Overview

Dataset statistics

Number of variables16
Number of observations10000
Missing cells21482
Missing cells (%)13.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 MiB
Average record size in memory151.0 B

Variable types

Numeric13
Categorical3

Dataset

Description한국부동산원(구.한국감정원)에서 제공하는 부동산 거래 통계를 조회할 수 있는 서비스로 충남의 거래원인별 면적 정보를 제공합니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/bigdata/collect/view.chungnam?menuCd=DOM_000000201001001000&apiIdx=2563

Alerts

지역명 is highly overall correlated with 번호 and 2 other fieldsHigh correlation
지역구분 레벨 is highly overall correlated with 번호 and 2 other fieldsHigh correlation
번호 is highly overall correlated with 지역코드 and 2 other fieldsHigh correlation
지역코드 is highly overall correlated with 번호 and 2 other fieldsHigh correlation
합계_면적 is highly overall correlated with 매매_면적 and 4 other fieldsHigh correlation
매매_면적 is highly overall correlated with 합계_면적 and 4 other fieldsHigh correlation
판결_면적 is highly overall correlated with 합계_면적 and 4 other fieldsHigh correlation
교환_면적 is highly overall correlated with 합계_면적 and 4 other fieldsHigh correlation
증여_면적 is highly overall correlated with 합계_면적 and 4 other fieldsHigh correlation
분양권전매_면적 is highly overall correlated with 기타소유권이전_면적High correlation
기타_면적 is highly overall correlated with 합계_면적 and 4 other fieldsHigh correlation
기타소유권이전_면적 is highly overall correlated with 분양권전매_면적High correlation
분양권_면적 has 1638 (16.4%) missing valuesMissing
분양권전매_면적 has 5958 (59.6%) missing valuesMissing
분양권검인_면적 has 5958 (59.6%) missing valuesMissing
기타_면적 has 1638 (16.4%) missing valuesMissing
기타소유권이전_면적 has 6290 (62.9%) missing valuesMissing
교환_면적 is highly skewed (γ1 = 38.50083954)Skewed
분양권_면적 is highly skewed (γ1 = 46.24188804)Skewed
기타_면적 is highly skewed (γ1 = 26.76781955)Skewed
번호 has unique valuesUnique
판결_면적 has 4455 (44.5%) zerosZeros
교환_면적 has 6128 (61.3%) zerosZeros
증여_면적 has 399 (4.0%) zerosZeros
분양권_면적 has 2973 (29.7%) zerosZeros
분양권전매_면적 has 2934 (29.3%) zerosZeros
분양권검인_면적 has 3862 (38.6%) zerosZeros
기타_면적 has 2236 (22.4%) zerosZeros
기타소유권이전_면적 has 2358 (23.6%) zerosZeros

Reproduction

Analysis started2024-01-09 21:08:09.911432
Analysis finished2024-01-09 21:08:31.679072
Duration21.77 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%
Mean8035.9675
Minimum2
Maximum16069
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T06:08:31.745390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile827.95
Q14045.75
median7988.5
Q312075.5
95-th percentile15249.05
Maximum16069
Range16067
Interquartile range (IQR)8029.75

Descriptive statistics

Standard deviation4623.1877
Coefficient of variation (CV)0.5753119
Kurtosis-1.197614
Mean8035.9675
Median Absolute Deviation (MAD)4016.5
Skewness0.0041797175
Sum80359675
Variance21373865
MonotonicityNot monotonic
2024-01-10T06:08:31.880362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5438 1
 
< 0.1%
8540 1
 
< 0.1%
15897 1
 
< 0.1%
5360 1
 
< 0.1%
10383 1
 
< 0.1%
6252 1
 
< 0.1%
13117 1
 
< 0.1%
2379 1
 
< 0.1%
8890 1
 
< 0.1%
10741 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
8 1
< 0.1%
11 1
< 0.1%
12 1
< 0.1%
13 1
< 0.1%
16 1
< 0.1%
17 1
< 0.1%
18 1
< 0.1%
ValueCountFrequency (%)
16069 1
< 0.1%
16068 1
< 0.1%
16065 1
< 0.1%
16062 1
< 0.1%
16061 1
< 0.1%
16059 1
< 0.1%
16057 1
< 0.1%
16056 1
< 0.1%
16055 1
< 0.1%
16054 1
< 0.1%

지역코드
Real number (ℝ)

HIGH CORRELATION 

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44387.547
Minimum44000
Maximum44810
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T06:08:31.991661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum44000
5-th percentile44000
Q144150
median44230
Q344760
95-th percentile44810
Maximum44810
Range810
Interquartile range (IQR)610

Descriptive statistics

Standard deviation296.11026
Coefficient of variation (CV)0.0066710209
Kurtosis-1.5821472
Mean44387.547
Median Absolute Deviation (MAD)99
Skewness0.4690314
Sum4.4387547 × 108
Variance87681.284
MonotonicityNot monotonic
2024-01-10T06:08:32.091659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
44180 638
 
