Overview

Dataset statistics

Number of variables13
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 MiB
Average record size in memory124.0 B

Variable types

Numeric10
Categorical3

Dataset

Description한국부동산원(구.한국감정원)에서 제공하는 부동산 거래 통계를 조회할 수 있는 서비스로 충남의 지목별 거래 건수 정보를 제공합니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/bigdata/collect/view.chungnam?menuCd=DOM_000000201001001000&apiIdx=2554

Alerts

지역명 is highly overall correlated with 번호 and 2 other fieldsHigh correlation
지역구분 레벨 is highly overall correlated with 번호 and 8 other fieldsHigh correlation
번호 is highly overall correlated with 지역코드 and 5 other fieldsHigh correlation
지역코드 is highly overall correlated with 번호 and 5 other fieldsHigh correlation
지목별합계_건수 is highly overall correlated with 번호 and 8 other fieldsHigh correlation
전_건수 is highly overall correlated with 지목별합계_건수 and 4 other fieldsHigh correlation
답_건수 is highly overall correlated with 지목별합계_건수 and 4 other fieldsHigh correlation
대지_건수 is highly overall correlated with 번호 and 5 other fieldsHigh correlation
임야_건수 is highly overall correlated with 지목별합계_건수 and 4 other fieldsHigh correlation
공장_건수 is highly overall correlated with 번호 and 4 other fieldsHigh correlation
기타_건수 is highly overall correlated with 지목별합계_건수 and 6 other fieldsHigh correlation
지역구분 레벨 is highly imbalanced (51.0%)Imbalance
번호 has unique valuesUnique
전_건수 has 422 (4.2%) zerosZeros
답_건수 has 622 (6.2%) zerosZeros
임야_건수 has 1103 (11.0%) zerosZeros
공장_건수 has 3160 (31.6%) zerosZeros
기타_건수 has 434 (4.3%) zerosZeros

Reproduction

Analysis started2024-01-09 22:24:46.891501
Analysis finished2024-01-09 22:24:57.964628
Duration11.07 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6065.9363
Minimum2
Maximum12138
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T07:24:58.021354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile601.95
Q13048.75
median6074.5
Q39081.5
95-th percentile11531.05
Maximum12138
Range12136
Interquartile range (IQR)6032.75

Descriptive statistics

Standard deviation3499.9056
Coefficient of variation (CV)0.57697698
Kurtosis-1.1946667
Mean6065.9363
Median Absolute Deviation (MAD)3016
Skewness-0.0017715854
Sum60659363
Variance12249339
MonotonicityNot monotonic
2024-01-10T07:24:58.135768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11272 1
 
< 0.1%
10879 1
 
< 0.1%
10017 1
 
< 0.1%
725 1
 
< 0.1%
8827 1
 
< 0.1%
7415 1
 
< 0.1%
4215 1
 
< 0.1%
9200 1
 
< 0.1%
2203 1
 
< 0.1%
6730 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
6 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
11 1
< 0.1%
12 1
< 0.1%
13 1
< 0.1%
14 1
< 0.1%
ValueCountFrequency (%)
12138 1
< 0.1%
12137 1
< 0.1%
12135 1
< 0.1%
12134 1
< 0.1%
12133 1
< 0.1%
12132 1
< 0.1%
12131 1
< 0.1%
12130 1
< 0.1%
12129 1
< 0.1%
12128 1
< 0.1%

지역코드
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44414.753
Minimum44000
Maximum44825
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T07:24:58.229107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum44000
5-th percentile44000
Q144150
median44230
Q344770
95-th percentile44825
Maximum44825
Range825
Interquartile range (IQR)620

Descriptive statistics

Standard deviation305.59372
Coefficient of variation (CV)0.0068804553
Kurtosis-1.7262536
Mean44414.753
Median Absolute Deviation (MAD)100
Skewness0.31155412
Sum4.4414753 × 108
Variance93387.524
MonotonicityNot monotonic
2024-01-10T07:24:58.308360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
44760 595
 
