing
일자 has 544 (5.4%) missing valuesMissing
현지조사순번 has 3221 (32.2%) missing valuesMissing
출장목적 has 7668 (76.7%) missing valuesMissing
출장시작일 has 3221 (32.2%) missing valuesMissing
출장종료일 has 3222 (32.2%) missing valuesMissing
출장장소 has 7698 (77.0%) missing valuesMissing
순번 has 9124 (91.2%) missing valuesMissing
주택등일반건축물 has 9980 (99.8%) missing valuesMissing
나대지전답과수원 has 9590 (95.9%) missing valuesMissing
점오염원 has 9925 (99.2%) missing valuesMissing
비점오염원 has 9404 (94.0%) missing valuesMissing
총점 has 9124 (91.2%) missing valuesMissing
거리_1 has 9124 (91.2%) missing valuesMissing
총점2 has 9124 (91.2%) missing valuesMissing
농업진흥구역 has 9850 (98.5%) missing valuesMissing
우선매수 has 9995 (> 99.9%) missing valuesMissing
감정의뢰순번 has 2674 (26.7%) missing valuesMissing
의뢰번호 has 2827 (28.3%) missing valuesMissing
의뢰일자 has 2690 (26.9%) missing valuesMissing
매수가격개수 has 5264 (52.6%) missing valuesMissing
매매계약순번 has 5283 (52.8%) missing valuesMissing
매수완료번호 has 5283 (52.8%) missing valuesMissing
신청서접수일 has 5284 (52.8%) missing valuesMissing
매수완료순번 has 5276 (52.8%) missing valuesMissing
계약체결일 has 5276 (52.8%) missing valuesMissing
이행예정일 has 5934 (59.3%) missing valuesMissing
이행완료일 has 5915 (59.2%) missing valuesMissing
매수완료번호_1 has 5283 (52.8%) missing valuesMissing
매수상황순번 has 4357 (43.6%) missing valuesMissing
매수완료번호_2 has 5276 (52.8%) missing valuesMissing
매수완료번호 is highly skewed (γ1 = 36.41627261)Skewed
매수완료번호_1 is highly skewed (γ1 = 36.41616423)Skewed
매수완료번호_2 is highly skewed (γ1 = 36.44330593)Skewed
거리 is an unsupported type, check if it needs cleaning or further analysisUnsupported
토지외물건개수 has 8234 (82.3%) zerosZeros

Reproduction

Analysis started2023-12-12 02:22:20.917457
Analysis finished2023-12-12 02:22:23.932597
Duration3.02 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

매도신청순번
Real number (ℝ)

Distinct4171
Distinct (%)41.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2508.4546
Minimum2
Maximum5624
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T11:22:24.013098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile148
Q11177.75
median2570.5
Q33670.25
95-th percentile5169.05
Maximum5624
Range5622
Interquartile range (IQR)2492.5

Descriptive statistics

Standard deviation1526.8373
Coefficient of variation (CV)0.60867646
Kurtosis-1.0313559
Mean2508.4546
Median Absolute Deviation (MAD)1212.5
Skewness0.057551472
Sum25084546
Variance2331232
MonotonicityNot monotonic
2023-12-12T11:22:24.194332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3482 151
 
1.5%
3483 141
 
1.4%
72 89
 
0.9%
3513 69
 
0.7%
3514 64
 
0.6%
3964 64
 
0.6%
73 63
 
0.6%
5322 34
 
0.3%
3517 31
 
0.3%
3780 29
 
0.3%
Other values (4161) 9265
92.7%
ValueCountFrequency (%)
2 1
 
< 0.1%
3 4
< 0.1%
4 1
 
< 0.1%
5 3
< 0.1%
6 2
< 0.1%
7 1
 
< 0.1%
8 2
< 0.1%
9 2
< 0.1%
10 3
< 0.1%
11 4
< 0.1%
ValueCountFrequency (%)
5624 1
< 0.1%
5623 1
< 0.1%
5622 1
< 0.1%
5621 1
< 0.1%
5620 1
< 0.1%
5619 1
< 0.1%
5618 1
< 0.1%
5617 2
< 0.1%
5616 1
< 0.1%
5613 1
< 0.1%
Distinct4156
Distinct (%)41.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T11:22:24.683062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length3.7555
Min length1

Characters and Unicode

Total characters37555
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

Unique2119 ?
Unique (%)21.2%

Sample

1st row3953
2nd row2086
3rd row3726
4th row3367
5th row358
ValueCountFrequency (%)
3445 292
 
2.9%
72 152
 
1.5%
3465 133
 
1.3%
3906 64
 
0.6%
5163 45
 
0.4%
5087 34
 
0.3%
3468 31
 
0.3%
3726 29
 
0.3%
1405 25
 
0.2%
1895 24
 
0.2%
Other values (4146) 9171
91.7%
2023-12-12T11:22:25.290429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 5419
14.4%
2 4842
12.9%
4 4788
12.7%
1 4787
12.7%
5 3720
9.9%
7 3103
8.3%
6 3008
8.0%
8 2641
7.0%
0 2586
6.9%
9 2583
6.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 37477
99.8%
Dash Punctuation 78
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 5419
14.5%
2 4842
12.9%
4 4788
12.8%
1 4787
12.8%
5 3720
9.9%
7 3103
8.3%
6 3008
8.0%
8 2641
7.0%
0 2586
6.9%
9 2583
6.9%
Dash Punctuation
ValueCountFrequency (%)
- 78
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 37555
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 5419
14.4%
2 4842
12.9%
4 4788
12.7%
1 4787
12.7%
5 3720
9.9%
7 3103
8.3%
6 3008
8.0%
8 2641
7.0%
0 2586
6.9%
9 2583
6.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 37555
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 5419
14.4%
2 4842
12.9%
4 4788
12.7%
1 4787
12.7%
5 3720
9.9%
7 3103
8.3%
6 3008
8.0%
8 2641
7.0%
0 2586
6.9%
9 2583
6.9%
Distinct1370
Distinct (%)13.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2003-03-14 00:00:00
Maximum2020-09-09 00:00:00
2023-12-12T11:22:25.472345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:22:25.622325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

소유자순번
Real number (ℝ)

Distinct4207
Distinct (%)42.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2704.612
Minimum2
Maximum5925
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T11:22:25.774513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile166
Q11377.5
median2805.5
Q33928
95-th percentile5465.05
Maximum5925
Range5923
Interquartile range (IQR)2550.5

Descriptive statistics

Standard deviation1613.1171
Coefficient of variation (CV)0.59643199
Kurtosis-1.0345103
Mean2704.612
Median Absolute Deviation (MAD)1257.5
Skewness-0.0022918159
Sum27046120
Variance2602146.8
MonotonicityNot monotonic
2023-12-12T11:22:25.930446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3733 154
 
1.5%
72 152
 
1.5%
3732 138
 
1.4%
3767 133
 
1.3%
5620 34
 
0.3%
1405 25
 
0.2%
1895 24
 
0.2%
5698 24
 
0.2%
673 23
 
0.2%
5696 21
 
0.2%
Other values (4197) 9272
92.7%
ValueCountFrequency (%)
2 1
 
< 0.1%
3 4
< 0.1%
4 1
 
< 0.1%
5 3
< 0.1%
6 2
< 0.1%
7 1
 
< 0.1%
8 2
< 0.1%
9 2
< 0.1%
10 3
< 0.1%
11 4
< 0.1%
ValueCountFrequency (%)
5925 1
< 0.1%
5924 1
< 0.1%
5923 1
< 0.1%
5922 1
< 0.1%
5921 1
< 0.1%
5920 1
< 0.1%
5919 1
< 0.1%
5918 2
< 0.1%
5917 1
< 0.1%
5914 1
< 0.1%

신청자순번
Real number (ℝ)

Distinct4195
Distinct (%)41.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2683.72
Minimum2
Maximum5878
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T11:22:26.113892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile152.95
Q11352.5
median2787.5
Q33905
95-th percentile5418.05
Maximum5878
Range5876
Interquartile range (IQR)2552.5

Descriptive statistics

Standard deviation1601.8804
Coefficient of variation (CV)0.59688803
Kurtosis-1.0395368
Mean2683.72
Median Absolute Deviation (MAD)1245.5
Skewness-0.0083335375
Sum26837200
Variance2566020.7
MonotonicityNot monotonic
2023-12-12T11:22:26.267611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
72 152
 
1.5%
3714 148
 
1.5%
3715 144
 
1.4%
3746 133
 
1.3%
5573 34
 
0.3%
5651 25
 
0.2%
1405 25
 
0.2%
1895 24
 
0.2%
673 23
 
0.2%
1875 21
 
0.2%
Other values (4185) 9271
92.7%
ValueCountFrequency (%)
2 1
 
< 0.1%
3 4
< 0.1%
4 1
 
< 0.1%
5 3
< 0.1%
6 2
< 0.1%
7 1
 
< 0.1%
8 2
< 0.1%
9 2
< 0.1%
10 3
< 0.1%
11 4
< 0.1%
ValueCountFrequency (%)
5878 1
< 0.1%
5877 1
< 0.1%
5876 1
< 0.1%
5875 1
< 0.1%
5874 1
< 0.1%
5873 1
< 0.1%
5872 1
< 0.1%
5871 2
< 0.1%
5870 1
< 0.1%
5867 1
< 0.1%

접수필지순번
Real number (ℝ)

Distinct7264
Distinct (%)72.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6048.424
Minimum2
Maximum12813
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T11:22:26.485405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile431.9
Q12864.75
median6447.5
Q38826.25
95-th percentile11944.05
Maximum12813
Range12811
Interquartile range (IQR)5961.5

Descriptive statistics

Standard deviation3570.727
Coefficient of variation (CV)0.5903566
Kurtosis-1.1090452
Mean6048.424
Median Absolute Deviation (MAD)2854.5
Skewness-0.062425264
Sum60484240
Variance12750092
MonotonicityNot monotonic
2023-12-12T11:22:26.679721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8479 21
 
0.2%
8478 20
 
0.2%
9337 20
 
0.2%
9338 19
 
0.2%
8477 17
 
0.2%
8440 17
 
0.2%
8475 17
 
0.2%
8428 17
 
0.2%
8476 16
 
0.2%
8480 16
 
0.2%
Other values (7254) 9820
98.2%
ValueCountFrequency (%)
2 1
< 0.1%
3 1
< 0.1%
4 2
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 2
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
11 1
< 0.1%
14 1
< 0.1%
ValueCountFrequency (%)
12813 1
< 0.1%
12810 1
< 0.1%
12809 1
< 0.1%
12808 1
< 0.1%
12805 1
< 0.1%
12802 1
< 0.1%
12801 1
< 0.1%
12800 1
< 0.1%
12799 1
< 0.1%
12798 1
< 0.1%
Distinct6863
Distinct (%)68.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T11:22:27.058299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length26
Mean length20.8911
Min length7

Characters and Unicode

Total characters208911
Distinct characters187
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4772 ?
Unique (%)47.7%

Sample

1st row대전광역시 동구 세천동 13
2nd row전라북도 진안군 진안읍 물곡리 555-1
3rd row충청북도 영동군 심천면 고당리 190
4th row충청북도 영동군 심천면 심천리 628-1
5th row충청북도 옥천군 군북면 대정리 664-5
ValueCountFrequency (%)
충청북도 4967
 
10.1%
전라북도 3072
 
6.2%
옥천군 2709
 
5.5%
진안군 2110
 
4.3%
영동군 1109
 
2.2%
대전광역시 1095
 
2.2%
충청남도 865
 
1.8%
금산군 865
 
1.8%
동구 859
 
1.7%
심천면 741
 
1.5%
Other values (4485) 30977
62.7%
2023-12-12T11:22:27.675883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
39369
 
18.8%
9225
 
4.4%
9109
 
4.4%
9021
 
4.3%
8515
 
4.1%
7920
 
3.8%
1 6522
 
3.1%
6479
 
3.1%
5832
 
2.8%
- 5733
 
2.7%
Other values (177) 101186
48.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 128890
61.7%
Space Separator 39369
 
18.8%
Decimal Number 34912
 
16.7%
Dash Punctuation 5733
 
2.7%
Uppercase Letter 5
 
< 0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
9225
 
7.2%
9109
 
7.1%
9021
 
7.0%
8515
 
6.6%
7920
 
6.1%
6479
 
5.0%
5832
 
4.5%
5528
 
4.3%
4995
 
3.9%
4122
 
3.2%
Other values (158) 58144
45.1%
Decimal Number
ValueCountFrequency (%)
1 6522
18.7%
2 5046
14.5%
3 4158
11.9%
4 3350
9.6%
5 3223
9.2%
6 2952
8.5%
9 2700
7.7%
7 2462
 