6.4%
44150 631
 
6.3%
44790 630
 
6.3%
44250 628
 
6.3%
44200 622
 
6.2%
44210 621
 
6.2%
44770 620
 
6.2%
44760 614
 
6.1%
44800 612
 
6.1%
44230 609
 
6.1%
Other values (7) 3775
37.8%
ValueCountFrequency (%)
44000 607
6.1%
44130 606
6.1%
44131 508
5.1%
44133 532
5.3%
44150 631
6.3%
44180 638
6.4%
44200 622
6.2%
44210 621
6.2%
44230 609
6.1%
44250 628
6.3%
ValueCountFrequency (%)
44810 537
5.4%
44800 612
6.1%
44790 630
6.3%
44770 620
6.2%
44760 614
6.1%
44710 604
6.0%
44270 381
3.8%
44250 628
6.3%
44230 609
6.1%
44210 621
6.2%

지역명
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
보령시
 
638
공주시
 
631
청양군
 
630
계룡시
 
628
아산시
 
622
Other values (12)
6851 

Length

Max length3
Median length3
Mean length2.9393
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row보령시
2nd row천안시
3rd row충남
4th row금산군
5th row홍성군

Common Values

ValueCountFrequency (%)
보령시 638
 
6.4%
공주시 631
 
6.3%
청양군 630
 
6.3%
계룡시 628
 
6.3%
아산시 622
 
6.2%
서산시 621
 
6.2%
서천군 620
 
6.2%
부여군 614
 
6.1%
홍성군 612
 
6.1%
논산시 609
 
6.1%
Other values (7) 3775
37.8%

Length

2024-01-10T06:08:32.208842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
보령시 638
 
6.4%
공주시 631
 
6.3%
청양군 630
 
6.3%
계룡시 628
 
6.3%
아산시 622
 
6.2%
서산시 621
 
6.2%
서천군 620
 
6.2%
부여군 614
 
6.1%
홍성군 612
 
6.1%
논산시 609
 
6.1%
Other values (7) 3775
37.8%

조사분기
Real number (ℝ)

Distinct198
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean201405.4
Minimum200601
Maximum202206
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T06:08:32.311868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum200601
5-th percentile200612
Q1201007
median201407
Q3201806
95-th percentile202108
Maximum202206
Range1605
Interquartile range (IQR)799

Descriptive statistics

Standard deviation466.5859
Coefficient of variation (CV)0.0023166504
Kurtosis-1.1531614
Mean201405.4
Median Absolute Deviation (MAD)400
Skewness-0.042911639
Sum2.014054 × 109
Variance217702.4
MonotonicityNot monotonic
2024-01-10T06:08:32.433422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
201203 66
 
0.7%
201610 65
 
0.7%
202011 63
 
0.6%
201804 63
 
0.6%
201712 63
 
0.6%
202003 62
 
0.6%
201309 61
 
0.6%
201311 60
 
0.6%
202006 60
 
0.6%
201707 60
 
0.6%
Other values (188) 9377
93.8%
ValueCountFrequency (%)
200601 45
0.4%
200602 35
0.4%
200603 45
0.4%
200604 41
0.4%
200605 45
0.4%
200606 45
0.4%
200607 42
0.4%
200608 39
0.4%
200609 44
0.4%
200610 43
0.4%
ValueCountFrequency (%)
202206 59
0.6%
202205 46
0.5%
202204 50
0.5%
202203 46
0.5%
202202 47
0.5%
202201 51
0.5%
202112 42
0.4%
202111 54
0.5%
202110 54
0.5%
202109 50
0.5%

거래유형
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3
2033 
5
2010 
1
2006 
4
1980 
2
1971 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row5
3rd row3
4th row1
5th row1

Common Values

ValueCountFrequency (%)
3 2033
20.3%
5 2010
20.1%
1 2006
20.1%
4 1980
19.8%
2 1971
19.7%

Length

2024-01-10T06:08:32.553550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:08:32.648443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 2033
20.3%
5 2010
20.1%
1 2006
20.1%
4 1980
19.8%
2 1971
19.7%

합계_면적
Real number (ℝ)

HIGH CORRELATION 

Distinct9850
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean812506.4
Minimum0
Maximum43982861
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T06:08:32.775424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2073.6874
Q111453.397
median79666.624
Q3767774.75
95-th percentile1986552.8
Maximum43982861
Range43982861
Interquartile range (IQR)756321.35

Descriptive statistics

Standard deviation2620134.4
Coefficient of variation (CV)3.2247554
Kurtosis51.754774
Mean812506.4
Median Absolute Deviation (MAD)76933.164
Skewness6.6474001
Sum8.125064 × 109
Variance6.8651042 × 1012
MonotonicityNot monotonic
2024-01-10T06:08:32.905330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
60.0 4
 