5.9%
44000 580
 
5.8%
44250 580
 
5.8%
44200 578
 
5.8%
44180 576
 
5.8%
44130 575
 
5.8%
44790 574
 
5.7%
44230 574
 
5.7%
44770 573
 
5.7%
44710 572
 
5.7%
Other values (8) 4223
42.2%
ValueCountFrequency (%)
44000 580
5.8%
44130 575
5.8%
44131 497
5.0%
44133 492
4.9%
44150 571
5.7%
44180 576
5.8%
44200 578
5.8%
44210 571
5.7%
44230 574
5.7%
44250 580
5.8%
ValueCountFrequency (%)
44825 570
5.7%
44810 571
5.7%
44800 562
5.6%
44790 574
5.7%
44770 573
5.7%
44760 595
5.9%
44710 572
5.7%
44270 389
3.9%
44250 580
5.8%
44230 574
5.7%

지역명
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
부여군
 
595
충남
 
580
계룡시
 
580
아산시
 
578
보령시
 
576
Other values (13)
7091 

Length

Max length3
Median length3
Mean length2.942
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row예산군
2nd row서천군
3rd row서산시
4th row충남
5th row계룡시

Common Values

ValueCountFrequency (%)
부여군 595
 
5.9%
충남 580
 
5.8%
계룡시 580
 
5.8%
아산시 578
 
5.8%
보령시 576
 
5.8%
천안시 575
 
5.8%
청양군 574
 
5.7%
논산시 574
 
5.7%
서천군 573
 
5.7%
금산군 572
 
5.7%
Other values (8) 4223
42.2%

Length

2024-01-10T07:24:58.396054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
부여군 595
 
5.9%
충남 580
 
5.8%
계룡시 580
 
5.8%
아산시 578
 
5.8%
보령시 576
 
5.8%
천안시 575
 
5.8%
청양군 574
 
5.7%
논산시 574
 
5.7%
서천군 573
 
5.7%
금산군 572
 
5.7%
Other values (8) 4223
42.2%

조사일자
Real number (ℝ)

Distinct213
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean201519.18
Minimum200601
Maximum202309
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T07:24:58.488816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum200601
5-th percentile200702
Q1201103
median201512
Q3202003
95-th percentile202301
Maximum202309
Range1708
Interquartile range (IQR)900

Descriptive statistics

Standard deviation514.73773
Coefficient of variation (CV)0.0025542865
Kurtosis-1.2059755
Mean201519.18
Median Absolute Deviation (MAD)489
Skewness-0.16246209
Sum2.0151918 × 109
Variance264954.93
MonotonicityNot monotonic
2024-01-10T07:24:58.845310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
201907 67
 
0.7%
202209 66
 
0.7%
202205 66
 
0.7%
202008 66
 
0.7%
202206 65
 
0.7%
202110 65
 
0.7%
202302 65
 
0.7%
202208 64
 
0.6%
202005 63
 
0.6%
202010 63
 
0.6%
Other values (203) 9350
93.5%
ValueCountFrequency (%)
200601 39
0.4%
200602 34
0.3%
200603 36
0.4%
200604 37
0.4%
200605 38
0.4%
200606 34
0.3%
200607 38
0.4%
200608 38
0.4%
200609 35
0.4%
200610 41
0.4%
ValueCountFrequency (%)
202309 60
0.6%
202308 53
0.5%
202307 59
0.6%
202306 57
0.6%
202305 58
0.6%
202304 62
0.6%
202303 58
0.6%
202302 65
0.7%
202301 57
0.6%
202212 62
0.6%

거래유형
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
3083 
3
3051 
2
3030 
8
836 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row8
2nd row3
3rd row1
4th row3
5th row2

Common Values

ValueCountFrequency (%)
1 3083
30.8%
3 3051
30.5%
2 3030
30.3%
8 836
 
8.4%

Length

2024-01-10T07:24:58.940696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:24:59.016654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 3083
30.8%
3 3051
30.5%
2 3030
30.3%
8 836
 
8.4%

지목별합계_건수
Real number (ℝ)

HIGH CORRELATION 

Distinct2699
Distinct (%)27.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1195.1425
Minimum5
Maximum25927
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T07:24:59.122824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile67
Q1237.75
median496
Q3979.25
95-th percentile5530.05
Maximum25927
Range25922
Interquartile range (IQR)741.5

