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 면적 정보를 제공합니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/bigdata/collect/view.chungnam?menuCd=DOM_000000201001001000&apiIdx=2555

Alerts

지역명 is highly overall correlated with 번호 and 2 other fieldsHigh correlation
지역구분 레벨 is highly overall correlated with 번호 and 6 other fieldsHigh correlation
번호 is highly overall correlated with 지역코드 and 3 other fieldsHigh correlation
지역코드 is highly overall correlated with 번호 and 3 other fieldsHigh correlation
지목별합계_면적 is highly overall correlated with 전_면적 and 5 other fieldsHigh correlation
전_면적 is highly overall correlated with 지목별합계_면적 and 5 other fieldsHigh correlation
답_면적 is highly overall correlated with 지목별합계_면적 and 5 other fieldsHigh correlation
대지_면적 is highly overall correlated with 번호 and 7 other fieldsHigh correlation
임야_면적 is highly overall correlated with 지목별합계_면적 and 5 other fieldsHigh correlation
임야_면적.1 is highly overall correlated with 대지_면적High correlation
기타_면적 is highly overall correlated with 지목별합계_면적 and 4 other fieldsHigh correlation
지역구분 레벨 is highly imbalanced (50.9%)Imbalance
대지_면적 is highly skewed (γ1 = 39.89473602)Skewed
번호 has unique valuesUnique
전_면적 has 421 (4.2%) zerosZeros
답_면적 has 636 (6.4%) zerosZeros
임야_면적 has 1145 (11.5%) zerosZeros
임야_면적.1 has 3181 (31.8%) zerosZeros
기타_면적 has 434 (4.3%) zerosZeros

Reproduction

Analysis started2024-01-09 20:35:38.282887
Analysis finished2024-01-09 20:35:51.154638
Duration12.87 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%
Mean5518.0138
Minimum1
Maximum11058
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T05:35:51.228846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile549.95
Q12747.75
median5501.5
Q38285.25
95-th percentile10507.05
Maximum11058
Range11057
Interquartile range (IQR)5537.5

Descriptive statistics

Standard deviation3195.378
Coefficient of variation (CV)0.57908118
Kurtosis-1.2016485
Mean5518.0138
Median Absolute Deviation (MAD)2769.5
Skewness0.0069423023
Sum55180138
Variance10210440
MonotonicityNot monotonic
2024-01-10T05:35:51.361513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1480 1
 
< 0.1%
10187 1
 
< 0.1%
5358 1
 
< 0.1%
9417 1
 
< 0.1%
3409 1
 
< 0.1%
10455 1
 
< 0.1%
8636 1
 
< 0.1%
4016 1
 
< 0.1%
6027 1
 
< 0.1%
2378 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
11058 1
< 0.1%
11057 1
< 0.1%
11056 1
< 0.1%
11055 1
< 0.1%
11054 1
< 0.1%
11053 1
< 0.1%
11052 1
< 0.1%
11051 1
< 0.1%
11048 1
< 0.1%
11047 1
< 0.1%

지역코드
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44414.098
Minimum44000
Maximum44825
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T05:35:51.474613image/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 deviation305.70896
Coefficient of variation (CV)0.0068831515
Kurtosis-1.7240603
Mean44414.098
Median Absolute Deviation (MAD)100
Skewness0.31666787
Sum4.4414098 × 108
Variance93457.97
MonotonicityNot monotonic
2024-01-10T05:35:51.568921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
44230 582
 
5.8%
44150 580
 
5.8%
44810 580
 
5.8%
44130 580
 
5.8%
44825 578
 
5.8%
44000 577
 
5.8%
44210 577
 
5.8%
44180 576
 
5.8%
44710 576
 
5.8%
44200 575
 
5.8%
Other values (8) 4219
42.2%
ValueCountFrequency (%)
44000 577
5.8%
44130 580
5.8%
44131 501
5.0%
44133 498
5.0%
44150 580
5.8%
44180 576
5.8%
44200 575
5.8%
44210 577
5.8%
44230 582
5.8%
44250 569
5.7%
ValueCountFrequency (%)
44825 578
5.8%
44810 580
5.8%
44800 572
5.7%
44790 567
5.7%
44770 571
5.7%
44760 563
5.6%
44710 576
5.8%
44270 378
3.8%
44250 569
5.7%
44230 582
5.8%