< 0.1%
1716.0 4
 
< 0.1%
1082.0 4
 
< 0.1%
840.0 3
 
< 0.1%
4547.0 3
 
< 0.1%
5596.0 3
 
< 0.1%
4929.0 3
 
< 0.1%
6981.0 3
 
< 0.1%
5916.0 3
 
< 0.1%
1842.0 3
 
< 0.1%
Other values (9840) 9967
99.7%
ValueCountFrequency (%)
0.0 1
 
< 0.1%
29.82 1
 
< 0.1%
49.95 1
 
< 0.1%
50.0 1
 
< 0.1%
59.64 1
 
< 0.1%
60.0 4
< 0.1%
72.0 1
 
< 0.1%
84.0 1
 
< 0.1%
85.0 1
 
< 0.1%
86.0 1
 
< 0.1%
ValueCountFrequency (%)
43982861.0 1
< 0.1%
34722814.0 1
< 0.1%
31692484.0 1
< 0.1%
31096804.0 1
< 0.1%
30803717.0 1
< 0.1%
30782343.0 1
< 0.1%
30049933.0 1
< 0.1%
28996216.0 1
< 0.1%
27028567.124984 1
< 0.1%
26446324.0 1
< 0.1%

매매_면적
Real number (ℝ)

HIGH CORRELATION 

Distinct9807
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean511498
Minimum0
Maximum20606431
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T06:08:33.034328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1453.9574
Q18179.4482
median50644.978
Q3484996.25
95-th percentile1290352.7
Maximum20606431
Range20606431
Interquartile range (IQR)476816.8

Descriptive statistics

Standard deviation1619344.7
Coefficient of variation (CV)3.1658868
Kurtosis45.227376
Mean511498
Median Absolute Deviation (MAD)48734.084
Skewness6.3795444
Sum5.11498 × 109
Variance2.6222774 × 1012
MonotonicityNot monotonic
2024-01-10T06:08:33.167805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
60.0 5
 
0.1%
1315.0 3
 
< 0.1%
1378.0 3
 
< 0.1%
3866.0 3
 
< 0.1%
5069.0 3
 
< 0.1%
889.0 3
 
< 0.1%
3427.0 3
 
< 0.1%
1551.0 3
 
< 0.1%
1093.0 3
 
< 0.1%
3722.0 3
 
< 0.1%
Other values (9797) 9968
99.7%
ValueCountFrequency (%)
0.0 2
 
< 0.1%
49.95 1
 
< 0.1%
50.0 1
 
< 0.1%
59.0 1
 
< 0.1%
59.64 1
 
< 0.1%
60.0 5
0.1%
72.0 1
 
< 0.1%
84.0 1
 
< 0.1%
85.0 1
 
< 0.1%
86.0 1
 
< 0.1%
ValueCountFrequency (%)
20606431.0 1
< 0.1%
20148900.0 1
< 0.1%
19813229.0 1
< 0.1%
17203769.0 1
< 0.1%
16871383.170772 1
< 0.1%
16799733.0 1
< 0.1%
16598495.0 1
< 0.1%
16556560.979454 1
< 0.1%
16422377.0 1
< 0.1%
16407214.0 1
< 0.1%

판결_면적
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct3740
Distinct (%)37.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25073.579
Minimum0
Maximum3351009
Zeros4455
Zeros (%)44.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T06:08:33.292642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median73
Q33595
95-th percentile99306.75
Maximum3351009
Range3351009
Interquartile range (IQR)3595

Descriptive statistics

Standard deviation116015.84
Coefficient of variation (CV)4.6270158
Kurtosis140.54766
Mean25073.579
Median Absolute Deviation (MAD)73
Skewness9.6337895
Sum2.5073579 × 108
Variance1.3459676 × 1010
MonotonicityNot monotonic
2024-01-10T06:08:33.421098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 4455
44.5%
85.0 93
 
0.9%
60.0 34
 
0.3%
42.0 24
 
0.2%
109.0 20
 
0.2%
59.0 18
 
0.2%
103.0 14
 
0.1%
50.0 12
 
0.1%
72.0 12
 
0.1%
30.0 12
 
0.1%
Other values (3730) 5306
53.1%
ValueCountFrequency (%)
0.0 4455
44.5%
1.0 8
 
0.1%
1.458 1
 
< 0.1%
2.0 2
 
< 0.1%
2.232824 1
 
< 0.1%
4.0 5
 
0.1%
5.470714 2
 
< 0.1%
7.0 1
 
< 0.1%
8.0 1
 
< 0.1%
8.816667 1
 
< 0.1%
ValueCountFrequency (%)
3351009.0 1
< 0.1%
2153558.0 1
< 0.1%
1911763.664284 1
< 0.1%
1639298.610275 1
< 0.1%
1573535.6 1
< 0.1%
1545967.89335 1
< 0.1%
1545960.0 1
< 0.1%
1541715.0 1
< 0.1%
1433148.0 1
< 0.1%
1362635.0 1
< 0.1%