Descriptive statistics

Standard deviation2436.6906
Coefficient of variation (CV)2.0388285
Kurtosis22.875542
Mean1195.1425
Median Absolute Deviation (MAD)317
Skewness4.4848361
Sum11951425
Variance5937461.3
MonotonicityNot monotonic
2024-01-10T07:24:59.267833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
82 25
 
0.2%
133 23
 
0.2%
76 22
 
0.2%
79 21
 
0.2%
331 21
 
0.2%
139 21
 
0.2%
86 20
 
0.2%
425 19
 
0.2%
150 19
 
0.2%
452 19
 
0.2%
Other values (2689) 9790
97.9%
ValueCountFrequency (%)
5 2
 
< 0.1%
7 1
 
< 0.1%
9 2
 
< 0.1%
10 1
 
< 0.1%
11 4
< 0.1%
12 1
 
< 0.1%
13 4
< 0.1%
14 4
< 0.1%
15 6
0.1%
16 1
 
< 0.1%
ValueCountFrequency (%)
25927 1
< 0.1%
23450 1
< 0.1%
23070 1
< 0.1%
23024 1
< 0.1%
22718 1
< 0.1%
21516 1
< 0.1%
21064 1
< 0.1%
20906 1
< 0.1%
20701 1
< 0.1%
19845 1
< 0.1%

전_건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct743
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean157.6785
Minimum0
Maximum3486
Zeros422
Zeros (%)4.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T07:24:59.405586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q19
median86
Q3135
95-th percentile317
Maximum3486
Range3486
Interquartile range (IQR)126

Descriptive statistics

Standard deviation372.00803
Coefficient of variation (CV)2.3592819
Kurtosis24.067591
Mean157.6785
Median Absolute Deviation (MAD)66
Skewness4.8042037
Sum1576785
Variance138389.97
MonotonicityNot monotonic
2024-01-10T07:24:59.545249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 422
 
4.2%
2 376
 
3.8%
1 342
 
3.4%
3 337
 
3.4%
4 271
 
2.7%
5 232
 
2.3%
6 175
 
1.8%
7 168
 
1.7%
8 132
 
1.3%
10 99
 
1.0%
Other values (733) 7446
74.5%
ValueCountFrequency (%)
0 422
4.2%
1 342
3.4%
2 376
3.8%
3 337
3.4%
4 271
2.7%
5 232
2.3%
6 175
1.8%
7 168
 
1.7%
8 132
 
1.3%
9 93
 
0.9%
ValueCountFrequency (%)
3486 1
< 0.1%
3432 1
< 0.1%
3428 1
< 0.1%
3372 1
< 0.1%
3320 1
< 0.1%
3225 1
< 0.1%
3106 1
< 0.1%
3077 1
< 0.1%
3040 1
< 0.1%
3031 1
< 0.1%

답_건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct832
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean199.924
Minimum0
Maximum5602
Zeros622
Zeros (%)6.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T07:24:59.686946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q19
median103
Q3175
95-th percentile405.05
Maximum5602
Range5602
Interquartile range (IQR)166

Descriptive statistics

Standard deviation479.76999
Coefficient of variation (CV)2.3997619
Kurtosis25.290095
Mean199.924
Median Absolute Deviation (MAD)87
Skewness4.8949647
Sum1999240
Variance230179.25
MonotonicityNot monotonic
2024-01-10T07:24:59.808151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 622
 
6.2%
1 496
 
5.0%
2 338
 
3.4%
3 293
 
2.9%
4 226
 
2.3%
5 177
 
1.8%
6 126
 
1.3%
7 98
 
1.0%
9 95
 
0.9%
8 81
 
0.8%
Other values (822) 7448
74.5%
ValueCountFrequency (%)
0 622
6.2%
1 496
5.0%
2 338
3.4%
3 293
2.9%
4 226
 
2.3%
5 177
 
1.8%
6 126
 
1.3%
7 98
 
1.0%
8 81
 
0.8%
9 95
 
0.9%
ValueCountFrequency (%)
5602 1
< 0.1%
4232 1
< 0.1%
4096 1
< 0.1%
4061 1
< 0.1%
4051 1
< 0.1%
3982 1
< 0.1%
3973 1
< 0.1%
3966 1
< 0.1%
3907 1
< 0.1%
3864 1
< 0.1%

대지_건수
Real number (ℝ)