7.1%
8 2398
 
6.9%
0 2101
 
6.0%
Uppercase Letter
ValueCountFrequency (%)
U 1
20.0%
E 1
20.0%
L 1
20.0%
V 1
20.0%
A 1
20.0%
Other Punctuation
ValueCountFrequency (%)
! 1
50.0%
# 1
50.0%
Space Separator
ValueCountFrequency (%)
39369
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5733
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 128890
61.7%
Common 80016
38.3%
Latin 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
9225
 
7.2%
9109
 
7.1%
9021
 
7.0%
8515
 
6.6%
7920
 
6.1%
6479
 
5.0%
5832
 
4.5%
5528
 
4.3%
4995
 
3.9%
4122
 
3.2%
Other values (158) 58144
45.1%
Common
ValueCountFrequency (%)
39369
49.2%
1 6522
 
8.2%
- 5733
 
7.2%
2 5046
 
6.3%
3 4158
 
5.2%
4 3350
 
4.2%
5 3223
 
4.0%
6 2952
 
3.7%
9 2700
 
3.4%
7 2462
 
3.1%
Other values (4) 4501
 
5.6%
Latin
ValueCountFrequency (%)
U 1
20.0%
E 1
20.0%
L 1
20.0%
V 1
20.0%
A 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 128890
61.7%
ASCII 80021
38.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
39369
49.2%
1 6522
 
8.2%
- 5733
 
7.2%
2 5046
 
6.3%
3 4158
 
5.2%
4 3350
 
4.2%
5 3223
 
4.0%
6 2952
 
3.7%
9 2700
 
3.4%
7 2462
 
3.1%
Other values (9) 4506
 
5.6%
Hangul
ValueCountFrequency (%)
9225
 
7.2%
9109
 
7.1%
9021
 
7.0%
8515
 
6.6%
7920
 
6.1%
6479
 
5.0%
5832
 
4.5%
5528
 
4.3%
4995
 
3.9%
4122
 
3.2%
Other values (158) 58144
45.1%

지역구분
Categorical

IMBALANCE 

Distinct40
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
수변구역
5445 
상수원보호구역
1652 
기타지역
904 
자연마을
761 
특별대책지역
603 
Other values (35)
635 

Length

Max length11
Median length4
Mean length4.7032
Min length1

Unique

Unique11 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
수변구역 5445
54.4%
상수원보호구역 1652
 
16.5%
기타지역 904
 
9.0%
자연마을 761
 
7.6%
특별대책지역 603
 
6.0%
특대2권역 293
 
2.9%
특대1권역 142
 
1.4%
특별대책지역Ⅰ 37
 
0.4%
특별대책지역2 20
 
0.2%
제외지역 20
 
0.2%
Other values (30) 123
 
1.2%

Length

2023-12-12T11:22:27.861817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수변구역 5445
54.4%
상수원보호구역 1652
 
16.5%
기타지역 906
 
9.1%
자연마을 766
 
7.7%
특별대책지역 603
 
6.0%
특대2권역 293
 
2.9%
특대1권역 142
 
1.4%
특별대책지역ⅰ 37
 
0.4%
특별대책지역2 20
 
0.2%
제외지역 20
 
0.2%
Other values (27) 116
 
1.2%

지목
Categorical

IMBALANCE 

Distinct47
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3290 
3104 
대지
1210 
임야
1062 
과수원
 
263
Other values (42)
1071 

Length

Max length7
Median length1
Mean length1.4351
Min length1

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
3290
32.9%
3104
31.0%
대지 1210
 
12.1%
임야 1062
 
10.6%
과수원 263
 
2.6%
도로 162
 
1.6%
146
 
1.5%
목장 142
 
1.4%
잡종지 125
 
1.2%
목장용지 115
 
1.1%
Other values (37) 381
 
3.8%

Length

2023-12-12T11:22:28.052795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
3293
32.9%
3104
31.0%
대지 1210
 
12.1%
임야 1062
 
10.6%
과수원 263
 
2.6%
도로 162
 
1.6%
146
 
1.5%
목장 142
 
1.4%
잡종지 125
 
1.2%
목장용지 115
 
1.1%
Other values (34) 378
 
3.8%

면적
Real number (ℝ)

Distinct2931
Distinct (%)29.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4175.435
Minimum0
Maximum462227
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T11:22:28.208937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile99
Q1421.75
median949
Q31931
95-th percentile13755.55
Maximum462227
Range462227
Interquartile range (IQR)1509.25

Descriptive statistics

Standard deviation18076.781
Coefficient of variation (CV)4.3293169
Kurtosis166.19744
Mean4175.435
Median Absolute Deviation (MAD)635.5
Skewness11.014355
Sum41754350
Variance3.2677003 × 108
MonotonicityNot monotonic
2023-12-12T11:22:28.365948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
513.0 44
 
0.4%
843.0 41
 
0.4%
2003.0 38
 
0.4%
1915.0 37
 
0.4%
99.0 33
 
0.3%
660.0 33
 
0.3%
245.0 27
 
0.3%
212.0 26
 
0.3%
347.0 26
 
0.3%
330.0 26
 
0.3%
Other values (2921) 9669
96.7%
ValueCountFrequency (%)
0.0 1
 
< 0.1%
1.0 7
0.1%
2.0 9
0.1%
4.0 7
0.1%
5.0 6
0.1%
6.0 5
0.1%
7.0 2
 
< 0.1%
8.0 4
< 0.1%
9.0 5
0.1%
10.0 2
 
< 0.1%
ValueCountFrequency (%)
462227.0 1
< 0.1%
407209.0 1
< 0.1%
355438.0 1
< 0.1%
337190.0 1
< 0.1%
303174.0 1
< 0.1%
290578.0 2
< 0.1%
274314.0 1
< 0.1%
260430.0 2
< 0.1%
251008.0 2
< 0.1%
237604.0 1
< 0.1%

용도
Text

Distinct65
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T11:22:28.577237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length2.9036
Min length2

Characters and Unicode

Total characters29036
Distinct characters88
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)0.2%

Sample

1st row농경지
2nd row축사
3rd row농경지
4th row농경지
5th row농경지
ValueCountFrequency (%)
농경지 6306
63.1%
임야 980
 
9.8%
나대지 618
 
6.2%
주택 614
 
6.1%
축사 360
 
3.6%
음식점 289
 
2.9%
과수원 239
 
2.4%
공장 151
 
1.5%
숙박시설 103
 
1.0%
기타건물 59
 
0.6%
Other values (42) 282
 
2.8%
2023-12-12T11:22:28.944122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6949
23.9%
6310
21.7%
6306
21.7%
1053
 
3.6%
980
 
3.4%
980
 
3.4%
674
 
2.3%
649
 
2.2%
631
 
2.2%
620
 
2.1%
Other values (78) 3884
13.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 27977
96.4%
Space Separator 1053
 
3.6%
Open Punctuation 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%
Decimal Number 1
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6949
24.8%
6310
22.6%
6306
22.5%
980
 
3.5%
980
 
3.5%
674
 
2.4%
649
 
2.3%
631
 
2.3%
620
 
2.2%
387
 
1.4%
Other values (73) 3491
12.5%
Space Separator
ValueCountFrequency (%)
1053
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 27977
96.4%
Common 1059
 
3.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6949
24.8%
6310
22.6%
6306
22.5%
980
 
3.5%
980
 
3.5%
674
 
2.4%
649
 
2.3%
631
 
2.3%
620
 
2.2%
387
 
1.4%
Other values (73) 3491
12.5%
Common
ValueCountFrequency (%)
1053
99.4%
( 2
 
0.2%
) 2
 
0.2%
2 1
 
0.1%
, 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 27977
96.4%
ASCII 1059
 
3.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
6949
24.8%
6310
22.6%
6306
22.5%
980
 
3.5%
980
 
3.5%
674
 
2.4%
649
 
2.3%
631
 
2.3%
620
 
2.2%
387
 
1.4%
Other values (73) 3491
12.5%
ASCII
ValueCountFrequency (%)
1053
99.4%
( 2
 
0.2%
) 2
 
0.2%
2 1
 
0.1%
, 1
 
0.1%

공시지가
Text

MISSING 

Distinct2097
Distinct (%)21.3%
Missing155
Missing (%)1.6%
Memory size156.2 KiB
2023-12-12T11:22:29.432895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length9
Mean length4.4222448
Min length1

Characters and Unicode

Total characters43537
Distinct characters22
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique595 ?
Unique (%)6.0%

Sample

1st row 64,100
2nd row 11,500
3rd row10300
4th row8100
5th row6390
ValueCountFrequency (%)
10600 92
 
0.9%
11500 79
 
0.8%
12000 76
 
0.8%
63800 73
 
0.7%
17500 64
 
0.7%
33000 57
 
0.6%
57
 
0.6%
11000 49
 
0.5%
8070 46
 
0.5%
14800 46
 
0.5%
Other values (2055) 9207
93.5%
2023-12-12T11:22:30.079826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 16055
36.9%
1 4705
 
10.8%
2 3083
 
7.1%
4 2898
 
6.7%
5 2841
 
6.5%
3 2776
 
6.4%
6 2639
 
6.1%
7 2457
 
5.6%
8 2400
 
5.5%
9 2153
 
4.9%
Other values (12) 1530
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 42007
96.5%
Space Separator 983
 
2.3%
Other Punctuation 481
 
1.1%
Dash Punctuation 57
 
0.1%
Other Letter 9
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 16055
38.2%
1 4705
 
11.2%
2 3083
 
7.3%
4 2898
 
6.9%
5 2841
 
6.8%
3 2776
 
6.6%
6 2639
 
6.3%
7 2457
 
5.8%
8 2400
 
5.7%
9 2153
 
5.1%
Other Letter
ValueCountFrequency (%)
2
22.2%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
Other Punctuation
ValueCountFrequency (%)
, 479
99.6%
. 2
 
0.4%
Space Separator
ValueCountFrequency (%)
983
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 57
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 43528
> 99.9%
Hangul 9
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 16055
36.9%
1 4705
 
10.8%
2 3083
 
7.1%
4 2898
 
6.7%
5 2841
 
6.5%
3 2776
 
6.4%
6 2639
 
6.1%
7 2457
 
5.6%
8 2400
 
5.5%
9 2153
 
4.9%
Other values (4) 1521
 
3.5%
Hangul
ValueCountFrequency (%)
2
22.2%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 43528
> 99.9%
Hangul 9
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 16055
36.9%
1 4705
 
10.8%
2 3083
 
7.1%
4 2898
 
6.7%
5 2841
 
6.5%
3 2776
 
6.4%
6 2639
 
6.1%
7 2457
 
5.6%
8 2400
 
5.5%
9 2153
 
4.9%
Other values (4) 1521
 
3.5%
Hangul
ValueCountFrequency (%)
2
22.2%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%

매수시작순번
Real number (ℝ)

MISSING 

Distinct7168
Distinct (%)72.6%
Missing125
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean6079.808
Minimum2
Maximum12801
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T11:22:30.284395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile452.7
Q12915.5
median6492
Q38841
95-th percentile11944.6
Maximum12801
Range12799
Interquartile range (IQR)5925.5

Descriptive statistics

Standard deviation3561.4855
Coefficient of variation (CV)0.58578914
Kurtosis-1.1031234
Mean6079.808
Median Absolute Deviation (MAD)2829
Skewness-0.07363352
Sum60038104
Variance12684179
MonotonicityNot monotonic
2023-12-12T11:22:30.451110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8464 22
 
0.2%
9323 20
 
0.2%
8465 20
 
0.2%
9324 19
 
0.2%
8466 18
 
0.2%
8463 18
 
0.2%
8413 17
 
0.2%
8425 17
 
0.2%
8460 16
 
0.2%
8409 15
 
0.1%
Other values (7158) 9693
96.9%
(Missing) 125
 
1.2%
ValueCountFrequency (%)
2 1
< 0.1%
3 1
< 0.1%
4 2
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 2
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
11 1
< 0.1%
14 1
< 0.1%
ValueCountFrequency (%)
12801 1
< 0.1%
12798 1
< 0.1%
12797 1
< 0.1%
12796 1
< 0.1%
12793 1
< 0.1%
12790 1
< 0.1%
12789 1
< 0.1%
12788 1
< 0.1%
12787 1
< 0.1%
12786 1
< 0.1%

매수시작접수일
Date

MISSING 

Distinct1362
Distinct (%)13.8%
Missing125
Missing (%)1.2%
Memory size156.2 KiB
Minimum2003-03-14 00:00:00
Maximum2020-09-09 00:00:00
2023-12-12T11:22:30.841212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:22:31.000461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