지역명
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
논산시
 
582
공주시
 
580
예산군
 
580
천안시
 
580
태안군
 
578
Other values (13)
7100 

Length

Max length3
Median length3
Mean length2.9423
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row동남구
2nd row동남구
3rd row서산시
4th row동남구
5th row서산시

Common Values

ValueCountFrequency (%)
논산시 582
 
5.8%
공주시 580
 
5.8%
예산군 580
 
5.8%
천안시 580
 
5.8%
태안군 578
 
5.8%
충남 577
 
5.8%
서산시 577
 
5.8%
보령시 576
 
5.8%
금산군 576
 
5.8%
아산시 575
 
5.8%
Other values (8) 4219
42.2%

Length

2024-01-10T05:35:51.676359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
논산시 582
 
5.8%
공주시 580
 
5.8%
예산군 580
 
5.8%
천안시 580
 
5.8%
태안군 578
 
5.8%
충남 577
 
5.8%
서산시 577
 
5.8%
보령시 576
 
5.8%
금산군 576
 
5.8%
아산시 575
 
5.8%
Other values (8) 4219
42.2%

조사일자
Real number (ℝ)

Distinct198
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean201448.77
Minimum200601
Maximum202206
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T05:35:51.793338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum200601
5-th percentile200701
Q1201010
median201502
Q3201904
95-th percentile202111
Maximum202206
Range1605
Interquartile range (IQR)894

Descriptive statistics

Standard deviation480.22464
Coefficient of variation (CV)0.0023838549
Kurtosis-1.2093083
Mean201448.77
Median Absolute Deviation (MAD)404
Skewness-0.13779466
Sum2.0144877 × 109
Variance230615.7
MonotonicityNot monotonic
2024-01-10T05:35:51.927381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
202001 70
 
0.7%
201911 69
 
0.7%
202107 69
 
0.7%
201902 69
 
0.7%
202104 68
 
0.7%
202201 68
 
0.7%
202011 68
 
0.7%
202102 67
 
0.7%
202008 67
 
0.7%
202003 67
 
0.7%
Other values (188) 9318
93.2%
ValueCountFrequency (%)
200601 38
0.4%
200602 40
0.4%
200603 39
0.4%
200604 38
0.4%
200605 42
0.4%
200606 37
0.4%
200607 38
0.4%
200608 43
0.4%
200609 43
0.4%
200610 44
0.4%
ValueCountFrequency (%)
202206 66
0.7%
202205 65
0.7%
202204 65
0.7%
202203 66
0.7%
202202 63
0.6%
202201 68
0.7%
202112 64
0.6%
202111 64
0.6%
202110 65
0.7%
202109 65
0.7%

거래유형
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3
3106 
2
3100 
1
3099 
8
695 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 3106
31.1%
2 3100
31.0%
1 3099
31.0%
8 695
 
7.0%

Length

2024-01-10T05:35:52.050420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:35:52.135143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 3106
31.1%
2 3100
31.0%
1 3099
31.0%
8 695
 
7.0%

지목별합계_면적
Real number (ℝ)

HIGH CORRELATION 

Distinct9958
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1303173.9
Minimum636
Maximum59845130
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T05:35:52.243502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum636
5-th percentile8725.8642
Q163288.5
median650768.73
Q31086843.8
95-th percentile3051138.3
Maximum59845130
Range59844494
Interquartile range (IQR)1023555.3

Descriptive statistics

Standard deviation3257258.7
Coefficient of variation (CV)2.4994813
Kurtosis38.611488
Mean1303173.9
Median Absolute Deviation (MAD)540263.26
Skewness5.5174641
Sum1.3031739 × 1010
Variance1.0609734 × 1013
MonotonicityNot monotonic
2024-01-10T05:35:52.368881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7923.0 3
 