HIGH CORRELATION 

Distinct2126
Distinct (%)21.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean620.7771
Minimum1
Maximum14752
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T07:24:59.909316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile33
Q182
median160
Q3484
95-th percentile2616.1
Maximum14752
Range14751
Interquartile range (IQR)402

Descriptive statistics

Standard deviation1319.4815
Coefficient of variation (CV)2.1255319
Kurtosis20.292414
Mean620.7771
Median Absolute Deviation (MAD)100
Skewness4.1822622
Sum6207771
Variance1741031.5
MonotonicityNot monotonic
2024-01-10T07:25:00.017316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
60 56
 
0.6%
70 55
 
0.5%
75 55
 
0.5%
67 54
 
0.5%
66 51
 
0.5%
80 50
 
0.5%
79 50
 
0.5%
61 49
 
0.5%
106 49
 
0.5%
65 49
 
0.5%
Other values (2116) 9482
94.8%
ValueCountFrequency (%)
1 1
 
< 0.1%
2 1
 
< 0.1%
3 6
 
0.1%
4 7
 
0.1%
5 9
0.1%
6 4
 
< 0.1%
7 12
0.1%
8 19
0.2%
9 14
0.1%
10 14
0.1%
ValueCountFrequency (%)
14752 1
< 0.1%
12225 1
< 0.1%
11554 1
< 0.1%
11517 1
< 0.1%
11382 1
< 0.1%
11159 1
< 0.1%
10932 1
< 0.1%
10885 1
< 0.1%
10659 1
< 0.1%
10643 1
< 0.1%

임야_건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct803
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean135.9812
Minimum0
Maximum3803
Zeros1103
Zeros (%)11.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T07:25:00.124305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15
median50
Q3106
95-th percentile388.2
Maximum3803
Range3803
Interquartile range (IQR)101

Descriptive statistics

Standard deviation332.47324
Coefficient of variation (CV)2.4449942
Kurtosis22.590123
Mean135.9812
Median Absolute Deviation (MAD)46
Skewness4.6210338
Sum1359812
Variance110538.46
MonotonicityNot monotonic
2024-01-10T07:25:00.230236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1103
 
11.0%
1 543
 
5.4%
2 366
 
3.7%
3 218
 
2.2%
4 161
 
1.6%
5 119
 
1.2%
6 93
 
0.9%
47 92
 
0.9%
46 84
 
0.8%
7 84
 
0.8%
Other values (793) 7137
71.4%
ValueCountFrequency (%)
0 1103
11.0%
1 543
5.4%
2 366
 
3.7%
3 218
 
2.2%
4 161
 
1.6%
5 119
 
1.2%
6 93
 
0.9%
7 84
 
0.8%
8 70
 
0.7%
9 53
 
0.5%
ValueCountFrequency (%)
3803 1
< 0.1%
2886 1
< 0.1%
2705 1
< 0.1%
2644 1
< 0.1%
2597 1
< 0.1%
2590 1
< 0.1%
2551 1
< 0.1%
2527 1
< 0.1%
2507 1
< 0.1%
2496 1
< 0.1%

공장_건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct276
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.9137
Minimum0
Maximum1315
Zeros3160
Zeros (%)31.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T07:25:00.342633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q36
95-th percentile63
Maximum1315
Range1315
Interquartile range (IQR)6

Descriptive statistics

Standard deviation56.573408
Coefficient of variation (CV)4.0660218
Kurtosis218.68804
Mean13.9137
Median Absolute Deviation (MAD)2
Skewness12.428368
Sum139137
Variance3200.5505
MonotonicityNot monotonic
2024-01-10T07:25:00.451566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3160
31.6%
1 1553
15.5%
2 954
 
9.5%
3 725
 
7.2%
4 492
 
4.9%
5 381
 
3.8%
6 290
 
2.9%
7 215
 
2.1%
8 160
 
1.6%
9 152
 
1.5%
Other values (266) 1918
19.2%
ValueCountFrequency (%)
0 3160
31.6%
1 1553
15.5%
2 954
 