거리
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1401
Missing (%)14.0%
Memory size156.2 KiB

거리순번
Real number (ℝ)

MISSING 

Distinct6852
Distinct (%)72.5%
Missing544
Missing (%)5.4%
Infinite0
Infinite (%)0.0%
Mean5664.3245
Minimum2
Maximum12086
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T11:22:31.163317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile405
Q12657.75
median6039.5
Q38209.5
95-th percentile11275.75
Maximum12086
Range12084
Interquartile range (IQR)5551.75

Descriptive statistics

Standard deviation3355.0767
Coefficient of variation (CV)0.59231717
Kurtosis-1.0868087
Mean5664.3245
Median Absolute Deviation (MAD)2614
Skewness-0.045757353
Sum53561852
Variance11256539
MonotonicityNot monotonic
2023-12-12T11:22:31.364018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7755 21
 
0.2%
8613 20
 
0.2%
8614 19
 
0.2%
7750 18
 
0.2%
7752 18
 
0.2%
7716 17
 
0.2%
7704 17
 
0.2%
7751 17
 
0.2%
7753 15
 
0.1%
7757 15
 
0.1%
Other values (6842) 9279
92.8%
(Missing) 544
 
5.4%
ValueCountFrequency (%)
2 1
< 0.1%
3 1
< 0.1%
4 2
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 2
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
11 1
< 0.1%
14 1
< 0.1%
ValueCountFrequency (%)
12086 1
< 0.1%
12083 1
< 0.1%
12082 1
< 0.1%
12081 1
< 0.1%
12078 1
< 0.1%
12075 1
< 0.1%
12074 1
< 0.1%
12073 1
< 0.1%
12072 1
< 0.1%
12071 1
< 0.1%

일자
Date

MISSING 

Distinct850
Distinct (%)9.0%
Missing544
Missing (%)5.4%
Memory size156.2 KiB
Minimum2000-06-03 00:00:00
Maximum2020-09-18 00:00:00
2023-12-12T11:22:31.528838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:22:31.699175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

현지조사순번
Real number (ℝ)

MISSING 

Distinct1943
Distinct (%)28.7%
Missing3221
Missing (%)32.2%
Infinite0
Infinite (%)0.0%
Mean1547.5128
Minimum1
Maximum2767
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T11:22:31.848795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile125
Q11127
median1515
Q32151
95-th percentile2613
Maximum2767
Range2766
Interquartile range (IQR)1024

Descriptive statistics

Standard deviation726.68132
Coefficient of variation (CV)0.46958018
Kurtosis-0.59612433
Mean1547.5128
Median Absolute Deviation (MAD)512
Skewness-0.39950716
Sum10490589
Variance528065.75
MonotonicityNot monotonic
2023-12-12T11:22:31.979676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2027 292
 
2.9%
1180 158
 
1.6%
2324 133
 
1.3%
2393 64
 
0.6%
2160 31
 
0.3%
2282 29
 
0.3%
1460 26
 
0.3%
1183 22
 
0.2%
1275 20
 
0.2%
1484 20
 
0.2%
Other values (1933) 5984
59.8%
(Missing) 3221
32.2%
ValueCountFrequency (%)
1 1
 
< 0.1%
2 4
 
< 0.1%
3 1
 
< 0.1%
4 13
0.1%
5 13
0.1%
6 13
0.1%
9 1
 
< 0.1%
10 1
 
< 0.1%
11 2
 
< 0.1%
13 5
 
0.1%
ValueCountFrequency (%)
2767 3
< 0.1%
2766 1
 
< 0.1%
2765 2
 
< 0.1%
2764 7
0.1%
2763 1
 
< 0.1%
2762 1
 
< 0.1%
2761 2
 
< 0.1%
2760 1
 
< 0.1%
2759 2
 
< 0.1%
2758 3
< 0.1%

출장목적
Text

MISSING 

Distinct71
Distinct (%)3.0%
Missing7668
Missing (%)76.7%
Memory size156.2 KiB
2023-12-12T11:22:32.348274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length73
Median length67
Mean length15.187393
Min length1

Characters and Unicode

Total characters35417
Distinct characters203
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)0.6%

Sample

1st row토지등의 매도신청지(3건 : 전운천, 김유태, 김영찬) 현지확인
2nd row토지등 매도신청지(9건) 현지확인
3rd row현지조사
4th row토지등의 매도신청지 현지확인
5th row토지등의 매도신청지 현지확인
ValueCountFrequency (%)
매도신청지 1465
20.9%
현지확인 1453
20.7%
토지등 839
11.9%
현지조사 626
8.9%
토지등의 623
8.9%
189
 
2.7%
매도신청지(3건 106
 
1.5%
매도신청지(2건 76
 
1.1%
71
 
1.0%
매도신청지(4건 48
 
0.7%
Other values (210) 1525
21.7%
2023-12-12T11:22:32.943441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5668
16.0%
4689
13.2%
2210
 
6.2%
1938
 
5.5%
1933
 
5.5%
1921
 
5.4%
1907
 
5.4%
1567
 
4.4%
1552
 
4.4%
1532
 
4.3%
Other values (193) 10500
29.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 28306
79.9%
Space Separator 4689
 
13.2%
Other Punctuation 1056
 
3.0%
Open Punctuation 450
 
1.3%
Close Punctuation 450
 
1.3%
Decimal Number 449
 
1.3%
Connector Punctuation 12
 
< 0.1%
Modifier Symbol 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5668
20.0%
2210
 
7.8%
1938
 
6.8%
1933
 
6.8%
1921
 
6.8%
1907
 
6.7%
1567
 
5.5%
1552
 
5.5%
1532
 
5.4%
1511
 
5.3%
Other values (175) 6567
23.2%
Decimal Number
ValueCountFrequency (%)
3 107
23.8%
2 79
17.6%
4 48
10.7%
5 48
10.7%
1 47
10.5%
9 39
 
8.7%
6 31
 
6.9%
0 26
 
5.8%
7 20
 
4.5%
8 4
 
0.9%
Other Punctuation
ValueCountFrequency (%)
, 837
79.3%
: 189
 
17.9%
· 30
 
2.8%
Space Separator
ValueCountFrequency (%)
4689
100.0%
Open Punctuation
ValueCountFrequency (%)
( 450
100.0%
Close Punctuation
ValueCountFrequency (%)
) 450
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 12
100.0%
Modifier Symbol
ValueCountFrequency (%)
˙ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 28306
79.9%
Common 7111
 
20.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5668
20.0%
2210
 
7.8%
1938
 
6.8%
1933
 
6.8%
1921
 
6.8%
1907
 
6.7%
1567
 
5.5%
1552
 
5.5%
1532
 
5.4%
1511
 
5.3%
Other values (175) 6567
23.2%
Common
ValueCountFrequency (%)
4689
65.9%
, 837
 
11.8%
( 450
 
6.3%
) 450
 
6.3%
: 189
 
2.7%
3 107
 
1.5%
2 79
 
1.1%
4 48
 
0.7%
5 48
 
0.7%
1 47
 
0.7%
Other values (8) 167
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 28305
79.9%
ASCII 7076
 
20.0%
None 30
 
0.1%
Modifier Letters 5
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
5668
20.0%
2210
 
7.8%
1938
 
6.8%
1933
 
6.8%
1921
 
6.8%
1907
 
6.7%
1567
 
5.5%
1552
 
5.5%
1532
 
5.4%
1511
 
5.3%
Other values (174) 6566
23.2%
ASCII
ValueCountFrequency (%)
4689
66.3%
, 837
 
11.8%
( 450
 
6.4%
) 450
 
6.4%
: 189
 
2.7%
3 107
 
1.5%
2 79
 
1.1%
4 48
 
0.7%
5 48
 
0.7%
1 47
 
0.7%
Other values (6) 132
 
1.9%
None
ValueCountFrequency (%)
· 30
100.0%
Modifier Letters
ValueCountFrequency (%)
˙ 5
100.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

출장시작일
Date

MISSING 

Distinct358
Distinct (%)5.3%
Missing3221
Missing (%)32.2%
Memory size156.2 KiB
Minimum2003-05-01 00:00:00
Maximum2018-01-01 00:00:00
2023-12-12T11:22:33.119435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:22:33.260852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

출장종료일
Date

MISSING 

Distinct248
Distinct (%)3.7%
Missing3222
Missing (%)32.2%
Memory size156.2 KiB
Minimum2003-05-02 00:00:00
Maximum2018-01-01 00:00:00
2023-12-12T11:22:33.411945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:22:33.579479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

출장장소
Text

MISSING 

Distinct146
Distinct (%)6.3%
Missing7698
Missing (%)77.0%
Memory size156.2 KiB
2023-12-12T11:22:33.882415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length21
Mean length7.0030408
Min length1

Characters and Unicode

Total characters16121
Distinct characters98
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)1.1%

Sample

1st row옥천군
2nd row무주, 진안
3rd row충남 금산군 제원면 용화리
4th row충청북도 보은군
5th row진안
ValueCountFrequency (%)
충북 489
 
10.0%
금산군 368
 
7.5%
충남 349
 
7.1%
제원면 325
 
6.6%
용화리 323
 
6.6%
진안 292
 
6.0%
전북 259
 
5.3%
충청북도 258
 
5.3%
옥천 258
 
5.3%
보은군 256
 
5.2%
Other values (101) 1728
35.2%
2023-12-12T11:22:34.330417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2731
 
16.9%
1221
 
7.6%
1108
 
6.9%
1088
 
6.7%
534
 
3.3%
526
 
3.3%
519
 
3.2%
516
 
3.2%
488
 
3.0%
465
 
2.9%
Other values (88) 6925
43.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12886
79.9%
Space Separator 2731
 
16.9%
Other Punctuation 308
 
1.9%
Decimal Number 161
 
1.0%
Dash Punctuation 23
 
0.1%
Modifier Symbol 10
 
0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1221
 
9.5%
1108
 
8.6%
1088
 
8.4%
534
 
4.1%
526
 
4.1%
519
 
4.0%
516
 
4.0%
488
 
3.8%
465
 
3.6%
439
 
3.4%
Other values (74) 5982
46.4%
Decimal Number
ValueCountFrequency (%)
1 48
29.8%
2 28
17.4%
6 25
15.5%
0 22
13.7%
8 21
13.0%
5 14
 
8.7%
4 2
 
1.2%
9 1
 
0.6%
Space Separator
ValueCountFrequency (%)
2731
100.0%
Other Punctuation
ValueCountFrequency (%)
, 308
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%
Modifier Symbol
ValueCountFrequency (%)
˙ 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12886
79.9%
Common 3235
 
20.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1221
 
9.5%
1108
 
8.6%
1088
 
8.4%
534
 
4.1%
526
 
4.1%
519
 
4.0%
516
 
4.0%
488
 
3.8%
465
 
3.6%
439
 
3.4%
Other values (74) 5982
46.4%
Common
ValueCountFrequency (%)
2731
84.4%
, 308
 
9.5%
1 48
 
1.5%
2 28
 
0.9%
6 25
 
0.8%
- 23
 
0.7%
0 22
 
0.7%
8 21
 
0.6%
5 14
 
0.4%
˙ 10
 
0.3%
Other values (4) 5
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12885
79.9%
ASCII 3225
 
20.0%
Modifier Letters 10
 
0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2731
84.7%
, 308
 
9.6%
1 48
 
1.5%
2 28
 
0.9%
6 25
 
0.8%
- 23
 
0.7%
0 22
 
0.7%
8 21
 
0.7%
5 14
 
0.4%
4 2
 
0.1%
Other values (3) 3
 
0.1%
Hangul
ValueCountFrequency (%)
1221
 
9.5%
1108
 
8.6%
1088
 
8.4%
534
 
4.1%
526
 
4.1%
519
 
4.0%
516
 
4.0%
488
 
3.8%
465
 
3.6%
439
 
3.4%
Other values (73) 5981
46.4%
Modifier Letters
ValueCountFrequency (%)
˙ 10
100.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

순번
Real number (ℝ)

MISSING 

Distinct811
Distinct (%)92.6%
Missing9124
Missing (%)91.2%
Infinite0
Infinite (%)0.0%
Mean1734.7671
Minimum1
Maximum2587
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T11:22:34.523079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile248.75
Q11457.25
median1816.5
Q32207.25
95-th percentile2504.5
Maximum2587
Range2586
Interquartile range (IQR)750

Descriptive statistics

Standard deviation610.31764
Coefficient of variation (CV)0.35181531
Kurtosis0.90393944
Mean1734.7671
Median Absolute Deviation (MAD)374.5
Skewness-1.0405702
Sum1519656
Variance372487.62
MonotonicityNot monotonic
2023-12-12T11:22:34.725824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1616 5
 