교환_면적
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct2307
Distinct (%)23.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5547.7999
Minimum0
Maximum3603684.5
Zeros6128
Zeros (%)61.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T06:08:33.552106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3655
95-th percentile15467
Maximum3603684.5
Range3603684.5
Interquartile range (IQR)655

Descriptive statistics

Standard deviation53523.475
Coefficient of variation (CV)9.6476937
Kurtosis2189.5649
Mean5547.7999
Median Absolute Deviation (MAD)0
Skewness38.50084
Sum55477999
Variance2.8647623 × 109
MonotonicityNot monotonic
2024-01-10T06:08:33.722934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 6128
61.3%
85.0 25
 
0.2%
50.0 18
 
0.2%
66.0 12
 
0.1%
48.0 12
 
0.1%
178.0 11
 
0.1%
120.0 9
 
0.1%
58.0 8
 
0.1%
76.0 8
 
0.1%
82.0 8
 
0.1%
Other values (2297) 3761
37.6%
ValueCountFrequency (%)
0.0 6128
61.3%
2.0 3
 
< 0.1%
4.0 2
 
< 0.1%
5.0 2
 
< 0.1%
6.0 1
 
< 0.1%
10.0 1
 
< 0.1%
11.766667 1
 
< 0.1%
12.0 4
 
< 0.1%
14.0 7
 
0.1%
16.0 3
 
< 0.1%
ValueCountFrequency (%)
3603684.45872 1
< 0.1%
1240543.0 1
< 0.1%
1240499.0 1
< 0.1%
1112307.314184 1
< 0.1%
1105489.175284 1
< 0.1%
980705.0 2
< 0.1%
883060.0 1
< 0.1%
882405.0 1
< 0.1%
834921.0 1
< 0.1%
694607.0 1
< 0.1%

증여_면적
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct8181
Distinct (%)81.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean160647.49
Minimum0
Maximum8550698
Zeros399
Zeros (%)4.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T06:08:33.855301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile46
Q1871
median3400.8395
Q3148183.96
95-th percentile436678.45
Maximum8550698
Range8550698
Interquartile range (IQR)147312.96

Descriptive statistics

Standard deviation545452.57
Coefficient of variation (CV)3.3953383
Kurtosis53.917257
Mean160647.49
Median Absolute Deviation (MAD)3317.1952
Skewness6.6976633
Sum1.6064749 × 109
Variance2.975185 × 1011
MonotonicityNot monotonic
2024-01-10T06:08:33.994802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 399
 
4.0%
85.0 49
 
0.5%
60.0 36
 
0.4%
58.0 16
 
0.2%
40.0 15
 
0.1%
42.0 13
 
0.1%
170.0 11
 
0.1%
118.0 10
 
0.1%
46.0 9
 
0.1%
160.0 9
 
0.1%
Other values (8171) 9433
94.3%
ValueCountFrequency (%)
0.0 399
4.0%
1.0 1
 
< 0.1%
6.0 1
 
< 0.1%
9.0 1
 
< 0.1%
13.0 1
 
< 0.1%
16.551 1
 
< 0.1%
20.0 1
 
< 0.1%
20.56 1
 
< 0.1%
23.52 1
 
< 0.1%
25.0 1
 
< 0.1%
ValueCountFrequency (%)
8550698.0 1
< 0.1%
8102899.0 1
< 0.1%
7539898.0 1
< 0.1%
7418123.0 1
< 0.1%
6937775.735187 1
< 0.1%
6612940.437662 1
< 0.1%
6320746.0 1
< 0.1%
5853216.38689 1
< 0.1%
5785843.0 1
< 0.1%
5750748.0 1
< 0.1%

분양권_면적
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct4191
Distinct (%)50.1%
Missing1638
Missing (%)16.4%
Infinite0
Infinite (%)0.0%
Mean23546.668
Minimum0
Maximum11298213
Zeros2973
Zeros (%)29.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T06:08:34.147748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median719
Q39825
95-th percentile103152.43
Maximum11298213
Range11298213
Interquartile range (IQR)9825

Descriptive statistics

Standard deviation160063.61
Coefficient of variation (CV)6.7977179
Kurtosis3012.3792
Mean23546.668
Median Absolute Deviation (MAD)719
Skewness46.241888
Sum1.9689724 × 108
Variance2.5620359 × 1010
MonotonicityNot monotonic
2024-01-10T06:08:34.298090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 2973
29.7%
85.0 64
 