9.5%
3 725
 
7.2%
4 492
 
4.9%
5 381
 
3.8%
6 290
 
2.9%
7 215
 
2.1%
8 160
 
1.6%
9 152
 
1.5%
ValueCountFrequency (%)
1315 1
< 0.1%
1306 1
< 0.1%
1279 2
< 0.1%
1272 1
< 0.1%
1113 1
< 0.1%
1082 1
< 0.1%
1080 1
< 0.1%
1072 1
< 0.1%
1015 1
< 0.1%
824 1
< 0.1%

기타_건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct625
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean66.8681
Minimum0
Maximum1935
Zeros434
Zeros (%)4.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T07:25:00.557386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q16
median23
Q354
95-th percentile284.1
Maximum1935
Range1935
Interquartile range (IQR)48

Descriptive statistics

Standard deviation158.41116
Coefficient of variation (CV)2.3690094
Kurtosis31.659817
Mean66.8681
Median Absolute Deviation (MAD)19
Skewness5.1187467
Sum668681
Variance25094.096
MonotonicityNot monotonic
2024-01-10T07:25:00.667777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 447
 
4.5%
0 434
 
4.3%
2 402
 
4.0%
3 393
 
3.9%
4 329
 
3.3%
5 271
 
2.7%
6 245
 
2.5%
7 203
 
2.0%
18 184
 
1.8%
11 182
 
1.8%
Other values (615) 6910
69.1%
ValueCountFrequency (%)
0 434
4.3%
1 447
4.5%
2 402
4.0%
3 393
3.9%
4 329
3.3%
5 271
2.7%
6 245
2.5%
7 203
2.0%
8 179
1.8%
9 177
 
1.8%
ValueCountFrequency (%)
1935 1
< 0.1%
1784 1
< 0.1%
1716 1
< 0.1%
1681 1
< 0.1%
1672 1
< 0.1%
1622 1
< 0.1%
1614 1
< 0.1%
1609 1
< 0.1%
1608 1
< 0.1%
1510 1
< 0.1%

지역구분 레벨
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
8431 
2
989 
0
 
580

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row0
5th row1

Common Values

ValueCountFrequency (%)
1 8431
84.3%
2 989
 
9.9%
0 580
 
5.8%

Length

2024-01-10T07:25:00.768560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:25:00.845512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 8431
84.3%
2 989
 