0.1%
1613 5
 
0.1%
1611 4
 
< 0.1%
1618 4
 
< 0.1%
1620 4
 
< 0.1%
1621 4
 
< 0.1%
1622 4
 
< 0.1%
1612 4
 
< 0.1%
1615 4
 
< 0.1%
1617 4
 
< 0.1%
Other values (801) 834
 
8.3%
(Missing) 9124
91.2%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
11 1
< 0.1%
12 1
< 0.1%
14 1
< 0.1%
17 1
< 0.1%
ValueCountFrequency (%)
2587 1
< 0.1%
2585 1
< 0.1%
2583 1
< 0.1%
2582 1
< 0.1%
2581 1
< 0.1%
2573 1
< 0.1%
2572 2
< 0.1%
2571 1
< 0.1%
2570 2
< 0.1%
2567 1
< 0.1%

폐수배출시설공장
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9991 
40
 
7
3
 
2

Length

Max length4
Median length4
Mean length3.998
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> 9991
99.9%
40 7
 
0.1%
3 2
 
< 0.1%

Length

2023-12-12T11:22:34.874610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:22:35.001076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9991
99.9%
40 7
 
0.1%
3 2
 
< 0.1%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9995 
8
 
4
30
 
1

Length

Max length4
Median length4
Mean length3.9986
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> 9995
> 99.9%
8 4
 
< 0.1%
30 1
 
< 0.1%

Length

2023-12-12T11:22:35.107137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:22:35.225929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9995
> 99.9%
8 4
 
< 0.1%
30 1
 
< 0.1%

돈사허가규모이상
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9999 
37
 
1

Length

Max length4
Median length4
Mean length3.9998
Min length2

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> 9999
> 99.9%
37 1
 
< 0.1%

Length

2023-12-12T11:22:35.366090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:22:35.506469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9999
> 99.9%
37 1
 
< 0.1%

돈사신고규모이상
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9999 
10
 
1

Length

Max length4
Median length4
Mean length3.9998
Min length2

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> 9999
> 99.9%
10 1
 
< 0.1%

Length

2023-12-12T11:22:35.651116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:22:35.785361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9999
> 99.9%
10 1
 
< 0.1%

우사허가규모이상
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9990 
37
 
4
25
 
2
7
 
2
30
 
2

Length

Max length4
Median length4
Mean length3.9978
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> 9990
99.9%
37 4
 
< 0.1%
25 2
 
< 0.1%
7 2
 
< 0.1%
30 2
 
< 0.1%

Length

2023-12-12T11:22:35.910511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:22:36.042584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9990
99.9%
37 4
 
< 0.1%
25 2
 
< 0.1%
7 2
 
< 0.1%
30 2
 
< 0.1%

우사신고규모이상
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9991 
27
 
5
10
 
2
20
 
1
5
 
1

Length

Max length4
Median length4
Mean length3.9981
Min length1

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> 9991
99.9%
27 5
 
0.1%
10 2
 
< 0.1%
20 1
 
< 0.1%
5 1
 
< 0.1%

Length

2023-12-12T11:22:36.193571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:22:36.317509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9991
99.9%
27 5
 
< 0.1%
10 2
 
< 0.1%
20 1
 
< 0.1%
5 1
 
< 0.1%

우사신고규모미만
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9999 
15
 
1

Length

Max length4
Median length4
Mean length3.9998
Min length2

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> 9999
> 99.9%
15 1
 
< 0.1%

Length

2023-12-12T11:22:36.472119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:22:36.598928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9999
> 99.9%
15 1
 
< 0.1%

기타신고규모이상
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9992 
8
 
4
3
 
4

Length

Max length4
Median length4
Mean length3.9976
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> 9992
99.9%
8 4
 
< 0.1%
3 4
 
< 0.1%

Length

2023-12-12T11:22:36.763923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:22:36.897882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9992
99.9%
8 4
 
< 0.1%
3 4
 
< 0.1%

기타신고규모미만
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9999 
5
 
1

Length

Max length4
Median length4
Mean length3.9997
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> 9999
> 99.9%
5 1
 
< 0.1%

Length

2023-12-12T11:22:37.020311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:22:37.120185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9999
> 99.9%
5 1
 
< 0.1%
Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9949 
4
 
33
30
 
8
10
 
5
1
 
3

Length

Max length4
Median length4
Mean length3.9862
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> 9949
99.5%
4 33
 
0.3%
30 8
 
0.1%
10 5
 
0.1%
1 3
 
< 0.1%
20 2
 
< 0.1%

Length

2023-12-12T11:22:37.237561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:22:37.371213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9949
99.5%
4 33
 
0.3%
30 8
 
0.1%
10 5
 
< 0.1%
1 3
 
< 0.1%
20 2
 
< 0.1%

주택등일반건축물
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)35.0%
Missing9980
Missing (%)99.8%
Infinite0
Infinite (%)0.0%
Mean9.225
Minimum0.5
Maximum20
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T11:22:37.498135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.5
5-th percentile0.975
Q12
median10
Q315
95-th percentile20
Maximum20
Range19.5
Interquartile range (IQR)13

Descriptive statistics

Standard deviation7.1753874
Coefficient of variation (CV)0.77781977
Kurtosis-1.3143371
Mean9.225
Median Absolute Deviation (MAD)8
Skewness0.32360878
Sum184.5
Variance51.486184
MonotonicityNot monotonic
2023-12-12T11:22:37.620888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
10.0 6
 
0.1%
2.0 5
 
0.1%
20.0 4
 
< 0.1%
15.0 2
 
< 0.1%
0.5 1
 
< 0.1%
1.0 1
 
< 0.1%
3.0 1
 
< 0.1%
(Missing) 9980
99.8%
ValueCountFrequency (%)
0.5 1
 
< 0.1%
1.0 1
 
< 0.1%
2.0 5
0.1%
3.0 1
 
< 0.1%
10.0 6
0.1%
15.0 2
 
< 0.1%
20.0 4
< 0.1%
ValueCountFrequency (%)
20.0 4
< 0.1%
15.0 2
 
< 0.1%
10.0 6
0.1%
3.0 1
 
< 0.1%
2.0 5
0.1%
1.0 1
 
< 0.1%
0.5 1
 
< 0.1%

나대지전답과수원
Real number (ℝ)

MISSING 

Distinct12
Distinct (%)2.9%
Missing9590
Missing (%)95.9%
Infinite0
Infinite (%)0.0%
Mean5.739878
Minimum0.25
Maximum15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T11:22:37.755702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.25
5-th percentile0.5
Q11.75
median5
Q310
95-th percentile10
Maximum15
Range14.75
Interquartile range (IQR)8.25

Descriptive statistics

Standard deviation3.7894834
Coefficient of variation (CV)0.66020278
Kurtosis-1.1410423
Mean5.739878
Median Absolute Deviation (MAD)4.25
Skewness0.10219525
Sum2353.35
Variance14.360185
MonotonicityNot monotonic
2023-12-12T11:22:37.885988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
10.0 140
 
1.4%
5.0 136
 
1.4%
0.5 48
 
0.5%
1.0 20
 
0.2%
1.5 18
 
0.2%
2.5 17
 
0.2%
0.75 10
 
0.1%
7.5 7
 
0.1%
15.0 6
 
0.1%
0.25 5
 
0.1%
Other values (2) 3
 
< 0.1%
(Missing) 9590
95.9%
ValueCountFrequency (%)
0.25 5
 
0.1%
0.5 48
 
0.5%
0.7 2
 
< 0.1%
0.75 10
 
0.1%
1.0 20
 
0.2%
1.5 18
 
0.2%
2.5 17
 
0.2%
5.0 136
1.4%
7.2 1
 
< 0.1%
7.5 7
 
0.1%
ValueCountFrequency (%)
15.0 6
 
0.1%
10.0 140
1.4%
7.5 7
 
0.1%
7.2 1
 
< 0.1%
5.0 136
1.4%
2.5 17
 
0.2%
1.5 18
 
0.2%
1.0 20
 
0.2%
0.75 10
 
0.1%
0.7 2
 
< 0.1%

임야
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9999 
0.5
 
1

Length

Max length4
Median length4
Mean length3.9999
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> 9999
> 99.9%
0.5 1
 
< 0.1%

Length

2023-12-12T11:22:38.032422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:22:38.134369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9999
> 99.9%
0.5 1
 
< 0.1%

상수원보호구역
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9928 
8
 
40
15
 
20
25
 
10
10
 
2

Length

Max length4
Median length4
Mean length3.9816
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> 9928
99.3%
8 40
 
0.4%
15 20
 
0.2%
25 10
 
0.1%
10 2
 
< 0.1%

Length

2023-12-12T11:22:38.257066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:22:38.375318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9928
99.3%
8 40
 
0.4%
15 20
 
0.2%
25 10
 
0.1%
10 2
 
< 0.1%

수변구역
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9763 
20
 
115
10
 
108
35
 
11
25
 
2

Length

Max length4
Median length4
Mean length3.9525
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> 9763
97.6%
20 115
 
1.1%
10 108
 
1.1%
35 11
 
0.1%
25 2
 
< 0.1%
1 1
 
< 0.1%

Length

2023-12-12T11:22:38.860948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:22:39.002499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9763
97.6%
20 115
 
1.1%
10 108
 
1.1%
35 11
 
0.1%
25 2
 
< 0.1%
1 1
 
< 0.1%

특별대책지역1권역
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9983 
5
 
12
15
 
4
3
 
1

Length

Max length4
Median length4
Mean length3.9953
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> 9983
99.8%
5 12
 
0.1%
15 4
 
< 0.1%
3 1
 
< 0.1%

Length

2023-12-12T11:22:39.136572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:22:39.256526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9983
99.8%
5 12
 
0.1%
15 4
 
< 0.1%
3 1
 
< 0.1%

특별대책지역2권역
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9965 
3
 
32
10
 
3

Length

Max length4
Median length4
Mean length3.9898
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> 9965
99.7%
3 32
 
0.3%
10 3
 
< 0.1%

Length

2023-12-12T11:22:39.366315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:22:39.460719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9965
99.7%
3 32
 
0.3%
10 3
 
< 0.1%

점오염원
Real number (ℝ)

MISSING 

Distinct11
Distinct (%)14.7%
Missing9925
Missing (%)99.2%
Infinite0
Infinite (%)0.0%
Mean7.3973333
Minimum0
Maximum10
Zeros5
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T11:22:39.572632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13.5
median10
Q310
95-th percentile10
Maximum10
Range10
Interquartile range (IQR)6.5

Descriptive statistics

Standard deviation3.8498148
Coefficient of variation (CV)0.52043278
Kurtosis-0.90700272
Mean7.3973333
Median Absolute Deviation (MAD)0
Skewness-0.95463744
Sum554.8
Variance14.821074
MonotonicityNot monotonic
2023-12-12T11:22:39.686231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
10.0 49
 
0.5%
2.0 8
 
0.1%
0.0 5
 
0.1%
1.0 3
 
< 0.1%
5.0 3
 
< 0.1%
8.0 2
 
< 0.1%
3.0 1
 
< 0.1%
1.2 1
 
< 0.1%
0.6 1
 
< 0.1%
6.0 1
 
< 0.1%
(Missing) 9925
99.2%
ValueCountFrequency (%)
0.0 5
0.1%
0.6 1
 
< 0.1%
1.0 3
 
< 0.1%
1.2 1
 
< 0.1%
2.0 8
0.1%
3.0 1
 
< 0.1%
4.0 1
 
< 0.1%
5.0 3
 
< 0.1%
6.0 1
 
< 0.1%
8.0 2
 
< 0.1%
ValueCountFrequency (%)
10.0 49
0.5%
8.0 2
 
< 0.1%
6.0 1
 
< 0.1%
5.0 3
 
< 0.1%
4.0 1
 
< 0.1%
3.0 1
 
< 0.1%
2.0 8
 
0.1%
1.2 1
 
< 0.1%
1.0 3
 
< 0.1%
0.6 1
 
< 0.1%

비점오염원
Real number (ℝ)

MISSING 

Distinct24
Distinct (%)4.0%
Missing9404
Missing (%)94.0%
Infinite0
Infinite (%)0.0%
Mean0.60956376
Minimum0
Maximum3.7
Zeros5
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T11:22:39.817384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.1
Q10.3
median0.5
Q30.9
95-th percentile1.3
Maximum3.7
Range3.7
Interquartile range (IQR)0.6

Descriptive statistics

Standard deviation0.42804124
Coefficient of variation (CV)0.70220914
Kurtosis4.8950613
Mean0.60956376
Median Absolute Deviation (MAD)0.3
Skewness1.4769684
Sum363.3
Variance0.18321931
MonotonicityNot monotonic
2023-12-12T11:22:39.961711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0.4 81
 