0.6%
170.0 27
 
0.3%
255.0 19
 
0.2%
425.0 14
 
0.1%
340.0 13
 
0.1%
59.0 10
 
0.1%
60.0 10
 
0.1%
595.0 9
 
0.1%
40.0 9
 
0.1%
Other values (4181) 5214
52.1%
(Missing) 1638
 
16.4%
ValueCountFrequency (%)
0.0 2973
29.7%
1.0 2
 
< 0.1%
2.0 1
 
< 0.1%
6.072455 1
 
< 0.1%
6.0725 2
 
< 0.1%
8.0 1
 
< 0.1%
9.0 1
 
< 0.1%
10.0 1
 
< 0.1%
11.06 1
 
< 0.1%
20.1055 1
 
< 0.1%
ValueCountFrequency (%)
11298213.0 1
< 0.1%
3548867.0 1
< 0.1%
2982735.0 1
< 0.1%
2378265.0 1
< 0.1%
2282561.0 1
< 0.1%
2216950.0 1
< 0.1%
1989903.0 1
< 0.1%
1924808.0 1
< 0.1%
1642413.0 1
< 0.1%
1633621.0 1
< 0.1%

분양권전매_면적
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct816
Distinct (%)20.2%
Missing5958
Missing (%)59.6%
Infinite0
Infinite (%)0.0%
Mean2119.8672
Minimum0
Maximum92034.014
Zeros2934
Zeros (%)29.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T06:08:34.455616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3160.41563
95-th percentile13167.602
Maximum92034.014
Range92034.014
Interquartile range (IQR)160.41563

Descriptive statistics

Standard deviation7244.8058
Coefficient of variation (CV)3.4175754
Kurtosis33.344181
Mean2119.8672
Median Absolute Deviation (MAD)0
Skewness5.2309844
Sum8568503.1
Variance52487211
MonotonicityNot monotonic
2024-01-10T06:08:34.599837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 2934
29.3%
84.8885 7
 
0.1%
169.9734 4
 
< 0.1%
84.9342 4
 
< 0.1%
81.9043 4
 
< 0.1%
169.777 4
 
< 0.1%
84.9867 4
 
< 0.1%
144.9133 3
 
< 0.1%
72.6072 3
 
< 0.1%
534.3093 3
 
< 0.1%
Other values (806) 1072
 
10.7%
(Missing) 5958
59.6%
ValueCountFrequency (%)
0.0 2934
29.3%
59.849 1
 
< 0.1%
59.9297 1
 
< 0.1%
72.6072 3
 
< 0.1%
74.2745 2
 
< 0.1%
74.912 2
 
< 0.1%
74.9551 2
 
< 0.1%
75.9943 2
 
< 0.1%
76.7574 1
 
< 0.1%
76.9183 1
 
< 0.1%
ValueCountFrequency (%)
92034.0139 1
< 0.1%
72555.4638 1
< 0.1%
72209.5563 1
< 0.1%
72124.5843 1
< 0.1%
70611.4498 1
< 0.1%
66344.35705 1
< 0.1%
60331.4299 1
< 0.1%
60246.4994 1
< 0.1%
54252.0245 1
< 0.1%
53475.2748 1
< 0.1%

분양권검인_면적
Real number (ℝ)

MISSING  ZEROS 

Distinct155
Distinct (%)3.8%
Missing5958
Missing (%)59.6%
Infinite0
Infinite (%)0.0%
Mean947.491
Minimum0
Maximum141380.86
Zeros3862
Zeros (%)38.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T06:08:34.732972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum141380.86
Range141380.86
Interquartile range (IQR)0

Descriptive statistics

Standard deviation8282.3195
Coefficient of variation (CV)8.7413174
Kurtosis136.25922
Mean947.491
Median Absolute Deviation (MAD)0
Skewness11.140621
Sum3829758.6
Variance68596817
MonotonicityNot monotonic
2024-01-10T06:08:34.873781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 3862
38.6%
85.0 3
 
< 0.1%
59.532 2
 
< 0.1%
59.6391 2
 
< 0.1%
144.7259 2
 
< 0.1%
5901.0 2
 
< 0.1%
2200.0 2
 
< 0.1%
6191.03565 2
 
< 0.1%
84.9983 2
 
< 0.1%
1042.0942 2
 
< 0.1%
Other values (145) 161
 
1.6%
(Missing) 5958
59.6%
ValueCountFrequency (%)
0.0 3862
38.6%
59.532 2
 
< 0.1%
59.6391 2
 
< 0.1%
59.9727 1
 
< 0.1%
62.9845 1
 
< 0.1%
65.71 1
 
< 0.1%
72.1396 1
 
< 0.1%
72.8334 2
 
< 0.1%
84.677 1
 
< 0.1%
84.9983 2
 
< 0.1%
ValueCountFrequency (%)
141380.85626 1
< 0.1%
139951.59996 1
< 0.1%
113334.790002 1
< 0.1%
111612.10375 1
< 0.1%
111233.156 1
< 0.1%
108553.27505 1
< 0.1%
104353.0 1
< 0.1%
103374.846514 1
< 0.1%
103067.69871 1
< 0.1%
102990.47145 1
< 0.1%