< 0.1%
56734.0 2
 
< 0.1%
10076.0 2
 
< 0.1%
754649.0 2
 
< 0.1%
15286.0 2
 
< 0.1%
16414.0 2
 
< 0.1%
6197.0 2
 
< 0.1%
11226.0 2
 
< 0.1%
1716.0 2
 
< 0.1%
854346.0 2
 
< 0.1%
Other values (9948) 9979
99.8%
ValueCountFrequency (%)
636.0 1
< 0.1%
798.0 1
< 0.1%
998.0 1
< 0.1%
1155.0 1
< 0.1%
1167.0 1
< 0.1%
1328.0 1
< 0.1%
1347.0 1
< 0.1%
1350.0 2
< 0.1%
1438.0 1
< 0.1%
1455.0 1
< 0.1%
ValueCountFrequency (%)
59845130.0 1
< 0.1%
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%
29915611.0 1
< 0.1%
29694030.0 1
< 0.1%

전_면적
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct8390
Distinct (%)83.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean137472.87
Minimum0
Maximum3307018
Zeros421
Zeros (%)4.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T05:35:52.507392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile54
Q11329.4612
median73700.909
Q3123992.62
95-th percentile274089.79
Maximum3307018
Range3307018
Interquartile range (IQR)122663.16

Descriptive statistics

Standard deviation338539.66
Coefficient of variation (CV)2.4625926
Kurtosis26.046408
Mean137472.87
Median Absolute Deviation (MAD)67821.676
Skewness4.9532848
Sum1.3747287 × 109
Variance1.146091 × 1011
MonotonicityNot monotonic
2024-01-10T05:35:52.634493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 421
 
4.2%
50.0 9
 
0.1%
60.0 8
 
0.1%
170.0 7
 
0.1%
198.0 7
 
0.1%
76.0 7
 
0.1%
210.0 7
 
0.1%
572.0 7
 
0.1%
129.0 6
 
0.1%
59.0 6
 
0.1%
Other values (8380) 9515
95.2%
ValueCountFrequency (%)
0.0 421
4.2%
12.0 1
 
< 0.1%
15.0 1
 
< 0.1%
18.0 1
 
< 0.1%
21.7 1
 
< 0.1%
23.26 1
 
< 0.1%
24.0 1
 
< 0.1%
26.0 3
 
< 0.1%
27.0 1
 
< 0.1%
29.7 1
 
< 0.1%
ValueCountFrequency (%)
3307018.0 1
< 0.1%
3292123.0 1
< 0.1%
3238653.122029 1
< 0.1%
3190626.459829 1
< 0.1%
3046619.0 1
< 0.1%
3041618.0 1
< 0.1%
2962311.311637 1
< 0.1%
2952954.701924 1
< 0.1%
2922730.0 1
< 0.1%
2919601.0 1
< 0.1%

답_면적
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct8106
Distinct (%)81.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean348376.17
Minimum0
Maximum13646199
Zeros636
Zeros (%)6.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T05:35:52.761341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11797.4544
median154099.88
Q3299018.82
95-th percentile835431.44
Maximum13646199
Range13646199
Interquartile range (IQR)297221.36

Descriptive statistics

Standard deviation919240.33
Coefficient of variation (CV)2.638643
Kurtosis39.099038
Mean348376.17
Median Absolute Deviation (MAD)151907.74
Skewness5.675911
Sum3.4837617 × 109
Variance8.4500278 × 1011
MonotonicityNot monotonic
2024-01-10T05:35:52.888586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 636
 
6.4%
59.0 12
 
0.1%
60.0 10
 
0.1%
96.0 10
 
0.1%
75.0 10
 
0.1%
84.0 10
 
0.1%
66.0 9
 
0.1%
85.0 9
 
0.1%
81.0 8
 
0.1%
56.0 7
 
0.1%
Other values (8096) 9279
92.8%
ValueCountFrequency (%)
0.0 636
6.4%
15.9876 1
 