0.8%
0.2 66
 
0.7%
0.5 62
 
0.6%
1.1 58
 
0.6%
0.3 58
 
0.6%
0.1 54
 
0.5%
0.7 50
 
0.5%
0.6 39
 
0.4%
0.8 26
 
0.3%
0.9 25
 
0.2%
Other values (14) 77
 
0.8%
(Missing) 9404
94.0%
ValueCountFrequency (%)
0.0 5
 
0.1%
0.1 54
0.5%
0.2 66
0.7%
0.3 58
0.6%
0.4 81
0.8%
0.5 62
0.6%
0.6 39
0.4%
0.7 50
0.5%
0.8 26
 
0.3%
0.9 25
 
0.2%
ValueCountFrequency (%)
3.7 1
 
< 0.1%
2.3 1
 
< 0.1%
2.1 2
 
< 0.1%
2.0 1
 
< 0.1%
1.9 6
0.1%
1.8 1
 
< 0.1%
1.7 1
 
< 0.1%
1.6 3
< 0.1%
1.5 5
0.1%
1.4 5
0.1%

연접토지
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9955 
10
 
38
0
 
5
20
 
2

Length

Max length4
Median length4
Mean length3.9905
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> 9955
99.6%
10 38
 
0.4%
0 5
 
0.1%
20 2
 
< 0.1%

Length

2023-12-12T11:22:40.134457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:22:40.250209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9955
99.6%
10 38
 
0.4%
0 5
 
< 0.1%
20 2
 
< 0.1%

총점
Real number (ℝ)

MISSING 

Distinct181
Distinct (%)20.7%
Missing9124
Missing (%)91.2%
Infinite0
Infinite (%)0.0%
Mean13.650057
Minimum0
Maximum70
Zeros62
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T11:22:40.373378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.5
median5.45
Q321.1
95-th percentile50.325
Maximum70
Range70
Interquartile range (IQR)20.6

Descriptive statistics

Standard deviation16.928516
Coefficient of variation (CV)1.2401792
Kurtosis0.68015449
Mean13.650057
Median Absolute Deviation (MAD)5.35
Skewness1.2400087
Sum11957.45
Variance286.57467
MonotonicityNot monotonic
2023-12-12T11:22:40.524972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.5 76
 
0.8%
0.0 62
 
0.6%
21.1 47
 
0.5%
0.4 44
 
0.4%
29.0 31
 
0.3%
0.2 30
 
0.3%
1.0 30
 
0.3%
0.3 28
 
0.3%
0.7 22
 
0.2%
0.1 22
 
0.2%
Other values (171) 484
 
4.8%
(Missing) 9124
91.2%
ValueCountFrequency (%)
0.0 62
0.6%
0.1 22
 
0.2%
0.2 30
 
0.3%
0.25 5
 
0.1%
0.3 28
 
0.3%
0.4 44
0.4%
0.5 76
0.8%
0.6 20
 
0.2%
0.7 22
 
0.2%
0.75 10
 
0.1%
ValueCountFrequency (%)
70.0 4
< 0.1%
68.0 3
< 0.1%
67.0 2
< 0.1%
66.0 1
 
< 0.1%
65.7 1
 
< 0.1%
65.0 2
< 0.1%
62.0 1
 
< 0.1%
60.7 1
 
< 0.1%
59.4 1
 
< 0.1%
55.5 3
< 0.1%

경사도
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9994 
5
 
6

Length

Max length4
Median length4
Mean length3.9982
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> 9994
99.9%
5 6
 
0.1%

Length

2023-12-12T11:22:40.683767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:22:40.801394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9994
99.9%
5 6
 
0.1%

하천경계로부터의거리
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9144 
501m~1000m
 
293
51m~250m
 
236
251m~500m
 
183
0m~50m
 
91

Length

Max length11
Median length4
Mean length4.417
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> 9144
91.4%
501m~1000m 293
 
2.9%
51m~250m 236
 
2.4%
251m~500m 183
 
1.8%
0m~50m 91
 
0.9%
1001m~1500m 53
 
0.5%

Length

2023-12-12T11:22:40.901393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:22:41.014155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9144
91.4%
501m~1000m 293
 
2.9%
51m~250m 236
 
2.4%
251m~500m 183
 
1.8%
0m~50m 91
 
0.9%
1001m~1500m 53
 
0.5%

거리_1
Real number (ℝ)

MISSING 

Distinct205
Distinct (%)23.4%
Missing9124
Missing (%)91.2%
Infinite0
Infinite (%)0.0%
Mean466.30479
Minimum0
Maximum2000
Zeros45
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T11:22:41.141160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1120
median409
Q3700
95-th percentile1165
Maximum2000
Range2000
Interquartile range (IQR)580

Descriptive statistics

Standard deviation399.10661
Coefficient of variation (CV)0.85589214
Kurtosis1.4375161
Mean466.30479
Median Absolute Deviation (MAD)291
Skewness1.1351211
Sum408483
Variance159286.09
MonotonicityNot monotonic
2023-12-12T11:22:41.283561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 45
 
0.4%
409 45
 
0.4%
800 20
 
0.2%
600 19
 
0.2%
60 18
 
0.2%
520 18
 
0.2%
700 17
 
0.2%
510 15
 
0.1%
170 13
 
0.1%
610 12
 
0.1%
Other values (195) 654
 
6.5%
(Missing) 9124
91.2%
ValueCountFrequency (%)
0 45
0.4%
2 1
 
< 0.1%
5 3
 
< 0.1%
6 1
 
< 0.1%
10 7
 
0.1%
13 1
 
< 0.1%
15 4
 
< 0.1%
20 5
 
0.1%
21 2
 
< 0.1%
24 5
 
0.1%
ValueCountFrequency (%)
2000 7
0.1%
1700 8
0.1%
1600 4
< 0.1%
1510 1
 
< 0.1%
1500 7
0.1%
1480 1
 
< 0.1%
1400 4
< 0.1%
1350 1
 
< 0.1%
1340 1
 
< 0.1%
1320 1
 
< 0.1%

총점2
Real number (ℝ)

MISSING 

Distinct181
Distinct (%)20.7%
Missing9124
Missing (%)91.2%
Infinite0
Infinite (%)0.0%
Mean13.650057
Minimum0
Maximum70
Zeros62
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T11:22:41.438114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.5
median5.45
Q321.1
95-th percentile50.325
Maximum70
Range70
Interquartile range (IQR)20.6

Descriptive statistics

Standard deviation16.928516
Coefficient of variation (CV)1.2401792
Kurtosis0.68015449
Mean13.650057
Median Absolute Deviation (MAD)5.35
Skewness1.2400087
Sum11957.45
Variance286.57467
MonotonicityNot monotonic
2023-12-12T11:22:41.571255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.5 76
 
0.8%
0.0 62
 
0.6%
21.1 47
 
0.5%
0.4 44
 
0.4%
29.0 31
 
0.3%
0.2 30
 
0.3%
1.0 30
 
0.3%
0.3 28
 
0.3%
0.7 22
 
0.2%
0.1 22
 
0.2%
Other values (171) 484
 
4.8%
(Missing) 9124
91.2%
ValueCountFrequency (%)
0.0 62
0.6%
0.1 22
 
0.2%
0.2 30
 
0.3%
0.25 5
 
0.1%
0.3 28
 
0.3%
0.4 44
0.4%
0.5 76
0.8%
0.6 20
 
0.2%
0.7 22
 
0.2%
0.75 10
 
0.1%
ValueCountFrequency (%)
70.0 4
< 0.1%
68.0 3
< 0.1%
67.0 2
< 0.1%
66.0 1
 
< 0.1%
65.7 1
 
< 0.1%
65.0 2
< 0.1%
62.0 1
 
< 0.1%
60.7 1
 
< 0.1%
59.4 1
 
< 0.1%
55.5 3
< 0.1%

농업진흥구역
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.7%
Missing9850
Missing (%)98.5%
Memory size97.7 KiB
True
 
150
(Missing)
9850 
ValueCountFrequency (%)
True 150
 
1.5%
(Missing) 9850
98.5%
2023-12-12T11:22:41.692019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

우선매수
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)20.0%
Missing9995
Missing (%)> 99.9%
Memory size97.7 KiB
True
 
5
(Missing)
9995 
ValueCountFrequency (%)
True 5
 
0.1%
(Missing) 9995
> 99.9%
2023-12-12T11:22:41.764906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

감정의뢰순번
Real number (ℝ)

MISSING 

Distinct3949
Distinct (%)53.9%
Missing2674
Missing (%)26.7%
Infinite0
Infinite (%)0.0%
Mean3688.964
Minimum2
Maximum6893
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T11:22:41.878242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile447.5
Q12115
median3889
Q35471.75
95-th percentile6539
Maximum6893
Range6891
Interquartile range (IQR)3356.75

Descriptive statistics

Standard deviation1963.7213
Coefficient of variation (CV)0.53232325
Kurtosis-1.1884223
Mean3688.964
Median Absolute Deviation (MAD)1716
Skewness-0.19909279
Sum27025350
Variance3856201.3
MonotonicityNot monotonic
2023-12-12T11:22:42.010436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4770 98
 
1.0%
4769 98
 
1.0%
4771 96
 
1.0%
2115 77
 
0.8%
2116 75
 
0.8%
5326 72
 
0.7%
5327 61
 
0.6%
6004 36
 
0.4%
6003 28
 
0.3%
4821 16
 
0.2%
Other values (3939) 6669
66.7%
(Missing) 2674
26.7%
ValueCountFrequency (%)
2 1
< 0.1%
3 2
< 0.1%
4 2
< 0.1%
6 1
< 0.1%
11 1
< 0.1%
12 1
< 0.1%
15 1
< 0.1%
16 1
< 0.1%
17 2
< 0.1%
18 1
< 0.1%
ValueCountFrequency (%)
6893 1
 
< 0.1%
6892 2
< 0.1%
6890 1
 
< 0.1%
6888 1
 
< 0.1%
6887 1
 
< 0.1%
6886 4
< 0.1%
6885 3
< 0.1%
6883 1
 
< 0.1%
6882 1
 
< 0.1%
6879 1
 
< 0.1%

의뢰번호
Text

MISSING 

Distinct2293
Distinct (%)32.0%
Missing2827
Missing (%)28.3%
Memory size156.2 KiB
2023-12-12T11:22:42.352105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length8
Mean length7.8260142
Min length1

Characters and Unicode

Total characters56136
Distinct characters35
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

Unique833 ?
Unique (%)11.6%

Sample

1st row2016-26
2nd row2015-17
3rd row2015-66
4th row2005-272
5th row2007-115
ValueCountFrequency (%)
2013-123 292
 
4.1%
2004-39 152
 
2.1%
2014-155 133
 
1.9%
2015-213 64
 
0.9%
2008-29 31
 
0.4%
2014-71 31
 
0.4%
2015-17 29
 
0.4%
2008-215 28
 
0.4%
2007-94 25
 
0.3%
상수원관리과-2111 24
 
0.3%
Other values (2281) 6340
88.7%
2023-12-12T11:22:42.773151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12229
21.8%
2 10178
18.1%
1 8888
15.8%
- 7253
12.9%
5 3553
 
6.3%
3 2610
 
4.6%
4 2519
 
4.5%
7 1997
 
3.6%
9 1870
 
3.3%
6 1790
 
3.2%
Other values (25) 3249
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 47268
84.2%
Dash Punctuation 7253
 
12.9%
Other Letter 1356
 
2.4%
Open Punctuation 113
 
0.2%
Close Punctuation 113
 
0.2%
Space Separator 32
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
242
17.8%
242
17.8%
214
15.8%
212
15.6%
212
15.6%
212
15.6%
2
 
0.1%
2
 
0.1%
2
 
0.1%
2
 
0.1%
Other values (10) 14
 
1.0%
Decimal Number
ValueCountFrequency (%)
0 12229
25.9%
2 10178
21.5%
1 8888
18.8%
5 3553
 
7.5%
3 2610
 
5.5%
4 2519
 
5.3%
7 1997
 
4.2%
9 1870
 
4.0%
6 1790
 
3.8%
8 1634
 
3.5%
Dash Punctuation
ValueCountFrequency (%)
- 7253
100.0%
Open Punctuation
ValueCountFrequency (%)
( 113
100.0%
Close Punctuation
ValueCountFrequency (%)
) 113
100.0%
Space Separator
ValueCountFrequency (%)
32
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 54780
97.6%
Hangul 1356
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
242
17.8%
242
17.8%
214
15.8%
212
15.6%
212
15.6%
212
15.6%
2
 