기타_면적
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct4731
Distinct (%)56.6%
Missing1638
Missing (%)16.4%
Infinite0
Infinite (%)0.0%
Mean102882.9
Minimum0
Maximum33755657
Zeros2236
Zeros (%)22.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T06:08:35.023929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1906.5
Q339131.985
95-th percentile368020.36
Maximum33755657
Range33755657
Interquartile range (IQR)39131.985

Descriptive statistics

Standard deviation615652.2
Coefficient of variation (CV)5.9840091
Kurtosis1180.0893
Mean102882.9
Median Absolute Deviation (MAD)1906.5
Skewness26.76782
Sum8.6030679 × 108
Variance3.7902763 × 1011
MonotonicityNot monotonic
2024-01-10T06:08:35.202430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 2236
 
22.4%
85.0 75
 
0.8%
60.0 30
 
0.3%
50.0 27
 
0.3%
56.0 20
 
0.2%
42.0 16
 
0.2%
120.0 15
 
0.1%
59.0 15
 
0.1%
170.0 15
 
0.1%
84.0 13
 
0.1%
Other values (4721) 5900
59.0%
(Missing) 1638
 
16.4%
ValueCountFrequency (%)
0.0 2236
22.4%
2.0 2
 
< 0.1%
3.0 1
 
< 0.1%
6.0 2
 
< 0.1%
8.0 1
 
< 0.1%
9.0 1
 
< 0.1%
10.0 2
 
< 0.1%
12.0 1
 
< 0.1%
12.970667 1
 
< 0.1%
14.0 1
 
< 0.1%
ValueCountFrequency (%)
33755657.0 1
< 0.1%
12974026.0 1
< 0.1%
12957763.0 1
< 0.1%
12015636.0 1
< 0.1%
11745207.0 1
< 0.1%
10215551.0 1
< 0.1%
9374657.0 1
< 0.1%
9096429.0 1
< 0.1%
7756534.0 1
< 0.1%
7120547.0 1
< 0.1%

기타소유권이전_면적
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct1236
Distinct (%)33.3%
Missing6290
Missing (%)62.9%
Infinite0
Infinite (%)0.0%
Mean8523.6821
Minimum0
Maximum354653.76
Zeros2358
Zeros (%)23.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T06:08:35.592928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31041.6712
95-th percentile56332.409
Maximum354653.76
Range354653.76
Interquartile range (IQR)1041.6712

Descriptive statistics

Standard deviation29494.159
Coefficient of variation (CV)3.4602603
Kurtosis32.817114
Mean8523.6821
Median Absolute Deviation (MAD)0
Skewness5.2287647
Sum31622861
Variance8.6990539 × 108
MonotonicityNot monotonic
2024-01-10T06:08:35.705621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 2358
 
23.6%
84.9873 3
 
< 0.1%
1355.5048 2
 
< 0.1%
1313.5904 2
 
< 0.1%
84.855 2
 
< 0.1%
837.2446 2
 
< 0.1%
254.982 2
 
< 0.1%
6191.03565 2
 
< 0.1%
2200.0 2
 
< 0.1%
144.7259 2
 
< 0.1%
Other values (1226) 1333
 
13.3%
(Missing) 6290
62.9%
ValueCountFrequency (%)
0.0 2358
23.6%
10.0 1
 
< 0.1%
19.8 1
 
< 0.1%
22.0 1
 
< 0.1%
37.59 1
 
< 0.1%
38.439 1
 
< 0.1%
42.42365 1
 
< 0.1%
42.475 2
 
< 0.1%
46.2 1
 
< 0.1%
46.68 1
 
< 0.1%
ValueCountFrequency (%)
354653.76497 1
< 0.1%
294609.9832 1
< 0.1%
290666.897 1
< 0.1%
274606.68425 1
< 0.1%
261376.67405 1
< 0.1%
255989.67365 1
< 0.1%
251988.211266 1
< 0.1%
249624.0106 1
< 0.1%
231392.86525 1
< 0.1%
226758.680089 1
< 0.1%

지역구분 레벨
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
8353 
2
1040 
0
 
607

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 8353
83.5%
2 1040
 
10.4%
0 607
 
6.1%

Length

2024-01-10T06:08:35.820219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:08:35.897382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 8353
83.5%
2 1040
 