< 0.1%
16.0 3
 
< 0.1%
16.0999 2
 
< 0.1%
16.551 3
 
< 0.1%
17.0 1
 
< 0.1%
18.0 1
 
< 0.1%
18.52 1
 
< 0.1%
24.0 2
 
< 0.1%
25.1989 1
 
< 0.1%
ValueCountFrequency (%)
13646199.0 1
< 0.1%
13638038.0 1
< 0.1%
9993350.0 1
< 0.1%
9981227.0 1
< 0.1%
9859239.0 1
< 0.1%
9857873.0 1
< 0.1%
9305790.0 1
< 0.1%
9304112.0 1
< 0.1%
8691728.0 1
< 0.1%
8689928.0 1
< 0.1%

대지_면적
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct9862
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean158005.82
Minimum519
Maximum45075800
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T05:35:53.022447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum519
5-th percentile5607.689
Q118890.076
median50157.5
Q3121390.25
95-th percentile525633.08
Maximum45075800
Range45075281
Interquartile range (IQR)102500.17

Descriptive statistics

Standard deviation762630.94
Coefficient of variation (CV)4.8266002
Kurtosis2143.1169
Mean158005.82
Median Absolute Deviation (MAD)37423.146
Skewness39.894736
Sum1.5800582 × 109
Variance5.8160596 × 1011
MonotonicityNot monotonic
2024-01-10T05:35:53.152312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24902.0 3
 
< 0.1%
17087.0 3
 
< 0.1%
13832.0 3
 
< 0.1%
6628.0 3
 
< 0.1%
9673.0 3
 
< 0.1%
25019.0 2
 
< 0.1%
39480.0 2
 
< 0.1%
186531.0 2
 
< 0.1%
13312.0 2
 
< 0.1%
8448.0 2
 
< 0.1%
Other values (9852) 9975
99.8%
ValueCountFrequency (%)
519.0 1
< 0.1%
636.0 1
< 0.1%
670.0 1
< 0.1%
694.0 1
< 0.1%
696.0 1
< 0.1%
787.4 1
< 0.1%
798.0 1
< 0.1%
966.0 1
< 0.1%
998.0 1
< 0.1%
1002.5 1
< 0.1%
ValueCountFrequency (%)
45075800.0 1
< 0.1%
41864666.0 1
< 0.1%
17254454.0 1
< 0.1%
12631776.0 1
< 0.1%
10040417.0 1
< 0.1%
9694148.0 1
< 0.1%
9614731.0 1
< 0.1%
8716137.0 1
< 0.1%
8499135.0 1
< 0.1%
8289334.0 1
< 0.1%

임야_면적
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct7066
Distinct (%)70.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean572104.1
Minimum0
Maximum15437280
Zeros1145
Zeros (%)11.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T05:35:53.301967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1791
median219967.54
Q3468355.7
95-th percentile1771086.5
Maximum15437280
Range15437280
Interquartile range (IQR)467564.7

Descriptive statistics

Standard deviation1476780.9
Coefficient of variation (CV)2.581315
Kurtosis27.740624
Mean572104.1
Median Absolute Deviation (MAD)219504.2
Skewness5.0116828
Sum5.721041 × 109
Variance2.1808819 × 1012
MonotonicityNot monotonic
2024-01-10T05:35:53.454982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1145
 