9.9%
0 580
 
5.8%

Interactions

2024-01-10T07:24:56.879366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:49.229725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:49.997300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:50.884995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:51.701191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:52.499223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:53.333361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:54.291667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:55.076542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:56.009197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:56.965266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:49.315619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:50.078111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:50.970390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:51.795657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:52.580234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:53.412598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:54.366584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:55.177224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:56.083108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:57.064883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:49.388018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:50.168507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:51.042494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:51.886029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:52.652137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:53.488957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:54.439313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:55.274899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:56.154748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:57.169631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:49.465258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:50.265741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:51.127623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:51.975428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:52.729720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:53.570053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:54.516395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:55.378556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:56.229854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:57.264540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:49.537255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:50.358990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:51.207553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:52.044975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:52.800453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:53.640530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:54.590030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:55.480534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:56.319648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:57.343606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:49.616196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:50.455273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:51.293468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:52.119796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:52.876614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:53.712541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:54.677908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:55.582682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:56.420792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:57.416086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:49.686168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:50.549987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:51.380461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:52.191044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:52.952727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:53.780946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:54.754804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:55.679299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:56.518087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:57.498515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:49.763407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:50.647126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:51.466613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:52.265072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:53.057644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:53.854048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:54.830435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:55.767448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:56.618865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:57.580684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:49.840440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:50.737230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:51.544165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:52.344229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:53.158754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:53.928993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:54.908843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:55.850646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:56.726081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:57.661812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:49.915590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:50.807775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:51.621630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:52.419040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:53.254739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:53.999191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:54.983700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:55.925719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:24:56.799692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T07:25:00.903093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호지역코드지역명조사일자거래유형지목별합계_건수전_건수답_건수대지_건수임야_건수공장_건수기타_건수지역구분 레벨
번호1.0000.9950.9810.2070.0650.6500.5640.4370.6570.4420.2050.5520.867
지역코드0.9951.0001.0000.1010.0000.1940.0370.0330.2400.1060.1090.2130.522
지역명0.9811.0001.0000.1070.0000.6760.5970.6770.6610.6870.3440.5881.000
조사일자0.2070.1010.1071.0000.3670.1150.1700.0650.1270.1300.1340.2150.113
거래유형0.0650.0000.0000.3671.0000.2170.1520.1350.1720.1370.0980.1440.000
지목별합계_건수0.6500.1940.6760.1150.2171.0000.8680.7390.9390.7220.4360.8710.786
전_건수0.5640.0370.5970.1700.1520.8681.0000.7520.7470.7690.2730.8470.723
답_건수0.4370.0330.6770.0650.1350.7390.7521.0000.5630.8410.3300.6610.866
대지_건수0.6570.2400.6610.1270.1720.9390.7470.5631.0000.6040.4170.7790.722
임야_건수0.4420.1060.6870.1300.1370.7220.7690.8410.6041.0000.4950.7120.866
공장_건수0.2050.1090.3440.1340.0980.4360.2730.3300.4170.4951.0000.3100.458
기타_건수0.5520.2130.5880.2150.1440.8710.8470.6610.7790.7120.3101.0000.690
지역구분 레벨0.8670.5221.0000.1130.0000.7860.7230.8660.7220.8660.4580.6901.000
2024-01-10T07:25:01.008202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역명지역구분 레벨거래유형
지역명1.0000.9990.000
지역구분 레벨0.9991.0000.000
거래유형0.0000.0001.000
2024-01-10T07:25:01.085075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호지역코드조사일자지목별합계_건수전_건수답_건수대지_건수임야_건수공장_건수기타_건수지역명거래유형지역구분 레벨
번호1.0000.9980.030-0.546-0.198-0.235-0.610-0.241-0.554-0.4170.9010.0390.796
지역코드0.9981.000-0.021-0.549-0.199-0.236-0.616-0.242-0.559-0.4250.9990.0000.837
조사일자0.030-0.0211.0000.1530.1270.1130.1700.1500.1380.2250.0420.2270.069
지목별합계_건수-0.546-0.5490.1531.0000.7220.7000.8310.7060.6180.8040.3360.1310.670
전_건수-0.198-0.1990.1270.7221.0000.8850.3730.8950.3500.8090.2760.0910.586
답_건수-0.235-0.2360.1130.7000.8851.0000.3450.8510.3290.7630.2910.0860.587
대지_건수-0.610-0.6160.1700.8310.3730.3451.0000.3600.6080.5320.3230.1040.585
임야_건수-0.241-0.2420.1500.7060.8950.8510.3601.0000.3170.7990.2990.0880.586
공장_건수-0.554-0.5590.1380.6180.3500.3290.6080.3171.0000.5300.1210.0620.228
기타_건수-0.417-0.4250.2250.8040.8090.7630.5320.7990.5301.0000.2700.0870.544
지역명0.9010.9990.0420.3360.2760.2910.3230.2990.1210.2701.0000.0000.999
거래유형0.0390.0000.2270.1310.0910.0860.1040.0880.0620.0870.0001.0000.000
지역구분 레벨0.7960.8370.0690.6700.5860.5870.5850.5860.2280.5440.9990.0001.000

Missing values

2024-01-10T07:24:57.770431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T07:24:57.903878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

번호지역코드지역명조사일자거래유형지목별합계_건수전_건수답_건수대지_건수임야_건수공장_건수기타_건수지역구분 레벨
112711127244810예산군201912843668141192213111
8872887344770서천군20110236900680011
4718471944210서산시201109111291811394922720451
64764844000충남2022043942795312079971251071250
6477647844250계룡시20170822517106101
7637763844710금산군20160637711701041
4581458244200아산시20200621302246324236259102271
8880888144770서천군201110310411982021
7386738744710금산군200603215036652813081
112261122744810예산군20190583748687151313161
번호지역코드지역명조사일자거래유형지목별합계_건수전_건수답_건수대지_건수임야_건수공장_건수기타_건수지역구분 레벨
108791088044810예산군2006102262767154280331
8453845444760부여군20190824196518361465591
4574457544200아산시2020053103521973320361
113071130844810예산군20210321064247425211820991
5294529544210서산시2021121197925942685328041571
9003900444770서천군2016072336839975572201
3593359444180보령시2012123188351705321
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