10.4%
0 607
 
6.1%

Interactions

2024-01-10T06:08:29.619079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:12.840240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:14.437278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:15.921174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:17.288662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:18.667406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:20.146153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:21.428770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:22.704849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:24.187642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:25.584304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:27.037897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:28.263968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:29.723538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:12.947711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:14.552548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:16.016371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:17.416756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:18.772628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:20.236304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:21.521452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:22.810313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:24.312986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:25.684403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:27.147686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:28.362171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:29.816175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:13.063385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:14.689213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:16.120044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:17.533912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:18.876066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:20.335259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:21.617709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:22.920383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:24.413842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:25.792828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:27.247822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:28.464272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:29.918137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:13.180033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:14.820762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:16.237121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:17.650024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:18.971720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:20.433317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:21.713348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:23.033832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:24.526915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:25.889229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:27.333967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:28.595846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:30.007540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:13.281287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:14.916912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:16.338597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:17.738798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:19.061427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:20.520032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:21.800191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:23.125911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:24.615880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:25.978955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:27.426390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:28.693983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:30.129408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:13.375519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:15.029964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:16.440061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:17.833007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:19.143975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:20.615916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:21.901958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:23.218514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:24.711175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:26.332755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:27.516217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:28.782308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:30.237743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:13.479909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:15.136271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:16.553809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:17.940934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:19.237417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:20.716189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:22.015964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:23.316467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:24.830915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:26.417490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:27.617876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:28.881212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:30.338172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:13.578942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:15.253729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:16.669974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:18.049811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:19.331695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:20.831021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:22.117646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:23.460276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:24.944697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:26.501585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:27.710740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:28.994540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:30.447790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:13.947546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:15.374099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:16.760088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:18.155365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:19.426006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:20.928558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:22.221612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:23.576659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:25.035954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:26.586371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:27.801524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:29.084048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:30.541674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:14.038345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:15.504613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:16.847905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:18.251302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:19.526042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:21.022520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:22.322508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:23.686249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:25.133522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:26.674544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:27.892104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:29.184524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:30.626633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:14.136705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:15.621514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:16.930097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:18.341249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:19.611206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:21.118510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:22.409720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:23.790756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:25.259362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:26.746949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:27.972017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:29.304597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:30.743630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:14.235199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:15.721854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:17.034369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:18.461340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:19.703888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:21.236703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:22.507962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:23.926266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:25.357922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:26.843299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:28.067112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:29.411806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:30.829417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:14.330982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:15.816778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:17.167096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:18.567654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:19.786711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:21.334155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:22.595004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:24.036669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:25.475202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:26.942254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:28.169104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:08:29.514439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T06:08:35.966653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호지역코드지역명조사분기거래유형합계_면적매매_면적판결_면적교환_면적증여_면적분양권_면적분양권전매_면적분양권검인_면적기타_면적기타소유권이전_면적지역구분 레벨
번호1.0000.9910.9770.2260.0680.3500.4610.2550.0990.4590.1100.3780.1560.1660.5010.848
지역코드0.9911.0001.0000.1150.0000.0000.0420.0370.0210.0710.0210.2080.0780.0000.3240.514
지역명0.9771.0001.0000.1450.0000.4830.4700.3620.1060.4680.0740.4560.1980.1750.4381.000
조사분기0.2260.1150.1451.0000.0000.0650.1250.0240.0670.0810.0650.0500.1620.0920.1010.129
거래유형0.0680.0000.0000.0001.0000.1750.2500.1390.0610.2440.0670.2730.1190.0680.3480.000
합계_면적0.3500.0000.4830.0650.1751.0000.8470.5890.2640.7780.4380.0000.0000.8080.0000.730
매매_면적0.4610.0420.4700.1250.2500.8471.0000.5750.3310.8440.1380.0000.0000.6480.0000.590
판결_면적0.2550.0370.3620.0240.1390.5890.5751.0000.2600.5760.1620.0000.0000.3260.0000.429
교환_면적0.0990.0210.1060.0670.0610.2640.3310.2601.0000.3190.0000.0000.0000.0600.0000.111
증여_면적0.4590.0710.4680.0810.2440.7780.8440.5760.3191.0000.5140.0000.0000.8010.0000.588
분양권_면적0.1100.0210.0740.0650.0670.4380.1380.1620.0000.5141.000NaNNaN0.556NaN0.057
분양권전매_면적0.3780.2080.4560.0500.2730.0000.0000.0000.0000.000NaN1.0000.738NaN0.6490.620
분양권검인_면적0.1560.0780.1980.1620.1190.0000.0000.0000.0000.000NaN0.7381.000NaN0.4420.279
기타_면적0.1660.0000.1750.0920.0680.8080.6480.3260.0600.8010.556NaNNaN1.000NaN0.178
기타소유권이전_면적0.5010.3240.4380.1010.3480.0000.0000.0000.0000.000NaN0.6490.442NaN1.0000.508
지역구분 레벨0.8480.5141.0000.1290.0000.7300.5900.4290.1110.5880.0570.6200.2790.1780.5081.000
2024-01-10T06:08:36.104286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역명지역구분 레벨거래유형
지역명1.0000.9990.000
지역구분 레벨0.9991.0000.000
거래유형0.0000.0001.000
2024-01-10T06:08:36.201335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호지역코드조사분기합계_면적매매_면적판결_면적교환_면적증여_면적분양권_면적분양권전매_면적분양권검인_면적기타_면적기타소유권이전_면적지역명거래유형지역구분 레벨
번호1.0000.9980.001-0.339-0.353-0.297-0.197-0.222-0.478-0.254-0.079-0.243-0.1970.8920.0280.765
지역코드0.9981.000-0.040-0.336-0.350-0.294-0.196-0.220-0.485-0.251-0.066-0.248-0.1930.9990.0000.833
조사분기0.001-0.0401.0000.0650.0660.0480.0860.0780.174-0.044-0.3210.203-0.1010.0570.0000.079
합계_면적-0.339-0.3360.0651.0000.9850.7730.7300.9230.282-0.253-0.1170.861-0.3330.2150.1020.435
매매_면적-0.353-0.3500.0660.9851.0000.7620.7280.9060.252-0.286-0.1270.832-0.3750.2030.1060.433
판결_면적-0.297-0.2940.0480.7730.7621.0000.6390.7480.237-0.236-0.1020.716-0.3020.1600.0850.303
교환_면적-0.197-0.1960.0860.7300.7280.6391.0000.7140.160-0.325-0.1280.689-0.3940.0540.0230.083
증여_면적-0.222-0.2200.0780.9230.9060.7480.7141.0000.176-0.358-0.1630.822-0.4390.2020.1040.432
분양권_면적-0.478-0.4850.1740.2820.2520.2370.1600.1761.000NaNNaN0.228NaN0.0380.0250.042
분양권전매_면적-0.254-0.251-0.044-0.253-0.286-0.236-0.325-0.358NaN1.0000.324NaN0.8690.2000.1610.341
분양권검인_면적-0.079-0.066-0.321-0.117-0.127-0.102-0.128-0.163NaN0.3241.000NaN0.2940.0800.0680.127
기타_면적-0.243-0.2480.2030.8610.8320.7160.6890.8220.228NaNNaN1.000NaN0.0910.0250.136
기타소유권이전_면적-0.197-0.193-0.101-0.333-0.375-0.302-0.394-0.439NaN0.8690.294NaN1.0000.1860.1510.354
지역명0.8920.9990.0570.2150.2030.1600.0540.2020.0380.2000.0800.0910.1861.0000.0000.999
거래유형0.0280.0000.0000.1020.1060.0850.0230.1040.0250.1610.0680.0250.1510.0001.0000.000
지역구분 레벨0.7650.8330.0790.4350.4330.3030.0830.4320.0420.3410.1270.1360.3540.9990.0001.000