0.1%
2
 
0.1%
2
 
0.1%
2
 
0.1%
Other values (10) 14
 
1.0%
Common
ValueCountFrequency (%)
0 12229
22.3%
2 10178
18.6%
1 8888
16.2%
- 7253
13.2%
5 3553
 
6.5%
3 2610
 
4.8%
4 2519
 
4.6%
7 1997
 
3.6%
9 1870
 
3.4%
6 1790
 
3.3%
Other values (5) 1893
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 54780
97.6%
Hangul 1356
 
2.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12229
22.3%
2 10178
18.6%
1 8888
16.2%
- 7253
13.2%
5 3553
 
6.5%
3 2610
 
4.8%
4 2519
 
4.6%
7 1997
 
3.6%
9 1870
 
3.4%
6 1790
 
3.3%
Other values (5) 1893
 
3.5%
Hangul
ValueCountFrequency (%)
242
17.8%
242
17.8%
214
15.8%
212
15.6%
212
15.6%
212
15.6%
2
 
0.1%
2
 
0.1%
2
 
0.1%
2
 
0.1%
Other values (10) 14
 
1.0%

의뢰일자
Date

MISSING 

Distinct224
Distinct (%)3.1%
Missing2690
Missing (%)26.9%
Memory size156.2 KiB
Minimum2003-04-29 00:00:00
Maximum2017-10-01 00:00:00
2023-12-12T11:22:42.933835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:22:43.072315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
5899 
<NA>
2827 
3
1109 
4
 
162
1
 
3

Length

Max length4
Median length1
Mean length1.8481
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row<NA>
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 5899
59.0%
<NA> 2827
28.3%
3 1109
 
11.1%
4 162
 
1.6%
1 3
 
< 0.1%

Length

2023-12-12T11:22:43.202366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:22:43.323933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 5899
59.0%
na 2827
28.3%
3 1109
 
11.1%
4 162
 
1.6%
1 3
 
< 0.1%

매수가격개수
Real number (ℝ)

MISSING 

Distinct18
Distinct (%)0.4%
Missing5264
Missing (%)52.6%
Infinite0
Infinite (%)0.0%
Mean1.7742821
Minimum1
Maximum21
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T11:22:43.432482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile6
Maximum21
Range20
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.8152067
Coefficient of variation (CV)1.0230654
Kurtosis16.328673
Mean1.7742821
Median Absolute Deviation (MAD)0
Skewness3.4895065
Sum8403
Variance3.2949752
MonotonicityNot monotonic
2023-12-12T11:22:43.587275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
1 3493
34.9%
2 477
 
4.8%
3 218
 
2.2%
4 178
 
1.8%
5 121
 
1.2%
6 77
 
0.8%
7 61
 
0.6%
8 41
 
0.4%
9 24
 
0.2%
10 17
 
0.2%
Other values (8) 29
 
0.3%
(Missing) 5264
52.6%
ValueCountFrequency (%)
1 3493
34.9%
2 477
 
4.8%
3 218
 
2.2%
4 178
 
1.8%
5 121
 
1.2%
6 77
 
0.8%
7 61
 
0.6%
8 41
 
0.4%
9 24
 
0.2%
10 17
 
0.2%
ValueCountFrequency (%)
21 1
 
< 0.1%
19 1
 
< 0.1%
18 2
 
< 0.1%
15 2
 
< 0.1%
14 4
 
< 0.1%
13 5
 
0.1%
12 1
 
< 0.1%
11 13
0.1%
10 17
0.2%
9 24
0.2%

매매계약순번
Real number (ℝ)

MISSING 

Distinct2902
Distinct (%)61.5%
Missing5283
Missing (%)52.8%
Infinite0
Infinite (%)0.0%
Mean2639.2589
Minimum1
Maximum4606
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T11:22:43.725160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile382
Q11515
median2853
Q33867
95-th percentile4394.2
Maximum4606
Range4605
Interquartile range (IQR)2352

Descriptive statistics

Standard deviation1329.4535
Coefficient of variation (CV)0.50372227
Kurtosis-1.167451
Mean2639.2589
Median Absolute Deviation (MAD)1125
Skewness-0.34807454
Sum12449384
Variance1767446.5
MonotonicityNot monotonic
2023-12-12T11:22:43.852405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4027 20
 
0.2%
4028 19
 
0.2%
4106 17
 
0.2%
4101 17
 
0.2%
4026 15
 
0.1%
4096 15
 
0.1%
4091 15
 
0.1%
4089 15
 
0.1%
4092 15
 
0.1%
4086 14
 
0.1%
Other values (2892) 4555
45.6%
(Missing) 5283
52.8%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 2
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
13 1
< 0.1%
14 1
< 0.1%
15 1
< 0.1%
ValueCountFrequency (%)
4606 1
< 0.1%
4604 1
< 0.1%
4603 1
< 0.1%
4602 2
< 0.1%
4601 2
< 0.1%
4600 1
< 0.1%
4598 1
< 0.1%
4597 2
< 0.1%
4596 1
< 0.1%
4594 2
< 0.1%

매수완료번호
Real number (ℝ)

MISSING  SKEWED 

Distinct1720
Distinct (%)36.5%
Missing5283
Missing (%)52.8%
Infinite0
Infinite (%)0.0%
Mean2157.4978
Minimum1
Maximum1325000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T11:22:43.994769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile106
Q1561
median1131
Q31551
95-th percentile1973.4
Maximum1325000
Range1324999
Interquartile range (IQR)990

Descriptive statistics

Standard deviation31059.048
Coefficient of variation (CV)14.395865
Kurtosis1453.1473
Mean2157.4978
Median Absolute Deviation (MAD)505
Skewness36.416273
Sum10176917
Variance9.6466443 × 108
MonotonicityNot monotonic
2023-12-12T11:22:44.172168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1493 292
 
2.9%
626 145
 
1.5%
1810 64
 
0.6%
1529 31
 
0.3%
1666 29
 
0.3%
736 19
 
0.2%
595 19
 
0.2%
847 19
 
0.2%
360 17
 
0.2%
1433 17
 
0.2%
Other values (1710) 4065
40.6%
(Missing) 5283
52.8%
ValueCountFrequency (%)
1 1
 
< 0.1%
2 4
< 0.1%
3 1
 
< 0.1%
4 2
 
< 0.1%
5 2
 
< 0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
8 5
0.1%
9 2
 
< 0.1%
10 1
 
< 0.1%
ValueCountFrequency (%)
1325000 2
 
< 0.1%
506000 4
< 0.1%
96500 2
 
< 0.1%
48000 4
< 0.1%
10910 1
 
< 0.1%
9003 2
 
< 0.1%
9001 9
0.1%
9000 1
 
< 0.1%
2089 1
 
< 0.1%
2088 1
 
< 0.1%

신청서접수일
Date

MISSING 

Distinct837
Distinct (%)17.7%
Missing5284
Missing (%)52.8%
Memory size156.2 KiB
Minimum2003-03-14 00:00:00
Maximum2017-07-13 00:00:00
2023-12-12T11:22:44.335440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:22:44.453918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

매수완료순번
Real number (ℝ)

MISSING 

Distinct2912
Distinct (%)61.6%
Missing5276
Missing (%)52.8%
Infinite0
Infinite (%)0.0%
Mean3740.8533
Minimum1
Maximum6982
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T11:22:44.908164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile468.15
Q12096
median3836
Q35503.75
95-th percentile6420.85
Maximum6982
Range6981
Interquartile range (IQR)3407.75

Descriptive statistics

Standard deviation1989.2496
Coefficient of variation (CV)0.5317636
Kurtosis-1.2159606
Mean3740.8533
Median Absolute Deviation (MAD)1698
Skewness-0.25249718
Sum17671791
Variance3957114.1
MonotonicityNot monotonic
2023-12-12T11:22:45.138883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5497 20
 
0.2%
5498 19
 
0.2%
5821 17
 
0.2%
5833 17
 
0.2%
5824 15
 
0.1%
5817 15
 
0.1%
5826 15
 
0.1%
5496 15
 
0.1%
5818 15
 
0.1%
5823 14
 
0.1%
Other values (2902) 4562
45.6%
(Missing) 5276
52.8%
ValueCountFrequency (%)
1 1
< 0.1%
6 1
< 0.1%
11 1
< 0.1%
12 1
< 0.1%
13 2
< 0.1%
14 1
< 0.1%
15 2
< 0.1%
16 1
< 0.1%
17 1
< 0.1%
19 1
< 0.1%
ValueCountFrequency (%)
6982 1
< 0.1%
6981 1
< 0.1%
6980 1
< 0.1%
6978 2
< 0.1%
6977 1
< 0.1%
6975 1
< 0.1%
6973 1
< 0.1%
6972 1
< 0.1%
6971 2
< 0.1%
6970 2
< 0.1%

계약체결일
Text

MISSING 

Distinct439
Distinct (%)9.3%
Missing5276
Missing (%)52.8%
Memory size156.2 KiB
2023-12-12T11:22:45.478168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters47240
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

Unique54 ?
Unique (%)1.1%

Sample

1st row2015-04-27
2nd row2015-06-23
3rd row2017-08-28
4th row2006-12-19
5th row2015-06-18
ValueCountFrequency (%)
2013-12-04 296
 
6.3%
2005-02-12 145
 
3.1%
2015-12-22 71
 
1.5%
2015-12-11 67
 
1.4%
2006-12-19 66
 
1.4%
2011-03-03 49
 
1.0%
2015-06-23 43
 
0.9%
2008-08-05 43
 
0.9%
2006-02-08 40
 
0.8%
2010-12-24 39
 
0.8%
Other values (429) 3865
81.8%
2023-12-12T11:22:45.949897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11815
25.0%
- 9448
20.0%
2 8900
18.8%
1 7302
15.5%
6 1807
 
3.8%
5 1645
 
3.5%
3 1563
 
3.3%
4 1310
 
2.8%
7 1273
 
2.7%
9 1126
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 37792
80.0%
Dash Punctuation 9448
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11815
31.3%
2 8900
23.5%
1 7302
19.3%
6 1807
 
4.8%
5 1645
 
4.4%
3 1563
 
4.1%
4 1310
 
3.5%
7 1273
 
3.4%
9 1126
 
3.0%
8 1051
 
2.8%
Dash Punctuation
ValueCountFrequency (%)
- 9448
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 47240
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11815
25.0%
- 9448
20.0%
2 8900
18.8%
1 7302
15.5%
6 1807
 
3.8%
5 1645
 
3.5%
3 1563
 
3.3%
4 1310
 
2.8%
7 1273
 
2.7%
9 1126
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 47240
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11815
25.0%
- 9448
20.0%
2 8900
18.8%
1 7302
15.5%
6 1807
 
3.8%
5 1645
 
3.5%
3 1563
 
3.3%
4 1310
 
2.8%
7 1273
 
2.7%
9 1126
 
2.4%

이행예정일
Text

MISSING 

Distinct81
Distinct (%)2.0%
Missing5934
Missing (%)59.3%
Memory size156.2 KiB
2023-12-12T11:22:46.269320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters40660
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

Unique8 ?
Unique (%)0.2%

Sample

1st row2015-01-01
2nd row2016-01-01
3rd row2018-01-01
4th row2007-02-28
5th row2015-01-01
ValueCountFrequency (%)
2016-01-01 860
21.2%
2010-01-01 617
15.2%
2015-01-01 457
11.2%
2011-01-01 373
9.2%
2013-01-01 329
 
8.1%
2018-01-01 226
 
5.6%
2017-01-01 200
 
4.9%
2012-01-01 158
 
3.9%
2008-01-01 150
 
3.7%
2014-01-01 118
 
2.9%
Other values (71) 578
14.2%
2023-12-12T11:22:46.728103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13113
32.3%
1 11569
28.5%
- 8132
20.0%
2 4413
 
10.9%
6 1014
 
2.5%
5 558
 
1.4%
8 540
 
1.3%
7 529
 
1.3%
3 477
 
1.2%
4 245
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 32528
80.0%
Dash Punctuation 8132
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13113
40.3%
1 11569
35.6%
2 4413
 
13.6%
6 1014
 
3.1%
5 558
 
1.7%
8 540
 
1.7%
7 529
 
1.6%
3 477
 
1.5%
4 245
 
0.8%
9 70
 
0.2%
Dash Punctuation
ValueCountFrequency (%)
- 8132
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 40660
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 13113
32.3%
1 11569
28.5%
- 8132
20.0%
2 4413
 
10.9%
6 1014
 
2.5%
5 558
 
1.4%
8 540
 
1.3%
7 529
 
1.3%
3 477
 
1.2%
4 245
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 40660
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13113
32.3%
1 11569
28.5%
- 8132
20.0%
2 4413
 