11.5%
85.0 16
 
0.2%
60.0 15
 
0.1%
35.0 10
 
0.1%
53.0 9
 
0.1%
39.0 8
 
0.1%
69.0 8
 
0.1%
70.0 8
 
0.1%
75.0 7
 
0.1%
42.0 7
 
0.1%
Other values (7056) 8767
87.7%
ValueCountFrequency (%)
0.0 1145
11.5%
2.0 1
 
< 0.1%
2.244 1
 
< 0.1%
13.225 1
 
< 0.1%
16.0 1
 
< 0.1%
18.0 2
 
< 0.1%
20.0 1
 
< 0.1%
22.0 1
 
< 0.1%
23.3 1
 
< 0.1%
24.0 2
 
< 0.1%
ValueCountFrequency (%)
15437280.0 1
< 0.1%
15435182.0 1
< 0.1%
14331555.0 1
< 0.1%
14328623.0 1
< 0.1%
13685425.0 1
< 0.1%
13678711.0 1
< 0.1%
13672823.0 1
< 0.1%
13668088.0 1
< 0.1%
13256471.0 1
< 0.1%
13250204.0 1
< 0.1%

임야_면적.1
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct5467
Distinct (%)54.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27354.543
Minimum0
Maximum1990053
Zeros3181
Zeros (%)31.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T05:35:53.924208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3170.5
Q316555
95-th percentile136670.18
Maximum1990053
Range1990053
Interquartile range (IQR)16555

Descriptive statistics

Standard deviation85382.537
Coefficient of variation (CV)3.1213293
Kurtosis98.752368
Mean27354.543
Median Absolute Deviation (MAD)3170.5
Skewness7.7809037
Sum2.7354543 × 108
Variance7.2901776 × 109
MonotonicityNot monotonic
2024-01-10T05:35:54.054746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 3181
31.8%
3121.0 7
 
0.1%
337.0 6
 
0.1%
675.0 6
 
0.1%
936.0 6
 
0.1%
163.0 6
 
0.1%
6611.0 6
 
0.1%
486.0 6
 
0.1%
3359.2 6
 
0.1%
570.0 5
 
0.1%
Other values (5457) 6765
67.7%
ValueCountFrequency (%)
0.0 3181
31.8%
1.0 1
 
< 0.1%
2.0 3
 
< 0.1%
3.0 2
 
< 0.1%
11.0 2
 
< 0.1%
11.9 1
 
< 0.1%
13.0 1
 
< 0.1%
14.0 2
 
< 0.1%
15.0 1
 
< 0.1%
17.0 1
 
< 0.1%
ValueCountFrequency (%)
1990053.0 1
< 0.1%
1808333.0 1
< 0.1%
1556492.0 1
< 0.1%
1551592.0 1
< 0.1%
1156302.3618 1
< 0.1%
1145602.3007 1
< 0.1%
1050944.0 1
< 0.1%
1043225.0 1
< 0.1%
1032898.8416 1
< 0.1%
962371.2127 1
< 0.1%

기타_면적
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct8496
Distinct (%)85.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59862.033
Minimum0
Maximum7499883
Zeros434
Zeros (%)4.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T05:35:54.192754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile46
Q12018.63
median14264.437
Q340323.206
95-th percentile228642.5
Maximum7499883
Range7499883
Interquartile range (IQR)38304.576

Descriptive statistics

Standard deviation213447.09
Coefficient of variation (CV)3.5656506
Kurtosis441.6037
Mean59862.033
Median Absolute Deviation (MAD)13531.112
Skewness15.999145
Sum5.9862033 × 108
Variance4.5559662 × 1010
MonotonicityNot monotonic
2024-01-10T05:35:54.318964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 434
 
4.3%
198.0 14
 
0.1%
50.0 8
 
0.1%
68.0 7
 
0.1%
60.0 6
 
0.1%
196.0 6
 
0.1%
27.0 6
 
0.1%
324.0 6
 
0.1%
97.0 5
 
0.1%
63.0 5
 
0.1%
Other values (8486) 9503
95.0%
ValueCountFrequency (%)
0.0 434
4.3%
1.0 2
 
< 0.1%
3.84 2
 
< 0.1%
7.0 3
 
< 0.1%
8.0 3
 
< 0.1%
10.7133 1
 
< 0.1%
12.0 2
 
< 0.1%
19.0 2
 
< 0.1%
20.0 2
 
< 0.1%
20.68 1
 
< 0.1%
ValueCountFrequency (%)
7499883.0 1
< 0.1%
7457479.0 1
< 0.1%
6119916.0 1
< 0.1%
6119562.0 1
< 0.1%
2973747.554719 1
< 0.1%
2689344.34707 1
< 0.1%
2632408.8895 1
< 0.1%
2380392.248467 1
< 0.1%
2250165.985067 1
< 0.1%
2136303.516295 1
< 0.1%