Missing values

2024-01-10T06:08:30.967539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T06:08:31.177577image/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.
2024-01-10T06:08:31.607929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

번호지역코드지역명조사분기거래유형합계_면적매매_면적판결_면적교환_면적증여_면적분양권_면적분양권전매_면적분양권검인_면적기타_면적기타소유권이전_면적지역구분 레벨
5437543844180보령시20170411849719.221041717064.274820809.95250.01080134.5542711565.0980.00.030145.341470.01
1525152644130천안시201206593745.082224.085.00.01500.09192.0<NA><NA>744.0<NA>1
63163244000충남2017053698539.463778385783.5803905.466643.342008.501863257513.0659850.00.011685.549630.00
104661046744710금산군20080611002638.0845469.03301.0178.0153690.00.0<NA><NA>0.0<NA>1
144151441644800홍성군2009111666845.0381847.0435.07637.0259463.0832.0<NA><NA>16631.0<NA>1
7097709844210서산시201407425163.020083.066.00.02101.02382.0<NA><NA>531.0<NA>1
82382444000충남201909211798287.9244037981682.09067192835.6526454474.5870162200749.929069426800.49580.00.0941745.1692080.00
9122912344250계룡시20120354825.04825.00.00.00.00.0<NA><NA>0.0<NA>1
3414341544133서북구2018012666741.999628550857.351416159.03482.074632.285840.00.00.015771.3682280.02
155151551644810예산군201304411550.09115.0107.00.0768.01560.0<NA><NA>0.0<NA>1
번호지역코드지역명조사분기거래유형합계_면적매매_면적판결_면적교환_면적증여_면적분양권_면적분양권전매_면적분양권검인_면적기타_면적기타소유권이전_면적지역구분 레벨
147381473944800홍성군2014052736175.0462495.03596.0107.0143026.0112535.0<NA><NA>14416.0<NA>1
2659266044131동남구2019101683201.406264489987.7368526.45199126473.90577288.74197324135.77680.00.064788.79370.02
116021160344760부여군200804316313.014780.072.00.01461.00.0<NA><NA>0.0<NA>1
7152715344210서산시201111563000.010851.00.00.01799.050350.0<NA><NA>0.0<NA>1
132231322444790청양군201202560.060.00.00.00.00.0<NA><NA>0.0<NA>1
121701217144760부여군20220151398.41071063.61440.00.00.0<NA>0.00.0<NA>334.79631
9159916044250계룡시201010510003.09885.00.00.00.00.0<NA><NA>118.0<NA>1
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