10.9%
6 1014
 
2.5%
5 558
 
1.4%
8 540
 
1.3%
7 529
 
1.3%
3 477
 
1.2%
4 245
 
0.6%

이행완료일
Date

MISSING 

Distinct128
Distinct (%)3.1%
Missing5915
Missing (%)59.2%
Memory size156.2 KiB
Minimum2003-12-10 00:00:00
Maximum2019-01-01 00:00:00
2023-12-12T11:22:46.888342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:22:47.080477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

매수완료번호_1
Real number (ℝ)

MISSING  SKEWED 

Distinct1705
Distinct (%)36.1%
Missing5283
Missing (%)52.8%
Infinite0
Infinite (%)0.0%
Mean2155.6718
Minimum0
Maximum1325000
Zeros5
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T11:22:47.229584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile105
Q1562
median1130
Q31551
95-th percentile1973.4
Maximum1325000
Range1325000
Interquartile range (IQR)989

Descriptive statistics

Standard deviation31059.128
Coefficient of variation (CV)14.408097
Kurtosis1453.1407
Mean2155.6718
Median Absolute Deviation (MAD)504
Skewness36.416164
Sum10168304
Variance9.6466946 × 108
MonotonicityNot monotonic
2023-12-12T11:22:47.374471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1493 292
 
2.9%
626 145
 
1.5%
1810 64
 
0.6%
1529 31
 
0.3%
1666 29
 
0.3%
736 22
 
0.2%
847 19
 
0.2%
595 19
 
0.2%
360 17
 
0.2%
1433 17
 
0.2%
Other values (1695) 4062
40.6%
(Missing) 5283
52.8%
ValueCountFrequency (%)
0 5
0.1%
1 1
 
< 0.1%
2 4
< 0.1%
3 1
 
< 0.1%
4 2
 
< 0.1%
5 2
 
< 0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
8 5
0.1%
9 2
 
< 0.1%
ValueCountFrequency (%)
1325000 2
 
< 0.1%
506000 4
< 0.1%
96500 2
 
< 0.1%
48000 4
< 0.1%
10910 1
 
< 0.1%
9003 2
 
< 0.1%
9001 9
0.1%
9000 1
 
< 0.1%
2089 1
 
< 0.1%
2088 1
 
< 0.1%

매수현황순번
Real number (ℝ)

Distinct7259
Distinct (%)72.6%
Missing4
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean6042.7008
Minimum2
Maximum12796
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T11:22:47.562108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile431.5
Q12863.25
median6439.5
Q38817.25
95-th percentile11933.25
Maximum12796
Range12794
Interquartile range (IQR)5954

Descriptive statistics

Standard deviation3566.1558
Coefficient of variation (CV)0.59015926
Kurtosis-1.10882
Mean6042.7008
Median Absolute Deviation (MAD)2848.5
Skewness-0.063137186
Sum60402837
Variance12717468
MonotonicityNot monotonic
2023-12-12T11:22:47.750956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9327 20
 
0.2%
8470 19
 
0.2%
9328 19
 
0.2%
8466 19
 
0.2%
8471 18
 
0.2%
8469 17
 
0.2%
8419 17
 
0.2%
8431 17
 
0.2%
8465 16
 
0.2%
8472 16
 
0.2%
Other values (7249) 9818
98.2%
ValueCountFrequency (%)
2 1
< 0.1%
3 1
< 0.1%
4 2
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 2
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
11 1
< 0.1%
14 1
< 0.1%
ValueCountFrequency (%)
12796 1
< 0.1%
12793 1
< 0.1%
12792 1
< 0.1%
12791 1
< 0.1%
12788 1
< 0.1%
12785 1
< 0.1%
12784 1
< 0.1%
12783 1
< 0.1%
12782 1
< 0.1%
12781 1
< 0.1%

면적_1
Real number (ℝ)

Distinct2931
Distinct (%)29.3%
Missing4
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean4176.7815
Minimum0
Maximum462227
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T11:22:47.899908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile99
Q1422.75
median949
Q31931
95-th percentile13761.75
Maximum462227
Range462227
Interquartile range (IQR)1508.25

Descriptive statistics

Standard deviation18080.264
Coefficient of variation (CV)4.328755
Kurtosis166.13154
Mean4176.7815
Median Absolute Deviation (MAD)635
Skewness11.012177
Sum41751108
Variance3.2689595 × 108
MonotonicityNot monotonic
2023-12-12T11:22:48.085812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
513.0 44
 
0.4%
843.0 41
 
0.4%
2003.0 38
 
0.4%
1915.0 37
 
0.4%
99.0 33
 
0.3%
660.0 33
 
0.3%
245.0 27
 
0.3%
212.0 26
 
0.3%
330.0 26
 
0.3%
347.0 26
 
0.3%
Other values (2921) 9665
96.7%
ValueCountFrequency (%)
0.0 1
 
< 0.1%
1.0 7
0.1%
2.0 9
0.1%
4.0 7
0.1%
5.0 6
0.1%
6.0 5
0.1%
7.0 2
 
< 0.1%
8.0 4
< 0.1%
9.0 5
0.1%
10.0 2
 
< 0.1%
ValueCountFrequency (%)
462227.0 1
< 0.1%
407209.0 1
< 0.1%
355438.0 1
< 0.1%
337190.0 1
< 0.1%
303174.0 1
< 0.1%
290578.0 2
< 0.1%
274314.0 1
< 0.1%
260430.0 2
< 0.1%
251008.0 2
< 0.1%
237604.0 1
< 0.1%

지목_1
Categorical

IMBALANCE 

Distinct48
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3288 
3103 
대지
1208 
임야
1062 
과수원
 
263
Other values (43)
1076 

Length

Max length7
Median length1
Mean length1.436
Min length1

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
3288
32.9%
3103
31.0%
대지 1208
 
12.1%
임야 1062
 
10.6%
과수원 263
 
2.6%
도로 162
 
1.6%
146
 
1.5%
목장 144
 
1.4%
잡종지 125
 
1.2%
목장용지 114
 
1.1%
Other values (38) 385
 
3.9%

Length

2023-12-12T11:22:48.233148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
3291
32.9%
3103
31.0%
대지 1208
 
12.1%
임야 1062
 
10.6%
과수원 263
 
2.6%
도로 162
 
1.6%
146
 
1.5%
목장 144
 
1.4%
잡종지 125
 
1.2%
목장용지 114
 
1.1%
Other values (35) 382
 
3.8%

매수상황순번
Real number (ℝ)

MISSING 

Distinct3651
Distinct (%)64.7%
Missing4357
Missing (%)43.6%
Infinite0
Infinite (%)0.0%
Mean3874.2694
Minimum1
Maximum7592
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T11:22:48.390701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile479
Q11973.5
median3841
Q35908
95-th percentile6964.7
Maximum7592
Range7591
Interquartile range (IQR)3934.5

Descriptive statistics

Standard deviation2169.7584
Coefficient of variation (CV)0.56004325
Kurtosis-1.2889813
Mean3874.2694
Median Absolute Deviation (MAD)1994
Skewness-0.11279331
Sum21862502
Variance4707851.6
MonotonicityNot monotonic
2023-12-12T11:22:48.599783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5935 20
 
0.2%
5936 19
 
0.2%
6251 17
 
0.2%
6239 17
 
0.2%
6244 15
 
0.1%
6236 15
 
0.1%
5934 15
 
0.1%
6242 15
 
0.1%
6235 15
 
0.1%
6238 14
 
0.1%
Other values (3641) 5481
54.8%
(Missing) 4357
43.6%
ValueCountFrequency (%)
1 1
< 0.1%
6 1
< 0.1%
11 1
< 0.1%
12 1
< 0.1%
13 2
< 0.1%
14 1
< 0.1%
15 2
< 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%
7588 2
< 0.1%
7587 1
< 0.1%
7581 1
< 0.1%
7579 1
< 0.1%
7578 1
< 0.1%
7577 2
< 0.1%
7576 2
< 0.1%
Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
매수완료
4709 
<NA>
4357 
매수취하
 
438
매수포기
 
226
취하
 
184
Other values (3)
 
86

Length

Max length4
Median length4
Mean length3.9462
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
매수완료 4709
47.1%
<NA> 4357
43.6%
매수취하 438
 
4.4%
매수포기 226
 
2.3%
취하 184
 
1.8%
반려 80
 
0.8%
대기 4
 
< 0.1%
진행중 2
 
< 0.1%

Length

2023-12-12T11:22:48.783192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:22:48.949956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
매수완료 4709
47.1%
na 4357
43.6%
매수취하 438
 
4.4%
매수포기 226
 
2.3%
취하 184
 
1.8%
반려 80
 
0.8%
대기 4
 
< 0.1%
진행중 2
 
< 0.1%

매수완료번호_2
Real number (ℝ)

MISSING  SKEWED 

Distinct1704
Distinct (%)36.1%
Missing5276
Missing (%)52.8%
Infinite0
Infinite (%)0.0%
Mean2157.2851
Minimum0
Maximum1325000
Zeros5
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T11:22:49.149696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile106
Q1563.75
median1133
Q31553.25
95-th percentile1972.85
Maximum1325000
Range1325000
Interquartile range (IQR)989.5

Descriptive statistics

Standard deviation31036.017
Coefficient of variation (CV)14.386609
Kurtosis1455.308
Mean2157.2851
Median Absolute Deviation (MAD)507
Skewness36.443306
Sum10191015
Variance9.6323436 × 108
MonotonicityNot monotonic
2023-12-12T11:22:49.364874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1493 292
 
2.9%
626 145
 
1.5%
1810 64
 
0.6%
1529 31
 
0.3%
1666 29
 
0.3%
736 22
 
0.2%
595 19
 
0.2%
847 19
 
0.2%
360 17
 
0.2%
1433 17
 
0.2%
Other values (1694) 4069
40.7%
(Missing) 5276
52.8%
ValueCountFrequency (%)
0 5
0.1%
1 1
 
< 0.1%
2 4
< 0.1%
3 1
 
< 0.1%
4 2
 
< 0.1%
5 2
 
< 0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
8 5
0.1%
9 2
 
< 0.1%
ValueCountFrequency (%)
1325000 2
 
< 0.1%
506000 4
< 0.1%
96500 2
 
< 0.1%
48000 4
< 0.1%
10910 1
 
< 0.1%
9003 2
 
< 0.1%
9001 9
0.1%
9000 1
 
< 0.1%
2089 1
 
< 0.1%
2088 1
 
< 0.1%

토지외물건개수
Real number (ℝ)

ZEROS 

Distinct29
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.155
Minimum0
Maximum60
Zeros8234
Zeros (%)82.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T11:22:49.540877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile8
Maximum60
Range60
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.5508923
Coefficient of variation (CV)3.0743656
Kurtosis36.646504
Mean1.155
Median Absolute Deviation (MAD)0
Skewness4.9985125
Sum11550
Variance12.608836
MonotonicityNot monotonic
2023-12-12T11:22:49.692144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0 8234
82.3%
2 623
 