지역구분 레벨
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
8424 
2
999 
0
 
577

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 8424
84.2%
2 999
 
10.0%
0 577
 
5.8%

Length

2024-01-10T05:35:54.438021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:35:54.545169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 8424
84.2%
2 999
 
10.0%
0 577
 
5.8%

Interactions

2024-01-10T05:35:49.955839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:40.745379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:41.655722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:42.527201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:43.881047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:44.907206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:45.849922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:46.748712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:47.584549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:48.609501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:50.042500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:40.825445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:41.740880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:42.614541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:43.975801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:44.995716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:45.935891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:46.827233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:47.675116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:48.725020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:50.136512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:40.916506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:41.817200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:42.722324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:44.069153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:45.086786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:46.015782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:46.901304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:47.761218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:48.837920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:50.242149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:41.014114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:41.912080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:42.846115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:44.189502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:45.198780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:46.111882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:46.984547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:47.867182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:48.977696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:50.328333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:41.102440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:41.999593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:42.943300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:44.315677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:45.288627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:46.201778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:47.065490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:47.968091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:49.099782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:50.411776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:41.187872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:42.086273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:43.065784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:44.443570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:45.375097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:46.295069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:47.147748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:48.059943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:49.472305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:50.501501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:41.279639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:42.176721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:43.180192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:44.541329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:45.468545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:46.383482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:47.243290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:48.162139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:49.560785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:50.591942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:41.369194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:42.254816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:43.276758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:44.621446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:45.567911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:46.464135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:47.319476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:48.253934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:49.655611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:50.693580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:41.469023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:42.345060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:43.380606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:44.720265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:45.662101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:46.553026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:47.405445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:48.358566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:49.762827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:50.796320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:41.565572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:42.437640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:43.777547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:44.816328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:45.761897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:46.653614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:47.493040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:48.490691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:35:49.856266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T05:35:54.616548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호지역코드지역명조사일자거래유형지목별합계_면적전_면적답_면적대지_면적임야_면적임야_면적.1기타_면적지역구분 레벨
번호1.0000.9950.9810.2110.0760.4390.5590.4200.1100.5630.3050.2320.866
지역코드0.9951.0001.0000.1110.0000.0000.0450.0390.0080.1690.0840.0250.521
지역명0.9811.0001.0000.1070.0000.6030.5910.6580.0840.5940.4380.3981.000
조사일자0.2110.1110.1071.0000.4090.0650.1560.0760.0890.1420.0720.0900.120
거래유형0.0760.0000.0000.4091.0000.2080.1510.1270.0320.1800.1630.0680.000
지목별합계_면적0.4390.0000.6030.0650.2081.0000.7760.7940.7070.8220.6440.4970.689
전_면적0.5590.0450.5910.1560.1510.7761.0000.7720.2940.8790.5010.5660.716
답_면적0.4200.0390.6580.0760.1270.7940.7721.0000.2290.7830.4910.4690.846
대지_면적0.1100.0080.0840.0890.0320.7070.2940.2291.0000.3110.1300.0510.097
임야_면적0.5630.1690.5940.1420.1800.8220.8790.7830.3111.0000.5180.5200.707
임야_면적.10.3050.0840.4380.0720.1630.6440.5010.4910.1300.5181.0000.3420.505
기타_면적0.2320.0250.3980.0900.0680.4970.5660.4690.0510.5200.3421.0000.551
지역구분 레벨0.8660.5211.0000.1200.0000.6890.7160.8460.0970.7070.5050.5511.000
2024-01-10T05:35:54.751318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역명지역구분 레벨거래유형
지역명1.0000.9990.000
지역구분 레벨0.9991.0000.000
거래유형0.0000.0001.000
2024-01-10T05:35:54.852476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호지역코드조사일자지목별합계_면적전_면적답_면적대지_면적임야_면적임야_면적.1기타_면적지역명거래유형지역구분 레벨
번호1.0000.9980.027-0.258-0.142-0.108-0.553-0.178-0.479-0.2570.9000.0460.794
지역코드0.9981.000-0.023-0.256-0.141-0.106-0.557-0.173-0.483-0.2590.9990.0000.836
조사일자0.027-0.0231.0000.0830.1080.1050.1870.0430.1420.1520.0420.2560.073
지목별합계_면적-0.258-0.2560.0831.0000.9020.8870.7040.9330.4460.7980.3040.0950.573
전_면적-0.142-0.1410.1080.9021.0000.8770.6150.8510.3890.7960.2720.0900.577
답_면적-0.108-0.1060.1050.8870.8771.0000.5670.8060.3450.7590.2790.0810.560
대지_면적-0.553-0.5570.1870.7040.6150.5671.0000.5420.6120.6560.0430.0260.073
임야_면적-0.178-0.1730.0430.9330.8510.8060.5421.0000.3240.7060.2740.1080.565
임야_면적.1-0.479-0.4830.1420.4460.3890.3450.6120.3241.0000.4700.2010.0740.371
기타_면적-0.257-0.2590.1520.7980.7960.7590.6560.7060.4701.0000.1700.0440.270
지역명0.9000.9990.0420.3040.2720.2790.0430.2740.2010.1701.0000.0000.999
거래유형0.0460.0000.2560.0950.0900.0810.0260.1080.0740.0440.0001.0000.000
지역구분 레벨0.7940.8360.0730.5730.5770.5600.0730.5650.3710.2700.9990.0001.000