6.2%
4 240
 
2.4%
6 232
 
2.3%
8 132
 
1.3%
12 111
 
1.1%
10 84
 
0.8%
3 77
 
0.8%
9 68
 
0.7%
14 47
 
0.5%
Other values (19) 152
 
1.5%
ValueCountFrequency (%)
0 8234
82.3%
1 1
 
< 0.1%
2 623
 
6.2%
3 77
 
0.8%
4 240
 
2.4%
6 232
 
2.3%
8 132
 
1.3%
9 68
 
0.7%
10 84
 
0.8%
12 111
 
1.1%
ValueCountFrequency (%)
60 1
 
< 0.1%
51 2
 
< 0.1%
39 2
 
< 0.1%
36 1
 
< 0.1%
34 2
 
< 0.1%
33 2
 
< 0.1%
32 5
0.1%
30 4
< 0.1%
28 3
< 0.1%
27 3
< 0.1%

Sample

매도신청순번접수번호신청일소유자순번신청자순번접수필지순번토지주소지역구분지목면적용도공시지가매수시작순번매수시작접수일거리거리순번일자현지조사순번출장목적출장시작일출장종료일출장장소순번폐수배출시설공장특정토양오염관리대상시설돈사허가규모이상돈사신고규모이상우사허가규모이상우사신고규모이상우사신고규모미만기타신고규모이상기타신고규모미만목욕장숙박식품접객업소공동주택주택등일반건축물나대지전답과수원임야상수원보호구역수변구역특별대책지역1권역특별대책지역2권역점오염원비점오염원연접토지총점경사도하천경계로부터의거리거리_1총점2농업진흥구역우선매수감정의뢰순번의뢰번호의뢰일자감정가격개수매수가격개수매매계약순번매수완료번호신청서접수일매수완료순번계약체결일이행예정일이행완료일매수완료번호_1매수현황순번면적_1지목_1매수상황순번매수상황진행상태매수완료번호_2토지외물건개수
13261401139532015-12-28429542609432대전광역시 동구 세천동 13상수원보호구역1812.0농경지64,10094212015-12-28150.087082015-12-282447<NA>2016-01-012016-01-01<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>61942016-262016-04-013<NA><NA><NA><NA><NA><NA><NA><NA><NA>94221812.06498매수포기<NA>0
4356208720862008-04-21208620865506전라북도 진안군 진안읍 물곡리 555-1자연마을목장663.0축사11,50054792008-04-21NaN48562010-05-26<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><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>5504663.0목장<NA><NA><NA>0
12051378037262014-12-23405640238961충청북도 영동군 심천면 고당리 190수변구역93.0농경지1030089462014-12-2380.082382014-12-232282<NA>2015-01-012015-01-01<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>55652015-172015-03-0121334016662014-12-2344882015-04-272015-01-012015-01-011666895293.04929매수완료16660
9509340433672013-04-10365336358093충청북도 영동군 심천면 심천리 628-1기타지역2900.0농경지810080782013-04-1020.073692013-04-102339<NA>2015-01-012015-01-01<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>60632015-662015-05-0125413317042013-04-1057102015-06-232016-01-012016-01-01170480842900.06137매수완료17048
113753593582005-08-11358358875충청북도 옥천군 군북면 대정리 664-5자연마을52.0농경지63908682005-08-11270.08752005-08-11247토지등의 매도신청지(3건 : 전운천, 김유태, 김영찬) 현지확인2005-08-222005-08-22옥천군<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>6972005-2722005-08-012<NA><NA><NA><NA><NA><NA><NA><NA><NA>87552.01603매수취하<NA>0
2121155715562006-07-27155615563389충청북도 옥천군 동이면 조령리 4수변구역대지992.0주택957033832006-07-271033892006-07-271424<NA>2010-01-012011-01-01<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>17902007-1152007-08-102<NA><NA><NA><NA><NA><NA><NA><NA><NA>3389992.0대지2011매수취하<NA>10
14199427042092016-11-04455845199979충청북도 옥천군 군서면 하동리 145특대2권역1520.0농경지1530099722016-11-040.092552016-12-302635<NA>2017-01-012017-01-01<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>66012017-132017-03-0121441720492016-11-0464342017-08-282018-01-012018-01-01204999691520.07073매수완료20490
27801711702005-02-02170170475전라북도 진안군 상전면 용평리 27수변구역임야39134.0임야2374722005-02-0204752005-02-031301<NA>2010-01-012010-01-01<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>331상수원관리과-1324(2005-85)2005-05-042<NA><NA><NA><NA><NA><NA><NA><NA><NA>47539134.0임야1496매수취하<NA>0
6819269526782010-12-15293029126625충청북도 옥천군 이원면 백지리 423특별대책지역2569.0농경지726066102010-12-1552059012011-02-19<NA><NA><NA><NA><NA>2477<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0.1<NA>0.1<NA>501m~1000m5200.1<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>6616569.0<NA><NA><NA>0
5415234123412009-05-26235223365120충청북도 옥천군 이원면 용방리 200상수원보호구역과수원705.0과수원3,52050912009-05-260<NA><NA>1376<NA>2010-01-012011-01-01<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>31982010-522010-05-012<NA><NA><NA><NA><NA><NA><NA><NA><NA>5118705.0과수원<NA><NA><NA>0
매도신청순번접수번호신청일소유자순번신청자순번접수필지순번토지주소지역구분지목면적용도공시지가매수시작순번매수시작접수일거리거리순번일자현지조사순번출장목적출장시작일출장종료일출장장소순번폐수배출시설공장특정토양오염관리대상시설돈사허가규모이상돈사신고규모이상우사허가규모이상우사신고규모이상우사신고규모미만기타신고규모이상기타신고규모미만목욕장숙박식품접객업소공동주택주택등일반건축물나대지전답과수원임야상수원보호구역수변구역특별대책지역1권역특별대책지역2권역점오염원비점오염원연접토지총점경사도하천경계로부터의거리거리_1총점2농업진흥구역우선매수감정의뢰순번의뢰번호의뢰일자감정가격개수매수가격개수매매계약순번매수완료번호신청서접수일매수완료순번계약체결일이행예정일이행완료일매수완료번호_1매수현황순번면적_1지목_1매수상황순번매수상황진행상태매수완료번호_2토지외물건개수
10913351734682013-09-09377337518491전라북도 장수군 천천면 장판리 375-5수변구역99.0농경지534084762013-09-09130.077672013-09-092160매도신청지 현지조사2014-03-242015-01-01전북 장수군<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>48222014-712014-04-2121301915292014-05-2841962014-06-162014-11-102014-11-031529848299.04660매수완료15290
12300382337682015-02-25410140669069충청북도 옥천군 안내면 서대리 336수변구역2139.0농경지1140090542015-02-2520.083462015-02-26<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>58252015-1142015-08-0121390217572015-02-2553352015-10-282016-01-012016-01-01175790602139.05792매수완료17570
732028282003-09-16282862충청북도 보은군 회남면 남대문리 172-4수변구역대지216.0음식점3640622003-09-16300622003-09-1671토지등 매도신청지(1건) 현지확인2003-10-022003-10-02충청북도 보은군<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>472003-152003-10-142135132003-11-27252003-12-29<NA>2003-12-291362216.0대지25매수완료130
8318311130742012-04-13334833307487전라북도 무주군 무주읍 읍내리 562-4기타지역496.0농경지300074722012-04-13550.067632012-10-10<NA><NA><NA><NA><NA>2527<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0.0<NA>501m~1000m5500.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>7478496.0<NA><NA><NA>0
185177377362005-12-307367361704충청북도 옥천군 안내면 인포리 산1-1특별대책지역임야58640.0임야46317062005-12-3010.017042005-12-30<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>3029<NA>2006-05-042<NA><NA><NA><NA><NA><NA><NA><NA><NA>170458640.0임야<NA><NA><NA>0
16426530050652019-06-115598555112180충청북도 영동군 심천면 고당리 818-1기타지역과수원1276.0농경지7520121692019-06-11720.0114542019-06-26<NA><NA><NA><NA><NA>2558<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0.0<NA>501m~1000m7200.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>121641276.0과수원<NA><NA><NA>0
6731181172004-12-08117117375충청북도 보은군 회남면 거교리 137-4수변구역576.0축사30903722004-12-08203752004-12-081197<NA>2010-01-012010-01-01<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>2302005-032005-02-072<NA><NA><NA><NA><NA><NA><NA><NA><NA>375576.0<NA><NA><NA>0
284107310722006-02-20263226122374충청북도 옥천군 동이면 석탄리 산6-7수변구역임야44949.0임야24023692006-02-20023742006-02-20<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><NA><NA><NA><NA><NA><NA><NA><NA>237444949.0임야<NA><NA><NA>0
13357403439762016-01-29431842839501충청남도 금산군 부리면 어재리 165-1기타지역866.0농경지1370094902016-01-2925.087772016-01-292551<NA>2016-01-012017-01-01<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>64192016-1252016-09-012<NA><NA><NA><NA><NA><NA><NA><NA><NA>9491866.06531매수포기<NA>0
1911149614952006-06-23149514953271충청북도 옥천군 안남면 도덕리 488-13특별대책지역2281.0농경지391032622006-06-23140032712006-06-23<NA><NA><NA><NA><NA>2183<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0.7<NA>0.7<NA>1001m~1500m14000.7<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>32712281.0<NA><NA><NA>0

Duplicate rows

Most frequently occurring

매도신청순번접수번호신청일소유자순번신청자순번접수필지순번토지주소지역구분지목면적용도공시지가매수시작순번매수시작접수일거리순번일자현지조사순번출장목적출장시작일출장종료일출장장소순번폐수배출시설공장특정토양오염관리대상시설돈사허가규모이상돈사신고규모이상우사허가규모이상우사신고규모이상우사신고규모미만기타신고규모이상기타신고규모미만목욕장숙박식품접객업소공동주택주택등일반건축물나대지전답과수원임야상수원보호구역수변구역특별대책지역1권역특별대책지역2권역점오염원비점오염원연접토지총점경사도하천경계로부터의거리거리_1총점2농업진흥구역우선매수감정의뢰순번의뢰번호의뢰일자감정가격개수매수가격개수매매계약순번매수완료번호신청서접수일매수완료순번계약체결일이행예정일이행완료일매수완료번호_1매수현황순번면적_1지목_1매수상황순번매수상황진행상태매수완료번호_2토지외물건개수# duplicates
22562552005-04-16255255649충청북도 청주시 상당구 문의면 소전리 724상수원보호구역912.0농경지20806462005-04-166492005-04-186토지등 매도신청지(4건 : 서재억, 이원우, 이상묵, 윤두임) 현지확인 및 공작물 철거확인(양상순)2005-06-032005-06-03청원,보은,옥천<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>5012005-1822005-07-15214832032005-10-074882005-11-03<NA><NA>203649912.0482매수완료20303
42562552005-04-16255255650충청북도 청주시 상당구 문의면 소전리 726상수원보호구역645.0농경지24606472005-04-166502005-04-186토지등 매도신청지(4건 : 서재억, 이원우, 이상묵, 윤두임) 현지확인 및 공작물 철거확인(양상순)2005-06-032005-06-03청원,보은,옥천<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>5022005-1822005-07-15214842032005-10-074892005-11-03<NA><NA>203650645.0483매수완료20303
8216221612008-09-05215421544770충청북도 옥천군 군북면 대정리 118-4수변구역1001.0농경지580047592008-09-0547082008-10-24994토지등 매도신청지 현지확인2008-10-282008-10-28충북 옥천<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><NA><NA><NA>47701001.0<NA><NA><NA>03
11216221612008-09-05215421544773충청북도 옥천군 군북면 대정리 495-3자연마을373.0주택4000<NA><NA>47112008-10-24994토지등 매도신청지 현지확인2008-10-282008-10-28충북 옥천<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>26352008-12-232010-01-012010-01-017274773373.0<NA><NA><NA>03
02562552005-04-16255255648충청북도 청주시 상당구 문의면 소전리 641-3상수원보호구역140.0농경지23806452005-04-166482005-04-186토지등 매도신청지(4건 : 서재억, 이원우, 이상묵, 윤두임) 현지확인 및 공작물 철거확인(양상순)2005-06-032005-06-03청원,보은,옥천<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>5012005-1822005-07-15214822032005-10-074872005-11-03<NA><NA>203648140.0484매수완료20302
12562552005-04-16255255648충청북도 청주시 상당구 문의면 소전리 641-3상수원보호구역140.0농경지23806452005-04-166482005-04-186토지등 매도신청지(4건 : 서재억, 이원우, 이상묵, 윤두임) 현지확인 및 공작물 철거확인(양상순)2005-06-032005-06-03청원,보은,옥천<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>5022005-1822005-07-15214822032005-10-074872005-11-03<NA><NA>203648140.0484매수완료20302
32562552005-04-16255255650충청북도 청주시 상당구 문의면 소전리 726상수원보호구역645.0농경지24606472005-04-166502005-04-186토지등 매도신청지(4건 : 서재억, 이원우, 이상묵, 윤두임) 현지확인 및 공작물 철거확인(양상순)2005-06-032005-06-03청원,보은,옥천<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>5012005-1822005-07-15214842032005-10-074892005-11-03<NA><NA>203650645.0483매수완료20302
53233222005-07-08322322790전라북도 진안군 정천면 망화리 56수변구역임야532.0임야20207832005-07-087902005-07-08994토지등 매도신청지 현지확인2008-10-282008-10-28충북 옥천<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>6252005-2402005-08-09215552252005-11-095222005-12-07<NA><NA>225790532.0임야515매수완료22502
63233222005-07-08322322792전라북도 진안군 정천면 망화리 121수변구역임야466.0임야5467852005-07-087922005-07-08994토지등 매도신청지 현지확인2008-10-282008-10-28충북 옥천<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>6252005-2402005-08-09215572252005-11-09<NA><NA><NA><NA><NA>792466.0임야518매수완료22502
7121912182006-03-15121812186287전라북도 진안군 상전면 구룡리 67수변구역833.0농경지397062722006-03-1555632010-08-11935토지등 매도신청지 현지확인2008-08-292008-08-29전북 진안<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>29472008-1302008-09-222119986652008-10-2125792008-11-172010-01-012010-01-016656278833.02699매수완료66502