Missing values

2024-01-10T05:35:50.924111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T05:35:51.084744image/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_면적전_면적답_면적대지_면적임야_면적임야_면적.1기타_면적지역구분 레벨
1479148044131동남구201205369579.01489.0301.066340.00.00.01449.02
1502150344131동남구201408375703.01357.0262.067034.0608.05622.0820.02
4612461344210서산시20150311616378.0201739.0751247.0180695.0463320.02713.016664.01
1807180844131동남구2022053106284.98841215.1001868.23895001.515803.656031.192365.29532
4626462744210서산시20151111307709.0214021.0435338.0238690.0314153.040613.064894.01
12012144000충남200603225998025.03041618.08689928.0992731.011751098.098840.01423810.00
9868986944810예산군2012121779651.0139986.0312061.0105839.0198844.00.022921.01
109771097844825태안군2020071953972.254866176239.50627275989.34116751845.719268382525.4219240.067372.2662371
8168816944770서천군20130135880.00.00.04200.00.01341.0339.01
9429943044800홍성군20081039346.0629.0235.07778.0219.00.0485.01
번호지역코드지역명조사일자거래유형지목별합계_면적전_면적답_면적대지_면적임야_면적임야_면적.1기타_면적지역구분 레벨
5152515344230논산시201203316377.084.037.014127.091.01047.0991.01
4537453844210서산시200706321521.0428.01309.017876.01575.00.0333.01
2051205244133서북구2014012322523.021902.042516.0185589.038218.0179.034119.02
4996499744230논산시2012111922815.078147.0297490.0145930.0387937.04440.08871.01
1788178944131동남구20210721228828.881851196589.835331186874.78180184598.055811680646.34098540422.039697.8679232
4801480244210서산시20191111216915.794602153837.021156482850.508394115904.570366428143.55984258.031922.1348861
1693169444131동남구2019103116644.420731089.5627.288699604.02053111.08513385.971826.55662
3266326744180보령시200705324348.0165.059.017516.0120.05407.01081.01
3516351744180보령시2020021833195.9877110232.3243433583.0366101391.9029167905.31190.020083.4121
8340834144770서천군201810315856.78025150.99745.26729602.2280562.810.05295.4851